17_jwe_1-2 UDC: 005.32:331.1 005.961:005.336.1 JEL: L26, M13, M2 COBISS.SR-ID: 238898700 ORIGINAL SCIENTIFIC PAPER Small Firm Owner Characteristics and Primary Employment Halil Dincer Kaya1 Northeastern State University, Broken Arrow, Oklahoma, United States A B S T R A C T Our objective in this study is to examine the relation between small business owners’ characteristics and their tendency of having their business as their “primary employment”. In order to achieve that objective, we compare owner characteristics in high “primary employment” U.S. states versus in low “primary employment” states. We use the “United States Small Business Friendliness Survey” done by Kauffman Foundation and Thumptack.com in 2013. Our nonparametric tests show that in the states where relatively high percentage of owners have their business as “primary employment” (i.e. “high primary employment states”), owners run their business in a more professional way (i.e. relatively more owners hire managers to run their business). We also find that, in these states, owners have significantly more previous startup experience. In addition, we find that, in these states, there are fewer “Caucasian” owners and significantly more owners from other races. On the other hand, our findings show that there is no significant difference between owner’s gender, age, political view, and education across high and low primary employment states. We advise policymakers to use these findings when formulating policies that support entrepreneurship. 1 Northeastern State University, Broken Arrow, OK 74014, United States, kaya@nsuok.edu Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 41 KEY WORDS: entrepreneurship, small business, primary employment, entrepreneurial activity, owner characteristics Introduction In this study, we examine the relation between small business owners’ characteristics and their tendency of having their business as their “primary employment”. In order to achieve that objective, we analyze U.S. states. First, we differentiate between states that have a higher percentage of small business owners that have their business as “primary employment” (rather than a side job or a hobby), and states that have a lower percentage of owners that have their business as “primary employment”. We call the first group the “high primary employment states” and the second group the “low primary employment states”. Then, we compare owner characteristics in “high primary employment states” versus in “low primary employment states”. A small business owner to have his/her business as “primary employment” is important because this form of entrepreneurship reflects a stronger form of entrepreneurship than a business run as a side job/hobby. Our purpose here is to differentiate between the characteristics of owners in “high primary employment states” versus in “low primary employment states”. What type of entrepreneurs tends to have their business as their primary employment? We are hoping to answer this question. The answer here will help policymakers with their policymaking process: In order to promote this stronger form of entrepreneurship (i.e. business as “primary employment”), what type of potential entrepreneurs should the policymakers focus their support on? If a state wants to successfully promote this stronger form of entrepreneurship, it needs to be efficient in allocating its resources, therefore it needs to know what type of potential entrepreneurs to support more. In our analysis, we use the “United States Small Business Friendliness Survey” by Kauffman Foundation and Thumptack.com in 2013. This survey contains questions for small business owners on whether their business is their “primary employment”. It also asks them questions about their position in their company, their previous entrepreneurship experience, their gender, age, political view, education, and race. 42 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) The paper proceeds as follows: Section 2 goes over the previous literature. Section 3 explains the data and the methodology. Section 4 shows the empirical results. Finally, Section 5 concludes. Literature Review Several previous studies examine entrepreneurial activities that start as a hobby. Heimonen (2013) classifies some business ventures as supplementary form of income where the entrepreneur seeks both personal and financial success. These entrepreneurs describe their purpose as “have fun, do what you want to do and at the same time earn some money; it is a hobby and at the same time an opportunity to earn money; part time entrepreneurship, small scale business, flexible working hours with long weekends; opportunity to maintain good health and functionality”. Giacomin et al. (2011) try to identify the impact of the socio-economic characteristics of entrepreneurs on their opportunity-necessity positioning. The authors show the impact of the socio-economic characteristics of entrepreneurs on the alignment of their project with a necessity or opportunity entrepreneurial dynamics. The authors state that not all jobseekers are necessity entrepreneurs and that new venture creation based on family influence may convey both a necessity and an opportunity dimension. They also describe “hobby entrepreneurship” as a new type of entrepreneurship. Cagetti and De Nardi (2006) examine the relation between the type of entrepreneur and his/her wealth. The authors argue that the poorest business owners might be the low-wage workers who turn to self-employment for lack of better opportunities or people who are self-employed as a hobby. Interestingly, the business owners who do not have an active management role in the business are very rich and are likely to use the business as an investment opportunity. Rantamaki-Lahtinen and Vihinen (2004) discuss the transition of “hobby” entrepreneurs into regular business owners. The authors examine the role of equine industries in Finnish rural development and rural entrepreneurship. Their objective is to discuss on what kind of role equine industries can have in Finnish rural development from rural entrepreneurship and rural policy point of views. According to the authors, equine industries are special among the rural industries because of their interaction between the “rural” and “urban”. Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 43 Equine industries bring new people, both customers and entrepreneurs, from urban areas to the countryside. The authors explain that especially young women from Southern-Finland are keen on cross-country horseback riding as a hobby. The authors state that “These new people bring significant amount of new financial and social capital, new ideas, networks and skills that are very much needed today. Entrepreneurs, who move to the rural areas from elsewhere, might see local business opportunities from a different angle. They also have their own social networks that will get attached to local networks. Urban customers bring money and their social networks along when they come to have their riding lesson or riding holiday. On the other hand, as trotting races are mostly organised in urban areas, equine enterprises are bringing the rural things to urban surroundings”. Rantamaki-Lahtinen and Vihinen (2004) also explain that the interaction between rural and urban might cause conflicts. For example, local people might not accept new entrepreneur or his/her clients. Newcomers may be arrogant or may not understand local norms. Block and Landgraf (2016) argue that part-time entrepreneurship is often a first step towards full-time entrepreneurship. The authors analyze how financial and non-financial motives of part-time entrepreneurs influence the propensity of part-time entrepreneurs to become full-time entrepreneurs. Their results show that “the motivation to supplement wage income or the motivation to achieve social recognition is negatively associated with transition behavior, whereas the motivation to achieve independence or self-realization is positively associated with transition behavior”. They show that the motivation to follow a role model, financial success, and innovation are not significantly related to transition behavior. Folta et al. (2010) argue that individuals may take on second jobs where they gain nonmonetary benefits that might not be available in their primary jobs. According to the author, “Hybrid entrepreneurship” may be preferred to a second wage position because it provides additional monetary and psychological benefits. Kerr and Nanda (2009) argue that most hobby entrepreneurs or sole proprietors will never seek to hire someone else, remaining permanently in the lower bubble. In some cases, the start-up will grow much larger, according to the authors, following the path of famous Silicon Valley firms like Hewlett-Packard that began in a garage. 44 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) Kourilsky and Walstad (2002) surveyed 1,001 owners/founders of high-technology businesses with under 200 employees. Their findings suggest an important potential role for education in general and entrepreneurship education in particular. The authors state that “One potential strategy recommended is to craft crosscutting educational partnerships that carefully blend entrepreneurship education, technology content-specific education, and high-technology venture experience at both the high school and college levels”. The entrepreneurs’ top six events towards starting or owning a business are “Past job or job experience”, “Technology idea or opportunity/Inventing the system”, “Losing a job or becoming unemployed”, “Independence/Freedom/Be my own boss/Work at home”, “Technology hobby”, and “Need/Demand/Market at right time”. Warnick (2016) states that “entrepreneurship research has, to date, focused on passion in terms of a passion for activities related to the entrepreneurial process (“entrepreneurial passion”), including the identification of new venture opportunities, the founding of new ventures, and new venture development”. The author “expands the conception of passion in entrepreneurship research to include entrepreneurs who engage in entrepreneurial activities not out of entrepreneurial passion, but out of a passion for the domain of their venture and product or service it provides (“domain passion”)”. The author develops a dynamic model of hobby monetization. Warnick (2016) shows “the mechanisms by which monetization of domain passion as a hobby-related venture can (1) bolster or (2) erode domain passion”. The author also “demonstrates the importance of founder domain passion and entrepreneurial passion to startup investors, finding that both are important in investors' decision-making in addition to domain and entrepreneurial experience and openness/receptivity to feedback”. The author states that “the appeal of entrepreneurial passion to startup investors was further elevated when accompanied by domain experience, and both passions become even more appealing when investors perceived the founder to be highly open and receptive to feedback”. Anwar and Daniel (2016) argue that home-based businesses and their founders represent an important, but under-researched facet of entrepreneurship. According to the authors, unlike hobby-businesses with little economic impact, home-based business makes significant contribution to national economies in terms of both turnover and employment. Rangarajan and Lakshmi (2013) argue that “creativity and innovation are considered to be inseparable from entrepreneurship, which is in turn Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 45 manifested in the act of starting up and running an enterprise. The authors argue that “people become more creative when they feel motivated primarily by the interest, satisfaction, and challenge of the situation and not by external pressures; the passion and interest - a person's internal desire to do something unique to show-case himself or herself; the person's sense of challenge, or a drive to crack a problem that no one else has been able to solve. Creative entrepreneurs possess high levels of energy and great degrees of perseverance and inauguration, which combined with a willingness to take moderate, calculated risk, enable them to transform what began as a very simple ill- defined idea or hobby into something concrete”. The authors support their arguments by surveying entrepreneurs in Chennai, India and by showing that these entrepreneurs’ production reflects a high level of creativity and innovation. According to the authors, “innovation is the key to push entrepreneurship”. According to Okpara (2007), creative entrepreneurs possess high levels of energy and great degrees of perseverance and inauguration, which combined with a willingness to take moderate, calculated risk, enable them to transform what began as a very simple ill- defined idea or hobby into something concrete. Shah and Tripsas (2007) develop a “process model of how users, an understudied source of entrepreneurship, create, evaluate, share, and commercialize their ideas”. The authors “compare and contrast our model to the classic model of the entrepreneurial process, highlighting the emergent and collective nature of the user's entrepreneurial process”. According to the authors, users are often “accidental” entrepreneurs who happen upon an idea through their own use and then share it with others. Shah and Tripsas (2007) contend that “users also tend to engage in collective creative activity prior to firm formation—often within the social context provided by user communities—that results in the improvement of ideas”. According to Williams (2007), informal business ventures can often arise from some hobby or interest. According to the author, this is “the systematic pursuit of an amateur, hobbyist or volunteer activity that participants find so substantial and interesting that they launch themselves on a career centered on acquiring and expressing its special skills”. Tambunan (2009) categorize women entrepreneurs in Asian developing countries into three groups: chance entrepreneurs, forced entrepreneurs, and created or pulled entrepreneurs. According to the author, one of the motivations of chance entrepreneurs is their business being their hobby or 46 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) special interest. Van der Merwe and Lebakeng (2010) investigate women entrepreneurship in Lesotho and find that 11% of the entrepreneurs are motivated by the further development and expansion of their hobby. Williams and Nadin (2012) argue that entrepreneurial business ventures in the informal economy, can be either a spin-off from the formal occupation of the informal entrepreneur, or alternatively, can derive from a hobby or interest. Williams and Round (2006) interviews 600 entrepreneurs in Ukraine and finds that one fifth of them arose out of a hobby or interest that leads them to set up enterprises selling goods produced or services resulting from it. The authors state that this percentage includes those who learned some skill by pursuing some hobby or interest (e.g., painting, carpentry) and then decided to establish an enterprise based on this skill. As we are seeing, there are several previous papers on entrepreneurship as a hobby. These papers explore the motives of the entrepreneurs and explain the process in which a hobby turns into a full-time job. The next section explains the data and the methodology. Data and Methodology In order to achieve our objective, we compare owner characteristics in high “primary employment” U.S. states versus in low “primary employment” states. For this purpose, we divide the U.S. states into two groups based on the percentage of respondents that have their business as their primary job. The states with a percentage above the mean percentage for all states are classified as “high primary employment” states. The states with a percentage below the mean percentage for all states are classified as “low primary employment” states. Then, we use nonparametric tests (i.e. Mann-Whitney-Wilcoxon tests) to compare the respondents’ characteristics (their position in their company, their previous entrepreneurship experience, their gender, age, political view, education, and race) across high- and low- primary employment states. All of the variables are explained below. These variables for each state are computed using the individuals’ responses: − Percentageofprimaryemp: the percentage of small business owners that have their business as their primary job. − Managerbutnotowner: the percentage of respondents who are the manager but not the owner Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 47 − Nonmanageremployee: the percentage of respondents who are an employee but not the manager − Ownerandmanager: the percentage of respondents who are the owner and the manager − Ownerbutnotmanager: the percentage of respondents who are the owner but not the manager − Previousentre: The percentage of owners who has previous entrepreneurship experience − Previousstartups1: The percentage of owners who started one previous business − Previousstartups2: The percentage of owners who started two previous businesses − Previousstartups3: The percentage of owners who started three previous businesses − Previousstartups4: The percentage of owners who started four previous businesses − Previousstartups>4: The percentage of owners who started more than four previous businesses The other variables are self-explanatory. For example: − Female: the percentage of small business owners in a state that are female − Age<25: the percentage of small business owners in a state that are less than 25 years of age Independent: the percentage of small business owners who are “Independent” in their political view − No Highschool: the percentage of small business owners in a state who did not attend high school − Asian: the percentage of small business owners in a state that are “Asian” For each owner characteristic variable (i.e. their position in their company, their previous entrepreneurship experience, their gender, age, political view, education, and race), we compute the percentage values for each state. For example, in Oregon, what percentage is female? If twenty percent of the small business owners are female, Oregon’s female score is 20. Therefore, each state in the survey has a percentage value for each of these variables. There are 41 states in our sample (we eliminated the states with insufficient data). These states are Alabama, Arizona, Arkansas, California, Colorado, Connecticut, Florida, Georgia, Hacwaii, Idaho, 48 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Utah, Virginia, Washington, and Wisconsin. Wyoming, West Virginia, and Mississippi have the smallest number of respondents and California has the greatest number of respondents. Table 1 shows the summary statistics for variables related to “Primary Employment”, “Current Position”, and “Experience”. All of the variables are in percentage per state. As we can see in the table, the median value of “Percentageofprimaryemployment” across all states is 72.83. This means that, in the median state, 72.83% of entrepreneurs have their business as their primary job. For “Current Position”, we have four variables. These are “Managerbutnotowner”, “Nonmanageremployee”, “Ownerandmanager”, and “Ownerbutnotmanager”. As we can see in the table, the median values of these variables across all states are 3.25%, 0.41%, 94.59%, and 2.01%, respectively. These values indicate that, in the median state, 3.25% of the respondents are manager but not owner of the firm, 0.41% are nonmanager employee, 94.59% are owner and manager, and 2.01% are owner but not manager. Table 1: Primary Employment, Current Position, and Experience Variable N Mean Median Stdev Min Max Percentageofprimaryemp 41 71.96 72.83 6.44 52.63 84.21 Managerbutnotowner 41 3.39 3.25 1.87 0.00 8.33 Nonmanageremployee 41 0.53 0.41 0.72 0.00 3.23 Ownerandmanager 41 94.02 94.59 2.80 86.11 100.00 Ownerbutnotmanager 41 2.05 2.01 1.80 0.00 8.33 Previousentre 41 43.84 43.33 6.78 29.49 57.14 Previousstartups1 41 44.74 44.64 12.08 16.67 100.00 Previousstartups2 41 30.53 31.51 8.03 0.00 41.67 Previousstartups3 41 15.10 14.68 7.42 0.00 33.33 Previousstartups4 41 4.18 4.42 3.63 0.00 14.29 Previousstartups>4 41 5.45 4.76 4.54 0.00 21.43 Note: All variables are in percentage. Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 49 For “Experience”, we have six variables. These are “Previousentre”, “Previousstartups1”, “Previousstartups2”, “Previousstartups3”, “Previousstartups4”, and “Previousstartups>4”. The definitions of these variables are provided above. As we can see in the table, the median values of these variables across all states are 43.33%, 44.64%, 31.51%, 14.68%, 4.42%, and 4.76%, respectively. As mentioned above, we first find each of these variables for each state and then we find the mean and the median values for all states. Table 2: Owner Characteristics Variable Mean Median Stdev Min Max Female 37.00 36.96 5.96 21.05 52.94 Age<25 2.09 2.18 1.67 0.00 8.70 Age25-34 18.72 19.21 5.14 5.26 35.48 Age35-44 24.27 25.32 3.98 14.29 31.82 Age45-54 28.18 28.46 5.88 10.00 46.67 Age55-64 21.38 20.45 6.32 8.70 42.11 Age>64 5.36 5.71 2.61 0.00 11.43 Independent 30.52 28.85 6.62 21.05 52.63 Otherpolitical 17.43 16.67 4.80 8.33 34.78 Leanconservative 14.51 14.17 4.54 0.00 26.32 Leanliberal 12.84 11.79 5.14 5.06 26.47 Strongconservative 14.86 14.71 6.70 0.00 26.09 Strongliberal 9.84 9.89 3.92 0.00 19.05 No Highschool 0.66 0.00 1.06 0.00 4.35 Highschool 17.18 17.09 4.73 4.76 34.09 Community College 17.99 17.28 6.67 5.26 35.00 Technical College 16.00 14.67 5.09 4.35 26.32 Undergrad 31.51 31.58 8.11 10.00 61.70 Masters 12.88 13.27 4.35 4.26 24.05 Doctoral 3.79 3.64 2.59 0.00 15.79 Asian 1.67 1.12 2.73 0.00 16.67 Otherrace 5.38 4.21 5.34 0.00 26.67 Black 7.36 4.84 7.72 0.00 34.71 Hispanic 4.95 3.85 4.26 0.00 16.16 White 80.63 81.82 11.33 53.33 100.00 Note: All variables are in percentage. 50 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) Table 2 shows the summary statistics for variables related to “Gender”, “Age”, “Political View”, “Education”, and “Race”. Again, all of the variables are in percentage per state. These are the mean and the median values, the standard deviations, the min and the max for each variable for all states. Empirical Results Table 3 shows the results of the Mann-Whitney-Wilcoxon tests that compare survey respondents’ position as well as their experience across high- and low- primary employment states. The table shows the results for the respondents’ current position and the results for their previous entrepreneurship experience. The table shows that small firms in “high primary employment states” tend to be more professionally managed when compared to small firms in “low primary employment states”. While the median percentage of survey respondents that are “Managerbutnotowner” for businesses in “high primary employment states” is 3.62%, the corresponding percentage is only 2.59% in “low primary employment states” (p-value of the difference is 0.0745). This implies that “the separation of ownership and management” is more prevalent in “high primary employment states” (i.e. more professional management). The table also shows that the median percentage of survey respondents that are “Ownerandmanager” for businesses in “high primary employment states” is 94.23%, while the corresponding percentage is 94.95% in “low primary employment states” (p-value of the difference is 0.0907). Again, this implies that “the separation of ownership and management” is more prevalent in “high primary employment states” (i.e. more professional management) because there are fewer owner-managers. The table shows that the owners in “high primary employment states” tend to be significantly more experienced when compared to the owners in “low primary employment states”. While the median percentage of survey respondents that have previous entrepreneurship experience is 45.01% in “high primary employment states”, the corresponding percentage is only 40.68% in “low primary employment states” (p-value of the difference is 0.0275). Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 51 Table 3: Current Position and Experience across High- and Low-Score States High-Score Low-Score Mann-W. Variable Mean Med. Mean Med. p-value Managerbutnotowner 3.72 3.62 2.93 2.59 *0.0745 Nonmanageremployee 0.45 0.40 0.65 0.43 0.4172 Ownerandmanager 93.65 94.23 94.54 94.95 *0.0907 Ownerbutnotmanager 2.18 2.18 1.87 1.63 0.2703 Previousentre 45.46 45.01 41.56 40.68 **0.0275 Previousstartups1 41.97 43.30 48.66 47.71 *0.0864 Previousstartups2 31.35 31.49 29.36 31.82 0.3654 Previousstartups3 16.58 15.24 13.02 14.29 0.1067 Previousstartups4 3.91 4.11 4.56 4.76 0.4786 Previousstartups>4 6.19 6.07 4.41 3.57 **0.0337 Note: *** shows significance at 1%, ** at 5%, and * at 10% level. The table also shows that a significantly higher percentage of owners started more than four businesses in the past in “high primary employment states” when compared to “low primary employment states”. While the median percentage of survey respondents that started more than four businesses in the past is 6.07% in “high primary employment states”, the corresponding percentage is only 3.57% in “low primary employment states” (p-value of the difference is 0.0337). On the other hand, owners with little experience (i.e. just one previous startup experience) are more prevalent in “low primary employment states”. While the median percentage of survey respondents that started only one business in the past is 43.30% in “high primary employment states”, the corresponding percentage is 47.71% in “low primary employment states” (p-value of the difference is 0.0864). So, we can conclude that more experienced entrepreneurs are more concentrated in “high primary employment states”, while entrepreneurs with little or no experience are more concentrated in “low primary employment states”. Table 4 shows the results of the Mann-Whitney-Wilcoxon tests that compare survey respondents’ gender, age, political view, education, and race across high- and low- primary employment states. When we look at the table for gender, age, political view, and education, we do not see any significant difference between high- and low- primary employment states. 52 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) Therefore, we conclude that these owner characteristics do not differ across high- and low- primary employment states. The table, on the other hand, shows that there are fewer “white” owners in “high primary employment states” when compared to “low primary employment states”. While the median percentage of survey respondents that are “White” in “high primary employment states” is 78.28%, the corresponding percentage is 86.96% in “low primary employment states” (p-value of the difference is 0.0136). The table also shows that there are more owners that are from “Other races” (i.e. other than Asian, Black, Hispanic, or White) in “high primary employment states” when compared to “low primary employment states”. While the median percentage of survey respondents that are from “Otherrace” in “high primary employment states” is 5.01%, the corresponding percentage is 3.85% in “low primary employment states” (p- value of the difference is 0.0318). The table shows that there is no significant difference between the two groups in terms of the percentages of Asian, Black, and Hispanic owners. From Table 4, we can conclude that only some of the race groups are significantly different across the two groups of states. Table 4: Comparison of Owner Characteristics Variable High-Score Low-Score Mann-W. Mean Med. Mean Med. p-value Female 36.47 36.79 37.76 38.64 0.2060 Age<25 1.85 2.16 2.44 2.27 0.2747 Age25-34 17.96 18.97 19.81 19.29 0.2714 Age35-44 24.40 25.11 24.07 25.32 0.3506 Age45-54 28.49 28.14 27.75 29.55 0.3654 Age55-64 22.05 20.36 20.43 20.45 0.3704 Age>64 5.25 5.82 5.50 5.45 0.4110 Independent 30.08 28.14 31.13 29.49 0.1360 Otherpolitical 17.58 17.61 17.22 15.45 0.1806 Leanconservative 14.61 14.12 14.37 14.71 0.4059 Leanliberal 12.02 10.68 14.01 13.64 0.1419 Strongconservative 15.30 15.07 14.25 13.64 0.2892 Strongliberal 10.41 10.57 9.03 8.73 0.1949 No Highschool 0.70 0.39 0.62 0.00 0.1431 Kaya, H.D., Small Firm Owner Characteristics, JWE (2017, No. 1-2, 40-55) 53 Variable High-Score Low-Score Mann-W. Mean Med. Mean Med. p-value Highschool 16.29 16.18 18.44 17.74 0.1479 Community College 17.84 18.55 18.19 17.28 0.4421 Technical College 16.47 14.86 15.33 14.29 0.2937 Undergrad 32.54 32.24 30.05 30.19 0.1637 Masters 12.02 12.71 14.08 14.91 0.1020 Doctoral 4.14 3.70 3.29 3.52 0.2293 Asian 2.08 1.16 1.10 0.00 0.1312 Otherrace 6.29 5.01 4.09 3.85 **0.0318 Black 8.56 5.16 5.68 3.85 0.1634 Hispanic 5.70 4.16 3.89 3.23 0.1735 White 77.37 78.28 85.23 86.96 **0.0136 Note: *** shows significance at 1%, ** at 5%, and * at 10% level. Conclusion In this study, we examine the relation between small business owners’ characteristics and their tendency of having their business as their “primary employment”. In order to achieve that objective, we compare owner characteristics in high “primary employment” U.S. states versus in low “primary employment” states. In our analysis, we use the “United States Small Business Friendliness Survey” done by Kauffman Foundation and Thumptack.com in 2013. This survey asks small business owners about whether their business is their “primary employment”. It also asks them about their position in their company, their previous entrepreneurship experience, their gender, age, political view, education, and race. First, we divide the U.S. states into two groups. The first group includes the states that have high “primary employment” (i.e. the states where relatively high percentage of owners have their business as their “primary employment”). The second group includes the states that have low “primary employment” (i.e. the states where relatively low percentage of owners have their business as their “primary employment”). Our nonparametric tests show that in the states where relatively high percentage of owners have their business as “primary employment” (i.e. “high primary employment states”), owners run their business in a more 54 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 40-55) professional way (i.e. relatively more owners hire managers to run their business). We also find that, in these states, owners have significantly more previous startup experience. In addition to these findings, we also find that, in these states, there are fewer “White” owners and significantly more owners from other races (i.e. races other than “Asian”, “Black”, “Hispanic”, or “White”. On the other hand, our findings show that there is no significant difference between owner’s gender, age, political view, and education across high and low primary employment states. We advise policymakers to use these findings when formulating policies that support entrepreneurship. Business owners’ characteristics are different in many ways in “high primary employment states” versus in “low primary employment states”. In order to promote a stronger form of entrepreneurship (i.e. business as “primary employment”), policymakers need to focus their support on potential entrepreneurs with certain characteristics (i.e. potential entrepreneurs with more previous entrepreneurship experience and potential entrepreneurs from other races). References [1] Anwar, Naveed, and Elizabeth Daniel. 2016. "The Role of Entrepreneur- Venture Fit in Online Home-based Entrepreneurship: A Systematic Literature Review." Journal of Enterprising Culture. [2] Block, Jörn H., and Andreas Landgraf. 2016. "Transition from part-time entrepreneurship to full-time entrepreneurship: the role of financial and non- financial motives." International Entrepreneurship and Management Journal, 12(1): 259-282. [3] Cagetti, Marco, and Mariacristina De Nardi. 2006. 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