.1. .k 1. \I..PV.1., A: . ..§+...r~..unv:sv.& ~ fifi..;d..:.tw\....o .hvutco "..q‘. p!“ . ,xw‘:$n a ."v" 6"“ flun'i .v’ . . v'.r,.clo.t #1.. 2?, ‘. ”An/,3“ "" 35C? -vvv- - $ . . P1; .. . .. It." ..:u ”L. .. . . i, I. plan. n ‘. 3‘ V."va 1-7 eva u- “- ..1 II, 1... . I r . . -r: 7 yrs. Bu::.!>f . ‘ ‘ :10“ . .. .. c 5.1» .o .46 .3 r8: )I‘..«ofll $.11 5...!5: .. . 32-3-, A GI.}'. r).vr-‘In1ll‘. .H Pu {L .. . a- Ann? ”:1. 0 ML). -.rf..u. 1.1? .3: . . \‘.\;£ I “V. I1 “I .L. ;P;..:12,, . . ....x ‘ . U . r t . .5 nit-3. .......... 095.4. b Hunt...) , . . Tut . . v . ‘ m . n V I .I‘ o , . .. .. A . y . , g \3‘.‘ ‘1. {(15.11 ir .n A F V . . . r. fifihhi. .31," ..?‘.AV “HI... “ . . . . Int. .3. 1.)" b y ‘ . 4 n '4 . . in... iv” '1 ti 2. \t‘ r u w . . v .33? . , _ ‘ . . . _ "n... . ‘ W" b. A - ,z ; ea... 9.45.. E .1? us}! I. ”W282. ‘2 .y , u. ‘ . , . . a , OI- . . .. . . .. . . b . . v . . .. I)! I . c... In . . . ‘ . . PI} I u.. a .. ‘ ‘ V r. .r...».:.........--ur£..i V . ‘ . ,. .. .. x... ».....m.hm. w... 11“. . . . . , . (It. . ‘7 l‘. .‘ .4 .\. r. , ‘ a. :3; . . . . .. .. . 8%,; an . .u, ,v A 1.! \Il. v . . . Il" u \ 'u‘ ‘ ‘1’ ’ I 7 ‘ TAT NIVERSITY LIBRARI leD%31V mm '1“; WWHWWMW 3 1293 00605 9632 LIBRARY Michigan State University This is to certify that the thesis entitled AN A'I'I'RIBUTION THEORY APPROACH TO BUSINESS PLANNING AIVDNG TOURISM-DEPENDENI‘ RETAILERS presented by BRIGID M. HART has been accepted towards fulfillment of the requirements for M.S. degree in Merchandising Management MajJr profesfl Date W 22/ /?70 0-7639 MS U is an Aflirmatiw Action/Equai Opportunity Institution PLACE IN RETURN BOX to romovo this checkout from your record. TO AVOID FINES return on or before data duo. DATE DUE DATE DUE DATE DUE MSU Is An Affirmative AdiorVEqual Opportunity Institution AN ATTRIBUTION THEORY APPROACH TO BUSINESS PLANNING AMONG TOURISM-DEPENDENT RETAILERS By Brigid M. Hart A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Human Environment and Design 1990 ABSTRACT AN ATTRIBUTION THEORY APPROACH TO BUSINESS PLANNING AMONG TOURISM-DEPENDENT RETAILERS By Brigid M. Hart The purpose of the study was to determine whether retailers in tourism-dependent areas use a different approach to planning than retailers in nontourism-dependent areas and further, whether the type of planning utilized by retailers leads to successful business operations. Data for this study were collected by a structured self-report survey instrument. Retailers that participated were selected from communities located in the northern-lower and upper peninsulas of Michigan. A control sample of nontourism-dependent retailers was used to make comparisons with tourism-dependent retailers. Findings of the study revealed the majority of retailers located in tourism-dependent areas did not view themselves as tourism- dependent. Additionally, it was found that tourism-dependent retailers' planning practices were not much different than other small businesses despite differences in business environments. However, tourism-dependent retailers were found to participate in more short-range, informal planning as compared to nontourism- dependent retailers. TABLE OF CONTENTS Page List of Tables .......................................................................................................... vi Chapter INTRODUCTION“, ....................................... 1 Statement of the Problem ........................................................... 2 Justification ........................................................................................ 2 Research Objectives ........................................................................ 3 Conceptual Framework ................................................................. 4 Attribution Theory- - -- - ----- -- ---5 Attribution Theory Process ........................................................ 8 Application of Attribution Theory ........................................ 1 1 Relationship Between Attribution Theory and Strategic Planning ..................................................................... 13 REVIEW OF LITERATURE ............................................................... 1 7 Economic Significance of Tourism in the United States ............................................................................... 17 Economic Significance of Tourism in Michigan ................ l 9 The Tourism Retail Industry ................................................... 2 0 Effects of Seasonality on Tourism ...................................... 21 Impact of Tourist Area Image ............................................. 2 2 Importance of Political Climate in a Resort Area ........ 23 Lack of Knowledge About Tourists .................................... 2 3 Maturation of the Tourism Market ................................... 2 5 Strategic Planning ........................................................................ 26 Strategic Planning Defined .................................................... 26 Strategic Planning and the Small Business .................... 27 Differences Between Planning for Small and Large Businesses ................................................................... 3 1 iii Strategic Planning for the Small Business ...................... 3 2 III. METHODOLOGYANDPROCEDURES -- - 3 4 Research Design ............................................................................ 34 Research Objectives ..................................................................... 3 4 Methodology ................................................................................... 35 Questionnaire--- -- -- - -- 35 Sample Selection ........................................................................ 3 6 Data Collection---- ------- - - -- - ------37 Theoretical Definitions - - -- 3 8 Operational Definitions .............................................................. 3 9 Hypotheses ...................................................................................... 3 9 Group 1 - -- --------40 Group 2--- -- - -- -----40 Group 3 .......................................................................................... 42 IV. RESULTSANDDISCUSSION ........................................................... 43 Introduction - -- -- - ----- -- ------- ---43 Sample Characteristics ............................................................... 43 Retail Classification ................................................................... 44 Annual Sales Volume-------- ------- ----- 44 Length of Time in Business ................................................... 4 7 Legal Form of Ownership ....................................................... 4 7 Business Definition - - -- ------- --_48 Place of Business - - ------50 Statistical Results of the Hypotheses -- 51 Group 1 Hypotheses ................................................................. 51 Group 2 Hypotheses -- - -- - - ----56 Group 3 Hypotheses - -- - - -- -------- 71 V. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ...... 8 2 Summary of Research Methodology and Data Analysis .............................................................................. 82 Summary of Findings ................................................................. 87 Importance of Tourism Trade to Different Types of Retailers Within Tourism-Dependent Communities ---------- - ----------------- - 8 7 Differences in Business Planning Between Tourism- Dependent and Nontourism- Dependent Retailers ............................................................ 87 iv Relation of Selected Dimensions of Business Planning (Locus of Causality, Controllability, and Stability) to the Financial Performance and Level of Planning Among Tourism-Dependent and Nontourism-Dependent Retailers ......................... 8 8 Conclusions ...................................................................................... 8 9 Limitations------ - ---------- - 9 3 Recommendations ........................................................................ 9 5 APPENDICES .......................................................................................................... 9 8 A. QUESTIONNAIRE ................................................................................ 9 9 B. STANDARD INDUSTRIAL CLASSIFICATIONS ...................... l 0 6 C TABLES ................................................................................................ 1 0 8 D. CAUSAL ATTRIBUTION RATINGS ............................................ 1 1 3 REFERENCELIST ................................................................................................ 1 l9 Table 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 LIST OF TABLES Page Comparison of Samples: Retail Classification of Businesses Within Tourism-Dependent and Nontourism-Dependent Locations .............................................. 4 5 Comparison of Samples: Annual Sales Volume of Retailers Within Tourism-Dependent and Nontourism-Dependent Locations .............................................. 4 6 Comparison of Samples: Length of Time in Business of Retailers Within Tourism-Dependent and Nontourism-Dependent Locations .............................................. 4 8 Comparison of Samples: Legal Form of Ownership of Retailers Within Tourism-Dependent and N ontourism-Dependent Locations .................. . ........................... 4 9 Comparison of Samples: Business Definition of Retailers Within Tourism-Dependent and Nontourism-Dependent Locations .............................................. 4 9 Comparison of Samples: Place of Business of Retailers Within Tourism-Dependent and Nontourism- Dependent Locations ........................................................................ 5 0 Comparison of Research Classification and Perception of Tourism-Dependency for Retailers Within Tourism-Dependent Areas. ........................................................... 55 Questions Used to Measure Operational Planning. .................. 5 8 Summary of Analysis of Variance in Operational Planning for Tourism-Dependent and Nontourism- Dependent Retailers by Form of Ownership, Place of Business, and Type of Business ................................................... 6 2 vi 4.10 4.11 4.12 4.13 4.14 4.15 5.1 3-1 C-l Questions Used to Measure Structured Planning ..................... 64 Summary of Analysis of Variance in Structural Planning by Tourism-Dependent and Nontourism- Dependent Retailers.-- ---------------- - ---------- 65 Summary of Analysis of Variance in Structural Planning for Tourism-Dependent and Nontourism-Dependent Retailers by Form of Ownership, Place of Business, and Type of Business ....................................................................... 6 9 Summary of Variables Used to Measure Causal Attribution Dimensions. ................................................................. 73 Summary of Analysis of Variance in Operational Planning for Retailers by Controllability, Causality, Stability, and Perceived Tourism-Dependency. ................... 77 Summary of Analysis of Variance in Structural Planning for Retailers by Controllability, Causality, Stability, and Perceived Tourism-Dependency. ................... 80 Summary of Hypotheses Testing. ................................................... 85 Standard Industrial Classification Major Group Codes ...................................................................................... 107 Comparison of Research Classification andRetailers' Perception as Tourism-Dependent. or Nontourism- Dependent ......................................................................................... 109 Summary of Analysis of Variance in Operational Planning by Tourism-Dependent and Nontourism- Dependent Retailers ...................................................................... 110 Summary of Analysis of Variance in Financial Performance of Tourism-Dependent and Nontourism- Dependent Retailers by Operational and" Structural Planning Level ................................................................................. 1 l 1 vii C-4 Summary of Analysis of Variance in Financial Performance of Retailers by Controllability, Causality, Stability and Perceived Tourism- Dependency ...................................................................................... l 12 D-2 Results of Expert Panel Categorization of Variables Measuring Controllability, Causality and Stability ............................................................................................ 118 viii CHAPTER I INTRODUCTION The tourism industry has become a major contributor to the economy of the United States as well as to that of Michigan. Tourism-related spending in the United States during 1986 was $269 billion (US. Travel Data Center, 1986-87). In 1985 the tourism industry in Michigan generated $12.6 billion making tourism the third largest contributor to the state's economy (Murgittroyd, 1986). In addition to generating revenue, the Michigan tourism industry supports 295,000 jobs (Whisenhunt, 1987b). Integral to the functioning of the tourism industry are the businesses that support it. Travel related businesses in the United States are comprised of over one-half million firms, of which 98% are classified as small businesses (US. Travel Data Center, 1986-87). Retail establishments represent a major component of these small businesses. The typical small business size and unique characteristics of the tourism market combine to create many obstacles to the successful operation of tourism-dependent businesses. These businesses function in highly seasonal markets within limited geographic areas with specialized products aimed at small market niches. Tourism retailers are faced with short planning cycles due to highly competitive business environments and dynamic consumer markets (Schwaninger, 1986). Additionally, they function with limited resources and as a result are unable to cope during extended periods of poor economic conditions (Manning & Powers, 1984; Meidan, 1986; Mill & Morrison, 1985; Scarborough & Zimmerer, 1987). Although the use of systematic business planning has been shown to be effective in dealing with these unique characteristics, research has shown that most small businesses do not utilize formal business planning (Bracker & Pearson, 1986; Robinson, Jr. & Littlejohn, 1981; Robinson, Jr. & Pearce II, 1984; Sexton & Van Auken, 1982, 1985). W Small tourism-dependent businesses lack resources to conduct, interpret, and apply research to investigate how the unique tourism market environment affects their businesses. Additionally, there has been little academic research investigating factors related to the successful operation of tourism businesses. Consequently, many tourism-dependent businesses end up being reactive rather than proactive to changes occurring in their market environments (Mill & Morrison, 1985). Therefore, an analysis of the level and sophistication of business planning utilized by tourism-dependent businesses is needed in order to develop planning strategies which will aid in the successful operation of these businesses. IT" A myriad of studies have been undertaken examining tourists and the economic and social affects of tourism. However, few research studies have investigated the businesses involved in the tourism industry. Of those studies undertaken, the primary focus has been on large scale tourist businesses (Rovelstad, 1981; Rovelstad & Blazer, 1983). In view of the fact that 98% of tourism- dependent businesses are small, a significant portion of the industry has been overlooked from a research standpoint (US. Travel Data Center, 1986-1987). Rovelstad and Blazer (1983) suggest that the tourism market is now entering into the mature stage of the product life cycle. This market is characterized by increasing competition and a slackening in overall demand growth. Travel figures for 1986 illustrate this trend by revealing that overall travel volume in the US. fell 2.3% from 1985 (US. Travel Data Center, 1986-1987). As the tourism market continues to mature, research identifying successful competitive strategies will become crucial to tourism-dependent businesses (Rovelstad, 1981; Rovelstad & Blazer, 1983). Not only will tourism businesses be faced with increased local competition but they will also have to compete for the increasing amount of discretionary money being spent by potential tourists on durables and alternative recreational activities (US. Travel Data Center, 1986- 87). Therefore, more research is needed to identify those factors that will enable tourism-dependent businesses to operate successfully in a highly competitive environment. B l 01' 'v The overall intent of this study is to determine whether tourism-dependent retailers are different in their approach to business planning than nontourism-dependent retailers. The research objectives for this study are to (1) determine the relative importance of tourism trade to different types of retailers within tourism-dependent communities, (2) compare and contrast differences in business planning between tourism-dependent and nontourism-dependent retailers, and (3) determine the relation of selected dimensions of business planning (locus of causality, controllability, stability) to financial performance and level of planning sophistication among tourism-dependent and nontourism- dependent retailers. W This study will utilize attribution theory as a conceptual framework for investigating the systematic planning factors utilized by retailers located in tourism-dependent areas. Attributions are the result of cognitive processes which allow an individual to understand the cause of observed events, to assess responsibility for particular outcomes, or to assess the personal qualities of an individual involved in an observed event (Jones & Davis, 1965; Kelley, 1973). Planning strategies utilized by businesses reflect how they perceive and evaluate the linkage between events and possible causes (Daft & Weick, 1984). Research has shown that the attributions of decision makers are used in this causal reasoning process (Hedberg, Nystrom, & Starbuck, 1976; Fink, Beak, & Taddeo, 1971). Specifically, these attributions form the basis for decision makers to take action, that is, initiate plans (Daft & Weick, 1984). Therefore, investigating the planning strategies of businesses facilitates an understanding of the causal schemata of these attributions. E 'l . II Attribution theory has evolved from a body of social psychological research directed at explaining how individual's perceptions of the causes of behavior and events influence them in resulting reactions. The theory is based on the concept that individuals are motivated to understand the causes of behavior and events in order to better control and predict the world around them. The framework for attribution theory can be found in the work of three primary researchers: Heider (1958), Jones and Davis (1965), and Kelley (1971, 1973). Each of these researchers has focused on different dimensions of the theory and therefore has developed contrasting perspectives on the attributional process (Baron & Bymc, 1984). Fritz Heider is credited with the original formulation of attribution theory. Heider‘s (1958) work centered on understanding "common sense psychology", that is, how people attempt to understand the world around them in order to reduce uncertainty and increase predictability and control (p. 146). The following three concepts were utilized by Heider to explain how this process works: 1. The person who was making the observation (p) was distinguished from the person being observed (0). 2. The action that was being observed could be classified as emanating from either (p) or (o). 6 3. The direction of the action could be either from (p) to (0) or from (o) to (p). In his theory, Heider postulated that an observer (p) perceives the behavior of another (0) and then attempts to understand that behavior through a determination of its intent and cause. The causal source and direction of the action being observed affects this determination process. As a result, the perceiver (p) discerns the other's (o) behavior to be either intentional or nonintentional and caused by internal personal factors such as personality traits or ability or external environmental factors such as social pressure, luck or task difficulty. Heider also pointed out that this attributional process is subject to dispositional properties of the observer such as desire and pleasure, sentiment, ought and value, and benefit and harm (Heider, 1958). Harold Kelley (1971, 1973) elaborated on Heider’s original theory by investigating the information needed by an observer to assign causality of another's behavior to internal or external factors. In his work, Kelley referred to the person making the observation as the observer and the person being observed as the actor. Kelley theorized that an observer uses three kinds of information when determining the cause of an actor's behavior: distinctiveness, consistency, and consensus. These terms were defined by Kelley in the following manner. Distinctiveness referred to the extent to which an actor reacts in the same manner to different situations. Consistency was a measure of how uniform an actor's performance was on the same task over time. Consensus dealt with the extent to which an actor reacted in the same manner as the observer would in a particular situation. Kelley theorized that as a result of analyzing these three factors simultaneously an observer could attribute an actor's behavior to internal or external factors (Kelley, 1973). Kelley's theory and resulting research lead him to conclude that an observer would be most likely to attribute an actor's behavior to internal causes if there was low consensus, high consistency, and low distinctiveness. Alternatively, an observer was most likely to attribute an actor's behavior to external causes if high consensus, high consistency, and high distinctiveness were present. In addition, an observer was most likely to attribute the behavior of an actor to a combination of these three factors when there was low consensus, high consistency, and high distinctiveness (Kelley 1971, 1973). In sum, Kelley argued that causal attributions provide the impetus to act and form the basis for deciding among alternative courses of action. Jones and Davis (1965) focused their research on the intentionality dimension of behavior causality. They contended that observers make inferences about a person's behavioral intentions and utilize these inferences to form dispositional perceptions. In other words, an observer links perceived intentions of an actor's behavior to perceived corresponding personal traits of the actor (Jones & Davis, 1965). This association is more firmly established when the actor's actions will directly impact the observer either positively or negatively. The strength of the association between behavioral intention and disposition is also affected by the observer's perception of the action occurring by choice and the distinctiveness and social desirability of the action (Baron & Byrne, 1984; Hewstone, 1983). ' Attribution Theory Process Although these three researchers differ in their approaches to understanding the attribution process, they all agree that a systematic attributional process is undertaken by people in an attempt to better understand, predict and control their interactions with others and their environment. A critical dimension of this attributional process is that individuals are motivated to control their environment and that this motivation affects the way they explain and act upon events that occur at the personal, interpersonal and intergroup levels (Bains, 1983). A This attributional process involves the following basic steps: (a) the observation of an action, (b) the inference of intentionality, (c) the attribution as to internality or externality, and (d) a response based on the attribution (Mitchell & Green, 1978). The control dimension of attribution theory has been investigated by Jullian Rotter (1966). Rotter investigated the relationship between an individual's expectancies for rewards and his/her locus of control. He hypothesized that individual differences in locus of control would differentially affect the perceived causal link between behavior and rewards or reinforcements. A person with an internal locus of control was defined as one who perceived a causal relationship between behaviors. and rewards as being contingent on his/her performance. Conversely, a person with an external locus of control was defined as one who perceived rewards as being contingent upon factors other than his/her behavior such as luck or fate (Rotter, 1966). Through his own research and that of related researchers Rotter (1966) developed an instrument entitled the "LE scale" that measured individual differences in locus of control. Rotter administered the scale to black college students who were divided into three groups based on their level of involvement in civil rights activities. Rotter hypothesized that those students who had an internal locus of control would be more likely to take part in activities attempting to change the environment than those with an external locus of control. This hypothesis was based on the theory that those students with a heavy involvement in civil rights activities would have the expectancy that their behavior could change the prejudice inherent in their environment (Rotter 1966; Rotter & Hochreich, 1975). The results of this study showed that those students who were the most highly involved in civil rights activities were also found to be more internal on the HE scale, thus confirming Rotter's hypothesis. In addition, the LE scale was found to have moderately high internal consistency and satisfactory reliability and validity (Rotter, 1966). Rotter cited the work of other researchers who had utilized earlier versions of his I-E scale and had obtained similar results (Phares, 1965; Seeman & Evans, 1962). As a result of Rotter’s investigation, it was illustrated that people differ along a dimension of expectancy for either reinforcements or rewards based on their internal or external locus of control. Although the locus of control dimension can not be expected to explain all the variance in behavior it can be extremely 10 insightful when used as a framework for understanding a variety of behavior (Bains, 1983; Lefcourt, 1976). Bernard Weiner (1979) investigated the explanations of success and failure from an attributional perspective. His work lead him to postulate that there was an additional dimension within the internal/external dichotomy of locus of control. Weiner suggested that the internal/external dichotomy of attributional causality would vary along three dimensions: locus of causality, stability and controllability. Locus of causality referred to behavior or events as being caused by internal factors within the individual such as ability and effort or to external factors outside the individual such as luck and task difficulty. Stability was a dimension that dealt with the duration of cause. The cause of behavior or events could be assigned to stable forces such as ability and typical effort or unstable forces such as mood and luck. Within the notion of controllability, causes of behavior or events were placed on a continuum ranging from those that an individual perceived they could directly control to those they felt they were powerless to control (Weiner,1979). To test this theory Weiner designed a study examining students' performances on an arranged set of tasks (Weiner, 1979; Weiner et al., 1976). Preceding the experiment, a questionnaire was given to each member of the group to discover their expectancy of success. Following a student's successful completion of a task, an assessment of cause was undertaken. Results of this experiment revealed that the perception of causal locus (internal/external) and controllability of the groups did not affect expectancy of success to the same degree as the students' ascriptions to stability factors. 11 These findings lead Weiner to conclude that the stability dimension is important in the assessment of causality. Weiner did not reject the concepts of locus of causality and controllability but suggested that the stability dimension should also be utilized in the assessment of causality in future research (Weiner, 1979). El"E!'l'Il The dimensions of causality, controllability, and stability within attribution theory have also been utilized by researchers as a theoretical framework to aide in the analysis of organizational behavior and processes (Bettman & Weitz, 1983; Ford, 1985; Staw, Mckechnie & Puffer, 1983). Utilizing attribution theory to analyze how organizations determine cauSes of successes and failures allows researchers to better understand organizational behavior. Staw et al. (1983) examined the justification for organizational performance by analyzing corporate reports. This research involved an investigation of the letters to stockholders to determine whether or not differences existed in the self-serving attributions between high performing and low performing companies. Self-serving attributions are causal attributions that enable an individual to take credit for success and to avoid blame for failure. They hypothesized that low performing corporations would attribute the cause of performance to external forces such as downturns in industry demand or the economy while high performing corporations would attribute the cause of their performance to internal factors such as positive product characteristics or accurate strategic planning (Staw et al., 1983). 12 Study results revealed that self-serving attributions did appear in the letters to stockholders. More importantly, when the performances relayed in the letters were negative the corporations were much more likely to attribute them to external rather than internal causes. These findings lead Staw et a1. (1983) to suggest that self-serving attributions may be utilized as a tool for understanding the position an organization takes towards its environment. Similar results were found in a study conducted by Bettman and Weitz (1983) which also examined the causal reasoning patterns of corporate performance by analyzing the letters to stockholders located in annual reports. Bettman and Weitz found that unfavorable organizational performances were more often attributed to external, unstable and uncontrollable causes than were favorable performances. Their study demonstrated that biases are present in the causal reasoning patterns utilized by corporations in the assessment of their performances (Bettman & Weitz, 1983). Ford (1985) utilized Weiner's causal attribution model as a framework for categorizing decision makers' responses to performance ' downturns. Specifically, Ford reviewed the work of numerous researchers in an effort to analyze the link between causal attributions of corporations' performance downturns and their internal and external response strategies. Ford determined that decision makers did indeed attribute performance downturns to causes that varied on the dimensions presented by Wiener (locus of causality, stability and controllability). In addition, Ford (1985) found that decision makers' choices of strategic responses (internal or external) were based on their attributions of causality and not the 13 actual causes of the downturns. This finding is supported by the work of Deft and Weick (1984) which found that decision makers' attributions form the basis for taking action. The research of Staw et al.(1983), Bettman and Weitz (1983), and Ford (1985) exemplifies how the attributional dimensions of locus of causality, stability and controllability can be utilized to understand and explain the ways organizations interact with their environment. When applied to organizational research these attributional dimensions can be utilized to analyze the posture an organization takes towards its environment through an examination of the strategic planning factors utilized by an organization. 81']: 5.1.1] IS 'El' The strategic planning factors utilized by an organization reflect how that organization perceives and evaluates the linkage between events and their possible causes (Deft & Weick, 1984). Strategy decisions can be explained as the result of the interaction between the decision maker and the environment (Maciariello, 1984). Decisions are made in an attempt to control those factors leading to organizational success (Miller & Ross, 1975). Cyert and March (1963) point out that the posture adopted by an organization towards the environment reflects its perception of environmental conditions in relation to its desire to attain organizational goals. In other words, it is a decision maker's attributions or interpretations that form the basis for action. It is through strategic planning that a decision maker determines causality and attempts to apply corrective action and maintain control. Successful organizational 14 strategies are those that correctly identify causal factors affecting performances and result in appropriate responses (Bettman & Weitz, 1983). Miles and Snow (1978) have deve10ped a classification scheme of organizations which place decision makers on a continuum based on their perceptions of controllability as reflected in their strategic planning orientations. This classification scheme divides decision makers' orientations into four categories: defenders, prospectors, analyzers, and reactors. Defenders are those decision makers who have external and reactive orientations. They perceive their environment to be static and feel they lack control over their environment. In contrast, a prospector has an internal and proactive orientation. Prospectors believe in taking advantage of opportunities and feel they have a great deal of control over their environment. In between these two orientations lie the reactors and the analyzers. Reactors represent unstable decision makers and organizations which lack a viable organizational strategy. Analyzers attempt to maintain balance in their strategy by exploring new market opportunities while simultaneously maintaining a solid base of traditional products and customers (Miles & Snow, 1978). Similarly, Miles (1982) discusses two contrasting models of organizational behavior which are based on the causality and controllability dimensions of attribution theory, that of natural- selection and strategic-choice. These models are based on the theory that organizational behavior and strategic choice are a reflection of the degree to which an organization perceives it can control its environment and also its perceptions of the causality of 15 organizational performance. The two models represent opposite ends of an organizational behavior spectrum. Those organizations with a natural-selection philosophy have external control orientations. Their organizational philosophy is governed by four assumptions: (a) organizations are "captives" of their environment, (b) the environment is "immutable" to attempts made to change it by organizations located within it, (c) "inertia" propels organizations, and (d) organizations are bound by their powerful environment and "possess little slack for dealing with imposed change" (Miles, 1982, p. 232). Basically, organizations with a natural-selection philosophy attribute causality of organizational performance to external factors embedded in the environments such as fate or luck. In addition, these organizations view strategic management as dysfunctional due to their perception that managers are incapable of controlling change in their environment. Contrary to the natural-selection model is the strategic-choice model. Organizations with a strategic-choice philosophy have internal control orientations. These organizations operate under three assumptions: (a) managers are capable of choosing how to most successfully operate in their environment and are able to select the most appropriate environment to operate within, (b) organizations can affect their environment, and (c) with effective managers an organization . can change with its environment (Miles, 1982). Strategic management plays a crucial role in the operations of organizations with a strategic-choice philosophy. It is through strategic management that these organizations 'attempt to control their environment by identifying proper strategies and establishing 16 effective alignments between the organization and its environment (Miles, 1982). 17 CHAPTERII REVIEW OF LITERATURE E 'S"fi [I"III'IS Tourism is recognized as having a significant impact on the economy of the United States. During 1986 tourism-related spending was $269 billion. This spending equaled 6.4% of the total United States gross national product for 1986 (U.S. Travel Data Center, 1986- 87). Although these figures illustrate the significance of tourist spending, they also represent the potential for generating more jobs, additional wages and salaries, and increased federal, state and local tax revenue (Mill & Morrison,1985; W 1984; U.S. Travel Data Center, 1986-87). In fact during 1986 travel-related spending in the United States generated 5.2 million jobs, paid approximately $58 billion in wages and salaries, and produced over $38 billion in federal, state and local tax revenue (U.S. Travel Data Center, 1986-87). The 5.2 million tourism generated jobs in 1986 indicate the importance of tourism as a prime employment source for many Americans. In 1986, the tourism industry was the second largest private employer in the U.S. (U.S. Travel Data Center, 1986-87). Further, tourism is one of the top three private industry employers in three-fourths of the states and is the top private industry employer in one-fourth of the states (Mill & Morrison, 1985). 18 Not only does the tourism industry serve as a major employment base, but it has stimulated the creation of new jobs faster than the rest of the economy. Since 1976, employment in the tourism industry has increased 57% which represents more than twice the growth rate of that for all U.S. industries (U.S. Travel Data Center, 1986-87). Additionally, tourism-related employment provides a disproportionate number of jobs to groups that have traditionally experienced difficulty in obtaining and retaining employment, particularly minority groups, women and youths (11.1. W 1984; U.S. Travel Data Center, 1866-87). The tourism industry also provides indirect economic stimulation of nontourism-related sectors of the economy. For instance, the demand for tourism» offerings such as hotels, shops, and restaurants creates demand for products and services from nontourism businesses such as furniture, agricultural products, and local handicrafts (Mathieson & Wall, 1982; Mill & Morrison, 1985; Tuttle, 1987). The economic impact of tourism is predicted to remain strong as the demographic segment of 35-54 year olds continues to age. Currently, this demographic segment is comprised of approximately 80 million people who are now entering their peak wage earning years (Lazer, 1981; Murgittroyd & Doherty, 1986; Rosenfeld, 1986). It is predicted that from 1990-2000, as the 35-54 year age group matures and their children begin to leave home, they will have increasing amounts of time and money to spend on entertainment activities such as tourism. This find is strengthened by the fact that by the year 2000, it is predicted that 60% of all married women will 19 be employed outside the home which is predicted to increase the amount of discretionary income available to individuals and families to spend on activities such as tourism (Lazer, 1981; Murgittroyd & Doherty, 1986; Rosenfeld, 1986). E 'S"Ei EI' 'll'l' Michigan is a state that is highly impacted by the tourism industry. From 1983 to 1986, the economic impact of tourism in Michigan has increased at an average annual rate of 8% (Whisenhut, 1987a). Economic impact figures for 1986 reveal that tourism activity in Michigan generated $13 billion, provided 295,000 jobs, and produced $611.7 million in state tax revenue (Whisenhunt, 1987b). These figures allow Michigan to be ranked among the top ten states economically impacted by tourism (Murgittroyd & Doherty, 1986). The importance of tourism to Michigan's economy is further demonstrated by the fact that tourism ranks as one of the three largest contributors to the state's economy along with manufacturing and agriculture (Murgittroyd & Doherty, 1986; W, 1984). This economic significance is augmented by the fact that tourism has demonstrated its ability to be a stable contributor to Michigan's economy. For example, in the 1970s and early 19803 when Michigan experienced heavy unemployment and recession, the tourism industry remained a stable contributor to the state's economy. This proven stability indicates that tourism has the potential to level out significant swings in economic cycles for Michigan; a state that traditionally has been reliant upon the dynamic contributions of the 20 auto industry and the economically unstable agricultural industry (Murgittroyd & Doherty, 1986). Because the State of Michigan has recognized the importance of utilizing tourism as a means of achieving economic stability, it has expanded its promotional campaign to capture a larger percentage of the tourism market. In 1986, Michigan had the second highest state travel promotional budget in the nation, spending $11.8 million to promote its tourism industry (Spandoni, 1986). As competition from surrounding states continues to increase, it is predicted that this promotional budget will grow (Whisenhunt, 1987a). I] I . B 'l I I The tourism industry is comprised of a heterogeneous mix of business and service operations which function to satisfy the needs of tourists. One integral facet of this industry is the tourism- dependent retailer. As with the overwhelming majority (98%) of businesses operating within the tourism industry, tourism- dependent retailers are primarily small businesses (U.S. Travel Data Center, 1986-87). As small businesses, these tourism-dependent retailers are often undercapitalized and therefore, lack the ability to survive extended periods of poor economic conditions. This trend is, in part, reflected by the fact that in 1984 the average failure rate for the total retail sector was 112.7 per 10,000 outlets (M_o_z_e W 1986). Although no figures are currently available, it is reasonable to assume that due to their seasonal nature, small size and undercapitalization, the failure rate for 21 tourism-dependent retailers is at least as high as that of retail businesses in general (Pysarchik, 1989). Additionally, tourism-dependent retailers are often financially unable to conduct research regarding how to successfully operate within the unique nature of tourism markets. Tourism-dependent retailers face many challenges which retailers in general do not encounter. These unique characteristics include the effects of seasonality, the impact of the tourist area's image, the importance of the political climate within the tourist area, the characteristic lack of knowledge about target market(s) faced by tourism-dependent retailers, and the increasing maturation of the tourism market. EEE E S l' I . All retailers are affected by the dynamic nature of their market environment, however, tourism-dependent retailers are additionally influenced by the seasonality component of their business cycle. Tourist travel is skewed according to the seasons and as a result fluctuations in the level of the demand for goods and services occurs. This creates additional management and personnel problems for the tourism-dependent retailer such as sharp inventory fluctuations and vacillating staff requirements (Manning & Powers, 1984; Mathieson & Wall, 1982; Mill & Morrison, 1985). Traditionally, the cyclical nature of tourist demand has been viewed by tourism practitioners as an uncontrollable factor similar to the weather (Manning & Powers, 1984). However, one study has discovered that there are various means available for the successful management of the seasonality component of tourism. This study 22 investigated the potential of distributing the overload of activity experienced in peak time periods to non-peak time periods in the Vermont State Park system. The findings of the study revealed that campers could be persuaded to shift their activity from peak to off peak time periods if certain actions were undertaken, such as price changes, altering opening and closing dates and locating parks closer to market areas (Manning & Powers, 1984). W A tourism destination is made up of an interdependent mix of elements including: attractions, facilities, transportation, support industries and hospitality resources. These elements are interdependent because taken together they provide tourists with either a favorable or unfavorable image of a tourism area (Jafari, 1983; Mill & Morrison, 1985). Because tourism-dependent retailers function within the infrastructure of the tourism area, they are greatly affected by the image that the area maintains. A tourism area's image serves to draw tourists to the area and an unfavorable area image may deter tourist visits. This phenomenon creates additional problems for the tourism-dependent retailer that retailers in general do not face. The essential problem this creates is that an unfavorable area image may be so pervasive that any efforts undertaken by an individual retailer to improve the unfavorable image may be futile (Jafari, 1983; Schwaninger, 1986). Further, the image that a tourism area creates has implications for the way in which a tourism-dependent retailer in an area positions itself. Not only must a tourism retailer create an image that 23 is distinct from other similar retailers in the area but it must also create an image that complements that of the tourist area (Pysarchik, 1989). This is exemplified by a study which found that next to natural beauty and climate, tourists rated the cultural and social characteristics of an area as the most important factors influencing the attractiveness of a tourism area (Ritchie & Zins, 1978). Therefore, this suggests the importance of tourism retailers creating images which reflect the cultural and social aspects of the area. Tourism-dependent retailers are affected by the political environment they function within (Mill & Morrison, 1985). It is not uncommon to find an adversarial political environment within a tourist area due to negative community sentiment toward tourism development. This negative sentiment is often the result of a tourist community deciding that the costs of tourism (e.g. increased inflation and the deterioration of the natural and cultural environment) far outweigh the economic benefits of tourism (Mathieson & Wall, 1982; Mill & Morrison, 1985). Functioning within a community that does not support tourism development can make it difficult for tourism- dependent retailers to succeed due to lack of financial and political support (Maddox, 1986). WWW Identifying the target markets for the product and service offerings of a retail operation is paramount to its successful Operation. However, as with many small businesses, tourism- 24 dependent retailers often lack the resources to effectively analyze their target markets. Defining target market(s) is difficult because the majority of tourism-dependent retailers' clientele is comprised of tourists who could be classified as out shoppers (Pysarchik, 1989). Out shoppers are those people who live in one area and travel to a different area to shop (LaFarge, 1984). Because tourism-dependent retailers know little about this out shopping group, frequently all types of tourists are grouped together into one homogeneous category. As a result, the product and service offerings of many tourism retailers do not match the needs of specific tourist segments (Pysarchik, 1989). One way tourism-dependent retailers can assess the needs of tourists is to determine why tourists are traveling to the tourist destination and design products and services which correspond with the tourist attracting features. One study investigated differences between tourists' and retailers' attitudes about a specific resort area (Witter, 1985). Research results revealed that retailers in the tourist area and the tourists themselves held different attitudes about the tourist-attracting features of the area. Specifically, retailers over evaluated many features of their area and as a result were not correctly identifying and meeting needs of tourists in their area. It was concluded that tourism retailers could design product and service offerings that would improve and more successfully market their tourist area only after they correctly evaluated the tourist-attracting features of their area (Witter, 1985). Another study, investigating American tourists' perceptions of retail stores in twelve countries illustrated the importance of 25 identifying the needs of a specific target market. It was concluded that retailers who showed concern for the customer through personal selling techniques and exhibited high business ethics were very successful in satisfying the needs of American tourists (Keown, Jacobs & Worthley, 1984). M . E l I . M l The tourism industry has experienced an extended period of market growth over the past three decades. However, it is believed that the tourism industry is now entering the mature stage of its product life cycle (Rovelstad, 1981; Rovelstad & Blazer, 1983; Spandoni, 1986). This development has important implications for tourism retailers. Specifically, tourism-dependent retailers will not only be faced with increased competition from other similar retailers operating in their area but also increased competition from other tourist areas. Evidence of this maturation is apparent in the shorter time spans available to tourism retailers for business planning. Traditionally, tourism retailers have operated with short-run profit orientations and did little or no business planning. These retailers were able to survive because demand was strong, there was little competition and few changes were occurring in consumer markets. Today, however, retailers are faced with shorter planning cycles due to increasing competition and dynamic consumer markets. In order to survive the effects of a maturing tourism market, tourism- dependent retailers will have to adopt more proactive, innovative planning strategies (Schwaninger, 1986). 26 S . El . S . El . D E' 1 Organizational strategy has been defined as the "fundamental pattern of present and planned resource deployments and environmental interactions that indicate how the organization will achieve its objectives" (Hofer & Schendel, 1978, p. 25). An organizational strategy is formulated into a set of plans which serve to define the particular environment in which the organization will operate and to guide the actions of the organization with its business operations in that environment (Bourgeois, III, 1980; Hambrick, 1980). An optimal strategic plan is one which most effectively aligns the resources of the, organization with the environmental conditions faced by that organization (Bourgeois, 1980). In an effort to operationalize the concept of organizational strategy, Hofer and Schendel (1978) have identified the following three levels of strategy: corporate strategy, business strategy and functional strategy. Corporate level strategies are concerned with answering questions about what set of business(es) an organization should be in. Specifically, these strategies deal with identifying the "breadth and depth of the product market scope" (Hofer & Schendel, 1978, p. 29). Business level strategies are those which identify how an organization competes in its chosen business(es). With business level strategies, strategic decisions concern such issues as identifying a firm's distinctive competences, developing market segmentation schemes, and allocating the firm's resources in order to gain competitive advantages over its competitors. Functional level 27 strategies are those which integrate all the activities of the organization in order to maximize its resource productivity. Strategy can also be operationalized through the interpretation of the process or content of the strategy. The process of strategy development is investigated to analyze the ways that management determines the actual strategies it will utilize (Bamberger, 1986; Bourgeois, III, 1980). One study found the following model to be an accurate description of the steps managers undertake in the strategic planning process: (a) establish the mission, (b) set objectives, (c) environmental scan (external environmental analysis), (d) identify internal strengths and weaknesses, (e) formulate alternative strategies, (f) select a strategy, (g) implement a strategy, and (h) control to insure that the strategy is achieved (Ginter, Rucks & Duncan, 1985). The content of strategies is studied to determine the actual strategies that management selects in the pursuit of its goals and whether these strategies are effective. Content can be broken down into intended. and realized strategies. Intended strategies are models for the firm's future behavior. In contrast, realized strategies are plans that have actually been undertaken and serve as the basis for comparison for future organizational performance (Bamberger, 1986). r ' P nin n 11 Tourism-dependent retailers, as with the majority (98%) of businesses operating within the tourism industry, are primarily small businesses (U.S. Travel Data Center, 1986-87). Although no 28 specific studies have explored the use of strategic planning by tourism-dependent retailers, many studies have investigated the use of strategic planning and the effect it has on the organizational effectiveness'of small firms, in general (Bracker & Pearson, 1986; Robinson, Jr. & Littlejohn, 1981; Robinson, Jr. & Pearce II, 1984; Sexton & Van Auken, 1982, 1985). It can be concluded from these studies that small businesses, in general, do not utilize strategic planning practices. This underutilization exists despite research evidence that supports a positive relationship between the use of strategic planning and organizational effectiveness. One such study was conducted on 67 small retailing, service- oriented, and manufacturing firms to determine the relationship of strategic planning to organizational effectiveness (Robinson, Jr. & Littlejohn, 1981). The businesses were selected from a group that had received in-depth consulting from a small business development center. Prior to their contact with the development center these firms had not engaged in systematic planning activities. Comparison of the firms' effectiveness before and after the implementation of strategic planning techniques was undertaken. The results of this comparison showed that systematic planning increased sales, employment, and profitability performance of the majority of the firms. The researchers, therefore, concluded that planning can affect small firm business performance. Sexton and Auken (1982) investigated the level of strategic planning utilized by a randomly selected sample of 357 small manufacturing, wholesale, retail and service businesses. Results of the study revealed that fewer than one-quarter of the businesses 29 surveyed engaged in true strategic planning (e.g. systematic planning focused on the achievement of forecasted sales and profit changes). Additionally, one-fifth of the businesses surveyed had not engaged in any strategic planning activities. In 1985 a follow-up study utilizing the same sample of small businesses was undertaken. Researchers found that of those firms identified in the earlier study as nonstrategic planners, 20% had failed. Further, only 8% of those firms previously identified as strategic planners had failed. It was concluded that a positive relationship exists between strategic planning and organizational effectiveness (Sexton & Van Auken, 1985). Robinson, Jr. and Pearce II (1984) reviewed the findings of over 50 planning-related studies of small firms. It was determined that most small firms do not formally plan and that evidence exists to support a relationship between strategic planning and small firm performance. These researchers state that the success of small firms in the future will depend on the quality of their strategic management decisions. Bracker and Pearson (1986) undertook a longitudinal study examining the relationship between planning process sophistication and financial performance of a group of small, mature dry cleaning businesses. The results of their study showed that those dry cleaning firms that were classified in the highest sophisticated planning level demonstrated better financial performance than businesses classified in lower levels of planning SOphistication. These findings lead the researchers to conclude that a strategy which 30 properly matches a firm to its environment is essential for success (Bracker & Pearson, 1986). Several studies have investigated the reasons why most small businesses do not engage in strategic planning despite the recognized relationship. between strategic planning and organizational performance (Robinson, Jr. & Pearce II, 1984; Scarborough & Zimmerer, 1987; Unni, 1981). One reason for small businesses' characteristic lack of planning is due to the fact that strategic planning is perceived to be a complex and difficult task for small business owners/managers. One study revealed that small firm executives found business planning to be the most difficult managerial task to perform (Cohn & Lindberg, 1972). Four main reasons can be cited to explain why small business owners/managers perceive strategic planning to be a difficult process. First, small business owners/managers are usually generalists who have gained their business knowledge through practical work experiences. Although this has provided small business owners/managers with solid practical knowledge, they often lack the working knowledge and expertise necessary to develop strategic plans (Scarborough & Zimmerer, 1987). A lack of planning knowledge has been cited by one researcher as the most serious obstacle to planning for small business owners/mangers (Unni, 1981). Second, many small businesses are undercapitalized and, therefore, lack the resources necessary to engage in strategic planning themselves or to hire outside experts (Scarborough & Zimmerer, 1987). Third, small business owners/managers are highly involved in the day to day operations of the business and often serve 31 many different functions within the business. As a result, they often lack the time necessary to devote to strategic planning (Robinson, Jr. & Pearce II, 1984; Scarborough & Zimmerer, 1987; Unni, 1981). Lastly, many small business owners/managers feel that existing strategic guidelines are suited to large companies and are not appropriate for the strategic planning needs of small businesses (Scarborough & Zimmerer, 1987). Dif-- - :- --, '41.} o 1..“ ,H : .- Some researchers have suggested that small businesses should not attempt to utilize the strategic planning techniques developed for big businesses (Moyer, 1982; Scarborough & Zimmerer, 1987; Welsh & White, 1981). This philosophy is reflected in one researcher's statement that "a small business is not a little big business" (Scarborough & Zimmerer, 1987, p. 11). This statement is based on the premise that small businesses differ greatly from big businesses in both organizational characteristics and business environments (Cooper, 1979). Big businesses usually operate with large product portfolios, a broad customer base and in many geographic areas. They function on a fairly static basis and typically are formally structured (Moyer, 1982; Welsh & White, 1981). Additionally, big businesses typically have the resources to conduct market research before launching new products or services into the market, therefore, increasing their chances of avoiding market failures. They are able to survive extended periods of adverse economic conditions by falling back on reserve assets (Welsh & White, 1981). 32 In contrast, small businesses typically have narrow product lines, a small customer base, operate in a limited geographic area and are often seasonally oriented. They generally operate under informal organizational structures and with flexible management styles that enable them to adapt quickly to changes in their environment (Scarborough & Zimmerer, 1987; Welsh & White, 1981). A small business usually survives by developing niche strategies, producing products or services that do not directly compete with those of big businesses (O'Neill & Duker, 1986). Due to the fact that they operate with limited resources, product development is usually undertaken following the owner's hunches or desires. If the product fails the small business seldom survives because it lacks reserve resources. Additionally, limited resources often cause a small business to fail during extended periods of adverse economic conditions (Welsh & White, 1981). 5.21.513115. Research has been undertaken which has provided some small business-oriented strategic planning procedures and techniques (Robinson Jr. & Littlejohn, 1981; Robinson, Jr. & Pearce II, 1984; Scarborough & Zimmerer, 1987). Specifically, it has been concluded that in order for strategic planning to effectively meet the needs of small businesses, several basic guidelines should be followed. 1. A small business strategic plan should be informal and based on a short time period of six months to two years. While this type of plan allows small business owners/managers to state objectives in concrete terms it also allows for adaptation of the plan 33 to the dynamic nature of the small firm environment (Meidan, 1986; Robinson & Littlejohn, 1981; Scarborough & Zimmerer, 1987). 2. Due to the fact that forecasting for future profits and sales growth is an extremely speculative task for small businesses, strategic plans should be designed with a highly functional focus. Plans should highlight basic operating tasks such as finances, promotion, production and inventory with an emphasis on improving competitive competences (Meidan, 1986; Robinson, Jr. & Littlejohn, 1981; Scarborough & Zimmerer, 1987). 3. Outsiders such as accountants, fellow business-persons, management consultants, and small business associations should be utilized whenever possible to design strategic plans. This allows small business owners/managers to obtain needed expertise in strategic planning techniques and increase the reliability and creativity of strategic plans (Robinson, Jr. & Littlejohn, 1981; Robinson, Jr. & Pearce II, 1984; Scarborough & Zimmerer, 1987). One study supported this notion by finding that it was the quality of the strategic plan not the amount of time spent on planning that made for successful planning results (Orpen, 1985). These procedures provide general guidelines for strategic planning by small businesses. However, more research is required to investigate specific strategies needed by different types of small businesses to increase their organizational effectiveness (Cooper, 1979; Robinson, Jr. & Pearce II, 1984). 34 CHAPTER III METHODOLOGY AND PROCEDURES Win This study involved the analysis of an existing data base as a means of investigating the planning practices of retailers located in tourism and nontourism-dependent areas. This data was previously collected as a part of a project entitled "Toward Achieving Michigan Rural Employment Potential: The Role of Resort Area Retailing" and was funded by the Michigan Agricultural Experiment Station and Michigan State University Cooperative Extension Service. The original study was cross-sectional and used survey research methodology to collect data on the business practices of retailers located in tourism and nontourism-dependent areas. Data for the original study was collected through a structured self-report survey instrument that was specifically designed for the study. B l 01' . The research objectives for this study are (1) determine the relative importance of tourism trade to different types of retailers within tourism-dependent communities, (2) compare and contrast differences in business planning between tourism-dependent and nontourism-dependent retailers, and (3) determine the relation of selected dimensions of business planning (locus of causality, 35 controllability, stability) to financial performance and level of planning sophistication among tourism-dependent and nontourism- dependent retailers. W O . . The questionnaire was introduced with a statement identifying the researchers' university affiliation and an assurance of confidentiality and anonymity. The body of the questionnaire consisted of five major sections. Questions in these sections were each headed by specific instructions for their completion. A total of 70 questions were included on the questionnaire (Appendix A). Section one, items 1-23, consisted of a series of questions concerning business persons' judgement about the quality of the areas' tourist attracting features. Section two, items 24-55, was comprised of statements dealing with specific business practices measured on a seven-point Likert scale (1 = "Strongly Disagree" to 7 = "Strongly Agree"). Section three, items 56—62, contained a series of questions dealing with business operating data. Specifically, questions were asked concerning monthly and annual sales volume, monthly employment figures, and the operating ratios of the business. Within section four, items 63-65, respondents were asked to indicate the number of employees hired from selected employment sources. Section five, questions 66-71, was comprised of several descriptive questions which defined business type, legal form of ownership, customer base, SIC classification, and business location. Only sections 2, 3, and 5 were analyzed in this study. 36 Emblem Businesses that participated in this study were selected from both tourism and nontourism-dependent communities located in the northern-lower peninsula and the upper peninsula of Michigan. Communities were selected based on the criterion that they were located at least 100 miles from a major U.S. urban area. Classification of a community as tourism or nontourism-dependent was based on an analysis of the economic base of the community. Nontourism- dependent communities had a nontourism-related economic base such as farming or oil exploration. Tourism-dependent communities were defined as relying on tourism as a major contributor to their economy. Additionally, persons familiar with the communities, the Travel Bureau of Michigan and directors of local Chambers of Commerce of eligible communities were consulted regarding their recommendations for classification of tourism and nontourism- dependent communities. A total of 11 Michigan communities were selected for inclusion in the study. Those communities identified as nontourism- dependent were: Kalkaska, Manton, Onoway, McBain, and Marion. Tourism-dependent communities were identified as: Marquette, Mackinac Island, Mackinaw City, St. Ignace, Cheboygan, and Sault Ste. Marie. Selection of businesses from the study site locations was undertaken through the use of a stratified random sampling technique. First, the business population was identified as those businesses listed in the Yellow Pages of local telephone directories of the selected communities. Second, this population was divided into 37 subpopulations or strata based on their product and service classifications as defined by the Standard Industrial Classification Manual (1972) (e.g. hair salon, barber shop, sporting goods store, etc.). Lastly, a simple random sample without replacement was drawn from within each strata. The first sample wave, selected during 1985, produced a sample size of 653 businesses representing all eligible businesses with at least one business within each strata. A second sample of 241 businesses was selected utilizing a similar methodology during the summer of 1987. Man In 1985, the first wave of 653 questionnaires was mailed to the selected businesses. A second wave of 241 questionnaires was mailed in the summer of 1987. Accompanying the questionnaire was an introductory letter directed to the manager/owner of each business (Appendix B-l). The purpose of this letter was to introduce the study and provide an explanation of the study, criteria utilized in business selection, need for business participation, and the assurance of anonymity and confidentiality. Instructions were included for those participants needing assistance completing selected questions. Questionnaires were self-addressed for return and postage paid. Approximately four weeks after each wave was sent, follow-up postcards with detachable reply cards were mailed. Several weeks later, second questionnaires and reminder postcards were mailed. Of the 894 questionnaires sent, a total of 133 usable questionnaires were returned yielding a return rate of 15.2%, after adjusting for non-deliverable questionnaires. 38 I] 'IDE'” mug-The short to medium range functional plans that are appropriate for use in small business such as marketing, finance, or personnel (Fry & Stone, 1985; Meidan, 1986; Robinson & Littlejohn, 1981; Scarborough & Zimmerer, 1987). WnA controllable dimension of business planning reflects a decision maker's perception that the cause of business performance is under his/her direct control such as level of effort, acquisition decisions or research and development activity. An uncontrollable dimension of business planning reflects a decision maker's perception that the cause of business performance is out of his/her direct control such as in the weather or government regulations (Ford, 1985; Weiner, 1979). W-An internal locus of causality reflects a decision maker's perception that the cause of business performance is within the organization such as in sales effort, products, or work force skill. An external locus of causality reflects a decision maker's perception that the cause of business performance is outside the organization such as the environment or situation (Bettman & Weitz, 1983; Ford, 1985). ' Planning levelW—-A measure adapted from a scheme developed by Bracker & Pearson (1986) that divides strategic planning of businesses into two levels of sophistication: structured plans, and operational plans. Structured plans are systematic, long-range plans, 3-5 years in length, which cover the information and processes necessary to establish future performance goals. Operational plans are formal, short-range plans which focus on business operations of the current budget year. Stability-A stable dimension of business planning reflects a decision maker's perception that the cause of business performance persists over time. An unstable dimension of business planning reflects a decision maker's perception that the cause of business performance changes over time (Bettman & Weitz, 1983; Ford, 1985). 39 rin f'i'n Many-Cognitive processes which allow an individual to understand the causes of observed events, to assess responsibility for particular outcomes, or to assess the personal qualities of an individual involved in an observed event (Jones & Davis, 1965). An attribution is a function of the analysis of the three causal dimensions: locus of causality, controllability, and stability. WWW-A measure that divides financial performance into two levels, high and low, based on retail sales and profit figures (Robinson, Jr., 1983). . . co 0 o o \- ' I t .I . 3... H“.-’-..'I -- - " Retailers located at least 100 miles from a major U.S. urban area and operating in communities with a nontourism-related economic base such as farming or oil exploration (Davis, Pysarchik, Sternquist & Chappelle, 1987). \"e l . ..-H. 0 I "-0‘3'30‘3 '2‘ -- Retailers located at least 100 miles from a major U.S. urban area and operating in communities relying on tourism as a major contributor to their economy (Davis et al., 1987). H I I S . . l E I In order to meet the research objectives .of this study three groups of hypotheses were proposed. -Group 1 hypotheses are related to the first research objective, Group 2 hypotheses are related to the second research objective, and Group 3 hypotheses are related to the third research objective. All hypotheses are stated in the null form. 40 91211124 No significant difference exists between selected situational characteristics (perception of tourism-dependency and retail type) and the business definition of retailers (tourism- dependent or nontourism-dependent) located in tourism- dependent communities. 1.1 No significant difference exists between the research classification of tourism-dependency and the retailers' perception of tourism-dependency. 1.2 No significant difference exists in the importance of tourism trade to different retail types within tourism- dependent communities. The statistical test for H1.1 was undertaken by cross-tabulating the research classification (tourism-dependent and nontourism- dependent) with the retailers" self classification of tourism- dependency. Chi-square analysis was conducted on the cross- tabulated data. Hypothesis Hl.2 was analyzed by cross-tabulating retail type and retailers' perception of the importance of tourism trade. Chi-square analysis was conducted on the cross-tabulated data. W No significant difference exists between selected business characteristics and the level of planning sophistication of tourism-dependent and nontourism-dependent retailers. 2.1 No significant difference exists in the operational planning of tourism-dependent and nontourism-dependent retailers. 2.2 When controlling for length of time in business and sales volume, no significant difference exists in the operational 41 planning of tourism-dependent and nontourism-dependent retailers. 2.3 No significant difference exists in the operational planning of tourism-dependent and nontourism-dependent retailers by form of ownership, place of business, and type of business. 2.4 No significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers. 2.5 When controlling for length of time in business and sales volume, no significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers. 2.6 No significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers by form of ownership, place of business, and type of business. 2.7 No significant difference exists in financial performance among tourism-dependent and nontourism-dependent retailers as a result of structural or operational planning. 2.8 When controlling for sales volume and length of time in business, no significant difference exists in financial performance among tourism-dependent and nontourism- dependent retailers as a result of structural or operational planning. The statistical tests for hypotheses 2.1 through 2.8 were analysis of variance (ANOVA) and analysis of covariance (ANOCOVA). Separate models were analyzed with level of planning sophistication (operational and structural) and the profitability changes of retailers as dependent variables. The independent variables were tourism dependency (tourism-dependent and nontourism-dependent), form of ownership, place of business, and type of business. The covariates 42 were length of time in business and sales volume. Level of planning sophistication will be measured according to a classification scheme adapted from Bracker and Pearson (1986). 5mm}. No significant difference exists between the attributions reflected in business planning and the financial performance and level of planning of tourism-dependent and nontourism-dependent retailers. 3.1 No significant difference exists between the locus of causality, controllability, and stability dimensions of business planning and the financial performance of tourism-dependent and nontourism-dependent retailers. 3.2 No significant difference exists in the operational planning of tourism-dependent and nontourism-dependent retailers as a result of the level of causality, controllability, and stability dimensions utilized in their business plans. 3.3 No significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers as a result of the level of causality, controllability, and stability dimensions utilized in their business plans. The statistical tests for hypotheses 3.1 through 3.3 were separate ANOVA models. The dependent variables were profitability changes and level of planning sophistication (operational and structural) of retailers and the independent variables were tourism dependency (tourism-dependent or nontourism-dependent) and the attributional planning dimensions of locus of causality, controllability, and stability. 43 CHAPTERIV RESULTS AND DISCUSSION W This chapter is divided into two sections. Section one contains a discussion of the sample characteristics. Section two presents the results of the statistical analysis of the hypotheses. The hypotheses are divided into three groups which are related to the research objectives for this study: (1) determine the relative importance of tourism trade to different types of retailers within tourism- dependent communities, (2) compare and contrast differences in business planning between tourism-dependent and nontourism- dependent retailers, and (3) determine the relation of selected dimensions of business planning (locus of causality, controllability, stability) to financial performance and level of planning sophistication among tourism-dependent and nontourism-dependent retailers. S 1 Cl . . Sample demographic data (retail classification, annual sales volume of previous year, length of time in business, legal form of ownership, business definition, and place of business) were compared by the research classification of business location (tourism-dependent and nontourism-dependent). The research 44 classification of retailers' business location as tourism-dependent or nontourism-dependent was based upon an analysis of the economic bases of the communities in which the retailers were located. As a result of this analysis, retailers were classified as either tourism- dependent or nontourism-dependent. Summaries of these comparisons are presented for each demographic variable. B '11:] '6’ Respondents were asked to specify the retail classification and standard industrial classification (SIC) code for their business. For analysis purposes, retail classifications were collapsed into six categories. Table 4.1 contains a summary of these categories. A detailed description of the SIC codes is presented in Appendix B. The two most frequently reported retail classifications for tourism-dependent location businesses were nontourism-specific retailing (24.3 percent) and general retailing (22.5 percent). Similarly, the most frequently identified retail categories for nontourism-dependent location retailers were nontourism-specific retailing (33.3 percent) followed by general retailing (23.8 percent). AnnnaLSachXQlume The data collection process for this research project consisted of two waves of questionnaires. The first wave of questionnaires was mailed in 1985 and was followed by a second wave of questionnaires which was mailed in the summer of 1987. As a result of this multiple data collection process, businesses reported annual sales volume for either 1985 or 1987. 45 For data analysis purposes annual sales volume for either 1985 or 1987 was collapsed into six categories. A summary of these categories is presented in Table 4.2. Table 4.1. Comparison of Samples: Retail Classifications of Businesses Within Tourism-Dependent and Nontourism- Dependent Locations. Research Classification When SIC Tourism- Nontourism- Variable Number(s) W Dependent N = 111 N = 21 H % bl % Retail Classification General Retail 53, 553, 56, ‘59a 25 22.5 5 23.8 Nontourism- 17, 52, 553, 57, 27 24.3 7 33.3 Specific Retail 593’ 75 Food/Beverage 54, 58, 59a 16 14.4 2 9.5 Lodging 7 0 13 11.7 3 14.3 Services 72, 73, 76, 80 13 11.7 1 4.8 Misc. 50, 79 16 14.4 2 9.5 No Response 1 .9 1 4.8 Detailed description of SIC codes are contained in Appendix aSIC codes 55 and 59 were separated and categorized into general retailing and nontourism-specific retailing. While the majority (56.7 percent) of retailers located in tourism-dependent areas had annual sales volumes of $499,999 or less, 25.2 percent had sales volumes of under $100,000. Similarly, 28.8 percent of nontourism-dependent area retailers reported sales 46 volumes of $499,999 and less with 14.4 percent specifying annual sales volumes of under $100,000. Retailers located in tourism-dependent areas reported average sales of $610,136. The mean sales volume for the previous year for retailers located in nontourism-dependent areas was somewhat higher, $984,045. However, t-test results indicated that the difference between the two sample means was not significant. Table 4.2. Comparison of Samples: Annual Sales Volume of Retailers Within Tourism-Dependent and Nontourism-Dependent Locations. Research Classification E E . I . Tourism- Nontourism- Variable mm Dependent N = 111 N = 21 H % N % Annual Sales Volume (1985, 1987) Under $100,000 28 25 .2 3 14.4 $100,000 to $499,999 35 31.5 3 14.4 $500,000 to $999,999 11 9.9 1 4.8 $1,000,000 to $1,499,999 3 2.7 2 9.6 $1,500,000 to $1,999,999 1 .9 -- -- $2,000,000 and Over 5 4.5 2 9.6 No Response 28 25.2 10 47.6 Mean $610,136 $984,045 n.s. (df. = 92; t = -.8, pooled variance) 47 IlEI"E' Comparison of the two samples indicated that almost 65 percent of retailers located in tourism-dependent areas and 67 percent of retailers located in nontourism-dependent areas had been operating 14 years or less (Table 4.3). Furthermore, 23.4 percent of tourism-dependent area retailers and 28.6 percent of nontourism- dependent area retailers had been operating for less than five years. Tourism-dependent area retailers had been operating for an average of 16.7 years and retailers located in nontourism-dependent areas had been operating for an average of 16.6 years. A t-test conducted on this data found that the difference between the two sample means was not significant. W Over 48 percent of tourism area retailers were incorporated while 41.4 percent were sole proprietorships (Table 4.4). Retailers located in nontourism-dependent areas stated that sole proprietorship was the most common form of ownership (57.1 percent) with incorporation as the second most common (28.6 percent). A chi-square test of significance was conducted on the crosstabulated variables of tourism-dependency (tourism and nontourism-dependent) and legal form of business. Chi-square was not significant, therefore, it was determined that no statistically significant relationship existed between tourism-dependency (tourism and nontourism-dependent) and legal form of business. 48 Table 4.3. Comparison of Samples: Length of Time in Business of Retailers Within Tourism-Dependent and Nontourism- Dependent Locations. Research Classification Whoa Tourism- Nontourism- Variable W N = 111 N = 21 N % N % Length of Time in Business Under 5 Years 26 23.4 6 28.6 5 to 14 46 41.4 8 38.3 15 to 29 21 18.9 3 14.4 30 to 44 7 6.3 1 4.8 45 to 59 2 1.8 2 9.5 60 to 74 2 1.8 l 4.8 75 to 89 2 1.8 -- -- 90 to 104 2 1.8 -- -- 105 to 119 1 .9 -- -- No Response 2 1.8 - - - - Mean 16.7 16.6 n.s. (df. = 128; t = .02, pooled variance) B' DE" The majority of retailers located in both tourism-dependent and nontourism-dependent areas functioned as independents (Table 4.5). Specifically, 82.9 percent of retailers in tourism-dependent areas and 95.2 percent of retailers in nontourism-dependent areas defined their businesses as independents. 49 Table 4.4. Comparison of Samples: Legal Form of Ownership of Retailers Within Tourism-Dependent and Nontourism- Dependent Locations. Research Classification Won Tourism- Nontourism- Variable N = 111 N = 21 N % N % Form of Ownership Sole Proprietorship 46 41.4 12 57.1 Partnership 9 8.1 3 14.3 Corporation 5 4 48.6 6 28 6 No Response 2 1.8 - - - - n.s. (Chi. sq. = 3.25; df = 2) Table 4.5. Comparison of Samples: Business Definition of Retailers Within Tourism-Dependent and Nontourism-Dependent Locations. Research Classification E E . I . Tourism- Nontourism- Variable N = 111 N = 21 N % H % Business Definition Independent 92 82 9 20 95.2 Chain 7 6.3 - - - - Franchise 1 0 9 1 4.8 No Response 2 1.8 - - - - 50 W Retailers located in tourism-dependent areas were most often situated in downtown business districts and strip areas near downtown (55.8 percent), followed by areas where there were no other businesses (19.8 percent) (Table 4.6). Similarly, retailers located in nontourism-dependent areas most frequently responded that they were established in areas where there were no other businesses (42.9 percent) and downtown business districts (33.3 percent). Table 4.6. Comparison of Samples: Place of Business of Retailers Within Tourism-Dependent and Nontourism-Dependent Locations. Research Classification E E . I . Tourism- Nontourism- Variable Dsmdem Dependent N = 111 N = 21 N % N % Place of Business Downtown Business 31 27.9 7 33.3 District Strip Near Downtown 31 27.9 4 19 Strip Away From 18 16.2 1 - - Downtown Largest City Mall 6 5.4 - - - - Other City Mall 2 1.8 - - - - 1 Areas Where There Were No Other Businesses 22 19.8 9 42.9 No Response 1 .9 - - - - 51 S"lBl [1111 01"!) Determine the relative importance of tourism trade to different types of retailers within tourism-dependent communities. W No significant difference exists between selected situational characteristics (perception of tourism-dependency and retail type) and the business definition of retailers (tourism-dependent or nontourism-dependent) located in tourism-dependent communities. Chi-square analysis was utilized to test each of the group 1 hypotheses. An analysis and discussion of the findings for Hypothesis 1.1 and 1.2 are consecutively presented. 1.1 No significant difference exists between the research classification of tourism-dependency and the retailers' perception of tourism-dependency. The relationship between the research classification of tourism- dependent and nontourism-dependent retailers and retailers' perception of tourism-dependency was measured by cross-tabulating the research classification with question number 24 in the questionnaire, resulting in a 2 x 2 contingency table. The research classification of retailers was determined through analysis of the economic bases of the communities in which the retailers were located. Based upon the economic analysis, retail areas were classified as ”tourism-dependent" or ”nontourism-dependent". Retailers' self-classification was determined by their response to question number 24 which measured retailers' perceptions of how 52 dependent their businesses were on tourism trade. The format for question 24 consisted of a seven-point Likert-type scale ranging from 1 = Strongly Disagree, to 4 = Neutral, to 7 = Strongly Agree. A response of 1, 2, and 3 was recoded as nontourism-dependent and a 9 response of 5, 6, and 7 was recoded as tourism-dependent. Since this study was designed to investigate the bipolarity of tourism- dependent and nontourism-dependent retailers, a neutral response of 4 was not analyzed. A chi-square test of significance was conducted on the cross- tabulated data. Chi-square was not significant at p<.05, therefore, it was determined that no statistically significant difference existed between the research classification of tourism-dependency and the retailers' self-classification of tourism-dependency (Table C-l, Appendix C). Hypothesis 1.1 was not rejected. Due to the fact that one cell in the contingency table had an expected value less than 5, these results need to be interpreted with caution. Since the contingency table is a 2 x 2, there was no alternative to recollapsing the variables to achieve an expected value of 5 or greater. From Table C-l insights into retailers' perceptions of tourism- dependency were gained. Specifically, almost 85 percent of retailers located in tourism-dependent locations perceived themselves to be nontourism-dependent while only 15 percent of these retailers considered themselves to be tourism-dependent. 53 1.2 No significant difference exists in the importance of tourism trade to different retail types within tourism- dependent communities. The relationship between importance of tourism trade to various retail types was measured by cross-tabulating retailers' perception of tourism-dependency with types of retailers located in tourism areas. Research classifications and retailers' perception of tourism-dependency were determined in the manner previously discussed in hypothesis 1.1. Retail type was determined by question number 68 in which respondents classified their business into one of 56 categories. The data from question number 68 was reclassified into six categories in order to facilitate data analysis. 1. General retail (e.g., general merchandise; apparel and accessory; gasoline service stations) 2. Nontourism-specific retail (e.g., building materials, hardware, garden supply, and mobile home dealers; furniture and equipment; automotive repair and services; construction and special trades) 3. Food/Beverage (e.g., food stores; eating and drinking places) 4. Lodging (e.g., hotels, rooming houses, camps, and other lodging places) 5. Services (e.g., personal services; business services; health services) 6. Miscellaneous (e.g., wholesale trade-durable goods; amusement and recreation services) A two-way chi-square test of significance was conducted on the cross-tabulated data which controlled for the research classification 54 of tourism-dependent location (Table 4.7). Chi-square was significant (p<.05); therefore, it was determined that a statistically significant relationship existed between retail types in tourism- dependent areas and retailers' perceptions of tourism-dependency. As a result, hypothesis 1.2 was rejected. Review of Table 4.7 indicated that tourism area retailers' perceptions of tourism-dependency was affected by their retail type. Specifically, in areas classified by the researcher as tourism- dependent, retailers involved in lodging, general retailing, and nontourism-specific retailing perceived themselves to be tourism- dependent. This contrasted retailers in the business of nontourism- specific retailing, general retailing, and food and beverage retailing who perceived themselves to be nontourism-dependent. ' These results must be interpreted with caution, however, since several cells had expected frequencies of < 5. 55 8. v.— 2. 8.2 u 053-20 3253 Gina: 3363 Gina: 3.9m: $368 33de N. a m _ m _ N _ m _ m N c N 33,—. 5.530 3.3: 3.8 32: 33.3 38.: 32.8 33.3 .5285 m _ c c c _ m m .5358. $3.33 33mm: Siam: $3.8 33.6: 3188 3.9m: 32......qu m m N_ m. o .1 mm m _ -EmtaeEoZ GS 33 3; $3 $8 38 38 Z Z z Z z Z 2 III... III... III. III III Illl 5:05:0qu A8 A3 2; A8 A3 A: -558. «a £28. 6&2 oumtom aim—cod .>om\ueom . EfiSeEez .2280 zeta—098m Baggage =23. .233. 8022.09-83.55. 55:5 30:83— .8 ago—Eugen Eat—.5. we comaoflom was 523E320 :33— ...o aemtaaEeU .5... 29$. 56 01" I Compare and contrast differences in business planning between tourism-dependent and nontourism-dependent retailers. W No significant difference exists between selected business characteristics and the level of planning sophistication of tourism- dependent and nontourism-dependent retailers. Group two hypotheses were broken down into four subhypotheses. Analysis of variance (ANOVA) and analysis of covariance (ANOCOVA) were used to test each hypothesis. Multiple classification analysis (MCA), a summary of the differences between the unadjusted operational and structural planning levels and those adjusted for by the independent variables and covariates, was also run for each hypothesis. An adapted form of the Bracker and Pearson (1986) planning sophistication scheme was utilized to classify the planning levels of retailers. This modification was needed in order to classify planning variables in this study (questions 24-55). Specifically, no items were present in the questionnaire which measured intuitive plans and the absence of planning by businesses. The two levels of planning sophistication used in this study were entitled "structured planners" and "operational planners". These two levels were based on the two levels of planning sophistication, structured strategic plans and structured operational plans, developed by Bracker and Pearson. 57 2.1 No significant difference exists in the operational planning of tourism-dependent and nontourism-dependent retailers. An ANOVA model was used to determine the effect tourism- dependency had on the operational planning level of tourism- dependent and nontourism-dependent retailers. The dependent variable was the level of operational planning utilized by tourism- dependent and nontourism-dependent retailers. Operational plans were identified by question numbers 26, 37, 40, and 52 and measured on a seven-point Likert-type scale (1 = Strongly Disagree to 7 = Strongly Agree). These questions measured constructs identified by the Bracker and Pearson (1986) classification scheme as representing operational plans (Table 4.8). The use of sales-per- square foot as a productivity measure was ascertained by question number 26 and represented the construct of production control. Whether or not businesses used accountants to determine taxes was measured by question number 37 and represented the construct of cost constraint. Question number 40 measured the extent to which businesses based purchase decisions for the next selling period on the results of the current selling period and represented the construct of a planning decision based on the current fiscal year. Question number 52 determined whether or not businesses had alternative plans for backup management in cases of illness and represented the construct of personnel requirements. A mean score was derived from the four measures of operational planning. It is important to note that the constructs utilized to measure operational planning did not represent all the planning options available to retailers. Specifically, negative responses may have 58 indicated that retailers did not utilize the exact planning method stated in the questionnaire but instead utilized a variation of the method. This lack of specificity may limit the conclusions that can be drawn from the statistical results. Table 4.8. Questions Used to Measure Operational Planning. Question Number Description of Construct Measured 26 Production Control 37 Cost Constraint 40 Planning Decision Based on Current Fiscal Year 52 Personnel Requirements The independent variable was the perceived tourism- dependency of retailers (tourism-dependent and nontourism- dependent). Tourism-dependency was defined by respondents' answers to question number 24. This question was analyzed in the same manner as described for group one hypotheses. Results of the ANOVA indicated that there were no significant differences between the operational planning level of tourism- dependent and nontourism-dependent retailers (p<.05), therefore, hypothesis 2.1 was not rejected. ANOVA results are presented in Table C-2 in Appendix C. Although tourism-dependent retailers operate in unique business environments, these findings indicate that their operational planning strategies do not differ from those used by nontourism- 59 dependent retailers (Manning & Powers, 1984; Mathieson & Wall, 1982; Mill & Morrison, 1985). This suggests that tourism-dependent retailers do not recognize the importance of utilizing planning strategies which address their unique market characteristics. 2.2 When controlling for length of time in business and sales volume, no significant difference exists in the operational planning of tourism-dependent and nontourism-dependent retailers. Additional variables were analyzed in hypothesis 2.2 to control for factors which may affect the operational planning level of tourism-dependent and nontourism-dependent retailers. Pearson's correlation coefficients indicated that the covariates (length of time in business and sales volume) were more highly related to each other than to the dependent variable (Operational planning level), therefore, ANOCOVA was not conducted. According to Hair, Anderson, Tatham & Grablowsky (1979), when the covariates are more highly correlated with each other than each is with the dependent variable there is no reason to run ANOCOVA. Pearson's correlations were as follows: length of time in business and sales volume had a correlation coefficient of .26 (p<.006); length of time in business and operational planning had a correlation coefficient of -.01 (p<.435); sales volume and operational planning had a correlation coefficient of .25 (p<.008). 60 2.3 No significant difference exists in the operational planning of tourism—dependent and nontourism-dependent retailers by form of ownership, place of business, and type of business. ANOVA was conducted to determine if form of ownership, place of business, and type of business would significantly affect the operational planning level of tourism-dependent and nontourism- dependent retailers. The dependent and independent variables for hypothesis 2.3 were defined as in hypothesis 2.1. However, additional independent variables (form of ownership, place of business, and type of business) were added to the model. To perform ANOVA the ownership form, place of business, and type of business variables were recoded. Form of ownership (question number 66) was collapsed into two categories: (1) sole proprietorship and (2) partnership and corporation. Place of business (question number 69) was condensed into two categories: (1) downtown business district and strip location close to but not in downtown business district and (2) strip location away from the downtown business district, mall locations, and other locations. Type of business (question number 67) was collapsed into two categories: (1) independent and (2) chain and franchise. Results of the ANOVA indicated that the joint effects of the independent variables were significantly related to operational planning level (p<.001), with form of ownership (p<.001) and place of business (p<.01) accounting for this significance (Table 4.9). Specifically, retailers that were partnerships and corporations participated in a greater degree of operational planning than those 61 who were sole proprietors. Furthermore, retailers whose place of business was in the downtown area were higher level operational planners than those located away from the downtown area. The amount of variance in operational planning of tourism- dependent and nontourism-dependent retailers explained by the model was 22.2%. The F-value was significant at p<.001. As a result, hypothesis 2.3 was rejected. These findings are not surprising in view of the fact that retailers in partnerships and corporations generally have more resources and expertise available to them for developing planning strategies than those in a single operator form (Cohn & Lindberg, 1972; Unni, 1981). Additionally, developing planning strategies is a less difficult task for retailers lOcated in downtown areas because they are operating in more well established and homogeneous markets than those retailers located in outlying areas (Carusone & Moscove, 1985). 62 Table 4.9 Summary of Analysis of Variance in Operational Planning for Tourism-Dependent and Nontourism-Dependent Retailers by Form of Ownership, Place of Business. and Type of Business. Sum of Mean F Source of Variation Squares df Square Value Main Effects 25.921 4 6.480 6865*" Perceived Tourism-Dependency .031 1 .031 .033 Form of Ownership 16.178 1 16.178 17.139*“ Place of Business 9.707 1 9.707 10.283" Type of Business .004 1 .004 .004 2-Way Interactions 2.201 6 .367 .389 Perceived T. D. x Form .004 1 .004 .047 Perceived T. D. x Place .300 1 .300 .317 Perceived T. D. x Type .007 1 .007 .007 Form x Type .062 1 .062 .065 Form x Place .079 1 .079 .084 Type x Place .608 l .608 .644 Explained 28.122 10 2.812 2.979" Residual 88.734 94 .944 Total 116.856 104 1.124 Operational Source of Variation N Planning Level (Mean)a Perceived Tourism-Dependencya Nontourism-Dependent 92 4.47 Tourism-Dependent 13 4.83 Form of Ownership Sole Proprietorship 47 4.34 Partnership or Corporation 58 5.13 Place of Business Downtown 57 4.95 Away From Downtown 48 4.58 Type of Business Independent 91 4.75 Other 14 4.98 Grand Mean =- 4.78 R Square = .222 a7 Point Likert Scale 1 = Strongly Disagree 4 = Neutral 7 a Strongly Agree **p<.01 ***p<.001 63 2.4 No significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers. An ANOVA model was used to determine the effect tourism- dependency had on the structural planning level of tourism- dependent and nontourism-dependent retailers. The dependent variable was the structural planning level of retailers. The independent variable of perceived tourism-dependency was measured in the same manner as stated in hypothesis 2.1. Structured planning was identified by question numbers 25, 28, 38, and 43 and were measured by a seven-point Likert-type scale (1 = Strongly Disagree to 7 = Strongly Agree). These questions measured constructs identified by the Bracker and Pearson (1986) classification scheme as representing structural plans (Table 4.10). Information concerning the use of published industry data to make comparisons of performance to similar businesses was determined by question number 25 and represented the construct of utilizing information about past and current performance in planning. The extent to which businesses kept abreast of changes in the field by reading trade journals and business publications was measured by question number 28 and represented the construct of obtaining information about future performance. Whether or not businesses evaluated performance by comparison to competitors was assessed by question number 38 and represented the construct of determining the strengths and weaknesses of the business. Question number 43 ascertained whether respondents had written, formal, long-range business plans of 3-5 years in length and represented the 64 construct of written, long-range plans. A mean score was derived from the four measures of structured planning. As stated for hypothesis 2.1, the constructs utilized to measure structural planning did not represent all the planning options available to retailers. Other forms of structural planning may have been utilized by the retailers. This limitation may restrict the conclusions that can be drawn from the statistical results. Table 4.10 Questions Used to Measure Structured Planning. Question Number Description of Construct Measured 25 Information About Past and Current Performance 28 Information About Future Performance 3 8 Determination of Strengths and Weaknesses 43 Written, Long-Range Plans, 3-5 Years in Length Results of the ANOVA test revealed that the structural planning level of retailers was significantly different (p<.05) depending upon whether the retailer perceived its business to be tourism-dependent or nontourism-dependent (Table 4.11). The grand mean for structural planning level was 4.68. The mean difference between tourism-dependent and nontourism-dependent retailers was .60, indicating that the structural planning level of nontourism- dependent retailers was higher than that of tourism-dependent retailers. While the main effect produced a significant result, the 65 model explained only 3.5 percent of the variance in structured planning level. Due to these findings, hypothesis 2.4 was rejected. These findings indicated that nontourism-dependent retailers engaged in a higher level of planning sophistication than tourism- dependent retailers. However, the model was not highly significant. Table 4.11 Summary of Analysis of Variance in Structural Planning by Tourism-Dependent and Nontourism—Dependent Retailers. Sum of Mean F Source of Variation Squares df Square Value Main Effect 4.654 1 4.654 3.900* Explained 4.654 . 1 4.654 3.900* Residual 130.060 109 1.193 Total 134.714 110 1.225 Structural Source of Variation N Planning Level (Mean)a Perceived Tourism-Dependencya Nontourism-Dependent 9 6 4.76 Tourism-Dependent 1 5 4.16 Grand Mean = 4.68 R Square = .035 a7 Point Likert Scale 1 = Strongly Disagree 4 = Neutral 7 = Strongly Agree *p<.05 66 2.5 When controlling for length of time in business and sales volume, no significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers. Additional variables were analyzed in hypothesis 2.5 to control for factors which may affect the structural planning level of tourism- dependent and nontourism-dependent retailers. Pearson's correlation coefficients revealed that the covariates (length of time in business and sales volume) were more highly correlated with each other than with the dependent variable, therefore, ANOCOVA was not run. As previously stated, when the covariates are more highly correlated with each other than each is with the dependent variable there is no reason to run ANOCOVA (Hair et al., 1979). The findings of the Pearson's correlations were as follows: length of time in business and sales volume had a correlation coefficient of .26 (p<.006); length of time in business and structural planning had a correlation coefficient of .02 (p<.402); sales volume and structural planning had a correlation coefficient of .16 (p< .06). 2.6 No significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers by form of ownership, place of business, and type of business. ANOVA was conducted to determine if form .of ownership, place of business, and type of business would significantly affect the structural planning levels of tourism-dependent and nontourism- dependent retailers. The dependent and independent variables for hypothesis 2.6 were the same as those in hypothesis 2.4. However, 67 additional independent variables (form of ownership, place of business, and type of business) were added to the model. The independent variables were recoded as previously stated for hypothesis 2.3. Results of the AN OVA showed that form of ownership had the most significant (p<.001) effect on the level of structural planning of tourism-dependent and nontourism-dependent retailers (Table 4.12). Place of business (p<.01) and tourism-dependency (p<.05) were also significant. Although ANOVA results indicated that one interaction, tourism-dependency with place of business, was significant (p<.05), Scheffe post-hoe analysis did not detect the interaction effect. The small sample size did not enable higher order interactions to be run. The grand mean for structural planning level was 4.66. The means for tourism-dependency showed that nontourism-dependent retailers (4.74) participated in structural planning more than tourism-dependent retailers (4.17). Comparison of the means representing different forms of ownership revealed that retailers who were partnerships or corporations (5.07) participated in more structured planning than did those in sole proprietorships (4.14). Furthermore, retailers located in the downtown area (4.79) participated in a higher level of structural planning than did those located away from the downtown (4.50). Overall, these results indicated that perceived tourism-dependency (tourism-dependent and nontourism-dependent), form of ownership, and the location of retailers had an effect on the structural planning levels of retailers. The amount of variance in retailers' structural planning explained by the model was 26.6 percent. The F-value was 68 significant at p<.001. On the basis of these findings, hypothesis 2.6 was rejected. These findings are similar to those of hypothesis 2.3. As previously stated, they are not surprising due to the business characteristics of partnerships and corporations and the market environments of retailers located in downtown areas. 69 Table 4.12 Summary of Analysis of Variance in Structural Planning for Tourism-Dependent and Nontourism-Dependent Retailers by Form of Ownership, Place of Business, and Type of Business. Sum of Mean F Source of Variation Squares df Square Value Main Effects 34.644 4 8.661 9.874*** Perceived Tourism-Dependency4.243 1 4.243 4.837"I Form of Ownership 22.778 1 22.778 25.967*** Place of Business 6.010 1 6.010 6.851“ Type of Business 1.614 1 1.614 1.840 2-Way Interactions 9.458 6 1.576 1.797 Perceived T. D. x Form .125 l .125 .142 Perceived T. D. x Place 4.621 1 4.621 5.268" Perceived T. D. x Type .004 1 .004 .005 Form x Type .060 1 .060 .069 Form x Place 1.890 1 1.890 2.154 Type x Place 1.282 1 1.282 1.462 Explained 44.102 10 4.410 5.5028*** Residual 85.963 98 .877 Total 130.065 108 1.204 Structural Source of Variation N Planning Level (Mean)a Perceived Tourism-Dependencya Nontourism-Dependent 94 4.74 Tourism-Dependent 15 4.17 Form of Ownership Sole Proprietorship 48 4.14 Partnership or Corporation 61 5.07 Place of Business Downtown 60 4.79 Away From Downtown 49 4.50 Business Definition Independent 94 4.68 Other 15 4.55 Grand Mean = 4.66 R Square = .266 a7 Point Likert Scale 1 = Strongly Disagree 4 = Neutral 7 = Strongly Agree *p<.05, “1K 01, mp<.oor 70 2.7 No significant difference exists in financial performance among tourism-dependent and nontourism-dependent retailers as a result of structural or operational planning. ANOVA was undertaken in order to determine the effect structural and operational planning had on the profitability changes of tourism-dependent and nontourism-dependent retailers. The dependent variable for hypothesis 2.7 was the profitability changes (from the previous year) of retailers. Perceived tourism dependency (tourism-dependent and nontourism-dependent) and operational and structural planning levels were the independent variables and were measured in the same manner as stated for previous group two hypotheses. Financial performance was. ascertained by question numbers 58 and 59. Question number 58 provided information regarding retailers' dollar sales volume (increase/decrease), and question 59 provided retailers' dollar profit figures (increase/decrease). Retailers' financial performance was determined by dividing dollar profit (increase/decrease) by dollar sales volume (increase/ decrease). The result of this analysis was not significant (p<.05), therefore, hypothesis 2.7 was not rejected. It should be noted that these findings may have been affected by the small sample size due to the low response to financial performance information, in addition to the fact that the dependent variable measured changes in financial performance rather than profit itself. A summary of these findings is presented in Table C-3 in Appendix C. 71 2.8 When controlling for sales volume and length of time in business, no significant difference exists in financial performance among tourism-dependent and nontourism- dependent retailers as a result of structural or operational planning. Sales volume and length of time in business were added to the model to control for variables which may affect the financial performance of tourism-dependent and nontourism-dependent retailers. Pearson's correlation coefficients indicated that the covariates (length of time in business and sales volume) were more highly related to each other than to the dependent variable, therefore, ANOCOVA was not run. As previously stated, when the covariates are more highly correlated with each other than each is with the dependent variable there is no reason to run ANOCOVA (Hair et al., 1979). The results of the Pearson's correlation were as follows: length of time in business and sales volume had a correlation coefficient of .26 (p<.006); length of time in business and financial performance had a correlation coefficient of .11 (p<.216); sales volume and financial performance had a correlation coefficient of .12 (p<.190). 01"11 Determine the relation of selected dimensions of business planning (locus of causality, controllability, stability) to the financial performance and level of planning among tourism-dependent and nontourism-dependent retailers. W No significant difference exists between the attributions reflected in business planning and the financial performance and level of planning of tourism-dependent and nontourism-dependent retailers. 72 Group three hypotheses were broken down into three subhypotheses. The statistical test utilized to analyze each hypothesis was ANOVA. The process used to rate causal attribution dimensions was based on previous studies (Bettman & Weitz, 1983; Lau & Russell, 1980; Staw, Mckechnie & Puffer, 1983). This process consisted of two main steps. First, an expert panel was used to determine which planning strategy variables (questions 24-55) measured the attributions of locus of causality, controllability, and stability. In research situations where no objective measures exist for the constructs being analyzed, the use of an expert panel to identify specific measures is an accepted research technique (DeGroot, 1969; Goode & Hatt, 1952). Lau and Russell (1980) state that the process of using expert raters to code attributions results in a coding system that has construct validity. The expert panel consisted of four members: one university faculty member and three graduate students who were not associated with this research project, yet had research experience. The panel was asked to rate the planning strategies (questions 24- 55) according to the causal attribution dimension the planning strategy measured (locus of causality, controllability, stability, or none) (Appendix D-l). Rater instructions included a brief discussion of attribution theory and business planning, causal attribution dimension definitions, and unrelated examples. Results of this rating test indicated an inter-rater agreement of 81.8 percent. A summary 73 of the rating results for the planning strategies is presented in Appendix D-2. Ultimately, seven variables measuring locus of causality, four measuring controllability, and three measuring stability were selected by the raters. The seven variables reflecting locus of causality were reduced to four after correlation testing indicated multicollinearity. A summary of the variables finally selected to measure the causal attribution dimensions is presented in Table 4.13. Table 4.13 Summary of Variables Used to Measure Causal Attribution Dimensions. Causal Attribution Dimensions Questionnaire Item Numbers Locus of Causality 32, 46, 47, 51 Controllability 27, 29, 33, 44 Stability 30, 48, 49 Second, for testing purposes, each of the causal attribution dimensions was divided into two levels, high and low. Retailers who scored at the mean or higher on the variables of controllability, causality, and stability. were placed in the high category. Conversely, retailers who scored lower than the mean on these variables were placed in the low category. 74 3.1 No significant difference exists between the locus of causality, controllability, and stability dimensions of business planning and the financial performance of tourism-dependent and nontourism-dependent retailers. In order to determine the causal attribution effect of business plans (causality, controllability, and stability) on the financial performance of tourism-dependent and nontourism-dependent retailers, hypothesis 3.1 was tested through ANOVA. The dependent variable was the financial performance of retailers and was determined in the same manner as stated for group two hypotheses. The independent variables were the levels of causal attributions dimensions reflected in the business plans of tourism-dependent and nontourism-dependent retailers and was determined as previously discussed. Retailers' perceived tourism-dependency was determined in the same manner as stated for group two hypotheses. Results of this analysis was not significant (p<.05), therefore, hypothesis 3.1 was accepted. Table C4 in Appendix C contains a summary of these results. This finding suggests that the financial performance of tourism-dependent and nontourism-dependent retailers was not affected by the causal dimensions (locus of causality, controllability, and stability) of their business plans. However, these results may have been due to the measure used to determine financial performance which analyzed annual changes in profit in relation to changes in sales. This measure may not have been sensitive enough to determine financial performance. 75 3.2 No significant difference exists in the operational planning of tourism-dependent and nontourism-dependent retailers as a result of the level of causality, controllability and stability dimensions utilized in their business plans. Analysis of variance was undertaken to determine if statistically significant differences existed between the dimensions of controllability, causality, and stability and the operational planning of tourism-dependent and nontourism-dependent retailers. The dependent variable was the operational planning level of tourism- dependent and nontourism-dependent retailers. Operational planning level was determined in the same manner as stated for group two hypotheses. The levels (high and low) of causal attribution dimensions reflected in the business plans of tourism- dependent and nontourism—dependent retailers were the independent variables. Causal attribution levels were determined as previously stated for hypothesis 3.1. Retailers were classified as tourism-dependent or nontourism-dependent in the same manner as discussed for group two hypotheses. While tourism-dependency and stability were not significantly related to operational planning, the joint effect of the independent variables was significant (p<.001), with controllability (p<.001) and causality (p<.01) accounting for differences in the operational planning levels of tourism-dependent and nontourism-dependent retailers (Table 4.14). Furthermore, the amount of variance in operational planning level explained by the model was 25.6 percent. The F-value was significant at p<.01. Due to these results, hypothesis 3.2 was rejected. 76 Test results revealed that retailers who perceived a high degree of control in their business plans participated in a greater degree of operational planning (mean=5.2) than did retailers who perceived a low degree of control (mean=4.3). Similarly, retailers who perceived a high degree of causality (mean=5.2) in their business plans were greater operational planners than retailers perceiving a lower degree of causality (mean=4.3). These findings indicated that retailers who participated in high levels of operational planning perceived that they could directly control the causes of business performance through their operational planning. Additionally, retailers identified as operational planners perceived the locus of causality for business performance to be within the organization and utilized planning strategies directly related to operational functions (Bettman & Weitz, 1983; Ford, 1985; Weiner, 1985). 77 Table 4.14 Summary of Analysis of Variance in Operational Planning for Retailers by Controllability, Causality, Stability, and Perceived Tourism-Dependency. Sum of Mean F Source of Variation Squares df Square Value Main Effects 30.400 4 7.600 8.302'“M Controllability 20.871 1 20.871 22.799"* Causality 9.519 1 9.519 10.399" Stability .000 1 .000 .000 Perceived Tourism-Dependency .009 1 .009 .010 2-Way Interactions 2.707 6 .451 .493 Controllability x Causality 1.130 1 1.130 1.234 _ Controllability x Stability .002 l .002 .003 . Controllability x Perceived T.D. .475 l .475 .519 Causality x Stability .001 1 .001 .001 . Causality x Perceived T.D. .630 1 .630 .688 1 Stability x Perceived T.D. .517 1 .517 .565 J 3-Way Interactions .999 4 .250 .273 Control x Cause x Stability .185 1 .185 .202 Control x Cause x Perceived T. D. .190 l .190 .208 Control x Stability x Perceived T. D. .000 1 .000 .000 Cause x Stability x Perceived T. D. .402 1 .402 .439 4-Way Interactions .630 1 .630 .688 Control/ Cause] Stable] Perc. T. D. .630 1 .630 .688 Explained 34.736 15 2.316 2.530Ml Residual 84.221 92 .915 Total 118.957 107 1.112 78 Table 4.14 (cont'd.) Operational Source of Variation N Planning Level (Mean)a Controllabilitya Low 56 4.33 High 52 5.21 Causalitya Low 52 4.28 High 56 5.18 Stabilitya Low 45 4.66 High 63 4.81 Perceived Tourism-Dependencya Nontourism-Dependent 94 4.74 Tourism-Dependent 14 4.82 Grand Mean = 4.75 R Square = .256 a7 Point Likert Scale 1 = Strongly Disagree 4 = Neutral 7 = Strongly Agree **p<.01, *"p<.001 3.3 No significant difference exists in the structural planning of tourism-dependent and nontourism-dependent retailers as a result of the level of causality, controllability and stability dimensions utilized in their business plans. Within hypothesis 3.3, the relationship between the dimensions of causality, controllability and stability and the structural planning of tourism-dependent and nontourism-dependent retailers was tested. A review of Table 4.15 indicated a significant joint effect (p<.001) with the controllability variable (p<.001) producing significant differences in structural planning. These results indicated that retailers categorized as high controllers (mean=5.3) participated in a greater degree of structured planning than did retailers categorized as low controllers (mean=4.3). 79 The amount of variance in the structural planning level explained by the model was 27.8 percent. The F-value was significant at p<.001. Due to these results, hypothesis 3.3 was rejected. This finding was similar to that of hypothesis 3.2 in that retailers who participated in high levels of structured planning perceived they could directly control the causes of business performance through structured planning (Bettman & Weitz, 1983; Ford, 1985; Weiner, 1985). It is interesting to note that locus of causality was not significant as in hypothesis 3.2. Since structured planning represented a greater degree of planning sophistication, it would seem to follow that the locus of causality dimension would be utilized to a greater degree in the structured planning of retailers. 80 Table 4.15 Summary of Analysis of Variance in Structural Planning for Retailers by Controllability, Causality, Stability, and Perceived Tourism-Dependency. Sum of Mean F Source of Variation Squares df Square Value Main Effects 29.876 4 7.469 9739*“ Controllability 26.539 1 26.539 34.60?" Causality .107 l .107 .140 Stability .826 1 .826 1.077 Perceived Tourism-Dependency 2.404 1 2.404 3.135 2-Way Interactions 4.443 6 .740 .996 Controllability x Causality .017 1 .017 .023 Controllability x Stability 1.652 1 1.652 2.154 Controllability x Perceived T. D. .769 1 .769 1.002 Causality x Stability .210 1 .210 .274 Causality x Perceived T. D. .007 1 .007 .009 Stability x Perceived T. D. .399 1 .399 .520 3-Way Interactions 2.147 4 .537 .700 Control x Cause x Stability .014 1 .014 .018 Control x Cause x Perceived T. D. -887 1 .887 1.157 Control x Stability x Perceived T. D. .439 l .439 .572 Cause x Stability x Perceived T. D. .894 1 .894 1.166 4-Way Interactions .480 1 .480 .625 Control x Cause it Stable x Perc. T. D. .480 1 .480 .625 Explained 36.945 15 2.463 3212*" Residual 70.555 92 .767 Total 107.500 107 1.005 81 Table 4.15 (cont'd.) Structural Source of Variation N Planning Level (Mean)a Controllabilitya Low 56 4.27 High 52 5.26 Causalitya Low 52 4.51 High 56 4.97 Stabilitya Low 45 4.61 High 63 4.85 Perceived Tourism-Dependencya Nontourism-Dependent 94 4.79 Tourism-Dependent 14 4.46 Grand Mean = 4.75 R Square = .278 a7 Point Likert Scale 1 = Strongly Disagree 4 = Neutral 7 = Strongly Agree **p<.05. “"p<.001 82 CHAPTERV SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS This chapter is divided into four sections. Section one contains a summary of the research methodology, data analysis, and findings of the research. The second section presents the conclusions of this research study. Section three discusses limitations associated with the research. Lastly, section four contains recommendations for tourism—dependent retailers and future research. WW5 The overall intent of this study was to determine whether tourism-dependent retailers were different in their approach to business planning than nontourism-dependent retailers. The research objectives for this study were to ( 1) determine the relative importance of tourism trade to different types of retailers within tourism-dependent communities, (2) compare and contrast differences in business planning between tourism-dependent and nontourism-dependent retailers, and (3) determine the relation of selected dimensions of business planning (locus of causality, controllability, stability) to financial performance and level of planning sophistication among tourism-dependent and nontourism- dependent retailers. 83 This study involved the analysis of an existing data base as a means of investigating the planning practices of tourism-dependent and nontourism-dependent retailers. The data in the original study was collected through a structured self-report survey instrument that was specifically designed for the study. Three sections of the original questionnaire were analyzed in this thesis. These sections utilized Likert-type scales, open-ended and closed questions. Businesses that participated in the original study were selected from both tourism-dependent and nontourism-dependent communities located in the northern-lower and upper peninsulas of Michigan. Communities identified as nontourism-dependent were: Kalkaska, Manton, Onoway, McBain, and Marion. Tourism-dependent communities were identified as: Marquette, Mackinac Island, Mackinaw City, St. Ignace, Cheboygan, and Sault Ste. Marie. A stratified random sampling technique was used to select businesses from the study site locations. In 1985, the first wave of 653 questionnaires was mailed to the selected businesses. A second wave of 241 questionnaires was mailed in the summer of 1987. Of the 894 questionnaires sent, a total of 133 usable questionnaires were completed and returned, yielding a return rate of 15.2%, after adjusting for non-deliverable questionnaires. Descriptive analyses were used to compare the characteristics of tourism-dependent and nontourism-dependent retailer samples. Chi-square analysis, analysis of variance, and analysis of covariance models were employed to test the hypotheses. Comparisons of these analyses were made by the retailers' own perceptions of tourism- 84 dependency (tourism-dependent or nontourism-dependent). Results of the statistical analyses are presented in Table 5.1. 85 Table 5.1 Summary of Hypotheses Testing. Hypothesis Test Result H1.1 Chi-Square Analysis Not Significant Model Association of Research Classification and Retailers' Perception of Tourism- Dependency. H1.2 Chi-Square Analysis Significant Model Association of Importance of Tourism Trade to Retail Types. H2.l Analysis of Variance Not Significant Model Dependent Variable = Operational Planning Level Independent Variable = Perception of Tourism-Dependency (Tourism—Dependent and Nontourism-Dependent) H2.2 Analysis of Covariance Not Tested Model Dependent Variable = Operational Planning Level Independent Variable =. Perception of Tourism-Dependency (Tourism-Dependent and Nontourism-Dependent) Covariates = Length of Time In Business, Sales Volume 112.3 Analysis of Variance Significant Model Dependent Variable = Operational Planning Level Independent Variables = Perception of Tourism-Dependency, Form of Ownership, Business Location, Type of Business H2.4 Analysis of Variance Significant Model Dependent Variable = Structural Planning Level Independent Variable = Perception of Tourism-Dependency (Tourism-Dependent and Nontourism-Dependent) H2.5 Analysis of Covariance Not Tested Model Dependent Variable = Structural Planning Level Independent Variable = Perception of Tourism-Dependency (Tourism-Dependent and Nontourism-Dependent) Covariates = Length of Time In Business, Sales Volume 86 Table 5.1 (cont'd.) H2.6 Model H2.7 Model H2.8 Model H3.1 Model H3.2 Model H3.3 Model Analysis of Variance Dependent Variable = Structural Planning Level Independent Variables = Perception of Tourism-Dependency. Form of Ownership, Business Location, Type of Business Significant Analysis of Variance Dependent Variable = Financial Performance Independent Variables = Operational Planners, Structural Planners Not Significant Analysis of Covariance Not Tested Dependent Variable = Financial Performance Independent Variables = Operational Planners, Structural Planners Covariates a Sales Volume, Length of Time in Business Analysis of Variance Dependent Variables = Financial Performance Independent Variables = Controllability. Causality, Stability, and Tourism-Dependency Not Significant Analysis of Variance Significant Dependent Variable = Operational Planning Level Independent Variables = Controllability, Causality, Stability, and Perception of Tourism-Dependency Analysis of Variance Dependent Variable = Structural Planning Level Independent Variables = Controllability, Causality, Stability, and Perception of Tourism-Dependency Significant 87 Analysis of retailers' perception of how dependent their businesses were on tourism trade revealed that the majority of retailers located in tourism-dependent areas did not view themselves as being tourism-dependent. However, the tourism- dependency perception of retailers located in tourism-dependent areas was affected by retail type. Specifically, only those retailers involved in lodging, general retail, and nontourism-specific retail viewed themselves as being tourism-dependent, while tourism-area retailers in nontourism-specific retail, general retail, and food and beverage retailing perceived themselves to be nontourism- dependent. J ' '1 ‘ ' i 9‘ .,tlll‘,:'1”l 0 [.11-""1"! :10 H . 'D I B .I The difference in planning sophistication between tourism- dependent and nontourism-dependent retailers was determined by categorizing retailers' planning strategies as either operational or structured planning. Operational planning represented a short- range, informal planning strategy, whereas structured planning represented a long-range, formalized planning strategy. An analysis of the planning sophistication of retailers found no differences in the operational planning level of tourism-dependent and nontourism-dependent retailers. When further investigation of operational planning was undertaken, it was found that retailers who 88 were in partnerships or incorporated participated in a greater degree of operational planning than did those who were sole proprietors. Furthermore, retailers who were located in the downtown area were greater operational planners than those located away from the downtown area. An investigation of the structural planning levels of retailers revealed that nontourism-dependent retailers participated in a higher level of structural planning than did tourism-dependent retailers. Additionally, retailers operating in partnerships or corporations participated in more structured planning than did those in sole proprietorships. Furthermore, retailers located in downtown areas participated in higher levels of structural planning than did those located away from downtown. The effect planning sophistication (operational and structural) had on the financial performance of retailers was analyzed. Results of this analysis did not reveal significant differences between the financial performance of tourism-dependent and nontourism- dependent retailers as a result of planning sophistication. However, these findings may have been influenced by the small sample size caused by a lack of response to financial performance information on the questionnaire. ":0 0 ‘I P115101 0. .3 1‘ '. 11‘ 7,01. 0 u o .." -uili o h i i " 0 ran ‘ 5!. '10 alll‘ 0011201411014 0 ' "P421071 1!. For data analysis purposes, the causal dimensions (causality, controllability, stability) of business plans were categorized into two 89 levels, high and low. An analysis of how the financial performance of tourism-dependent and nontourism-dependent retailers was affected by the use of these causal dimension levels in business plans was undertaken. Results of this analysis did not reveal any significant differences in financial performance as a result of causal attribution dimension levels in business plans. Planning sophistication levels (operational and structural) among tourism-dependent and nontourism-dependent retailers were analyzed to determine the effect of controllability, causality, and stability planning dimensions. Analysis of tourism-dependent and nontourism-dependent retailers showed that no significant differences existed in operational planning resulting from the use of controllability, causality, and stability dimensions in business plans. However, retailers (tourism-dependent and nontourism-dependent) perceiving a high degree of controllability and causality in their business plans participated in a greater degree of operational planning than did retailers who perceived a low degree of controllability and causality. Conclusinns Results of this study provided insights into the business planning strategies utilized by tourism-dependent businesses as compared to nontourism-dependent businesses. Analysis of these findings allowed several conclusions to be drawn. First, findings revealed that the overall business planning of tourism-dependent retailers was not much different than that of other small nontourism-dependent retailers. Neither group engaged 90 in any significant amount of strategic planning. Rather, both groups focused predominantly on immediate tactical concerns affecting their daily operations. Previous research on small businesses, in general, has indicated that the strategic business plans for small firms should be informal, adaptable, and short-term (Median, 1986; Omura & Cooper, 1983; Robinson & Littlejohn, 1981; Scarborough & Zimmerer, 1987). In other words, small firm strategic business plans should be more operational than structural. However, tourism-dependent retailers operate in more complex and cyclical markets than do average small businesses (Manning & Powers, 1984; Mathieson & Wall, 1982; Mill & Morrison, 1985). Studies by Yip (1985) and Schwaninger (1986) suggested that businesses operating in dynamic markets need more structured and proactive planning methods. Second, findings indicated that Michigan retailers located in areas defined as tourism-dependent did not recognize the importance of tourism trade to their businesses. This seems to suggest that these businesses have not defined their target markets. Economic impact figures for 1986 indicated that tourism activity in Michigan generated $13 billion (Whisenhunt, 1987b). By not recognizing this potential, tourism area retailers are missing out on a large segment of their potential market. A third conclusion is that the lack of perception of tourism- dependency on the part of retailers located in tourism-dependent locations may explain why their planning does not significantly differ from other small nontourism-dependent retailers. Specifically, these retailers do not perceive themselves to be vulnerable to the unique 91 characteristics of their business environments. Research has shown that successful businesses are those that have appropriately defined their target markets and business environments and have developed business strategies that properly match the business to their environments (Bracker & Pearson, 1986; Cravens, 1986; Keown, Jacobs & Worthley, 1984). Because tourism-dependent retailers are subject to marked seasonal business cycles, greater attention to strategic business planning is merited. An analysis of how the planning level (operational or structural) of tourism-dependent retailers affects their financial performance did not yield significant differences. However, these results may have been due to the measure used to analyze financial performance of retailers. Specifically, financial performance was measured by analyzing profit changes from one year to the next. Actual changes in financial performance may have been small, contributing to a nonsignificant result. The fourth conclusion is that, regardless of tourism- dependency, retailers operating as partnerships or corporations plan more, both operationally and structurally, than sole proprietors. Studies on small businesses by Cohn & Lindberg (1972) and Unni (1981) concur with this conclusion. These findings are not surprising in view of the fact that businesses operating as partnerships or corporations generally have more resources and expertise available to aid in developing planning strategies than those in a single operator form. A fifth conclusion is that, regardless of tourism-dependency, retailers located in downtown areas plan more, both operationally 92 and structurally, than retailers located in areas away from the downtown. This conclusion is related to the findings of previous studies which determined that the nature of the environment in which a business operates affects its planning strategy (Ackelsberg & Arlow, 1985; Scarborough & Zimmerer, 1987). In the type of small towns analyzed in this study, the downtown area is typically the main center for shopping as opposed to shopping malls in metropolitan areas. Therefore, retailers located in the downtown areas of small towns are selling products to a more established and relatively homogeneous target market than retailers located in outlying areas that rely on a heterogeneous group of outshoppers (Carusone & Moscove, 1985). As a result, developing planning strategies may be a simpler task for retailers located in downtown areas as opposed to those located in more dynamic areas away from the downtown area. The research of Staw et al. (1983), Bettman and Weitz (1983), and Ford (1985) exemplifies how the attributional dimensions of locus of causality, controllability, and stability can be utilized to understand and explain the way in which an organization interacts with its environment. When applied to organizational research these attributional dimensions can be utilized to analyze the posture an organization takes towards its environment through an examination of the strategic planning factors it utilizes. A sixth conclusion is related to the analysis of attributional dimensions in business plans utilized by tourism-dependent and nontourism-dependent retailers. Specifically, it was concluded that tourism-dependent and nontourism-dependent retailers who 93 participated in a high level of operational planning perceived a high level of control and causality in their business plans. This researcher was unable to find specific research analyzing how the planning level (operational and structural) of retailers was affected by their causal schemata. However, applying the conclusions of general business research on causal attributions leads to two notions (Bettman & Weitz, 1983; Ford, 1985). First, retailers who are operational planners perceive that they have the ability to control their business environment. Second, retailers who are operational planners are attempting to manipulate the perceived causes of business performance. The last conclusion is that retailers who participated in a higher level of structural planning utilized a higher level of control in their business plans. Applying the conclusions from general attribution research leads to the conclusion that retailers who are structural planners perceive that they can control their business environments. I... This study involved the use of survey research methodology. Although a popular research method, many limitations are associated with the use of survey research (Babbie, 1986). Babbie discussed the limitations of survey research related to the use of structured questionnaires. Specifically, Babbie stated that structured questionnaire items are designed to assess attitudes and characteristics that are common to all respondents and use a finite number of measures. As a result, responses that are most appropriate to respondents may not be measured by a structured 94 survey. Perhaps an interview survey would be a more effective way to obtain precise responses, since it provides an opportunity to probe for additional information. A second limitation was the low response rate (15.2%) that resulted despite aggressive follow-up procedures. Although the response rate was not atypical for a study of this nature, it may have limited the representativeness of the sample and ultimately the findings (Babbie, 1986). The third limitation was the surprisingly large number of retailers located in tourism-dependent areas who did not perceive themselves to be tourism-dependent. This may be due to a lack of tourism-dependency awareness by retailers located in these areas or that the question used to determine tourism-dependency may not have been sensitive enough to detect differences. The fourth limitation was the low response to financial information by respondents. This lack of information restricted the ability to ascertain which planning strategies lead to successful tourism-dependent businesses. Financial information is generally difficult to obtain, but it is needed in future research in order to establish successful planning guidelines for tourism-dependent retailers. Also, the measure used to determine the financial performance of retailers analyzed changes in profit in relation to changes in sales from one year to the next. This measure may not have been sensitive enough to determine financial performance. A fifth limitation is related to the use of an adapted scheme from a previous study to classify the operational or structural planning levels of retailers. While research has been conducted 95 previously using these schemes they have never been applied to a study of tourism-dependent retailers. Future research should be directed at validating these schemes. A sixth limitation is related to the use of an expert panel to classify the causality, controllability, and stability attributional dimensions. Although an accepted research technique, the resulting classification scheme may not have the reliability of those previously tested (DeGroot, 1969; Goode & Hatt, 1952). The last limitation is that the study analyzed only tourism- dependent retailers in Michigan. Therefore, the results of the study are only generalizable to Michigan. Tourism-dependent retailers located in other parts of the United States may utilize different business planning strategies than tourism-dependent retailers in Michigan. Recommendations The first recommendation is that Michigan retailers located in northern tourism areas need to reevaluate their target markets and business environments in order to further their awareness of tourism-dependency. Since an accurate definition of one's business is a requisite to strategic planning, this reevaluation may serve to enlighten retailers to the unique and dynamic nature of their business environment and convince them of the merits of adopting a more structured planning approach. The reason for this lack of recognition on the part of tourism area retailers was not ascertained by this study. The second recommendation is that more research is needed in order to 96 determine why tourism-area retailers do not recognize the business potential tourists represent. Perhaps, as suggested by a previous research study, tourism-area retailers are not correctly identifying the needs of the tourists in their area and as a result are not successful in marketing products to this group (Witter, 1985). This phenomenon may cause tourism area retailers to shy away from the tourist market and rely on local residents for their business. It may be helpful for tourism-area retailers to work with their local chamber of commerce and travel bureau to help them "identify why people travel to their area. Retailers would then have a better idea of who their target markets are and could match product offerings to the needs of these groups. A positive relationship between structured planning and financial success was not evident. Therefore, the third recommendation is that more research is needed to determine if the lower level operational planning utilized by tourism-dependent retailers leads to successful business operations or if a higher level of structured planning or combination of the two strategies should be utilized by these retailers. Research results revealed that retailers operating as partnerships or corporations in downtown areas were involved in higher levels of operational and structural planning than those operating as sole proprietors away from the downtown area. These findings lead to the fourth recommendation that in remote areas sole proprietorships should increase their planning efforts. More research is needed to determine which planning level (operational or structural) would be most appropriate for these retailers. 97 There has been a lack of research on business planning of tourism-dependent retailers. A fifth recommendation is that the data generated from this study be used as a base to develop additional dimensions of planning strategies to analyze in future research. 98 APPENDICES 99 APPENDIX A QUESTIONNAIRE 100 1 2 3 4 S 6 OO "01 It” "us In It IS tor cctdlnq purposes ultl‘. BUSINESS SURVEY ThIs Is a regtonal study conducted by researchers at MichIgan State Unwerstty. We would appreCIate yr: .Ir assIsmnce In completing lhts auestronnalre The responses to 1m: questIonnaIre are anonymous. therefore, your answers wul be kept on the strictest confidence. None 01 the data wall be released tor IndeduaI respondents. IF YOU OWN MORE THAN ONE BUSINESS ESTABLISHMENT. PLEASE ANSWER THE QUESTIONS FOR THE BUSINESS TO WHICH THE QUESTIONNAIRE HAS BEEN ADDRESSEO. In thrs sectIon ol the questIonnaIre. we would lIlre to obtarn your Iudgment concerning the quality at "us area's tour-st attractmq Ieatures. Please cucle the number whlch Indicates your optnton. For example. it you were asked to rate the twenty 01 the area's drugstores and Ielt that they were 01 poor qualIty you should circle number 2. Exceptionally Exceptionally . . Poor Average Good 1. Faculrtues Ior water sports (e.g., beaches. saIIIng. szmmIng. water Skltng, etc.) ....................................................... 1 2 3 4 5 6 7 I7) 2. FaCIlItIes for golfing. tennrs. etc. ................................... 1 2 3 4 5 6 7 (81 Nature acthtIes such as hIlung, backpaclung. bIrdwatchIng. photography. etc. ................................................ _1 2 3 4 5 6 7 l9) 4. HustorIcaI and Cultural interest le...g museums. monuments. hIstorIcal buIIdIngs the pear: e. theIr tradItIons. muSIc. lestwals. etc.) .......... 1 2 3 4 5 6 7 (10) 5. BeautIIuI scenery lsIght-seemgl .................................... 1 2 3 4 S 6 7 l1 1 I 6. Pleasant attItudes ol the people .................................... 1 2 3 4 5 6 7 112) 7. Opportuntty for rest and relaxatIon ................................. 1 2 3 4 5 6 7 (13) 8. 571000an 780111188 ................................................ 1 2 3 4 5 5 7 (74) 9. Eat-n9 establishments (0 n . restaurants) ............................ 1 2 3 4 5 6 7 (15) 10. Entertainment teg . nIght IIleI ................................... 1 2 3 4 S 6 7 (16': 11. Sultaulc acnommodatuons (e.g., motels hotels. cottages. campgrounds. etc.) .................... 1 2 3 4 S 6 7 117) How Important do you thInlt the IOIImeg lcatures are In tourIsts‘ decrsIons to vusIt a tounst area? . V." Neutral v'” Untmponant Important 12. FacIlItIes for water sports (e.g., beaches saIlIng. szmmIng. water strung. etc.) ............. .. . 1 2 3 4 5 6 7 1'5) 13. Facmues lor golfing tennIs etc. ............................... 1 2 3 4 5 6 7 HS) 14. Nature .‘ICllleleS such as Mung backpaclung. bIrdwatchIng photography etc. .................... . . .. ............. . 1 2 3 4 5 6 7 I201 15 Histortcnl and Cultural Interest to q , museums. monuments. hastortcat buuqus. the people the" lrndttrons. musuz. lestwals. etc.) ..... . . . 1 2 3 4 S 6 7 I211 16. BeautIIul scenery lsIgtItcseeIngI ................................... l 2 3 4 5 6 7 I22) 17. Pleasant attItudcs ol the people , . ................................ 1 2 3 4 S 6 7 (23.) 18. Opportunnty for rest and IQ‘JXJIIOD .............................. 1 2 3 4 S 6 7 (2M 19. ShoppIng InCIIItIes .... . .. . ..... .................. 1 2 3 4 5 6 7 ‘25- 20. Entmq CS'IJIIII‘lllllIflIIIS II‘ «I rt:;.l.1umnl';I 1 2 3 4 5 6 7 i261 21. Entertamtrmut I'm; , mIIIIt mm 1 2 3 4 5 6 7 '27! 22. SUIIODIU .1t,cnrltmrld.tttttrw’1 (e 9., motels ”Ulli'S. cottages, cmnpqmunds etc.). ........ . ... 1 2 3 4 5 6 7 IISI Eacepttonally A Exceptionally Poor ""9. Good 23. In commnson to vaur perceptlon OI the Ideal resort. how womd you rate thvs tour-st area? _ . ,. . I. ... ........................ 1 2 3 4 5 6 7 (29) ‘ 'Q.‘ In this section of the questionnaIre we wOuld like to know yOur responses to the Icilowing busmess practices. indicate vaur agreement or disagreement to questions 24 through 55. 24. 25. 26. 27. 26. 36. 37. 39. 41. 42. 45. 47. 49. 51. 8.815 101 know my customers personally ..................................... I study published industry data for businesses like mine and compare the results of my operation with these. ............................. I use sales-perosouare foot of space I net sales divided by total number 0' Sauare feet of space) as a measure of productivity ................. I advertise consistently ltwice a month or more) in at least one medium le.g.. newspapers. direct mail, handbills. local television. radio. etc.). . I lteep abreast of changes in my field by reading trade journals and general business publications. ..................................... When a shipment comes in. it Is carefully checked to make sure the order is correct and the merchandise Is undamaged .................. Every month my books are balanced and my accOunts summarized. . . I know who my customers are. therefore. I cater to them rather than to all groups. ........................................................ I use gross profit margin per-dollar-of-cost investment in merchandise as a measure of productivity. ...................................... Before I mark down goods for clearance. I consider alternative or supplementary ways of movrng them -— such as special displays. repackaging. or including them In a package deal. ................... Goods that the customers may not be specifically looking for but are likely to buy on sight limpulse merchandise) are displayed near my store entrances and at other points that have heavy traffic. ........... I find it very Important to know what merchandise Is selling well. therefore. I keep sales. inventory and purchase records by types of merchandise categories. .......................................... When planning promotions. I try to obtain cooperative advertising “Md! from my suppliers. ......................................... I use an accountant 'o malre sure that I do not overpay my taxes. ..... l evaluate my own performance by shopping competitors to compare their assortments. prices. and promotional methods with my own. . .. l delegate as much authority as I can to those immediately responsible to me. freeing myself from unnecessary operating details. ........... I know how many units of each product I sell and base my purchase decisions on these figures for the next selling period ................. l consult my suppliers about dealer displays helpful to the promotion of their merchandise In my store .................................... If price competition Is important to my business. I will attempt to meet or beat competitors' prices. ........................................ Long range planning Is very important. therefore. lmalta sure that I have a written plan of where my business should be In three to five years. ........................................................... I frequently compare actual results with budget protections then adjust my plans accordingly. ............................................. I use net profit expressed as a percentage of net worth as a measure of productivity. ...................................................... I use selling cost percent (salary plus fringe benefits of a salesperson divided by the person's sales) as a measure of salaspuson produaivity. ...................................................... My employees have a great deal of input Into decisions such as what merchandise to carry and how to display and promote merchandise. . I always take advantage of trade discounts on merchandise that I Order. ............................................................ I always use suggested retail priee or keystoning (double the cost plus $1) to determrne markup. .......................................... I use electonic data base services for making business decisions. ..... I use stocktum (ratio of sales to the value of average inventory) as a measure of productivity. ........................................... If I were to get sick tomorrow. I have someone that I could depend on to run my business. ............................................... I use “co-op ads" with other merchants in my community. ........... When I plan my business expenses. I budget a salary for myself. ..... I view family members who work in my business the same as other employees. ....................................................... Strongly I depend primarIly upon tourist trade for business. therefore. I rarely 0m 1 1 1 1 1 1 1 I 1 1 1 1 1 1 I 1 1 1 I 1 1 1 2 MN Neutral 4 4 Please Smash Agree 6 7 (30) 6 7 I31) 6 7 (32) 6 7 133) 6 7 (34) 6 7 (35) 6 7 I36) 6 7 I37) 6 7 (38) 6 7 I39) 6 7 (40) 6 7 I41) 6 7 I42) 6 7 (43) 6 7 I44) 6 7 (45) 6 7 I46) 6 7 (47) 6 7 '18) 6 7 I49) 6 7 (50) 6 7 I51) 6 7 I52) 6 7 (53) 6 I (54) 6 7 (55) 6 7 (56) 6 7 ‘‘57) 6 7 I56) 6 7 (59) 6 7 I60) 6 7 l61I 102 $6. How long has your firm been In business? years ‘: ‘.: 57. Please Indicate your annual Sulus VOlllltlc ibelnre taxes) for the previous ye." S (:1, x ‘i l have not been in busmess long enough to answer this question. 7'." 58. Loolumi at last year‘s Iigures In dollars. how much has your sales volume increased or decreased as compared to II‘r: year before? Increased by . dollars I73 ‘8) Decreased by dollars (2 ‘ 12) l have not been In business long enough to answer this question. '2 13) 59. According to the net profit figures in dollars for last year. how much has yOur net prolit increased or decreased when compared with the year before last s figures? Increased by dollars (2 14 ISI Decreased by -. dollars (2 20 25I I have not been In business long «Ought to answer this question. '2 261 60. Please schIIy the percentage of not sales (e.g., expenses for adveflisrngnet sales) that you allocated toward each of the following expenses In the previous year? Cost of Goods Sold _ ___% (2 27-281 Advertising expense .. - _% (2 2930) Payroll expense _ - - -_ ."s (2 31-32) Rent expense _ _ _, _ - __°/. (2 3334) Insurance - - ._ __ ‘1. l2 35 36) Shrinkage (shoplifting expense) . - °'. (2 37-381 Other _ -. _ -- °’. (239-40) (Please specify) l have not been in business long enough to answer this question. . ..-_.- (2 41) 61. Please indicate the number of indwiduals you empIOyed monthly during the previous year. Jan. Feb. Mar Apr. May June (2 42-44) (245-471 (2 48-50) (2:51.53) (2254-561 (257-59) July Aug. Sept. Oct. Nov. Dec. (260 62) (2 63 65) I2 6668) (2 69.71) (2:72-74) I2 7577) l have not been In busmess long enough to answer this Question. (2 78) 62. Indicate the percentaiie of your sales volume that was achieved during each month of the previous year. Jan. Feb. Mar Apr. May June v. v. r. ... 9'. °'- (279-80) (3.7-8) (39-10) (311-121 (3:13-14) (315-16) July Aug. Sept. Oct. Nov. Dec. 0!. 0'. 0. 0'. Or. .‘° 100°. (317-18) (3119-20) (3 21 22) 32324) (3.2626) (327.28) I have not been III business loriu enouiih to answer this question. I3 29) 63. Based upon the personnel you employed for the previous maior toorist season. please indicate the number of each In the following groups. Male high school students (3 30 31) Fumaic hiuli sctiOOI students (3 32 33) 1.1.Ile college students I3 34-35) FI-rnaie college students (3 36 37) Male audits (other than college students) - ' (3 3839) Female adults (Other than college students) l3 40-411 Other . .. (3 42431 (Please speedy) Total Number EmpIOyed I have not been In business long enOOgh to answer this question. i3 44) 103 64 Based on y0ur personnel for the DICVIUJS'113IOTTOU!lslSe(t‘3cn please indlLJle the number that were employed from each group; Hum school students from your community .3 .15 .15; High school students from OuISide your community (3 47-48) College students from yOur community (3 49 50) College students from putSide vOur community (3 51-52) Adults lather than college students) from your community . - (353-54) Adults (other than college Students) from outSide your community _- (355-56) Relatives .. - (367-58) Others - __.. - (3359-60) (Please speCifyi Total Number Employed l have not been in business long enough to answer this queStion. --.. ... (3.61) 65. Based upon 'he sources used to hire employees during the previous mayor tOurist season. please indicate the number of yOur empIOyees that were hired through the following agencies andsor media types. 3f J" Re." I n F- ... Michigan Employment Security Commission ... ' (3 62 -63) Private Employment Agency ..- (164-65) Local Newspaper ._ (366-67) Newspaper - outside of area -... (3:68-69) Local Radio ---- (3170-71) Radio - outside of area ... (3172-73) Trade assoaation advertisements __ (3174-75) Rehire previous employees .. f3i'76-77) Walk-ins - - l3-‘78~79) Employee recommendations (478) University and college placement services (4:9-10) Published directories such as the Summer Employment Directory - (411-12) Relatives -..- (4.13-14.) Personal contacts - - (4.15-lb» Other (4.17-18) (Please speCilyl Total Number Hired l have not been in busmess long encugh to answer this Question. (4.19) 66. Indicate the legal form of ownership for your company. (4 20; n Sole Proprietorship l1) .- Partnership (2) _ - Corporation (3) 67. How would you define your busmess? (4.21) . Independent il) Chain (2) Franchise t3) Strongly Strongly Disagree Neutral Agree 67A. Purchases by t0urists represent i 2 3 4 5 6 7 (4 66) a mater part of my saies volume. 68 69. 104 Hliw Vii/(lull) IOU CLISSIIV 131m “Grilliiislirnnnfl (Bi'li'r‘f .-llf') Amount nit Jiiifitit‘rt rim) or (multr‘r'piriq smwces (I) AII‘vP'IISan .iitt‘l1(.v (2) Apparel .‘_)f1II (Ci "snow-s store excliirling shoe SIOre (3) All rlJlIirry or museum «1) Automobile repair shop (5) Banii 0r savings 8i loan (6) Battier shop l7) Beauty shop (8) Ml‘lt‘f‘llflnl'nUS personal SGHVICP“. i'?) Bowlma alleys billiard and or elcrtrtinit‘ .‘lrcndn (IO) Biinirtess rrl.iii.ii_iirrtti.-n( and ur rjonfiitltlntt serVIce (I1) Chtrl;[)ricttJrl17) Computer DYOUIJIHHTIDQ scrvrce ('13) Credit agency (14) DJIIV products store (15) Dentist i. . 0116) Department store and or mail enter ((7) Dressmakinq shop (18) Drug store (19) Eating and or drinking place (20) Elirirtlical "90.!” shop (21) Ertzpluyrnetil and It‘lllpofarv' liirlr) aiiirrir‘y (22) Erittirieeriitq .‘mdor arcnztmztural svrwces (23) Pam and or garden Slipp'v storei2r1) Fuel and or ice dealer (25) Furniture and or home furnishings store (26) Gasoline sewice station (27) Gift shop (28) What is your busmess location7 (4?: :1» Grocery store '29) Hardware and or Iarm equipment store (30) Hotel or motel (311 Lodqrnq place excludin‘: hetels or motels (32) Household appliances. TV. andior radio store (.33) Insurance agency (34) Jewelry store (35) Laundry. cleaners. and or other garment services (36) Legal services (37) Limited price variety store (38) Liquor store (39) Lumber and or DUIHII"13 materials store (40) Motor vehicle dealer (41) MiscellaneOus vehicle dealer (42) Physician (43) Retail bakery (44) Retail florist (45) Real estate office (46) Serwces to dwellings and other buildings (47) Shoe store (48) Shoe repair shop (49) Theater or motion pictures (50) Miscellaneous entertainment and recreation services (51) Tires. battery. and or accessory dealer (52) Miscellaneous repair serwce (53) Miscellaneous profess coal and related services (54) Vending machine operator (55) Other (56) (Please specify) (4 24) Downtown Busmess District ('1) Strip location close to but not in Downtown Business District (2) Strip location away from the Downtown Busmess District (3) Located in the largest city mall (4) Located in a mall other than the largest city :‘lall (5) Located in an area where there are no other trusrnesses (6) 70 81"UW is .i but (if ()I‘llJ'llIuIltllts‘ .‘lt.llvr'|v iiivrilviril in promoting tourism within the stair.r of Michigan. Some of these OYllilnllrIUOnS are sutipurti .1 ‘ry lilx ilnlinis Based upon your perception of the organization's ability to promote tourism that Will benefit your business. how would you allocate $100 among them 7 Travel Bureau. Department of Commerce (Dr-.irloner of "Yes M'chlgan" cairlpiiiqn pulilislier of The Guide to Lodging in Michigan 71. and other travel brochures. etc.) State Chamber of Commerce Local Chamber of Commerce Tourist Information Centers (Located in hiqrrc. ii, rest areas) (4 25 27) (4 28 30l (4 31 33) (4 34-36) Michigan Department of Natural Resources publisher of Michigan Natural Resources magazine) (4.37 39) AAA (American Automobile Assomationl (4 40-42) Travel Agents (4 43 45) Conference Bureaus (4 4r} 43) Local Merchant Assooations (4 49 SH Michigan Bell (publisher of Michigan Travel Directory) (4 52 ‘34) U P Travel and Recreation Association (4 5557) Other (4 53 60) (Please specdy) $100 What is your (our aim: summit miluaIHJ' classification (SIC) code? (a 61 64) I do not know my SIC code (4 Girl I 2 3 4 5 6 00 not Itll this in l! (ls ..J' coding purposes oriiy THANK YOU FOR YOUR ASSISTANCE IN COMPLETING THIS QUESTIONNAIRE. Michigan State UnivetSily Dr Brenda Witter 114 Human Ecology East Lansing. Michigan 48824 7 I 6662 105 US Postage P A l D [“l’ .- - . " ‘ “(1 PFIMIT NO 21 "'8' CM“ BUSINESS REPLY MAIL ”In" ~o .1 (A31 LANSlNG Ml POSTAGE WILL BE PAID LI" ADCFES‘SLL Miijhirmn SIMI- Univctsnv Dr Bri'nil.) Niltcr 1'14 Human Ecology East Lansing. Michigan 48824 (no 'OSTAGE NICESSARY (F MAILED m rut UNITED STAI’CS ‘ -$ iii Jar-J ‘-->? ..v or 106 APPENDIX B STANDARD INDUSTRIAL CLASSIFICATIONS 107 Appendix B-l Standard Industrial Classification Major Group Codes. Major Group. Code Description 17 50 52 53 54 55 56 57 58 59 70 72 73 75 76 79 80 Construction, Special Trade, Contractors Wholesale Trade- Durable Goods Building Materials, Hardware, Garden Supply, and Mobile Home Dealers General Merchandise Stores Food Stores Automotive Dealers and Gasoline Service Stations Apparel and Accessory Stores Furniture, Home Furnishings, and Equipment Stores Eating and Drinking Places Miscellaneous Retail )E Hotels, Roaming Houses, Camps, and Other Lodging Places Personal Services Business Services Automotive Repair, Services, and Garages Miscellaneous Repair Services Amusement and Recreation Services, Except Motion Pictures Health Services 108 APPENDIX C TABLES 109 Table C-l Comparison of Research Classification and Retailers' Perception as Tourism-Dependent or Nontourism- Dependent. Retailers' Perception Research Tourism- Nontourism- Classification Remnant Dependant Totals N N N (Row %) (Row %) (Row. %) Tourism- 1 5 . 8 3 9 8 Dependent (15.3%) (84.7%) (83.8%) Nontourism- 3 16 19 Dependent (15.8%) (84.2%) (16.2%) Column Total 1 8 9 9 1 17 ‘ (15.4%) (84.6%) (100%) Chi-Square =.003 df = 1 p = .96 110 Table C-2 Summary of Analysis of Variance in Operational Planning by Tourism-Dependent and Nontourism-Dependent Retailers. Sum of Mean F Source of Variation Squares df Square Value Main Effect .058 1 .058 .049 Explained .058 1 .058 .049 Residual 124.114 105 1.182 Total 124.172 106 1.171 Grand Mean = 4.77 n.s. R Squared = .02 111 Table C-3 Summary of Analysis of Variance in Financial Performance of Tourism-Dependent and Nontourism- Dependent Retailers by Operational and Structural Planning Level. Sum of Mean F Source of Variation Squares df Square Value Main Effects 3.825 2 1.913 .935 Operational .212 1 .212 .104 Structural 3.613 1 3.613 1.766 Two-Way Interactions .687 1 .687 .336 Op. Plan x St. Plan .687 1 .687 .336 Explained 4.513 3 1.504 .735 Residual 104.335 51 2.046 Total 108.848 54 2.016 Grand Mean = .49 ‘ n.s. R Squared = .187 112 Table C-4 Summary of Analysis of Variance in Financial Performance of Retailers by Controllability, Causality, Stability and Perceived Tourism-Dependency. Sum of . Mean F Source of Variation Squares df Square Value Main Effects 9.402 4 2.351 1.066 Controllability 5.181 1 5.181 2.350 Causality .008 1 .008 .004 Stability 3.496 1 3.496 1.586 Perceived T. D. .717 1 .717 .325 Two-Way Interactions 8.955 1.492 .677 3.312 1.502 2.223 1.008 Controllability x Causality 3.312 Controllability x Stability 2.223 Control x Perceived T. D. .010 .010 .005 Causality x Stability .470 .470 .213 Causality x Perceived T. D. .007 .007 .003 Stability x Perceived T. D. .002 .002 .001 Explained 18.357 10 1.836 .832 Residual 90.409 41 2.205 Total 108.766 51 2.133 Grand Mean = .51 n.s. R Squared = .086 113 APPENDIX D CAUSAL ATTRIBUTION RATINGS 114 Appendix D-l Causal Attribution Rating Test Rater _ Coding of Causal Attributions I l . ! 'I . I Attribution theory attempts to explain how individuals' perceptions of the causes of behavior and events influence them in resulting reactions. The theory is based on the concept that individuals are motivated to understand the causes of behavior and events in order to better control and predict the world around them. This causal reasoning process involves the use of attributions by individuals. Attributions are the result of cognitive processes which allow an individual to understand the cause of observed events. to assess responsibility for particular outcomes. or to assess the personal qualities of an individual involved in an observed event (Jones 8t Davis 1965; Kelley. 1973). !l"f!'l']] B'El' Research has shown that causal attributions form business decision makers' bases for taking action. that is. making plans. Specifically. planning strategies utilized by businesses reflect how they perceive and evaluate the linkage between events and possible causes (Daft & Weick. 1984). Therefore. investigating the planning strategies of businesses facilitates an understanding of the causal schemata of these attributions. DEE" EC l!'l' Causal attributions reflected in the planning strategies of businesses can be categorized along three dimensions: locus of causality. stability. and controllability (Weiner. 1979). l. Magnum-«A locus of causality dimension reflects decision makers' perceptions that the causes of business performance reside within the organization (internal) or outside the organization but within the environment or situation (external). Planning strategies of decision makers who perceive causes of performance as internal to the organization (mm mm would be based upon activities within the organization such as sales effort. product or process development. quality control. production efficiency. management expertise. and work force skill. etc.. Planning strategies of decision makers with an WW would be based little on internal organizational activities because causes of performance are perceived to be external to the organization such as the economy. competition. govemments' action. technological changes. demographic shifts. market prices. and weather (Bettman & Weitz. 1983; Ford. 1985). 2. mam-Stability is a dimension which indicates decision makers' perceptions of the relative duration of the causes of performance (Lau dt Russell. 1980; Ford. 1985). A an“; dimension of business planning reflects decision makers' perceptions that the causes of business performance w and may predict similar future outcomes. Because stable causes of 115 business performance are viewed as permanent. planning strategies would be ..ulllC (i.e. always using the same strategy) and would not be monitored for change. For example. relatively unchanging production or program costs. An W dimension of business planning reflects decision makers' perceptions that the causes of business performance W. Because unstable causes of business performance are viewed as temporary. planning strategies would be dynamic and monitored for change. For example. dynamic changes in profitability. 3. WuControllability is a dimension that reflects decision makers' perceptions of their power to change the causes of performance (Ford. 1985). Planning strategies of decision makers who view the causes of business performance as W would involve activities under his/her W such as level of effort. acquisition decisions. level of strategic planning. and research and development activity. Planning strategies of decision makers who view the causes of business performance as W would involve Wu, on the part of the decision maker. This lack of direct activity is due to the perception that causes of business performance are out of the direct control of the decision maker such as in the weather. limits to ability. market prices. and the government (Bettman & Weitz. 1983; Ford. 1985). Eamnlss The following statements taken from annual reports contain the three dimensions of causal attributions (locus of causality. controllability. stability) (Bettman 8t Weitz. 1983). Although these statements are not the same as the planning strategies of the study you will be asked to classify. they serve to further illustrate the three dimensions of causal attributions. 1. "This net income was a historical high for the mine (unstable). and was due to higher prices on the free market (external) where all production was sold (uncontrollable). 2. ”...continues to maintain its program (controllable) for new product design (internal). Such a program is costly (stable). however. and this cost is reflected in the modest profits. Please continue on next page. 116 Instructions Using the preceding definitions. discussion. and examples please classrfy the following planning strategies according to which dimension of causal attribution (locus of causality. controllability. stability) you feel they reflect. Circle the number corresponding to the selected dimension (l=locus of causality. 2=controllability. =stability) for each item (1-16). If you feel that a planning strategy cannot be classified into one of the three dimensions circle "4" for "none". 1. Locus of Causality I depend primarily upon tourist trade for business, therefore. I rarely know my customers personally. (24) l advertise consistently (twice a month or more) in at least one medium (e.g. news- papers. direct mail. handbills.local tele- vision. radio. etc.). (27) When a shipment comes in. it is carefully checked to make sure the order is correct and the merchandise is undamaged. (29) Every month my books are balanced and my accounts sumized. (30) I use gross profit mrgin per-dollaroof- cost investment in merchandise as a measure of productivity. (32) Before I mark down goods for clear-ice. I consider alternative or supplementary ways of moving themosuch as special displays. repackaging. or including them in a package deal. (33) 1 find it very important to know what mer- chandise is selling well. therefore. 1 keep sales. inventory and purchase records by types of merchandise categories. (35) 1 know how many units of each product I . sell and base my purchase decisions on these figures for the nest selling period. 1 Controllability Stability None 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 10. 11. 12. 14. 15. 16. 117 Locus ”Controllability Stability of Causality IJ U l consult my suppliers about dealer dis- 1 plays helpful to the promotion of their merchandise in my store. (41) l frequently compare actual results with l 2 3 budget projections then adjust my plans accordingly. (44) 1 use net profit expressed as a percentage 1 2 3 of net worth as a measure of salesperson productivity. (45) I use selling cost percent (salary plus 1 2 3 fringe benefits of a salesperson divided by the person's sales) as a measure of sales- person productivity. (46) My employees have a great deal of input 1 2 3 into decisions such as what merchandise to carry lid how to display and promote mer- chandise. (47) 1 always take advantage of trade discounts l 2 3 on merchandise that I order. (48) 1 always use suggested retail price or key- I 2 3 stoning (double the cost plus $1) to deter- mine markup. (49) I use stockturn (ratio of sales to the value 1 2 3 of average inventory) as a measure of productivity. (Sl) J] l E . I . None 118 Appendix D-2 Results of Expert Panel Categorization of Variables Measuring Causality, Controllability, and Stability. W Item Number Rater 1. 2. 3. 4. 27 2 2 2 3 29 2 2 4 2 3 0 3 3 2 3 3 2 1 1 3 1 3 3 2 2 3 2 44 2 2 3 2 46 1 l 1 1 47 1 1 3 l 48 3 3 2 3 49 3 3 3 3 5 1 1 1 1 1 1 = Locus of causality Overall Inter-Rater Agreement = 81.8% 2 = Controllability 3 = Stability 4 = None of the dimensions 119 REFERENCE LIST 120 REFERENCELIST Ackelsberg, R. & Arlow, P. (1985). Small businesses do plan and it Pays off. LcnsJanaLElanninnm. 61-67. Babbie. E. (1986). Wk Belmont. CA: Wadsworth Publishing Company. Bains, G. (1983). Explanations and the need for control. In M. Hewstone (Ed). WWW. W (pp. 126+). Oxford, England: Basil Blackwell. Bamberger, I. (1986). Values and strategic behavior. Management IntemationalJezim 2.6.. 57- 69. Baron, R» A- & Byrne. D. (1984). Wine. W (4th ed.). Newton, MA: Allyn and Bacon. Beard, D. W. & Dess, G. G. (1981). Corporate-level strategy, business- level strategy, and firm performance. WW mutual. 24.. 663-688- Bettman, J. R. & Weitz, B. A. (1983). Attributions in the board room: causal reasoning in corporate annual reports. mm W 2.8.. 165-183 Bourgeois, L. I. III. (1980). Strategy and environment: A conceptual integration. AcademLcLManagemenLRsximi (1). 25-39. Bracker, J. S. & Pearson, J. N. (1986). Planning and financial performance of small, mature firms. W 1.9111131. 1. 503- 522. Bureau of the Budget. (1967). MW Mannal. Washington D. C.: U. 8. Government Printing Office. 121 Carusone, P. S. & Moscove, B. J. (1985). Special marketing problems of smaller-city retailing humalJLthLAcademmMarkctina. Sciencnu (3). 198-211 Cohn. T. & Lindberg. R. A. (1972). W W. New York: American Management Association. Cooper, A. C. (1979). Strategic management: New ventures and small business. In D. E. Schendel & C. W. Hofer (Ed.), m Mmgomom. (pp. 316-327). Boston, MA: Little, Brown and Co.. Cravens, D. W. (1986). Strategic forces affecting marketing strategy. W 2.9.. 77- 86 Cyert. R. M. & March. J. G. (1963). WWW Engelwood Cliffs, N.J.: Prentice-Hall. Deft, R. L. & Weick, K. E. (1984). Towards a model of organizations as interpretation systems. Wain. 9.. 284- 295. Davis, 3., Pysarchik, D., Sternquist, B. & Chappelle, D. (1987). A_ is. ‘ C 0 °ti"-'1I‘t é!‘ \OI-OOIIP‘O'19‘l Rotaflozs (Report No. 484). East Lansing, MI: Michigan State University Agricultural Experiment Station. DeGroot, A. D. (1969). Mothooology. Belgium: Mouton & Co.. Fink, S., Beak, J., & Taddeo, K. (1971). Organizational crisis and change WW1. 15- 27 Ford, Jeffrey D. (1985). The effects of causal attributions on decision makers' responses to performance downturns. ARMY—Qt. W. 1.0. 770-786. Fry, F. L. & Stoner, C. R. (1985). Business plans. two major types. MWWLZL 1-.5 Ginter, P. M., Rucks, A. C. & Duncan, W. J. (1985). Planners' perception of the strategic management process. LoumoLoL W22. 581-595. 122 Goode, W. J. & Hatt, P. K. (1952). Waggon. New York, NY: McGraw Hill Book Co. Inc.. Hair, J. R, Anderson, R. E., Tatham, R. L. & Grablowsky, B. J. (1979) W. Tulsa, Oklahoma: Petroleum Publishing Company. Hambrick, D. C. (1980). Operationalizing the concept of business- level strategy in research. WM 5.. 567-575 . Hedberg, B., Nystrom, P., & Starbuck, W. (1976). Camping on seesaws: Prescriptions for a self-designing organization. Wfluués VHeider. F. (1958). W. New 0’7? York: John Wiley & Sons. 6 34 . y 3.3"} Hewstone, M. (1983). Attribution theory and common-sense explanations: An introductory overview. In M. Hewstone (Ed.), {/19 ...) .3, , WWW (pp-1-26)- /, , Oxford, England: Basil Blackwell. 2. :1 Hofer, C. & Schendel, D. (1978). W 99.119.99.13. St. Paul. MN; West Publishing. Jafari, J. (1983). Anatomy of the travel industry. WM QuaneflLZQJMay). 71-77. Jones, E. E. & Davis, K. E. (1965). From acts to dispositions: The attribution process in social perception. In L. Berkowitz (Ed.,) W N ew York Academic Press. Kelley. H. H. (1971). AntihnngnLJnJmiaIJmeractinn Morristown. N. J.: General Learning Press. {Ll/151'. (1973). The process of causal attribution. . anthologies. 2.8.. 107-128. Amn— Keown, C., Jacobs, L. & Worthley, R. (1984). American tourists' perceptions of retail stores in 12 selected countries. lounmLoL mm 2.2 (Winter). 26-30. 123 LaFarge, R. W., Reese, R. M. & Stanton, W. W. (1984). Identifying and attracting consumer outshoppers. WWW Management. 22 (January). 22- 29. Lau, R. D. & Russell, D. (1980). Attributions in the sports pages. Walla. 3.2. 29-38. Lazer, W. (1981) A scenario of the future-the next fifteen years. In J D Ffidsen&D J Allen (EdS). WM. W (pp. 69-76). East Lansing, MI: Department of Parks and Recreational Resources, Michigan State University. Lefcourt, H. M. (1976). W. Hillsdale, N. J.: Lawrence Erlbaum Associates. Macriello, I. A. (1984). W. Englewood Cliffs, NJ .: Prentice-Hall. Maddox, R. N. (1986). Factors contributing to satisfaction with tourism: the residents view. In Academy of Marketing Science, 0 r n ‘a “ it. wit” .0 -l' 't It 0a it «- (vol. 2) (pp. 76-84). Manning, R. E. & Powers, L. A. (1984). Peak and off-peak use: Redistributing the outdoor recreation/tourism load. ,[oumaLQL ImeLResearch. 23. (Fall). 25-31. Mathieson. A & Wall. C (1982) WW. W. New York: Longman Group Limited. Meidan, A. (1986). Business strategies of small versus large firms. MW 24. (4). 102-112. Miles. R. E. & Snow. C. C. (1978). Wm... W. New York: McGraw-Hill. Miles. R. H. (1982). MW Englewood Cliffs, N .J .: Prentice-Hall. Mill, C. M. & Morrison, A. M. (1985). W. Englewood Cliffs, N. J.: Prentice-Hall. 124 Miller, D. & Ross, M. (1975) Self-serving biases in attribution of causality: Fact or fiction? RayohologioaLBnllonn, 82, 213- 225. Mitchell, T. R. & Green, S. G. (1978). Leadership and poor performance: An attributional analysis. In R. J. Hackman, E. E. Lawler. III & L W Porter (EdS). W nganjzationa (2nd ed.) (pp. 510+). New York: McGraw-Hill. More restaurants survive in 1985. (1986). W W 6 (4). 37-37. Moyer, R. (1982). Strategic planning for the small firm. 101mm W111. 8- 14 Murgittroyd. C. & Doherty, J. (1986). Tourism in Michigan. Michigan Emnnmx. 5. (1). 3-7 Omura, G. S. & Cooper, B. M. (1983). Three strategic planning techniques for retailers. mm 11 (1), 2-8. O'Neill, H. M. & Duker, J. (1986). Survival and failure in small businesses W. 2.4. (January). 30- 37. Orpen, C. (1985). The effects of long-range planning on small business performance: A further examination. JonmaLoLSmalL W23. 623 Phares, E. J. (1965). Internal-external control as a determinant of amount of social influence exerted. W W 2. 642- 647. Pysarchik, D. (1989). Tourism retailing. In S. F. Witt & L. Moutinho (EdS). loudsnLMatkeununLManagemenLHandhook. United Kingdom. Prentice Hall International. Ritchie, I. R. & Zins, M. (1978). Culture as determinant of the attractiveness of a tourism region. W, 5 (April- June), 252- 269. Robinson, R. B. , Jr. (1983). Measures of small firm effectiveness for strategic planning research. W Management. 21. (2). 22-29. 125 Robinson, R. B. , Jr., & Littlejohn, W. F. (1981). Important contingencies in small firm planning. W Managemnt. 12 (April). 45-48. Robinson, R. B. , Jr., & Pearce, J. A., H. (1984). Research thrusts in small firm strategic planning- WM. 2 (1), 128-137. Rosenfeld, Jeffrey P. (1986). Demographics on vacation. AmorioaL 22212222211122. (January). 38-41. 58. Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. EoyohologioaL_Monograohs, 8_O_ (1), 1-28. Rotter, J. B. & Hochreich, D. J. (1975). W. Scott, Foresman and Company. Rovelstad, J. M. (1981). State of the art in tourism research: an applied perspective. In J. D. Fridgen & D. J. Allen (Eds.,) Mjohigan_ W212i (PP 55-60) East Lansing. MI: Department of Parks and Recreational Resources, Michigan State University. Rovelstad, J. M. & Blazer, S. R. (1983). Research and strategic marketing on tourism: A status report. WWII. 2.2, (2), 2-7. Scarborough, N. M. & Zimmerer, T. W. (1987). Strategic planning for the small business. Easiness. (April-June), 11-19. Schwaninger, M. (1986). Strategic business management in tourism Inuflsm_Manag2tn2nt. (June). 74 85. Seeman, M., & Evans, J. W. (1962). Alienation and learning in a hOSPital setting MW. 21. 772-783 Sexton, D. L. & Van Auken, P. M. (1982). Prevalence of strategic planning in small business WWW. 2_Q, 21 -.26 126 (1985). A longitudinal study of small business strategic Planning humaLoLSmMnnaLManagm. 23. (1) 7- 15 Spandoni, M. (1986, July 14). Marketing takes to the highroad. We. 52 Staw, B, Mckechnie, P., & Puffer, S. (1983). The justification of organizational performance W18. 582-600. 'Tourism vital for economic growth'--Governor. (1984). Mighigam’a 2 (3). 1-3. Tuttle, D. F. (1987, February 16). Whether your business is tourism or not, tourism is your business. W, 3-6, 8. Unni, K. V. (1981). The role of strategic planning in small businesses. MW 14. (April), 54-58. U.S. travel and tourism industry highlights. (1984, May 28). W 6. U 8 Travel Data Center (1986- 87) W W. Washington, D. C. :(:ISSN 0733 -642X). Weiner, B. (1979). A theory of motivation for some classroom eXPeriences loumalJLEdncationallsxchology. 7.1 (l). 3 -25 (1985). Human Motivation. New York, NY: Springer- Velag. Weiner, B., Nierenberg, R. & Goldstein, M. (1976). Social learning (locus of control) versus attributional (causal stability) interpretations of expectancy of success. Wily. 43.. 52-68. Welsh, J. A. & White, J. F. (1981). A small business is not a little big business. WW :2 (July-August), 18- 20, 22, 24, 26, 28- 30, 31. Whisenhunt. E. (1987a). Travel and tourism. MW. 3, (12), 28-31. 127 (1987b). Take it higher. Winona, 1 (12), 34-37. Witter, B., Sternquist. (1985). Attitudes about a resort area: A comparison of tourist and local retailers. LoumaLoLIrayoL Wu (1). 14-19. Yip, G. (1985). Who needs strategic planning. W 311W 6. (2). 30-34.