ORGANIZATIONAL INTERACTION IN SOCIAL SERVICES SYSTEMS: A TWO - CITY COMPARISON Dissertation for the Degree of Ph. D. MICHIGAN STATE UNIVERSITY ANN WORKMAN SHELDON 1975 LIBRA R Y Mich-Egan 3r 1:“: University TH 3-5, .25 —-- __N This is to certify that the thesis entitled ORGANIZATIONAL INTERACTION IN SOCIAL SERVICES SYSTEMS: A TWO-CITY COMPARISON presented by Ann Workman Sheldon has been accepted towards fulfillment of the requirements for _Bh.1L__ degree in Sociology fl Major professor Date December,. 1975 0-7639 fI oaoocaooaaiam::1azoaoocaoacatoQ99 I acoocoocaaooooocooooaoo -_ N u . a m c a 33.35...as:a$.33332333333a:a:“3323:2222“:21..3:32”333332. _.________._.‘__#_____‘_ddm_______fi___..._____.____._.___ N----~N-1~1~1---~N--~N-~N-NN----N-NNNNNNN uwuuwuwuuz:uuuuuuuwuflwuuuuuuuwwuumwuuuuuuuuuumwuwuuuuuwwwu asaaaaaahknanaaAAAaa“IAAAAAAAAAA.aaaaaugaAAAAAAQAAAAAA“AAA maumwmmmmmmm mmmmmwzuuwtmmmmmmmmummummummmmmmwammmmmmmmwwm mmmmmmmmmmmmmmmmmmmmmmwmmmma mmmmmmmmmmammmmmmmmmmmmmmmmmm ----~u~u--~u-----~q guy----~N-uggguu--ug oug.uaaa..a.auammm aucoaammamam.aaaaaaaaawaaaaaaaaaaaaaua- caammuomuommma‘mommamummammmmmmmmmowoammuaauuoommmuamomamm .cu. sass :83 an uo~ooa=flfl335 333283 3 fixuuuouuunuooetanttauo-S33.823333339 8:8! \. x \5 of) g \ ABSTRACT ORGANIZATIONAL INTERACTION IN SOCIAL SERVICES SYSTEMS: A TWO-CITY COMPARISON By Ann Workman Sheldon This study investigates interorganizational relationships within the social service systems of two middle size metropolitan areas. The focus is the network of interacting organizations, and the analysis examines: (l) the types and extensiveness of interorganizational re- lationships of 68 social service agencies and the patterns of organiza- tional interactions in two social service networks; (2) the relationships of organizational characteristics and resources and the agency's position in the hierarchy of organizations in the local system (its power) to interaction behaviors; and, (3) the effect of competition for resources on the pattern of interorganizational relationships established by social service agencies and within local systems. The study emphasizes power relationships using a causal model which assumes that competitive relationships in the process of seeking resources determine organization and system interaction patterns. Social service organizations seek resources for service delivery through exchange relationships with other agencies, but the primary stimulus for interrelationships is competition to acquire and keep the resources needed for survival and/or growth. Power is a key ingredient in the interactions. The research incorporates an exchange theory approach and the organization-set concept. The system is conceptualized as the collection of organization-sets of all the social service organizations I I, Ann Workman Sheldon in each community and is measured using sociometric techniques and aggregated organization variables. The data came from lengthy, structured interviews and self-administered questionnaires from the directors of all the formally established social service organiza- tions meeting minimal size and policy-making criteria (System A, N=33; System B, N=35) and from organization records. The independent variables of sponsorship, type of work, age, size, staffing patterns, and service diversity came from records and responses to questions about agency operations. Two types of competition were measured by asking directors to identify organizations and groups involved with the agency in four types of competitive relationships and to estimate the extent of the competitive pressures experienced by the agency. Directors reported interorganizational ties (dependent variables) with the organizations and groups sharing the pool of commonweal resources for 14 different types of non-competitive relationships. Organization power, or network position was derived from the number of sociometric choices received for these 18 different types of resource relation- ships. The twenty hypotheses tested concern (1) relationships among the independent variables, or conditions connected with network position (incoming, or Target, interactions), and (2) the relationships of the independent variables to several kinds of outgoing (Actor) inter- actions (e.g., simple exchanges, reference-group relationships, and cooperative interactions). The two systems are compared for service emphases, organizational composition, organizational hierarchy, competitiveness, and types and patterns of interactions. In addition, the system position, competitiveness, and interaction behaviors of 21 Ann Workman Sheldon pairs of organizations -- offices or chapters of national and/or state organizations similar in work and resources —- are compared. Analysis shows work-related interactions are minimal; all types of interactions, including those connected with the division of labor characteristic of the social service sector, are primarily stimulated by competition for resources. Further, interorganizational relation- ships involving cooperation and coordination principally depend upon power or system position and to a lesser extent reflect organization service delivery needs. Without command over those resources valued by system members, the Actor organization cannot develop cooperative exchanges with other organizations even when stimulated by high come petition. There are no consistent patterns of relationships of the various charter-domain characteristics, specific organizational resources, or perceptions about competitive pressures with outgoing interactions. Differences between the two systems in the positions of various types of agencies within the systems and of the 21 pairs indicates system conditions as well as organizational characteristics are important determinants of interaction patterns. The findings strongly support the general political economy perspective. Regardless of system differences in types of organizations considered important, those organizations high in both competition and system power have the most extensive and the most varied interorgani— zational relationships. System differences in competition and inter- action parallel the causal relationship between competition and inter- action; the system with higher competition also has more extensive relationships among members, fewer system isolates, and more cooperative and reciprocal relationships. Ann Workman Sheldon The report includes discussion of (l) the implications of the findings for increasing coordination among autonomous social service organizations and (2) the contribution of the design to problems of methodology in interorganizational relations research. ORGANIZATIONAL INTERACTION IN SOCIAL SERVICES SYSTEMS: A TWO-CITY-COMPARISON By Ann Workman Sheldon A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Sociology 1975 <:>Copyright 1975 by Ann Workman Sheldon. I i. ACKNOWLEDGMENT This dissertation deals with.central aspects of a larger research project conducted over a period of several years by a team of graduate and undergraduate students working under the overall supervision of Philip M. Marcus. I am grateful for the help of all the members of the Organization Relations Research Unit but especially thank Margaret J. Adams who trained and supervised the interviewers in both cities and has continued to provide invaluable help with data preparation and analysis problems. Bernard J. Offerman carried a major share of the interviewing in both cities and helped with the necessarily tedious aspects of the data preparation and preliminary analysis. As project secretary, Jackie Kron not only coped with the umny drafts of questionnaires, memos and working papers, but remained efficient and enthusiastic. Tom Nichol's help with analysis suggestions mm.computer programming was invaluable. The research was a cooperative project between two local United erorganizations, the College of Social Science, and the Department «meociology, Michigan State University. It was made possible by generous direct and indirect contributions from these organizations and the extensive cooperation of the directors of these 68 local agencies. I want to thank the members of my committee, Philip M. Marcus as Chairman and Richard Child Hill, James B. McKee and Harry Perlstadt for their encouragement of the research and their helpful, critical comments. I am particularly indebted to Harry Perlstadt for his exten- sive suggestions which helped improve the written report and clarified several points for me. ut usually they are pictured as involving exchanges. This -.... ... v \ *- .‘.-' .1 . . u a —.- . .. .. . I.» '~. g . . s._»‘. .._‘ ' _'\\. s .\ “ n u ‘h N A -‘ .~~ a .1 ' I ‘N.. R.r \ . ~- ~ I I . I . I Q . I . I 1 . . ‘ I -v ., u‘ ‘\ i ,x . -- Jav- . b, ' 19 type of interaction is work-based or operational. Other relation- ships which concern institutional maintenance activities involving issues of domain consensus and long-run agency survival, based on values according to B. Aldrich (1972), are sometimes described. Some studies suggest that organizations interact to lessen their de- pendence and increase their bargaining power relative to their organi- zation-set (Milio, 1972: 161+). Interagency relationships are considered to be voluntary activities and to involve exchanges of tangible resources. For ex- ample, exchange is the dominant basis for interaction, and resource exchanges can be formal or informal (Levine and White, 1961); joint programs are means to get resources (Aiken and Hage, 1968); exchanges involve dependence but it does not have to be direct (Jacobs, 1974). Linkages are categorized in several ways: as functional, normative, and diffuse (Blase, 1973); as involving resources or recognition (Ross and Smith, 1974); directed toward coordination, communication or conflict (Hall, 1974); as facilitative, competitive, adjudicative, or communicative (Litwak and Rothman, 1970); involving pro- deing services or interchange of clients, exchange of material resources (money,'space), or as about policy, goals, or the future (Rieker _§_t_ a1, 1974); and as immediate economic transactions or long—range resource— ac“Tulisition in nature (Benson, 1974). For the most part, cooperation and consensus are stressed, and few anthers relate organization position within the system, or Power, to interactions. Further, little information is available to Suggest the proportion of relationships which fit into the various QMCEPtual categories. Findings describe the range of interactions . . n .. .. Q Q‘ I. . ' O 1'. ‘ u 5“ .t- \ 20 and seek to connect interaction patterns, but give little informa- tion about numbers of interactions or the proportion of interactions of various types. Although not directly expressed, underlying these ideas are several important assumptions: (1) that needed elements exist in the system somewhere; (2) that organizations ggg_obtain these desired resources through interaction, or that others will share regardless of potential for return on investment or scarcity; and (3) the system generally operates under the norm of reciprocity, and sharing is welcomed. Following the exchange perspective, organizations are pictured as in partial interdependence and partial conflict (Hall, 1974). Most of this literature has the organization as the unit of muflysis although the research of Turk and Warren illustrate efforts to attack the interorganization field or the network of similar agencies. Some recent articles imply that one cannot seek informa- tion about the system itself through a focus on patterns of organiza- tion-organization linkages (Benson, 1974; Rieker g£_§1, 1974; Warren, 1974). Problems of using organization level data to predict network Characteristics and the technical difficulties involved in moving Past: the dyadic interaction are discussed as interest in the field incrxeases and researchers attempt to develop ways to investigate inte‘lt'organizational phenomena. There are many difficulties in developing a workable approach. Heydebrand (1973b) states there is general agreement that prevailing concep ts and theories concerned with intraorganizational phenomena are inadequate when one shifts to the interorganization level. Co"celj’tual schemes for thinking about the problems are limited. Two ‘ nl‘! p bub. 21 perspectives have prevailed in the pre-l970 literature and much of recent work as well. The first is the exchange perspective developed by Levine and White, and the second is the organization-set model posed by Evan. In this extension of Merton's role-set idea, instead of selecting a status as the unit of analysis and charting a complex of role relationships in which the status occupant is involved . . . let us take as the unit of analysis an organization or a class of organizations and trace its interactions with the various organizations in its environment, viz its organization-set . . . the organization or class of organizations that is the point of reference is referred to as the "focal organization" . . . As in the case of role-set analysis, the focal organization interacts with a complement of organizations in its environment, i.e., its "organization-set." . . . We partition the organization— set into an "input-organization-set" and an "output- organization-set." By an input organization-set . . . a complement of organizations is meant that provides re— sources to the focal organization . . . (and) which receive the goods and/or services, including organizational de- cisions, generated by the focal organization (Evan, 1972: 183). In Evan's model the members of the organization-set are all those organizational entities with which the focal organization is directly and fairly frequently involved for input and output connected activities. Collections of organization-sets make up the inter? organizational network. The network, then, is a relatively closed system. The organizations' interactions are with organizations in their task environment (Dill, 1958). The interactions are managed by boundary spanning personnel (Evan, 1966). Extending this,organi- zational relations are the input-output activities of single organi- zations (Rieker g: 31, 1974) or all of the group organizations with which the focal (Actor) organization is directly and frequently in- volved. 22 Following Turk (1973b), "system" is interpreted as linkage among units. Thus, the imagery can be extended and the collection of linked organizations, i.e., those in each others organization-sets, considered to make up the interorganization network. Using this cluster of sets idea, the network is the same as the "interorganizational field" (Warren, 1967). Using Rieker's useful discussion of this per- spective, When an organizational network itself is the unit of analysis, environment will refer to forces or factors external to that network. When the organization is the unit of analysis, environment will generally be used to include a part of the organizations which have relation- ships with the organization of interest (Rieker g£_§1, 1974: 5). Evan uses the concept of organization—set, and others used the idea of the network (or collection of sets) to distinguish between the interorganization network in which a particular organization is involved and environmental factors external to the network, i.e., the local community. The organization-set members are the primary environment for the organization. The environment outside the network is considered the organization's secondary environment (Rhenman, 1973). In this model preperties of the network which affect the individual organization can be considered (i.e., the impact of the primary en- vironment on the focal or Actor organization,)and properties of the secondary environment,(i.e., the larger society),which affect the network and thus the organization as well, can be identified. As this model is extended (by Evan himself in his 1972 paper, and by Rhenman's contribution of the idea of the secondary environ- ment), the referent is still the single organization. The primary environment, the network, is viewed as the collection of organization- .... I ‘4 —__..--—-—‘ _ Mi ___..__ 1 23 sets, and presumably all network members are linked directly or indirectly with fairly immediate consequential implications for the focal organiza- tion. As Rieker points out, this model does not attack important questions of the network itself, and research in this tradition is not currently directed toward network properties. Research using the relational perspective, or the network itself, is almost non-existent. In fact, only very recently has systematic attention tried to develop an interorganizational perspective and work toward an integrative theory. To date only Turk has done com- parative network analysis, although Anderson (1967), Erickson (1974), Marcus, Sheldon, and Adams (1974a), and Warren (1974) have investigated properties of networks of organizations. Interorganization level re— search is frustrated by the extremely high cost of collecting informa- tion about a sizable number of networks as well as by problems of conseptualizing. Although approaches used for intraorganization research may be inadequate when one shifts to the interorganization level, a body of highly useful information exists connecting environment factors with organization structure and behavior. Information about intra- organization phenomena provides useful leads to important variables. An extensive body of literature indicates size and technology are major determinants of structure and organization behavior (e.g., Anderson and Warkow, 1973; Blau and Schoenberr, 1971; Harvey, 1968; Klatsky, 1970; Pugh g£_al, 1968; Terrien and Mills, 1973; Woodward, 1965; and Zwerman, 1970.) Interaction is innovative behavior, and in the organization literature such behavior is linked to a variety of internal character- istics including the nature of the work, staff diversity, autonomy, —- x...— ." . ‘ A. .l - 24 and complexity (Aiken and Hage, 1968; Corwin, 1969; Heydebrand, 1973a; Lefton and Rosengren, 1966; Wilson, 1966; and Wren, 1969). Both Corwin (1969) and Pondy (1967) provide support for ideas connecting internal characteristics such as heterogeneity, specialization, com- plexity, and size to styles of conflict management, and these ideas seem applicable to the management of competition as well as internal conflict. A smaller body of literature concerns charter and domain conditions. Sponsorship serves to differentiate organizations and to connect them to segments of the community which offer varying amounts of support (Elling and Halebsky, 1961: 185). Sponsorship differences involve varying constituencies and entail dissimilar rules for operation and levels of decision-making. According to Wamsley and Zald (1973), organizations with public funding have distinctive characteristics including different policy sub-systems and perceptions of 'ownership' and face different resource constraints than do profit- making or private organizations. Age is another potentially signifi— cant characteristic. Rosengren (1968) shows that age is related to orientations to patrons. Crum (1953), Starbuck (1965), and Stinchcombe (1965) describe the probable effects of period of establishment on organization structure; Stinchcombe ties resource levels to age in discussing "the liability of newness." The general work of the organization is another charter-related important factor, because it affects staffing patterns, orientation of staff to work, the resources needed, staff autonomy, and hence, communication and authority structures, and size (Zwerman, 1970). Even with the network itself as the research focus, character- istics of member organizations require consideration. For example, ~---.'. - . u... . .‘ ~ ~ i.v: a a... : ...,_ , : ‘ 'I . ‘ F. '. -- -'u , -- .3 .,-- ..1 . ‘n o‘- d ‘. t o‘- t - p o . ' I ‘. a' \ '~ \_| .k ‘ . .. t ‘. \, >1. - I ._ V" ‘ 25 a group of well-funded large public people-processing organizations may have different patterns of relationships than a group of organi- zations offering very diverse services. Accordingly, some structural variables in the comparative organization literature such as age, sponsorship, technology, complexity, centralization, size, and staffing patterns should probably be included in interorganizational research. The interorganization literature is dominated by research within the human services sector, especially health care systems and social services. Perhaps this accounts for the heavy emphasis on consensus. Much of the research is problem oriented, and perhaps this explains the concentration on coordination and cooperation and on improving service integration. The relationships between conflict and cooperation is not a major focus, although the dominant approach, the exchange model, assumes competition for scarce resources stimu- lates interactions. Conflict-based interactions are largely ignored, and competition is rarely, if ever, not measured. In addition, although a great deal of the sociology of organi- zations literature emphasizes cooperation and coordination and the minimization of conflict, some are examining power and conflict. For example, Thompson (1967) states many power-related propositions; Zald (1970a) examines power relationships as a stimulus to organiza— tion behavior, as does Selznick (1949); Randy (1967) argues the concept of conflict needs a prominent place in organization theory as do Assael (1969), Corwin (1969), Walton g£_al_(l969) and others; and some interested in service organizations explore conflict (Adamek and Lavin, 1974; Earth, 1963; Hage and Aiken, 1974; and Litwak, 1961). A series of fairly recent articles urges a focus on power and conflict ...o-, .. F... .u .. ‘ . . u . .l .. ..,. - v~ ”a.... “a a o- I ' c. U u. . o --... I, 0 o.>. . 'o.‘ _- .. 4.. ‘- -._ ~. '1 n. ‘ . .-_ D -. . M\ ‘ .‘_I ‘- \ '~ I .N. -,. v. w W, .; ,n- V- . p J ‘ . H .u‘ \.I ~ \I . ‘I s ' e a ‘: . - In . ;. .g. . 26 in interorganizational research (B. Aldrich, 1972; Benson, 1974; Hall, 1974; Rieker g5 g1, 1974; wamsley and Zald, 1973), and a few empirical studies are now reported including Adamek and Lavin (1974), Halpert (1974), and Turk (1970). The political economy perspective Benson proposes a theoretical perspective on interorganizational relations that focuses on resources and power within a single general framework incorporating many of the diverse concerns of interorgani— zational relations research (1974: 2). He views the interorganiza- tion network as an emergent phenomenon that should be the unit of analysis, not the formal organization and its environment or set. The network consists of organizations engaged in a significant amount of interaction that ranges from extensive, reciprocal exchanges of resources to intense hostility and conflict. Some networks may be a set of organizations linked by multiple direct ties, while others may cluster linkages around a few mediating or controlling organi- zations and have indirect links as well. Interactions can be reciprocal or relatively one-sided, dependent relationships. Through linkages organizations pursue two general types of resources; those related to money, and those related to authority. Network analysis frequently examines only those interaction patterns which are concerned with the actual work of the organization (i.e., for social service organizations making and receiving referrals, providing information about agencies to clients, sharing specific services and programs), but Benson argues phenomena on this level are really dependent on a second, deeper mode of analysis focused on 27 the processes of resource acquisition or the activities undertaken in pursuit of an adequate supply of organizational resources. He emphasizes that interactions may occur at either level in the delivery of services or in the acquisition of resources, but: Interactions at the level of service delivery are ulti- mately dependent upon resource acquisition . . . Considera- tions of resource adequacy determine, within fairly re- strictive limits, the nature of the interactions in the performance of mandated functions. Phenomena at the level of service delivery are partially autonomous in the sense that orderly patterns of dependence linking variables at that level may be discovered. For example, common or con- sensual domain conceptions may be associated with coopera- tive work relationships (and) reasonably precise and accurate theoretical models may be applied to phenomena at the level of service delivery. Nevertheless, it is argued that interactions must be explained ultimately at the level of resource acquisition (emphasis added) (1974: 3)} Benson argues that organization decision-makers are principally oriented to acquiring and defending an "adequate" supply of resources. Thus, "abstract purposes, charter goals, and the like come to be translated into ongoing programs, established structures, and trained personnel . . . and decision-makers are responsible for maintaining or expanding this established 'organizational machine' (1974: 4)." Organization decision-makers seek to acquire and defend a secure supply of the key resources, money and authority. Benson uses authority to refer to the legitimation of activities, the right and responsibility to carry out programs dealing with a broad problem area or domain. Money is the road to needed material resources, i.e., staff, space, services, etc. "Money and authority are interrelated . . . (in that) authority to conduct activities is generally assumed to imply a claim upon money adequate to performance in the prescribed sphere (1974: 4)." 28 Many different interagency actions may be compatible with the broad assertion that organizations pursue an adequate supply of Inoney and authority, and Benson describes four: (1) to fulfill pro- gram requirements; (2) to maintain a clear domain of high social importance; (3) to maintain Orderly, reliable patterns of resource flow; and (4) to secure and defend the agency's way of doing things or, as he puts it, a defense of the agency's paradigm or its techno- logical commitment (1974: 6). Within networks, organizations differ in power, and some gain power over others because of network characteristics, e.g., they may provide services vital to a large number of other organizations and so have central function, or they may control access to clients. 'Tower may be said to derive from the central organization's control over 'strategic contingencies' confronted by the peripheral organi— zations . . . (and) strategic location gives the central organization enhanced bargaining power vis-a—vis the peripheral organizations (1974: 6)." Another source of power is the linkage of organizations to the larger pattern of social dominance or the secondary environ- ment (Rhenman, 1973). Interorganizational power may have a variety of effects upon network relationships, and the primary effects of interorganizational Power lie in control of network resources, including the flow of resources to other organizations. The secondary expression of inter- organization power is in the process of negotiation between organi- zations since the powerful organization can force others to accept its terms and can permit an organization to determine the policies in the weaker organization. 29 Within the network, specific ties are fixed by the structure ()f political and economic forces. Money and authority go to the organization on the basis of its sphere of activities and its technology. Differentially powerful organizations interact in pursuit of scarce resources -- money and authority. Power in these inter- actions is said to derive from two sources: (1) Network structure, or patterns of direct linkage between agencies in a specific network, e.g., control by one network agency over contingencies vital to re- source acquisition by another network agency; (2) Extra-network structura.or patterns of linkages between network agencies and organi- zations, officials, and public in the network environment, e.g., ties of any agency to important interest groups in the society (1974: 24). The political economy perspective has several major advantages. First, it is relatively simple with a minimum set of assumptions. Second, the basic ideas can be tested and empirically based propositions developed. Third, it connects interorganizational research to macro- theory and deals with basic issues of power and the distribution of resources. Although the words used are different, this perspective is really an extension of the evolutionary ecological framework and chews freely from economic models of imperfect competition (e.g., (eves, 1967; Duncan, 1964; Lenski, 1966). Finally, although Benson Sees this as "an integrative framework which establishes a genuinely interorganizational level of analysis because its focus is on the Characteristics of networks and their environments (1974: 25)," this approach can be used to study network members as well (Wamsley and Zald, 1973; Zald, 1970b). 30 T11e Research Desigg_ This research is within the general political economy per- spective described by Benson (1974). It seeks to test hypotheses about the relationships between organizational characteristics and resources, organization position in the interorganizational network, and competition for resources (independent variables) and styles of interaction with system members (dependent variables) using infor- mation about the social service systems in two middle size midwestern cities. Information about the respondent organizations which is used comes from agency records, interviews with key informants, the agency directors, and questionnaires completed by the directors. Chapter II describes the project and discusses the method of data collection and processing. Because information about the primary environments of social agencies (i.e., the network) is limited, in addition to testing the general model and the specific hypotheses which are part of that model, the analysis includes descriptive information about networks, system similarities and differences, and, within systems, the re- lationship of competition to other network factors. In addition, the design and analysis tests other major ideas about interorganizational relationships in order to demonstrate the explanatory power of the political economy model in contrast to other approaches. The design uses organization characteristics of technology, age, sponsorship, size, staffing patterns, and diversity of services identified as significant in the organization-environment literature, network position indicators, and two measures of competition to test a series of hypotheses about agency interactions. Two general 31 Eijpproaches from the organizational literature, the exchange per- ssjpective and the organization-set model, are basic aspects of the design. The causal model predicts that competitive pressures stimulate innteractions with other organizations because interactions are ways to secure both material and authority resources (Benson, 1974). Be— cause of the function interdependence in the social services sector some interactions are part of the regular or "normal" work of the agency. This means not all the interagency relationships are stimu- lated by resource seeking or competition. Organizations seek resources through interactions with other organizations in their primary environment (i.e., in the network), but since success in developing resource-based interactions requires an ability to offer valued resources in exchange, the resources the organization has to trade are key determinants of its interactions with system members. Further, the network or interagency system is hierarchically organized with some members controlling resources for others. The organization's position within the stratification system affects its attractiveness to potential interaction partners. Since need for resources is a stimulant to interaction and valued resources a prerequisite, some organizations may have resources needed by others but engage in few interactions as Actors because they have few needs. Others may have valued resources and be stimu- lated by competitive pressures and need for more resources to seek interactions with system members.and as Actors engage in a large number of varied interactions. Still others may be stimulated by - u 4 "' -. . .- - 4 “' v-.- u .— ~~~1 .. ,. a- ll .. ‘o. 4._ .. . .g. -. UI. ‘ ‘ I O. ‘ E o._ .' ~. .§\\ - . \I'o. "I‘ .' -_‘ . v .x *4 “s. §.‘ .h_ t ., xx . ' C 1.... ‘I, s . I ~ _ l h'. ‘. C.- . . x I A, - U. 1‘ -- ‘\ .‘ . ~ '.‘ ~ ‘— 3 1“ \ . 32 competitive pressures and resource needs but have little to offer trading partners and, thus, be limited in Actor interaction behavior because of these factors. And a fourth group may have few valued resources but because of low needs and/or few competitive pressures engage in a small number of interactions. In summary, the model assumes interorganizational relationships are caused by (l) work—related needs for the resources of other agen— cies, and (2) resource scarcity and the subsequent competition for resources. The interdependence in the system and procedures for conflict management legitimate resource acquisition through organi— zational exchanges. These exchange interactions need not be balanced or reciprocal, but sustained direct resource exchanges probably re- quire rough reciprocity. Thus, some interactions require that the Actor organization have valued resources. Further, the system or interagency network is not a collection of members of equal status, but is hierarchically organized with some members controlling re- sources for others. The principal research focus is the Actor organization in the interagency network, but characteristics of the primary environment, the network, are analyzed because these affect the Actor organiza- tions behavior. The analysis considers types of organizations inter- acting within the organizational system. Because the system is em- bedded in the city, some characteristics of the agency's secondary environment are considered as these probably affect the agency's primary environment, the network. Because data come from only two cities, causal relationships between city characteristics and network and organization factors are not tested. 33 Because information about interaction patterns is limited, tine research is designed to collect data about the extent of inter- aqctions and the types of interactions. In addition, the relation— sfdps of organization and network factors to interactions involving interagency cooperation are examined. Following Evan (1966), the network is viewed as a cluster of interacting organization-sets, and the model is expanded to include four different types of sets: competitive, reference—group, simple exchanges about normal work, and coordinated exchanges. As an Actor the focal organization (ego) may have a variety of interaction part- ners and a single partner may be involved in several of its sets. With some partners interaction may be restricted to one type of set. Each respondent is potentially a setdmember for other organizations; it is involved in interaction as a Target (alter). When respondent organizations are selected by system members as interaction Targets for a variety of exchanges, the organization is clearly a source for valued and needed resources. The types and number of Target inter- actions are, therefore, a measure of position in the organizational hierarchy, and an organization which is chosen as a Target in inter- actions by a large number of organizations for a variety of types of exchanges is an organization which is powerful within the system because it has command over resources others want. Expanding on Levine and White's exchange approach (1961), agency interactions are considered to involve the exchange of intangible as well as tangible elements, or to use Benson's words, to involve both money and authority interactions. In this highly interdependent system, agencies depend on other social service organizations for 34 cmstomers, a market for their product, a share of money, suitably trained staff, and other concrete resources. To survive they need resources such as recognition, support, goodwill, legitmacy, prestige, a clear, valued domain, and information. A list of interactions (Appendix B) covers the different types of exchanges used. These interactions are grouped into four types: competitive (i.e., for money, resources, domain), reference-group (i.e., involving recognition and support), simple exchange interactions (i.e., referrals, exchanges of information), and cooperative interactions (i.e., those requiring planning and commitment of resources and involving agency autonomy). The type of work is an important aspect of interactions, as the mode of production affects both internal characteristics and inter- actions (Woodward, 1965; Zerman, 1970). There are two broad types of social service organizations. Treatment agencies, seeking to change people somehow, generally have a Clinical model of work. Some Treatment agencies try to change groups or neighborhoods. The second type, Distributive agencies, provide an array of services and programs from which the user selects. There is no commitment to directly change or immediately affect the client, although there is the idea that the user will be better off as he uses the services, and they are planned to be beneficial. Distributive agencies are vaguely people changing, but their focus is on long-range development of the person. According to Lefton and Rosengren (1966), organizations have varying degrees of interest in the client as a person; some have continuing broad lateral interests (Treatment), and for others the interest in client biography is more limited (Distributive). Wilensky 35 and Lebeaux (19653) state that professional social workers have broad lateral interests in clients and consider they are primarily people or group-changing professionals. Eichhorn and wysong (1968: 21) demonstrate that orientation toward clients is a dynamic factor in contact among agencies at both the administrative and operational levels, and organizations which differ in the nature of their interest in clients also differ in their propensity for interorganizational collaboration. Those with broad lateral interests are more likely to seek cooperation of other service organizations to realize them and, by doing so, contribute to the overall integration of agencies and services. The range of Treatment agencies in a local community can include a Child Guidance Clinic, Mental Health Center, Department of Vocational Rehabilitation, Office of Economic Opportunity, Family Service Agency, Big Brothers, Center for Retarded Children, Model Cities, Urban League, Community Development League, Substance Abuse Center, and Employment Training Center. Examples of Distributive agencies are YMCA and YWCA, scouts, Legal Aid, Visiting Nurses, Department of Welfare, Employment Security Board, Health Department, American Red Cross, Day Care for Children, Housing Department, Veteran's Center, and the local Social Security office. These two approaches to social service differ in the degree of complexity of the necessary technology (Perrow, 1967). Treatment agencies do work which requires highly trained professionals to deal with the non-routine needs of the clients. Each case has to be diagnosed and a plan of care devised. These organizations require a larger number of professional and/or highly trained workers than 36 Distributive organizations. Those Treatment agencies which provide a variety of different services following the clinical model require staff with a variety of professional training. Diverse Treatment agencies, then, have the most complex technology. As Hall shows in his summary of the literature on professionalism (1972), such organizations develop different communication and decision systems which may affect interaction patterns. The needs clients bring to Treatment agencies can stimulate service delivery exchanges (simple exchanges and cooperation), but if such agencies can meet clients needs internally, there is less stimulus to seek resources externally. Thus, high diversity of services may lead to low outgoing inter- actions, but may increase the organizations attractiveness to other agencies who need to refer clients to it. Distributive agencies are a diverse group. Some provide services which require a high degree of training (e.g., home nursing care); some are very specialized, and/or serve a single type of client. Others offer fairly routine services (e.g., recreation, camping, income maintenance) to a wide range of people. In general, their technology is simpler than Treatment agencies; but since people are involved, it is still somewhat non-routine. Considering technology of this type of organization as varying in degree of non— routiness, the least non-routine are non-diverse Distributive agencies. Diverse Distributive are second; non-diverse Treatment, third; and diverse Treatment are the most non-routine. As the number of services offered by the Distributive agency increases, the technology tends to become more complex because new skills are required, a more varied population is served, etc. As 37 Treatment agencies are more diverse they are not necessarily also more complex because they continue to counsel and prescribe, ex- panding the number of problems with which they deal but continuing the clinical model. Thus, these two types of organizations may respond differently to varying internal characteristics, and these differences may translate into varying service delivery interactions. Because of these important differences, the local agencies in each system were categorized as either Treatment or Distributive agencies, and the analysis compares the two Mode of Work types. Other important characteristics are age and auspices. The younger, 1960's era group of agencies were established with an empha- sis on effecting a redirection of services. Many were charged with developing new patterns of service relationships among local agen- cies. Funding requirements and survival needs stimulate them to develop extensive interagency interactions. But, these younger agencies may suffer the "liability of newness" (Stinchcombe, 1965) as they have had little time to develop a firm place in the system. Their long-term survival may be uncertain because they deal with stigmatized clients, and thus, other organizations may not find them attractive interaction partners. The pre-l960's group is a collection of many types of agencies; some are very small privately funded organizations which offer very few services; others are large, public agencies providing essential income support programs. The nature of their work will affect interactions, but information about the effect of period of establishment on structure and behavior in— dicates they will respond differently in resource exchanges than will younger organizations regardless of their work. Two age categories, Old and Young, are used in this work. 38 Sponsorship is another important condition. In each city, there are both public and private agencies, and organizations of both work types and of varying ages are funded within each sponsor- ship (Auspices) category. Although Auspices is interrelated with Age, it has a direct effect On relationships as well. As compared to private agencies, public agencies have a monopoly of the key services and important resources because they provide the major in— come support and other expensive services. Thus, they are the target for many types of interactions and are high in the hierarchy in the system. Having public sponsorship is probably an indicator of high resources. Like age, Auspices is an important charter-domain or situational variable, but it is not an organization type as is Treatment or Distributive. In this model of interorganizational relationships,resources are a necessary condition for the development of extensive inter- actions. In the organization literature size of staff, type of staff, and service diversity are associated with organization structure and behavior. For this reason these variables are included in the de- sign. In addition, for social service agencies, size reflects im- portant resources such as money, staff, and a domain valued enough to be allocated a large amount of resources. Size is evidence of success in the competitive struggle. Professional staff are an added resource in that many clients require skilled help, and organi- zations with such staff may attract interactions and increase their power in the system. Further, the literature indicates boundary spanning roles are primarily assigned to professionals. Service diversity may be a specific resource for organizations as variety 39 increases the possibility of attracting interaction partners. These three variables are considered to be resources agencies can use in bargaining for resource exchanges and important because they affect agency position within the network. Competition is a major independent variable. Since needed re- sources are in scarce supply, and the list of needed services readily expandable, these organizations exist in a competitive environment. But acceptable forms of competition are limited. The norms of the social work profession discourage expression of the competition which undergirds this system. Thus, it is difficult to measure competition by asking about it. Competitive pressures may be strong, and directors may report low pressure. The agency may compete with others for funds and other resources; the director may recognize this and be willing to report competitive interactions but report low competitive pressures, or vice versa. Actual competitive interactions seem a better measure of competition than perceived pressures. In a test of this two measures are used, Felt Competition based on reports of competitive pressures, and Actual Competition based on reported competitive interactions. Organizations vary in the degree they depend on other agencies for needed resources. They vary in internal resources and system position or power. As discussed earlier, in order to develop re- source exchange relationships, the organization must have some assets. Thus, some organizations with a lot of what other agencies need will have greater ability to engage in resource exchange relationships than those with few valued resources. As noted earlier, agencies need information, services, expertise, facilities, good will, legitimation, 40 etc. The kinds of services they provide will affect both resource needs and attractiveness as a partner. Further, the nature of the services provided by the whole group of agencies, by the system, will affect the type of services system members need and provide and will affect the local hierarchy of organizations. Agencies in a network with heavy emphasis on recreation services may not value the services of the rehabilitation agencies as highly as a system stressing remedial services. Hence, standing in the hierarchy will depend upon the combined needs of system members as well as on the specific resources of the agency. If an organization is named by many others as a provider of a variety of resources, it is an attractive trading partner. Thus, the organization's position in the sociometric picture reflects its relative status in the system and its relative level of valued resources. Power or influence is dependent on possession of re- sources such as expertise, information, or rewards which can be ex— changed for compliance (Rice and Mitchell, 1973). A major independent variable is Importance (i.e., position) which is measured by the number and variety of nominations the agency receives. This is an indicator of power within the system; it is an indicator of general ability to exchange- The dependent variables are aspects of agency interaction patterns and include the number of setdmembers, the number of choices of interaction partners, the variety of interactions, reciprocalness, and extensiveness of the several types of interactions, e.g., refer- ence—group interactions, simple exchanges, and cooperative interactions. In addition, the agency position in the network (Importance) is used 41 as a dependent variable as well as an independent variable in order to test the relationships between competition, organizational characteristics, and charter-domain conditions which may affect both the organization's ability to develop interactions and the whole pattern of interactions in the network. A series of specific hypotheses (described below) about inter- organizational relations test the general political economy-competition and power model and other ideas about c00peration and interactions based on a review of the literature in field which concentrates on the importance of charter-domain and organization factors. The network itself is an important emphasis, and the research seeks to connect network conditions to organizational behaviors and to bggi§_ to examine the social organization of networks rather than continue the focus on the Actor organization. In this the research breaks away from the existing body of empirical findings which concentrates on the specific characteristics of the Actor organization as an independent entity which relate to interorganizational relationships. Here, both the organization and the system are considered, but because data are available for only two cities, causal hypotheses about system characteristics are not possible. In addition to testing hypotheses about competition and power and interactions, by testing a series of other hypotheses the data are used to show the low explanatory power of other approaches to the problem of interorganizational relations. Therefore, as hypotheses based on the other views are tested and found unsupported agd_the political economy-competition and power-based hypotheses find support, 42 the explanatory power of the model used here is demonstrated. The limitations on analysis because of the size (i.e., number of organizations) and the highly differentiated nature of social service systems are described in Chapter II. These limitations affect the extensiveness of some of the hypotheses. Summary of variables Chapter 11 includes information about the operational defini- tions of the following variables and Appendix B gives wording of questions used to develop these variables. I Independent variables A. Characteristics connected to domain and charter 1. 2. 3. Mode of Work. Two categories, Treatment and Distributive. Age. Two categories, Young and Old. Auspices. Two categories based on funding sources, Public and Private. Specific resources 1. Size. Number of employees 2. Degree professional. The proportion of the total staff with professional training. 3. Service Diversity. The number of distinct services the agency provides. Competition 1. Felt Competition. Reports by the directors of the extent the agency experiences competition from different sources. 2. Actual Competition. The number of competitive inter- actions reported for the agency. II 43 Network position (i.e., power, ability) 1. Overall Importance (or Position). The number of times the agency is nominated as an interaction partner by system members; a measure of system power. 2. Scope of Importance. The number of different inter- actions for which the agency is named as an inter— action partner by system members; a measure of extensiveness of influence. Dependent variables A. Organization-set. The number of agencies identified as interaction partners in all types of relationships. Network, Sector, and Community interactions. Number of different interactions reported with various types of organizations and groups (described in Chapter II). Variedness. The number of different types of inter- actions reported by the organization. See Appendix B. Reciprocity. The number of organizations with which the agency is involved for bg£h_outgoing and incoming choices, i.e., mutual set members. Reference-group interactions. These relationships in- clude intangible resources such as good will and support. Simple exchanges. The number of relationships reported which involve direct exchanges without requiring planning or commitment. Cooperative interactions. These relationships involve planning, some commitment of resources, and require sharing autonomy. ._.._—_———— __.~.— _ 44 SUMMARY OF RESEARCH HYPOTHESES Work-related hypotheses Needs related to their general type of work and function stimulate agencies to develop relationships with other social service organizations and with community groups. They seek resources to meet specific client needs or are stimulated by agency users. These work-related needs are different for Treatment and Distributive organizations. Since their work follows the clinical model, Treat- ment agencies require a variety of services to meet complicated client needs (e.g., emergency aid, medical or nursing care, financial assistance, child care help, physical rehabilitation services, voca- tional training, legal assistance, etc.). In their customary work activities, Treatment agencies with non—routine technology are stimulated toward relationships with both Distributive organiza- tions and other Treatment agencies. Work requirements stimulate a need for consistent sources for needed resources, which can be secured by planned interactions (cooperation). For Distributive agencies the type of clients served affects the need for such services. For example, the welfare and unemploy- ment offices serve a more "needy” population than do scouts or the Y's, since the majority of users of such Distributive organizations are non-problem families. Therefore, it is expected that, although some Distributive organizations have extensive relationships, perhaps stimulated by client diversity or the type of services provided, many Distributive organizations will not be highly involved with others 45 and will have less need for reliable sources for needed resources. Therefore, the interaction patterns of the two work types of organi— zation will vary because of work-related factors. Hl As compared to Distributive organizations, Treatment agencies will have: a. More non-competitive or resource exchange interactions with other organizations; b. More varied relationships with other organizations; c. More cooperative relationships with other organizations. Local social services systems require functions or services related to both Treatment and Distributive types of work. Thus: H2 Type of work is not a determinant of organizational position in local systems of social service organizations. Sponsorship and age-related hypotheses Sponsorship is an important factor in system position and agency behavior. The essential and expensive service, needed by a variety of clients from many agencies, are supported by tax funds, and Public agencies, as a group, are usually more important to other members of the system than the Private agencies. Further, because they often have large budgets and authorization to contract, Public agencies are a source of material resources for other organizations. 0n the other hand, some Public agencies are small, highly specialized, and have limited budgets and are not attractive sources of resources for many agencies. The Private agency group is highly differentiated. Private organizations exist for varied reasons; some suit the needs of particu- lar constituencies and continue because they are popular with certain 46 types of givers; others are considered to serve general community needs or to have a preventive function (e.g., youth-serving agencies, recreation centers, the Red Cross, etc.); and still others meet specialized service needs (e.g., day care, services for the elderly, family and youth counseling, help for the handicapped and retarded, etc.). Users of many of the Private agencies do not think of themselves as clients, as "needing service" but, as participants in activities which are agency programs. Agencies with such clients do not need other agencies for client services but for resources such as legitimation, information, clients, etc. Age is an additional factor. The post-1960's group of agen- cies customarily are charged with developing new service patterns and seek to affect the delivery system through increased coordina- tion with other agencies and redirection of services into difficult areas (e.g., crisis intervention, services to poor, community organization, etc.). The voluntary sector has some outreach agencies, but the public sector has responsibility for the more expensive and complex new efforts. These newer Private agencies, frequently created in response to pressure from special groups or stimulated by public or foundation funds, are innovative but limited in financial re- sources and community standing. Because of distinctly different service emphases, general functions and clients, both Public and Private agencies vary widely in specific resource levels, and depending upon the type of work, vary in level of professionalization. Overall, public sponsorship is a sign of resources and is an important indicator of system position, but within Auspices types there are wide variations. . .I~ I; § :‘§ .- u .. I. - u I.§~ I. s -!~II c \ y I s _ .INIi ~-. ~ ~0~u~¢ .uao‘ I. ..u 47 The highly differentiated nature of these systems and the restrictions imposed by the small number of cases limit the testable hypotheses. H3 As compared to Private agencies, Public agencies: a. Are more important to other agencies (higher Overall Importance and wider Scope of Importance); b. Have more specific resources (size, services, pro- fessional staff). Because of the nature of their work (e.g., multiple-problem IJSEIS, newer outreach services) and age-related factors, HA In comparison to Private-Treatment agencies, Public-Treatment agencies are: a. Higher in Resource Exchanges; b. More varied in relationship with other organizations. Because of the nature of their work and higher resource levels, H In comparison to Private-Distributive agencies, Public- Distributive agencies are: a. Lower in Resource Exchanges; b. Lower in Cooperativeness. For organizations like these, age reflects a 'press toward interactions and cooperation. But, successful development of inter- actions requires the ability to attract interaction partners. In the general competition for resources over the years, older agencies acquire system position and resources which are important factors in developing interactions. As mentioned, the limited number of cases prohibits examining the joint effect of Mode/Auspices/Age and, without this, interaction pattern data are difficult to interpret. This limits the hypotheses dealing with age. 48 H As compared to Old organizations, Young agencies: a. Have fewer resources; b. Are lower in Overall Importance and in Scope of Importance. H7 When general resource levels are the same, as compared to Old organizations, Young agencies will: a. Have higher levels of Resource Exchanges; b. Have more varied relationships with other organizations. Ability-related hypotheses Agencies are able to develop relationships with other organi- zations and groups to the extent they have generally valued resources (e.g., perform needed functions, offer valued services, are sources for various intangible as well as tangible resources). Although systems may differ in the specific resources generally valued, within systems organizations vary in overall attractiveness to others as interaction partners. System valued resources are prerequisites for extensive interorganizational relationships. Thus: H8 The higher the level of generally valued resources (network position), a. The greater the number of Resource Exchanges; b. The more varied the relationship with other organizations; c. The higher the level of Cooperativeness. Regardless of their Mode of WOrk, for social service organi- zations employees are resources and an important determinant of network position and interaction behavior. Since many needed services are only provided by highly trained professionals, a large number of professionals in the staff is a further resource. To establish inter- agency relationships, an organization needs appropriate staff to inn-u — n u. 5..-“! can... c‘v- . \. u: u 1 .I J" '5 . . “'T I.‘ ‘n ‘I 49 perform boundary-spanning work, and usually this is handled by professionals. If an organization is small, professional staff ‘members are needed for organizational maintenance and immediate client related work and cannot be used to develop complex relation- ships with other organizations, thus limiting the development of cooperative relationships. H9 Regardless of the Mode of Work, the larger the organization, a. The more it is valued by other organizations (higher Overall Importance and wider Scope of Importance); b. The higher the level of Resource Exchanges; c. The more varied the relationships with other organizations. H10 Regardless of Mode of Work, the higher the Professional Ratio, a. The more it is valued by other organizations (higher Overall Importance and wider Scope of Importance); b. The higher the level of Resource Exchanges; c. The more varied the relationships with other organizations; d. The higher the level of C00perativeness. The number of services offered is another important resource affecting system position and interactions. A large number of services attracts a variety of interaction partners and so increases agency network position. As a stimulus to agency interactions the effect of Service Diversity varies by Mode of Work. For Treatment agencies, the more services provided internally, the less the need to seek needed resources from other agencies. Diversity stimulates other agencies to use the organization as a source for services and re- sources. The clinical model of work means Treatment agencies require stability in resource exchanges, and they will invest resources in 50 cooperative relationships to a greater extent than will Distributive agencies. For Distributive organizations, Service Diversity stimulates interactions because it is connected with a more varied client popu— lation (e.g., varied in interest, age, race, or place of residence). Because the type of work does not require long lasting exchange re— lationships,these organizations do not commit resources to cooperative relationships but primarily limit interactions to exchanges. H11 Regardless of the Mode of Work, the higher the Service Diversity, the more the agency is valued by other organizations (higher Overall Importance and wider Scope of Importance). H12 For Treatment agencies, the higher the Service Diversity, 3. The higher the Resource Exchanger level (Target); b. The lower the level of Resource Exchanges (Actor); c. The higher the level of Cooperativeness. H13 For Distributive organizations, the higher the Service Diversity, a. The higher the Resource Exchanger level (Target); b. The higher the level of Resource Exchanges (Actor); c. The higher the level of CooPerativeness. Competition-related hypotheses - the relationship of competition and Aggher conditions Competition is connected with agency resources. Resource levels are the result of two major types of factors: (1) past success in the competition for valued domain and resources; and (2) the value of the services the agency provides. Value may be related to the extent of need in the community or to demands from leaders of in- volved community groups. In addition, the opinions of elites are important determinants of value or demands. Demands do not need to 51 reflect needs and are stimulated by p0pu1arity of the service, personal opinions, and national fashions in services. Although it may be logical to expect directors of organizations engaged in a high number of competitive interactions with other agencies to also report high feelings of competition, data from other fields finds an un- reliable relationship between attitudes or opinions and behavior. Because the norms in the social welfare field support expression of ideals of partnership, cooperation, consensus, devotion to clients, and unselfishness, competition is rarely discussed. This means directors may easily report both high Actual Competition and low Felt Competition. Accordingly, H14 There is a low positive correlation between Actual Competition and Felt Competition. Resource levels are connected with success in competition. Thus, instead of high resources leading to high security and limited competitive behavior, H15 The higher the general and specific resource levels, the higher the competitive interactions. Organizational security is a factor in perceptions about competitive pressures. Because funding patterns differ, Public and Private agencies experience different competitive pressures. Older organizations have greater security than newer agencies. Thus: "16 The higher the position in the network, the lower the Felt Competition. H17 Public agencies have lower Felt Competition than Private agencies. H18 As compared to Old organizations, Young organizations have higher Felt Competition. 52 H19 Because interorganizational relationship require resources, Felt Competition level is unrelated to interaction level. The relationship between competition and styles of interaction The basic assumptions of this research are: (1) Interactions are stimulated by need for resources which are related to the normal or customary work of the organization and the nature of the inter- dependence in the social services system. A certain minimal level of interaction is expected regardless of other factors. (2) Inter— actions require resources or ability. Hence, the higher the resource level, the larger the number of relationships, (3) When work-related interactions and ability-related interactions are considered, com- petition for resources will stimulate additional interactions. Thus: H20 Considering work needs and resource levels, the higher the level of competition: a. The more extensive the interactions with other organizations; b. The higher the level of Cooperativeness; c. The more varied the relationships with other organizations. Plan of the report Chapter II describes the research methods and analysis techniques, including details of operationalization of measures, distributions of measures, and statistical tools and factors about the data collection which affect the usefulness of the findings. Chapter II includes demographic information about the settings for these systems (the cities) and describes various aspects of the two social service systems which relate to variations in the patterns of relationships among the independent and dependent variables. The 53 relationships among the independent variables are considered in Chapter IV,and hypotheses relating to system position, or ability (Target interactions) are tested. Chapter V tests the relationships of the independent variables to specific aspects of the dependent variable, interaction patterns. The final chapter, building on the political-economy framework, focuses on system factors and discusses the relationships of system differences to the organization's power or system position and system differences in competitiveness, power, and patterns of organizational interactions. The data are used to explore the process by which competition for resources determines the hierarchy of dominance in social service system. As noted earlier in this chapter, this research has both theoretical and applied value. Accordingly, Chapter VI includes a section discussing the implications of these findings for social planning and the findings describing existing interactions are presented in considerable detail, because of their value to planners and policy makers. This is exploratory research, designed to test a number of ideas which the literature indicates may be determinants of inter- action patterns. (Dne purpose is to show the weakness of many of the prevailing approaches and the power of the parsimonious power and competition model. Therefore, two main data chapters (IV and V) test various hypotheses from the literature as well as those hypothe- ses based on the political-economy framework. Because the body of “Wflrical findings in interorganizational research is so severely limited, a great deal of evidence is included in this report, 54 probably more than the reader will welcome. It is presented because future development of theory requires rich detail. Hopefully, others can use these very detailed and complex data for future work and begin to develop an integrated body of empirical findings. Finally, Chapter VI includes a discussion of the contributions of this research to issues in research on interorganizational re- lationships. -~. ' o» ".-.L '-. -»s ..,. ; "n. a "u. ‘. In... . . <~ H; u '0 u - n.- 5.. 55 CHAPTER II METHODS Source of the data - the larger research_project The data used in this report come from a larger study of social service systems in two middle size cities in a midwestern state. The project was under the overall supervision of Philip M. Marcus and directed by Ann W. Sheldon with help from Margaret J. Adams. This re- port describes one important aSpect of the larger project, the relation- ships social service agencies have with similar organizations in the immediate environment, i.e., within the local set or system of social service agencies. Because the nature of the larger research program affects the quality of the information used in this report and, hence, the nature of the conclusions which can legitimately be drawn from these data, information is presented now about the larger project. The larger study, conducted between October, 1972 and July, 1974, collected information about many aspects of social service organizations and organization-environment relationships. TheSe include: (1) Organization structure factors of size, staffing patterns, decision-making processes, communication channels, and staff autonomy and conflict; (2) Attitudes and opinions of agency directors about the provision of social services, inter-agency competition and cooperation, re- source needs, community relationships, and agency problems; (3) Social support networks and the social and economic exchange relationships, or transactions, among social service organiza- tions in these local communities, including agency and services integration; (4) Budgets, funding sources, and resources allocations; 56 (5) Details of agency work including number and types of staff number and types of clients, number and kinds of services, work complexity, and referral practices; and, (6) Competition with other organizations for needed resources. The information was collected for two purposes: first, to test major ideas in the organizational and inter-organizational literature which seem relevant to organization-environment questions and, second, to provide information about existing local patterns of cooperation, conflict, and services integration to the primary sponsors, the local United Way organizations, and to the service agencies who participated. An important consideration is that both theoretical and applied aspects of the project focused on interorganizational relationships. Research procedures including the preliminary field work, selection of the respondent organizations, design of the data collection instruments, and details of administration and data preparation were planned to con— centrate on interaction patterns. Further, the research was designed and these data were collected and prepared within the general model of com- petition for resources as a cause of interorganizational relationships outlined in the previous section. Although using only part of the available information, the material presented is a key part of the total research project and not appended for other purposes and then adapted to the study of interorganizational relationships. Preliminary work on the research design began early in the summer, 1972, after an extensive review of existing research, the various annec— dotal and speculative writings, and the different models of interorgani— zational relationships preposed in the limited literature in this field. In addition, both investigators had prior experience in the social 57 services sector useful in evaluating the existing literature and roughing out initial plans. An opportunity to do a community attitudes survey for social agencies was used to develop entree to agencies and collect preliminary information about the set of agencies in the first city. The field work- developmental phase, October, 1972 through March, 1973, included a thorough review of the type of written records used by these agencies, interviews with public and private planning officials and with agency personnel at several levels, and contact with agency clients, community leaders, and local agency board members. During this period, the field work was combined with progress on the conceptual level through prepara- tion of background papers, regular meetings of the research group, and with members of several graduate seminars. Links to informants permitted discussions about the nature of organizational life, agency interaction, and important agencies in the community. These discussions were valuable because they permitted an on—going exploration of the tentative research hypotheses with those directly involved in this field and helped work out the practical as- pects of the research plan (e.g., meaning of words and phrases for respondents, length of interviews and questionnaires, selection of organizations for the interaction questions list, and details of securing simultaneous access to a large number of different organizations). Although the preliminary field work and the development of the basic research plan were developed in one city, the research was planned from the beginning to be a comparative study. When funds permitted study in the second city, background interviews with local community leaders, agency board members and personnel, and planning officials were 58 conducted and the original instruments were refined to meet the par- ticular conditions in the second city. Agency and planning personnel were involved in develOping those parts of the instruments connected to interaction choices for that city, local information was used to select respondent agencies, and local informants helped with access questions and the preliminary interpretation of interaction patterns in that city. Thus, extensive fieldwork preceded data collection in both cities. There was a continual interchange between those concretely involved and those with a more abstract interest in the general problem. The instru- ments were developed for comparative research but with the peculiar needs of each city in mind. Of central importance, the primary purpose of the larger project was theory testing. Research instruments - design and testing Three instruments were used: first, a highly structured formal in- terview with agency directors lasting about one hour conducted by a project-trained mature interviewer; second, a self-administered question- naire requiring about 30 minutes to complete left with respondents and returned by mail; third, as supplement to agency records, a short questionnaire developed later to ensure comparability of record-based data. As noted earlier, work on these instruments and data collection plans began after several months of field work. Various drafts were developed with help and advice of local officials and people at Michi— gan State University interested in interorganizational relations, and the instruments were pre-tested in the spring, 1973 under the expected research conditions in a city very similar to possible target cities in population and work-force characteristics and the family of social 59 agencies. Information was collected in the first city from May through July, 1973. In the second city field work occurred between October, 1973 and March, 1974 with interviews held during the spring, 1974. Copies of all the instruments used in the overall project are available from the Department of Sociology, Michigan State University. Appendix B gives the questions used to collect the specific information used in this analysis. Data collection Because social service agencies are interdependent and hier- archically organized, management of access is an important aspect of securing sound information. The preliminary information about system dominants was used to develop access procedures and interviewing tech- niques because agency interdependence can lead to normative responses as well as to low response rates. These organizations are in an uncertain environment and staff are subjected to a variety of external pressures. Accordingly, personnel are sensitive and suspicious. To obtain useful information, the data collection process must insure respondents feel secure enough to respond fully and accurately. To gain cooperation, di- rectors and involved personnel received written and oral guarantees of confidentiality. In addition, the need these organizations have for this highly useful information, agency involvement in research planning, and agreements to supply reports which fully insure agency anonymity to all agencies are further procedures which give confidence in data adequacy. The success of access plans is shown by the excellent response rate. One hundred per cent of the 68 organizations gave full information to the interviewer and only one organization did not complete the shorter self-administered questionnaire. This single missing case affects only 60 two variables used in this report, Felt Competition and Professional Ratio. (The missing case was assigned the mean score of organizations similar to it for these variables.) All other information used was available for all respondent organizations from interview-questionnaire responses or existing records. A potential source of difficulty in research like this is the interview itself. These data were collected through a long session with agency directors. Such elite respondents require well-trained inter- viewers, informed about the social services sector, and able to establish sufficient rapport with the directors to insure trust (and hence, accurate answers) and cooperation in all the phases of the research-~a consider- able commitment of time and agency resources. Criteria for selecting interviewers were familiarity with the community and social services in general, non-student appearance, previous contact with policy—makers or elites or high self-assurance, willingness to work under very close super- vision, and overall interest in the research. The same person, Margaret J. Adams, was the Interview Supervisor in both cities and participated in the general planning, design of instruments, and testing procedures. She was, therefore, fully familiar with the research and the nature of the organizational scene in each city. All interviewers received at least four hours of training and both males and females were used. Interviewers involved in the pre-test assisted in developing training guidelines for the interviewers in both cities. Close contact was maintained by the Interview Supervisor to ensure common techniques were used in all cases. Completed interviews were re- viewed immediately to spot missing information and clear up ambiguities. Interviewers prepared a report after each interview which described 61 interpersonal aspects of the interview, potential areas of misunder- standing, and recorded information volunteered by the directors and any contradictions, hesitancies, or areas of confusion were noted. Review of these reports indicates a high level of rapport was established in almost every case, and the high response rate shows this to be the case. In summary, the careful supervision and thorough training of the interviewers gives additional confidence in the information collected. Respondent organizations At the community level social services are delivered through a variety of groups and organizations. Some limit themselves to social services while others have different primary objectives (e.g., religion, education, health care, crime control, or political action) but have social service sub-units to help with major work objectives. Some pro- grams are provided by groups of unpaid workers; others operate through the activities of voluntary associations within generally non-social service programs. Further, some agencies are well-established, secure organizations while others are very transitory. Since this re- search concerns the behaviors of formally established, on-going organi- zations whose primary purpose is providing social services, criteria for the selection of respondent organizations were essential. Unfortu- nately, there is little agreement in the literature about what is an organization. Most research does not seek to include the universe of social service organizations, but instead studies a Specific subset without formally describing criteria for inclusion. Clearly, not all groups which provide social services are really formal organizations. Further, what is a social service? Again, research into organizations in.the general field does not provide guidance as to selection of a 62 universe of such organizations. For budgeting purposes local and national funding organizations in the social welfare field have developed standard service categories or 'functional budgeting' categories and these were used to define social services. If an organization is considered by local social planning professionals to have as its primary task objective provision to local residents of one or more of the services included in the funding-based categories, it was listed as a potential social service organization. Lists of such groups were developed from directories in each community and from interviews with informed local planners. This list was used to delineate the boundaries of the social service sector for interaction list purposes and to identify respondent organizations. Because the research goal was to study formal organizations, addi- tional criteria were developed to select agencies from this pool of potential organizations. Detailed criteria for designation as an organi- zation for this research are in Appendix A. The operational definition sought to include all local formal organizations of sufficient size to develop characteristics such as a hierarchy of authority and formal rules. Some of the very small private agencies are recognized as a formal organi- zation for funding purposes and these were included if United Way members. All the small United Way agencies met the minimum budget part of the operational definition and had policy-setting boards. Non-United Way groups which did not meet staff size and budget criteria were excluded. Public and private agencies have different policy decision pro- cedures and varying degrees of independence. The existence of an identi- fiable‘policy-setting body can be used as a basic criterion for both tYPes of organizations, although the policy-setting body may not exist 63 at the local level. The policy criteria were designed to exclude organi— zations with non-social service primary objectives and those which are units within other organizations or formed to reflect the work of another organization, e.g., a church or union welfare office, probation office, or hospital social service department. Some agencies spin off highly autonomous units which operate as independent organizations although not legally separate and dependent upon the sponsor for funding. Several recently established agencies are or- ganized with component agencies as units (e.g., Model Cities, Community Mental Health Board). Because the operating procedures and structure of these agencies are very similar to the legally autonomous organizations, when components met other size and minimum budget criteria they were in- cluded in this study. Because this aspect of social service organiza- tions was not fully understood initially, unfortunately, some were not identified as organizations in the beginning phases of the study in the first city and thus were not included on the interaction list. Although data were collected later, the limitation of network analysis which re- quire all Targets to also be Actors, or a closed chain, means these organizations' data cannot be used in this analysis which relies on sociometric measures. All eligible components were included in the second city. This limits the size of the sample by eight organizations in City A, i.e., there are 41 organizations which meet the criteria for inclusion but only 33 can be used because of the limits of network analy- sis and missing sociometric measures for the other eight. Since all of the included component organizations are supported from tax funds, they are considered part of the group of public organizations. 64 In each city only one non-United Way, privately funded organiza- tion met the modest size and budget criteria. The category Private is largely made up of the group of United Way or voluntary agencies as these are the organizations which have developed powerful enough constituencies to continue over time and gain sufficient support to employ full-time staff. Most of the Private organizations are the old, well-established agencies represented in hundreds of local communities. None of the newer privately established organizations met the very low budget and size criteria so the research does not include such groups as privately spon- sored local crisis centers, emergency aid projects, or community organi- zation programs. Such groups were included in the list of interaction Targets as part of the social welfare sector but very few in either city received more than eight nominations which indicate they are unimportant elements in local networks. In summary, the organizations included in this research are all the privately funded agencies in each city that are members of the local United Way or sufficiently large enough to be included, all the major public agencies, primarily offices of state agencies or county organiza- tions, and most of the component agencies. Data were collected from the universe of organizations meeting these specifications rather than a sample of such organizations. Hence, statistical tests of significance are presented only to indicate the magnitude of associations or differ- ences. Data were collected from agency records and reports of agency directors. Obviously, the director is not the organization and differ- ences probably exist among organization members and between staffing levels. The need to develop organizational level variables requires the 65 use of informants for some measures as well as manipulations of responses for all or a sample of members to develop aggregative measures. The task is to constructorganization indicators which are not aggregations of member perceptions, attitudes, or Opinions. One solution is to rely heavily on records and measures integral to the organization level of data; another is to use key informants. In this research the director was interviewed as the key informant and, while not always fully informed about every aspect of organizational behavior, the director is the chief executive officer authorized to speak for the organization in interactions. At the t0p of the communication and authority chains, with multiple responsibilities, he or she is more informed about the various subunits than the second level staff with limited responsibilities. In small organizations such as these, the di- rector can be in fairly regular touch with the several parts of the organization and thus an informed reporter. He or she is a major influ— ence (and usually the major influence according to Demarche and Johns, 1951) on organizational behavior with powers to hire /fire staff, allo- cate funds, direct planning for new programs,and reallocate resources. For these reasons, the responses of the director are used as measures of the organization. For the most part, the variables used avoid the difficulties of measures based on perceptions. Only one variable, Felt Competition, is based on director opinions, and other variables come from agency records. Director reports of agency interactions are used as organization measures, and, although replies to questions about inter— agency transactions may fail to report every organization in the organi- zation set, the design limits analysis to a maximum of five Targets 66 for each interaction question, it seems safe to assume the director will know these major transaction partners. Development of variables In this research, four general groups of independent variables are used to examine eight aspects of the general dependent variable, interaction behavior. Chapter I includes a description of the variables and Appendix B gives the exact wording of the questions used to collect the information. This section is limited to a description of the development of variables and discusses analysis-related factors. Summary information about distributions is provided in Appendix C. Independent variables 1. Characteristics connected to domain and charter1 a. Age Agencies are categorized either Young or Old based on period of national establishment of organizations with similar general functions and objectives. The early 1960's is used as the Age cutting point because that period was a critical point of change in the general direction of social welfare services. Necessary information for categorization comes from interviews with planning professionals, social work literature (e.g Romanyshyn, 1971).and personal experience. b. Auspices Based on the characteristics of the policy making body and the source of the major portion of the agency's regular allocation (core funding) agencies are called 1Although this approach to organization level indicators raises questions of validity and reliability, much of the comparative research uses the key informants strategy, e.g., Meyer, 1966; Pugh gt a}, 1968 and the anthropology research methods literature. In two careful reviews, Heydebrand (1973b) and Price (1972) conclude this approach is sound. It does avoid other difficulties such as excessive aggregation. 67 either Public or Private. Information for classification came from organization records. (See also Appendix A giving Operational definitions of an organization for information about policy-making board criterion.) c. Mode of WOrk ’ Two basic types of work are used, Treatment and Distributive. Information about the basic differences in these two types is in Chapter I. Classification information comes from: (1) written descriptions of program objectives in local directories, United Way service priority material, and budget application forms; (2) interviews with local planners and officials; and (3) author's own experience. Table 4 in Chapter III gives the number of agencies in each city in the general charter-domain categories. 2. General resource variables a. Overall Importance (or Network Position) This variable is based on the total number of nominations the organization re- ceives for all_the transaction questions listed in Appendix B. Each respondent named Up to five organizations and groups in the local social welfare sector as Interaction Targets from a list prepared for each community. Nominations as Targets in- dicate the organization has valued resources; this variable is an indicator of within—system power or influence. As dis- tributions show, scores fall at the low end of the possible distributions and in System B are more skewed than in System A (Appendix C). Each city has five organizations with high scores; in System A, one-half of the organizations received between 21 and 42 choices, and in System B one—half of the 68 cases have scores from 14 to 29. These scores are approxi- mately linear, but the distributions limit analysis,and the high variances within each city or system need recognition. Data analysis uses these scores three ways: (1) actual scores in correlations and t-tests; (2) ranks in the system for Counterpart organization comparisons, using Spearman rank order correlations; and (3) cut at System median to form High and Low Importance (or Position) categories. Additional information about the distribution of scores by city is in Appendix C and Table 10. b. Competitor and Resource Supplier These variables are the two parts of Overall Importance and are Target or sociometric choice measures. Nominations received for the four competi- tive transaction questions (Appendix B) form the Competitor score. Nominations received for all non-competitive trans— action questions (Appendix B) make up the Resource Supplier score. Distributions for both variables are in Appendix C and are approximately linear with some skewness. The agency's actual score is used in the analysis. c. Scope of Importance The organization's score for this variable is the total number of interaction questions for which it receives nominations from the respondent organi- zations. Distributions are linear. Other information is in Appendix C. Only the actual score is used. Overall Importance (or Position) and Sc0pe of Importance are two analyti— cally distinct measures of position in the systems' organizational heirarchy and are based on different manipulations of the data. 69 Specific resources a. ‘gigg This is the number of full-time and full-time equivalent employees reported in written records of funding organizations or in response to specific questions (Appendix B). As distributions in Appendix C show, these respondent organizations are small. Only 12 of the 68 agencies have 40 or more employees, and 35 have fewer than 20 (Table 10). The distributions in Appendix C show extremely high standard deviations, an indication of the wide variations in staff size, but data are approximately linear. Size is used in two ways: (1) actual scores in correlations and t-tests; (2) rankings within each system for Counterpart organization com- parisons using Spearman rank-order correlations. Degree professionalized (or Professional Ratio) This variable is computed from organization records or responses to specific questions (Appendix B) and is the proportion of the whole staff who hold administrative and professional positions. Organization Size affects the variable and A limits its usefulness as very small agencies may have a high Professional Ratio because the director will be included as a professional without also having the boundary- spanning resources usually assumed to be connected with professionalized staffing. Distributions are in Appendix C and Table 10 and are approximately linear. The higher mean and median scores in System B probably reflects Size differences rather than a significantly greater degree of professionalization. The actual score is used in the analysis. 70 Service Diversity Directors described the services provided by the agency, and the number of different services reported is used to develop this variable. A standardized system, Functional Budgeting, used by local United Way organizations to describe social services, pro- vided a list of services that helped to determine if a program mentioned is indeed a distinct service. A maxi- mum of eight services were coded for each agency. In the very few instances in which more than eight services were mentioned, the director clearly was describing related programs rather than identifying distinctly different services. Distributions are in Appendix C and are linear. Competition measures a. Actual Competition The agency's score is the total of Actor (outgoing) choices for the four competitive transaction ques- tions (Appendix B). Distributions are in Appendix C. For System A scores four and five are the modal categories and the remaining scores are well spread out. In System B the modal category is three. The distribution is very flat -- 63 per cent report scores from three to seven -- but not bimodal. In analysis this variable is used in three ways: (1) actual scores are used in correlations and comparisons of means; (2) rankings within systems are used for comparisons of Counter- part agencies; (3) cut at system median to form High and Low Competition categories. Felt competition This variable uses eight questions about competition (Appendix B). These items are highly 71 intercorrelated and form one general cluster in the cities.2 Distributions are in Appendix C. Inter-city differences in the independent variables are discussed further in the narrative associated with Tables 9 through 12. All of the measures are sufficiently linear to use Pearsonian product-moment correlations but the sociometric measure Overall Importance (or Position) is negatively skewed, particularly in City B, and both cities have high variances for the Size, Actual Competition, and two Position measures, Competitor and Resource Supplier. Dgpendent variables All of these measures are develOped using outgoing (Actor) choices for all or groups of interaction questions. Directors reported interactions with agencies and groups using an extensive list of or- ganizations and groups in the social services sector in each community. One to five responses were coded for each transaction. Directors rarely reported more than five Targets for a question. Interviewers did not probe for five, and frequently fewer than five were mentioned. If more than five were named, a random number table was used to select from those mentioned the five for recording. Coding procedures counted global responses (e.g., "all on the listf'"all United Way agencies") but did not select specific agencies for recording. Organizations or groups named which were not on the sector list but in the general healthdwelfare field were counted as Section interactions. Global re- sponses and non-health and welfare groups were included in the Community interaction variable. Thus, Actor behavior within the sampled organizations (network), interactions with others in the 2Standard score coefficient alphas are 86 and 85. 72 general social welfare sector, and general responses are three ways of summarizing reported interactions. Community interaction is the most inclusive variable. Distributions of the dependent variables are summarized in Table II. 5. Interaction variables a. Set This score is the number of different organizations named as partners in all the transactions questions (Appendix B). It includes only interactions with named organizations; global responses are excluded. The Actor organization may have several different relationships with a single partner. Inclu- sion of an additional interaction question in City B permits slightly higher scores than for City A, but this is generally unimportant because interaction patterns are limited to a relatively few agencies although organizations do report a variety of transactions with these same organization-set mem- bers. The additional question elicited few nominations. Network interactions This is the number of choices the Actor organization reports for all interaction questions or the total number of interaction ties of any kind the organiza- tion has with agencies which met the criteria for inclusion in the research (Appendix A). This Actor variable is similar to Overall Importance or Position, a Target variable. Sector Interactions An agency's score is the number of choices made from the interaction list or other organizations in the general health and welfare field identified by name by respondents. This variable includes the Network inter— action count. 73 Community interactions The most inclusive interaction score, this variable uses up to five responses for each inter- action question, and choices of any sort of group in the community (e.g. schools, League of WOmen Voters, Police Depart- ment, Garden Club, etc.) are added to the Sector variable. Because it does not reflect the organizations and groups di- rectly sharing a resource pool, this variable is not important for hypothesis testing but is reported for comparisons. Variedness This is the number of different interactions or transactions reported by the agency. The maximum is 18 in City A and 19 in City B. All questions eliciting a response of some sort are included. This Actor variable resembles the Target variable Scope of Importance. Reciprocity The agency's score is the number of organiza- tions with which it has relationships both as Actor and Target, or the number of organization-set members which also include the agency in their organization-set. Reciprocity is not limi— ted to an exchange of the same resources between agencies but involves any mutual interactions across all the interaction questions. This is a descriptive measure and not used in hypotheses. Resource Exchanges The number of choices of specific organi- zations made for the non—competitive interactions (14 in A, 15 in B) is the organization's score for this variable. This Actor variable is similar to the Target variable Resource Supplier. There are three sub—variables in this inclusive variable -- Reference-group exchanges, Simple Exchanges, and 74 Cooperativeness (see below). Questions used for each sub- variable are in Appendix B. h. Cooperativeness The score is the choices made for all interaction questions that involved planned action and some commitment of agency resources and autonomy. Scores in- clude reported interactions with any named organization in the sector or general health and welfare field. Variable independence Network and Sector interactions include the measures Actual Competition and Resource Exchanges; Resource Exchanges in- cludes Cooperativeness; and Reciprocity is embedded in Set. Set is not part of the larger interaction measures and thus not part of Re— source Exchanges or Actual Competition. To avoid correlations using embedded variables, in a few instances the Competitive-set score is substituted for Actual Competition. Although based on different counts the correlation between choice-based Actual Competition and organiza- tion-based Competitive-set is high -- System A r = .84; System B r = .80 -- as would be expected. Thus, when necessary, organization- based information is used for Actual Competition rather than choice- based data. Organization-set is never substituted for Network inter- actions. Choice-based Actual Competition can legitimately be used with Organization-set and, of course, with Resource Exchanges and Cooperativeness. If the Actual Competition measure is based on organi- zations rather than choices, it is footnoted in the table. When not noted, the measure is always based on choices. 75 Data analysis problems Because social service systems have a small number of members, research such as this is limited by the relatively few cases.3 Com- bining data from individual cities is one way to increase the N, but this is unwise as it may obscure important characteristics of these systems. Although here there is no real attempt to test hypotheses relating community characteristics to organizational behavior because data are available from only two cities, the preliminary examination of the data indicated important community differences exist. Accordingly, data from each city are kept separate, and the N is small. Agency characteristics and behaviors are described separately for each city, and cities are compared in selected instances. Criteria appropriate for the particular city are used to develOp categories (e.g., the organizations above the median 35 are High Importance in City A; in City B the category includes those above the median of 20). Even though multiple regression techniques are sometimes used with small N's, this is not sound, particularly for these kinds of data. When such measures are inappropriately used, the findings are misleading. As a further consideration, zero-order correlations are of limited help in testing the major hypotheses in this study, although they are useful in describing interrelationships eSpecially among the various independent variables. What is required is a method to consider wmrk-related or 'normal' interaction levels, the added effects of varia- tions in resources (or the ability to interact), and competition (a stimulus to interact). These three conditions are interrelated. There is no base of earlier findings which permits estimating how many Even in large metropolitan areas the number of distinct social SErvice organizations is probably under 150. 76 interactions are part of the organization's customary work, but field experience indicates some interactions are part of the normal work. Individual agencies supply specific segments of the community's package of services and their work requires interactions (e.g., re— ceiving referrals and giving information). Other interactions are the result of the high interdependence of these organizations (e.g., getting money from the same sources, receiving referrals) and not specifically initiated by the organization to seek resources. Thus, there is a certain interaction level not specifically related to the kinds of resource exchanges described in the interorganizational literature. There is no way to identify the extent of these inter- actions using these data. Organizations may experience strong competition and some 'press' for interactions but not have resources valued by others to use in exchanges. Competition and Overall Importance must be considered to- gether as well as separately. Further, organizations may have highly valued resources but be self-sufficient and need few services from other agencies because of the nature of their work and resources.- All three factors -- work—based needs, valued resources, and competi- tion -- produce interactions. It is difficult to separate 'normal' ' interactions from those stimulated by other factors because it is unwise to use second or third order partials. Preliminary analysis indicates these systems are highly differ- entiated. Some agencies are highly specialized in work, type of clients served, and niche in the overall system. This means there are only a few agencies of a particular type. Thus, there are only three Small-Public agencies in City A, and only one is a Treatment 77 organization; there are five Large-Private agencies, but again only one is a Treatment agency. The cities differ in the members in multipledvariable categories,and some cells are empty -- a serious limitation for comparative research. In addition, although the independent variables are approxi- mately linear, there are some extreme values for certain important variables. The components of the sociometric measures (i.e., the separate interaction questions) have skewed distributions. Pooling questions produces a more even distribution, but the measures remain somewhat skewed and there is high variance. Dichotomizing at the median seems the sensible way to handle this,although correlations are also presented to illustrate general trends in the data. Finally, since the community social setting may be significant, Network Importance or Position must be determined by standards of the separate communities. A high number of Target nominations in City B is not high in City A, if the general level of integration is con- sidered, and it should be. This complicates the comparison of Counterpart organizations (about two-thirds of the system) because- relative size, position, interaction levels, etc. must be considered. Previous research can give no guidance as to the meaning of size for these agencies or indicate what is a high_professional ratio. In- terpretations are difficult. Most research on the effects of Size considers an organization with 100 employees as small; here that is very large. Agencies with fewer than ten employees may operate like small groups rather than develop the organization characteristics de- scribed in the literature; yet these are autonomous formal organizations. ihxthis research large organizations are not large by the thinking in the 78 organizational literature, and data about the effect of Size needs to be interpreted cautiously. To handle this problem, system ranks are used to make comparisons for the Counterpart agencies. When variables are dichotomized, the median for the city is used, not a general median. Additionally, the base for computing variables which use the interaction questions is slightly different in these two cities. Nine— teen rather than 18 questions were used in City B. Consequently, scores 222 be slightly higher in B than A, yet indicate similar interaction levels. System B mean scores for all sociometric questions (both Actor and Target) are, in fact, much lower than System A's. Thus, the p .10 level of significance is used instead of the p .05 level. Procedures There are no really satisfactory solutions for the problems posed by the small number of cases, the interrelationships among the three charter-domain conditions, differentiation, and uneven distributions. Two techniques are used -- zero-order correlations by system and by single variable type and comparison of means (t-test). In most instances, correlations are by Mode of Work, as this is a primary characteristic of social service organizations. Some compari- sons are by sponsorship (Auspices) but other variables such as Age or Size are conditions associated with organizations, not types. It is tempting to develop Mode/Auspices types for correlations,but the number of cases in the smallest category is only six. In order to examine a variety of two-variable types, categories are developed and mean scores compared. ‘Mode and Auspices are considered together and types compared through t-tests. Importance is cut at the nedian to create High and Low categories and used with other variables 79 to create types. Although some N's are small, in most cases this tech— nique can be successfully used. In an extension of this approach, types are compared by competition level. Actual Competition is cut at the median to create High and Low Competition and used as a category. In a limited way, this begins to examine the three interrelated factors, type of work, valued resources, and competition. Again, comparisons of means are used and, although some cells have only a few cases, the data are used to describe general trends in each city. Embedded measures As noted earlier, some variables are actually parts of other variables. Actual Competition is a component of Sector interactions. Cooperativeness is a part of Resource Exchanges as well as Sector inter- actions, but it is possible to compare Actual Competition (a choice measure) with Size of Set or use Competitive set in correlations with Network interactions without correlating a measure with part of itself. Extreme care was exercised when using Actual Competition. In almost every instance, the choice measure is used and is never correlated with the larger interaction level variables. It is used with ResourceEx- changes as it is not embedded in that variable. In the few cases when Actual Competition was used with the larger interaction measures, the Competitive set score has been substituted for the choice based measure. When this is done in tables, it is footnoted. There is no problem re- lating Actual Competition to Resource Exchange or Cooperativeness. Cooperativeness is embedded in all interaction-level variables and in Resource Exchanges. It is pp£_part of Actual Competition. Thus, one can examine the relationships between Competition and Cooperation but 80 not describe the relationship between general involvement in resource exchanges and cooperation.4 Although high correlations exist between Interaction levels and Variedness and between Overall Importance and Sc0pe of Influence, these variables are analytically distinct and not affected by any embeddedness. Naturally, as the types of interactions reported increases, some increase occurs in the total number of choices of organizations for interaction partners; as organizations are attractive Targets for a variety of trans— actions their overall popularity also increases. Overall Importance and Scope of Importance are different aspects of organizational position. The number of choices and the variety of interactions are two different ways to measure interactions. Significance tests When data are not from a sample, assessing the meaning of correla— tions is difficult. To help in interpretation, significance levels for sample data for 'r"with appropriate N's are used following a table in Bruning and Kintz. For correlation interpretations and t-test measures, the p .10 level, one-tailed test, is used as the minimum because of the exploratory nature of this research; Table D Distribution of 't' from Blalock is used. 4This means a test of Levine and White's ideas are impossible at this point. 81 CHAPTER III SOCIAL SERVICE SYSTEMS AND COMMUNITY CHARACTERISTICS Introduction In the United States the social service system is highly frag- mented, multi-leveled, and’pcomplicated.l Although decisions about the appropriate ways to meet needs are often made within local communities, national and state officials also initiate policies and allocate re- sources which establish programs and affect local delivery systems. The complex process of decision~making about policy and fund allocations may be semi-visible, but, in addition, there is a process of redefini- tion of needs, goals, and priorities that occurs through an historical mixture of the work of voluntary associations, formal organizations, 'crusades,' influential writings, and changing national trends.2 The local social service delivery system is the product of decisions at several levels, including decisions by local elites. Since these systems have evolved over many decades, local differences may be very important. Many public and private agencies are locally planned, administered, and funded. Some are affiliated with national agencies while others are not, but their equivalents in hundreds of local communities offer similar 1Information about the organization and historical development of the social welfare sector is very limited. Wilenskv and Lebeaux (1965b) show the development of the mix of public and voluntary sponsor- ship; Piven and Cloward (1971) provide evidence about the combination of nation-state—local levels in decision-making; Morris and Randall (1965) show the fragmented nature of services provided to a particular needy group; and various texts in community organizations, e.g. Brager and Spedht (1973) also provide some support for the following statements. Decision research in related areas (e.g. Hayes, 1972; Ripley, 1972; Wolman, 1971; Zurcher, 1969, and others) coupled with the community—decision literature illustrates a pattern which seems similar to the situation in the social welfare field. How something gets on the decision 'agenda' is poorly understood -- see for example Bachrach and Baratz (1970) and Cobb and Elder (1972). 82 programs. Across the country the community social service system has local chapters of national agencies (e.g. YMCA, Girl Scouts, Visiting Nurses, Urban League, American Red Cross) plus a group of locally unique agencies generally providing a roughly similar package of services in— cluding youth programs, settlement houses, crisis centers, rehabilita- tion centers and the like.3 Regardless of how they are organized, agencies providing local services reflect national and state definitions of appropriate needs and services as well as local definitions. Local service patterns are determined within a larger institution framework (Sills, 1957; Zurcher and Bonjean, 1970). As community organizers soon learn, local public agencies partially operate within state guidelines; offices of major Federal and state basic services agencies are governed by a com- plicated series of Federal as well as state regulations and policies. The newer cluster of public agencies (e.g. Office of Economic Opportu- nity, Model Cities, Community Mental Health Board) are developed by local officials, use the existing local organizational system, but are heavily influenced by non-local guidelines, restrictions, and funding policies.4 In addition, for some types of services there is a filtering up as well 3The Functional Budgeting manual of National United Way of America is a good illustration of this aspect of these systems. 4The Older Americans Act gives an interesting example of this. Federal funds are channeled through state agencies which, upon evidence of local initiative, fund local planning groups. These are inter- agency Councils with some citizen representatives which must work within state and Federal guidelines to plan programs suitable apd_politically feasible in local areas. Without local initiative the funds will not enter the community, but the planning process itself, and the programs eventually offered, are due to non-local factors coupled with local de- mands. 83 as a trickle down pattern of decisiondmaking, and national policies are partially determined by the sum of local decisions.5 The material available about this sector is primarily case study research and how-to-do-it texts, but the picture that emerges from the available evidence is of a loosely joined system. Many local agencies are tied, at least partially, to non-local organizations although they seem autonomous. The agencies operate within the set of agencies, ser- vice resources, demands, and the pool of available clients in the local community. They are part of the local organizational hierarchy (Stinchcombe, 1965), limited by the local structure while at the same time forming it. Local agencies must be understood in the context of the interdependent set of agencies and the overall life conditions in their respective setting. Although empirical work demonstrates a variety of local conditions affecting social services outputs, (e.g. Bonjean 23 El, 1971; T. Clark, 1968; Fowler, 1964; Lineberry, 1971; Turk, 1970; and many others), it is not clear h2!_selected factors affect the system itself, and it is far from clear just what the major factors are. Further, the information is often contradictory. Because this research involves only a two-city comparison, a causal model with city characteristics as independent variables is in- appropriate. Yet, considering characteristics of local delivery systems, one must proceed under the assumption that factors such as variations in financial resources, definitions of problems and needs, the local group 5This is particularly true for those national voluntary agencies with a federated decision structure such as Family Service Association, Urban League, Camp Fire, YWCA. 84 of clients and customers, and the orientation of community leaders, as well as non-social service factors such as the local tax base, the age of the community, the composition of the population, political character- istics, etc. do affect the local system, although how this process occurs may not be understood. It is reasonable to assume community differences may very likely affect the way agencies are organized, the way they seek resources, and the way they interact. Although an analysis of city fac- tors is not the primary focus of the research, this chapter presents in— formation about the two cities and the pool of services and agencies which make up the local social services systems as a basis for under- standing system differences detailed later. City demographic characteristics Information about these cities is limited, and it is difficult to know which factors relate to social services. Accordingly, Table 1 presents some demographic characteristics of these two cities which seem likely to influence the nature of the two social service systems. City B is much smaller than City A and, although service needs may be similar in the two cities, the smaller population means fewer consumers of these services are available for each agency and the supply of private and public dollars is smaller, although per capita figures may be the same. As will be shown later, the cluster of agencies in the cities is very similar, and the smaller City B provides 82 per cent of the services pro- vided in City A. This may translate into different interaction patterns because agency operation costs may require a larger proportion of avail— able dollars and staff in the smaller city. This should affect client services, outreach efforts, and inter-agency coordination. Time, efforts, and funds needed to develop cross-agency programs and planning 85 TABLE 1 DEMOGRAPHIC CHARACTERISTICS* City A City B SM SA SM SA General pppulation (1970)‘ Total population 378,423 201,550 Per cent white 95.5% 94.7% Per cent Negro 3.8% 4.7% Per cent with Spanish heritage 2.2% .7% Per cent foreign born or with foreign or mixed parentage 15.0% 11.0% Per cent population change, 1960-1970 26.6% 18.8% Net in-migration 9.9% 5.3% Per cent families with female head 8.6% 8.5% Median age 23.4 years 24.5 years Per cent under 5 years 9.4% 8.5% Per cent 65 years and older 6.9% 7.8% Education (1969) Median school years completed by persons 25 years and older 12-4 years 12-3 years Per cent with less than five years schooling 2.0% 2.5% Per cent with high school degree or more 63.1% 60.7% Per cent with four years of college or more 14.9% 14.5% Percent elementary and secondary school enrollment is in private schools 16.2% 20.0% Income (1969) Median family income White families $11,313 $11,162 Negro families 8,435 7,659 Per capita money income 3,343 3,355 Negro per capita money income 2,400 1,976 Spanish per capita money income 2,228 2,807 Families with income (per cent) Under $3,000 6.2% 6.1% $3,000 - $4,999 7.0 6.8 $5,000 - $6,999 8.3 8.8 $7,000 - $9,999 19.8 20.8 $10,000 - $14,999 31.7 31.9 $15,000 - $24,999 22.0 20.2 $25,000 and more 5.0 5.4 86 TABLE l--Continued City A City B SMSA SMSA Poverty (1969) . Per cent all families below poverty level . 6.1% 5.9% Per cent families below 125% of poverty level 8.6% 8.3% Per cent of population receiving Public Assistance 6.2% 4.2% Per cent persons below poverty level are under 18 years old ' 32.9% 28.5% Per cent persons below poverty level are 65 years and more 17.1% 19.0% Per cent Negro families below poverty level 20.5% 18.5% Per cent Negro families below 125% of poverty level 26.4% 25.2% Per cent Negro families receiving Public Assistance 17.2% 13.3% Per cent Spanish families below poverty level 9.9% 10.4% Per cent Spanish families below 125% of poverty level 13.9% 14.2% Per cent Spanish families receiving Public Assistance 6.5% 13.1% Emplgyment (over 16 years, 1970) Total labor force 157,737 85,039 Per cent labor force is female 38.4% 38.1% Per cent female workers are married with husband present 55.8% 56.3% Per cent unemployed (1970) 5.1% 4.7% Types of employment (per cent) Manufacturing 24.8% 33.4% Wholesale/retail trade 18.8% 19.7% Services 5.8% 5.8% Education 16.2% 12.9% Government 26.5% 17.3% Construction 5.8% 4.5% Per cent white collar 51.4% 49.7% Per cent professional/managerial 24.3% . 24.4% Per cent sales/clerical 27.1% 25.3% Per cent craftsmen and foremen 13.0% 12.7% 87 TABLE 1--Continued ‘ City A City B SMSA SMSA Local government finances (1967) Tax rate per $1,000 State Equalized Valuation ,9. $48.47 $59-47 Property tax per capita $129.00 $140-00 Expenditures (per cent) Public welfare 3.1% 3.9% Health care and hospitals 4.9% 2.1% Education 55.6% 55.7% Political behavior Votes cast for President (1968) Per cent Republican 53.2% 53.9% * Sources: U. S. Bureau of the Census, County and Citprata Book, 1972; Washington, D. C. U. S. Government Printing Office, 1973; U. S. Bureau of the Census, Census of Population: 1970 General Social and Economic Characteristics; Final Report PC(1)-C24 Michigan Washington, D. C., U. S. Government Printing Office, 1972. 88 may be limited because of on-going maintenace needs for City B organi- zations. Further, both cities are overwhelmingly white. Although the pro- portion of non-white residents is slightly greater in City B than in City A, City A has a more”heterogeneous non-white population. Thirty- seven per cent of City A's non-white population reports a Spanish heritage as compared to only 13 per cent in City B. The existence of two minor- ity groups, generally lower in income and requiring more social services than the white population, but with differences (e.g. discrimination, migration rates, skill levels) translates into different pressures (and perhaps more pressure) for services than found in City B. Services-related pressures may stem from migration patterns and poverty. City A has experienced a higher rate of population change be— tween 1960 and 1970 (a period of rapid expansion of social service organizations), and net in-migration is much higher than in City B. In addition, the per cent of the population which is foreign born or with foreign or mixed parentage is higher in City A. Another measure of heterogeneity, enrollment in private schools,presumab1y reflecting re- ligious heterogeneity, shows City B with a higher proportion of its population in private schools. City A has a slightly greater proportion of its population with incomes below the poverty level and a larger proportion receiving Public Assistance. A larger proportion of Negro families are receiving Public Assistance in City A than in City B; for Spanish families, a much larger proportion receives Public Assistance in City B. This factor indicates some important differences exist between the two cities. There is a nchh higher proportion of residents with Spanish heritage in City A than 89 in City B. The difference between the two cities in the per cent of the Spanish population who are poor is very slight, i.e. about .5 per cent. Yet, the per cent of Spanish families receiving Public Assistance is twice as high in City B as in City A. A different pattern exists for Negroes. A somewhat greater proportion of the Negro population are poor in City A than in City B, i.e. about 2 per cent, Yet the per cent receiving Public Assistance is almost four points higher in City A than in City B. Further, Table 1 shows that a higher per cent of the popula— tion received Public Assistance in City A than in City B although the overall proportion of needy families is similar. These factors show a different assistance climate exists in the two cities. Additional evidence of differences in the local services climate is shown in allocations of local public funds. Although the form of government and political preferences are similar in the two cities, local public monies are allocated differently as Table 1 shows. (Later tables will show differences in service patterns.) Reasons for different allocations of public funds are not known. Presumably some combination of factors and pressures leads to these differences in treatment of low income families. Although there are differences between the two cities in education levels, occupation patterns, and income distribution, these do not seem sufficiently great to account for this. The median school years completed by adults is similar in each city and, while City A has approximately three per cent tore people with at least a high school education, the differences in college-educated residents are slight. The per cent of families headed by a female (frequently associated with poverty) is the same in the two cities. 90 The overall distribution Of employment between white collar categories and skilled/unskilled blue collar workers is very similar but, when work setting is considered, differences appear. A much higher pro- portion of the work force in City A is employed in education and in government. In City B a higher proportion is employed in manufacturing enterprises, and there are more large manufacturing enterprises em- ploying over 100 workers than in City A (Consumer's Power Company, 1970). Additional work force differences are indicated in income level comparisons but these are not substantially dissimilar in the two cities. In City B 42.5 per cent of the families have incomes under $10,000 yearly as compared to 41.3 per cent in City A; in City B 25.6 per cent have in- comes of $15,000 or more as compared to 27 per cent in City A. The overall per capita income in the two cities is very similar. Perhaps of importance, the gap between white and black income is greater in City B than in City A. In City A Negro family income is 75 per cent that of white family income and in City B this drops to 69 per cent. Since target groups vary in general popularity (Marcus, 1973) the age composition of the populations in these two cities may be an im- portant factor in differences in the organization of the social services system. In City B there is a larger pr0portion of residents who are elderly and when low income families are considered, in City A a higher per cent are under 18 years of age, while in City B a higher per cent are elderly. To the extent services for children and youth are more generally approved than services for the elderly, these population dif— ferences should be a factor in the development of services such as Scout- ing, local Y's and Boy's Clubs in contrast to senior citizen services. 91 Whether these differences are causally related to the nature of interaction patterns in these two cities is, of course, unknown. From the fragmentary data and annecdotal evidence in the limited human servi- ces literature, they seem to be important considerations. Additional research is required to permit more complete discussion of these factors. Distribution of social service resources Table 2 presents information about services differences which also may affect interaction patterns. When services are grouped into general types, there is a different pattern of services between City A and City B. City A uses 21 per cent of the pool of social service workers to provide mental health services as compared to 10 per cent in City B. Although the number of agencies is similar, the amount of service pro- vided must be different given the allocation of workers. In each city the basic public services (public assistance, social security, health, and employment) are provided and about the same proportion of staff is committed to these services. An important difference between these two cities is the focus on physical rehabilitation. City B has both more agencies and more employees working in this general area, yet it seems unlikely that a significantly larger per cent of the population suffers from physical handicaps or mental retardation in that city. Although the minority population proportion is similar in each city, City A allo- cates a larger proportion of its resources to that broad service area, perhaps reflecting the more heterogeneous minority population in City A. Although a smaller per cent of the population is young in City B, more weight is given to leisure time, character-building organizations whose primary constituency is youth. The focus on substance abuse (alcohol, drugs) is another point of difference. 92 TABLE 2 COMPARISON OF CITIES BY RELATIVE EMPHASIS GIVEN £0 TYPES OF SOCIAL SERVICES, SELECTED CATEGORIES City A Number Number of of em- agencies ployees Mental health 7 262 Physical rehabili— tation 2 45 Substance abuse 1 15 Minority clients 5 146 Character- building, leisure- time, group work 5 116 Basic public services 4 451 Other 9 201 Total 33 1236 Network staff CO t- ment % 21% 12 9 36 16 99% Number of agencies 4 7 35 City B Number of em- ployees 78 93 63 25 126 294 71 750 Network staff commit- ment % 10% 12 985% 8Although City B has only 56 per cent as large a population as City A, the number of employees within the social services organizations studied is 61 per cent of City A. City B has approximately 3.7 social service employees per 1000 population and City A has 3.3 employees per 1000. bNetwork staff commitment is the per whole system employed in each service type. cFigures may not add to 100% in this due to rounding. Spearman rs between cities by number of agencies = .25 cent of employees of and subsequent tables Spearman r by network staff commitment - .36 (significance level p. 05 - .317. 93 On balance, Table 2 shows considerable difference exists between the two cities concerning the relative emphasis given to types of social services. There is a low inter-city correlation by number of agencies providing these general types of services (Spearman rS = .25) and by net? work staff commitments (Spearman rs = .36). In a later section the data show the general mode of work for an organization is an important de- terminant of interorganizational relationships. The different service emphases affect differences in mode of work and are, thus, a factor in interaction patterns at the system level. In addition to different service emphases in the two cities, the number of different services and service units also varies. As Table 3 shows, City A has a larger number of different services and a larger number of service locations than does City B. City B is 56 per cent as large as City A, has 61 per cent as many social service workers, yet offers 82 per cent as many different services in 87 per cent as many service locations. In each city there is some duplication since many services are provided by more than one agency, and in fact, fewer than one-third of local services are given at only one service location in both cities. Although City B provides slightly fewer services, the de— gree of duplication is greater than in City A. To the extent there is competition within systems for domain and clients, then City B agencies experience a greater degree of resource uncertainty. Without information about what level of services exists in local communities (or what is 'normal'), the meaning of these differences is not known. Perhaps the lower interaction level (described later) is tied to this situation about services. Agency staff may be spread thin in an effort to provide the large number of services existing in City B; perhaps this does not matter since the number of potential clients for 94 TABLE 3 PROVISION OF SERVICES City A City B Number of different services provided ,5 67 55 Number of service units8 181 158 Per cent of services offered by only one agency 31% 29% Per cent of services offered by two agencies 21 31 Per cent of services offered by three to four agencies 31 18 Per cent of services offered by five or more agencies _l§ _22 T°tal 99% (67) 100% (65) b Extent of duplication Mean score 2.70 2.87 Standard deviation 1.68 2.16 Coefficient of varia- bility .62 .75 Range 6 8 aService units are the number of times the package of differ- ent services is provided. It is equal to the sum of Service Diversity for each agency. bDuplication reflects the degree of overlap of domains among agencies in each city. 95 each service is smaller. It is impossible to judge from available information. These data are presented to indicate another point of difference in the millieu in which the agencies operate. Organizational Composition of Systems Table 4 shows the percentage of each system accounted for by the major types of agencies and, when Auspices, Mode of Work, and Age are considered, the two systems are fairly similar. In both systems there are more Private agencies than Public, more Distributive agen- cies than Treatment, and more Old agencies than Young. In both cities Public agencies are more likely to be Treatment and Private agencies more likely to be Distributive. More Distributive agencies are Old, but Treatment agencies are approximately evenly divided in terms of Age. However, the more detailed examination of agency types shows considerable variation between cities. If 10 per cent is used as a criterion for significant differences between cities, then there are many such differences (Table 5). In a later section the impact of public auspices is discussed in greater detail. In brief, as the social services sector developed.expensive, widely needed, and basic services were shifted from private to public auspices. Through a series of decisions made over several generations, public dollars are allocated to primary services and private dollars to less important servies, as supplementary funding, or for innovation. IIn addition, some private agencies have influential supporters and/or are important in federated fund-raising and have continued regardless of user need for such services. In general, public agencies offer more important services, have larger staffs, more money, are less affected by local 96 TABLE 4 AGENCY COMPOSITION OF SOCIAL SERVICES SYSTEMS City A ‘Number Per cent Total number of agencies Auspices Public Private Mode of work Treatment Distributive e Old (Pre-l964) Young (Post-1964) Auspices/Mode of work Public-Treatment Private-Treatment Public-Distributive Private-Distributive Age/Mbde of work Old-Treatment Young-Treatment Old-Distributive Young—Distributive Auspices/Neda of work/Age Public-Distributive-Young Public-Distributive-Old Public-Treatment-Young Public-Treatment-Old Private-Distributive-Young Private-Distributive-Old Private-Treatment-Young Private-Treatment-Old 33 l4 l9 14 19 20 women LJ'IL‘CDO‘ L‘N‘ObNO‘LflI—J 100% 42 58 42 58 61 39 24 18 18 39 18 24 42 15 15 18 12 27 12 City B Number Per cent 35 100% 15 43 20 57 15 43 20 57 23 66 12 36 10 29 5 l4 5 14 15 43 8 23 7 20 15 43 5 14 5 14 6 17 4 ll 5 14 10 29 1 3 4 ll CHARACTERISTICS OF TYPES OF AGENCIES Public agencies Per cent treatment Per cent old Per cent large Per cent important Total number Private agencies Per cent treatment Per cent old Per cent large Per cent important Total number Treatment agencies Per cent public Per cent old Per cent large Per cent important Total number Distributive agencies Per cent public Per cent old Per cent large Per cent important Total number Large agencies Per cent public Per cent treatment Per cent old Per cent important Total number Small agencies Per cent public Per cent treatment Per cent old Per cent important Total number 97 TABLE 5 City A % 57 50 79 71 32 68 26 37 57 43 57 79 32 74 42 32 69 50 69 62 18 65 53 41 14 19 14 15 16 17 City B N 67 6O 67 67 25 70 35 40 67 53 47 60 25 75 50 45 59 42 82 65 28 61 50 39 15 20 15 20 17 18 98 level community factors, and are charged with meeting essential needs, e.g., income maintenance, health care, and employment, or expensive needs, e.g., psychiatric help and long-term rehabilitation. Thus, having public auspices differentiates agencies in several ways more fully described later. Inter-city differences in public agencies are important aspects of the general community differences which affect individual agency behavior. In City A, Public agencies are more often Large than in City B; in City B they are more often Treatment-oriented and Old. In both cities, Private agencies are primarily Distributive, Old, Small, and unimportant to others. In both systems Treatment agencies are more important than Distributive ones but the importance is greater in City B than in City A, and in B Distributive agencies are more frequently important than in A. Since size is connected with resource-levels (shown later), the differences between the two cities in terms of characteristics of large and small agencies is important. In City A Large agencies are more likely to be Public, and hence they have two important general clusters of resources. Further, more City A. Public agencies are young than in City B. Young agencies, established under charters intended to stimulate coordination, should seek more inter-agency interactions when work requirements and their overall bargaining position permit, and this factor may affect city inter— action levels. Table 5 shows a considerable degree of similarity between cities about which agencies are unimportant to others. In each case, Pri- vate, Distributive, and Small agencies are less important than Public, Treatment, and Large organizations. Thus, although the 99 examination of single variable types of agencies indicates general similarities across city type, when the several two-variable types of agencies are analyzed, important differences are clear. Unfortunately, because of the limitations imposed by the small number of organizations in each city, these two-variable types cannot be analyzed sufficiently. Under these limits, of particular note is the difference in importance to other organizations of Treatment agencies; e.g., in City A 79 per cent of them are in the top half of all agencies in terms of importance to others as compared to 60 per cent in City B. It seems the nature of the cluster of services and characteristics of agencies in City A some— how translates into a greater system-level dominance of Treatment organi- zations. Table 6 provides more information about which agencies are im- portant within the local network of agencies and group of services in each city. When the top half of agencies on Overall Importance are analyzed, Treatment agencies make up 65 per cent of this group in City A as compared to 50 per cent in City B, and most of the difference is due to the greater importance Private-Treatment agencies have in City A. When size is considered, Large-Treatment agencies are more important than Small-Treatment agencies in each city, but in City A both Large- Public and Small-Private-Treatment agencies are more important than in City A. In City B Distributive agencies are more often important than in City A, and this is particularly evident in the case of Private-Distribu- tive agencies, Small as well as Large. Interestingly, in City B Private- Distributive agencies are a larger part of the top importance group than in City A. A later section provides information about the characteristics of Public-Treatment, Private-Treatment, Public-Distributive, and COMPARISON OF COMPOSITION OF HIGH IMPORTANCE GROUPS, BY TYPESZ Public-Treatment Public-Distributive Private-Treatment Private-Distributive Large—Public Large-Private Small-Public Small-Private Large-Public-Treatment Small-Public-Treatment Large-Private-Treatment Small-Private-Treatment Large-Public-Distributive Small-Public-Distributive Large-Private-Distributive Small-Private-Distributive Old Young 100 TABLE 6 City A. (N=17)‘ Number WOOL») LDI-‘l-‘O‘ 01-4on LOL‘UJN $0 Per cent 41 18 24 18 53 47 City B (N=18) Number .l-‘i-‘NUI Ull-‘wm GNLDN $53000 Per cent 39 17 ll 33 44 17 6 28 28 11 6 6 17 0 ll 22 56 44 8Important agencies are those in the tOp half of number of received choices for all interaction questions, dichotomized Median in City B is much lower than in separately for each city. City A. 101 Private-Distributive agencies connected to the relationships among resource levels, competition, and interaction patterns. Since Overall Importance or Position is a major determinant of interaction level, one reason for the different intensity of interactions between City A and City B (presented later in Table 10) is probably connected to city differences in types of agencies comprising the top importance group as shown in Table 6. Counterpart organizations Since local social service systems are part of the national social services sector, there are inter-city similarities in their agen- cies. Each city has the major state offices and a group of affiliates or chapters of some major private agencies (e.g. American Red Cross, Scouts, Y's, Visiting Nurses, etc.), and about two-thirds of the group of agencies in each city are these Counterpart organizations (N=21). These local outlets do much the same work regardless of the city, and, of course, are the same in terms of Age and Auspices. If units of state and/or Federal agencies, they operate under the same policies and regulations, and some Private agencies are not fully autonomous. These common factors should be connected with similar positions in the separate community networks and perhaps with similar interaction patterns if other factors associated with organizational characteristics (e.g. Size, Diversity, staffing, etc.) are similar. Table 7 describes the positions of these Counterpart organizations in the systems. From this table the importance of these organizations to the systems is clear. They make uP about two-thirds of the cluster of agencies and the employees of these organizations form a very substantial portion of the total pool of Social service workers in each city. Further, they provide a large 102 A TABLE 7 POSITION OF COUNTERPART ORGANIZATIONS IN LOCAL SERVICE SYSTEMS Total number of Counterpart organizations Counterparts as per cent of systems Employees as per cent of total work-force City A City B Number of Public—Counterpart organizations Public-Counterparts as per cent of all Public organizations Employees as per cent of total work-force City A City B Number of Private-Counterpart organizations Private-Counterparts as per cent of all Private organizations Employees as per cent of total work-force City A City B Per cent of all local service units provided by Counterpart organizations City A City B Counterpart organizations as per cent of the top quarter of all organizations in each system in Overall Importance (N=8) Counterpart organizations as per cent of the top half of all organizations in each system in Overall Importance (N-17) 21 62% 68% 74% 72% 25% 28% 70% 65% 75% 47% 103 proportion of all the local service units. Although the group of Public-Counterpart organizations are less than one-half of the group of Public agencies, they are an even smaller proportion of the family of agencies in each city, or about 20 per cent. But, the employees of these Public Counterpart organizations comprise over 40 per cent of the system workers. The Private Counterpart agencies make up 40 per cent of the local agencies in each city, but the number of employees working in such organizations is smaller, or about 25 per cent. When the two cities are compared as to the group of agencies which are highly im- portant in the local systems (i.e. are in top quarter of agencies by number of received choices for all interaction questions), the same six agencies are in the highly important group in each city. When the top half of agencies in Overall Importance are examined, there is somewhat less agreement between cities; the same agencies make up a little less than one-half of the group called Important. Table 8 gives additional evidence of the importance of Counterpart agencies by showing mean score comparisons for Public agen- cies as a group with the Public-Counterpart group and the Private agen— cies group with the Private-Counterpart agencies. As compared to Public agencies as a whole, Public-Counterparts are higher in both Overall Importance and Network interactions. They are more important to the system of organizations and engage in more outgoing behavior within the network than do the group of Public agencies. As compared to the group of Private agencies, Private-Counterparts are more important in City A and slightly less important in City B. ‘In City A, they are more involved in outgoing behavior than the Private group but in City B they are slightly less outgoing. 104 TABLE 8 COMPARISON OF COUNTERPART ORGANIZATIONS WITH ALL ORGANIZATIONS BY IMPORTANCE TO OTHERS AND OUTGOING CHOICES, MEAN SCORES City A Overall Importance Network interactions City B Overall Importance Network interactions All Public 54.5 41.1 36.8 31.9 Public Counter- parts 70.7 46.1 45.3 33.1 All Pri- vate 27.4 37.2 23.2 26.5 Private Counter- parts 32.0 41.2 22.6 20.1 105 The Public-Counterpart organizations are more dominant than the Public. The Private-Counterparts resemble the Private agencies in general and are much less important in both Actor and Target Position: within the whole network than Public-Counterparts. Turning next to the correlation between cities of the characteris- tics of these Counterpart organizations, Table 9 shows the high correla- tions on some organizational variables for the whole Counterpart group, but interesting differences when the effect of Auspices is examined and very important differences in the dependent variable, Network inter- actions. As compared to Private-Counterpart agencies, Public-Counter- parts are similar in Size, Service Diversity, and Overall Importance, with lower correlation for professional staffing. Private-Counterpart organizations are highly similar in Service Diversity and staffing patterns, with a lower but still significant correlation for Size. The major differences in the independent variables appear when the two comr petition variables are compared. The Counterpart agencies show little similarity in Felt Competition level; the inter-city relationship for Actual Competition shows an important negative correlation of -.52 for the Public agencies. The competitive interaction patterns for the Pri- vate-Counterpart agencies are somewhat similar. An indicator of inter- city differences is the high negative correlation between cities in interaction levels of Public-Counterpart agencies. The insignificant positive correlation of .30 for Private-Counterpart agencies again indi- cates the lack of agreement across cities. These data are presented to illustrate an important difference in the overall organizational millieu in the two cities, namely the differences in the competitive behaviors of organizations which are very 106 TABLE 9 CORRELATIONS BETWEEN CITIES BY CHARACTERISTICS OF COUNTERPART ORGANIZATIONS Variables Size Degree professional Service Diversity Overall Importance Actual Competition Felt Competition Interactions All Counter- part’ organi- zations N=21 ,70*** ,53*** ,93*** .69*** .13 .20 .31 Public Counter- part organi- zations N=7 ,39*** .47 ,95*** .89*** -.52* .21 _.7o** Spearman rank order correlation coefficients *Two-tailed test, significance level .10 **Two-tailed test, significance level .05 ***Two-tailed test, significance level .01 Private Counter- part organi- zations N=l4 .48* .71** ,92*** .39 .43 .18 .30 107 similar in each city. Not only are there city-level differences for all organizations in terms of the various independent variables (see Table 11 later), but these Counterpart agencies, identical in Auspices, general charter, Mode of Work, and Age, and very similar in relative position within each system for Size, Service Diversity, and professional staffing are somehow located in social space differently in these two cities. The Private agencies differ in importance to other agen- cies. Both Public and Private agencies differ in interaction levels across the city types. In terms of the causal model for this research it is important to point out the major difference in competition levels echoed by differences in interactions, and this point is discussed further in subsequent sections. In sum, considering the degree to which these Counterpart organi- zations form the majority of organizations within these two systems and the extent their staffs comprise the pool of available social service workers, these data provide additional information about the differing organization mix and overall climates in the two cities. Differences in agency characteristics Continuing this examination, Table 10 shows differences in agency characteristics in the two cities. A much larger proportion of agencies in City B are very small, i.e., have under ten employees. City A has many more organizations with 30 or more employees. Probably city size affects agency size. Smaller cities have fewer welfare dollars and fewer clients. But, although as Table 10 will show later, the mean size of agencies in City A is larger than in City B (37.5 employees as com- pared to 21.4), the difference between these cities does not reach the P .10 level of significance using the t-test. The larger number of very 108 TABLE 10 CHARACTERISTICS OF SOCIAL SERVICE AGENCIES City A City B Number per cent Number per cent Size of staff Under 10 5 15% 13 37% 10 - 19 11 33 6 17 20 - 29 3 9 9 26 30 - 39 5 15 4 11 40 and over ._2 .21 __3 9 Total 33 99% 35 00% Median 25 17 Number of services offered Under 3 2 6% 6 17% 3 - 4 8 24 12 35 5 - 6 13 39 13 37 7 and over lg. .39 _4_ 11 Total 33 99% 35 100% Median 6 5 Degree staff professional Under 20% 3 9% 1 3% 20% - 39% 8 24 8 23 40% - 59% 18 55 16 46 60% and over _4_ .12 _;ga 29 Total , 33 99% 33 101% Median .46 .50 .derall importance (number choices received from other agencies) Under 20 8 l7 , 20 _ 29 6 42% , 9 74% 30 - 39 8 1 4o — 59 6 42 3 11 60 and over _;5 .15 ._§ .lfl Total 33 99% 35 99% Mbdian 35 20 aHigh per cent professional staff is affected by small staff size for 'many City B agencies. 109 small agencies in City B is important because these very small agencies have a different overall profile as compared to those somewhat larger or large. (This is fully described in a later chapter.) In addition, more agencies in City B offer only one or two ser- vices than in City A. Sixty-nine per cent of the agencies in City A are very diverse as compared to 48 per cent in City B. Although the cities differ in terms of professionalization of agency staffs, when the effect of Size on Professionalization is considered, the cities are very similar in this characteristic. System Intggration As Table 10 shows, a much larger number of agencies in City B are fringe members of the system than in City A. In City B 74 per cent of the agencies received fewer than one interaction choice per system member while in City A only 42 per cent were as limited. In addition, twice as many agencies received fewer than 20 choices in City B than in City A. The low choice agencies are social isolates, and their number suggests System B is less integrated than System A. On the other hand, in each city five organizations received about two choices per system member (Table 5) and the top agencies are the 'same' organizations in each city (Table 7). Taken as a whole, this information shows that both cities have social services systems dominated by few organizations,but System A has a group of 14 moderately well integrated agencies, a much larger number than in System B. Table 11 gives additional information about system differences in the distributions of several network position variables and includes data about Actor inter- action pattern differences as well. 110 The data presented in Table 11 provide support for the idea that the two cities differ in system integration. Because an additional question was asked in City B, interaction mean scores should be slightly higher than for City A. Instead, A's scores for Position and Interaction are higher than B's, and t-test scores show significant system level differences. The number of different organizations in agencies' organization- sets does not differ between these cities. Apparently, as interaction increases types of exchanges with customary partners increase rather than a wider web of relationships being established. The differences in Reciprocity scores vividly illustrate this point. Further, Coopera- tiveness, an indicator of planned, committed interactions, is lower in City B. When the cities are compared by the number of organizations in- volved in Resource Exchanges, in City B 37 per cent of the agencies are involved in .5 choices or less per system member as compared to. 15 per cent in City A. Further, 89 per cent of City B organizations re- port one or fewer Resource Exchanges per system member as compared to 58 per cent in City A. Thus, from both vantage points, Actors and Tar- gets, organizations are in much less contact with each other in City B. These findings show different system level interaction patterns exist. There is a small clique of dominants in each city, tightly inte- grated, but a general theme of social isolation for many other members, especially in City B. . Summary Clearly, the social services systems in these communities Egg different. Thus, the setting, the primary environment in which agency 111 TABLE 11 SYSTEM INTEGRATION DIFFERENCES City A City B Variables ’, i S.D. i S.D. t-test Network Position characteriStics Overall Importance 38.9 32.5 29.0 22.4 1.449* Resource Supplier 32.1 29.7 23.5 20.8 1.349* Scope of Importance 13.4 4.1 12.0 3.9 1.414* Interaction character- istics Set-size 11.1 3.5 10.5 3.0 .633 Network interactions 38.8 16.9 28.6 12.7 2.811*** Sector interactions 44.3 18.5 37.3 17.1 1.591* Community interactions 53.2 15.6 49 7 15.5 .921 Variedness 12.0 3.7 13.5 3.3 l.744** Reciprocity 6.4 3.2 3.6 2.2 4.118*** Resource Exchanges 32.1 13.8 23.1 11.3 2.903*** Cooperativeness 11.3 7.7 7.9 6.7 1.943** *p .10 **p .05 ***p . 01 112 behaviors occur, is dissimilar and agency actions probably Egg affected by characteristics of the communities and of the local family of social service agencies. Although in this research demographic differences cannot be causally linked to system variations or agency actions, and system variations cannot be directly tied to agency behaviors, the weight of the evidence reported here, and in other research findings connect- ing community characteristics to policy outputs, gives reason to conclude the general community milieu -- the secondary environment -- is an im- portant determining factor in agency actions and interorganizational relationships. There are three important general factors which relate to this major point. First of all, for reasons not now known, both public and private funds are used differently in these two cities. Some combina- tion of historical circumstances, dissimilar local conditions, probably reflecting varying perspectives and goals of local community leaders, and previous interorganizational linkages has led to variations in service emphases in both public and private sectors. These cities have different local priorities, definitions of needed programs, and valued agency actions and services. The differences in local emphases are shown by the different allocations of personnel (the equivalent of money) without strong indications of unusual needs. One expects a generally similar group of services in local communities in the U. S. unless the population and work-force characteristics are very dis- similar. Indeed, a comparison of available services shows 82 per cent of the services provided in City A are also available to City B resi- dents, although City B is only 56 per cent as large as City A in popula- tion. But, as Table 2 shows, existing manpower resources are used to 113 provide a different overall mix of services. The pool of services, which seems similar at first, particularly since two-thirds of the agen- cies in each community are the 'same' or Counterpart agencies, is actually dissimilar. In both cities there is about the same emphasis on the basic public services and offices of the same major public agencies are system dominants. But, in contrast to City B, City A's system stresses mental health programs and services to minorities, while in City B there is a different allocation of personnel (i.e., funds) and instead, resources go to leisure-time, character building services andprograms for the physically disabled. Is it reasonable to think there really is three times the need for physical rehabilitation personnel in City B than in City A? Are residents of City A somehow much more prone to mental ill- ness? Probably not. A second general factor is the make up of the community set of agencies. Although cities have many of the same agencies, and the systems have similar prOportions of organizations with Public-Private Auspices and Treatment-Distributive Modes of Work, there are variations associated with agency type and characteristics of the Counterpart organi- zations which reflect differences in the inter-agency context in which these Actor organizations operate. The differences within types illu- strate different system characteristics. As examples of this, more Treatment agencies are under public auspices in City B than in City A; Treatment agencies as a group are more likely to be important to the other system members in City A than in City B; Large agencies are more often Old in City B than in City A (Table 5). Further, when High— Importance organizations are compared by type characteristics in City A, Private-Treatment agencies are a more important part of this group, but 114 in City B Private-Distributive agencies are more significant (Table 6). In general, Treatment organizations seem to provide valued resources to other agencies in City A; in City B the Distributive organizations are more important. Probably this difference stems from the dissimilar service priorities in the-two cities, and later chapters discuss this. The Counterpart organizations form a major part of the family of social agencies in each city. Differences in this important part of the systems point to basic system variations. The Counterpart organi- zations are of primary importance in each city. Two-thirds of the members of each system are these equivalent organizations. The Counter- part group has over two-thirds the worker resources and is assigned responsibility for about two-thirds of all the service units. Sig- nificantly, they make up 75 per cent of the t0p quarter of agencies in terms of Overall Importance and these very important organizations in each city are the Public-Counterparts (Table 7). These agencies are, of course, the same in AuSpices, Mode of work, and Age. As the data in Table 9 demonstrate, the inter-city correlations of characteristics of these agencies show many areas of similarity, e.g. in size of staff, service diversity, staffing patterns. As mentioned, the network position of Public-Counterpart agencies is highly similar in each city, but the position of the Private-Counterparts is not the same. The major differ- ences are the level of Actual Competition and interaction levels. Such differences between system dominants affects the general interaction levels in each city and should be an important factor in the possible agency interaction patterns because interaction requires both needs and resources from the participants. 115 Third, the systems have different characteristics. City B has a larger proportion of very small member organizations and many ' are non-diverse. Further, members are less well integrated within the system in City B. A greater number are very low in importance as interaction Targets (Table 10) and in outgoing relationships or Actor behavior (Table 11). Although a greater proportion of members are relatively isolated in City B, in both cities the Large—Public organi- zations are well integrated. The contrast between cities in degree of system integration is great. This report does not try to include other types of data which may also be connected to system integration, e.g., perceived barriers to coordination, ideas of overall profita- bility of interaction, internal conflict, demands of funding organi- zations, willingness of top staff to innovate, etc. Here the emphasis is on organization structure characteristics (i.e. professionaliza- tion, diversity, and type of work) as these relate to two measures of system integration, Actor behavior and organization position (Target status). These general differences at the system and community level have been described because they relate to the apparent differences in general interaction patterns between these two cities. These differences should be considered as background data when organizational characteristics and behavior are examined in the following chapters. 116 CHAPTER IV ORGANIZATIONAL CHARACTERISTICS IN TWO SYSTEMS Introduction Chapter III discussed some significant similarities and differ- ences in the two social serVices systems because the environment for agency actions is presumed to affect agency behavior. In this chapter the focus is the organizations that make up the two systems. Chapter V describes interaction patterns and the relationships among organizational characteristics and agency behaviors within these two different systems. This chapter describes interrelationships among the independent variables. There are four sections. The first compares the two systems by resources and competition levels and shows the distribution of inde— pendent variables by several charter—domain organization types. A detailed discussion of these characteristics is needed to understand the effects of interactions among variables on organizational interaction patterns. The second section describes the relationships among the vari- ous independent variables and includes an examination of the relation- ships among the various resources and competition measures for different organization types. The third section examines importance in the systems, or power, and section four tests the specific hypotheses which relate to the independent variables. Throughout, analysis is restricted by the nature of social services systems. As Table 4 illustrated, in local communities the group of social agencies form a highly differentiated system, and there are few cases of any particular type of agency. Yet, the combination of charter-domain characteristics, coupled with resource and competition factors seem highly important determinants of agency interaction patterns. As an 117 example, Young-Public-Treatment organizations occupy a different general position or niche in the overall system than do Old-Private-Distributive organizations. Their impetus for transactions differ and so does their ability to attract interaction partners. Further, competition varies by type. The general model predicts interaction results from an impetus to interact stemming from work-related needs and competition for re- sources, and further specifies ability (i.e. system valued resources) to attract trading partners is required. Therefore, the cluster of factors associated with various organization types needs to be examined, but the joint effects of the various charter-domain variables are difficult to examine because the number of cases is small. To manage under these limitations, the following approach is used: first, the systems are compared to each other using all the members; second, the relationship between either Mode of Work or Auspices and various other organizational characteristics is described; and finally, as possible and/or desirable, distributions of variables and interrelationships by two-variable organi- zation types are provided (e.g. Auspices/Mode of Work, Age/Auspices, etc.). Two general themes link the various portions of this material: (1) the relationships among the various ability measures (resources) and agency type; and (2) variations in competition level by type of organization. Comparison of the two systems Chapter III detailed important differences in the two cities' social services systems. However, the distribution of types of agencies within the systems is roughly similar. When the relative network posi- tions of the group of Counterpart organizations is considered, then there are high inter-city correlations for the system positions of these agencies for the various resource measures (Table 9). The major 118 positional differences for Counterpart agencies are in Competitiveness and Interaction levels. As noted, when the systems are compared, there are significant differences in degree of system integration (Table 9). Table 12 gives the distributions of the independent variables in each system. Although the Counterpart organizations are similar, when all system members are considered, there are important differences be- tween the cities. Agencies in System A are more diversified,but those in System B are more highly professionalized.l Although directors in each city report about the same perceptions of competition, Actual Compe- tition is higher in System A than in System B. Network position measures (repeated from Table 11) are indicators of valued resources (see Chapter I), and it is clear resource transactions are greater in both number and variety in System A than in System B. Of particular interest is the greater variety of exchange transactions reported for System A (Scope of Importance measure).. Organizations in A are larger than in B even though the t-test score fails to indicate significant differences due to the extreme. variances in size within the systems in each city. In fact, the high standard deviations for Size provide additional evidence of the highly differentiated nature of these two systems. Table 10 gave size differ- ences. The median size in A is 25 employees, and in B the median is 17. In A 27 per cent of the agencies have 40 or more employees while in B this drops to nine per cent. More importantly, in B 72 per cent of the belowethefmedian agencies have fewer than ten employees as compared to _g lThis is probably related to the large number of very small agencies in Citv B. This point is discussed furrhar hp1nw, 119 H>wfim Hm UHmHWHwCHHOZ om <>WH>wfiwm. aw mflmamz mwmnma > mwmnma w nzuwwv AZmeV oncmH noswmnwnwon o.m b.m m.m u.» mmHn oosomnwnwos N.»H .ow ~.¢m .mu Zonzonw womenwos onncmH nwmm men noammnwneos Zontonw womunwoa owrm Hm oozw>WHmoz ow OWO>ZHN>HHOZm w< 306m ow Soww. mMmHmZ > HHmmnamSn dumnHHUandm onmmawumneonm onmmownmnHOSm Azquv AZnHmV m m.o. m m.u. nunmmn bH.Ho mw.Ho uu.oa Mm.mb z.m. m.mm N.mo m.>u H.mo z.m. .wm .Hm .w» .HH u.oum»»» m.~H b.mb u.mu u.mu H.Hm¢ N.No .mb ~.¢o .uo H.me» wa.om um.mm bN.wH Hm.wo z.m. o.oo b.0m u.ou w.mm H.uwow wo.om ww.o~ wb.um Hu.mo z.m. HN.~H >.uu Hm.ow N.~m N.~mmx» 126 oncmH nwmm mmHn noawmnenwo: ZmnSOHw womHnHos owrm Ho nozw>meoz om OWQ>ZHN>HHOZm ma 206m om zoww. mwmamz w anmmnamsn cwmnnHUCnH.oo H.m> Hemuwxx .um .Hm .bw .Hm u.mmm»»» o.uu w.mu b.ww ~.¢m H.uuo»» ~.uo .uo ~.Nm .oo H.mbo» wo.uu Hm.»> ~u.um Nb.m~ z.m. u.uu w.>o m.»o w.mm z.m. Mm.oo Ha.om -.wm Nu.u~ z.m. Hw.mw w.h~ Ho.mo w.mu ~.Hom»» H>mfim Hu HZHNWIOHH& Uwamwmzomm Hz HZUmmeUmza <>WH>mem mow me>HZmza owO>ZHN>HHOZm 127 mwmnma > mwmnms w AZquv AanmV 54538 M m .e. m me. Tammi” onmmowumnwoomp osmnmnnmnwmnhnm mwum A >H.Ho uw.Ho Hw.oo m.Hm H.~Hm»» mmdnncmH nwmm m.~p b.mb m.uw w.mu z.m. men nosmmnwneo: N.~o .ob ~.uo .um H.mHm» Zonzouw womHnHoo onncmH nwmm men oosvmanwon ZmnSOHw womenwo: owbm Hull nonnuscmm HZHMWIOHH4 UHmmmwmzomm Hz qumwmzumza <>WH>wfimm wow UHmHWHwCHHzHN>HHOZm mwmnma > mwmnma w 9&3 9&8 m we. N. me. 733” u~.me Nm.m> mm.mo ww-Nm z.m. w.bw H.mo b.oo H.m» .ooo .m» .HH .bw .Hu N.u~u»»» u.mu u.mw b.um N.mm ~.uou*w» PE. .3 Pmo .oo Tum? bN.uH Hm.oo Nu.um Nb.m~ N.owu»w u.ow w.mm m.ao w.mo ~.ooo»» wa.uo Hu.mo NN.wm ~w.u~ H.me»» Hm.ow N.~m Ho.mo u.mw b.Hum»*» 129 Another specific resource, professionalized staff, again has an unexpected distribution, but this may be due to differences in agency size (noted in Chapter II). In System A, unlike what would be expected from the nature of the work, Treatment organizations have a smaller proportion of staff with professional standing than do Distributive agencies, while in System B the pattern is as expected and the Pro- fessional Ratio is higher for Treatment agencies than for Distributive ones. In Table 17 inter-city differences by Mode of Work for professional staff resources are tested, and the differences are large for each type of organization. Treatment agencies in System B are more professional but also much smaller. When the Distributive organizations are compared, then System A has a higher Professional Ratio, although the differences in Size are not significant. One conclusion drawn from these data is that Distributive organizations in System A do have more professional staff capacity than in System B and hence more ability to commit the agency to cooperative exchanges.4 For Treatment organizations the data are more difficult to understand. It is hard to know how much of the high Professional Ratio is due to Size and how much to real staffing differ- ences. Treatment agencies in City B probably have staff-related re- sources which tend to cancel each other out. There are more professionals per agency per number of employees, but the agencies are much smaller. If professionals do play both direct—service and boundary-spanning roles for organizations, then a high professional component handicapped by small size is not as useful for developing extensive interactions as it is for organizations with more employees to assume interaction roles. 4Data presented in Chapter V show this is the case. 130 To further complicate things, the third specific resource, Service Diversity, also varies by Mode of Work in the two systems. Given some stimulus (e.g., resources, service popularity, and client demand), Distributive organizations can more easily diversify than can Treatment agencies because of the relative ease with which a Distributive organization can provide different programs or the same programs to a varying client population (both aspects of Service Diversity). Of course this is not true for programs that distribute money), but most Distribu- tive agencies do not perform this function because that is limited to only a few very large major public organizations, (e.g. Social Security, Department of Welfare). Treatment services are more complex. Providing different services or similar services to varying clients requires specially trained staff and, because of the nature of the work, agency personnel costs will be higher for Treatment services. In City B, Distributive agencies are more diverse than Treatment ones. In System A the two different types of agencies are similar in diversity. Further it is clear that the entire system is generally less diverse in City B (Tables 3, 10, and 12) and the least diverse group of all is the System B Treatment type. Note these are primarily small organizations, and they are significantly smaller in B than in A. Because of the interaction between type of work and Service Diversity which is described in the next section, the differences by system are important and may be one factor which helps explain the system-level differences in interactions patterns. Both Overall Importance and Scope of Importance are measures of valued resources. Because of the mix of programs and services offered by these two types of organizations, the type of work is not an 131 indicator of its importance to others, or of system position. Some Distributive organizations provide very needed services including health assistance, emergency services, financial aid, day care, etc., while others provide what might be considered fringe services such as group and leisure time activities and recreational facilities. Clients of Treat- ment organizations may require a variety of additional services and the clinical model under which such agencies work implies tailoring services to particular combinations of needs. If Treatment organizations do not provide the required services themselves, they may then refer clients to specialized agencies. Further, depending upon the services provided and characteristics of their client population, Distributive agencies may also be involved in referrals to both Distributive and Treatment organizations. Rather than stemming from work type, system position (Overall Importance) is tied to the value to other organizations of the resources the organization has -- to the primacy of its services, the variety of services, and capacities. Mode of Wbrk is not an indicator of system position; instead a combination of independent variables including specific resources and type of work, coupled with system requirements, are determinants of network position and agency power in the system. This is described further in the next section. To survey the characteristics of different types of organizations, Table 15, 16, and 17 show that when types of organizations are compared within cities, A's Distributive organizations generally have more valued resources. They receive interactions for a greater variety of items than do Treatment agencies, and their Overall Importance scores are higher but, because of the variance within the category, the difference does not reach 132 minimum significance levels. B's Treatment organizations are generally more valued by system members than are Distributive ones. They have higher Scope scores and are somewhat higher in Overall Importance. Table 17 compares the two systems and shows the greater difference be- tween systems for Distributive organizations. The much higher Scope score for System A is especially noteworthy. All of this material provides additional evidence that the combination of services offered in the system is an important aspect of the exchange relationships which develop. The Network Position measures are indicators of ability to interact, located outside the organization in the community and the network of social service organizations but also related to internal characteristics and resources of the organizations. Both measures of competition also follow this same general pattern. In System A, Distributive agencies name more organizations as involved with them in competitive relationships and their directors report a higher feeling of competition. For System B, Treatment agencies are higher in both measures than Distributive organizations. From Table 17 one sees that directors of organizations of the same broad type do not perceive their organizations as experiencing the same levels of competition.5 For Directors of Treatment organizations those in City B report a higher level of Felt Competition and,in the case of Dis- tributive agencies, those in City A are higher. This is further indi- cation of differences within the networks in the two cities. Tables 15, 16, and 17 show a fairly consistent pattern within the systems-of the distribution of variables by types of organizations. 5The differences for Counterpart organizations shown in Table 9 mean directors of very similar organizations report dissimilar per- ceptions. 133 Of interest, though, are the differences by type of work between these two cities. Unlike City B, in City A Distributive agencies are more valued by system members than are Treatment agencies for both general resources measures (Importance and Scope). They are also higher in competition levels and, with their higher professionalization, have greater staffing capacity. For other specific resource measures there is no difference by type in System A. In System B the type valued is Treatment organizations, a group that has a much higher Scope of Im— portance score although only slightly higher Overall Importance score. Again, the valued type is higher in competition and staffing capacity but, unlike System A, the valued organizations are not larger or more diverse. When inter~city comparisons by type of work are made, Treatment organizations are larger and more diverse in System A than System B, but are lower in Degree professionalized and Felt Competition. In- terestingly, although Treatment agencies are smaller in City B than City A they are involved in somewhat more diverse interaction re- lationships (see Scope scores) and the number of nominations reCeived is not smaller although Service Diversity is less. One explanation may be the greater professional staffing capacity which seems to re— flect a real difference even when the effects on this measure of very small size are considered. Looking at Distributive organizations across city-type, City A Distributive agencies consistently have greater resources than do City B's. They are somewhat larger and more diverse, have much higher level of professionalization, and more general re- sources. Unlike Treatment organizations, in City A Distributive organi- zations report higher Felt Competition and more competitive ties. 134 One interpretation of this material is that it indicates differences in the requirements of the entire network of organizations coupled with resource allocations which differ in the systems by type of work of the organization. Comparisons by Auspices and Age The relationships of Sponsorship and age with the general work climate of social service agencies and variations in the nature of competition for organizations which have different types of sponsor- ship is important because these factors affect interactions among system members. This section is a comparison of the two systems in terms of resource and competition levels associated with sponsorship and age differences. Beginning with the relationship between Auspices and importance to system members, Table 18 compares High and Low Importance agencies in each city. Sixty per cent of the High Importance organizations have Public sponsorship, and the Low Importance agencies are primarily Pri- vate. Further, Public-Treatment agencies make up over 40 per cent of the High Importance group, and almost 50 per cent of the Low Im— portance group are Private-Distributive agencies. Mere information is in Tables 19 and 20. In both systems the Public organizations, regardless of type of work or age, are much higher in Overall Importance and Scope scores, measures of general resources. The differences in Resource Supplier scores shows a much greater number of system linkages are toward Public organizations rather than to Pri- vate organizations. Public agencies are not significantly higher than Private agencies in Competitor scores but they do dominate the systems as sources of many resources. 135 TABLE 18 GENERAL RESOURCES AND ORGANIZATION TYPES System A System B High Overall Importance Public % Z Young, Distributive -- -- Young, Treatment 31 22 Old, Distributive 19 17 Old, Treatment 12 17 Private Young, Distributive 12 22 Young, Treatment -- -- 01d, Distributive 6 11 Old, Treatment '19 _‘ll 99% 100% Total (16) (18) Low Overall Importance Public Young, Distributive 6 -- Young, Treatment 6 12 Old, Distributive 12 12 Old, Treatment -- 6 Private Young, Distributive 12 6 Young, Treatment 12 6 Old, Distributive 47 47 Old, Treatment __Q _;g 101% 101% Total (17) (17) 136 OncmH nemm wmwn coaumnwnwos Zonsosw womunwos owfim Ho oozw>meoz ow wdwfiHa >26 wwH<>Hm own>zHN>HHOZm. mMmHmZ > wccHHn .wHHm.mo wu.wm ~H.b~ H>.uw N.Nu~»» Hm.ou ~.om H~.~H b.mo N.Houw* H>wrm No nozw>meoz om wdern >26 wwH<>Hm owb>zHN>HHOZm. meHmz w 137 wcwwwn wnw.~u H.uu b.oo H.m~ z.m. ummnmm vnommmmwosmH .uo .HH .bm .Hu H.mmew nosbmnwnwoo bnncmw neon m.No p.Ho a.mm N.mm qomo MmHn nosfimnunuos ~.w~ .mu N.mm .mm .uou zmnzonw womwnwos Odmnmpw stonnmbnm wm.mo N¢.¢o Nu.wo H¢.No H.woo*» nosvmnwnon u.ou w.uo m.bm w.um z.m. wmmocunm mcmvuwmn uH.Hw Nb.ow Hu.uw Hb.u~ Hsumuss moons omHsfltnnmsom Hu.mo u.mm Ho.um w.uH H.mou*» so .Ho ssv .om wise .OH 138 In both systems Public agencies are larger than Private agencies, and in System A Public agencies are also more diverse, but there is no difference by sponsorship in staffing patterns. In System B Public organizations have more professionalized staffs but are not more diverse. These data confirm earlier statements that Public agencies as a group have more resources than Private agencies even when variations in work and age factors are considered. In both systems Public organizations report more competitive ties with other organizations and, as expected, directors of Private agencies report higher levels of Felt Competition than do directors of Public agencies, although this difference is less in System B. This is probably because competition is much more localized and specific for Private agencies than Public. The comparison of organizations with the same sponsorship across systems, shown in Table 21, indicates again the highly differentiated nature of the social services systems in these communities. Public agencies in both communities vary widely in Size and the various Network Position measures. In System B, Public organizations have more pro; fessional staff resources, but in System A they have higher Service Diversity scores, and this is tied to differences in Mode of Work described earlier. Public organizations are very similar in competition measures in the two systems. Private agencies seem to occupy similar system niches in the two cities and to possess very similar resources and competition levels. Reflecting the generally higher rate of exchange in System A, Private agencies have slightly higher Resource Supplier and Scope of Importance scores . 139 onsmH nHmm mmHn noavmnwnwos zmnzonw womwnwos owbm NH HZHMWIOHH< UwaWWMZOMm Hz HZUmwmzumza <>wH>wEMm mow wdwfiHn OWQPZHN>HHOZm_ mwmnos > m%mnma w Azure Queue M m.d. m m.U. nlnmmn mp.ob mo.~w uH.mo ww.m~ H.~»~ o.uo N.w> b.~u H.uu N.»u~»* .pa .Hw .mb .HH ~.HNm»» u.wm a.- m.~o b.Ho .omb ~.Ho .uo N.w~ .mu .mHu mb.mo mo.mm u¢.mo ~a.mo H.~wm V.NH b.uH w.ou w.wo H.N¢m pm.mo wu.o~ uH.Hw Nb.mw H.~um Hm.0u N.m¢ Hw.mo w.mo H.Nwo 140 nncmH nHmm flown noawmnwnwo: 2mn€onw momHnHos owbm NH 1 oosnwocma HZHNWIOHHK Uwamwwzomm Hz HdemeUmza <>wH>wfimm wow wNH<>Hm own>zHN>HH02m mwmnma > mwmnma w AzuHov AanoV m we. m we. Ho.u© Ho.om Hu.om o.om she “Two Foo Lia» .5 .Ho .bm .Hu mbu ~72. atom Moo N.ab .om N.mm .mm Nu.wu Ho.ow Nw.No H¢.Nm 9“; uLm Pom P; NH.bN H».ww Hu.wm Hb.w~ HN.NH k.oo Ho.um w.uH 141 To summarize, within the two systems Public agencies are generally more important to system members than Private agencies. This lends support to the earlier discussion about the impact of sponsorship upon social service agencies. Further, although the systems differ markedly when Mode of Work types are considered, there are few differences in system positions and resource allocations which are directly tied gnly_ or consistently to Auspices. Yet, because Auspices is associated with resources (and resources with ability to interact) it is an important consideration and is expected to affect interaction patterns. Age is another important factor for social service agencies be- cause of service shifts begun in the mid-1960's period. Table 22 gives information about resources and competition by Age. If agencies do suffer the liability of newness described by Stinchcombe, then one expects lower levels of resources for younger agencies regardless of other considerations. In System A, when only Age is considered, Young organizations are not particularly different from Old agencies in re- source levels. Although older agencies have a larger average size than younger agencies, for both groups there are wide differences. 1 Older agencies are somewhat more diverse which is as expected. There is little difference in generally valued resources by Age. In contrast, in System B Age is connected to resources; older agencies are larger and somewhat more diverse. In addition, older agencies have much higher Overall Importance scores than do younger ones, but Young organizations are involved in a greater variety of interactions, unlike the situation in System A. 142 mwmnma > oncmH nwmm men nosvmnwnwos Zmneonw womunwos onncmH nHmm men nosmmnwnwos Zmnzonw womenwon owfim NN wmmochm >26 oozwmaHHHoz fimnm &o:dm GHQ onmmswsmnwoom onmmswumnwosm Azuwwv Aanov m we. m we. mo.w wH.m bw.u mH.w >.o m.» b.@ ~.w .bm .Hb .bb .Ho b.m b.~ m.¢ u.m ~.uu ~.o N.mm .cw uu.o Nw.o bH.o wu.m Hw.m b.o Hu.m w.m AZHHNV Azumwv HH.N o.m Nm.m wo.m b.o H.“ b.u H.u .mH .Hu .bm .Hm b.u >.u b.o N.w ~.ob .mb ~.Hm .wu wH.~ Ho.o on.m mm.o Hw.H 5.0 Hp.» w.m Hlnmmn as». 143 When competition is reviewed, Young agencies in System A are less involved in competitive exchanges than Old agencies but this is not the case in System B. In A there is virtually no difference in level of Felt Competition by Age, but in B, Directors of younger organizations report a much higher level.0f Felt Competition. In summary, when AuSpices and Age are considered separately, it appears that, in general, Public agencies are more important to the system as a whole and that Auspices is a clue to resources. When the Age factor is considered, about half of the Young organizations in both systems are Public. Although younger and older agencies have differences to a significant extent, these seem to be due to both Auspices and Age. Interaction of charter-domain factors To handle the interactions between the charter and domain vari- ables within the limits imposed by the small number of cases in each system, several tables are presented which give mean scores (Tables 23 and 24). Although there may be wide variances within organization types due to the differentiated nature of these systems, the means are given to indicate general patterns in these data and several correla- tion-based tables included later give additional information. As Table 23 shows, when Age is held constant, the influence of Auspices on resource levels and competition is clearer. In both systems, Public agencies are consistently higher than Private agencies in level of system valued or general resources (i.e., Overall Im- portance and Scope of Importance). Further, in System A Old-Public agencies have generally higher resource levels than the other three types. They are larger, more diverse, and higher in Overall Importance. The Old-Private agencies are larger, more diverse, and more 144 TABLE 23 RESOURCES AND COMPETITION, BY AGE AND AUSPICES, MEAN SCORES System A General resources Overall Impor- tance Scope of Impor— tance Specific resources Size Service Diversity Degree professional Competition Actual ties Felt Competition System B General resources Overall Impor- tance Scope of Impor- tance Specific resources Size Service Diversity Degree professional Competition Actual ties Felt Competition Young agencies Public (N=7) 43.6 14.8 LIIN L‘NH MG (AM u (N=6) Private (N=6) 29. 11. (N=6) 29.2 11.3 (94> MN #0 I-‘N U1CD «L‘NCD Old agencies Public (N=7) 65.3 15.3 bUJkO Hm HO (N=9) 38.7 Private (N=l3) (N=l4) 20.6 10.5 «L‘U! LBJ-\N NLfl we: 145 professionalized than the Young-Private agencies and, although Young— Private agencies in System A are somewhat more important to other system members than in System B, there is no real difference for Scope scores. Looking at System B, regardless of Age, Public agen- cies are larger than Private agencies, and have more generally valued resources as well, but Young-Private agencies are higher in professional staff than Old-Public organizations. When comparing organizations of similar sponsorship but different ages, in both cities the older Public organizations are larger, more diverse, and higher in Overall Importance than younger Public agencies. The pattern for Private agencies is less consistent. Although in both cities older Private agencies are larger, the older Private agencies do not seem to have more resources than the younger Private group. This is probably due to the nature of the mix of services older agencies provide. For the most part, Old-Public agencies are the basic service suppliers while Old—Private agencies are traditional agencies such as Scouts, Y's, American Red Cross, etc. with a heavily middle class_ clientele. Young-Public agencies are more specialized in services and directed toward innovative programs meeting complex needs, while the Young-Private agencies serve minority group members and have specialized clientele, but do not offer specialized services. Such differences in agency function are related to differences in the two competition measures (Table 23). Looking first at System A, the marked difference in Actual Competition scores for Young—Public and Young-Private organizations is noteworthy. Both types of older agencies have very high levels of Actual Competition. The responses of agency directors in System A are interesting, also. Two groups of 146 directors (Young—Private and Old-Public) feel their agencies experi- ence low competition althOugh they report a high level of existing competitive interactions. Old-Public organizations are relatively free from perceived competitive pressures indicating the high stability of their environments described in Chapter I. Young-Public agencies are less secure and constantly threatened by new legislation or budget cut- backs at the Federal level. The Old-Private agencies are members of the local United Way organization and have shared a common pool of money for many years. This is clearly related to the high Felt Com— petition levels these directors report, and shown in System B as well. In City A, Young-Private agencies are organizations which serve minority people (N=2), and children needing unique service (N=2), or provide education and information about specialized problems (N=2). When sys- tem members and functions are analyzed,6 it is clear the Young-Private agencies in City A do not have competitors offering the same services and have very secure domains. In City B, the agencies reporting the largest number of competi- tive ties are Young-Public organizations and, interestingly, this group has the highest scores of the four groups in the two systems. This may be because more Component agencies are included in City B than City A (see Chapter II). Members of the younger Public group are the most vulnerable to shifts in public funding. Differences in competition scores seem related to the different collection of functions served by the two types of Young organizations in each city. Although in System A 6Respondent organizations were guaranteed confidentiality and promised that reports would not identify individuals, groups, or organi- zations. Thus, identifying details are not included. 147 the Young-Private agencies seem to have secure domains, in System B these organizations primarily serve disadvantaged groups, e.g., minority people (N=l), the poor (N=3), the old (N=1); only one of six cases serves children needing unique service, a marked contrast to City A. In City B, all the Young-Public group members are Treatment agencies serving multiple problem clients needing relatively complex and intensive care (e.g., substance abuse problems, crisis intervention, and mental illness). The Young-Public group is similar in City A but additionally includes Distributive organizations working with disadvantaged clients. The weight of the information presented about Age and Auspices shows the highly differentiated nature of these systems but generally supports the notion that both Age and Auspices are important indicators of ability to attract interactions. In each system the agencies with highest resources have Public sponsorship, not Private. Young agencies may be limited by lack of resources but they also are heavily influenced to seek interactions by their type of work. Table 24 presents information by Age and Mode of Work. Again, there is a mixed picture, and the data generally echo the findings pre- sented earlier for Mode of Wbrk alone. Young and Old Treatment agencies are not very different from each other in City A except the older agen- cies have much higher professionalization scores, and the younger Treatment agencies are involved in a greater variety of interactions. For both types of Treatment agencies, there are high competitive inter- action scores. Differences are more apparent when Distributive agencies are compared. Old-Distributive agencies are much larger (because they are Public), more diverse, and generally more important to other system members than Young-Distributive agencies. The older Distributive 148 TABLE 24: RESOURCES AND COMPETITION BY AGE AND MODE OF WORK, MEAN SCORES City A General resources Overall Impor- tance Scope of Importance Specific resources Size Service Diversity Degree professional Competition Actual ties Felt Competition City B General resources Overall Impor- tance Scope of Importance Specific resources Size Service Diversity Degree professional Competition Actual ties Felt Competition Young agencies Old agencies Treatment Distributive Treatment Distributive (N=8) (N=5) 27.4 (N=6) 41.7 14.3 O‘UDN Nko O‘UI H (N=8) 29.2 12.9 4-‘(13 UIGJO NU! Ntfi (N=l4) 39.0 13.0 O‘H DON-L‘ NU! (N=15) 25.5 WWW 8 2.14 149 agencies report higher competitive interactions than Young-Distributive but scores are lower than for Treatment agencies. Young-Distributive agency directors have very low Felt Competition scores. In City B, Treatment agencies do not vary much by Age, although Old-Treatment agencies are more diverse and Young-Treatment agencies involved in more types of interactions. As compared to Old-Distributive agencies, Young-Distributive organizations are smaller, more diverse, and high in Scope and Overall Importance scores. Young-Distributive agencies are markedly lower in Actual Competition than are Old-Distribu- tive ones, although slightly higher in Felt Competition. Unlike System B Young-Distributive organizations, in System A these directors report high Felt Competition scores. A final series of two variable charter—domain tables gives the differences by Auspices and Mode of Work as these seem from the preceding data to be the critical variables. Tables 25 and 26 show resource levels for these four categories, including t-test figures. It is useful to imagine there is some 'normal' amount of interaction based on work of .the agency, not stimulated by resources or by competition-based pressures. When resources (i.e. ability) are added to this 'normal' interaction level, then the measured interaction level should increase, and Tables 25 and 26 test this idea using Target interactions. In System A the pattern is clearly as expected for Treatment agencies (Table 25). Public-Treatment organizations have significantly more specific resources than do Private-Treatment agencies, they are involved in more interactions as Resource Suppliers, and the range of interactions is broader. For System A Distributive agencies the pattern is similar but not quite as vivid. Public-Distributive agencies are larger and TABLE 25 150 DISTRIBUTION OF VARIABLES BY AUSPICES AND MODE OF WORK, SYSTEM A Variables Organizational characteristics Size Service Diversity Degree professional Competition Actual ties Felt Competition Network position Overall Importance Competitor Resource Supplier Scope of Importance Variables Organizational characteristics Size Service Diversity Degree professional Competition Actual ties Felt Competition Network position Overall Importance Competitor Resource Supplier Scope of Importance *p .10 **p .05 Public- Treatment (N=8) i S.D. 45.0 34.9 6.2 1.2 .50 .14 7.9 4.3 2.23 74 50.1 23.2 8.8 4.8 41.4 20.7 16.0 2.0 -Public- Distributive ' (Ns6) i S.D. 83.8 78.3 6.8 4.4 .36 .09 6.7 4.8 1.63 70 60.2 62.2 6.5 5.1 53.3 57.6 13.8 3.4 Private- Treatment (N=6) i S.D. 16.2 7.3 4.3 1.6 .59 .07 7.2 3.8 3.01 .64 32.7 12.5 6.8 2.7 26.0 10.2 13.8 2.3 Private- Distributive (N=13) i S.D. 21 O 24.2 5.0 1.8 .34 .19 6.0 5 2.36 98 24.9 19.2 5.5 4.0 19.3 16.3 11.5 5.4 t-test 2 2 1 N 1 l l 1 .259** .406* .S. .950** .675* .909 .702* .719* t-test NZ ratazzrd .769** .882 .154** .247 .298 .065 151 TABLE 26 DISTRIBUTION OF VARIABLES BY AUSPICES AND MODE OF WORK, SYSTEM B Variables Organizational characteristics Size Service Diversity Degree professional Competition Actual ties Felt Competition Network position Overall Importance Competitor Resource Supplier Scope of Importance Variables Organizational characteristics Size Service Diversity Degree professional Competition Actual ties Felt Competition Network position Overall Importance Competitor Resource Supplier Scope of Importance **p .05 Public- Treatment (N=10) NI S.D. meow NV DOD-1N him) on b-UIO\P‘ hJ\J u>a>e~c> U1U1 \1 P‘ #4 NJO\UJ\J P‘hJ aaoaoxu: u>na a) Public- Distributive (N=5) >0 S.D. 41 12 3.6 2.1 1.57 57 46.0 40.9 7.8 12.1 41.8 38.7 12.2 5.2 Private- Treatment (N=5) x: U: :5 Private- Distributive (N=15) NI S.D. bu} £‘\o&fl N H ox . NJ> b0 0 \O .L.\ P‘P‘ n: C>U1U1hi UJ\JGJGD t-test 2:2:2 0:030) .846 N.S. .980 N.S. 1.286 t-test .909 2.051** 1.158 N.S. 1.325 .706 152 somewhat more diverse; interaction levels as Target organizations are higher but with high variances.7 Table 26 gives this same information for City B. but the material is not as straightforward. For Treatment agencies Auspices is largely unrelated to resources or interactions, although somewhat important for Scope. For Distributive agencies sponsorship is a factor.and as in System A, Public-Distributive agencies are larger and higher in Overall Importance and Resource Exchanges, but again there are large variances within type. In System A Private—Treatment and Private-Distributive organi- zations have significantly higher Felt Competition scores than those agencies with Public sponsorship. In System B Private-Distributive agencies also follow this predicted pattern but there is no difference for Private-Treatment and Public-Treatment organizations. Taken as a whole, these data show important differences in organizational positions in each system according to variations in type of work, sponsorship, and organizational age. Further, the systems are different in important respects. The cluster of agencies and ser- vices is associated with different positions and characteristics for similar charter-domain types of agencies. Considering the weight of the evidence, clearly system-level differences affect how resources are allocated. One cannot conclude that organizations that appear similar in charter-domain characteristics, and even have similar specific re- sources, will have the same ability to attract interaction_partners or the same level of competition. 7Clearly, there are types within these types, e.g., Small, or Young, etc. which affect these scores and the high standard deviations. 153 Relationships among_the independent variables - resources Information presented in the preceeding section indicates that the interactions among charter-domain characteristics and other inde— pendent variables are related to system differences as well as to organization characteristics. The interrelations among the resource indicators and various organization types affects both need for resources of other agencies and ability to interact with fellow system members. This section describes these interrelationships using three correlation matrices. To help gauge the meaning of the correlations the p .10 level of significance for r with a sample is used as an indication of signifi- cant relationship even though the research subjects form the population of such organizations in each city. The small number of cases pre- cludes examining interrelationships among variables for Auspices/Mode types although that would be the most useful. Accordingly, in the material which follows information is given first for all the organiza- tions, and for the two Mode of Work types second. Based on the previous section, Auspices is considered a general indicator of system status and resources. Throughout this section the focus is on the relationships of charter-domain factors with both resources and competition and the association between resources and competition. Material which repeats findings of previous sections is not described again. In both cities the two measures of general resources are strongly associated (Table 27). Yet, the differences in the correlations of these measures with other independent variables shows the measures are tapping into different aspects of importance to others or Position in the system. Apparently, if the number of different transactions in which an organization is involved with other agencies as Target is high, then the 154 mwmnms > Aznwwv mwmm dmmdmm onommmmwoomw mmndwom demnmenw >oncmH ooavmnwnwoo down noswmnunfio: omm >cmwwomm Zoom om Soaw OOQNO’\UIJ>U3NH O p...- msmnms w AznumV memo dmmnmm uuommmmHoowH mmnnncmH noavmneneo: mmpn coaumnwnwos omm >Cmownmm Zoom om Sour Oxooouosmwat-a H nu .Ho saw .om sawv .OH Harm NV oowwMH>aH02m >ZOzn szmwNZUmza <>WH>wfiMm. owsws Nu up» muss» NV Hm boss» Hm -Ho up» mwsxw as» No we.» use -Hb so as». Hp w@** b u muss» IwH» HH m H Nu IHo o moss» FM two am»»z as» No was» .8 H0 1H0 Iuo» b m ww» Ho INN Nw No pox» No .HH Inc Hm NV ww» was» to bm*%* m Imm Hm IHw Hu Nb laws» mwsws bex Ho moxxs um we» >HH own>zHN>HHOZm we. as» -No wmmla as». m o IHo IwH Mm IHo INw amnxx 155 number of different organizations which include it in their organization- sets is also high. For an organization to be high in Importance, it must be identified by fellow members in the system of agencies as being a supplier of a variety of resources. A variety of resources attracts a variety of interaction partners. This relationship holds when Treat- ment and Distributive organizations are considered separately (Tables 28 and 29). Specific resources, e.g., size of staff and number of services offered, are associated with the general resource measures in both systems but the third specific resource, professional staff, is not associated with Overall Importance in either system and is related to Scope only in A. Table 28 shows the figures for Treatment agencies, and Table 29 for Distributive agencies. It is difficult to understand the relation- ship of professional staffing to Network Position and interaction patterns. In System A the relationships between professionalized staff and Overall Importance are neglible for both Treatment and Distributive agencies. For Treatment agencies the Scope-professionalized correlation is positive (.36); for Distributive agencies it is negative (-.29)- Service Diversity is not connected with high Professional Ratio. In City B professionalized staff has a neglible correlation with Overall Importance for Distributive agencies and a higher but negative relationship for Treatment agencies (-.33). The association with Scope is very weak. Although the correlations do not reach the p .10 level of significance, note that the relationships are in the opposite directions by agency type in the two cities. As in System A, in System B there is a low negative correlation between professional staff and Service Diversity for both types of organizations. 156 mwmnos > Aznebv memo comnoo vnomommeoooe mononsme cosmoneneos woen cosmoneneoo Odonmee Havonnmsno mnooo om Haoonnmboo >mo ,>Cmoeoom \DmNO‘Ul-fib-DNH mwonoa m Aznemv memo domnoo onomommeosoe mononcme ooBvonenoo moen cosponeneoa omo >meeooo 0mNOMwaH so .eo ssv .om *‘fiv . OH HM musss m» INH messs be mm muss we INN mm mmss Nu em nowwmr>aHOZm >Kozo HZUmwMZUmza <>WH>wrmm lee em Mm mm H» 1H0 Iem um Imu lea mu H>wbm Mm wow me>Hzmza ow0>zHN>HHOZm 1we Imm Jew new umsss mws mm we mus eu mess mes lmu .Nm two no mus Imo Iwm lbw moss em 5N mmsss I N ee u m Mm mu em sew wN Iwm 157 mwmnoa > Azueov memo Uomnoo mnemommeoome mononcme cosmoneneoo woe" cosmoneneoo omo >Cmvenom \OGJVO‘UIJ-‘UJNH mwonoa m Azumov memo domnoo onomommeosme momdeno Uenncme cosmoneneo= moen cosmoneneod Ododoee Havonnmsno mnovo om.HBooHnm:oo >mo >Cooenom \OCDVC‘U'IJ-‘WNH so .eo ssv .ou sssv .oe mo mu No HN up» -Hw boss HM Im oasss smss mm ossss H>mfiw no nowwmfi>aHOZm >Zozn HZUmwmzumza.<>WH>wfimm wow UHmeHwCHHzHN>HHOZm INm ea mass use ses» -us INH Iww em em Ho sess In» on 1e» mosss as .H» was» boss -NN new INm tub abs -Nm -us Immss He no» -sN wusss 1m abs e.oosss leo ems s m .N@ sass usN» new we we 158 There are further contrasts between the two systems in the rela- tionships between Service Diversity and the general resources or Position measures. Table 28 shows System A Treatment agencies have strong positive correlations between Service Diversity and general re— sources (.55 and .43) but the relationship does not hold for System B Treatment organizations (-.17 and -.17). From Table 29, for System A Distributive agencies the Service Diversity-general resources associa- tion is very low (.27 and .05) but strong for System B Distributive agencies (.54 and .47). From Table 26 it appears agencies which are large are also higher in Overall Importance in each city but the relationship with Scope is less strong. But, turning to Tables 27 and 28, the correlation between Overall Importance and Size is very strong for System A Treatment agen- cies (.81), low for System B Treatment agencies (.38), neglible for System A Distributive agencies (.08), and strong again for System B Distributive agencies (.74). Although the numbers vary for the two general resources measures, for three of the four categories Size is generally associated with high network Position. The notable exception is the System A Distributive group. On the whole, Table 27 confirms earlier tables showing that in City A Public agencies are usually larger, more diverse, and generally more important for system members than are Private agencies. In City B, Public organizations are larger, as compared with Private agencies, and generally more important, but Service Diversity correlation is low (-.lO). Turning to Tables 28 and 29, in City A Public-Treatment agencies are larger than Private—Treatment,and there is a moderate positive re— lationship between Auspices and Overall Importance (.42). For 159 Distributive agencies, Public agencies are also larger, more diverse, and have a higher network position but they are lower in professional staffing than Private agencies (-.37). For City B's system, Public- Treatment agencies are not higher in specific or general resources than are Private-Treatment agencies. Public-Distributive agencies are larger and higher in Overall Importance than Private-Distributive, but the re- lationships for other specific resources are neglible. Although information was given in Table 24 about the relationship between Age and Mode of Work, it is important to reexamine these re- lationships using the information from Tables 28 and 29 because the variance within types could not be considered in Table 24. Tables 28 and 29 show that Age is not associated with network Position for either type of agency; the correlations are all under .29 although in both positive and negative directions. For System A Distributive agencies Age has a low negative association with Size {-.13) and the reverse is the case in City B (.28). In System A Age is strongly associated with Professional Ratio but not in System B, and in both systems it has no relationship with Service Diversity for Distributive agencies. In the case of Treatment organizations, older agencies are somewhat more likely to be larger but the correlations are fairly low (.33 and .27). There is no difference by Age for Professional Ratio but there is an association for Service Diversity, and it is especially strong in City B (.75). In general, Age is not consistently associated with resource levels when the different types of work are considered. Age is a factor for a few specific resources but since it is not connected to the generally valued resources (or network Position) for these general types 160 of work it is more important to consider Age in combination with particular agency functions. Hence, the relationship between Age and Auspices is probably important. Competition and other variables Findings from a variety of other fields, (e.g., social psychology, attitude change, public opinion polling, race relations, industrial psychology, etc.) show there is an unreliable relationship between atti- tudes and behavior and these data restate the familiar. In both systems the correlation between Actual Competition and Felt Competition is .32 but when type of work is held constant, the relationships are different. In System A, for Treatment agencies the correlations between the two competition measures is .52, but-.18 for Distributive agencies; for System B Treatment agencies the correlation is .17 and for Distributive agencies it is .37. There is some reason to expect that organizations with secure domains will feel less pressured by general competition within the system. Thus, although the agencies may report a variety of competitive relation- ships with system members, the perceived competitive pressure may be 1ow. There is no measure of domain security but Overall Importance seems to be, at least partially, an indicator of this, as is public sponsorship. There should be positive relationships for resources and Actual Competition. The model for this research requires longitudinal data to test the general hypothesis that success in getting resources requires developing extensive competitive transactions, but some evidence should be visible in these cross-sectional data. Note, this model does not assume staff members will voice perceptions of the competition under which they work. 161 Earlier tables gave competition scores by Auspices/Mode types and, at this point, only the relationship between competition and general and specific resources by type of work is described. Supporting the research model, for Treatment agencies the higher the Actual Competition level, the higher the general resources in both systems but the rela- tionship is much stronger in System B than in System A. For Distribu- tive agencies the pattern is not consistent, and System A Distributive agency data show a moderate negative relationship between Actual Com- petition and general resources (-.28 and -.34) while City B Distributive agency data show low positive or moderate positive correlations (.11 and .36). When relationships between Actual Competition and specific re- sources are examined, an inconsistent pattern is found. In both cities, for Distributive organizations Actual Competition is associated with Service Diversity. For Treatment agencies there is little relationship between specific resources and Actual Competition, although there is a moderate negative relationship between Service Diversity and Actual Competition for City B Treatment agencies (-.3l). In terms of resources and perceived competition, for Treatment agencies four of the six correlations are lowemoderate negative (for Size and Service Diversity), and correlations for Professional Ratio and Felt Competition are low-moderate positive. For Distributive agencies patterns are less consistent across city-type, and for A there is a strong positive correlation between Felt Competition and Pro- fessional Ratio while in B this is -.33. In both cities high Service Diversity is somewhat associated with low Felt Competition (-.34 and -.l4). 162 Clearly, there are no consistent trends in these data relating competition to specific resources -- the pattern varies by type. These cross-sectional data do support the idea that having generally valued resources i§_related to competitive behaviors for most organizations. Those in the upper section of the community's organizational hierarchy are not sitting in isolation at the top of the pyramid. They are actively competing. These data Show that without information about the network, it is not possible to make sound estimates about which specific agencies will have higher competition levels or high Position in social service systems using organizational characteristics alone. Systems seem to vary, and it is difficult to identify which resources will be generally valued by the system itself. Size and Service Diversity seem to matter, but the agency's function (domain) seems equally important. Certain functions or services are needed by many system members, others are valued by fewer organizations seeking services to complement their own domains. For example, almost all agencies have at least some clients needing material assistance and will seek resources from the major' public agencies. An adoption agency on the other hand, may receive few transactions and be low in system Position as its services are specialized and needed by relatively few people. The services pool in communities has common basic features, but communities also have specific characteristics, and the hierarchy in the social service systems reflect differing local factors. Thus, ability (network Position) and competitive behavior reflect community differences as well as specific organizational characteristics. 163 The powerful organizations An organization's ability to participate with other organizations in resource exchanges is severely restricted if it has low standing with other system members. Without resources required by others or bargain— ing power it is difficult to see how organizations gan_develop external relationships regardless of the stimuli of need and competition. Al- though exchanges are not, and need not be, directly reciprocal (e.g., A may send clients to B and get back information or honor) a rough sort of reciprocity over time is probably necessary. Thus, an important determinant of interaction patterns within systems is the types of or- ganizations needed by the other members, stemming from the combination of services and agencies in the locale. To expand on this point, this section compares the characteristics of the High and Low Importance agencies in each system and gives information about system dominants, or those in the top 25 per cent in Overall Importance, and the system's fringe members, or those in the bottom 25 per cent. There are general similarities between the systems in the types of organizations most involved with others (Tables 6 and 18). In both systems Private-Distributive agencies are unimportant and Public- Treatment agencies are important. As Table 30 shows, in both systems the High Importance group is larger and more diverse than the Low Importance group, and in City B High Importance agencies have more competitive ties as well but this is not the case in City A. As expected, a characteristic of High Importance organizations is to be selected by others.for a greater variety of exchanges. 8Those agencies receiving above the median number of nominations for all interaction questions are High Importance. 164 TABLE 30 RESOURCES AND SYSTEM IMPORTANCE System A Scope of Importance Size Degree professional Service Diversity Actual Competition Felt Competition System B Scope of Importance Size Degree professional Service Diversity Actual Competition Felt Competition *p .10 **p .05 ***p .01 High Importance (N=16) i S.D. Low Importance (N=17) i S.D. 11.1 3.9 24.4 21.2 .49 .14 4.8 2.2 6.6 4.1 2.36 .86 (N=l7) 8.8 2.6 16.5 4.4 .48 .28 3.8 1.5 4.6 2.9 2.40 .97 t-test 5.053*** 1.654* 1.091 1.829** N.S. N.S. 6.629*** 1.470* '1** 57*** ZJ-‘NZ cnxococn 165 In social service systems, both Treatment and Distributive agencies have valued resources and provide services required by other organizations. Table 31 shows the relationship between resources and system importance for the two different Modes of Work. The High Im- portance Distributive organizations in each system have more specific resources than the Low Importance Distributive agencies. But System A Treatment agencies in the Low Importance group are only slightly smaller than those in the High Importance Treatment group, somewhat lower in professional staff resources, and slightly more diverse. In System B they are quite a lot smaller but otherwise do not have fewer resources than High Importance Treatment agencies. In addition, in B both types of High Importance agencies are also higher in Actual Competition but this is not the case in A. These data indicate the relevance of the types of services provided to system Position. If systems vary in emphasis and mix of service (and these do), then the services associated with system-level needs will be the valued ones, and organizations with such services in their domain will be important to other system members. In both systems, four large Public-Counterpart and two Private- Counterpart agencies are dominants. One large Public-Counterpart agen- cy is in the top group in B and the lowest half in A. The powerful organizations are primarily large; in both cities only about one-third are small. In each city there are two small powerful agencies, and they have similar functions in each city. As expected, both Distributive and Treatment agencies are im- portant in the systems, but almost all of the dominant Treatment 166 TABLE 31 RESOURCES, COMPETITION, AND SYSTEM IMPORTANCE BY MODE OF WORK, MEAN SCORES System A Resources Size Service Diversity Degree professional Competition Actual Competition Felt Competition System B Resources Size Service Diversity Degree professional Competition Actual Competition Felt Competition Low Import- ance (N=3) Treatment Agencies High Import- ance (N=ll) Low Import- ance (N=l3) 27.0 4.8 .32 Distributive Agencies High Import- ance (N=6) (I‘M meA HO‘ moo (N=9) MO‘ bNO‘ NU! 167 organizations are also large.9 In both cities over two—thirds of the powerful agencies have Public sponsorship. In each system the most important group has one Private-Treatment agency which provides a variety of counseling services, and one Private Distributive agency. In both cities the tax—supported system dominants are those organizations which provide the basic or foundation services. As Table 2 showed, these systems both use over one-third their total social welfare personnel for such services. Thus, this is an important point of simi- larity between the systems. These two systems are amazingly alike in terms of the dominant agencies, and since the greater proportion of these dominant agencies also provide the same types of services and have pretty much the same resources in each city, this general similarity reflects a similar press for certain important services even though the system's cluster of services is somewhat different. Are they also similar in terms of their weakest members? The answer is somewhat, but the similarities are not as strong when specific agencies are considered. Most of the fringe group are Private agencies and almost all of this group are small and most are very small. Well over half are the smaller Private agencies (Table 32). However, the least powerful group does not have members with the same general func- tions-as the dominant group does.11 9The exception is a large-budget agency which contracts for service with other organizations and is, thus, an important source for added resources although it is both small and new. 10This is a community center which provides a place for local agen- cies to operate de-centralized services. This explains its importance to system members. 11The Private-Counterpart agencies have low inter-city correla- tions (Table 9). Public Large Small Private Large Small Public Large Small Private Large Small 168 TABLE 32 System A Top quarter % 62% 12 25 Total 99% (8) Bottom quarter % 11% 22 11 56 Total 100% (9) System B Top quarter % 56% 11 ll 22 100% (9) Bottom quarter % 11% ll 78 100% (9) 169 Both systems have only a few weak organizations which are Large—Distributive or Small-Treatment. In each city there is one Treatment agency and it is small, offers few services, and has a very low Professional Ratio. These fringe members provide a variety of services, and it is impossible to identify a consistent pattern for their functions which explains their weak position. In City A six of the organizations offer very Specialized services to a limited client population. Three are fairly diversified in terms of the types of people served, and their low positions do not seem to be due to the type of client served, even though some members of this group do serve undesirable people (e.g., the poor and the handicapped). Three of them are primarily directed toward serving 'normal' people but ones with very specialized needs. Two are old-line agencies offering a variety of programs for 'normal' pe0p1e. In City B three of the agencies provide very specialized services. Only two primarily serve undesirable peOple, and four are group and leisure time agencies serving a varied population with 'character-building' services.12 Analyses of system positions show high inter-city correlations for Public-Counterpart agencies and divergent rankings for Private- Counterparts.13 A very lengthy search of the network position rankings revealed little correlation between systems when agency functions are 12City B commits more of its social welfare personnel resources to this type of service than does City A (Table 2), but of the six agencies involved, four are extremely unimportant within the system. These same agencies are higher in Importance in City A. 13As a further contrast, one of the dominant Public-Counterpart agencies in City B is in the lowest quarter in terms of system im- portance in City A. 170 compared for the non-counterpart groups. Apparently, although the top group in each system is very similar, and the Public-Counterparts hold similar rankings, the rest of the members are located differently within the two systems. When this information is coupled with other material about system differences, it helps explain the differences between systems in interrelationships of independent variables and in inter- action patterns. Hypotheses related to independent variables H2 Type of work is not a determinant of organizational position in local systems of social service organizations. There are two indicators of network position, Overall Importance and Scope of Importance. Overall Importance, which has two parts, Com- petitor and Resource Supplier, measures the number of times other organi- zations choose the Respondent as an interaction partner. Scope, the range of types of interactions for which an organization is named a partner by others, measures the variety of different types of exchange relationships. In interpreting these findings it is important to recognize that Overall Importance is a measure of dependency, while Scope is a measure of extensiveness of influences. These two variables are highly correlated (Tables 27, 28, and 29). When Treatment and Distributive organizations in these two systems are compared, t—test scores show no significant differences for the Overall Importance measure (Tables 15 and 16). In System A Dis- tributive organizations are more important as Competitors than are Treatment organizations but this is not the case in System B. In both cities there is no difference by type of work for the Resource Supplier measure. There are significant inter-city differences for the Scope 171 measure. In System A Distributive agencies are chosen by other members in a greater variety of exchanges than are Treatment agencies; in System B the situation is reversed. But, variations in the same associa- tion of these two with the other variables indicate they are not measures of the same thing but empirically as well as conceptually distinct. These inter-city differences tend to support the general idea that differences in the characteristics of these systems lead to dis- similar values for the visible output of system members, i.e., served people. Local factors dictate which system members are important and network positions will reflect these factors in addition to agency characteristics. In these two systems both general types of social service organizations provide services valued by system members, but the systems differ in the values attached to the various types of resources which the Distributive agencies have. One way to get more information about this is to look at the scores for Counterpart agencies (Table 33).14 The Counterpart scores for these two network position measures show no difference in Overall Importance by Mode of Wbrk in either city but the Scope of Importance scores are an interesting supplement to the data in Tables 15 and 16. The Counterpart agencies follow the overall pattern in System B, de- scribed earlier, and Treatment-Counterparts report higher Scope scores than Distributive-Counterparts. However, in System A the group of non— counterpart Treatment agencies (N=7) are much lower in Scope and this depresses the Systems' scores; the non-counterpart Distributive agencies (N=5) have higher scores. Fifty per cent of the Treatment agencies in 4Counterpart organizations make up two-thirds of the organi- zations in each city. 172 TABLE 33 COUNTERPART ORGANIZATIONS AND NETWORK POSITION Treatment- Distributive- -Counterparts Counterparts (N=7) (N=l4) System A i S.D. i S.D t-test Overall Importance 43.9 18.8 45.5 41.3 N.S. Scope of Importance 15.3 2.8 14.3 3.1 .741 System B Overall Importance 37.9 23.3 30.3 28.5 .618 Scope of Importance 15.0 3.0 10.5 4.2 2.320** **p .05 173 System.A follow the System B pattern of higher Scope scores for Treat- ment organizations.15 Five of the seven non-counterpart Treatment organizations are younger Public agencies which serve one particular client group, minority people, the poor, or mentally ill. Since organizations cannot interact with other agencies only on their own -- they have to consider the wishes of potential interaction partners -- basic agency domain is an important factor in system position. There is no information about what broad types of services are most im- portant, but basic life-support programs would seem more important than character building or even counseling services. Since these basic services are more often provided through Public agencies, Auspices is an indicator of the essentialness of the agency's functions. Table 34 compares Treatment and Distributive agencies within the same type of sponsorship on the two network position measures and shows there are no significant differences by Mode of WOrk when Auspices is controlled even for Scope of Importance scores. Considering all these pieces of evidence, it seems clear that factors unconnected to organizational type are important determinants of agency position in the system's hierarchy. Considering the important effect of public sponsorship on salience of agency domain for other system members, it seems type of work is not the controlling factor in determining the organizations position in the network. Although there seem to be differences in the extensiveness of agency influence by Mode of work, when Auspices is considered these are less important. The inter-city differences in Scope scores for Distributive-Counterpart Note the similarity in mean scores across systems. 174 TABLE 34 NETWORK POSITION AND MODE OF WORK, BY AUSPICES System A Overall Importance Sc0pe of Importance System B Overall Importance Scope of Importance System A Overall Importance Scope of Importance System B Overall Importance Scope of Importance Public- Treatment )? S.D. (N=8) 50.1 23.2 16.0 2.0 Private- Treatment )? S.D. Public- Distributive >0 S.D. (N=5) 46.0 40.9 12.2 5.2 Private- Distributive t-test P'Z: um 00 \O .704 .750 t-test 1.013 1.186 .673 ' 175 agencies is another piece of evidence pointing to the importance of system needs to network position. H3 As compared with Private agencies, Public agencies: a. Are more important to other agencies (higher Overall Im- portance and wider Scope of Importance); b. Have more specific resources. In both systems Public organizations, as a group, are much higher in both measures of network position than the Private organization group (Tables 19, 20 and 27). In System A, Public agencies provide more services than do Private agencies but this is not the case in System B. This is probably because the System A Public group includes organiza- tions with domains which are not included in System B. In City A there are two young, well-funded, innovative, and diverse organizations which have not been established in City B. In City B the Public agencies have higher professional resources but in City A the differences by Auspices are neglible (Tables 19 and 20). Because different system~level combinations are significant, in- formation about the Counterpart organizations is used to explore this hypothesis (Table 14). In both systems, Public-Counterparts are much higher in both network position measures and are larger. In A they are more diverse but there are no differences in diversity by Auspices in B. The apparent differences in Professional Ratio for System B Pri- vate agencies is probably due to the large number of very small agencies in that city. Most of the differences visible in Table 14 are related to the larger population served by System A. When within-system ranks on resource measures are considered, the resource levels for the different types of Counterpart agencies are very similar and 176 Public-Counterparts are higher than Private-Counterparts in the posi- tion measures (Table 9). The small number of cases makes it meaningless to examine the Counterpart agencies by both Auspices and Mode of Wbrk, but when Mode of Work is held constant forthe systems, in A Public—Treatment agencies are higher in network position and all specific resource measures, but the differences for Distributive agencies are less (Table 25). This is because of the high differentiation within Auspices/Mode types. Table 25 shows Public-Distributive agencies are more important and have more specific resources but with considerable within-category variation. Tables 27, 28, and 29 show generally strong positive correlations be- tween Auspices and Size for both types of organizations in City A, but the relationships between sponsorship and level of professionalization is weak for both types of organizations. In City B there are fewer differences between Public and Private agencies when Mode of work is controlled (Table 26). Again, there is high differentiation within categories. Although the t-test scores for the resources measures in the Distributive comparison do not reach the p .10 level (except for Size) because of the within-category variation, the Public-Distributive agencies are considerably higher in Overall Importance than the Private-Distributive type. An explanation for the comparatively low network position measures for City B Public- Treatment agencies is that 50 per cent of them are Young and highly specialized. Unlike the situation in System A, in System B correlations for Treatment agencies show no relationship between Auspices, network 177 position or specific resources, but the pattern of relationships is similar for System B Distributive organizations. For Distributive agencies Size and Overall Importance are highly correlated with Public sponsorship, but Professional Ratio and Service Diversity are unrelated to Auspices (Tables 28 and 29). On balance, the weight of the evidence strongly supports this hypothesis -- the conclusion that the generally higher valued resources within systems are located in the Public agency group. The data support the idea that the most important functions are usually within the domain of the Public organizations although within cities this will vary, par- ticularly according to the period of time in which agencies were es- tablished. Auspices is then an important indicator of ability to be involved with other agencies in interactions, either as the interaction Target (incoming transactions) or as Actor (outgoing transactions). H6 As compared to Old organizations, Young agencies: a. Have fewer resources; b. Are lower in Overall Importance and Scope of Importance. When Young and Old organizations are compared in City A, there are no differences in network position or specific resources. In City B, Old agencies are higher in Overall Importance than Young and somewhat lower in Scope of Importance scores (Tables 22 and 27). Age is not a characteristic apart from its effect in tandem.with agency domain or sponsorship and type of work. Table 23 is used to examine effect of Age on resources level by Auspices. Although Table 23 does not provide t-test scores, these findings are congruent with Pearson product-moment correlations by Auspices (not shown). In System A, when agencies are under the same sponsorship, the Old-Public agencies 178 are higher in network position measures than the Young-Public, but the differences for Sc0pe scores are very slight. Old-Public agencies are larger and more diverse than Young-Public, but there is little difference in Professional Ratio. For the System A Private group Age is not associated with network position although Old-Private agencies are larger, more diverse, and professionalized. This is probably be- cause their resources are not generally needed by other agencies.16 In contrast, City B Old-Public agencies are only slightly larger than the Young-Public, and Young-Public have more extensive influence than Old-Public even though the Old-Public agencies provide the basic services. The situation in City B clearly shows the effects of the charter-related press for service. Although Old-Public agencies are larger and more diverse than Young-Public, there is little difference in Overall Importance between the two types in this system. Although the Young-Public agencies are less diverse, they have higher Professional Ratio because they are primarily Treatment agencies. Old-Public agen- cies are primarily Distributive. In System B, as in System A, the Young-Public agencies are some- what more important to others in the system than the Old-Private agencies. Although they are smaller, they are more diverse and have fewer pro- fessional staff. Given the distortions introduced by very small size in City B, these organizations are really heavily non-professionalized which makes their higher network position scores most interesting. These six Young-Private agencies (five are Distributive) all serve 16Note earlier discussion of the divergent organizations within the Private agency sector -- the group is made up of strange bed- fellows! 179 special groups -- three are community centers serving the poor or minority population, one gives specialized service to the poor, one serves a special population with a range of services, and one serves youth. To test the relationships of resources and Age holding Mode of WOrk constant, Tables 28 and 29 show a consistent pattern between cities for Distributive organizations. Both Young and Old organizations are important to others and, on balance, Age is not connected to system position for Distributive agencies. Looking at specific resources, the picture is inconsistent. City A's Old-Distributive organizations are smaller (because they are Private) but much higher in Professional Ratio than Young agencies; City B's Old-Distributive organizations are more likely to be Large but the correlation is only .28, and Professional Ratio is not connected with Age. In both cities, Age is not associated with diversity. The major difference, the higher level of pro- fessionalization for Old-Distributive organizations in City A, is rela- tively unimportant. For Treatment agencies there is little association between Age and network position in either city, although Old agencies are somewhat larger and more diverse. Professional Ratio is unconnected with Age. Using Table 24 system-level differences are clear. In one city Old-Distributive agencies are the more generally valued while in the other the valued group are Young-Distributive. In both cities the Young-Distributive organizations are primarily under Private sponsorship (only one of the ten in this total group is Public) and provide highly specialized services to a particular client population. In City A this group includes those agencies serving a 180 special need but without the outreach focus found in the City B group (see previous section). The differences by city in the positions of Young-Distributive organizations are due to the dissimilar specific organizations which make up the type in each city. The City A organi— zations do very different-work than those in the same category in City B. When Young agencies are compared to Old agencies they generally do not have fewer resources or lower system position, and thus these data do not support the hypothesis. But sponsorship and work need to be considered when the effect of age on resources is considered. When this is done, an uneven pattern is found. The differences between types and between systems are due to the different specific agencies which make up the types in each city. Here again, the effect of the whole system upon organizational positions in the network is visible. In each city Old-Public agencies have higher network positions than Young-Public; Young-Private are higher in Overall Importance scores than Old—Private; Age is not associated with network position when Mode is held constant although specific resources vary. In conclusion, in each system some younger agencies have high network positions even with lower levels of specific resources, and Age is not consistently associated with higher resources.17 Accordingly, the hypothesis is rejected. 17It would be helpful if Age/Mode/Auspices types could be com- pared, but in City B there are no Young-Distributive-Public agencies and only one Young-Treanment-Private. 181 H93 Regardless of the Mode of work, the larger the organization, the more it is valued by other organizations (higher Overall Importance and wider Scope of Importance). In general, large organizations are more important to others than small organizations with the notable exception of Distributive organizations in System A. Tables 28 and 29 show strong or fairly strong correlations between Size and network position for Treatment agencies in both system and for System B Distributive agencies.18 The correla- tions between Size and the network position measures is neglible for System A Distributive agencies and, in explanation of this difference, Table 35 gives some additional information.19 For the Public agency group in both systems there is a strong positive correlation between Size and Overall Importance but a much lower relationship between Size and Scope of Importance. Unlike the situation in System A, in B the Private agencies show a higher correlation between Size and both net- work position measures (.31 and .35).20 In both systems over two-thirds of the Private agencies are Distributive organizations. It seems from this that many of the Pri- vate agencies in A are fringe members of the system. However, when the information in Table 25 is considered, it is clear that within the Distributive organization group there are wide variations in Overall Importance within the two sponsorship types. In a later section 18The correlation between Size and Scope of Impdrtance in City A is .41 which is somewhat lower than the p .10 level (dfl3=.48). In City B the correlation between Size and Overall Importance is .38, again slightly below the p .10 level (df14=.46). 19Complete information on correlations by auspices is not included. 20For df19, p .10-.39. 182 TABLE 35 STAFFING PATTERNS AND NETWORK POSITION System A Private Public agencies agencies (N=l9) (N=l4) Correlations of Size'with: Overall Importance 3 71*** Scope of Importance 15 20 Correlations of Degree professional with: Overall Importance 31 -5 Scope of Importance 40* 26 *p .10 ***o ’01 System B Private Public agencies agencies (N=20) (N=15) 31 68*** 35 24 2 -6 16 29 183 Actor interaction patterns are analyzed and those data show no differ- ences between Public and Private Distributive organizations in outgoing interaction behavior in either city. Further, since integration is higher in System A than in System B, what is low for A is moderate for B. (Note the higher Overall Importance scores for City A Private— Distributive agencies, Table 25 and 26.) This information about Distributive agencies in System A points to the importance of the particular services or agency function within the system for network position. In A some small agencies apparently have very needed domains, particularly when the differences in the Scope of Importance scores are considered. In B the Private agencies with extensive influence (almost all are Distributive) are more likely to have large staffs. In System A the relationship between staff size and extensiveness of influence is low regardless of sponsorship, but for the Distributive agencies as a whole (almost all Private), there is a low negative relationship between Size and Scope.21 It is certainly un- fortunate the small number of cases prevent adequate exploration of these relationships. I In summary, in most cases organizational size does seem to be a factor in how valued the agency is by others within the system. But, clearly domain somehow matters, too, and in some cases organizations with high value to other agenCies are small. The weight of the evidence tends to support this hypothesis and indicates size is an important factor. 21It is tempting to think Age is an explanation and that as these organizations get older their staff resources will increase. Unfortu- nately, only 4 of the 13 in City A Private-Distributive agencies are Young, and two of these are highly specialized and system isolates based on sociogram data. 184 'HlOa Regardless of Mode of Work, the higher the Professional Ratio, the more the organization is valued by other organizations. The evidence about the relationship of Professional Ratio to network position fails to support this hypothesis. In Tables 28 and 29, none of the correlations between Professional Ratio and Overall Im- portance or Scope, reach the p .10 level of significance and three of the relationships are neglible. For System B Treatment organizations the correlation is moderate negative (-.33). Turning to Scope of Im- portance, none of the correlations reach p .10 level although there is a moderate positive correlation between Professional Ratio and Scope for System A Treatment organizations (.36). For System A Distributive agen- cies there is a low-moderate negatiVe correlation of -.29. Table 35 shows the correlations between Professional Ratio and Scope by Auspices showing only one case in which the correlation reaches the p .10 level (i.e., System A Private agencies). In conclusion, the evidence fails to support the hypothesis but does not suggest an alternative one. On the whole, the evidence is very inconclusive. One factor affecting these relationships is the unreliableness of the Professional Ratio measure. The meaning of boundary-spanning staff seems to be lost when agencies are very small. H11 Regardless of the Mode of WOrk, the higher the Service Diversity, the more the agency is valued by other organizations. The data about the relationship between Service Diversity and network position show divergent patterns in these two cities (Table 36). Both System.A Treatment organizations and System B Distributive agencies have a strong relationship between the number of services they offer and their attractiveness to other organizations but the other categories 185 TABLE 36 RELATIONSHIP BETWEEN SERVICE DIVERSITY AND NETWORK POSITION, BY MODE OF WORK AND AUSPICES System A System B Correlations of Service Diversity and Network position for Treatment agencies Overall Importance 552* -l7 Scope of Importance 43 -17 Distributive agencies Overall Importance 27 54** Scope of Importance 5 47** Public agencies Overall Importance 46* 22 Scope of Importance 59** 1 Private agencies Overall Importance 23 55g* Scope of Importance 6 33 :p .10 I .46 p .10 = .38 *p .10 **p .05 186 show little relationship between these two variables. When the Public/Private material is examined, the same divergent pattern exists. Although without more sophisticated tools it is impossible to know if the relationship between diversity and position holds for System A Public-Treatment and System B Private-Distributive agencies, these data are highly suggestive.22 The inter-city correlation (Spearman rank-order) for Treatment- Counterparts is .804 and for Distributive-Counterparts it is .612, both scores -p .10 level of significance. Table 9 gives correlations by Auspices showing high inter-city correlations for Public agencies but much lower correlations for Private organizations. Since the inter-system positions are similar for the counter- part agencies, the differences are probably connected with the non- counterpart agencies and part of the overall pattern of differences in the thrust of the systems in each city. In System A the non- counterpart Public-Treatment agencies are all Young and definitely founded to seek innovation and redirection of services. They are all above the median in Size and well-funded. The non-counterpart Private- Distributive agencies are very small and highly specialized. In System B, three of the five Private-Distributive non-counterparts are new, outreach organizations involved in multi-service projects; 22Of the eight Public-Treatment agencies in A, six are above the median and none are below the median on both measures. The Private-Distributive group in A.have six cases below the median and one case above for both measures. In City B, the ten Public- Treatment agencies have two above the median and two below the median on both variables and the 15 Private-Distributive agencies have six above and seven below the median for both measures. 187 the non-counterpart Public-Treatment agencies are primarily small and very specialized. Although many are post-1960 agencies, they are spin off agencies, collectively part of newer efforts in ser- vices but with few resources individually. In short, they are very different from the System A group. These data do not support the idea that simple diversity in- creases network position. When the general importance of the domain (indicated by sponsorship) is coupled with diversity, then there is some relationship but it differs in the two systems. In System.A diversity of the type of services offered by the Public- Treatment agencies increases network position, but in System B it is those services associated with the Private-Distributive agencies which increase position. In sum, diversity of valued services does increase position, but the value attached to services varies by system. The relationship of competition and other conditions H14 There is a low positive correlation between Actual Competition and Felt Competition. When the organizations in each system are considered as a group, the hypothesis seems to be supported. Table 27 shows correlations of .32 (p .10 level of significance) between Actual Competition and Felt Competition in both cities, but when the different Mode of WOrk types are considered, the picture shifts. In System A, Treatment organizations have a .52 correlation between Actual and Felt Competition (reaching the p .10 level) but Distributive organizations have -.18 for the same 188 variables. In System B the correlations vary less dramatically, and for both types of agencies there are lowdmoderate positive correlations (Tables 28 and 29). The only information available to shed any light on these differences are the correlations for Public-Private agencies. When these are considered,'in System A Private agencies have a .57 correlation (p .05) between Felt and Actual Competition, but Public agencies have a neglible -.01. In System B, for Private agencies the correlation is .13 and for Public agencies it is .56 (p .05). No satisfactory explanation exists for these relationships. As mentioned previously, it seems reasonable to expect that Private agen- cies experience competition more directly and both the salience of competitive pressures and competitive interactions will be higher. The material in Tables 19 and 20 show this is the case only in A. In neither system are Private agencies engaged in significantly more com- petitive interactions than Public agencies. Perhaps in System B the sense of competition for United Way money is lower. There is some interview evidence that supports this idea, and in System B the member agencies do receive a lower proportion of their total regular allocations from United Way than member agencies do in System A. In B, agencies more often solicit funds directly and although they are tapping the same pool of potential givers, perhaps some have a strong constitutency and funds are easy to raise. When competition levels are examined by Mode of Wbrk, in System A Distributive organizations are higher and in System B Treatment organi- zations are higher (Tables 15 and 16). In conclusion, when all the evidence is considered, the hypothesis receives only moderate and mixed support, and these data tend to support 189 earlier findings indicating an unreliable relationship between behavior and attitudes. H15 The higher the general and specific resource levels, the higher the competitive interactions. The correlations between general resource levels and Actual Com- petition for Treatment agencies support this hypothesis but, unfortu- nately, relationships are not the same for Distributive organizations. As Table 28 shows, for System B Treatment agencies there are strong positive correlations between general resources as indicated by the two network position measures (.54 and .51). In System A the correlations are lower (.32 and .34) but indicate moderate association. Turning to Distributive organizations, the correlations in A are moderately nega- tive (-.28 and -.34) and in B the correlation between Overall Impor- tance and Actual Competition is neglible (.11) and somewhat higher for Scope of Importance (.36) (Table 29). When the specific resource measures are considered, the only re- lationship which reaches the minimum level is between Actual Competition and Service Diversity for System A Distributive agencies. Of the other 11 correlations between specific resources and Actual Competition, seven are under .20 (both positive and negative) and only one is as high as .36. The correlations are inconsistent between system by type of organization. Public sponsorship is associated with valued resources but there is no evidence that Public agencies, regardless of Mode of Work, have significantly higher levels of Actual Competition (Tables 19, 20, and 25). The evidence is mixed. When Mode type is ignored, then the relation— ship in System B between general resources and Actual Competition 190_ is strong enough to reach the p .05 level (Table 27). It is low- moderate in System A. The correlations between the specific resources measures and competitive interaction is low in A and neglible in B. One part of the hypothesis should be rejected; there is no relation- ship between specific resources and competitive interactions. This cross-sectional data provides limited support for the other part, the higher the general resource levels, the higher the competitive be- havior. Success in securing resources in the past does not lead to diminished competition, and high status agencies continue to compete. H16 The higher the position in the network, the lower the Felt Competition. In general, these data give only very limited support to this hypothesis. In no case do the correlations reach the minimum level of significance but for the two Mode of Work types, the relationship between Overall Importance and Felt Competition for Treatment organi- zations in both cities is low moderate (-.26 and -.38), while for Dis- tributive organizations the correlation in A is -.26 but only .02 in B. H17 Public agencies have lower Felt Competition scores than Private agencies. This seems to be the case for System A organizations. Table 19 shows the t-test score reaching the p .05 level but in System B the difference by Auspices is not large (Table 20). When Auspices and Mode are both considered, in System A both Public-Treatment and Public- Distributive have significantly lower Felt Competition scores than Pri- vate-Treatment and Private-Distributive (Table 25). In System B there is no difference by Auspices for Treatment_agencies but Private-Dis- tributive agencies have higher scores than Public-Distributive ones. 191 When the correlations between Auspices and Felt Competition by Mode of Work are examined in Tables 28 and 29, Distributive agen- cies in both systems show negative correlations indicating Public agencies have lower Felt Competition scores but System B Treatment agencies show no relationship between Auspices and Felt Competition although the System A Treatment agencies show low-moderate associa- tion (-.29). When all the evidence is considered, it tends to support this hypothesis. Public organizations do not report the same perceptions about competition as Private agencies. In contrast, the Public agen- cies in each system report more competitive interactions than Private agencies although the differences do not reach the p .10 level of sig- nificance because of wide variations within types (Tables 19 and 20). Although director perceptions about competitive pressures are lower in Public agencies,1nore of the agencies 235 actively engaged in a large set of competitive relationships than are the Private organizations. H18 As compared to Old organizations, Young organizations have higher Felt Competition. Table 22 gives the Felt Competition scores by Age and in System B the data support the hypothesis but not in A. The between systems contradictions in these data can be seen quite vividly in Tables 28 and 29. In A, Old-Treatment agencies are higher in Felt Competition than Young—Treatment organizations, but in B Old-Treatment group members have lower Felt Competition scores. This same relationship is found for System B Distributive agencies and the Correlation between Age and Felt Competition is -.34, not as high as for Treatment agencies but still indicating older agencies have lower scores, as expected. In System B 192 the Distributive group shows no relationship between Age and Felt Competition. In two of the four major types, Young organizations have higher Felt Competition scores than Old, but the correlations are significant in only one case (System A-Treatment agencies),and Table 24 shows mean differences are quite small in the other three cases. Apparently, the directors of some pre-l96O agencies perceive many competitive pressures. and the directors of some of the newer agencies have a sense of security or low competition. Young-Public agencies in City A have higher Felt Competition scores,but for other Auspices types scores are higher for Old agencies (Table 23). On balance, the data do not justify concluding that the hypothesis is supported. As the evidence pertaining to these five hypotheses about Actual and Felt Competition is considered, the conclusion which should be drawn is that it is very difficult to know just what types of organizations will experience high levels of competition. As has been repeatedly demonstrated, these are highly differentiated systems. There are im- portant differences in the nature of the systems in the two different cities,and competition factors are not consistent either within or across systems. Although there are no inter-system differences in level of Felt Competition (Table 12), when the Counterpart organizations are examined, the systems have very low correlations for both types of Counterpart agencies on the Felt Competition measure indicating that for Counterpart organizations the climate is different in each city (Table 9). Further, when the Public-Counterparts are considered, there is a fairly strong negative correlation (-.52) between cities and 193 moderate positive correlations for Private-Counterpart agencies for Actual Competition (.43).18 The next chapter presents extensive evidence linking high Actual Competition with extensive interactions, particularly when organizations have high ability (indicated by network position measures). This section has demonstrated that the relationship between organizational characteristics and competition levels is difficult to specify. Thus, although competition is apparently strongly related to an organiza- tion's outgoing or Actor-based relationships with other organizations, it is difficult to identify consistent factors connected to competi- tive behaviors. Summagy This chapter examined system differences in the distributions of the independent variables and the interrelationships among these variables. The overall model for this research assumes the relation- ship between competition and interaction is affected by organizational ability to attract partners, or by resources wanted by other system members. Thus, the several sections in this chapter sought to identify consistent relationships among the independent variables which help in unraveling the connections between work-related conditions and ability related characteristics and to explore factors connected with varia- tions in competition which relate to the interaction patterns to be described in Chapter V. Although the causes of the system differences described in this chapter and Chapter III are unclear at this point, the significant point 18This score is adjusted for different means for Actual Com- petition in two cities because it is based on rankings. 194 is that the data show important differences in the social organization of these systems and the distribution of resources within the systems. In turn, these differences are related to member organizations' ability and motivation to develop interaction strategies. As discussed in Chapter I, the major purpose of this research is to test some of the most popular explanations for organizational interactions to demonstrate their inadequacy and the power of the competition/conflict political economy perspective. The data presented in this chapter make it clear that system needs are important determinants of agency power or system position. Thus, if interaction requires systemevalued resources, agency behavior will be importantly determined by system characteristics as well as by organizational factors. Chapters III and IV have docu- mented extensive system differences,and Chapter V connects these differences to interorganizational relationships. As system differ— ences are related first to agency needs, ability, and competitiveness and then to interactions, the limitation of the assumptions so prevalent in the inter-organizational relations literature, which regards in- ternal organizational characteristics as the key determinants of ' interrelationship, are apparent. Further, the relationships between agency position and competition,and system-level competition and extent of system integration, provide considerable support for the competition model in contrast to other perspectives described in Chapter I which focus on interactions at the service delivery level and assume coopera- tion undergirds the sector. The data presented in this chapter show the hierarchical arrange- ment of organizations in these two systems is different. This is dramatically shown when the Counterpart organizations are compared but 195 other data show consistent variation in system position connected to Mode of Wbrk, Auspices, and resources. Given the similarity in services and programs for the Counterpart organizations and the similar levels of resources, one expects generally similar interaction behavior. But, although the status of the top-quarter group, the major public organizations, is highly similar in the two systems, the other Counter- part members are dissimilar in status, and the non-Counterpart organi- zations are ranked differently also. Further, it seems clear that position within the set of local agencies is not related to the general type of work or to Specific re- sources. This means predictions about interaction patterns based on these internal characteristics fail to receive support. In both systems position is tied to sponsorship. The Public agencies generally are higher in the hierarchy, and as these are primarily large organiza- tions, size is related as well. But, when one examines position for those Public agencies which are not responsible for providing the expensive basic services such as income maintenance, then sponsorship is less clearly connected with position, and there are wide variations between the systems. In both systems services within the two basic types of work are valued by system members,but when the two Mode of Work groups are com- pared by system position, then there are significant variations be- tween the systems, e.g., Public-Distributive agencies are valued in one system but Public-Treatment agencies in the other. In sum, the patterns of relationships among the independent variables are inconsistent in the two cities but there is a fairly consistent pattern within each system. 196 Although the levels of specific resources (i.e. size, service diversity and professional staffing) are higher in System A than in. System B, the important finding,which is related to the interaction patterns described in Chapter V,is that the systems vary in the re- sources assigned to the different types of organizations. There are differences by Mode of WOrk for these specific resources and for the general resource measures of Overall Importance and Scope of Influence as well. Age is connected with resources differently by system, and this means the potentially important press for interaction connected to age translates into position and interaction levels differently in the two systems. Thus, an important point of system difference is the variation in interrelationships among the charter-domain variables and the several resource measures. In addition, there are differences in the extent and the location of Actual Competition and Felt Competition both within and across systems. Competition is higher in System A than in System B,and inte- gration is greater in System A as well. Competition varies widely by charter-domain and resource characteristics, and it is impossible to predict competitiveness from any of the other variables although there is some relationship between high system position and high actual competition. The differences in competition scores for the Counter- part organizations further illustrate this point. Finally, the significant differences in interaction levels in the two systems is evidence of important variations in the general environment for individual organizations. These differences parallel differences in competition levels but probably are also connected with characteristics of umnber organizations such as the kind of work 197 performed, since only some services require interactions, or the number of very small organizations, since organizations without sufficient slack cannot commit staff to the work required to develop interactions. Perhaps system norms support interactions in System A to a greater extent than in System B; perhaps there are more incentives from funding organizations or more opportunities for informal inter- actions in one city than the other which set the stage for future interactions. The important point is that the systems do stimulate very different degrees of interorganizational interactions. In conclusion, it seems the high degree of differentiation and specialization, together with the relatively small number of local social service agencies and the high resource interdependence, means organizations tend to occupy specific niches within the systems. It is difficult to find consistent patterns relating agency characteristics to either system position or competitiveness. The set or family of agencies form different systems in each city, and in turn this seems related to which organizations are needed by the others. This factor affects the organization's ability to interact with system members. System conditions are important determinants of interorganizational relationships as are organizational characteristics. 198 CHAPTER V ORGANIZATIONAL INTERACTION STRATEGIES Introduction This chapter describes the relationships between organiza- tional characteristics and interaction behavior to test the hypotheses about Actor interaction patterns. The material about system differ- ences and organizational characteristics presented in Chapters III and IV serves as the foundation for the material presented now. Additionally, Chapter V presents supplementary evidence about some similarities and differences between these two systems. The first section of this chapter is a comparison of inter- action patterns in the two systems. Next, the hypotheses about inter— actions are tested, and some information about various aspects of Resource Exchanges is included although the specific hypotheses are directed only to Cooperativeness. A final section describes the relationship between competition and interaction strategies in a test of the research model. System difference in interactions In System A, agencies are involved in Resource Exchanges with each other and other groups in the social welfare sector and the community to a greater extent than are members of System B (Table 37). In each system, organizations tend to have about the same number of organizations as interaction partners or organization-set members, but in A they are generally more involved with these Organizations. Since the three general interaction measures include competitive as well as non-competitive interactions, the differences in the Resource Exchanges are better indicators of exchange transactions, and the data show important inter-system differences. In addition, in System A 199 TABLE 37 ORGANIZATIONAL INTERACTIONS, BY CITY , City A City B (N=33) (N-35) Variables 3i S.D . i S.D . t-testa Interaction character- istics Size of set 11.1 3.5 10.5 3.0 N.S Network interactions 38.8 16.9 28.6 12.7 2.811*** Sector interactions 44.3 18.5 37.3 17.1 1.591* Community interactions 53.2 15.6 49.7 15.5 .921 Variedness 12.0 3.7 13.5 3.3 l.744** Reciprocity 6.4 3.2 3.6 2.2 4.118*** Resource Exchanges 32.1 13.8 23.1 11.3 2.903*** Cooperativeness 11.3 7.7 7.9 6.7 l.943** Reference-group inter- actions 7.6 3.7 4.1 3.2 4.069*** Simple Exchanges 13.4 4.1 10.9 4.2 2.451** a One-tailed test is used because prediction that System B has higher scores than System A is determined by number of questions asked in B. 1*p .10 **p .05 ***p .01 200 there are more cooperative relations than in System-B.and since such transactions involve some surrender of agency autonomy, the between- system differences show there are more planned interactions in System A than in B. These differences are also shown in higher reciprocity scores in System B. There is a significant exception in that the Actors in City B report a greater variety of types of trans- actions with their interaction partners than do City A's agencies (Table 37). Table 38 shows the interaction scores for the Counterpart group. In System A the organization-set scores are lower for the Public-Counterparts than for Private-Counterparts, but the reverse is the case for System B. In both systems the Public-Counterparts have more Resource Exchanges than the Private—Counterparts, but the differences are slight in System A. In comparison to other members of the system, System A Counterparts are more involved with other organizations and groups than are those in System B, and the between system differences in Resource Exchanges and Variedness scores for the Private-Counterparts are especially striking. Table 14 showed the incoming interactions or Target scores for these same organizations, and in both systems the Public- Counterpart agencies receive many more nominations than they make choices. Their exchange relationships are lopsided, and others depend upon them for resources to a greater extent than they depend on fellow system members. In contrast, the Private-Counterparts tend to have more balanced exchanges and incoming and outgoing choices are roughly similar. 201 TABLE 38 INTERACTIONS OF COUNTERPART ORGANIZATIONS, MEAN SCORES System A “ ~ All V,Public~. _Private- 2 i Counters Counter- Counter- >,parts parts parts (N=21) (Ni-7) (Pi-14) . Variables Interaction character- istics Size of set 11.7 10.3 12.4 Network interactions 42.9 46.1 41.2 Sector interactions 47.9 54.0 44.8 Community interactions 53.1 57.6 50.9 Variedness 12.6 13.6 12.7 Resource Exchanges 35.2 37.7 34.0 System B Interaction character- istics Size of set 10.1 12.3 9.1 Network interactions 24.5 33.1 20.1 Sector interactions 33.9 48.4 26.6 Community interactions 44.4 55.6 38.8 Variedness 10.6 12.4 9.6 Resource Exchanges 20.0 29.4 15.4 202 When the higher potential interaction scores for System B are LOUSI cred, the higher actual Resource ExChanges scores in System A are more important.1 These data show two impOrtant inter-system differences that are related tothegeneral theoretical model of this research. The system with the higher competition also has the larger numbers of Resource Exchanges and a greater number of Coopera- tive interactions (compare Tables 12 and 37; see Table 9,) Charter-domain characteristics and interactions2 1. Mode of Work and Auspices The general type of work affects the number of outgoing interactions only in System B. In that system, Treatment organiza- tions are involved in more Resource Exchanges, relationships are more varied, and they are involved in more COOperative relationships than are Distributive organizations. In System A there are fewer differences, but Distributive agencies tend to have higher inter- action levels than do Treatment organizations (Table 39). In both systems Public agencies have more Sector interactions and more varied ties than Private agencies, and in System B they have larger organi- zation-sets. In neither system do the differences in Resource Ex- changes reach the minimum level of significance (Table 40). Tables 41 through 44 give comparisons for interaction scores by Auspices and Mode of WOrk, and in System A there are no differences in outgoing relationships when both variables are considered (Tables 1In City B, 15 non-competitive interaction questions were used and in City A, 14. 2In the next two sections, discussion of data ranges over a variety of tables. Tables are introduced in groups as near as possible to appropriate place in narrative. 203 TABLE 39 ORGANIZATIONAL INTERACTIONS, BY MODE OF WORK System A Variables Interaction character- istics Size of set Network interactions Sector interactions Community interactions Variedness Reciprocity Resource Exchanges Cooperativeness' System B Interaction character- istics Size of set Network interactions Sector interactions Community interactions Variedness Reciprocity Resource Exchanges Cooperativeness *p .10 **p .05 ***p .01 Treatment organizations (N-14) i S.D. 10.79 3.32 36.53 17.93 40.58 19.30 50.05 16.96 11.21 3.66 6.05 3.28 30.32 14.84 10.79 8.24 (N=15) 11.13 2.63 33.67 10.69 45.07 16.18 57.27 11.33 14.87 2.22 26.93 8.35 9.67 5.71 Distributive organizations (N=19) i S.D. 11.50 3.66 42.00 14.88 49.43 16.07 57.50 12.14 13.14 3.42 6.86 2.97 34.43 11.76 11.93 6.90 (N=20) 10.00 3.11 24.75 12.79 31.50 15.30 44.00 15.77 12.45 3.53 3.45 2.40 20.20 12.33 6.65 7.02 t—test N.S. .932 .973 1.445* 1.484* .789 .856 N.S. 1.111 2.176** 2.442** 2.812*** 2.444** N.S. 1.861** 1.361* 204 TABLE 40 ORGANIZATIONAL INTERACTIONS, BY AUSPICES **p .05 Public Private organizations organizations (N=l4) (N-l9) System A i S.D. i S.D. t-test Variables Interaction character- istics Size of set 10.50 2.06 11.53 4.18 .877 Network interactions 41.14 15.09 37.16 17.97 .661 Sector interactions 50.21 15.63 40.00 19.28 1.619* Community interactions 56.71 13.56 50.63 16.39 1.129 Variedness 13.00 2.95 11.32 4.00 1.360* Reciprocity 7.50 2.53 5.58 3.36 l.792** Resource Exchanges 33.79 11.20 30.79 15.27 .630 Cooperativeness 12.93 5.43 10.05 8.85 1.133 System B (N=15) (N=20) Interaction character- istics Size of set 11.27 2.82 9.90 2.95 1.372* Network interactions 31.93 12.29 26.05 12.46 1.356* Sector interactions 44.07 19.00 32.25 13.37 1.983** Community interactions 55.87 14.06 45.05 14.91 ‘2.l37** Variedness 14.60 2.82 12.65 3.32 l.887** Reciprocity 4.07 2.05 3.30 2.19 N.S. 'Resource Exchanges 25.73 9.04 21.10 12.38 1.230 -Cooperativeness- 9.40 6.20 6.85 6.78 1.145 *p .10 205 TABLE 41 :ORGANIZATIONAL INTERACTIONS BY AUSPICES AND MODE OF WORK, SYSTEM A Public- . ' Private- Treatment Treatment (N'8) (N-6) Variables i S.D. K S.D. t-test Interaction character- istics Size of set 10.2 2.3 13.2 5.1 N.S. Network interactions 41.1 13.7 43.2 18.8 N.S. Sector interactions 51.6 15.6 43.7 18.7 N.S. Community interactions 60.4 9.2 53.7 16.2 N.S. Variedness 13.8 3.1 11.2 4.6 1.098 Resource Exchanges 33.2 9.7 36.0 15.8 N.S. Public- Private- Distributive Distributive (N-6) (N'13) Interaction character- istics Size of set 10.8 2.4 10.8 3.8 N.S. Network interactions 41.2 19.4 34.3 25.3 N.S. Sector interactions 48.3 18.4 37.0 20.1 N.S. Community interactions 51.8 18.6 49.2 17.6 N.S. Variedness 12.0 3.0 10.8 4.1 6N.S. Resource Exchanges 34.5 20.3 28.4 15.6 N.S 206 TABLE 42 ORGANIZATIONAL INTERACTIONS BY AUSPICES AND MODE OF WORK, SYSTEM B Public- Private- Treatment Treatment (N-10) (N-S) Variables i S.D. i S.D. t-test Interaction character- istics Size of set 11.4 3.0 10.6 2.1 N.S. Network interactions 48.9 18.6 35.8 6.5 1.790** Sector interactions 54.7 13.6 40.4 9.7 2.097** Community interactions 59.9 10.6 52.0 13.3 1.039 Variedness 14.3 2.6 11.8 2.8 N.S. Resource Exchanges 27.9 9.3 25.0 7.7 1.286 Public- Private- Distributive Distributive (N-S) (N=15) Interaction character- istics Size of set 11.0 2.9 9.7 3.3 N.S. Network interactions 32.8 18.4 31.1 15.4 N.S. Sector interactions 40.0 16.9 33.9 15.9 N.S. Community interactions 47.8 19.2 42.7 12.8 N.S. Variedness 11.4 6.4 10.5 3.9 .N.S. Resource Exchanges 21.4 8.7 19.8 14.0 N.S. **p .05 207 TABLE 43 MODE OF WORK AND INTERACTIONS, BY AUSPICES, SYSTEM A Public- Public- Treatment Distributive (N-8) (N-6) Variables i S.D. i S.D. t-test Interaction character- ' istics Size of set 10.2 2.3 10.8 2.4 N.S. Network interactions 41.1 13.7 41.2 19.4 N.S. Sector interactions ' 51.6 15.6 48.3 18.4 N.S. Community interactions 60.4 9.2 51.8 18.6 N.S. Variedness 13.8 3.1 12.0 3.0 N.S. Resource Exchanges 33.2 9.7 34.5 20.3 N.S. Public- Private- Treatment Distributive (N-6) (NI-13) Interaction character- istics Size of set 13.2 5.1 10.8 3.8 N.S. Network interactions 43.2 18.8 34.3 25.3 N.S. Sector interactions 43.7 18.7 37.0 20.1 N.S. Community interactions 53.7 16.2 49.2 17.6 N.S. Variedness 11.2 4.6 10.8 4.1 N.S. Resource Exchanges 36.0 15.8 28.4 15.6 N.S. MODE OF WORK.AND INTERACTIONS, BY AUSPICES, SYSTEM B Variables Interaction character- istics Size of set Network interactions Sector interactions Community interactions Variedness Resource Exchanges Interaction character- istics Size of set Network interactions Sector interactions Community interactions Variedness Resource Exchanges *p .10 208 TABLE 44 Public- Treatment (N-10) NI S.D. u: b x: h‘h‘h‘ xouv1:c»<»c» uaoxoxo~o\c> Private- Treatment (N'S) Public- Distributive (N=5) i S.D. 11.0 2.9 32.8 18.4 40.0 16.9 47.8 19.2 11.4 6.4 21.4 8.7 Private- Distributive (N-15) 9.7 3.3 31.1 15.4 33.9 15.9 42.7 12.8 10.5 3.9 19.8 14.0 t-test N.S. 1.450* 1.547* 1.186 N.S. 1.226 O UJMNCDUJUJ O O ZZl-‘ZZZ o§o O 209 41 and 43). In System B, Public-Treatment agencies make more Actor choices than the Private-Treatment agencies,but Auspices does not affect interactions for Distributive agencies (Table 42). When agencies with the same Auspices are compared in System B Public-Treatment agencies are higher in interaction levels than Public- Distributive organizations,but there are no differences in the two Private groups (Table 44). As discussed in Chapter IV, agencies doing both general types of work are important to other agencies. One indicator of valued domain is sponsorship. When sponsorship is held constant, there are very few differences in outgoing interactions between Treatment and Distributive organizations (Tables 43 and 44). The following hypotheses are related to charter-domain characteristics: H1 As compared to Distributive organizations, Treatment agencies will have: a. More non-competitive or resource exchange interactions with other organizations; b. MOre varied relationships with other organizations; c. More cooperative relationships with other organizations. H In comparison to Private-Treatment agencies, Public-Treatment agencies are: a. Higher in Resource Exchanges; b. More varied in relationship with other organizations. H In comparison to Private-Distributive agencies, Public- Distributive agencies are: a. Lower in Resource Exchanges; b. Lower in Cooperativeness. 210 When only Mode of Work is considered, these data show support for H1 in one city but not the other.~ When the sponsorship informa- tion is considered, the hypothesis clearly is not supported. The conclusion is that the general type of work of the organization, even when domain is highly valued (e.g. is publicly funded), is 222. a determinant of extensive Actor relationships, although charter- domain characteristics usually do affect Target-based interactions (Overall Importance). Organizations providing system-valued services, especially if they are diverse, may not need to seek resources through interorganizational exchanges (especially through cooperative relationships) but will attract interactions. Thus, they may be un- involved in cooperative relationships but will be important to other system members for Simple Exchanges and Reference-group transactions and, therefore, be high in network position (i.e. have high Overall Importance and/or Scope of Influence scores) (Tables 25 and 26). Comparisons in Tables 43 and 44, which examine Mode of Work holding Auspices constant, also lead to a rejection of both parts of H4 and H5. In addition, Tables 48 and 49 show that Public-Treatment organizations are not higher in either Resource Exchanges (.19 and .16) or Variedness (.15 and .34) than Private-Treatment agencies, and Tables 50 and 51 give very low correlations between Auspices and both Resources Exchanges and Variedness for Distributive organiza- tions (System A, -.12 and .21, System B,.O6 and .09). From this information it seems neither the type of work or the general value Of the services as indicated by Auspices is a determinant of outgoing (or Actor) interaction behaviors. 211 TABLE 45 ORGANIZATIONAL INTERACTIONS, BY AGE System A Variables Size of set Network interactions Sector interactions Variedness Resource Exchanges Cooperativeness System B Size of set Network interactions Sector interactions Variedness Resource Exchanges Cooperativeness *p .10 **p .05 ***p . 01 Young Organizations (N=l3) i S.D. 10.1 2.7 32.7 14.1 40.1 19.2 10.7 4.1 26.5 15.1 9.7 7.7 (N=13) 11.6 3.3 36.2 15.5 43.3 24.2 14.9 3.2 27.3 15.2 11.2 8.3 Old Organizations (N=20) i S.D. 11.9 .9 44.3 16.6 47.1 18.5 13.1 3.0 34.6 15.2 12.6 7.7 (N=22) 9.9 2.6 24.6 8.6 32.3 12.6 12.7 3.0 19.7 8.9 6.2 4.8 t-test 2.250** 2.071** 1.000 1.714** 1.446* 1.017 2.463*** 2.417*** 1.333* 1.964** 1.583* 1.923** 212 TABLE 46 ZERO-ORDER CORRELATIONS OF INDEPENDENT AND SELECTED DEPENDENT VARIABLES FOR ALL ORGANIZATIONS Number of Varied- organiza- Network Sector- Community- ness of tions"' inter- inter- inter- inter- SYstem A in set actions actions actions actions (N=33) Size -4 18 23 27 20 Degree professional 8 29 29 42** 41** Service Diversity 3 12 22 16 21 Actual Competitiona -- 75*** 72*** 66*** 73*** Felt Competition 32* 29 24 33* 31* Overall Importance 12 32* 35** 40** 23 Scope of Importance 26 43** 50*** 51*** 46*** Age 23 29 19 11 29 Auspices -15 12 27 19 23 Mode of WOrk 10 16 24 24 26 System B (N=35) Size 23 -5 -4 16 10 Degree professional -1 16 23 21 36** Service Diversity 25 1 —4 15 11 Actual Competitiona -- 55*** 55*** 49*** 47*** Felt Competition 19 31* 32* 21 26 Overall Importance 58*** 34** 32* 56*** 44*** Scope of Importance 49*** 47*** 46*** 69*** - 64*** Age -27 -44*** -41** -37** -32* Auspices 23 23 34** 35** 30* Mode of Work 19 35** 39** 42*** 37** aOrganization measures is substituted for choice measure. *p .10 **p .05 ***p .01 213 mwmnma > Azuwwv mHNm cmmflmm vnommmmHode moneHom UHoncmH noaomanHon mmHn nosvmanHoo omm >5manmm zoom om Soar mwmnma w Aznumv.m mHNm Ummnmm vnommmmwoomH mmnoncmH noaomanHo: mmHn noaomanHoa OdmanH Havonnmbom moovm om HBoonnmnnm >Wm >CmoHnmm zomm om Sour H>wfim bu nowwmr>HHOZm ow HZUmwMZUNZH <>WH>wfiMm >26 wamm Ow Hzamwown>2HN>HHoz>H WMfi>HHOmeme. >Hr owh>2HN>HHOZm wommnmsnml mHBon ooBomanHwbm be nowwmr>HHOZm ow H2dmwmzumza <>WH>wVMm >20 Hawmm ow Hzamwown>zHN>HHoz>h wmfi>HHOmeme wow me>Hzmza meszN>HHOZm wommnmoomI mHBon ooawmanH AZHHbV mHuo uN HH No HN ummumm vnommmmHoomH Hm mu 1m Nw moHoncmH noaomanHo: II bus Hm oo»» men ooavmanHoo mN» uo IH Na omm mN» Ho Iw Hm >CmoHnmm o Hm bN Hu mwmnma w Aanmv MHNm .1 m Ibo Ibm» lb Ummnom vaommmmHoumH IH¢ IHo IHm INN mmHoncmH ooavmanHo: II um IHw omaam den noaooanHo: Hu bu HH IHN OdmanH Haoonnmbom was» IHm Iww box» mooom om HBuOHnmanm mHas INm Imaxa 9N. >mm qu Imu»» u IHm >CmoHomm Nm . um IN Hw »v .Ho saw .om ssav .oH wmmocnom mxosmommm No Nu H mH»» mo bu» owes Hm Ho Iwm IwH IbH bN H» 10 INN Ho 216 TABLE 50 ZERO-ORDER CORRELATIONS AMONG INDEPENDENT AND SELECTED DEPENDENT VARIABLES FOR DISTRIBUTIVE ORGANIZATIONS System A (N=19) Size Degree professional Service Diversity Actual Competitiona Felt Competition Overall Importance Scope of Importance Age Auspices System B (N=20) Size Degree professional Service Diversity Actual Competition Felt Competition Overall Importance Scope of Importance Age Auspices a Organization measure *p .10 **p .05 ***p o 01 Number of organiza- tions in set -20 25 18 38 -5 -25 35 -3921: 36 2 48** 35 56*** 53** -44** 19 Network inter- actions 29 45* 77*** -20 -32 52** 13 37 46** 31 35 55** -46** is substituted for Sector- inter- actions 20 13 62*** 73*** -5 —17 -22 30 16 14 ~ 41* 56*** 31 36 48** -28 5 Community- inter- actions 23 16 68*** 44* 6 22 2 6 27 30 12 51** 36 28 50*** 62*** -34 14 choice measure. Varied- ness of inter- actions 30 23 57** 31*** -16 -23 —34 34 21 21 32 41* 43** 26 50** 60*** ~22 217 H>whm UH oowwMfi>HHOZm om HZUmwmzcmza <>wH>wfimm >26 HNNMm ow Hzamwowo>zHN>HHoz>fi me>HHOmeme mow UHmeHwCHHZHN>HHOZm wmmmfimsnml mHBoHo ooaomanH Aanov MHNm No Io u m Ummsmm vsommmmHoomH HN we Nu Ho moHoncmH noaumanHos II we»»» mN»»» ou»»* men noaooanHoo IHm m V IN OdemHH Havonnmsnm INm Ibo» INN o mooom om Haoonnmonm IN» Imus» Ibo» Io >mm an» mo»» boa» Nb >cmanmm o IEH» Iwm Hm mwmnma w AzuNOV ES . .m .5 a G Ummnmm vnommmmHoomH a o No m mmHoncmH noSwmanHos II No IHo Ho men ooaomanHOD mu bu»» a No omm w Iuw Irma» lama» >CmvHomm INH INN Ho m an .Ho wxo .Om **su .oH womocnom mxnrmbmmm wH pH» “Nara IHm INo mN*» IHN HN NH No N» we no»* Ibow» 218 TABLE 52 ORGANIZATIONAL INTERACTIONS BY MODE OF WORK AND NETWORK POSITION, MEAN SCORES Treatment Distributive Organizations Organizations Low High Low High Import- Import- Import- Import- ance ance ance ance System A (N=3) (N=11) (N=l3) (N=6) Resource Exchanges 48.7 34.3 26.3 36.3 Sector interactions 66.3 49.1 35.5 48.3 Network interactions 58.0 41.7 32.2 42.5 Variedness 15.7 11.9 10.5 12.2 System B (N=6) (N=9) (N=11) (N=9) Resource Exchanges 27.8 26.3 12.7 29.3 Sector interactions 45.3 53.0 26.3 46.7 Network interactions 43.3 45.3 23.1 42.0 Variedness 13.3 13.6 8.8 13.4 219 2. Age In System A Old organizations are higher in the number of organization-set members, Resource Exchanges,and Cooperativeness, but in System B the Young agencies are higher on these interaction measures than the Old (Table 45 and 47). The evidence about Age and other independent variables (discussed in Chapter IV, H6) showed there is an inconsistent relationship between Age, network position, and specific resources. As mentioned earlier, these data show Age is not an independent characteristic of organizations.and therefore it should be considered in connection with other charter-domain factors. When the two Mode of Work types are considered, in System A Old-Treatment agencies have more varied relationships and higher com- petitive interactions than Young-Treatment, but there is no relation- ship between Age, Resource Exchanges.or Cooperativeness (Tables 48 and 49). System A Old-Distributive agencies have more Network interactions and more Reference-group and Simple Exchange interactions than do Young-Distributive, but there is only a low~moderate correla- tion between Age and Cooperation for Distributive agencies (Tables 50 and 51). For Treatment agencies there is little relationship between Age and the various types of relationships. In explanation, nine of the 13 Private-Distributive agencies are Old, and only one Public-Distributive agency is Young. Three of the Young-Distributive agencies are highly specialized and in the middle third in Overall Importance. In System B for both Treatment and Distributive agencies the correlations between Age and interaction measures are negative. 220 Although there is no relationship between Age and size of organization- set for both types of agencies, Young organizations have higher interaction levels,and there is a low-moderate correlation for Variedness (Tables 48 and 50). System B Treatment organizations show a significant negative correlation between Age and Reference- group interactions, and Distributive agencies show sizable negative correlations in Simple Exchanges and COOperative interactions as well as in Resource Exchanges. Age affects interactions differently in these systems because of the characteristics of the Young group. In System B Young agencies are smaller and less diverse than in System A. With fewer internal resources and more charter-related pressures to interact, they seek resources externally. In System A most Young-Public agencies are very diverse and well funded, and therefore, probably need fewer external resources; the other Young agencies are small and highly specialized, requiring fewer resources from other system members. If ability to attract interaction partners requires valued re- sources, then unless resource levels are somewhat the same, the effect of Age,or the press for coordination and service integration growing out of the shift in social welfare services in the mid-1960's. cannot be explored. Table 53 compares Young and 01d agencies under similar general resource levels (i.e. Overall Importance scores). In both systems when Low Importance agencies are compared by Age, there are no differences in four of the interaction measures, partially because of the wide variations in scores in the several categories. When High Importance agencies are considered, in System A Old agen- cies are higher in the two general interaction measures and have more 221 TABLE 53 AGE AND INTERACTIONS, BY NETWORK POSITION System A Variables Network interactions Sector interactions Variedness Resource Exchanges Network interactions Sector interactions Variedness Resource Exchanges System B Network interactions Sector interactions Variedness Resource Exchanges Network interactions Sector interactions Variedness Resource Exchanges *p .10 **p .05 29.2 35.4 10.0 25.0 37.5 38.8 11.8 23.0 Young (N=5) S.D. 13. 19. N-L‘I-‘w 10. Young (N=8) 14. 17. \IRODJN 10. Young (N=4) 17.5 17.5 5 3 Low Importance Old (N=11) x! U) :1 oahln~ c>hac> coxo~u Hi PIN) O\u>\lhl O O I IOIo~ome 1 . High Importance Old (N=10) 37.9 43.3 . 1 . 12.3 23.8 \INNO I~.bI~xo t-test zzzsz mmmoo 1.427* 1.850** 1.765** 1.772** IAIHIZIA u:n>a:o~ 222 Resource Exchanges as well as more varied ties. In System B, the Young agencies are higher on these same measures. The specific agencies making up these Importance categories in each city are fairly similar. In System A five of the eight are fairly large, diverse agencies,and three are mental health agencies. Four serve the poor and/or minorities, and one is a youth-serving organization. In System B three are community centers serving the poor and/or minority population, one serves the elderly, and four offer mental health services. The System B agencies in this category are smaller than those in System A. Table 54 shows the correlations between the two network position measures and three types of exchanges for Young and Old agencies. Several correlations are of interest. For Old agencies in A, as Overall Importance goes up, so do Simple Exchanges, but the difference occurs in B for Young agencies. In all instances, as the Scope of Importance scores increase so do Cooperative exchanges, and as network position increases, the Variedness of outgoing inter- actions also increases. The following hypothesis concerns Age and interactions: H7 When general resource levels are the same, as compared to Old organizations, Young agencies will: a. Have higher levels of Resource Exchanges; b. Have more varied relationships with other organizations. There is some support for this hypothesis but it is not con- sistent or very strong. Clearly this is the case for High Im- portance agencies in City B. For the other three Age/Importance 2 Exchange theory predicts this behavior for individuals (Blau, 1964). TABLE 54 RELATIONSHIPS BETWEEN NETWORK POSITION AND INTERACTIONS, BY AGE Correlations of Overall Importance with: Reference-group exchanges Simple exchanges COOperative exchanges Variedness Correlations of Scope of Importance with: Reference-group exchanges Simple exchanges Cooperative exchanges Variedness *p .10 **p .05 ***p . 01 System A Young Old (N=13) (N=20) 7 21 -16 42* 44 18 25 21 43 56*** 10 43* 44 65*** 41 58*** System B Young Old (N=12) (N=33) 3 -28 12 -44** 20 32 28 70*** 30 5 7 O 33 61*** 70*** 57*** 224 categories the relationship does not hold. In general, as resource levels (indicated by Overall Importance and Scope of Importance) in- crease then cooperative exchanges and the variety of exchanges also increase, and this is especially true for the Scope of Importance indicator. (Some Young agencies are in favorable environments and will interact heavily but others are more isolated even though they may have valued resources.) The stimulus to interaction for the post- 1960's group apparently depends on local system factors including needs of other agencies, resources allocated, and probably on general standing in the community.3 Resources and interactions 1. General resources An important general hypothesis in this research is that system- valued resources are prerequisites for extensive interorganizational relationships. Although systems differ in what resources are valued (see Chapter IV) given a domain which includes these services, the organization's ability to interact is enhanced. Table 46 through 52 and Table 55 describe the relationships in these cities. Considering all the organizations, in both cities the two network position measures are generally highly correlated with the various interaction variables. In System B the relationships are very strong; in System A they are slightly less strong (Tables 46 and 47). Regardless of variations in domain and age, the highly 3City A has two large anti-poverty organizations; City B had one but it 'died' just as our research began. From interview information it seems serving the poor is not as respectable in City B as in City A, and it's.not too well regarded in A. (Marcus, 1973). 225 differentiated nature of the systems or inter-system differences, organizations with valued resources generally have extensive Actor relationships. In both cities, Scope of Importance is highly correlated with Cooperative interactions,a1though the correlation for Overall Importance withCooperativeness reaches the specified level only in City B (Table 47). When Mode of Work is considered, the picture changes. In System A Treatment agencies show positive correlations between ability (position) measures and Sector interactions and Resource Exchanges (Tables 48 and 49). The relationships are very different for Distributive agencies--the correlations are primarily negative and, although only a few reach minimum significance levels, the pattern is consistent (Tables 50 and 51). In contrast, in City B the relationships between the general resource measures and interactions are in a positive direction for Distributive organizations and less consistent, indeed sometimes negative, for Treatment agencies. As exceptions, there are positive correlations between position measures and Community interactions and Cooperativeness; for Simple Exchanges the relationships are high negative for Treatment agencies and moderately positive for Distributive agencies. These patterns of differences by Mbde by city shown in Table 5 largely parallel those in Table 36 and extensively described in both narrative and tables in Chapter IV when differences by system are discussed. This material will not be restated here but when it is considered with the information in Tables 48 through 55, the system differences are apparent. Even when network position (and presumably 226 valued domain) is considered, these consistent inter-city differ- ences in characteristics associated with various organization types reappear in the interaction patterns. Auspices is one indicator of system-valued domain. Table 55 gives the correlations for network position (general resources) and interactions showing the extreme differences between these two systems when only Auspices is controlled. In A, the correlations between the two position measures and the various interaction variables are very high for Private agencies and generally neglible for Public agencies. In B only a few of the correlations for Private organi- zations are important, but the relationships are very high for Public organizations. It is difficult to explain these differences, but the inter- system correlations of the Counterpart organizations provide an important clue. As Table 9 indicated, the correlations for the Public-Counterparts--and these are the system dominants in each city-- are rS = -.70 and for Private-Counterparts rS = .30. These correla- tions directly parallel inter-system differences in Actual Competi- tion. This is discussed more in a later section. The following hypothesis concerns general resources. 227 TABLE 55 RELATIONSHIPS BETWEEN NETWORK POSITION AND INTERACTIONS, BY AUSPICES Private Public Organizations Organizations System A Correlations of Overall Importance with: Network interactions 44* 27 Sector interactions 50** 18 Variedness 44* -1 Resource Exchanges 49** 27 COOperativeness 47** 9 Simple Exchanges 40* 28 Correlations of Sc0pe of Importance with: Network interactions 52** 17 Sector interactions 55** 19 Variedness 51** 14 Resource Exchanges 54** 24 Cooperativeness 47** 1 Simple Exchanges 46** 34 System B Correlations of Overall Importance with: Network interactions 14 43 Sector interactions 6 54** Variedness 44** 37 Resource Exchanges 22 49* Cooperativeness 39* 55** Simple Exchanges -9 62** Correlations of Scope of Importance with: Network interactions 32 58** Sector interactions 18 59** Variedness 57** 64*** Resource Exchanges 22 ‘ 59** Cooperativeness 39* 58** Simple Exchanges -9 52** *p .10 **p .05 ***p .01 228 H The higher the level of generally valued resources: a. The greater the number of Resource Exchanges; b. The more varied the relationships with other organizations; c. The higher the level of Cooperativeness. A summary of the relationships shows: Part a--Resource exchanges and network position City A Treatment - general support City B Treatment - neglible correlations City A Distributive - low~moderate negative correlations City B Distributive - general support Part b--Variedness and network position City A Treatment - general support City B Treatment - general support City A Distributive - moderate negative correlations City B Distributive - general support Part c--C00perativeness City A Treatment - general support City B Treatment — general support City A Distributive - neglible correlations City B Distributive - general support In two cases there are moderate negative correlations which are in the -.16 to -.34 range, indicating that some organizations in each type show relationships between valued domain and outgoing inter- actions and two cases of neglible correlations can be interpreted . this way, too.4 This means that there is a particular group of agencies (specifics unknown) for whom high network position is fairly strongly associated with low outgoing interaction levels. Considering these findings, the data tentatively support all parts of this hypothe— sis, and, in general, organizations with high ability to provide valued services, indicated by high number of nominations as interaction 4There is evidence for this interpretation in correlations by Auspices: Overall Importance - Resource Exchanges, B Public = .49; B Private = -.17; Overall Importance - Cooperativeness, A Public = .09; A Private = .47. 229 partners and by extensive influence in types of interactions, also are engaged in extensive interorganizational relationships. This is discussed again when the joint effects of ability and competition are considered. 2. Specific resources a. Size is related to network position (except for City A Distributive organizations) and seems frequentlyvto be a determinant for Target interactions (Tables 27, 28, and 29). The correlations for Size with the various Actor interaction measures show largely neglible or low relationships, and there are only a few significant relationships (Tables 46 to 51). In System B some correlations are negative, indicating smaller organizations have more inter- action, and for B Treatment agencies, the correlation between Size and Simple Exchanges is -.48. Correlations for Reference-group interactions with Size is also fairly high (-.40) in B. For System A Treatment agencies, the correlations are low but positive. One reason may be that the small agencies in City B are primarily Young. There are several reversed correlations by agency type. For Distributive agencies, the correlations between Size and Size of Set is -.20 in A and .36 in B; for Treatment agencies Size-Resource Exchanges correlation is .20 in A and -.38 in B; and when Size and Network interactions are considered, the relationship in A is .25 and in B -.28. Variedness does not seem related to large size; indeed, for the only correlation over .30, size is negatively correlated with Variedness. The next hypothesis is related to the resource of staff size. 230 H9 The larger the organizations: b. The higher the level of Resource Exchanges; c. The more varied the relationships with other organiza- tions. These data do not support either part of this hypothesis. Part a relating size to network position was generally supported (Chapter IV). Certainly the data described above indicate size is connected to interactions in conflicting ways and the conclusion is that although size is an important condition for Target—based interactions, it is not consistently important as a determinant of Actor inter- actions. b. Professional staff are considered an important resource because, unlike lower echelon staff, they may be empowered to negotiate for the agency. Material in Chapter IV showed no real relationship between professionalization and network position (Tables 27, 28 and 29). When Tables 46 to 51 are considered, in System A professionali- zation does seem related to Community interactions and Variedness, and the relationship, while low or lowdmoderate, does not change when Mode of Work is considered. In System B professionalization is associated with Variedness (Table 46) but when Mode is considered, the relationships are lower. The relationships with Variedness is con- sistent, but on balance, the relationships shown in Tables 46 to 51 are weak. Chapter II explained the distortion introduced by the small size of many organizations,and in Chapter IV it was indicated that Professional Ratio as a real resource in interactions may be relatively meaningless for the very small agencies. To amplify that discussion, 231 Table 56 gives the correlations of Professional Ratio and other measures with Size held constant. The correlations for the large agencies in System B shows high Professional Ratio is related to ex- tensive interactions of several types, but the relationships in System A for large organizations show an opposite trend although the correlations are not very high. For small agencies in A, professional staff ig related to interaction levels, but for B small agencies (these are primarily under ten employees) the relationships are low or negative. Forty-four per cent of the System A large agencies are Public—Treatment agencies as compared to 29 per cent Public- Treatment in System B. Further, A's Public-Treatment agencies are more diverse than B's (Tables 25 and 26). For Treatment agencies diversity is not a stimulus for interaction, and this seems to be a reason for the pattern of relationships for the large agencies shown in Table 56. A very high proportion of System B agencies are very small. Indeed, 72 per cent of the small agencies have under ten employees. In System A average organization size is higher, and only 29 per cent of the small agencies are in the under ten employee category. Thus, for small agencies in A, Professional Ratio has more meaning as a measure, and the data show it is a factor in interorganizational relationships. These data, combined with extensive material in previous chapters show distribution of organizations in the systems and other system differences, indicate that when agencies pggg to seek re- sources from other sources, professional staff is an important factor in establishing these relationships. In System B large agencies are 232 less diverse, and may need other agencies' services for their clients. This is particularly true for these primarily low diversity agencies. Many are Young and seek service integration. A professionalized staff enables them to do that. In System A the large agencies pro- vide more services internally and have less need for resources from the other agencies. The small System A agencies are not so handi- capped by size as in System B, and professional staff seem to be a resource in developing inter-agency relationships, especially Coopera— tive relationships. The following hypotheses relate to the resource of professionalized staff. H10 Regardless of Mode of Work, the higher the Professional Ratio: b- The higher the level of Resource Exchanges; C- The more varied the relationships with other organizations; d- The higher the level of Cooperativeness. Professional Ratio is a resource only when other conditions stimulate interactions (Table 56). When organizations need resources, then having a high proportion of professionals seems to increase inter- actions. If agencies can meet service-related needs using their own resources, have secure sources of funds (Public), and are sufficiently large to release staff from organizational maintenance and direct service responsibilities, then the higher the Professional Ratio the more interactions established. Professional Ratio is consistently associated with Variedness.' In summary, when the very small organizations are excluded, the data tend to support the idea of the value of professional em- ployees in developing cooperative relationship and increasing agency interactions generally, but probably organizations must have some 233 TABLE 56 RELATIONSHIPS BETWEEN PROFESSIONALIZATION AND INTERACTIONS, BY SIZE System A System B Large organizations (N=16) (N=17) Correlations of Degree professional with: Overall Importance -17 37 Network interactions -27 52** Variedness 2 55** Reference—group interactions 4 23 Simple Exchanges -26 16 Cooperativeness -25 46* Actual Competition —32 40 Small organizations (N=17) (N=18) Correlations of Degree professional with: Overall Importance 34 -43* Network interactions 58** -12 Variedness 50** 15 Reference-group interactions 72*** 11 Simple Exchanges 33 2 Cooperativeness 42* —21 Actual Competition 42* -14 *p .10 **p .05 ***p . 01 234 slack for this to be an important factor. c. When Service Diversity as a resource is considered, the data related to H11 described in Chapter IV show that diversity of valued services lg a determinant of system position but that the two systems differ in the value placed on services offered by the two Modes of Work. In one system Treatment Diversity is tied to high incoming interaction, while in the other Distributive Diversity is related to high Target interactions. The effect of Service Diversity on Actor interactions is expected to show higher incoming resource exchange interactions for diversified Treatment agencies, but a lower level of outgoing interactions since diverse Treatment agen- cies need fewer services from external sources. H12 and H13 are considered together and test ideas about the resource of services. H12 For Treatment agencies, the higher the Service Diversity: a. The higher the Resource Exchanger level (Target); b. The lower the level of Resource Exchanges (Actor); c. The lower the level of Cooperativeness. H13 For Distributive organizations, the higher the Service Diversity: 3. The higher the Resource Exchanger level (Target); b. The higher the level of Resource Exchanges (Actor); c. The higher the level of Cooperativeness. Table 57 gives the correlations between Service Diversity and Resource Supplier measures for the different Modes of work. These data repeat the findings presented earlier showing a high relationship between Service Diversity and the Target-based variable Resource Supplier for System A Treatment and System B 235 TABLE 57 RELATIONSHIP BETWEEN DIVERSITY AND TARGET INTERACTIONS, BY MODE OF WORK Treatment Distributive Organizations Organizations System A (N=l4) (N=19) Correlations between Service Diversity and Resource Supplier 53** 23 System B (N=15) (N=20) Correlations between Service Diversity and Resource Supplier 13 49** **p .05 236 Distributive organizations and much lower, although positive, correlations for the other types. As discussed earlier, some System A Distributive and System B Treatment agencies are diverse but not needed by other agencies, and hence do not attract nominations for non-competitive interactions. No information is presently available to additionally clarify these relationships. With increased diversity Treatment agencies are expected to have fewer outgoing non-competitive interactions (Resource Exchanges), and the data in Tables 49 and 51 show a fairly high negative correla- tion (-.41) for System B Treatment agencies which almost reaches the minimum significance level (df l4 p.10=.46). The neglible correlation of .01 for System A Treatment agencies, when considered with neglible correlations for these variables by Auspices (not shown), means the hypothesis is not supported with System A data. Again, for System A Treatment agencies there is no relationship between Diversity and Cooperativeness, and the relationship in City B is low-moderate but in the expected direction. In summary, these data do not consistently or strongly support H12 and do not suggest an alternative hypothesis. Considering interactions for Distributive agencies, there is somewhat stronger support for H123, and in both cities diversity of Distributive services is related to more incoming non-competitive interactions, although the correlations are weaker in A than in B (Table 57). The data for A show strong support for H13b and H13C; Tables 49 and 51 show high correlations between Service Diversity and both Resources Exchanges and Cooperativeness (.41 and .47). For B the relationships are in the expected direction but are moderate (.31 and .38). 237 These data consistently support the idea that diversity of services for Distributive agencies is a stimulus to the development of interorgani- zational relationships. Attitudes about competition and interactions Feelings about competitive pressures may stimulate agency directors to seek exchange relationships with other organizations, but expressed attitudes may be a highly inadequate basis for predicting behavior, particu- larly when professional norms support ideals of agency teamwork to meet client needs and limit expressions about competition. Two measures of com— petition are required, one attitudinal and the other behavioral. This model of interorganizational relationships assumes ability to contribute valued resources is a necessary ingredient for inter-agency relationships or exchange transactions. Competition may be considered but if organiza- tional ability is low, interactions will be minimal. Thus, H19 Because interorganizational relationships require resources, Felt Competition level is unrelated to interaction level. Some agencies are high in perceptions of competitive pressures as well as in actual competitive interactions. With the limited number of cases in each city it is impossible to separate these effects. Table 27 shows the correlation between Actual Competition and Felt Competition for all agencies is .32, but when Mbde of Work is considered the relationships change. Correlations between the two competition measures are fairly strong for System A Treatment organizations (.52); but only moderate for System B Distributive agencies (.37), low positive for System B Treatment agencies (.17), and low negative for System A Distributive organizations (-.18). The correlations between Actual and Felt Competition may account for some of the relationship between Felt Competition and interaction levels for 238 System A Treatment and System B Distributive agencies. Therefore, compari- sons should be between Felt Competition and types of Resource Exchanges for categories with minimal relationship between the two measures. The two categories which had low correlations between Actual and Felt Competition, A Distributive and B Treatment, also have neglible correlations for the various types of transactions and Felt Competition, with only one exception--B Treatment agencies have a fairly high correlation between Felt Competition and Reference-group interactions. For A Treatment organizations there are some moderate correlations with Resource Exchanges and two com- ponents, Cooperative and Reference-group interactions; for B Distributive agencies the correlation with Reference-group interactions is strong but low for other exchange types (Tables 49 and 51). Testing the relationship of Felt Competition with interaction measures requires considering both organization ability and the interrelationship of competition measures. Since organizations under Public sponsorship generally provide resources more valued by the other agencies in the local network, one way to get around the limitation imposed by small number of cases is_ to examine the relationship between Felt Competition and interaction be- haviors for Public and Private agencies separately. This permits estimates of the effect of ability coupled with competition. Table 58 gives corre— lations between the competition measures and interactions by Auspices. Note that in two instances there are high correlations between Felt Competition and Actual Competition which affect the apparent relationships between Felt Competition and interactions. In the System A Public group (i.e. the high resource group) the core- lations for Felt Competition and these same measures are very low. Turn- ing to System B Public agencies, the same strong pattern of high correlations TABLE 58 COMPETITION AND INTERACTIONS, BY AUSPICES System A Correlations of: with interaction measures Size of set Network interactions Sector interactions Community interactions Variedness Resource Exchanges Cooperative interactions Simple Exchanges Reference-group interactions Actual Competition System B Correlations of: with interaction measures Size of set Network interactions Sector interactions Community interactions Variedness Resource Exchanges Cooperative interactions Simple Exchanges Refefence—group interactions Actual Competition *p .10 **p .05 ***p .01 Public (N=l4) Actual Compe- tition 42 81** 79*** 62** 85*** 79*** 75*** 71*** 82*** Felt Compe- tition -9 -3 5 15 23 -4 6 -l7 -6 -1 Public (N=15) 57** 34*** 75*** 60** 54** 79*** 54*** 38 63** l 38 40 35 53** 27 21 -2 53* 56** Private (N=19) Actual Compe- tition 38 72*** 7o*** 68*** 67*** 59*** 55** 14 41* Felt Compe- tition 42* 53** 49** 54** 48** 45* 41* 22 44* 57** Private (N=20) 13 31 35 44** 38* 38* 33 40* 22 14 3O 15 18 54** 13 240 appears between Actual Competition and the interaction measures. The high correlation between Actual and Felt Competition probably ex- plains these scores (Table 58). As shown in Chapter IV, Private agencies on the whole offer less valued services than'Public agencies. In System A the correlation between Actual and Felt Competition for Private agencies is very high (Table 58). The correlations between the competition measures and interaction variables are generally high but the relationships be- tween Actual Competition and the various interaction behavior measures are much stronger than those between Felt Competition and interactions, indicating that the interactions between these two measures leads to the apparent relationship. For System B Private organizations the relationship between Actual and Felt Competition is very low. For the most part the competition variables are not highly related to interaction levels in this group. Felt Competition is associated with Size of Set and Sector interactions, and the correlation between Felt Competition and Reference-group interactions is strong. No relationship exists between Actual Competition and Reference-group interactions. Actual Competition is related to Community interaction and Variedness, and there is an interesting moderate negative relationship between Actual Competition and Simple Exchanges (Table 58). This set of data about Private agencies when considered with other information about re- sources for Private agencies shows the intervening effect of ability on the relationship between Competition and interactions. This is discussed more in a later section. 241 In System B 62 per cent of the Private agencies are small.and these small agencies are generally very small. As Table 13 showed, the very small agencies in System B are extremely low in the general resource measures. Further, the Private-Counterpart agencies also are low in resources (Table 14); 71 per cent of the low importance group are Private (Table 18); the Private agencies are very low in Resource Supplier scores (Table 20); and the Private-Distributive type (sixty—five per cent of System B Private are Distributive) is the lowest group in terms of position as Resource Supplier (Table 26). Certainly there is sufficient evidence about the general weakness of most System B Private agencies. Although in both systems Private agencies are lower in the network position measures, the Private group in A is higher in ability than the B group. Considering these findings, when Felt Competition is coupled with resources and not correlated with Actual Competition (System A Public), then the relationships between Felt Competition and inter- actions are neglible. Even when the High Competition, high ability agencies are also high in Felt Competition (System B Public), Felt Competition is not as strongly correlated with interactions as is Actual Competition. Low ability agencies (System B Private) show lower correlations between both competition measures and interactions than do somewhat higher ability agencies (System A Private), and for System A Private agencies it is impossible to identify the effect of Felt Competition because of the high correlations between the two competition measures. These findings support the idea that expressed attitudes about competition is not a good predictor of interorgani— zational relationships. Thus, if only perceptual measures are used, 242 the importance of competition as a cause of interorganizational relationships is missed. The weight of evidence about the relationship of Felt Com- petition and interaction patterns fails to support H Ability 19' is an important factor in developing such interactions. Compgtition and interaction This research model of interorganizational relationships among social service agencies assumes relationships are caused by (1) work- related, service delivery needs for the resources of other agencies, and (2) scarcity and competition which stimulates interaction to gain resources by exchange with others in the group of agencies sharing the local pool of tangible and intangible resources connected with social services. Exchange theory predicts exchanges will not continue over time unless there is a balance between rewards and costs. When cross—sectional instead of longitudinal data are used, then this rewards-minus-costs-equals-profit idea can be partially tested by assuming ability to exchange valued resources is required to establish extensive relationships, or that probable rewards are needed to make profit seem possible. The model assumes some interactions gill_occur regardless of competition or ability because the local social services sector is made up of interdependent parts. Each part, the agency, is responsible for one or more pieces of the whole local services package. This interdependence produces some interactions. How many is not known, but for this type of relatively passive interaction, competition is probably of minimal importance. Competition without ability may lead agencies to seek exchange relationships, and they may have 243 Reference-group and/or Simple Exchange interactions which stem from system interdependencies. But without generally valued resources and the requisite staff, extensive relationships, particularly cooperative interrelationships which require planning and commitment, cannot be established. 4 Test of the general model To support the thrust of this model, these data need to show: (1) work-related factors do affect interaction patterns; (2) ability is related to outgoing interactions; and (3) competition stimulates increases in interaction levels when ability exists. Reviewing the general pattern of the findings to this point, there is no relationship between the type of work (Mode) and net— work position (i.e., measures of generally valued resources), but there is a relationship between sponsorship and importance. Thus, Auspices is an indicator the organization has system-valued resources. As shown, Mode of WOrk alone does not affect outgoing interaction levels, but, in general, outgoing interactions do increase as im- portance to other organizations increases, i.e., as position in the hierarchy increases. Hence, ability is an important factor in inter- actions. WOrk-related factors stimulate varying degrees of outgoing interactions. When Treatment organizations are diverse and can pro- vide many system-valued services, they do not need to seek resources outside their own boundaries. In contrast, diversity stimulates Distributive agencies to establish more extensive relationships. Staff size affects the organization's position when its' domain is generally valued but is of limited importance for low position 244 agencies. A highly professionalized agency can develop extensive interactions when its work stimulates such transactions and the resources it has are needed by other agencies, but professional staff- ing does not lead to interaction unless other conditions are met. These data provide no direct information about the specific service delivery needs agencies have which stimulate exchanges with particular agencies but do show work is a factor in interaction patterns. Age is another clue to the interaction pressures generated by work or charter-domain factors. When Age is coupled with system importance and resources, then recently established agencies tend to have more interorganizational ties than the older group, but ability is a determining factor as well as Age. The data have shown that younger agencies cannot develop extensive interorganizational linkages only because of staff perspectives and desires or in response to stimuli from parent organizations or funding sources. In summary, these data have supported the first two parts of the model -- various aspects of service delivery and work-related- stimuli are connected with agency interactions, but ability (i.e., system-valued resources) is required before extensive interactions occur. Further, there is not a consistent relationship between organizational characteristics and either competition measure. Many organizations with valued resources are high in Actual Competition but other high ability agencies are not involved in a large number of competitive ties. This permits examining the effect of competition when ability is held constant. If competition is the spur to 245 interaction, high ability agencies with high competitiveness will be involved in more outgoing interactions than the ability group with low competition scores. Thus: H20 Considering work needs and resource levels, the higher the level of competition: a. The more extensive the interactions with other organiza- tions; b. The higher the level of COOperativeness; c. The more varied the relationships with other organizations. Table 46 showed consistently very high positive correlations between Actual Competition and the three general interaction categories, and high correlations between competition and Variedness.5 These relationships hold when Mode of WOrk is considered (Tables 48 and 50). Competition stimulates extensive interactions with other organizations, but it is particularly a factor in reference-group and Cooperative interactions (Tables 47, 49, and 51). The association with Simple Exchanges is less clear because these interactions are frequently part of the normal work of the organization and may not require purposive action by the agency or indicate dependency. Reference-group ties involve intangible transactions of influence, cooperation, support, and favorable opinion -- all resources needed to ensure legitimacy within the set of agencies and valued domain. Cooperation does require commitment of resources and at least partial surrender of autonomy, and thus clearly involves purposive and 5In these tables the organization-based measure is substituted for the choice—based measure of Actual Competition when needed to avoid the embeddedness problem discussed in Chapter II. 246 tangible exchanges.6 There are high positive correlations between Actual Competition and Cooperativeness in both cities,and when Mode is considered, this relationship holds for all cases except System B Distributive organi- zations (Tables 49 and 51); Ten of these are small Private agencies which are very low in valued resources (discussed above). For such agencies, competition cannot stimulate interactions. The relation- ships shown in Table 51 for Distributive agencies are reflected in the Public—Private scores shown in Table 58. These findings strongly support the idea that competition leads to planned interactions in- volving commitment of organizational resources. The more competitive the organization, the more likely it is to establish cooperative interactions and to develop highly varied interactions.7 There are high positive correlations between Actual Competition and Cooperativeness in both systems, and when Mode is considered, the relationship continues except for System B Distributive organiza- tions,and in B this type is very low in valued resources. For most agencies high Competition also leads to high Reference- group interactions, as expected, although the correlation for these variables for System B Treatment agencies is moderate, (.36), and for B Distributive agencies it is low (.20). These low correlations seem suprising as weak agencies might seek COOperation and support and 6Appendix B gives the questions used in these three aspects of the Resource Exchanges variable. 7Because of the nature of the design and the character of the variable Variedness, a high score indicates high number of coopera- tive interactions. 8Reasons for these relationships were discussed in the previous section describing Public-Private correlations shown in Table 58. 247 might want the good opinions of other organizations to gain stature. But information about the specific agencies involved leads to a different interpretation. The System B Distributive group (N=20) includes nine agencies which are low in Overall Importance ggd_very low in Sector choices -- they make fewer than 35 choices for the 19 interaction questions. They are very isolated. All but one of these agencies have either very strong private constituencies or an extremely secure public funding base. Three others are young and well funded. Thus, sixty per cent are very secure agencies, with minimal motivation toward the kinds of dependencies involved in Reference-group interactions. As discussed in the previous section, Table 58 gives additional confirmation of the general model. For organizations with generally valued resources, i.e., important to others in the set of agencies, high Actual Competition is very strongly correlated with the inter- action measures, and even in System B the Private agencies have high correlations between Actual Competition and Variedness, although the association with Cooperativeness is low. As noted in Chapter IV, these are the generally powerless organizations in that system. Thus, for System B organizations with ability, Actual Competition is highly correlated with interactions. The data for the Private agencies in City A do not permit concluding that ability is an inter- vening variable permitting high competition to lead to extensive interactions,because it is impossible to disentangle the valued re- source factor for Private agencies or compare High and Low Importance Private agencies. When all the information about resources of System A Private agencies as compared with System B Private 248 organizations is considered, the data do suggest ability is the determinant. The Counterpart data provides additional information per- mitting inferences. Table 9 gave the between-system correlations and showed high negative correlations for Public-Counterparts in both Actual Competition and Network interaction. System B's major public agencies are lower in both Actual Competition and interactions than A's, yet they have approximately the same resources when the general differences between the cities are considered. Differences in competitive interactions are associated with differences in the extensiveness of network relationships. Table 59 gives the mean scores for organizational characteris- tics and interaction levels under similar network position or im- portance by varying levels of competition. Although the figures do not permit t-tests, the pattern of the mean scores is highly suggestive. For High Importance organizations both Network and Sector inter- action levels are considerably higher in the High Competition state than in Low Competition, and the pattern of variances in other tables indicates these differences, except for Variedness, are probably significant. In System A the High Competition-High Importance agencies are larger but in System B they are considerably smaller, showing that the major Public-Distributive agencies in B fall in the Low Competition group, in contrast to A. When competition is high, Low Importance agencies in System A also have much higher inter— action scores than the Low Competition group. In System B the differences between the High and Low Competition groups are much less, and this seems to be related to ability. 249 TABLE 59 ORGANIZATION CHARACTERISTICS AND INTERACTION LEVELS, BY NETWORK POSITION AND COMPETITION, MEAN SCORES High Importance Low Importance High Low High Low Actual Actual Actual Actual Compe- Compe- Compe- Compe- tition tition tition tition System A (N=9) (N=8) (N=7) (N=9) Organizational characteristics Size 60.3 35.1 17.7 22.8 Service Diversity 6.0 5.9 5.3 4.8 Degree professional .55 .46 .42 .29 Felt Competition 2.43 2.19 2.95 1.82 Interaction characteristics Network interactions 56.2 30.5 49.0 24.2 Sector interactions 59.4 37.2 54.3 27.8 Variedness 14.9 10.2 14.3 9.0 Resource Exchanges 42.3 27.8 37.9 21.1 System B (N=12) (N=6) (N=7) (N=10) Organizational characteristics Size 19.5 45.3 10.6 17.0 Service Diversity 4.6 5.2 4.3 3.5 Degree professional .52 .47 .48 .47 Felt Competition 2.39 2.17 2.60 2.25 Interaction characteristics Network interactions 50.3 31.3 34.6 27.2 Sector interactions 53.9 41.7 36.1 30.8 Variedness 13.9 12.7 11.9 9.4 Resource Exchanges 30.1 23.3 17.4 18.5 250 These data consistently provide strong support for the hypothesis. When ability is present, the higher the competition, the higher the interaction level. Further, when coupled with ability, competition leads to cooperation,to deliberately planned resource acquisition transactions. 'The other two types of interactions, i.e., Reference-group and Simple Exchanges, seem to be the result of regular work or interdependence; cooperative transactions involve active, seeking behavior by the organizations. Blalock suggests we focus upon the "explanatory power of a number of independent variables taken together, rather than in the relationship between the dependent variable of each of the independent variables taken separately (Blalock, 1972: 454)." Table 60 presents squared multiple correlations for independent variables which seem to have the greatest significance. When Competition is combined with Importance (ability), a sizable percentage of the variation in inter- action patterns is explained. The combination of Importance, Com- petition, Auspices, and Size has more explanatory power in City A than in City B, but in both cities the combination of Importance and Competition has the greatest explanatory power. Considered together, these findings about the relationship of competition and interaction levels strongly support the general model and the specific hypothesis about the causal effect of high competi- tion on extensive interactions (H All social service agencies 20)' are involved in some inter-agency transactions. When an agency has resources others seek, outgoing interactions also are higher but outgoing interactions increase to an even greater extent when the organization is involved in a highly competitive environment. 251 TABLE 60 MULTIPLE CORRELATIONS City A City B Independent Variables to ‘ 2 2 Sector Interactions ' R R Importance 12 10 Plus Actual Competition 55 38 Plus Auspices 57 40 Plus Size 61. 45 252 Competition alone is not a sufficient stimulus for developing ex- tensive ties with other social agencies, but when the organization has bargaining power, then high competition leads to very extensive relationships, including establishing COOperative exchanges which involve a commitment of agency resources. Summagy This chapter examined system differences in interaction patterns and the relationship of the independent variables to the organizations' interaction strategies. When the systems are com- pared, the data show two major differences between these systems: (1) Competitiveness is much higher in System A than in B as measured by Actual Competition although reported competitive pressures are similar (Table 12). Even when very similar agencies are considered, there are sizable system differences in competitiveness (Tables 9 and 14). (2) Interaction levels are much higher in System A than in System B, including higher Resource Exchanges scores and higher Cooperativeness, and this is true for the highly similar Counterpart organizations as well. Thus, there is a system level relationship between competitiveness and the patterns of interorganizational re- lationships. One idea in the literature is that work-related factors stimu- late interorganizational relationships. This analysis assumes some interactions are part of the division of labor in this sector of local communities. Other interactions may be related to aspects of service delivery but are not primarily stimulated by client considerations. Instead, extensive interactions occur because of resource inter- dependence and needs of organizations for material and authority 253 resources. Thus, a series of hypotheses tested the importance of various charter-domain factors. As the pattern of the findings shows, the general type of work is not connected with the level of outgoing exchange relationships (Actor interactions), although it is a factor when incoming interactions (Target interactions) are considered and is, therefore, an important aspect of the organization's position within the system. Apparently, there is no group of organizations in either system which is stimulated by service delivery and client service pressures to be involved in an extensive pattern of both in- coming and outgoing relationships. (See Tables 39 through 44.) For many younger agencies there are pressures from funding organi- zations and their general orientation to service delivery to develop new patterns of services for clients and coordinated or integrated services. These data show that only some of these newer style agencies are involved in extensive interactions and cooperative relationships because some of them have very few resources other agencies value. They lack the ability to engage in interaction even when stimulated by service ideals (Tables 45 through 51). Whether these newer agencies develop extensive resource exchanges depends upon system conditions and their general standing in the community in addition to their specific programs and resources. An important part of this general model is that ability to attract interaction partners is a prerequisite to interactions. Further, even when ability is present, competition is £hg_major stimulus for interagency cooperation and extensive interorganizational relation- ships. In general, these data show that ability is an important determinant of interaction strategy, and organizations with command 254 over valued resources, or those with power, tend to be involved in more ties with other organizations than those with fewer resources (Tables 52 through 55). There are some organizations which do not fit this pattern; they have resources others want (high system position) but are relatively uninvolved with other members of the system. Some of these are the system dominants. The influence of staff on interaction patterns is difficult to judge. Clearly, the size of the organization is not related to its interaction strategy, but the degree the staff is professional does seem to be an important determinant. Because System B has so many very small agencies, it is best to test the relationship between staffing patterns and interaction strategy only in System A, and the data show that a professionalized staff is an important factor in establishing varied relationships with other conditions which stimu- late interaction are also present (Tables 46 through 51 and 56). Knowing that an organization has a high proportion of professional employees does not help identify its interaction strategy. In order to test the general model it is necessary to examine the effect of competition without considering ability. A series of steps in the analysis explored the relationship between competition pressures, reported by directors, the competitive behaviors of the organizations; and interaction strategies. (See Tables 58 through 60.) Because there are high correlations between Actual and Felt Competi- tion for some types of agencies and because of the relationship between Actual Competition and ability (or power), it is complex to examine the effect of competition alone. - 255 But, regardless of the difficulties, it is possible to see a con— sistent theme running through these findings which shows competition by itself does not lead to extensive interactions. Competitive pressures are not a factor in stimulating interrelationships. When Felt Competition is coupled with resources, but not with Actual Competition, then there are neglible relationships with interaction levels. When agencies are low in resources, neither high Felt Com- petition, nor high Actual Competition is related to interaction patterns. Although there are high positive correlations between Actual Competition and Cooperativeness, one reason for this is the correlation between power (ability) and Actual Competition. Organi- zations which are high in power 32d low in competitiveness have lower levels of interorganizational relationships than those high in power and high in competitiveness. The explanatory value of the two variables of competition and power considered together is very great (Table 60). By itself competition is not a sufficient stimulus to the develOpment of extensive ties with other agencies. By itself ability or power stimulates some interactions and even when competition is low, the interaction level is higher for organizations with system- valued resources than for those with fewer resources but high com- petition. Significantly, when the organization has bargaining power, then high competition leads to extensive relationships. Thus, the pattern of relationships shown by these data provide very strong support to the general model for this research (Chapter I). 256 CHAPTER VI SUMMARY AND CONCLUSIONS Introduction The problems under investigation in this study were the patterns and determinants of organizational interactions in two social service systems. Using information about 68 agencies in two middle size cities collected from interviews with the agency director, organizational records and a self-administered questionnaire completed by the di- rector, a series of hypotheses about interorganizational relationships were tested. The general model for the research assumes power and competition for resources determine interorganizational relation- ships in the social services sector, although it is recognized that some interactions occur because of the division of labor in this sector. Three general questions guided this analysis. 1. What relationships with similar organizations do social agencies develop? What are the interaction patterns in local agency networks? 2. What are the relationships between organizational resources, agency position in the organizational stratification system, and interactions with similar organizations? 3. How does competition for resources affect the pattern of interorganizational relationships in local social service systems? The research emphasized power relationships. Although the major focus of the analysis was on the interaction behavior of types of organizations within these two systems, characteristics of the systems were considered as well. 257 The findings provide very strong support for the general political economy framework, and the research strategy developed pro— vides a basis for additional work within this powerful integrative perspective. A series of hypotheses derived from major trends of past empirical work in this field received little support. Although organization size and domain are, to some extent, related to system power, when systems are compared, it is evident that similar organi- zations are positioned differently in social space or have different ecological niches within the systems. Conditions characteristic of the network as a whole are important determinants of agency inter- organizational relationships because system factors affect the organi- zation's needs and its ability to attract interaction partners. The data provided strong support for the idea that the configuration of an interorganizational network affects the interactions of individual member organizations (H. Aldrich, 1974). By using organization indicators and measures developed from sociometric choice questions, this research provides a workable way to conceptualize and measure a population of organizations in network terms and to develop network-level indicators. The pattern of these findings illustrates the need to move from a focus on individual organizations, perceptual measures, and internal characteristics and develop a body of data about the organization's primary environment, the network, and the impact of the group of loosely integrated members on the focal organization. This chapter reexamines some important aspects of system differences as these relate to organizational interaction behaviors and discusses the effects of power and competition on the structure 258 of local social service systems. Some implications of these data for social planning are considered, and a final section considers the contribution of this research to the thorny problems of methodology in interorganizational research. System differences and interorganizational relationship§_ The limited body of empirical findings in the interorgani- zational literature primarily focuses on Actor organizations seeking material and authority resources through exchange relationships with other social service organizations. There is little attention to relationships within systems of organizations or the impact of the system on the organization's interactions. This focus, by directing attention to the individual organizations, develops specific ideas about the effect of organization characteristics on exchange relationships rather than considering the organization's social setting as well. Yet, the literature pictures social service organizations embedded in a network of similar agencies, interacting with each other in the process of service delivery and seeking material and authority resources through exchange relationships with each other. The organizations are considered to be in function interdependence (i.e., interacting to attain work objectives) and to have resource interdependence because of resource allocation procedures. Thus, the network of other social service agencies is a key factor as organiza- tions seek to meet work and maintenance needs. But, if these organi— zations are members of interdependent systems, then characteristics of the network (their primary environment) will not only influence aspects of the organization's internal characteristics but will set the condi- tions under which interactions 332 occur regardless of organizational factors. 259 The focus on organizational characteristics is very limited. There is no reason to assume agencies can or do act unaffected by the social setting in which they operate. The open-system perspective on organizations assumes the environment influences organizational structure and process. These data go further to show the environment influences their external behavior. Further, there is no reason to assume social service systems are similar. These local systems are emergent phenomena and may very well differ in important characteristics. The pattern of inter- organizational relationships may be reciprocal or lopsided; the system may be dominated by a few members with subordinates interacting by indirect ties through the dominants, or there may be few dominants and members in contact with most other members of the system (Benson, 1974). The collection of services and programs offered by the system to local residents may vary since these reflect a series of historical decisions, and the system's domain produces a collection of needs and resources which may affect the ability of the Actor organization to develop resource exchanges with system members. The point is. V the nature of the systems may vary, and variations in system character- istics will necessarily affect the individual organization's inter- action behavior. Both the social setting and agency characteristics are related to interorganizational relationships. This research assumes both the larger society and the local community affect the characteristics of the systems and that system characteristics affect the individual organization in interaction. Because data come from only two systems, no hypotheses about the effect of community characteristics on the systems are tested. Instead, the 260 data are used to show there are important differences between these systems in service emphases, the allocation of resources within the systems, the relative position within the local hierarchy of similar agencies, degree of competitiveness, and the extensiveness of resource exchanges. These network differences relate to organizational power, and power is importantly related to interaction patterns. To illustrate, as the mix of services offered by systems varies, the resources needed by system members may differ. The agency's position in the organiza- tional hierarchy will be tied to the nature of its work, its function in terms of system needs, and does not depend only upon internal re- sources. The needs of the system as a whole have an important impact on the organization's ability to develOp resource exchanges. Chapter III described certain demographic differences which seem to be factors in the evident difference in service emphases, including: pressure from two minorities in City A instead of one as in City B; the different emphases in expenditures of public funds; various population differences in age, heterogeneity, and employment sites; and the unusual relationships between income and public assistance payments for Negro and Spanish families. These system differences in service emphases lead to a different set of needed resources for member agencies. The systems are similar in organizational composition (Tables 4 and 9) but differ in the rela- tive importance to the system of the various types of agencies (Table 6). System importance, or power, indicates ability to provide valued services and is a better predictor of interactions than the specific organization characteristics of size, staffing patterns, service di- versity, age, or sponsorship (Chapter V). 261 When the body of evidence is considered, it is clear that the agency's level of specific resources is not a determinant of either its power or its interactions, although size is a factor when coupled with valued functions. Neither type of work (Mode) or age is con— sistently related to network position or interactions. Public sponsor- ship is an important factor, and generally Public agencies are higher in position than the Private agencies, but this is because a large number of the Public group are those agencies which are the only source for key, basic, expensive services. Even when sponsorship is considered, system differences in the service mix seem to produceai different distribution of the variable Overall Importance (system position). For example, public sponsorship is not associated with Importance for Treatment agencies in System B but is in System A (Chapter IV). Several pieces of evidence in Chapter IV show that the type of services offered by the Treatment agencies in System B are not as required by system members as those services offered by the Distributive agencies, and the opposite pattern consistently appears in System A and Treatment agency services are more valued. I The study includes data from 21 agencies in each system which are chapters or offices of the major state and/or national agencies, and the differences associated with the system positions of these Counterpart agencies provide additional evidence about significant system differences. Although some of the Public Counterparts are very important in each system, when the other Public-Counterparts and the Private-Counterparts are considered, there are wide variations in system positions and interaction patterns. These Counterpart agencies provide similar services in each city and have the same general 262 domain, but for many their functions are differently valued by the other members of the system. System position, an indicator of system valued resources, is a measure of power showing command over resources. Throughout this analysis the data have shown differences in the types of re- sources valued by the members of these different systems, and this is connected to differences in the ability of organizations to deve10p resource exchanges. Thus, differences in needs within the systems translate into different interaction patterns for the member agencies. System characteristics as well as organizational characteristics determine interactions. Thus, the data support the idea that "within networks organizations differ in power, and some gain power over other members because of characteristics of the network (Chapter 1, page 28)." As Benson (1974) argues, there may be system-level differences in interaction patterns. These data show significant differences between these two systems. First, System B has a much lower level of interactions than does System A (Tables 10 and 11). In both systems a few large public agencies have high Target interaction scores (i.e., receive many sociometric choices) but in System B twice as many agencies receive fewer than 20 nominations as compared to System A (Table 10; A=8, B=l7). System A is characterized by a large number of social isolates. In addition, System A has significantly higher Actor interaction scores (Table 11). As noted in Chapter I, the exchange perspective developed by Levine and White (1961), and widely discussed and utilized, assumes 263 the needed resources exist in the system and can be obtained through interactions, that organizations will share resources, and that the system is roughly balanced. These data do not support that view of social service systems. Unless organizations are willing and able to exchange, resources cannot be obtained through interactions. These data show that relationships are very one-sided in both systems. Organization-set size in both systems is about 11 (Table 11), but the number of reciprocal relationships is much smaller (Table 61). In System A the mean number of organizations with which Actor organi- zations have reciprocity is about 6 and in System B only 3.5.1 Relationships are very one-sided in both systems. Some high position organizations make few outgoing choices, e.g., high diversity Treat- ment agencies and the major Public-Distributive agencies. Many organizations are rarely chosen by others. When linkages involving the mutual exchange of three or more of the 14 different resource exchange items are considered, the mean number of this type of strong reciprocal exchange is 2.48 for members of System A and 1.75 for System B members. Forty-eight per cent of the System A organizations are involved in three or more strong reciprocal resource exchanges as compared to 23 per cent in System B. In addition, the number of strong reciprocal interactions is larger in System A than in System B (A=82, B=62). 1Reciprocity is not limited to an exchange of the same re- sources between agencies. It is measured by the mutual set memberships over the entire range of interaction questions and does not imply similar resources are exchanged, e.g., information can be the resource identified in A's choice of B as a partner, but B may report A is a partner in competition or referrals. 264 TABLE 61 STRONG RECIPROCAL RESOURCE EXCHANGE INTERACTIONS, System A Number of strong recipro-‘ cal interactions -" 82 Mean number of strong recipro- cal interactions 2.48 Distribution of reciprocal scores Number Percent None 4 12% 1-2 13 39 3-4 12 36 5 or more 4 12 Total 33 99% BY SYSTEM System B 62 1.75 Number Percent 5 14% 22 63 6 l7 2 6 35 100% 8This measure of strong reciprocal interactions uses three or more mutual choices, or two-way exchanges, made for all the 14 (15 in B) resource exchange interaction questions. is based on one or more mutual choices. Reciprocity (Table 11) 265 Sociograms of the strong reciprocal ties among system members show both systems have inter-member linkages through a few dominant organizations (Figures 1 and 2).;2 The dominant organizations in System B have clusters of satellites which are rarely linked directly to other organizations (Figure 2). The pattern in System A also shows linkage through dominant organizations, but there are many more lines connecting member organizations which do not pass through the central members (Figure 1). In both systems when Public agency linkages are examined, sociograms (not included) show an elaborate maze but the Private agency interaction patterns are clustered around a few agen- cies. Private agencies are relatively unimportant to the Public agencies, and Public agencies are the major interaction Targets for Private agencies. The evidence from these two systems is that only some social agencies operate in a condition of high function interdependence. Sharing is not a widespread phenomena. A few agencies dominate the systems and can control access to needed resources. The overwhelming majority of agencies in both systems are involved in some resource. exchange interactions and indicate they are in competition with other agencies for resources. This confirms the view that social service organizations operate within a system, serving as input and output sources for each other (Parsons, 1956; Thompson, 1967), but members are not equally interdependent. Instead, the situation is one of subordination and dependency for a large proportion of system members... 21 am indebted to Werner Cheng for the preparation of these sociograms. 03‘ \v\\: .5 $ ‘9» ®@4 >:‘®®9 01-19,37=PRIVATE AGENCIES ao-¢o=rumc AGENCIES Figure 1. Strong reciprocal interactions, System A. 267 GE GE 0 0 623 e 0 46 ID 0 ID 31 69 623 01-30: PRIVATE AGENCIES 41-55: PUBLIC Icsuclis Q Figure 2. Strong reciprocal interactions, System B. AI 268 Competitiveness is another major point of difference between the two systems. Although they report similar perceptions about competitive pressures (Felt Competition), the level of Actual Competition is much higher in System A than in B (Table 12). There are large system differences in the competitiveness of the Counter- part organizations, and the inter-system differences reported by the Public-Counterparts are very great (e.g., A Public-Counterparts, 7.9; B Public-Counterparts, 4.8 (Table 14)). System variation is visible when organizations in the same Mode of WOrk are compared. In both systems Treatment agencies report a similar number of com- petitive relationships, but System A Distributive organizations are higher in Actual Competition than are System B's. Consistently, high competitiveness is associated with high interaction, and the effect of competition on interactions seems to hold regardless of system differences in the general level of competition or theAparticular resources valued by system members. When the systems are compared, the system with the higher competitive- ness is the one with more resource exchanges. Thus, at the system level the effect of competition on interorganizational relationships is apparent. A final point of difference. According to the political economy perspective, interactions stem from service delivery requirements and needs for material and authority resources. These two systems differ very significantly in the level of Reference-group interactions as well as in cooperativeness and competitiveness (Table 37). Thus, the systems differ in the extent agencies are in autonomy-related inter- actions. Since two-thirds of the agencies in each system have the same 269 general service areas (i.e., the Counterpart agencies), service de- livery interactions should probably be roughly similar, and the differences for the Counterpart agencies is further support for the idea that competition leads to more interactions in general. It seems to increase the normal work-related relationships, too. However, the number of planned interactions in either system is low. The social welfare literature leads one to expect a larger number of resource-seeking coordinated programs, but the number of joint programs and cooperative relationships is very low in these two systems. From the directors' descriptions of their agency's joint programs (data not included), the level of commitment and months of involvement in these programs seems extremely low.3 The evidence indicates interactions are quite minimal for some agencies but are extremely high for a small number. These data cannot explain why these systems differ. The significant point is they do differ. Most scholars describe the social service sector assuming there are similarities in agency behavior re- gardless of the agency's primary environment. For example, they assume family counseling agencies establish consistent links with youth service agencies and the courts and develop planned referrals and consultative agreements because of complementarity of functions. (See Black and Kase, 1963; Friesema, 1970; and the Klongdon-Beal series of papers for examples.) In this comparison of two systems these ideas are not supported; instead, the importance of system needs for agency behavior is clear. Although complementarity seems logically to lead 3This information is supplied by Bernard J. Offerman; see his forthcoming analysis of agency characteristics and joint programming. 270 to interactions, the low level of cooperation found indicates these expected links occur infrequently even though complementarity seems evident when lists of services organizations provide are examined. In summary, knowledge about characteristics of social service systems is essential in understanding the interorganizational re- lationships developed by social service agencies. The system itself, their primary environment, is an important determinant of each agency's interaction behavior. The traditional focus on the individual Actor organization misses the importance of organizational power which is determined by system needs as well as by agency characteristics. The social organization of organizations cannot be ignored as we seek understanding of organization—organization linkages. Power, competition, and interorganizational relationships This research shows power is an important determinant of inter- organizational relations. Some agencies have valued resources and are high in the organizational stratification system in the two cities. Command over resources, or power, is clearly a prerequisite for es- tablishing relationships with other organizations, although agency work and resource needs as well as competitiveness influence resource- seeking exchange behavior. Those agencies high in Overall Importance (the measure of position or power) can establish extensive relation- ships as they desire, and they seem particularly able to be involved in long-range resource acquisition relationships rather than the more limited service delivery exchanges. Those agencies at the upper end of each system are the ones which are high in reciprocity scores and 271 enter into cooperative relationships involving some surrender of organizational autonomy and an investment of agency resources (Chapter V). But, power does not seem to inevitably lead to extensive interorganizational interaction, as some organizations high in im- portance engage in a relatively low number of outgoing interactions (e.g., high diversity Treatment agencies and Public-Distributive agencies). Their work needs do not involve many outgoing (or.Actor): relationships. Except for the top dominant group, power is not a condition con- sistently associated with particular agency characteristics (Chapter IV). Instead, it is determined to a large extent by system require- ments. Some service areas, and the organizations mandated to provide them, are consistently powerful in these systems (i.e., the major public organizations responsible for income maintenance, employment, rehabilitation, health care, and psychiatric treatment). For the other organizations, network power is affected by the system's general characteristics and probably by conditions in the community, the secondary environment. These data strongly support Stinchcombe's model of an organi- zational stratification system in which a limited number of dominants control resources and can determine the behavior of subordinate members and entry to the system. The evidence does support the idea that social service organi- zations are in resource competition and engage in interactions to secure resources. Agencies vary in involvement in competitive re- lationships, and some report few competitors. In both cities Treatment agencies report more competitive relationships than do Distributive 272 organizations. Competition level does not vary by Auspices, although there are differences in reported competitive pressures between Public and Private agencies. Public agencies apparently Egg part of the general resource interdependence in this sector. Some Private agencies, expected to report high direct competition because of their funding base actually are low in competitive interactions, perhaps because of a secure area of work and minimal dependence on the others for resources. Although Actual Competition is not consistently related to specific organizational characteristics, there is evidence from these cross-sectional data that organizations with high resources also are high in competition. The overall model for this research assumes some interactions will occur regardless of either competition or ability because of the nature of the division of labor within the sector. It seems this level is minimal, and some organizations are very isolated from system members. Although competition is a stimulus to seek resources through interactions, because many relationships require ability or bargaining power before the organization is an attractive partner, unless the organization has something to offer exchanges will necessarily be limited, and probably they will primarily be Simple Exchanges or Reference-group interactions. The idea that valued re- sources are a necessary ingredient in establishing sustained resource acquisition relationships is strongly supported by these data. In general, outgoing interactions increase as importance within the system increases. Some agencies, low in system position and with few specific resources, may report fairly high competitiveness and be stimulated to 273 seek relationships but, because they have little to offer in return, engage in few interactions. (See System B Private agencies (Table 58).) The data presented to test H 0 showed consistently high positive 2 correlations between competitiveness and interaction strategies and strongly support the idea that competition leads to resource exchange relationships in which social service agencies seek both material and authority resources. Competition stimulates extensive interorggnir zational relationships at the individual organization level and the §ystem level as well. Even when variations in work-related needs and ability are considered, clearly competition is the spur for exchange- based interactions and undergirds these systems. The Counterpart organization data provide the best test of these ideas at the system level (Table 9), but the clear pattern is shown in other tables as well (e.g., Tables ll, 17, 37, and 60). Further, at the organization level those powerful agencies which are high in competitiveness have the highest interaction levels (Table 59). Thus, the data provide strong support for the general causal model relating competition for resources and organizational ppwer within the system (the ecolggical niche) to interaction stratggies. Longitudinal data are needed to show the relationship of competition to system position, but these cross- sectional data do show success in garnering valued resources does not mean the organization ceases to be involved in the competitive struggle. Competition and social service systems The model for this research is an extension of the evolutionary ecological framework and assumes a hierarchy of dominance will emerge from competition among organizations. Some of the organizations in local systems, unsuccessful in the competition for resources, will 274 merge with others or die. Others will become suppliers to the dominants as they successfully differentiate and develop the ability to provide other organizations in the system with needed resources. The dominants will need the resources of the subordinate suppliers and in response to the interdependence competition produces, organi- zations will develop coalitions (Marcus, Sheldon, and Adams, 1974a). These data show this process in two differing systems. In both there is a hierarchy of dominance; a few organizations are extremely powerful and can set the social situation of others (Hawley, 1950). (See Table 10 showing the distribution of Overall Importance scores and Table 30 showing relationship of dominance to specific resources.) Some organizations have succeeded in developing a strategic position through differentiation and provide the dominant organizations with needed resources. The sociograms illustrate this pattern of dominants and suppliers (Figures 1 and 2), but it is also apparent in the interaction scores of the important organizations which are non-diverse and the correlations between both network position measures and Resource Exchanges. (See Tables 47, 52, and 59.) Inter- dependence is produced by this process of differentiation in response to competition; it leads to coalition formation among competitors as shown in the correlations between competition and cooperative exchanges (Tables 47 and 58). By showing the relationships between competitiveness and cooperative resource exchanges, these data extend the model proposed by Benson and show how function interdependence results from an on-going struggle for resources, or competition. Conflict and competition may not be as dysfunctional for these systems as some fear. Competition is a stimulus to interaction and coordination. 275 Implications for social planning Increasingly, those interested in improving local human service delivery systems urge increased coordination among the various autonomous organizations which comprise such systems. Planners seek increased coordination for more efficient utilization of existing resources and more effective provision of services to users. The presumption is that integration of services will benefit both clients and those who must pay for the services.4 However, many, if not most, efforts at integrating the programs of autonomous organizations fail, and there is little information about the pattern of interorganizational interactions available for social engineering purposes. Thus, one purpose of this research has been to provide information about external and internal factors which may stimulate or prevent agency interaction to serve people. A great deal of information about agency interaction patterns has been included. These have shown that many organizations are involved in a wide variety of types of relationships with others and that organization-set relationships are complex. In contrast to the Litwak g£_§1 model, organizations are involved simultaneously in a variety of competitive, reference—group interactions, work-related exchanges,and coordinated relationships and have few reciprocated relationships. In general, there is a low level of cooperation in both systems when the ideals prevalent within the social work profession, the encouragement of policy makers and funding organizations, demands 4Alminority consider that coordination may lead to a stifling of initiative, rigid delivery patterns, and tighter, more oppressive social control through the central regulation of needed services. 276 from the general public and clients, and the function interdependence characteristic of this sector are considered. Agencies do not fre- quently surrender autonomy to others. It takes the strong stimulus of competition to establish service integration. The interorganizational relations literature frequently empha- sizes the importance of values, shared perspectives, domain consensus, and opinions about the complementarity of programs as determinants of interactions. Many efforts to increase system integration are built on the idea that educating staff members about the value of coordination, establishing communication links, and generally developing shared views about client needs will lead to more coordination among agencies. That approach assumes staff attitudes, especially the directors' perceptions, are important determinants of interactions.5 This re- search examined internal and external factors at the organization level which affect cooperation rather than examining social-psychologi- cal characteristics.6 Attitudes about the general profitability of coordination may affect interaction patterns, but attitudes about competition are not particularly good predictors of actual interactions, although competitive behavior is an excellent predictor. These data suggest that positive attitudes about cooperation may be a stimulus when the other conditions which lead to interactions are also present. Two primary variables, system power and number of current competitive relationships, do account for an impressive amount of the variance in interaction behavior (Table 60). 5Data about director and staff attitudes are not included in this analysis but will be reported in other papers. 6If the focus had been on social-psychological characteristics, the important relationships between competitiveness and cooperation would not be revealed because Felt Competition is a very unstable measure. 277 These data show the hierarchical arrangement of these local systems. Efforts to stimulate increased coordination need to recognize the dominance of these systems by a few major agencies, and use the patterns of dependency described in the analysis to stimulate greater service integration. Only a few agencies in the local systems are important. As their behavior is changed, the system can be changed. Appeals to service ideals made to the powerless, generally the private agencies, do not seem productive approaches or likely to lead to higher system integration. Knowledge of the impact of the period of establishment is im- portant for social planning. It seems the post-1960's group of agen- cies do develop more extensive relationships with the other agencies _if they have sufficient resources to attract interactions. If newer model agencies provide services valued by the other members in the system (and this may differ from system to system) and/or if they are a source for resources such as special contracts, they are able to establish extensive cooperating relationships. Without resource clout they do not succeed in developing coordinated programs even when charged with that task. Establishing new agencies, with resources, seems to be one means to increase service integration within local systems. It may not be necessary to establish new out-reach agencies. Providing existing organizations with the resources needed in the general competi- tive struggle would seem an equally fruitful approach. The dominant organizations can stimulate differentiation. There is a group of agencies in each system high in competition but low in resources, and as they are made attractive trading partners, integration will increase 278 as long as competition does not diminish. Competition can be used to stimulate differentiation. It may not be necessary to establish rigid delivery systems and increased central regulation which some fear. Instead, the nature of the systems can be utilized to stimulate greater differentiation and thus better service for local residents. Building upon these data about the hierarchical nature of social service systems and the effect of competition upon system integration, social planners should consider increasing competition within these systems by channeling additional resources through the dominant organizations with the requirement that funds be used for special contracts or differentiation. It is doubtful that an in- crease in coordinated services will develop as supplier budgets are merely increased and/or competition decreased. The importance differ— ences between these two systems, if supported by additional research on other local systems, indicate planning cannot occur solely at the Federal and/or state level but must build on knowledge of the local system.7 The hierarchical nature of these systems and the value of competition, then, have important implications for social planning and should be recognized and used. Problems in interorganizational research In the past several years a series of papers have (1) reviewed the same limited body of empirical findings about interorganizational 7In the field work phase of this study, I asked two planners in City A and one in City B to tell me the important agencies, asking "What agencies must be considered? Which might have a significant say in how things are done here?" The organizations they identified in these two systems are in the top group in the sociometric analysis, although in both cities two organizations were identified which our analysis indicates are low in importance. 279 relations and commented about various theoretical speculations; (2) bemoaned the missing theory base and the lack of agreement about concepts, levels of measurement, point of attack, etc.; and (3) urged more work in this field, extolling its significance for under- standing modern society and for applied purposes. Few have collected data to test the theoretical assumptions or grappled with the diffi- cult problems of methodology and research strategy. To date there seems to be no other research which compares social service systems. This design and analysis provides some workable approaches to data collection in this field and illustrates solutions to certain methodological issues. The problems facing researchers attempting such system com- parisons are formidable.8 In addition to the problems of theory, fully discussed in Chapter I, this field presents very difficult prob- lems of research strategy, methodology, and analysis procedures. First, the interdependent nature of the systems is difficult to manage. Almost simultaneous access to all members is required; agency personnel are frequently fearful of the way information will be used by research sponsors and fellow system members. The hierarchical nature of the systems requires enlisting the help of the dominant organizations to open doors to the subordinate agencies, but access is required to identify these agencies“ The necessary field work involved in access questions is expensive. In addition, the familiar problems of research legitimacy, persuasion at several levels, etc., amply described in the literature on organizations, are multipled tenfold when simultaneous access to the entire system is attempted. 8Some of these are more fully described in an earlier paper which goes into more detail about practical difficulties and possible solu- tions (Marcus, Sheldon, and Adams, 1974b). 280 Second, costs are high. This is true of all comparative re- search, but most of the comparative organization research examines a group of organizations (i.e., 50-300). For interorganizational system research, a sizable number of systems, each with many members, is required. This research strategy required extensive field work to identify possible organizations, develOp a comprehensive list of possible target organizations, adjust the instruments to local conditions, and translate the organizations' records into usable form. Data preparation is expensive as available computer programs for sociometric analysis require considerable hand preparation of the data, and the development of organization-level variables frequently requires hand processing. Third, selection of systems is difficult. What criteria should be used? Clearly, since the research target is the inter- organizational field, community environment must be considered. Turk's (1970) work indicates community structure significantly affects the structure of interorganizational relationships. The network probably responds to demands that vary over time and across cities. When data collection is restricted to a few cities, analysis requirements which relate to networks can conflict with a desire to examine the effect of community structure. And that means the cities selected should be dissimilar in some respects -— but in what re- spects? To insure comparability of networks the variance in types of demand should be minimal -- but how is this estimated? Finally, funding presents problems. Obtaining funds and sponsorship for such research is difficult because there are few pre- cedents to guide benefactors as to the importance of the work. 281 Possible funding sources include supra-organizations with an interest in affecting the network somehow; an applied emphasis must be built in. The aegis of the client may help access but hinder data gathering because resource shortages make agency personnel suspicious they_ will be negatively evaluated in comparison to other agencies. Suppressed animosities emerge; hidden agendas become visible; the findings can become weapons. There are difficult questions of feed- back and confidentiality at the respondent organization level, but it is more complex than that. Local umbrella organizations and public officials seem to fear comparison between cities, and system confidentiality becomes a problem. These are some of the research strategy questions. Of more importance are methodological issues. This design tackled a series of difficult questions. What is interorganizational level data? What are useful organization variables? How do you use information from one or a few respondents to develop organization-level variables, or do you sample the staff? How do you move past the dyadic level to focus on the network itself? What are valid indicators of inter- organizational linkages? How can processes and properties of inter- locking populations be studied? How do you handle the relative values of exchanges, or do you? What should be the focus -- the linkage itself or the organizations in interaction? What analysis techniques are suitable when you have a limited number of organizations and a very long list of seemingly important independent variables, or when you need partial correlations? This has been exploratory research. The goal was to investigate a wide range of phenomena which the literature indicates might be 282 connected to organizational interaction patterns. It uses organi- zational variables to concentrate on both system and organizational characteristics yet seeks to avoid the loss of richness and speci- ficity needed for theory development which sometimes is part of comparative research. For this project, local umbrella organizations and community leaders helped secure agency involvement and provided informants during the field work phase, but because their financial support was minimal made few demands on the design. Guarantees of agency and system confidentiality and promises of full reports helped with access (Chapter II). After one set of data (City A) was in hand, the second selection sought to minimize community differences. Unfortunately, funds were not available for extension to other cities. Although the research would be greatly improved if more systems were included, the decision to compare two systems rather than analyze the first and use data from the second for replication seems a sound one. It stimulated the development of system-level variables using aggregated organization-level data; it forced attention to variations in systems as these relate to organizational behavior; and required consideration of networks rather than organization-organi- zation linkages. Thus, these data from two systems can form a basis for additional studies examining system properties using these data for comparison purposes. Several aspects of this design are significant advances in the study of interorganizational relationships. The use of sociometric measures makes it possible to examine organizational power as a complex phenomena and use the system members perspective rather than 283 using the reputation or decision approaches. In addition, getting reports about other organizations from the respondent organizations avoids the problem of Actor distortions of their own behaviors. In— terestingly, preliminary analysis showed directors describe outgoing ties which go unreported by the identified partner. Sociometric measures seem to have greater validity than ego-organization reports. Second, the two measures of competition, perceptions and behavior, yield different findings. The behavior measure gets around the problem of acknowledging competition. Directors seem to experience no difficulty describing their competitive interactions and identify- ing competition-set members. While this approach may not include all the important aspects of the general state of competition underlying such systems, it is workable and seems to measure the concept fairly well. Further, the Target variable Competitor can be used to identify important system dominants, and systems can be compared using socio- logical data rather than self-reports. Aggregating organization reports permits designing inter- organizational variables for system comparisons, e.g., services em- phases and extent of duplication, distributions of financial and staff resources, prevailing attitudes and opinions (service climate, system norms, system needs), nature of linkages within the system (reciprocal, sequential, indirect, etc.) patterns of coalitions, prevailing patterns of interactions and organizational composition of systems. Once the focus is the system and data come from all members, the range of possible variables is extensive. 284 The device of considering the network to be the collection of organization-sets is very useful. Instead of focusing on characteristics of two partners, which tends to keep the analysis and interpretation on organizational characteristics instead of the organization-environment problem which is the subject of the research, the Actor organization's interaction pattern is translated into patterns at the system level. This research did not try to assess the values of exchanges but did try to identify types of resources. The focus in this analysis was the interacting organizations rather than the linkages. These data can be used to examine the linkages but this poses problems because of inflated Actor reports. An effective device is to examine the Target linkages. (See Marcus, Sheldon, and Adams, 1974a.) As part of the overall project, data were collected from agency staff to supplement the information supplied by the director as key informant. Getting a random sample of the employees of all these organizations proved to be very difficult and unless data are secured from all the organizations, analysis using the important sociometric measures is impossible. The practical route is to use the director, supplement that information with use of agency records as possible, and add a few additional key informants in large organi- zations. At this point in the development of the field there are few guidelines about useful organization variables. The high multiple correlations produced by using system position, competitiveness, sponsorship, and size indicate these are useful. Characteristics of staffing (i.e., professional ratio, administrative-clerical ratio, etc.) 285 can be used with organizations of 20 or more members but these local social services agencies are small, and these traditional measures are distorted. In addition, it is difficult to know how to examine the internal structure of such small organizations, although this seems an important research approach not attempted at this time. This re- search avoided using opinion/attitude/perception measures such as domain-consensus, attitudes about problems in coordination, etc. be- cause these do not seem to be organizational variables. A needed measure is service complementarity, but this is difficult to operationalize. One obvious limitation of these findings is that they do not permit longitudinal analysis, and the model obviously assumes come petition and differentiation occur over time. In addition, it may seem from this analysis that organizations are pictured dependent upon network factors, passively responding to environmental conditions, drifting, masterless (Perrow, 1972). However, the overall project assumes an interplay between internal and external factors shapes the community's social service system. Analysis of internal structures is the subject for another report. To conclude, this exploratory-project collected data about interorganizational relationships and social service systems from two middle-size communities. The findings provide a base for others to use for comparison purposes. Replication of this design could be a way to secure comparative data within current funding restrictions. The difficulties of comparative research on systems are obvious but the need for system data is equally obvious. Meyer (1972) seeks to extend the information collected about 254 finance departments by 286 using "the most different systems" method advocated by Przeworski and Teune (1970) comparing social systems (organizations, communities, societies) which are maximally different with respect to theoretically significant variables. In this model, if "similar patterns of relationships among variables hold across maximally different systems, it is presumed these relationships hold for all systems (Meyer, 1972: 104)." Without a larger data base it is difficult to see how this approach could be used -- what are the theoretically significant variables? Information from more systems is required. In this research a series of interorganizational level variables were developed and a start made on conceptualizing systems and identifying and measuring system characteristics as well as organi- zational interaction patterns. The general theoretical model received strong support from the data indicating this approach, which builds on a body of empirical work and parsimonious economic and ecological theory, is a productive one. APPENDICES APPENDIX A DEFINITIONS 287 APPENDIX A DEFINITIONS Organization or agengy Criteria for inclusion as an organization in the study of private and public social agencies include: Private Agencies - The agency must be a formally organized, task-oriented group which provides at least one social service as defined in the func- tional budgeting guide of the United Way of America (UWA). The agency should be generally regarded by local social planning professionals as having its main objective providing social services to people. The services can be at the individual or group level and can include helping individuals and families in solving problems, working with groups to attack common problems, or responsibility for planning for the provision of social services. Since the primary purpose of the organization must be directed toward the type of services described in UWA guide, for purposes of this project, organizations and agencies primarily offering services and programs in the field of health, education, recreation, and law enforcement are excluded even though such agencies may also offer social services. All members of the local United Way organization are included regardless of the orientation of the services they offer. In other cases, the organization must have a paid, full-time-equivalent staff of at least five persons and an annual budget of at least $10,000. The work of the staff must be primarily directed toward the provision of social services (see above) and the staff must work directly for this organization in carrying out the policies and programs determined by this organization's governing body. The organization must have its own policy making body (Board, Commission, Council, Committee) with power to hire and fire the top staff and to determine allocation of funds. The policy making body must be independent from other Boards or Commissions in allocation of funds and making staff decisions without review. It must be composed of people from more than one organizational source or elected from some governmental jurisdiction through a formal process. This means an organization with Board members from a single source is excluded (e.g., church organization, union agency). Public Agencies - Organizations primarily dependent upon tax funds, federal, state, regional or local which have as their major function provision of social services as described in the UWA guide are included. Funding sources may also include contributions and grants from'non-public sources. Agencies which are local offices of federal and state agencies are included as are local organizations considered by local planning professionals as meeting the definition of social agency detailed in the definition of private agencies. gpmponent programs identified as orggnizations for this study - The pro- gram must employ five full-time-equivalent paid staff and have a yearly budget of at least $10,000. The director must have the power to hire and 288 fire staff without consultation with the parent organization and con- siderable freedom to determine funding allocations. There may be a semi— autonomous governing body and must be some sort of Advisory Board with representatives selected according to details under private agencies. A generally recognized community visibility as an agency is important in determining qualification. This means agencies which once were inde- pendent organizations and which are now included within the new umbrella- type public agency are considered separate organizations for purposes of this study. New organizations which are considered agencies by local planning profeSsionals with representatives involved in community efforts to develop services are included also. Organization—set The group of organizations in an organization's environment with which it interacts as it seeks to attain its own objectives and to secure resources. More narrowly, the other local social service organizations a focal or Actor organization identifies as linked to it by transactions, exchanges, or relationships involving one or more resources. Resources Resources are the tangible and intangible elements an organization needs to continue to exist and to achieve its specific objectives. For social service organizations these include clients, money, staff with necessary skills, space, equipment, information, a valued domain, as well as less tangible elements as community support, prestige, political leverage, and recognized domain. Transactions or relationships Reports of exchanges of tangible and/or intangible resources between two or more agencies. Organizations are involved in these transactions as -- Actors: Focal organizations; reporters of choice-of-others behaviors in the various transactions; as 'ego'; Targets: Recipients of the choice behaviors of other organi- zations in the research; the 'alter' role. Types of transactions are: Competitive, Cooperative (requiring planning and commitment of some agency autonomy), and other Non-competitive ex- changes involving reference—group type relationships (exchanges of influ- ence) and simple exchange relationships (those which do not require planning or surrender of agency autonomy and limited to client referrals, information exchanges, and help for agency in delivery own program.) APPENDIX B QUESTIONS USED IN DATA COLLECTION 289 APPENDIX B QUESTIONS USED IN DATA COLLECTION Variables Questions Size and Professional ,,- Ratio Part III: 1. a. How many paid staff positions ‘ does your agency have? (Please express part—time positions in full-time equivalents) b. How many are administrative positions? c. How many are professional positions? d. How many are clerical-technical positions? Auspices Part III: 15. Approximately what percentage of your total income or revenue came from public sources? 16. Approximately what percentage of your total income came from non- public sources? 18. What percentage of your 1972 regular allocation: a. Came from federal funds? b. Came from state funds? c. Came from local (city or county) funds? 19. During 1972 did your regular allo- cation include any non-public funds? Yes No If YES, please identify the sources and proportion of total in each case (Estimate if necessary) (list of private sources was given ‘with room to indicate if each was a source and proportion) Service Diversity Part I: 1. What are the major services and programs offered by this agency? (up to 8 programs were codes) 290 APPENDIX B (continued) Felt Competition II: 3. To what extent is there competition between your agency and others for the following resources? CHECK ONE ON EACH LINE responses included: very great extent, great extent, some extent, slight extent, no extent a. money from United Way b. professional staff c. prestige in the community d. good board members e. technical assistance f. funds from the state g. funds from the federal government h. clients 1. money from the community j. other programs of sponsoring organizations Interaction questions Competitive inter- I: 9. Which agencies compete with yours for actions resources in this community? (five responses coded) 14. Which of these agencies are most likely to get money from the same sources as you do? 5. Which agencies provide services that are similar to those provided by your agency? 26. Which agencies on the list have Board/ Commission members also on your Board/ Commission? Cooperative inter— 15. Do you share staff with any other organi- actions zations? IF YES, which ones? 16. Do you share facilities with other organizations? IF YES, which ones? 17. ‘With which organizations do you jointly seek funds? ' 23. With which agencies do you do joint planning? 18. Please identify any agencies you run programs‘with. 291 APPENDIX B (continued) 19. And any that run programs for your agency? 24. Which of these agencies have upper eche- lon staff serving with you on community or regional committees? 20. With which organizations do you have formal contracts? (City B only) Reference-group inter- 8. Which agencies provide you with coopera- actions tion and support for your programs? 10. Which agencies have influence over what goes on in your agency? 11. Which agencies' good opinion of your work is important to you? Simple Exchanges 4. Which of these agencies are the ones to which you refer most pe0ple? 7. Which agencies make referrals to your agency? 6. Which agencies do you rely on to provide services that help you deliver your own programs to people? 12. With which agencies do you exchange opinions, information and ideas? APPENDIX C DISTRIBUTION OF INDEPENDENT VARIABLES 292 >wwMZUHx O UHmeHwCHHOZm ow qumwmzcmza <>wH>wfimm noannHmon I om Hmomm on x m.u. dmnHmcHHHnw KmaHmo wmnmm BHamHo won . wrote OdmanH Havonnmoom anw > um.o uN.b .mw um uIHmH NHIbN . .wm OHnw w Nm.o NN.» .Nu No NIHow HeINo H.NH moomm om Hamonnmoom . anw > HN.» b.H .uH H» NIHN oIHm .bu OHnw m HN.o u.c .NN HH eIHo HOIHw .uu Haoonnmbom mm cosmoanon anw > o.m e.H .oc u OIHN wIHo III oHnw w m.m w.¢ .mo m OINm bIm .bN Hamonnmnnm mm wmmocuom mcovHHmH OHnw > NN.H No.u .ow No NIHom Hmem .uN anw w Nw.m No.m .mm HN NIwu claw .ob mHum 0Hn% > wu.m be.u H.Ho Nm wINHm HNIbw .me OHnw w NH.» N¢.N H.NN Hu wIHmo mINm .mo common onommmmHosmH OHnw > . .bw .Hu .bo .em .HOI.N> .NoI.mm .mw OHnw m .eo .Ho .uu .wo .ooI.m¢ .BwI.oN .Ho mmndHnm UH m.m N.» .me a HIHN blu .oN anw w b.m H.u .mm m HIm bIm .mm mmHn ooBmmanHoo oHnw > N.bH .oH .um N.bb HOOIaoo HBBIwHH .Ho oHnw w N.Sm .mu .wo N.Ne HOOINNN HmquHH .NN >oncmH noaomanHon anw > m.m e.m .mm 0.0 OIHm bIHo .uu OHnw w m.m w.» .oN m.u OIHe ula III smwmssmmm I amiss m LI ST OF REFERENCES 293 REFERENCES Adamek, Raymond J. 1975 "Interorganizational Research: Some Perspectives and Findings," Paper presented at Annual Meeting of the North Central Sociological Association, Columbus, Ohio (May). 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