. $qu m S... .C 1.35.“ 3.! a!“ q .. {(23. w) 1.1)! :2! x; .. , 5.0” an". iin 1.4! s! u: z . _ z? L» .. e . uw «it»... .c0..o...._.~ : 1 sAila. 1").v‘ €1.er . “0.1.2 u Thing. in? 4....n.....1_....f;.$i .E. 2 : é Iu‘i'li'i'liiliii]tl‘ii‘liiifliiiiiiiiil 3 1293 01555 3187 This is to certify that the dissertation entitled HOME-BAS- FAHILY BUSINESSES' NET ANNUAL INCOME AND ITS RELATIONSHIP TO BUSINESS , FAMILY, OWNER-MANAGER AND ENVIRONMENTAL CHARACTERISTICS IN THE UNITED STATES presented by Luis G. Maldonado has been accepted towards fulfillrnent of the requirements for Ph.D. Family and Child Ecology degree in Date WM MSU is an Affirmative Action/Equal Opportunity Institution 0-12771 PJBRARY M'Chigan State University PLACE IN RETURN 80X to remove this checkout from your record. TO AVOID FINES rotum on or before date duo. MSUJoAn Affirmative Mend Opportunity Inflation Walla-9.1 HOME-BASED FAMILY BUSINESSES’ NET ANNUAL INCOME AND ITS RELATIONSHIP TO BUSINESS, FAMILY. OWNER-MANAGER, AND ENVIRONMENTAL CHARACTERISTICS IN THE UNITED STATES By LUIS G. MALDONADO A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Family and Child Ecology 1996 ABSTRACT HOME-BASED FAMILY BUSINESSES’ NET ANNUAL INCOME AND ITS RELATIONSHIP TO BUSINESS, FAMILY, OWNER-MANAGER, AND ENVIRONMENTAL CHARACTERISTICS IN THE UNITED STATES By Luis G. Maldonado This study was designed to analyze and describe influences on home- based family business net annual income in nine US. states. Specifically, it examined the effects of four domain characteristics; business, family, owner- manager, and environmental on home-based family business net annual income. For each domain it was hypothesized that there is a linear relationship between the domain and home-based family business net annual income. Moreover, it was hypothesized that there is a linear relationship between the integrated four domains and net annual income. These five research hypotheses were tested using multiple regression equations such as y: [)0 + b1 (X1) + D2 (X2) + ........... + bp (Xp). The data used were generated from interviewing 899 household managers by telephone in 1989. Households from nine states participated in the Luis G. Maldonado study: Hawaii, Iowa, Michigan, Missouri, New York, Ohio, Pennsylvania, Utah, and Vermont. The focus was on families in which at least one individual generated income by working at or from the home. This study used a subsample of 620 families who owned and operated a business at home from the 899 household managers that were interviewed. The study found that three separate domains: Business, Owner-Manager, and Environmental and the integrated business, owner-manager, family and environmental domains were linearly related to home—based family business net annual income. Moreover, the business domain variables had the largest standardized regression coefficients (Betas). However, the owner-manager characteristics domain had the largest coefficient of determination (R2). The following variables were the most relative important in predicting home-based family business net annual income: Categories of occupation, categories of education, hours of work, gender, and marital status. All these variables were statistically significant at the .05 level. To my parents Luis Alberto and Elma Asuncion. iv ACKNOWLEDGMENTS I wish to express my deep appreciation to Dr. Rosemary Walker who served as my doctoral program advisor and dissertation committee chairperson. I would like to thank Dr. Walker for her joyful approach to teaching, creativity and flexibility as well as for her concern with accuracy and my professional growth. Without her thoughtful guidance the completion of this dissertation would have been more difficult. Special appreciation is also extended to Drs. Norma Bobbitt, Frank Bobbitt, and Dennis Keefe, members of my committee. I would like to thank Drs. Norma and Frank Bobbitt for their suggestions and advice; and, to Dr. Dennis Keefe, for his concern with my ecological growth. Appreciation is also proffered to the W. K. Kellogg Foundation for its financial support through my study. Moreover, I want to thank Dr. Marjorie Kostelnik, Chairperson of the Department of Family and Child Ecology; lng. Pedro Gonzalez, Dean of the College of Agricultural Sciences at the National University of Asuncion-Paraguay; the late lng. Nelson De Barros Barreto, and Dr. Meredith Smith who supported me financially and academically through my doctoral program. Finally, I wish to thank Dr. Linda Nelson for her contagious excitement over my ecological growth and for editorial assistance. Also Drs. Yonis Reyes and Lillian Phenice for their encouragement to pursue my doctoral degree. TABLE OF CONTENTS Page LIST OF TABLES .............................................................................................. x LIST OF FIGURES ......................................................................................... xiii CHAPTER 1. INTRODUCTION ......................................................................... 1 Problem Statement ................................................................................. 4 Purpose of the Study .............................................................................. 5 Importance of the Study .......................................................................... 5 Conceptual framework ............................................................................ 6 Organism ..................................................................................... 9 Environments ............................................................................... 9 Organization .............................................................................. 10 Conceptual Model to Study Home-based Family Businesses .............. 16 CHAPTER 2. REVIEW OF LITERATURE ....................................................... 20 Home-based Family Business Financial Success ................................ 2O Home-based Family Business .............................................................. 23 Home—based Family Business Characteristics ..................................... 27 Occupation ................................................................................ 28 Borrowed Capital ....................................................................... 29 Seasonality ................................................................................ 30 Home-based Family Business Size .......................................... 32 Home-based Family Business Age ........................................... 33 Urban/Rural Location ................................................................ 34 Business Management .............................................................. 34 Family Characteristics .......................................................................... 37 Family Functioning Type ........................................................... 38 Family Size ................................................................................ 40 Presence of Children Under 6 Years Old .................................. 42 Dependents Needing Care ........................................................ 42 Family Management .................................................................. 43 Home-based Family Business Owner-Manager characteristics ...................................................................................... 45 Age ........................................................................................... 45 vi Gender ..................................................................................... 46 Education .................................................................................. 49 Marital Status ............................................................................ 50 Expedence ................................................................................ 51 Hours of Work ........................................................................... 53 Environmental Characteristics ............................................................. 54 Chapter Summary ................................................................................ 57 CHAPTER 3. METHODOLOGY ..................................................................... 60 Data ..................................................................................................... 61 Sample Selection ................................................................................. 61 Dependent Variable ............................................................................. 63 Home-based Family Business Net Annual Income ................... 63 Independent Variables ......................................................................... 64 Business Characteristics.................... ....................................... 64 Occupation ...................................................................... 64 Borrowed capital ............................................................. 65 Seasonality ..................................................................... 66 Home-based family business size .................................. 66 Urban .............................................................................. 67 Home-based family business age ................................... 68 Business management of home-based business owners .............................................................. 68 Family Characteristics ................................................................ 69 Open family functioning type ............................................ 69 Presence of children under 6 years old ........................... 70 Dependents needing care ................................................ 71 Family size ....................................................................... 71 Family management ......................................................... 72 Owner-manager Characteristics .................................................. 73 Age ................................................................................... 73 Gender ............................................................................. 74 Education ......................................................................... 74 Marital status .................................................................... 75 Work experience .............................................................. 75 Total hours of work ........................................................... 76 Environmental Characteristics .................................................... 77 Unemployment rate 1988 ................................................. 77 Per capita personal income for 1988 ............................... 78 Investment 1988 ............................................................... 79 Population density ............................................................ 79 Research Questions .............................................................................. 80 Research Hypotheses ........................................................................... 81 vii Research Instrument .............................................................................. 82 Management Instruments ........................................................... 83 Data Analysis Procedures ...................................................................... 84 Research Question 1 ................................................................... 86 Research Question 2 ................................................................... 88 Research Question 3 ................................................................... 89 Research Question 4; ............. ‘. .................................................... 90 Research Question 5 ................................................................... 91 Generalizability ....................................................................................... 93 Limitations of the Study ........................................................................... 94 CHAPTER 4. ANALYSIS AND RESULTS ....................................................... 96 Checking Multiple Regression Assumptions .......................................... 96 Descriptives ............................................................................................. 97 Home-based Family Business Net Annual Income ....................... 97 Owner-Manager Characteristics ................................................... 98 Age ..................................................................................... 98 Gender ............................................................................... 99 Educafion ......................................................................... 100 Marital status .................................................................... 101 Work experience .............................................................. 102 Hours of work ................................................................... 103 Business Characteristics ............................................................ 104 Occupation ....................................................................... 104 Borrowed capital ............................................................... 105 Seasonality ....................................................................... 105 Home-based family business size .................................... 106 Urban/rural location .......................................................... 107 Home-based family business age ..................................... 108 Business management ...................................................... 119 Family Characteristics ................................................................. 110 Open family functioning type ............................................. 1 10 Children under 6 .............................................................. 111 Dependents needing care ................................................. 111 Family size ........................................................................ 112 Family management .......................................................... 113 Environmental Characteristics ..................................................... 1 14 Unemployment rate, 1 988 .................................................. 1 14 Per capita personal income, 1988 ...................... _ .............. 115 Investments 1988 .............................................................. 1 17 Population density ............................................................ 117 Summary of Descriptives ....................................................................... 118 Regression Results ............................................................................... 120 Research Question 1 ................................................................... 120 Research Question 2 ................................................................... 125 viii Research Question 3 ................................................................... 126 Research Question 4 ................................................................... 130 Research Question 5 ................................................................... 132 CHAPTER 5. DISCUSSION, CONCLUSIONS AND IMPLICATIONS .............. 139 Business Domain ................................................................................... 139 Family Domain ....................................................................................... 146 Owner-manager Domain ........................................................................ 148 Environmental Domain ........................................................................... 151 Business, Family, Owner-manager, and Environmental Domains ......... 152 Conclusions ........................................................................................... 154 Implications ............................................................................................ 155 Implications for Research ............................................................ 156 Implications for Education .......................................................... 160 Implications for Policy .................................................................. 161 APPENDICES A. HOME-BASED WORKER STUDY (SELECTED QUESTIONS FROM SCREENING AND INSTRUMENT USED FOR THIS STUDY ....................................................................... 165 B. CORRELATION MATRIX TABLES ............................................. 171 REFERENCES .................................................................................................. 176 ix LIST OF TABLES Table Page 1. Distribution of Home-based Family Business Net Annual Income .......... 98 2. Distribution of Owner-Managers by Age Category .................................. 99 3. Distribution of Owner-Managers by Gender .......................................... 100 4. Distribution of Owner-Managers by Educational Level .......................... 100 5. Distribution of Owner-Managers by Marital Status ................................. 101 6. Distribution of Owner-Managers by Years of Work Experience .............. 102 7. Distribution of Owner-Managers by Hours of Work (per week) ............... 103 8. Distribution of Home-based Family Businesses by Occupations ............ 104 9. Distribution of Owners who Borrowed or not Capital ............................... 105 10. Distribution of Home-based Family Businesses by Seasonality .............. 106 11. Distribution of Home-based Family Businesses by Size .......................... 106 12. Distribution of Home-based Family Businesses by Residence ................ 107 13. Distribution of Home-based Family Businesses by Business Age ........... 108 14. Distribution of Home-based Family Businesses by Business Management Scores ............................................................ 109 15. Distribution of families who Own a Home-based Business by Functioning Type ................................................................................ 110 16. Distribution of Owners with Children Under 6 Years Old ........................ 111 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. Distribution of Home-based Family Businesses by Number of Dependents Needing Care ................................................ 112 Distribution of Home-based Family Businesses by Family Size .............. 113 Distribution of Home-based Family Businesses Home Managers by Family Management Scores ............................................................... 114 Distribution of Home-based Family Businesses by Unemployment Rate of County of Residence .................................................................. 115 Distribution of Home-based Family Businesses by Per Capita Personal Income of County Residents Where the Business is Located ................................................................................................... 116 Distribution of Home-based Family Businesses by County Residents’ Investments ........................................................................... 1 17 Distribution of Home-based Family Businesses by County Population ............................................................................................. 1 18 Means, Standard Deviations and Percentages of Selected Variables ................................................................................................ 119 Regression of Log Net Annual Income on Business Characteristics ....................................................................................... 121 Examples of Jobs for Nine Occupations ................................................ 124 Regression of Log Net Annual Income on Family Characteristics ....................................................................................... 125 Regression of Log Net Annual Income on Owner-Manager Characteristics ....................................................................................... 127 Regression of Log Net Annual Income on Environmental Characteristics ....................................................................................... 1 31 Regression of Log Net Annual Income on Business, Family, Owner-Manager and Environmental Characteristics ............................. 134 lntercorrelations between Log Income and Business Characteristics ....................................................................................... 171 lntercorrelations between Log Income and Family Characteristics ....... 172 xi 33. lntercorrelations between Log Income and Owner-Manager Characteristics ...................................................................................... 1 73 34. lntercorrelations between Log Income and Environmental Characteristics ...................................................................................... 1 74 35. lntercorrelations between Log Income and Business, Family, Owner- Manager and Environmental Variables ................................................. 175 xii LIST OF FIGURES Figure Page 1. The conceptual model identifying interrelations of domains to home-based family business ................................... 18 2. The overlap of the family owned business and Home- based business sector ............................................................... 24 xiii CHAPTER 1 INTRODUCTION Rowe, Haynes, and Bentley (1993) characterize home-based businesses as a special case of family businesses: “Home-based business refers to an enterprise operated either in or from a residence”(p.383). There is a great deal of overlap among the issues and concerns of small business, family business, home-based business and the self-employed. Therefore, this study will draw from diverse bodies of literature to frame the examination of the relationship of home-based family businesses’ net Income with many domains. Home-based family business research has gained increasing amounts of attention in recent years (Masuo, Walker, 8. Furry, 1992). For instance, Masuo et al. list four factors that have contributed to the increased interest in studying work at home: the changing nature of office work, the changing composition of the labor force, the permeable boundaries of economic markets, and the lift of a ban on practically all types of home-based work by the US. Department of Laban Small family businesses account for more than 80 % of all businesses in the United States today (Kirchoff & Kirchhoff, 1987). Moreover, family 2 businesses are believed to account for at least half of the US. Gross National Product and employment (Pratt & Davis,1985). Furthermore, small business is a major contributor to economic growth and job creation (US. Small Business Administration, 1984). Besides, home-based family businesses provide jobs to those who otherwise might be unable to work because of personal handicaps, household responsibilities, or the need to supervise children or elderly members of the household (Heck, Stafford, Winter, & Hennon, 1993). Home-based family business is often seen as a positive choice for owners who intermix major work and family responsibilities. Some researchers, however, point out problems and challenges when "family" and "business" are combined (Rosenblatt, de Mik, Anderson, 8 Johnson, 1985). For example, Birch (1987) reported that many small family businesses cease to exist within the first 2 years, and only a few survive beyond 5 years. Studies have reported the causes of small business failure (Larson & Clute,1979; Dickinson,1981); however, prior to 1992, little empirical research has investigated common factors associated with net income generated by home-based family businesses. A review of the literature reveals that most of what has been written about home-based family businesses’ net income is anecdotal. Much of what is known is based on circumstantial evidence, word-of-mouth wisdom, and reports in the popular press. The lack of empirical work may be due to the fact that many problems arise when research in this field is attempted. For instance, income is not the 3 only measure used by family firm owners to assess their businesses’ success. Rosenblatt et al. (1985) pointed out that these owners have many measures of success: customer satisfaction, production of a quality service or product, people’s development, or the owner's feelings of personal achievement. Another problem is obtaining a representative sample from which to make generalizations. Moreover, decisions about the unit of analysis and who is or are interviewed may have different effects on studies. Thus, to avoid these problems and to try to discern what variables may be related to home—based family businesses’ net annual income, this study will use the most comprehensive home-based enterprise data collected to date. The data were collected by the Cooperative Regional Research Project (North East-167) for the study: “At- home income generation: Impact on management, productivity, and stability in rural/urbanfamilies”.1 The data for the at-home income generation study were drawn from nine states: Hawaii, Iowa, Michigan, Missouri, New York, Ohio, Pennsylvania, Utah, and Vermont. ' The Cooperative Regional Research Project, NE-I67, entitled “At-Home Income Generation: Impact on Management, Productivity, and Stability in Rural/Urban Families”, was partially supported by the Cooperative States Research Service, US. Department of Agriculture and the Experiment Stations at the University of Hawaii, Iowa State University, Lincoln University (Missouri), Michigan State University, Cornell University (New York), The Ohio State University, The Pennsylvania State University, Utah State University, and the University of Vermont. 4 Problem Statement Recent research on entrepreneurship, management, and organizations has underscored the importance of understanding better the conditions that promote small business success (Kalleberg 8. Leicht, 1991 ). Previous studies, have reported the causes of small business failure (Larson & Clute,1979; Dickinson,1981). However, prior to 1992, little empirical research has examined home-based family businesses for common factors associated with net annual income (Rowe, Haynes et al.,1993). Furthermore, the review of the literature shows that research on small business financial success has focused on the contributions of two domains only: the small-scale business and the owner (Kepner, 1983). In contrast, current theoretical advancements emphasize the importance of the interaction and influence of three domains: business, family, and owners (Churchill & Hatten,1987) on the financial success of small family businesses. In addition, a fourth domain, the economic and non-economic environment, can have an influence on home-based family businesses’ net annual income. Therefore, prior to 1992 empirical studies to investigate small businesses, and specifically home- based family business income, have been scarce, conceptually fragmented, and fraught with sampling problems. Hence, a study to overcome these problems and to investigate the relationship of the four domains on home-based family businesses’ net annual income is important. “a..- 5 Purme of the Study The purpose of this study is to explore influences on home-based family business net annual income in nine US. states. Specifically, it will examine the relationship among four domain characteristics: business, family, owner- manager, and environmental characteristics and home-based family business net annual income. Importance of the Studv A study such as the one proposed here presents many significant potential outcomes. It could help further illuminate knowledge about home-based family businesses. For example, variables that have not been contemplated in previous research, such as certain environmental variables, may be found relevant in explaining home-based family businesses’ income generation. This research, on the one hand, could identify variables that impede greater income production of home-based family business. On the other hand, it may identify major variables that positively influence the owner’s net income. Potential findings of this research could have implications for policy makers and economic development practitioners. For instance, if factors that impinge upon home-based family businesses’ income generation are identified, then, policy-makers; and economic development practitioners could target policies and programs that would allow encouragement of the identified positive factors and the elimination of those negative factors. In other words, 6 identification of factors either positive or negative can help in a more rational allocation of scarce resources by policy makers and economic development practitioners. Results from this research could indicate to economic development practitioners and policy makers the domain that needs most attention to keep home-based family businesses alive and successful. Ultimately, the study presents a conceptual advance. Domains which have not previously been studied together will be integrated and a domain, the environment in which the business operates, usually excluded from studies, will be added. This enlarged conceptual framework can improve the understanding of important influences on home-based family businesses’ income generation. Conceptual Framework The literature on family business is largely written by management professionals, thus the slant is toward the business domain rather than the family or the owner-manager. All the literature on the family-owned business has been written from the firm's perspective implying a separation of family and business environment. This is an artificial separation because, as Riordan and Riordan (1993) pointed out, it Is impossible for the majority of individuals to remove the ”business" system from the context of the family and business. Thus, to better understand family businesses, a more holistic approach to include neglected domains is necessary. As Kepner (1983) remarked: "the ecology of the family firm as a whole system can not be comprehended unless 7 the more neglected half of the system [the family] Is placed in the foreground"(p.58). To understand small family business, many disciplines have contributed with concepts and frameworks. These perspectives come from major fields such as economics, business management, psychology, and sociology. Each field has its own interpretation of the characteristics and dynamics of small family businesses. As a result, different points of emphasis originated from each field. For instance, the economic approach focuses on the financial characteristics and the economic environment in which family businesses operate. Another approach, business management, looks at the managerial characteristics of the firms, i.e., how they are managed, what their planning procedures are like, their technical capabilities, marketing strategies, and other business practices. In contrast, the psychological approach studies the personal characteristics of the entrepreneur. The psychological approach assumes that there are certain personality characteristics which help individuals in being more successful than others in their businesses. Finally, the sociological approach contends that business ownership and success are largely dependent upon social group resources (Fratoe, 1986). In summary, these different approaches engaged in the study of family businesses have provided a fragmented theoretical framework. Riordan and Riordan ( 1993) pointed out one major omission of these approaches. They mention that owner-managers of small businesses are usually overlooked. Hence, there is a need to incorporate this dimension when studying family businesses. In their words: because owner-managers of small family businesses are key decision-makers in their firms and have the discretion to make choices and override business control systems at all levels, it is critical that the theoretical framework used as a research tool reflect this environmental fact (p.66-67). Another criticism raised toward the approaches mentioned above is the lack of a system perspective. Kanter (1977) suggested that an integrated system perspective is the only logical theoretical framework within which to study family businesses. These criticisms suggest that when studying small family businesses more inclusive frameworks should be utilized. This research aims to be more ecological by incorporating the environmental domain and studying the impact of four domains on net annual income. Hence, the research proposed here will examine families in their living settings as the units (organisms), and the domain’s impact on net annual income will be under review. A Family Resource Management approach is suitable as a general framework for this study because it sees families as systems within an ecological perspective. That is with the Family Resource Management framework families can be analyzed from an ecosystem perspective. One fundamental characteristic of the family ecosystem is that it is made up of a collectivity of interdependent parts working together to achieve a 9 common purpose. Each element (organism and environment) is interrelated. The basic elements of the family ecosystem are: (a) organisms (family members), (b) environments (natural and human-built) and (c) the family organization which functions to transform energy in the form of information into family decisions and actions (Paolucci, Hall, & Axinn, 1977). Mme Family members, viewed as a set of interacting, interdependent but independent persons working together are the organisms in an ecosystem framework. The family is viewed as a set of mutually interdependent organisms where intimate, transacting, and interrelated persons share some common goals, resources, and commitments to one another over time. Moreover, the family’s character is significantly different from that of its individual members. That is, the family characteristics differ from the characteristics of the individual members (Paolucci et al., 1977). Environments Broadly defined, the environment includes anything external to the family that can affect it. There are three components of the environment: biophysical, psychosocial, and technological. The biophysical environment is composed of the sun, land, water, air, space, plants, and animals. The psychosocial component includes kinship, religious, political, economic, productive, 10 recreative, symbolic, and ideological aspects of the near environment. The technological components, consisting of materials, tools, and techniques of the physical and social environment, are used by families to manufacture objects or alter people and environments. In summary, the environment is the sum total of the physical, biological, social, economic, political, aesthetic, and structural surroundings of the individual or household (Bubolz, & Sontag, 1993). Organization According to Paolucci et al. (1977), the family organization is the processing system that transforms matter-energy and information and directs it toward family goal achievement. That is families transform matter-energy and information through key adaptation and activity processes such as management, decision-making, sustenance activities, and so forth. In the ecological perspective, management is a set of particular responses and adaptations to a certain situation and environment (Deacon & Firebaugh, 1981 ). The process of adapting and changing within the family can be viewed as the management of environmental and human resources. The family adapts to the environment through a process using inputs, transformations and outputs. Inputs usually consist of energy as matter and information (Paolucci et al., 1977). For families, inputs are demands from their goals, values, or events that require action as well as human and nonhuman resources. Human resources 11 include the cognitive, affective, or psychomotor traits or qualities within people, and nonhuman resources include temporal resources which are time and methods of using time, economic resources of money and property, and environmental resources which are both physical and social (Nickell, Rice, 8 Tucker, 1976). Transformations are the process of planning and implementing change of input into output. Outputs are met demands and used resources that result from the process of transformation. Information from the environment about the output returns to the family system as feedback (Deacon 8 Firebaugh, 1981). Decision-making processes are critical in the family resource management context. The family can be characterized as a decision-making unit. As a decision-making unit, the basic task of the family unit is to choose among competing ends in order to maximize satisfactions (or utility) subject to the limitations of scarce resources. Decision making is essentially a process of evaluation in the choice or resolution of alternatives. When these decisions involve the utilization of means such as information, material goods, or money to find an acceptable solution, they become managerial in nature, involving economic decision processes (Deacon 8 Firebaugh, 1988). In summary, families are viewed by the Family Resource Management perspective as part of an ecosystem with two major subsystems: personal and managerial. Inputs as resources are introduced into the family system. Resources are transformed through planning and implementation. Decision- 12 making is a vital process for the functioning of the system (Deacon 8 Firebaugh, 1988). Moreover, the systems format in which the Family Resource Management theory is dovetailed provides a frame of reference for analyzing the goal-directed and self-regulating behavior of families as they address their living situations. The family system’s context changes partly because of other systems. Viewing these interactions in a dynamic context is a special advantage of the systems approach to family analysis (Deacon 8 Firebaugh, 1988, p.16). Ultimately, It is important that the assumptions and implications of this proposed general framework be well understood. For this purpose, following Deacon and Firebaugh (1988); Gross, Crandall, and Knoll (1980); Nickel, Rice, and Tucker (1976); and Paolucci, Hall, and Axinn (1977) a summary of the Family Resource Management theory assumptions is presented. 1. The family in interaction with its environment constitutes an ecosystem. 2. The family manages the biophysical, psychosocial, economic and nurturance needs and functions of its members. 3. All humans are interdependent with one another and with environmental resources. 4. Families are interdependent with other forms of life and the nonliving environment. 5. Families are semiopen, goal directed, dynamic, adaptive systems. They can respond, change, develop, act on, and modify their environment. Adaptation to their environments is a continuous process. 13 6. All parts of the environments (natural biological-physical, social- cultural, and human built) are interrelated and influence each other. 7. Families are part of and interact with many environments. 8. Families are energy transformation systems that use energy for survival, interaction, and adaptation. 9. Family interactions are guided by physical and biological laws of nature and human derived rules. 10. Environments provide limitations and opportunities for families. 11. Families have varied amounts of control related to environmental interactions. 12. Decision-making is the central control process that families use to attain individual and family goals. 13. Families are complex adaptive systems, capable of elaboration of organization and morphogenetic and reorientation levels of feedback. 14. Families can change values, goals, and rules in response to internal or environmental changes. 15. Families can take action to change environments to serve human purposes as well as react to environmental changes. 16. An ecosystem contains goal-oriented, controlled components, some of which are cooperative and others competitive. 17. Families are composed of two major subsystems: personal and managerial. 18. Inputs are introduced into the family system as resources; they are l-I transformed via throughput processes (planning and implementation). The process of transformation ends up In outputs (outcome) that can feedback into the system as input. 19. Families are goal oriented. Decision-making is a vital process for the functioning and attainment of family goals. After reviewing the assumptions, it is also important that the implications of the proposed general framework be understood. For this purpose, a summary of the implications of Family Resource Management theory for this study is presented. 1. For this study the unit of analysis is families with home-based workers. This is consistent with the family ecological approach where the family serves as the primary unit of analysis. 2. A family is a system which is defined as “a set of parts coordinated to accomplish a set of goals” (Deacon 8 Firebaugh, 1981, p.7). This study focuses on the family components and how they coordinate to accomplish the goal of financial success. 3. This study considers home-based family businesses as part of an ecosystem, that is, the family business In interaction with its physical-biological, social- cultural, and human built environments. 4. Families have needs that must be met to survive. The production process may be considered as the way by which needs are met. The process uses human and material resources. 15 5. The family ecological approach sees families and individuals in an environmental context which provides many alternative ways to meet their needs. The resources necessary to meet families’ basic needs are found within themselves and their environment and are made available through interactions and transactions. 6. The family is considered to be a managerial unit where decision-making is the central control process that families use to attain goals. This leads to the exploration of the effects both family and business managerial processes have on income produced by home-based family businesses. 7. The interdependence between family members with one another, with other nonfamily humans, and with the living and nonliving environments is recognized. 8. This study focuses on the impact of business, family, owner-manager, and environmental characteristics on home-based family business net income. 9. Families have different levels of control about the above mentioned domains. They can have greater control over the personal and microsocial environment than over the macrosocial and wider context. 10. Families can impact or be impacted by their internal dynamics and external environments. That is families change continuously to adapt to their environments and accomplish their goal(s). 11. Families are goal directed. One goal of family business owners is to produce income out of their businesses. 16 Conceptual Model to Study Home-based Family Businesses The theoretical framework proposed here will point out the relevance of integrating systematically four domain characteristics when studying home- based family businesses: business, family, owner-manager, and environmental characteristics. The model follows Churchill and Hatten’s (1987) framework which emphasizes business, owner, and family to study family businesses. Moreover, it is in accord with Beckhard’s (1983) approach to studying family firms: Basically, my own approach to family firms is a system approach. I start by recognizing the existence of three basic components: the firm as an entity with a life of its own, the family as an entity with a life of its own, and the founder[owner-managerj-who has a life of its own and who, typically, heads both of the other two systems. I would argue that, to manage the complex interdependence between them, it is necessary to acknowledge the existence of these three subsystems (p.31 ). However, the model of this study incorporates the environmental domain that neither Churchill and Hatter’s (1987) nor Beckhard’s (1983) models contemplated. The conceptual framework for this study was also influenced by the framework developed by Owen, Carsky, and Dolan (1992a) for the at-home income generation project. Consistent with family resource management theory, Owen, et al., (1992a) view families as having demands and resources that serve as inputs into decisions about family behavior. Owen, et al. (1992a) arrange these behaviors on an activities continuum as follows: away employment, home- 17 based work, household production, and propinquous2 production. From this continuum, Owen, et al., (1992a) studied principally home-based work, which in conjunction with away employment, is identified with money as outcome. For the cross-sectional research,‘proposed for this study, a model representing concepts that could be assessed under the restrictions of such analyses needed to be developed. Figure 1 shows the conceptual model that will be used to study the relationship of business, family, owner, and environmental characteristics with home-based family businesses’ net annual income. The model reflects the Family Resource Management framework that constitutes the theoretical perspective of this study. First, a systems structure where four main domains that, according to the literature review, affect home- based family businesses’ income is portrayed. Moreover, the selection of concepts that are considered in each domain reflects the theoretical perspective that is behind it. For instance, the ecological perspective can be seen in the selection of variables such as investment, unemployment, population density, and so forth that capture the macrosocial and wider context. Relationships between the independent and dependent variables are shown by the one way vertical arrows. These vertical arrows show that the variables selected have an impact on net annual income of home-based z Propinquous activities have properties of relationship, kinship, and affinity. Examples include the care and nurture of family members, preparation of foods with meaning beyond nutritional content (ethnic or favorite foods), and the practice of religion within the home. 18 .0509: _m3CCN “QC $835 253 oommnoEo: 9 85.56 .0 50:29:25 55:52 .255 635850 of. .F 9:19 a; HEOUE i327? Hmz mmmzumbm >A=z52 2500 326 52.6 Total 620 100.00 There is a predominance (52.6%) of home-based family businesses operating in towns or cities with populations larger than 2,500. The other 47.4% lived in rural communities and towns with populations under 2,500. Farm households accounted for only 7.9% of the sample. It is appropriate to recall that 108 farm businesses were not included in the sample unless they added value to their farm products. Home-basecflamilv business age. Home-based family business age refers to the number of years the home-based family business has been in operation. The distribution of home-based family business by years of operation can be seen on Table 13. Business years of operation varies from less than 5 to more than 15 years. All the businesses included in the sample had been operating at least one year. According to Table 13, around 37% of the businesses studied are relatively new with less than five years of operation. Table 13 also shows that approximately 22% of the businesses had been operating for 15 years of more. The average years of operation was 9.48 years. Table 1 3 Distribution of Home-based Family Business by Business Age (N=620) Years of operation Number Percentage Less than 5 years 228 36.8 5-9 years 149 23.9 10-14 years 104 16.8 15 years or more 139 22.5 Total 620 1 00. 00 109 Business management. Business management scores are presented for 304 business owners who were simultaneously family and business managers. Data limitations impede presentation of business management scores for the whole sample of 620 businesses. Due to this data limitation, business management was excluded from the regressions. The distribution of owners’ management scores is shown in Table 14. High scores for Business Management indicate behavior most closely aligned with what was assumed to be better management practices. Table 14 DIstribution of Home-based Family Business Owners by Business Management Scores (N=304) Business management scoresa Number Percentage 21 -3O 23 7.60 31 -40 160 52.60 41 -50 121 39.80 Total 304 100.00 Note. N=304. respondents who were not business owners were excluded. ' Scores could range from 10 to 50. Table 14 shows that only 7.60% of home-based family business owners scored between 21 and 30. The remaining 92.4% scored 31 or above. No owner manager scored below 21. These scores suggest that home-based families have no problems in managing their business activities. 110 To explore the relationship between the business management scores and the 304 owners’ net business incomes, the researcher performed a correlation analysis. Results showed that r=-.08 , p=.02 , indicating that there is a weak but significant and negative correlation between the business management variable and the log net annual income of home-based businesses. Emily Characteristics Open family functioning ME. The distribution of families by their functioning type is shown in Table 15. The majority of the families with home- based businesses included in this study are not open. Around 90% of the business families were categorized as other. From the 620 families studied only 9.7% were open. Table 15 Distribution of Families who Own a Home-based Business by Functioning Type (NF-620) Family functioning type Number Percentage Open 60 9.7 Other 560 90.3 Total 620 100.00 Ill Children under 6. The distribution of owners who had children under 6 years old in the family is shown in Table 16. Table 16 Distribution of Owners with Children Under 6 Years Old (|_\I_=620) Presence of children under 6 years old Number Percentage With children under 6 182 29.3 Without children under 6 438 70.7 Total 620 1 00.00 Around 71% of the home-based family business owners studied do not have children under 6 years old. This finding contradicts the idea that owners with young children prefer home-based work to other types of work because it provides an alternative way of taking care of young children while generating income at home. The notion that home-based business provides jobs to families with young children appears to be applicable to only around 30% of the owners studied. @endents needing care. Dependents needing care refers to the number of people in the family that require care or supervision on a daily basis, like children, or disabled or elderly family members. The distribution of home-based family businesses by the number of people needing care in the family is shown in Table 17. 112 Table 17 Distribution of Home-based Family Businesses by Number of Dependents Needing Care (3:620) Number of dependents needing care Number Percentages 0 324 52.2 1 110 17.7 2 119 19.3 3 46 7.4 4 15 2.5 6 2 0.3 7 3 0.6 Total 620 100.00 Note. 3 Includes children, disabled, and elderly persons. More than one half of home-based family business owners have no dependents needing care. Moreover, around 37% have one or two dependents needing care and 10.8% have three or more. This finding challenges the notion that the major reason why people engage in home-based family business is because they need to take care of dependents while producing income. Family size. Family size refers to the total number of people (blood related or not) who share the residence and define themselves as a family. Table 18 shows the distribution of home-based family businesses by family size. 113 Table 1 8 Distribution of Home-based Family Businesses by Family Size (N=620) Family size ............. Number Percentages 2 172 27.7 3 133 21.5 4 159 25.7 5 111 17.8 6 29 4.7 7 and more 17 2.6 Total 620 100.00 Only 7.3 % of the owners have family sizes with six or more members. Around 47% have three or four persons. Moreover, Table 18 shows that 27.7% of the families are composed of just two persons. Family size was considered important in regards to income because it can be assumed the larger the family size the larger the quantity of workers it could provide to help with the business. Family management. Family management refers to the score obtained on the instrument Family Management (see Heck, Winter & Stafford, 1994). The distribution of family management scores of home-based family business owners is shown in Table 19. High scores indicate behavior most closely aligned with what was assumed to be better family management practices. 114 Table 19 Distribution of Home-based Family Business Home Managers by Family Management Scores (N=620) Family management scoresa Number Percentage 10-20 6 0.9 21 -3o 77 12.6 31 -40 438 70.7 41 -50 99 15.8 Total 620 100.00 Note. ‘ Scores could range from 10 to 50. Around 83% of the home managers scored between 21 and 40. Approximately 16% of the home managers scored between 41 and 50. Expectations of this researcher were that the higher the family management score, the larger will be the income generated by the business. Environmental Characteristics Unemployment rate, 1988. All civilians 16 years old and over were classified as unemployed if they were not currently working for pay but actively looking for work or persons temporarily laid off from a job to which they expect to return. Table 20 shows the distribution of home-based family businesses by the unemployment rate of their respective counties of residence in 1988. 115 Table 20 Distribution of Home-based Family Businesses by Unemployment Rate of County of Residence (N=620) Unemployment rate 1988 Number Percentage 1.70 to 5.40 368 59.3 5.41 to 6.60 128 20.5 6.61 to 9.00 88 14.3 9.10 to 16.30 36 5.9 Total 620 100.00 In 1988 the annual average national unemployment rate was 5.40 (US. Department of Labor, 1990). Table 20 shows that around 60% of the counties in which home-based family businesses were located had unemployment rates below the 1988 national average. The remaining 40% had unemployment rates above the national average. Counties’ unemployment rates in which home- based family businesses were located range from 1.70 to 16.30. Per capita personal income. 1988. Per capita personal income refers to the money income received by persons 15 years old and over living in the county where the, home-based family business was residing. Total income is the algebraic sum of the amounts reported from wage or salary income; net nonfarm self-employment income; net farm self-employment income; interest, dividend, or net rental income; social security or railroad retirement income; public 116 assistance or welfare income; retirement or disability income; and all other income. Table 21 shows the distribution of home-based family businesses by per capita personal income of county residents where the home-based businesses were located. Table 21 Distribution of Home-based Family Businesses by Per Capita Personal Income of County Residents where the Business is Located (N=620) Per capita personal income 1988 Number Percentage (3) 8021.00 -11618.00 63 10.1 ($)11652.00 - 12926.00 61 9_9 ($)13033.00 - 14648.00 124 20,0 ($)14695.00 - 16527.00 124 20,0 ($)16561.00 -19419.00 172 27,7 ($)19420.00 - 29124.00 76 12.3 Total 620 100.00 In 1988, the national average per capita income for all earners (part-time and full-time workers) was $ 19,419 (US. Department of Labor, 1990). Around 88% of the home-based family businesses were residing in counties with per capita personal incomes lower than the national per capita income average. Hence, only about 12% of the counties in which home-based were located have per capita personal incomes above the national average in 1988. 117 Investments 1988. Investments refers to the total amount of interest, dividend, net rental or royalty income of persons in the county where the home- based family business was operating. Table 22 shows the distribution of home- based family businesses by the county residents' investments. Table 22 also shows that there is a great variation in investments of county residents in which home-based family business were residing. Table 22 Distribution of Home-based Family Businesses by County Residents’ Investments (N=620) Investments 1988 (51000)“ Number Percentage 4973.00 - 96295.00 124 20.0 101062.00 - 235748.00 124 20.0 236882.00 - 840020.00 124 20.0 885131.00 - 241622500 124 20.0 2751735.00-7621690.00 124 20.0 Total 620 1 00.00 Note. 3 Includes dividends, interests, and rents. Poptfittion density. Refers to the number of persons per square mile in the counties in which home-based family businesses were residing. Table 23 shows that from the 620 home-based family businesses studied, around 36.3% of them were located in counties with population density between 0.77 and 150 persons per square mile. More than 39% were residing in counties with population densities between 151 and 1,000 persons per square mile and 25% 118 were residing in counties with population densities of over 1,000 persons per square mile. Population density may be related to business income because it could be assumed that counties with larger populations will provide a larger market size; that is, a larger number of business customers. Table 23 Distribution of Home-based Family Businesses by County Population Density (N=620) Population density Number Percentages 0.77- 150 225 36.3 151 - 300 94 15.1 301 - 450 55 8.9 451 - 600 33 5.3 601-1,000 61 9.8 over 1 ,000 152 24.6 Total 620 100.00 Summary of Descriptives Since the quantitative study of home-based family business is relatively new, it was thought that full display of descriptive statistics would be useful to characterize this type of business. Describing and characterizing the home- based family businesses studied can provide insights to understand better the relationships that might emerge in the regressions run on home-based family net annual income. Table 24 summarizes the descriptive statistics presented in this chapter. 119 Table 24 Means, Standard Deviations and Percentages of Selected Variables ([11:620) Variable Mean E % distribution — Net annual income 15,881 832.13 _OLwner-maniqg Age (years) Education (years) Work experience (years) Hours of work (1 year) Business Occupation Professional and technical Marketing and sales Clerical and administrative Mechanical and Transportation Crafts and artisans Managers Services Contractors Agricultural products and sales Borrowed capital (yes) Not seasonal businesses Business size (number employees) Business age (years) Business management score Family Open Without children under 6 Dependents needing care Family size Family management score Environmental Unemployment rate Investments (in $1000) Per capita personal income Population density (pop/mi) 44.09 13.63 14.92 1822.25 3.71 9.48 38.78 .94 8.11 .36 .30 .05 .06 .20 09 13288792 71987.69 157.61 36.71 14.8 10.7 15.7 4.3 2.8 18.4 15.7 14.4 3.2 20.8 83.6 9.7 70.7 120 Regression Results Regressions were modeled to answer the research questions and test the hypotheses posed in Chapter 3. What follows are the answers to the research questions in the light of the regression results. Regression coefficients from all analyses reflect the change in log net annual income earned by home-based family businesses. Research Question 1. Is there a relationship between home-based family business net annual income and home-based family business characteristics variables? The null hypothesis related to question 1 stated that there is not a linear relationship between variables corresponding to the home-based family business domain and home-based family business net income. That is, R2 is 0. To answer question one and test its related null hypothesis, a multiple regression equation model was developed as shown below. Table 25 presents the regression results. The regression equation used was: y1= be + b, X1+b2 X; + b; X3 + ................... + b13 X13 + e. where the dependent variable is y1= Home- based family business net business income and the independents variables are: X1= Occ1 (Professional/technical); X2: Occ2 (Marketing and sales); X3: Occ3 (Clerical and administrative support); X4: Occ4 (Mechanical and transportation); X5: Occ5 (Crafts and artisans); X6: Occ6 (Managers); X7: Occ7 (Services): 121 Xe= Occ8 (Contractors); X9: Borrowed capital; X10: Seasonality; X11=Home- based family bUSineSS size; X12=Urbanixia=Home-based family business age; ei=error term. Table 25 Regression of Log Net Annual Income on Business Characteristics (_N_=620) Variable B _l; B (3 OCC1 3.21 .77 82* OCC2 4.03 .75 .45* COGS 4.24 .88 .28* OCC4 3.32 .73 .39* OCC5 2.88 .75 .33* OCC6 1.02 1.01 .06 OCC7 2.02 .75 .24" OCC8 4.07 .73 .51 * BORRCAP .36 .31 .05 SEASWOR -.07 .33 -.01 HBFBSIZE .06 .02 .17* URBAN .01 .27 .00 HBFBAGE .02 .01 .04 (Constant) 4.54 .73 Male. OccQ=Agricultural products and sales(0mitted). F=6.57, p=.00. R2=.12; adjusted R2=.11 ‘Q< .05. The analysis of variance from the regression results indicate that F=6.57 p=.00. Therefore, the null hypothesis 1 is rejected. That is, there is a linear 122 relationship between the business characteristics variables and home-based family business net annual income. Based on a decision rule of p<.05, eight of the variables in the model were statistically significant. These variables were: Occ1(Professional/technical), Occ2(Marketing and sales), Occ3( Clerical and administrative support), Occ4 (Mechanical and transportation), Occ5 (Crafts and artisans), Occ7( Services), Occ8(Contractors), and HBFBSIZE. In terms of relative importance, the standardized coefficients (Betas) show that when considering variables from this domain, all the occupational variables are positive. Occ8 (Contractors) 8:51 is relatively the most important predictor of home-based family business net annual income. Following in importance are Occ2 (Marketing and sales) 8:45, and Occ4 (Mechanical and transportation) 8:.39. Occ5 (Crafts and artisans) and Occ1 (Professional/technical) with 8:33 and 8:32 respectively are also important variables. Occ3 (Clerical and administrative support) 8:28, and Occ 7( Services) 8:24 are of less relative importance among the occupation variables. Business size was also significantly and positively related to income (8:.17). That is, as the size of the business is larger, the higher the net income. The remaining variables: Occ6 (managers), borrcap, seaswor, urban, and hbfbage were not statistically significant at the .05 level. Because most of the occupation variables had important and positive effects on net income, the researcher investigated the job titles that described 123 the occupations. Table 26 illustrates selected job titles for each of the occupations. Results from the business domain regression show that Occ 8 (contractors) is the most relatively important variable. That is, occupations such as road construction, house painting, and home maintenance contractors are jobs which are making more income compared to jobs such as egg sales or meat processing which pertain to Occ 9 (agricultural products and sales), the basis for comparisons. Recall that in the regression model, Occ 9 was the category omitted. Regression results from the business domain also indicate that marketing and sales was the second most important occupation in terms of producing income. That is, owners in real estate, insurance, auto leasing, sales representatives and so on are, on average, making more income than the beauticians, barbers, and child care providers in the service occupations; and both groups, on average, have higher business incomes than those in agricultural sales, holding constant relevant variables. Finally, business regression results from Table 25 show that the amount of variation in home-based family business net annual income explained by the business domain itself for the total sample was adjusted R2=.11. That is, 11 % of the variation on home-based family business n'et annual income was accounted for by variables in the business domain. Table 26 124 Examples of Jobs for Nine Occupations Occupational category Job title examples 1. Professional and technical 2. Marketing and sales 3. Clerical and Administrative suppon 4. Mechanical and transportation 5. Craft and artisans 6. Managers 7. Services 8. Contracting 9. Agricultural products and sales Computer consultants; computer programmers; consulting engineers; teachers of piano, art, music; college tutors. Fleamarket sales; real estate, insurance, auto leasing agents; sales representatives. Secretaries; bookkeepers; computer label makers; computer workers; office managers; real estate appraisers; tax preparers; data processing workers. Truck drivers; bus drivers; building service repairs; structural and electrical inspectors. Crafts; potters; blacksmiths; T-shirt painters; musicians; graphic designers. Garbage collection, cleaning businesses, property maintenance, and motels; rental property managers. Beauticians; dog groomers; barbers; day care and child care providers; private duty nurses; housekeepers; house and office cleaners; caterers. Road and other construction; carpentry; house painting; home maintenance contractors. Herb, flower, and egg sales; fishermen; meat processing workers; boarding and training dogs. 125 Research QuestiorLg. Is there a relationship between home-based family business net income and the family characteristics variables? To answer question 2, it was hypothesized that family characteristics are not linearly related to home-based family business net income. To test this hypothesis, multiple regression was performed. For that purpose, an equation model was developed as shown below. Table 27 shows the regression results. The regression equation used was y2= bo + b, X, + b; X; + b3 X; + be X. + b5 )6; + e: where the dependent variable is y2=Home-based family business net annual income and the independent variables are: X1: Open (Family functioning type); X2= Children under 6; X3: Family size; X4: Dependents needing care; X5: Family management; ei=error Table 27 Regression of Log Net Annual Income on Family Characteristics (N=620) Variable B _S_§ (3 OPEN .72 .42 .07 KIDUND6 -.09 .34 -.01 FAMSIZE -.01 .12 -.01 DNCARE .15 .15 .06 FAMMNGT . -.05 .02 -.08* (Constant) 10.01 .96 M9. F=1.85 p= .10 R2=.01; adjusted R2=.01; 'g< .05. 126 The analysis of variance from the regression results indicate that F=1.85 p=.10. Therefore, there is no linear relationship between the family characteristics variables and home-based family business net annual income, contrary to the research hypothesis. As pointed out in the literature review, the family functioning types concepts have not been well operationalized. Furthermore, recall that this analysis is not gender specific. A gender specific analysis would probably yield different results than the one found in this study since the other four variables (KIDUND6, FAMSIZE, DNCARE, and FAMMNGT) may be influences on women’s net income. This researcher may be finding no significance because the presence of male and female owners could cancel them out. Hence, the effect of family variables turned out not to be related to income. men Qgestion 3. Is there a relationship between home-based family business net income and personal characteristics of the owner-managers’ variables? To answer question 3, it was hypothesized that owner-manager characteristics are not linearly related to home-based family business net income. To test this hypothesis, multiple regression was performed. For that purpose, an equation model was developed as shown below. Table 28 presents the regression results. The equation used was y3= bo + b, X, + b; X; + b3 X; + b4 X. + b5 X5 + be X6 + by X7 + be X8 + e. where the dependent variable is y3=H0me- 127 based family business net annual income and the independent variables are: X1: Age; X2: Male; X3: Not graduates; X4= High school graduates; X5: Some college; X5: Married; X7: Work experience; X8: Hours of work; e = error. Table 28 Regression of Log Net Annual Income on Owner-Manager Characteristics ($620) Variable _B _S_g (3 HBWAGE .03 .01 .10” MALE 1.64 .27 26* NOTGRAD -2.73 .52 -.22* HSGRAD -1.42 .31 -.22* SOMECOLL -1.22 .32 -.18* MARRIED .84 .42 .08" WORKEXP -.04 .01 -.14* HOURS .00 .00 .26* (Constant) 5.69 .66 Egg. College is omitted. F=16.87 p= .00. R2=.20; adjusted R2=.19 'Q< .05 Analysis of variance from the regression indicates that F=16.87, p=.00. Therefore the null hypothesis 3 that there is not a linear relationship between the owner-manager characteristic variables and home-based family business net annual income is rejected. 128 Regression results in Table 28 show that all the variables from this domain are statistically significant. In terms of relative importance, the standardized coefficients (Betas) show that being male (8:26) and hours of work (8:.26) are the most relatively important variables; the second most relatively important variables are the educational categories notgrad (B=-22), hsgrad (B=-22) and somecoll (B=-18). The variables with less relative importance were work experience (B=-.14), hbwage ((3:10), and married (8:.08). These results indicate that within this domain there are variables that are positively and negatively related to income. The positively related are: HBWAGE, MALE, MARRIED, and HOURS. These suggests that owners who are older, male, married, and working more than average hours make more net income than owners who are young, female, nonmarried and work less than average hours. Table 28 shows negative regression coefficients for educational dummy variables. These negative signs should not be interpreted in the sense that educational categories have negative effects on income. Regression coefficients for educational dummy variables estimate the net difference in expected log income for each educational group relative to the reference group, controlling for other independent variables in the equation. College education, the variable left out, was selected as the reference group for comparisons. Therefore, the regression coefficient for NOTGRAD tells that, on average, it should be expected that owners who have not graduated from high school earn 2.73 (in logarithmic terms) less than college graduate owners. Owners who have 129 graduated from high school expectedly will earn 1.42 less than college graduate owners; and owners with some college education will earn 1.22 less than owners who have graduated from college. In other words, the less education owners has, it is expected that, on average, they will make less income relatively to owners who have college education. These regression results from the owner-manager domain can be helpful in understanding better the relationship between owner-manager characteristics and net annual income. For instance, it is possible to profile home-based family business owners with the highest income. Based on these results, males who worked more hours and with a college degree are the ones who, on average, are making more income. On the other hand, an owner with low net business income would be a woman who work less hours and who has not graduated from high school. Regression results are also instrumental in clarifying that some characteristics such as work experience, owners’ age, and marital status are relatively less important in relation to income. From these variables, work experience was negative. This result indicates that the more experience a home- based business owner has, the less the income produced by the business. To further explore the variable HBWAGE it was squared and reintroduced into the equation. It was found that HBWAGE was statistically significant. This suggests that age of the owner is curvilinear. Moreover, all the other variables remain statistically significant and the R2 did not change. 130 Table 28 also reveals that the amount of variation in home-based family business net annual income explained by the owner-manager domain for the total sample was adjusted R2=.19. That is, 19% of the variation in home-based family business net annual income was accounted for by the variables that pertain to the owner-manager characteristics domain. Research uestion 4. Is there a linear relationship between home-based family business net income and environmental characteristics variables? To answer question 4, it was hypothesized that environmental characteristics are not linearly related to home-based family business net income. To test this hypothesis, multiple regression was performed. For that purpose, an equation model was developed as shown below. Table 29 shows the regression results. The equation used was y4= bo + b, X, + b; X; + b; X; + e. where the dependent variable is y4=Home-based family business net annual income and the independent variables are: X1=Unemployment;X2=Per capita income; X3=Population density; ei=error term. 131 Table 29 Regression of Log Net Annual Income on Environmental Characteristics (£5620) Variable _B _S_E_ j) UNEMP88 -.11 .07 -.08 PCPI88 -.00 .00 -.07 POPDENS .00 .00 .17" (Constant) 9.18 .98 0t : F= 5.26, p= .00 R =02; adjusted R2=.02 ‘p<. 05. Previous checking of assumptions demonstrated that there was a high correlation between the variables investment and population density (r=.94, p=.00) see Appendix B. Therefore the investment variable was excluded from the regression of log net income on environmental characteristics. Analysis of variance from the regression shown in Table 29 indicates that F=5.26, p=.00. Hence, the null hypothesis 4 that there is not a linear relationship between environmental characteristics variables and net annual home-based family business income is rejected. Based on the regression results of the environmental domain, it seems that a high population density is the only variable within the model which is conducive to higher levels of income. That is, home-based businesses located in counties with higher than average population densities make higher incomes than businesses located in counties with low population densities. 132 Overall the domain was linearly related to income. These results indicate that the environmental domain is a promising one which can be helpful in explaining income differences. It would be important to continue the search for more and better measured variables within this domain. Table 29 also indicates that the amount of variation in home-based family business net annual income explained by the environmental domain for the total sample was adjusted R2=.02. That is, 2% of the variation in home-based family business net annual income was accounted for by the variables that pertain to the environmental characteristics domain. Research Elation 5. Is there a relationship between home-based family business net income and business, family, owner-manager, and environmental characteristics variables? To answer question 5, it was hypothesized that business, family, owner- manager, and environmental characteristics variables are not linearly related to home-based family business net income. To test this hypothesis, multiple regression was performed. For that purpose, an equation model was developed. Table 30 shows the regression results. The equation used was: y5= b. + b, X1+ b; X; + by. X; + .................. + D29 X29 + e; where the dependent variable is y5= Home-based family business net annual income and the independent variables are: X1: Occ1 (professional/technical); X2= Oc02( marketing and 133 sales); X3: Occ3( clerical and administrative support); X4= Occ4(MechanicaI and transportation); X5: Occ5(Crafts and artisans); Xs= Occ6(Managers); X7= Occ7(Services); Xe: Occ8(Contractors); X9: Borrowed capital; X1o= Seasonality; X11: Home-based family business size; X12: Urban; X13: Home-based family business age; X14: Open; X15: Children under 6; X13: Family size; X17: Dependents needing care; X13: Family management; X19: Age; X20: Male; X21: Notgrad; X22: Hsgrad; X23= Somecollege; X24: Married; X25: Work experience; X26: Hours of work; X27: Unemployment; X23: Per capita personal income; X29: Population density; e5: Error term. The analysis of variance from the regression results indicate that F=6.25, p=.00. Therefore, the null hypothesis 5 is rejected. That is, there is a linear relationship between business, family, owner-manager, and environmental characteristics variables and home-based family business net annual income. Based on a decision rule of p<. 05 the following variables were found to be statistically significant: Occ1, Occ2, Occ3, Occ4, Occ5, Occ7, Occ8, FAMMNGT, MALE, NOTGRAD, HSGRAD, SOMECOLL, MARRIED, WORKEXP, and HOURS. In terms of relative importance, the standardized coefficients (Betas) show that in the full model, that is, considering all the variables together from the four domains, Occ8 (Contractors) is the most important predictor of home-based family business net annual income ((3:40); following in importance are Occ4(Mechanical and transportation), Occ5(Crafts and artisans), and 134 Table 30 Regression of Log Net Annual Income on Business, Family, Owner-Manager and Environmental Characteristics (N=620) Variable B _S_§ (3 OCC1 2.32 .84 .23" OCC2 3.52 .81 .37" OCC3 4.12 .95 .26" OCC4 3.24 .81 .38* OCCS 3.24 .79 .38“ OCC6 1.99 1.06 .11 OCC7 3.16 .81 .38* OCC8 3.25 .81 .40" BORRCAP -.21 .32 -.03 SEASWOR .44 .35 .05 HBFBSIZE .02 .02 .04 URBAN -.17 .30 -.02 HBFBAGE .01 .02 .03 OPEN .51 .46 .04 KIDUND6 -.23 .36 -.03 FAMSIZE -.19 .12 -.09 DNCARE .20 .15 .08 FAMMNGT -.06 .03 -.09* HBWAGE .02 .02 .08 MALE 1.52 .37 .24” NOTGRAD -3.09 .57 -.25* HSGRAD -1.63 .37 -.25* SOMECOLL -1.28 .35 -.19* MARRIED 1.05 .44 .10* WORKEXP -.03 .02 -.11* HOURS .00 .00 .25” UNEMP88 -.06 .07 -.04 PCPI88 -.00 .00 -.05 POPDENS .00 .00 .02 (Constant) 6.10 1.82 flot_e. Categories omitted are: Occ9 (agricultural products and sales); and college. $6.237. p=.00. Adjusted R2= .22 ‘g<. 05. 135 Occ7(Services) with (l3=.38) respectively. Occ2 (marketing and sales) p=.37, Occ3 (clerical and administrative support) 8:26, and Occ1 (Professional/technical) (3:23, were the less important occupations. Occ6 (Managers) was the only occupation that was not statistically significant at the .05 level. Other important variables are: educational categories notgrad ([3= -25), hsgrad (B=-25), somecollege ([3119), hours (8:25), and male (8:.24). Other significantly related variables, in descending order of their Betas were: work experience (B=-.11), married (8:10), and family management (8=-.09). Useful inferences can be derived from the full model results. For instance, changes in the pattern of the variables’ behavior seen in the domain-by-domain regressions are noticeable in the full model. When looking at the variables belonging to the business domain, it is noticeable that for the occupations the pattern of significance is the same with occupation 6 (managers) being the only nonsignificant variable. From this, it is possible to conclude that the relationship of occupations as important variables connected to income is very strong and that the addition of variables from other domains did not change the importance of occupations. In contrast, HBFBSIZE was no longer significant when the full model was considered. That is, HBFBSIZE is not related to income. In the full model, family management was the only variable that was significant from the family domain. Contrary to expectations, family management was negative. This implies that greater management efforts result in lower 136 income. There is one plausible explanation for this surprising result. First, the type of analysis used, that is, multiple regression, assumes a one-way causation model. But, the direction of effects may be opposite to those assumed by regression. Perhaps lower levels of income require more management. Presumably, owners with lower income levels will need more goal setting, planning, organizing, and directing of resources to make ends meet goals than owners with higher income levels. Regarding the owner-manager domain, results found in the domain-by- domain analysis and the overall analysis differ. When the owner-manager domain was considered by itself, all the variables from the domain were statistically significant. In the overall regression, HBWAGE was not statistically significant. Some variables from the owner-manager domain are important and statistically related to income, for instance, NOTGRAD, HSGRAD, HOURS, MALE, SOMECOLL, WORKEXP, and, MARRIED. Finally, in the overall regression, none of the variables from the environmental domain were statistically significant. The only variable, population density, which was significant in the domain-by-domain analysis, turned out to be not significant in the overall regression. This result suggest that variables from the environmental domain are very weak; hence, there is a need to further explore other variables within this domain. All in all, four main variables emerged as important to explain home- based family businesses’ net annual income: the occupation in which the home- 137 based family business owner is engaged, the hours of work the owner-manager put into the business, the owner-manager gender, and his/her educational level. Other less important variables that emerged as related to home-based family business net income are: owner-manager’s work experience, marital status, and family management. These variables were expected to have a positive relationship with income; however, work experience and family management were significant and negatively related to income. To further explore the relation between work experience and income, years of work experience was squared and introduced again in the equation. Experience squared was found to be nonsignificant. This fact suggests that years of experience, as measured in this study, is not curvilinear. Moreover, the betas of the variables remain the same as well as the R2. The last overall regression is useful to see the behavior changes and strength of all the variables placed together. The strength of a multiple regression model is that it makes it possible to see the behavior of specific variables while at the same time holding constant other variables. One practical use of the results from the overall regression would be that certainly the occupation, the hours of work, and gender of home-based family business owners are powerful in explaining who will make more or less income. That is, on average, an owner who is a contractor, with a college degree, male, and working more hours will make considerably more income than an owner who 138 sells agricultural products, has not graduated from high school, is female, and work fewer hours than average. Finally, regression results from table 30 indicate that the amount of variation in home-based family business net annual income explained by the variables that pertain to the four domains for the total sample was adjusted R’=.22. That is, 22 % of the variation in home-based family business net annual income is accounted for by all the variables from the four domains considered. CHAPTER 5 DISCUSSION, CONCLUSIONS, AND IMPLICATIONS In this chapter, results of the study will be discussed and conclusions summarized within the context of the literature reviewed. As mentioned in Chapter 1, specific studies related to home-based family business income are scarce; therefore, the study referred to findings from fields such as small business, self-employment, and family firms to formulate comparisons and generalizations. What follows is the findings’ discussion and conclusion organized according to the four domains studied. Ultimately, implications of these conclusions for education, policy, and research are presented. Business Domain Results from the business domain indicate that business is a sphere which contains important variables related to income. For instance, the occupations in which home-based family businesses owners are engaged were predominant predictors of income. At least two plausible explanations why occupations are so predominant in predicting home-based family businesses’ income can be mentioned. First, 139 Hi) there may be differences in levels of competition for different occupations. For example, agricultural products and sales occupations operate in rural areas where the competition is great. This is a disadvantage in comparison to other occupations where the competition is less marked. Moreover, it is known that occupations providing services have greater competition and higher labor intensity than others (Humphreys 8. Mc Clung, 1981). In addition to higher competition, certain occupations such as those in the service sectors may impose geographical limitations that, aggravated with lack of capital, impede growth and consequently the income of the business. Second, certain occupations may be more flexible in responding rapidly to market incentives in the short run. For instance, an increase in demand could promptly be responded to by certain occupations. However, responses to market incentives may be limited by biological and intellectual capacity for other occupations. For instance, personal service occupations such as beauticians, barbers, caterers, and so forth can respond only up to a point to demand increases due to biological limitations; that is they can serve only a limited number of clients. Descriptives from this study suggest that home-based businesses have a tendency to stay small. Around 39% of them, with an average of 9 years of operation, have no employees. Hence, as is the case with self-employment, home-based family businesses appear to be a case of near-perfect inelasticity of labor supply. The owner-worker can alter the firm’s labor supply by improving the 141 quality and productivity of his/her own labor. However, at the limit of the home- based family business capacity, output can be increased only by adding capital or by employing others. This implies changes in scale and technology representing a long rather than a short-run response. Finally, to account for income differences in occupations, customers may place greater value on products or services provided by certain occupations (i.e., technology-driven services) rewarding them more than those supplied by other occupations. This study found that size of the business was statistically significant. The Beta was small, however. This result is in contradiction to small business findings which suggest that firm’s size is very important in determining business income (Aldrich & Weiss, 1981; Loscocco et al.,1991). Differences in results may be due to the scale used to measure business size. The Small Business Administration generally uses employment data as a basis for size comparisons, with firms having fewer than 100 or fewer than 500 employees defined as small. This business scale is much larger than the scale ~ of most home-based businesses. Descriptives from this research indicate that home-based family businesses’ average size is near four. Moreover, around 39% of the home-based family businesses studied have no employees, and approximately 70% of them have a maximum of three employees. Thus, by comparison these home-based businesses could be considered 142 microbusinesses. These differences in scale may explain, in part, differences in findings. Another important implication in relation to size of the business is that most of the home-businesses studied were not new, averaging over 9 years in the marketplace. This fact and its relation to size suggests that home-based family business owners may purposely keeping their enterprises small. The motivation for this fact can not be explained by this research. Cromie (1987) argued that starting and growing a business could be motivated by a number of reasons. Some pe0ple start their own business because they want the freedom to be their own bosses, others because they have a strong need for personal achievement or to express their creativity. Therefore, if home-based businesses only hire one or two employees it seems reasonable that the size of the business will not be a big influence on income. Understandably, bigger firms gain more from size because they are able to streamline, standardize, and program their operations. However, it seems that home-based family businesses do not reach the point where increases in the scale of operation result in increased output at decreasing incremental cost. In other words, economies of scale may be more applicable to small businesses than to micro-home-based businesses. It is possible that home-based businesses that grow to benefit from economies of scale have to move out of the home. Space constraints could be a limitation home-based businesses have to grow forcing them to move out of the home. 143 These conclusions should be taken carefully, however. First, the measure of business size did not distinguish differences between family, unrelated, paid and nonpaid employees. Heck and Walker (1993) reported that not all workers increase business outputs. This could be a reason why increased business size does not yield increased incomes. Heck and Walker suggested that if the highest level of output is to be achieved, family business owners need to select their employees carefully and may fare better by utilizing paid and contracting family workers and unrelated workers, not by utilizing unpaid family workers or unpaid helpers. Another variable considered within the business domain was borrowed capital. Contrary to expectations, this study found that borrowed capital was not significant. Descriptives of this study show that around 79% of the respondents reported that owners did not borrow capital. Assuming availability of capital to borrow, the low percentage of owners who borrowed capital may result from a variety of factors. Among those factors high information costs, underestimation of the capital required to sustain the enterprise beyond its infancy, and owner’s limited managerial and technological capacity to utilize capital can be mentioned. Small business research indicates that more capital is associated with better performance. The US. Small Business Administration (1988) provides substantial support for the importance of the role of business capital in explaining differences in earnings, especially for women. They report that, on 144 average, women sole pr0prietors started their businesses with only half the capital of men and were less likely than men to have borrowed capital, partly because a larger proportion of women reported that no capital was required. For small businesses, the amount of initial capital is related to the initial strategy that might be pursued. More initial capital permits a business to carry a broader mix of merchandise or to undertake more ambitious projects. More initial capital also buys time, while the entrepreneur learns to overcome problems (Cooper & Gimeno-Gascon, 1992). While levels of capitalization are very important for small businesses, descriptive and regression results from this study appear to indicate that the same conclusion is not applicable to home-based family businesses. Scale differences between small businesses and home-based family businesses can account for these contrasting findings. Home-based businesses’ fixed and operational capital could be assumed to be lower than small businesses’ volume of capital needs. Moreover, as was already pointed out, home-based businesses tend to stay small. Home-based owners, at the beginning of their businesses, may have a clear idea of the business size and volume they can handle and have no intention to operate beyond that size and volume. The conclusion that home-based family businesses may not need as much capital as other small businesses has to be taken cautiously, however. This research conclusion about the influence of borrowed capital on net income is based on a yes/no question: Did you(home-based worker) have to borrow 145 money or find an investor to start this business? Limitations of the data precluded more in-depth analysis of this variable. For instance, issues such as capital availability and financial institutions' discrimination against home-based business owners could not be investigated with the data available; nor could the amount borrowed. Another variable included for analysis within the business domain was seasonality. The rationale for including seasonality into the equation was that seasonal work may be less efficient than nonseasonal work. Also, it was thought that seasonal workers will care less about the economic outcomes of their enterprises due to marginal engagement with the business. Furthermore, if seasonal work does not provide the main income for the family, the lack of care and efficiency would be aggravated resulting in less income than nonseasonal work. Contrary to these views, no statistical relationship at .05 level between seasonality and income was found. This result indicates that holding constant the hours worked and other relevant variables, the assumptions about seasonal work were not correct. Another variable studied was the influence of the urban/rural location on income. The rationale for inclusion of this variable within the business domain was that businesses located in urban areas will have bigger markets than businesses located in rural areas. In addition, higher incomes of urban residents in comparison to rural area residents will translate into greater purchasing power for urban residents. Contrary to these expectations, urban residence was not 146 statistically significant at the .05 level. Based on this finding, this researcher reached the conclusion that businesses located in urban areas are not earning more income than businesses located in rural areas. This conclusion contrasts with the results of Rowe, Haynes et al. (1993). They found that urban location positively affects net business income. Differences in findings may be due to differences in operationalization of the dependent variable and the urban variable. Age of the business was studied within the business domain also. It was thought that businesses with more years of operation would have better organization, clientele formed, and operations systematized. Based on these presumptions, old firms would have greater incomes compared to younger firms. Findings contradict this expectation; age of the business was not statistically related to income. One plausible explanation for this finding is that the sample of this study is composed of home-based family business with at least 1 year of operation. Furthermore, these businesses have been, on average, operating 9 years. Hence, the sample did not capture new businesses where the liabilities of inexperience could be greater. Family Domain Results indicate that the family domain is not linearly related to home- based family business income. There are at least two plausible explanations for this finding. First, the variables included within this domain do not reflect the 147 power of the domain and its relation to income. Second, the family domain included variables such as open-not open family functioning type and a family management scale. The way these variables were measured and operationalized may not be capturing the strength of the underlying concepts and their relationship to income. One interesting finding, however, is that the variable family management was statistically significant when included in the overall regression. The relationship between family management and income was negative, however. That is, higher scores in family management were associated, with less net annual income. This finding contradicted the researcher’s expectation regarding this variable. This puzzling finding could have at least two explanations. One related to the statistical model used by the researcher. The multiple regression equation model assumes a one way causation. In this case, it was assumed that higher levels of income result from higher levels of family management. However, the direction of causation may be contrary to what was assumed. In other words, it may be the case that low levels of income require higher levels of management. Another plausible explanation is that family businesses located in the home may demand high levels of family managerial effort. Home-based businesses’ great family managerial needs may divert owner’s efficacy to manage their businesses. This may create a business management deficit affecting negatively the net business income. 148 All the other variables such as children under six years old, family size, and number of dependents needing care studied within the family domain were found to be not statistically significant when included in the overall regression. This finding seems to discredit the notion that family businesses are burdened by family responsibilities which inhibit higher incomes. Owner-manager Domain Results from this study indicate that within the owner-manager domain all the variables considered were statistically significant. Owner’s educational category, being male, and married were important variables in explaining income variation. In terms of relative importance, hours of work and being male were the most important variables. When exploring this domain, many questions could be asked: Does the age of the owner influence income earnings of the business? Does the gender of home-based family business owners affect the net income generated by the businesses? Do home-based family business owners with less education earn less income than those owners with more education? Regarding the influence of the age of the owner-manager, this study found that owner’s age is not a strong predictor of income. Moreover, it was found that gender does matter in explaining variation in net income. Evidence from this study indicates that on average home-businesses owned by males earn more income than those owned-managed by women. This finding is 149 consistent with a cumulative body of literature. For instance, Walker and Haynes (1995) found that regardless of the definition of earnings, women's earnings are considerably lower than those of men. Losccoco and Leicht (1993) also found differences between women's and men’s economic success among small business owners. It seems that gender earnings differences are well documented in the small business field. Although differences in income between women and men appear to be well documented, the factors that account for these differences are still elusive. Human capital theory posits that women earn less income than men because they invest less in their human capital. This study, however, controlled for education and years of work experience and still earnings differences by gender exist. Another plausible explanation is the theory which poses that women select lower paying occupations than men. Human capital theory posits that women choose to invest less in their education based on a rational cost/benefit decision. That is, women do not expect to regain their investment costs because they usually stop working due to pregnancy, family, or other responsibilities. Consequently, women are less educated and trained than men deterring their access to high paid occupations. Findings from this study have already pointed, out the importance of occupations in earnings. Therefore, this rationale seems to be more tenable in explaining income variation between women and men. Nevertheless, as will be seen in the last regression, where variables from all 150 domains were included, after controlling for occupations, differences in incomes remained. Hence, one question still needs to be investigated: What factors account for income differences between male and female owners? Another question posed is: Do home-based family business owners with less education earn less income than those owners with more education? Educational categories were statistically related to net annual income after controlling for age, gender, marital status, work experience, and hours of work. Taking college graduate owners (dummy variable not included in the equation) as the basis for comparison, the data revealed that educational categories were related to income in the following order: College graduate owners earn more income than owners with some college; owners with some college education earn more than owners who graduated from high school; and owners who graduated from high school earned more income than owners who did not graduate from high school. In other words, the greater the education the owner possesses, the greater will be his/her income. This finding is partly consistent with Loscocco and Leicht (1993) who argued that earnings are determined largely on the basis of productivity enhancing investments, such as education and experience. In contrast to Loscocco and Leicht, this study did not provide evidence that years of work experience was positively related to income. In fact, this study found that additional years of work experience decreased income. This contrasting finding is presumably due to differences in the definition of experience. Loscocco and 151 Leicht defined experience as the number of years a business owner has been in his/her industry. On the other hand, this study defined experience as the number of years a business owner had worked in any job prior to opening his/her own business. Moreover, in this study, the question related to years of work experience did not distinguish what type of experience owners had outside the home previous to starting their own businesses. It is plausible that certain types of work experience have more influence than others on income. Finally, the effect of marital status on net income was explored. Results show that owners who are married are making more income than those who are not. This finding is consistent with Cooper et al. (1990) who studied new small businesses in America. They found that married business owners tend to be more successful than single business owners. Many plausible explanations could be suggested for this finding. One is that married owners are more stable than nonmarried owners. Moreover couples can share business and family responsibilities, alleviating the burden of merging family with business. Environmental Qoma_i_r_t_ This study introduced the environmental domain to study home-based businesses. It was rationalized that broader environmental factors such as characteristics of a geographical region in terms of population density and income of the region could influence the income generated by home-based family businesses. 152 A linear relationship between the environmental domain and home-based family business income was found. However, results also indicated that the environmental domain by itself was able to explain only 2% of the variation in home-based family businesses’ annual income. Furthermore, from the three variables that were studied in this domain, only population density was statistically significant. These results suggest that the theoretical model is correct in including environmental variables to account for influences on income. Nevertheless, further exploration for variables within this domain is needed. Here it will be useful to remember that this study utilized secondary data. This fact prevented considering the effects of environmental variables such as local zoning, taxation, licensing, and the physical structure such as availability of water, electricity, sewage capacity and roads on home-based income. Business, Family, Owner-manager, and Environmental Domains All variables from the four domains considered, regardless of previous statistical significance, were entered in a final regression. Results from this final regression show that, in general, variables which were related to income in the domain-by-domain analyses are also significantly related to income in the overall regression. For instance, from the business domain variables, occupations continue to be the most relatively important variables related to income in the overall regression. 153 Among the occupations contractors (oCCUpation 8), was the most important occupational category. Following in importance were: mechanical and transportation (occupation 4), crafts and artisans (occupation 5), and services (occupation 7). Recall that the importance is relative to agricultural products and sales (occupation 9) which was not included in the regression. Professional/technical (occupation 1), clerical and administrative support (occupation 3), and marketing and sales (occupation 2) were also related to income but were less important. However, the order of relative importance of occupations is different from the order found when they were analyzed separately within the business domain. This finding suggests that there are forces other than occupations per se which influence the relative Importance of occupations; however, these forces are not strong enough to weaken the significant relationship between occupations and income. From the family domain variables, family management had a negative influence on income. As was already pointed out, this striking finding that the more the family manages, the lower is the income, may be due to higher family management requirements for low income owners. Looking at the variables pertaining to the owner-manager domain, the final overall regression shows that except for the age of the owner-manager and work experience all the other variables remain significant at the .05 level. This 154 pattern of significance is similar to that encountered when they were analyzed separately. In terms of relative importance, owner-manager variables show higher betas than the family and environmental domain variables, but lower than business domain variables. For instance, variables such as Hsgrad (B=-25) (dummy categories for education), hours of work (8:25), and male (8:.24) are found to be important. Considering the Betas of the overall regression it can be seen that after occupations, owner’s education, owner’s gender, and hours of work remain important variables related to income. Also, the relative importance of marriage has increased from (8:08) to ((3:10). Ultimately, the pattern of significance for the environmental variables changed. In the overall regression none were significant. Conclusions After reviewing the results of this study, the following conclusions can be mentioned: 1. Three of the four domains hypothesized as spheres of important variables: business, owner-manager, and the environmental domain, were linearly related to home-based family business net annual income. This, to some extent, validates the theoretical framework proposed for this study. 155 2. The business domain contributes with the most relatively important variables. Occupations are the most relatively important variables related to business income. 3. The owner-manager or personal domain is the domain with the largest coefficient of determination (R2) explaining the largest proportion of variation in income. Moreover, important variables related to income emerged from this domain such as categories of education, hours of work, gender, and marital status. 4. Opposite to expectations, the variables family management and years of work experience negatively influence income. 5. The environmental domain is linearly related to income; however, all the variables pertaining to the environmental domain were found not statistically significant. 6. From a research standpoint, results from this study suggest that owners’ occupation, education, and gender are extremely important determinants of income. This has been documented in general labor force literature for years and it seems to also be true for owners of micro-businesses. Implications This section attempts to draw out some implications of the findings from this study, address the gaps in knowledge about the relationship between home- based family business and its relationship to net annual income. Also, the 156 questions left out due to data limitations, and translate this information for researchers, educators, and policy makers. Implications for Research This research made an effort to measure and incorporate the elusive concepts of family and business management as income predictor variables. Family management was found to have a negative and statistically significant relationship to net annual income. However, the fact that the direction of the variable was contrary to expectations has implications for future research. The negative sign of the family management variable may indicate that reciprocal causation exists. Hence, it will be useful that future research studies incorporate more sophisticated statistical models such as multiequations or simultaneous- equations to gain more insights about the relationship of the management variable and income. Data limitations prevented inclusion of the business management variable into the regressions. However, descriptive statistics provided some insight regarding this variable. Future research needs to incorporate this variable to further understand its relationship to income. Moreover, this study made a first attempt to introduce a measure of family functioning type to test its relationship to income. The study found that the category open, is not related to income. Theoretically, the concepts are well defined. Family functioning types such as closed, open, random, and synchronous are well defined as mutually exclusive concepts by the literature. 157 Conceptually, family functioning types are consistent and may be useful in relation to the satisfaction family members experiment with different types of businesses. For example, open families may enjoy businesses that bring new experiences, putting them in contact with new persons and situations. It could be suggested that if families are content with the type of business they are doing, this could be important in the running of the business, which would translate in better incomes. Despite the conceptualization and seeming usefulness of the family functioning types, in reality, many families present mixed characteristics which make them difficult to type. Moreover, the instrument used in this study allowed the types to overlap. Hence, the operationalization of family functioning types needs further measurement refinement in order to gain empirical knowledge regarding their relationships to income. One theme that needs further study is the effect of technological change on home-based family businesses and how this change affects income. Today, home-based family businesses are probably using a lot of technical equipment such as computers, faxes, and modems. Data used for this study did not include information relating to the levels of technological sophistication used by the home-based family businesses and how the utilization of more technology affects income. It would be worthwhile for future research to look. at the effect of technological use and changes in use on the income of home-based family businesses. 158 This study found that owners who borrowed capital did not systematically have higher net business income. However, issues related to the availability of financial capital were not addressed directly. More investigation is needed in relation to financial institutions’ willingness to lend money to very small businesses, especially those owned by women whom lenders may see as high risk. This investigation is necessary to shed light on the question posed by Aronson (1991): Do women choose lower-paying businesses because they are unable to obtain financing for larger-scale and higher paying enterprises, or is the level of financing obtainable, especially from financial institutions, generally lower for women than for men because of a propensity among women to establish smaller-scale and financially riskier businesses? This research confirmed previous findings that there are differences between the earnings of women and men home-based business owners. Human capital theory suggests that differences in educational level, work experience, occupational choice, and family responsibilities intermingle to create these gender income differences. This study held constant levels of education, work experience, occupations, number of children less than 6 years old, and other important variables; however, differences in income between women and men remained. Therefore, the search for factors that account for gender differences in income should continue. Finding out what factors account for these gender differences in income will be very important for home-based family businesses 159 considering that approximately 42% of the home-based family business owners from the nine states studied are owned and managed by women. One theme omitted by this study, due to data limitations, was the effect of ethnic background on incomes. Previous small business studies have indicated that minorities are at disadvantage in terms of education and access to financial sources. This study found that education is related to income. That is, the more education owners have, the more income they will make. Therefore, it is important to investigate the educational level of minorities groups such as African Americans, Hispanic Americans and Asian Americans who own home- based businesses. Literature on minority-owned businesses cites characteristics of the business owners as factors mitigating against business success (Enz, Dollinger, & Daily, 1990; Green & Pryde, 1989). Moreover, the literature emphasizes the low rates of business participation by African Americans. An enlarged framework as the one utilized by this study could be useful to investigate not only owners but also family, business, and environmental factors as possible influence on the success of minority home-based businesses. Many studies dealing with small businesses, family businesses, or home- based businesses ignore issues of the wider economic and noneconomic context in which businesses are embedded and the impact of that broad domain on the potential business earnings. This study examined a number of environmental factors to determine relationships with net annual income. For 160 that purpose an enlarged theoretical framework including the environmental domain was developed. The study found the environmental domain to be related to income when family, business, and owner variables were excluded. However, the environmental domain variables had no explanatory power in the full model. This may be due to the limited selection of environmental variables imposed by secondary data. The fact that the environmental domain is related to income suggests that future research should continue searching within this domain for variables that may influence income. It could be suggested that variables that measure counties’ money flow, level of industrial capacity, and even an overall measure such as gross county product could be related to home-based net annual income. lmgljggtions forgducation This study found that occupational category variables are the most important variables related to income. Hence, occupations with higher income potential were identified. This finding implies that training programs and technical education should be developed around these occupations to prepare future workers with the knowledge and skills necessary to facilitate their entry into those occupations. A very strong finding from this study was the importance of educational categories in predicting incomes. It was found that more education represents higher incomes for home-based family business owners. As pointed out by the 161 literature reviewed, education is probably related to knowledge, skills, problem solving ability, discipline, motivation, and self-confidence. These may help home-based family business owners to deal and cope with the many problems encountered in their business. The study descriptives show that around 44% of home-based family business owners had no college education. Therefore, it will be important to develop educational programs targeted towards these owners with lower educational levels. Ultimately, due to data limitations, this study could not assess the effect of vocational education on income. However, it is assumed that educational programs that include training in developing business plans, advertising and marketing strategies, bookkeeping courses, legal advice, and computer training would be helpful. Mtions for Policy This study found that occupations were the important variables in explaining variation in income. Hence, if the goal is to increase the level of income earned by home-based family businesses, the policy recommendation that emerges from this finding is that policy makers should through legislation eliminate entry barriers to more lucrative occupations. This is especially important for women who are producing less income from their labor than their male counterparts. Moreover, selection of occupations is based on a rational decision; that is, owners assess available human and nonhuman resources to 162 decide to venture into specific occupations. Policy—makers could intervene by facilitating the access to human and nonhuman resources enabling owners to enter into occupations with higher income prospects. For example, providing information to avoid legal conflicts can assist potential home-based workers regarding legal and regulatory issues, thereby reducing the barriers to entry. This study also found that the owner-manager domain contains the second most relatively important variables in explaining net annual income. Those variables are: educational categories, hours of work, male, and marital status. From these variables, educational categories and hours of work can be influenced by policy. Hence, policies to help the educational and training needs of entrepreneurs should be written. Today, however, policy trends are directed toward cutting funding that supports education programs. This trend should be reversed, taking into account that higher levels of owners' education pay. In terms of gender differences this study found that women are earning less than male owners. Therefore, it seems critical that the policy environment give more attention to the empowerment of women entrepreneurs. Women may lack specialized knowledge related to business such as marketing, developing financing, and management of employees. Hence, it is recommended that the real needs of women business owners be assessed and addressed by policy makers. Finally, one significant finding in this study was that there was a strong relationship between the number of hours worked and net annual income. This 163 finding suggests that differences in earnings depend on differences in the amount of labor supplied. According to the descriptives, around 51% of the owners work less than 35 hours per week; that is, they are part-time workers. In line with findings about self-employment, this suggests that home-based workers are choosing to work less hours. Aronson (1991) asserts that there has been a change in the role of self-employment. He argues that self-employment has declined as the primary job between 1955 and 1980; however, it has shown an increase as the secondary job. Moreover, he suggests that increases in women’s self-employment has encouraged this development. These changes are posing time constraints to owners who have to combine to combine multiple jobs and family responsibilities. The policy implication of these developments is that policy makers should work toward policies that redefine flexible time. If today home-based workers are combining jobs, it is essential that time flexibility be reconsidered to allow the primary/secondary work combination. Moreover, it will be important to determine the time flexibility single-parent families need to allow the benefits of home-based work. This policy implication is important for policy- makers who want to reduce the number of persons on aid by training them to set up home-based enterprises. Ultimately, no one study can provide all answers, particularly for such a complex entity as home-based business. There is still much unknown about home-based businesses' net annual income and its relationship to different domains. However, it is hoped that this study be useful conceptually and 164 methodologically. It incorporated many domains and variables not studied together in previous research. It is thought that the model presented is a contribution toward studying home-based business more ecologically. Moreover, the study made an effort to indicate questions that were not asked and difficulties in the operationalization of some variables; hence, it is expected that these indications will enable future researchers to design and implement better- informed surveys. Finally, the use of a random data set drawn from many states and multivariate analysis give strong statistical validity to make generalizations about what was found. APPENDICES APPENDIX A 165 APPENDIX A Home-based worker study (selected questions from screening and instrument used for this study). From screening (:6. How long has (name) been doing this work from home? (From screening) ............. 1=months ............. 2=years Q7. 3. How many hours in an average day, week or month does (name) work at this job? .............. 1=Day Hours 2: Week 3: Month b- How many (days, weeks, months) did helshe work at this job last year? .............. 1=Day Hours 2: Week 3: Month 918. '3 this work seasonal? 1=Yes -> What months does helshe work? ............................ (Months) 2=No I66 Frgm Questionnaire q2. Do you live. . . 1= On a farm 2= In a rural area, but not a farm 3= In a small town, under 2,500 or 4= In a town or city larger than that? q4. Now we’d like to know a little bit about each member of the household. I’d like to know the first name of each household member. Let's begin with you, then list your spouse, followed by any children, oldest to youngest, and finally, anyone else who lives here and has no other home. a) What is (person’s) first name? b) Is (person) male or female? c) What is (person’s) relationship to you? d) How old was (person) on his/her last birthday? 6) Is helshe married? f) What is the highest grade of school (person) has completed? Include college, vocational, professional or technical training. 9) Is person employed full-time (35 hours or more per week); part-time; unemployed, but looking for work; unemployed, not looking for work; retired; disabled; or a full-time student? q5a. How many people in the household require care or supervision on a daily basis, like children, or disabled or elderly family members. .................. (number). 167 q10. One the things we are interested is learning about is how households operate with a home-based worker. These questions are about how you manage your household. Think of the scale from 1 to 5. The one (1) means the statement is not at all like your family, a 3 means it is somewhat like your family, and a 5 means it is exactly like your family. Tell me which number from 1 to 5 describes how much that statement is like you. Here is the first one. (a) When there is chore to be done at home, you wait until the last minute. 1 2 3 4 5 (b) You think about when to do a job, and not just how much time it will take. 1 2 3 4 5 (c) Each week you decide some way you can improve your life. 1 2 3 4 5 (d) When planning a job you think the plan through so that your goal is clear before you actually begin doing the job. 1 2 3 4 5 (e) Before you begin a job, you figure out how much of your time, money and energy that you can devote to this particular task. 1 2 3 4 5 (f) Before starting a job, you have a firm idea about how to judge the outcome. 1 2 3 4 5 (9) As you work, you check whether things are going as you want them to. 1 2 3 4 5 (h) You are pleased if the work just gets done; you do not spend time thinking about how effectively it was done. 1‘ 2 3 4 5 (i) When things are not going well, you figure out another way to do it. 1 2 3 4 5 0) When a job is done, you think about how well you like the results. 1 2 3 4 5 168 q11. Now I am going to read another series of statements. Would you tell me how closely each statement describes your family? Again think of the scale from 1 to 5. The one (1) means the statement is not at all like your family, a 3 means it is somewhat like your family, and a 5 means it is exactly like your family. Tell me which number from 1 to 5 describes how much that statement is like your family. Here is the first one. (b) Your family enjoys the variety of people and activities the home based work brings to your life. 1 2 3 4 5 (h) Your family is open to new ideas if they seem practical. 1 2 3 4 5 (I) In your home, friends often drop by and are easily included in whatever your family is doing. 1 2 3 4 5 (e) Your family makes decisions by rules you have always used. 1 2 3 4 5 (j) Your family usually does things the same way time after time. 1 2 3 4 5 q14. This section is about the people who worked for the business or helped out during 1988. (a) Did anyone besides (hbw) work for or help out with this business during 1988? 1=Yes 2=No (b) Were there (type of worker)? (c) How many were there in 1988? (d) How many were household members? (e) How many were relatives who did not live in the household? I69 (a) (b) (C) ((1) Type of worker Have in I988 How Household Other Yes No many member relatives Paid employees? 1 0 Independent contractors I O (accountant, bookkeeper, electrician?) People who did some work I 0 for the business and were not paid? q16. Did (home-based worker) have to borrow money or find an investor to start this I business? ' 1=Yes 2=No q26 What was the net income your household received from your business in 1988? $ q35c. How many years in total did (helshe/you) work outside the home? q36. This section includes general questions on how (type of work) is planned and done. Think on the scale from 1-5. Remember that 1 means not at all like you, the 3 means somewhat like you, and the 5 means it is exactly like you. Which number most closely describes you and how you work. Here’s the first one. 170 (a) Each week you decide how much work you will do. 1 2 3 4 5 (b) When planning a job you think the plan through so that your goal is clear before you actually begin doing the job. 1 2 3 4 5 (c) Before starting a particular job, you figure out what you need, like tools, supplies, time, etc. 1 2 3 4 5 (d) Before starting a job you have a firm idea about how to judge the outcome. 1 2 3 4 5 (6) Although you are flexible, you make work schedules. 1 2 3 4 5 (f) When there is work to be done, you wait until the last minute. 1 2 3 4 5 (9) As you work, you check whether things are going as planned. 1 2 3 4 5 (h) You change how you are doing a task when the results are not as planned. 1 2 3 4 5 (I) When finished, you ask whether people and equipment have been used to the best advantage. 1 2 3 4 5 (j) When you finish a job, you think about whether the results meet your standards as well as your client’s or employer’s. 1 2 3 4 5 I71 8.8. dam. .- - $38: .8 8.- -. 28.58. .3 B. .9.- i mummumx .9 8. .3.- 8. .- moswfim .9 8. 8.- 8. .9. . .- 9658 .: 8. .2.- 8. .9. .:. i 88 .2 S.- 8: 8. .3. .9- 8.- .- 88 .8 .2.- 8. .9.- .:.- .9.- 8.- 8.- .- 88 .8 no.1 mo... .vv. 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Smwuzv 003990908020 commemEemcso. 0cm 0Eooc_ mo. c0023 09.290.860.099: mm 03m..- I74 I wzmomOm .m ha. I mmhmm>z_ .v .05. .mn. I wmaoa .m .mNr .vmr «mm... I anus—NZ: .N .3. .9. «mo. «mor I 02.004 ._. m v m N F AONOH av m®_Dmtm> mozwtmuomgmco _macmECOCSCO UCN 08005 GO. Cwmgmn wC0_um_m.:OU._0~C_ vm 03m... APPENDIX B REFERENCES REFERENCES Aldrich, H., & Weiss, J. (1981). Differentiation within the United States capitalist class: Workforce size and income differences. American Sociological Review 46, 279-290. Aronson, R.L. (1991). Self employment: A labor market perspective. Ithaca. N.Y:ILR Press. Bates, T. (1993). Banking on black enterprise: the potential of emerging firms for revitalizing urban economies. Washington, DC: Joint Center for Political and Economic Studies. Lanham. MD: University Press. Bates, T. (1987). Self-employed minorities: Traits and trends. Social Scieng Quarterly, 68, 542-544. Bates, T. (1989). Small business viability in the urban ghetto. Journal of Regional Science, 29, 625-643. Beckhard, R. (1983). Conversation with Richard Beckhard. Organizational Dynamics, 12. (Summer,1993) pp 29-38. Bender, H. (1980). Report on women tysiness owners. American Management Association. Berk, SF. (1985). The gender factory: The apportionment or work in Ameripp households. New York: Plenum. Birch, D. (1987). Jpp crejation in America: How fl); smallest companies M the most people to work. New York: Free Press. Blau, FA, & Ferber, MA. (1992). The economics of women. men and work (2ned.). Englewood Cliffs, NJ: Prentice-Hall. Bonacich, E., & Light, I. (1988). Immiggpnt entrepreneprs: Koreans in Los Angeles 1965-1982. Berkeley: University of California Press, 1988. 176 I77 Bubolz, M.M., & Sontag, MS. (1993). Sourcebook of family theories and methods: A contextual approach. In P.G. Boss, W. J. Doherty, R. LaRossa, W.R. Schuman, & S.K. Steinmetz (Eds), Human ecology theogy (pp. 419-448). New York: Plenum. Bryant, W. K. (1992). Human capital, time use, and other family behavior. Journal of Family and Economic Issues. 13 (4), 395-405. Carrol, GR. (1983). A stochastic model of organizational mortality: Review and reanalysis. Social Science Research, 12, 303-329. Churchill, NC, and Hatten, K. (1987). Non-market based transfer of wealth and power: A research framework for family businesses. American apprnal of Small Business, 12, (2) 51—64. Coates, V. (1988). Office automation technology and home-based work. In k. Christensen (Ed), The new era of home-basep work: Directions a_n_q policies (pp. 114-125). Boulder, CO: Westview. Cohen, J., & Cohen, P. (1975). Applied multiple regression/correlation analysis for the pehavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates. Constantine, L. (1986). Family paradigms: The practice of theom in family therapy. New York: Guilford. C00per, A.C., Dunkelberg, W.C. Woo, C.Y., & Dennis, W.J. (1990). New business in America: The firms and their owners. Washington, DC: NFIB Foundafion. Cooper, A.C., & Gimeno-Gascon, F .J.(1992). Entrepreneurs, process of founding, and new firm performance. In D. Sexton & J. Kasarda (Eds), The state of the art in entrepreneurship (pp. 301-340) Boston, MA: PWS- Kent. Covennan, S. (1983). Gender, domestic labor time, and wage inequality. American Sociological Review. 48, 623-637. Cromie, S. (1987). Motivations of aspiring male and female entrepreneurs. Journal of Occupational Behaviour, 8 (3), 251-261. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. mchometrika. 16. 297-334. 178 Dannhaeuser, N. (1993). The survival of family-operated firms under developed conditions: The case of Hassfurt, Germany. The Journal of Developing Areas 27, 307-328. Deacon, R.E. & Firebaugh, F. M. (1981). Family resource management: Principles and applications. Boston: Allyn and Bacon. Deacon, R.E. & Firebaugh, F. M. (1988). Family resource management: Principles and applications (2nd ed.). Boston: Allyn and Bacon. Dickinson, R. (1981). Business failure rate. American Jogrnal of Small Business 7(2) 17-25. Enz, C.A., Dollinger, M.J. & Daily, CM. (1990). The value orientations of minority and non-minority small business owners. Entrepr_enet_lrship: Theory and Practice, 15(1), 23-25. Ferber, M., & Huber (1979). Husbands, wives, and careers. Journal of Marriage and the Family. 41, 315-325. Fitzsimmons,C., Larery, DA, 8- Metzen, E.J. (1971). Maior financial decisions arflgrises in the family life spap (North Central Regional Research Publication N0.208) West Lafayette, IN: Purdue University, Agricultural Experiment Station. Fratoe, F A. (1986). A sociological analysis of minority business. The Review pf flack Political Economy. 15, 5-29. Green, S., & Pryde, P. (1989). Black entremnegrship in America. New Brunswick, NJ: Transaction. Goffee,R., & Scase, R. (1985). Women in charge: The experience pf femal_e_ entrepreneu_r_§. London: Allen 8- Unwin. Griliches, G. (1957). Specification bias in estimates of production functions. Journal of Farm Economics. 39, 8-20. Gross,l. H., Crandall, E. W.,& Knoll, M. M. (1980). Management for mcfiern families (4th ed.). Englewood Cliffs, NJ: Prentice-Hall. Gross, I.H., 8- Zwemer, EA. (1944). Management in Michigan homes (Technical Bulletin 196). East Lansing: Michigan Agricultural Experiment Station. Heck, R. (1988). A profile of homebased workers. Human Ecology Forum, 16, (4), 15-18. 179 Heck, R. (1991). Employment location choices: Factors associated with the likelihood of home-based employment. Lifestyles: Family and Economic Issues, 12, 217-233. Heck, R. (1992). The effects of children on the major dimensions of home-based employment. Journal of Family and Economic Issues, 13 (3) , 315-346. Heck, R., Stafford, K., Winter, M., 8- Hennon, CB. (1993). Home-based business and family outcomes. Proceedings of the American Council on msumer Interest, 39, 352-356. Heck, R & Walker, R. (1993). Family-owned home businesses: Their employees and unpaid helpers. Family Business Review, 4, 397-415. Heck, K.Z., Winter, M., & Stafford, K. (1992). Managing work and family in home- based employment. Journal of Family and Economic Issues, 13 (2),187-212. Heck, R., Winter, M., 8- Stafford, K. (1994). Family management behavior of households owning home-based businesses. Home-based businesses and their families. Cornell Cooperative Extension In-Service Education. Heck, R., Winter, M., 8- Stafford, K. (1995). _B_t_.isiness management behavior of home-pasedgusiness owners. Home-pased business and their families. Cornell Cooperative Extension ln-Service Education. Hisrich, RD, 8- Brush, C.G.(1984). The woman entrepreneur: Management skills and business problems. Journal of Small Business Management, a, 30-37. Horvath, F .W. (1986). Work at home: New findings from the current population survey. Monthly Labor ReviewJOQ (11), 31-35. Humphreys, M. A., 8 Mc Clung, H. (1981). Women entrepreneurs in Oklahoma. Bgview of Rewal Economics and Business 6 (2), 13-20. Jovanovic, B. (1982). Selection and the evolution of industry. Econometrica 50, 649-670. Juster, F. T. 8- Stafford, F. P. (1991). The allocation of time: Empirical findings, behavioral models, and problems of measurement. Journal of Economic Literature 29, 471-522. Kanter, R (1977). Worflnd family in the United States: A critical review and agenda for research and policy. New York: Russell Sage Foundation. 180 Kantor D., & Lehr, W. (1975). Inside the family: Toward a theory of family process. New York: Harper Colophon. Kalleberg, A. L., 8- Berg, l. (1987). Work and industry. New York: Plenum. Kalleberg, A. L., & Leicht, K.T.(1991). Gender and organizational performance: Determinants of small business survival and success. Academy of Management Journal. 34 (1) , 136-161. Keeble, D. 8. Walker, S. (1993). New firms, small firms and dead firms: Spatial patterns and determinants in the United Kingdom. Regional Studies, 28, (4) , 411-427. Kepner, E. (1983). The family and the firm: A coevolutionary perspective. Organizational Dynamics, 12, (Summer, 1993) 57-70. Key, R.J.(1985). Sequencing of household activities. In K.S. Behm (Ed.), Proceedings of the Southeastern Family Economics-Home Management Association (pp.127-131). Baton Rouge: Louisiana State University. Kirchhoff,B.A., 8. Kirchhoff, J.J. (1987). Family contributions to productivity and profitability in small businesses. Journal of Small Business Management, _2_§ (4), 25-31. Larson, C. M. 8. Clute, R. C.(1979). The failure syndrome. American Journal of Small Business 4 (2) 35-43. Lewis-Beck, M. S. (1980). Applied regression: An introd_uction. Beverly Hills: Sage. Long, L.H. (1974). Women's labor force participation and the residential mobility of families. gaciafl‘orces. 52, 342-348. Loscocco, K.A., & Leicht K.T. (1993). Gender, work-family linkages, and economic success among small business owners. Journal of Marriage and the Family, 55, 875-887. Loscocco, K.A. 8- Robinson, J. (1991). Barriers to women’s small business success in the United States. Gender & Society. 5. 511-532. Loscocco, K.A., Robinson, J., Hall, R. H., & Allen, J.K. (1991). Gender and small business success: An inquire into women’s relative disadvantage. Social Forces 70(1), 65-85. 181 Marini, MM. (1978). The transition to adulthood: Sex differences in educational attainment and age at marriage. American Sociological Review, 43, 483- 507. Marshack, K.J. (1993). Coentrepreneurial couples: A literature review on boundaries and transitions among copreneurs. Family Business Review. _6_ (4), 355- 369. Masuo,D., Walker, R., & Furry, M. (1992) Home-based workers: Worker and work characteristics. Journal of Family and Economic Issues. 13 (3), 245- 262. Mefford, RN. (1986). Introducing management into the production function. Review of Economics and Statistics. 68, 96-104. Moyes, A. & Westhead, P. (1990). Environments for new firm formation in Great Britain. Regional Studies, 24 (2), 123-136. Nickell, P., Rice, A., 8- Tucker, 8. (1976) Management in family living. New York. Wiley. Norusis, M.J., & SPSS Inc. (1993). SPSS for wingows: Base system user’s guide. release 6.0. Chicago, SPSS Inc. Owen, A.J., Carsky, ML, 8- Dolan, E. M. (1992a). Home-based employment: Historical and current considerations. Journal of Family and Economip Issues, 13121-138. Owen, A.J, Rowe B.R. & Gritzmacher,J.E. (1992b). Building family functioning scales into the study of at-home income generation. Journal of Family and Economic Issues, 13 (3), 299-313. Paolucci, B., Hall, 0. A., & Axinn, N. (1977). family resogrce management: Principles and applications. New York. John Wiley. Pellegrino, ET. 8- Reece BL. (1982) Perceived formative and operational problems encountered by female entrepreneurs in retail and service firms. Journal of Small Business Management. 29, 15-24. Pleck, J.H. (1977). The work-family role system. Social Problems 24, 417-427.Pratt, J.H. (1993). Myths and realities of working at home: Characteristics of homebased business owners and telecommuters. Washington, DC: Government Printing Office. 182 Pratt, J. H.,& Davis,J. (1985). Measurement and evaluation of the populations of family-owned and home-based businesses (US. Small Business Administration, Contract SBA-9202-AER-85). Washington, DC: Small Business Administration. Riordan DA, & Riordan MP. (1993). Field theory: An alternative to systems theories in understanding the small family business. Journal of Small Business Management, 31 (2), 66-77. Robinson, P.B., & Sexton EA. (1994). The effect of education and experience on self-employment success. Journal of Business Venturing, 9, 141-156. Rosenblatt, P.C., de Mik, L., Anderson RM, 8- Johnson PA. (1985). The family in business: Understanding and dealing with the challenges; firepreneurial families face. San Francisco: Jossey-Bass. Rowe, B.R., Haynes, G.W. 8- Bentley, MT. (1993). Economic outcomes in family-owned home-based business. Eapmily Business Review. 6, 383- 396. Rowe, B.R., Heck, K.Z., Haynes,G.W. & Bentley, MT. (1993). Family-owned home businesses and their economic outcomes. Proceedings of the American Cogncil on Consumers Interests. 39. 362-365. Rowe, B.R., & Bentley T.M.(1992). The impact of the family on home-based work. Jo_urnal of Family ang_Economic lssgfi, 1a (3), 279-297. Rowe, B.R., & Heck K. 2. (1995). Homeworking families and how they make it work. In R.K.Z. Heck, A. J. Owen & B.R. Rowe (Eds), Home-based employment and family life ( pp 107-134). London: Auburn House Safilios-Rothschild, C. (1976). Dual linkages between the occupational and family systems: A macrosociological analysis. Signs, 1, 51-60. Scase, R., & Goffee, R. (1982). The entrepreneurial middle class. London: Croom Helm. Sexton, E.A., & Robinson, P. B. (1989). The economic and demographic determinants- of self-employment. In R. H. Brochaus et al., (Ed), Frontiers to entreprenegrship research (pp.28-42). Wellesley, MA: Babson College. Shamir, B. (1992). Home: The perfect workplace? In S. Zedeck (Ed.), Work, families and organizations. San Francisco: Jossey-Bass. 183 Sharpe, D. L. B. (1988) Time devoted by women to selected household tasks, 1975-1981: lmpligations for assessing change in standards. Unpublished doctoral dissertation, Iowa State University, Ames. Shelton, B.A., & Firestone, J. (1989). Household labor time and the gender gap in earnings. Gender and Society&, 105-112. Silver, H. (1989) The demand for homework: evidence from the US. census. In E. Boris 8- C.R. Daniels (Ed), Homework: Historical and contemporagy perspectives orQaid labor at home (pp 103-129). Urbana: University of Illinois Press. Stafford, K, Winter,M.,Duncan,K.A., & Genalo, MA. (1992). Studying at- home income generation: Issues and methods. Jourrlal of ijily fig Economic Issuesg13 (2), 139-158. Tauer, L. W. (1984). Productivity of farmers at various ages. North Central Journal of Aggcultural Economics. 6 (1), 81-87. Tigges, L.M. & Green, GP. (1994). Small business success among men and women-owned firms in rural areas. Rural Sociology, 59, 289-310. Tufte. E. R. (1974). Data analysis for politics and policy. Englewood Cliffs, NJ: Prentice-Hall. US. Small Business Administration.(1984). The state of small business: A report to the president. Washington DC:U.S. Government Printing Office. U. 8. Bureau of the Census (various years). Census of population and housing. Washington, DC: US. Bureau of the Census (Producer and distributor). US. Department of Commerce, Office of Federal Statistical Policy and Standards. (1980). Standard occgpational classification manual. Washington, DC: US. Government Printing Office. US. Department of Commerce, Bureau of the Census. Statistical abstracts of the United States. (1994). Bernan Press (114th edition) Washington, DC. 401-402. US. Department of Labor. Bureau of Labor Statistics. (1986). Employment and earnings. Washington, DC: Government Printing Office. US. Department of Labor. Bureau of Labor Statistics. (1990). Monthly Labor Review 113, (12). 184 U. 8. Small Business Administration. (1986). The state of small business: A report of the President. Washington, D.C:U.S. Government Printing Office. U. S. Small Business Administration. (1988). Small business in the America_n_ economy. Washington DC:U.S. Government Printing Office. U. 8. Small Business Administration. (1991). The state of small business: A [_e_port to thapiesident. Washington DC:U.S. Government Printing Office. US. Treasury Department. (1978). Credit and capital forrgation: A report to the president’s interagency task force on women business owners. Washington, DC: Government Printing Office. Walker, K. E., & Woods, M. E. (1976). Time use: A measure of household production of family goods and services. Washington, DC: American Home Eganomics Association. Walker, R., Furry, MM, 8- Masuo, D. M. (1993) The gender factor in hours workecLarfi net income of home-basecupusiness owners. Paper presented at the American Council on Consumer Interests, Lexington, KY. Walker, R., & Haynes, G. (1995). Economic ogtcomes: The gender factor. Paper presented at the annual conference of the International Family Business Programs Association, Nashville, TN. Winter, M., Puspitawati, H. , Heck, R., & Stafford K. (1993) Time-management strategies used by households with home-based work. Journal of Family and Economic Issues-14 (1) , pp. 69-92. Wolfgram, TH. (1984). Working at home: The growth of cottage industry. Futurist 18(3), 31-34.