T STRATEGY A MODEL OF POTENTIAL ENTREPRENEURSHIP: PROFILES AND EDUCATIONAL IMPLICATIONS James W. Carland JoAnn C. Carland Western Carolina University ABSTRACT ln an effort to determine the propensity for entrepreneurship of potential entrepreneurs, students enrolledin Small Business Management classes at the graduate and undergraduate level were examined. A series of surveys including Jackson's Personality Inventory for Innovation and Risk Taking, and Jackson 's PRF for Need for Achievement as well as the Carland Entrepreneurship Index were completed The results supported the empimcal developmentofa model ofpotentialentrepreneurship That model was testedPom theoretica( statisti cal and visual perspectives. Finally, the model was used to develop implications for entrepreneurship education INTRODUCTION Who is an entrepreneur? How does one draw the lines? How does one give distinction to the profile? Such are the questions which are being asked by the researchers. When surveying the literature, the term entrepreneur is ubiquitous. It describes individuals who own businesses of every shape and size. It is used in the literature of small business and in the literature of large corporations. How can such diversity describe, detail or delineate the true entrepreneur? Is s/he male or female, black or white or brown? Is s/he found in the halls of CorporateAmericaor in the corner hardware store? What is it that researchers and educators are seeking and how can it be defined? DEFINITIONS OF ENTREPRENEUR ln the United States, Ely (1912) was one of the first to explain the term, entrepreneur. Interestingly, El y (1912)explained that economists were forced to choose a term, entrepreneur, from the French language because the earlier terms dealing with individuals who started businesses had become corrupted. These earlier terms included undertaker, which Ely explained had been appropriated by a single group of business owners, and adventurer which had come to imply a level of rashness which was undesirable (Ely, 1912). Schumpeter(1934) credited Mill (1848) with bringing the term, entrepreneurship, into general use among economists. Mill (1848) believed that the key factor in distinguishing a manager from an entrepreneur was the bearing of risk. The idea of risk bearing has been I I integral as far back as Cantillon, circa 1700, who described an entrepreneur as a rational decision maker who assumes the risk and manages the finn (Kilby, 1971). Perhaps the most important aspect of entrepreneurship from a societal perspective is innovation (Brockhaus, 1982). McClelland (1961) was a champion of that concept. Drucker (1985) posits that entrepreneurship is innovation in a business setting. ENTREPRENEURSHIP EDUCATION For some time researchers have looked to education as the means to spur entrepreneur id activity. Entrepreneurshipand small business classes are gaining popularity in many large and regional institutions today, often with high enrollments. After all, is not starting one's own business the American Dream? Entrepreneurial education and student potential for entrepreneurial activities have been examined by such authors as Birley, Gross, & Saunders (1986);Hills & Welsch (1986);Miller(1987); Sexton & Bowman(1983, 1984, 1986); Barbato & Durlabhji (1989); Solomon & Fernald (1990);and Robinson, Huefner, & Hunt (1991). Various instruments and hypotheses have been tested and the results have varied greatly. Many authors have created their own instruments(e.g., Sexton & Bowman, 1983, 1984, 1986; Robinson, Huefner, & Hunt, 1991; Carland, Carland & Hoy, 1992) and others have used existing instruments to test their theories (e.g., Hoy & Boulton, 1983; Solomon & Fernald, 1990; Barbato & Durlabhji, 1989). Yet because of the various methodologies, different instruments and samples used, there is no universal portrait of an entrepreneur, much less a profile of potential entrepreneurs. It has long been established that owners of small businesses are not homogeneous and yet terms for various sets of owners are used interchangeably. Many definitions have been posited but none seems comfortable enough to most entrepreneurship researchers to become generally accepted. Some seem to follow the more generic approach of identifying anyone who starts a business (Gartner, 1988) or more than one business (Robinson et al., 1991)as an entrepreneur. Others tend to follow the more di fferentiatingapproach posited by Carland, Hoy, Boulton and Carland (1984) which suggests that small business owners are more family oriented in their focus and entrepreneurs are more growth and profit oriented in their perceptions. Still others posit a series of different groups of business owners, each of whom displays unique characteristics (Vesper, 1990). Nevertheless, there has been no clear cut distinction or definition universally accepted in the literature. Process versus behavior arguments still rage as to what initiates the starting of a business and determ ines an entrepreneur. The process of opening one's doors (Gartner, 1988)or making the first sale (Gatewood, Shaver and Gartner, 1992) are argued by some as the only viable definition of entrepreneurship without regard to potential for success or goals. Others argue that personality traits have a major impact on the process (Carland, Hoy & Carland, 1988). There have been empirical studies which imply that the process of launching a business and the personality traits which drive that process are inextricably entwined (Carland, Carland & Dye, 1991). The search continues. 2 - r ltr, n,i"'i '- ~,.I t METHODOL'OGY OF THE RESEARCH Two groups of students enrolled in Small Business classes at a regional university in the southeast at the graduate (N = 55) and undergraduate levels (N = 50) were surveyed to determine their propensity for entrepreneurship. Since the courses were elective in nature, the inference was that an interest in the subject existed. Several survey instruments were administered to the students over the period of the semester. The survey results were examined empirically and the insights which the analysis provided were utilized to develop a model of potential entrepreneurshi pand to draw conclusions with regard to the educational implications inherent in the model. Several instruments were employed with establishedreliability and validity to determine the level of entrepreneurial drive and other key characteristics displayed by students. The purpose was to attempt to draw a profile of potential entrepreneurs. The instruments measured the need for achievement, preference for innovation, risk taking propensity and entre preneurid drive. The Achievement Scale of the Personality Research Form (Jackson, 1974) was used to measure the need for achievement. Jackson (1974) reported that the test-retest reliability (N=135) was .80. and odd-even reliability (N=192) was reported to be .77. Jackson and Guthrie(1968), testing for validity, reported correlations with self ratings and peer ratings of .65 and .46, respectively. These findings support the conclusion that the instrument contains convergent and discriminant validity. Risk taking propensity was measured using the Risk Taking Scale of the Jackson Personality Inventory (Jackson, 1976). For risk taking propensity, Jackson (1976) tested the internal consistency reliability with two samples (N=82 and N=307), and reported values of .93 and .91 using Bentler's coefticient theta, and .81 and .84 using coefficient alpha. Testing for validity(N=70), Jackson(1976) reported correlations with the completion ofan adjective checklist, with self rating and peer rating of .75, .77, and .20 respectively. Innovation was measured using the Innovation Scale of the Jackson Personality Inventory (Jackson, 1976). The internal consistency reliability of the Innovation Scale produced values of .94 and .93 using Bentler's coefficient theta, and .83 and .87 using coefficient alpha. Validity was checked using the completion of an adjective checklist, with self rating, and peer rating of .79, .73, and .37, respectively. Reliability for the instruments pertaining to risk taking propensity, preference for innovation, and need for achievement were analyzed in a study by Stewart, Carland and Carland (1996) using Cronbach's Alpha. The alphas were .76, .77. and .72, respectively. These scores suggested that the instrument accurately measured the above characteristics, and that the individual items on the test produced comparable patterns of responses over all cases. 'fhe Entrepreneurship Index administered in the research is the 33 item forced choice form of the Carland Entrepreneurship Index. The Index measures the strength of an individual's entrepreneurial drive and it was shown to have high validity and reliability in a 3 I variety of statistical evaluations(Carland, Carland & I-loy, 1992). In a sample of 209 business owners, the Index produced split-half, odd-even reliability of .73. The Index also produced a Kuder-Richardsonor Cronbach Alpha score of.73. With dichotomous questions, the Kuder- Richardson produces the same score as the Cronbach Alpha test for validity (Bruning and Kintz, 1987). A reliability coefficient of.70 or higher means that the test was accumtely measuring some characteristic of the people taking it and that the individual items in the test were producing similar patterns of response in different people. The statistics of .73 indicate that the Indexproducesvalidresults(Bruningd'c Kintz,1987). In atest retestcorrelationusing 40 business owners retested at least two months aAer the original test date, there was a statisticallysignificantcorrelationof.80 indicating that the index was consistent over time in producing unique scores for respondents. ANALYSIS OF THE DATA The followingtabledisplaysthe make up of the sample by academic level and sex. As the table indicates, the 105 respondents were almost evenly divided between graduate and undergraduate students, although there were more females than males in the graduate group. Undergraduate Graduate Total Male 24 16 40 Female 26 39 65 Total 50 55 105 The first step in the analysis was an examination of correlationsamong the scores on the various instruments. A Pearson correlation was conducted on the scores for the need for achievement (ACH), preference for innovation (INN), and risk taking propensity (RISK) instruments, and the Carland Entrepreneurship Index (CEI). The results are displayed in the following exhibit. PEARSON CORRELATION MATRIX AC H INN RISK CE I Need for Achievement 1.000 Preference for Innovation 0.274 1.000 Risk Taking Propensity 0.325 0.374 1.000 Carland Entrepreneurship Index 0.451 0.439 0.492 1.000 PROBABILITIES ACH INN RISK CEI Need for Achievement .000 Preference for Innovation .005 .000 Risk Taking Propensity .001 .000 .000 Carland Entrepreneurship Index .000 .000 .000 .000 4 9'in i As the exhibit shows, there is a significant relationship between the scores on all of the instruments. The highest correlations are between scores on the CEI and the scores on the other instruments. 'fhe correlation analysis suggests that there is a potential for the development of a model of entrepreneurial drive, as measured by the CEI, among these potential entrepreneurs. To that end, the relationships between instrument scores were examined in more detail. First, the direction of the relationships between the CEI and the other scores was determined. The researchersemployed the quadratic smoothing technique (Wilkenson. 1990) in preparation of a graph ofentrepreneurialdrive as a function of the need for achievement. The graph showed an upward sloping line of best fit, supporting the existence of an appropriate relationship. The quadratic smoothing analysis was repeated with entrepreneurial drive as a function of risk taking. Again, the trend line supported the existence of an appropriate relationship. Finally, entrepreneurial drive as a function of the preference for innovation was examined. That graph also supported additional analysis. Noting that the graphical analyses and quadratic smoothing techniques supported appropriate relationships between entrepreneurial drive and the other characteristics, group diversity and its potential impact on the data were considered. First, there was an investigation of whether the involvement of both undergraduate and graduate students in the data set has any influence on the relationships among the variables. To consider this question, a group of independent t tests were performed. First, t-tests were calculated on the CEI, Risk, Innovation and Achievement scores grouped by status of the respondent: undergraduate or graduate student. The results are displayed in the following exhibit. T-TESTS BETWEEN GRADUATE AND UNDERGRADUATE STUDENTS Carland Entrepreneurship Index Group N Mean SD T p Graduate Students 55 21.273 4.057 2.047 .043 Undergraduate Students 50 19.440 5.011 Preference for Innovation Group N Mean SD T p Graduate Students 55 13.709 4.545 1.404 .164 Undergraduate Students 50 12.327 5.398 Need for Achievement Group N Mean SD T p Graduate Students 55 11 545 2 911 I 601 .113 Undergraduate Students 50 10.571 3.253 Risk Taking Propensity Group N Mean SD T p Graduate Students 55 11.655 4.904 1.046 .298 Undergraduate Students 50 10.592 5.400 5 I 'fhe exhibit shows that there were differences in entrepreneurial drive as measured by the CEI between the two groups, but there were no difTerences in the other instrument scores. Graduate students displayed stronger entrepreneurial drive, as measured by the CEI, than undergraduate students. Clearly, there are characteristics displayed by the graduate students in this study which influence the index. These factors do not include the need for achievement, preference for innovation, or risk taking propensity. This suggeststhat any model which might evolve will be underdefined. Nevertheless given the fact that academic standing had no effect on the key variables of innovation, risk and achievement, the possibilityofa model employing those factors as predictors of entrepreneurship can be investigated. Next, an investigation of sex was considered as a factor in the model. Again, t-tests were conducted, this time between males and females. The results are displayed below. T-TESTS BETWEEN MALE AND FEMALE STUDENTS Carland Entrepreneurship Index Group N Mean SD T p Males 65 21.369 3.955 2.666 .010 Females 40 18.825 5.178 Preference for Innovation Group N Mean SD T p Males 65 14.531 3.932 3.777 .000 Females 40 10.700 5.612 Need for Achievement Group N Mean SD T p Males 65 11.516 2.600 1.667 .100 Females 40 10.400 3.699 Risk Taking Propensity Group N Mean SD T p Males 65 13.016 4.474 5.151 .000 Females 40 8.175 4.779 As the exhibit reveals, males produced higher scores on entrepreneu rial drive, preference for innovation, and risk taking propensity. This finding suggests that sex may well have a bearing on a model of potential entrepreneurship. Nevertheless, the fact that the females were consistently lower in all three areas in which differences exist, suggests that such differences may not prevent the development of a model. Since the preliminary examination disclosed a strong relationship between entrepreneurial drive and the other three characteristics, the analysis was continued by examining the value of those three factors as predictors of entrepreneurship. To identify relationships in the data, a stepwise regression using the CEI as the dependent variable and 6 preference for innovation, risk taking propensity, and need for achievement as the independent variables was conducted. The results are displayed in the following exhibit. As the exhibit shows, the stepwise regression indicated that al I three factors, innovation, risk and achievement affected entrepreneurial drive as measured by the CEI. The linal R's a respectable 39%. Clearly, the independent variables do not explain entrepreneurial drive fully, but they do contribute to the function in significant ways. STEPWISE REGRESSION ANALYSES Dependent Variable: Entrepreneurial Drive Step ¹ I R Square: 0.242 Variable Coefficient Std Error Std Coef Tolerance F p Risk 0.442 0.078 0.492 . I E+.01 32.558 .000 Step ¹ 2 R Square: .337 Risk 0.347 0.007 0.386 0.89457 20.319 .000 Achievement 0.486 0.128 0.325 0.89457 14.431 .000 Step ¹ 3 R Square: .388 Innovation 0.229 0.229 0.247 0.83434 8.290 .005 Risk 0.277 0.277 0.308 0.80694 12.474 .001 Achievement 0.423 0.423 0.283 0.86750 11.375 .001 In developing any model, it is a valuable exercise to visualize the relationships being proposed. To that end, three dimensional plots of the independent variables against entrepreneurialdrive were drawn. Since one cannot visualize in four dimensions, two sets of analyses were prepared to ensure that all three independent variables were included. To make the data points in three dimensional space more comprehensible, a surface displaying the interaction was constructed. The first construction featured negative expo- nential smoothing which produces a three dimen- sional topographical map (Wilkenson, 1990). The results, dis- .iU played to E 4 the right, g i'sii contrast so risk taking and inno- tit w vation against entrepre- neurial drive. Shading proceeds from lighter shades at lower levels to progressively darker shades at 7 higher levels. The surface suggests that higher levels of risk combined with higher levels of innovation produce higher levels of entrepreneurial drive. The overall shape of the surtace suggests that, although the relationships are not perfect, they generally move in the right directions. A second graph, employing a quadratic smoothing technique, is displayed to the leR. This technique smooths the data into a much Ratter surface (Wilkenson, l990), making the relationships easier to examine visually. This graph shows a remarkably well established relationship. The visual analysis continued, substituting ~p achievement for risk taking in the graph. Using g~ negative exponential smoothing, the resulting sur- face pp shown in ,iii the graph a pp to the right, is not as pp 0 well de- veloped as the earlier zi display. The surface climbs appropriately, but its shape is more rugged. When quadratic smoothing is applied, the result is much more pleasing. The leR graph displays the resulting surface. This surface climbs appropriately to support the existence of a model. T 0 ip complete ~g pp v i s u a 1 P ip analysis, yone must ap contrast achieveme p nt and risk I ccf''', against + entreprene g4 'C urial drive. The right graph displays negative exponential smoothing, while the leR displays quadratic smoothing. The first surface is the most rugged yet, but the leR supports the model. The foregoing visualization suggests that a model of entrepreneurial drive based on achievement, innovation, and risk is a viable prospect. To proceed with construction of the model, the results of the stepwise regression were tested with an analysis of variance on the final regression model. The results, displayed below, show a high probability of the existence 8 I I'i I of a relationship and the R'hows that the model explains 39% of the variance in the CEI score. Further. the individual t tests show that every independent variable is significantly related to the dependent variable. REGRESSION ANALYSIS N= I 05 Dependent Variable: Entrepreneurial Drive R Square: 0.388 Variable Coefficient Std Coef Tolerance T p Constant 9.65 I Error 0.000 . 6.466 .000 Innovation 0.229 I A93 0.247 0.83434 2.879 .005 Risk 0.277 0.229 0.308 0.80694 3.532 .001 Achievement OA23 0.277 0.283 0.86750 3.373 .001 OA23 ANALYSIS OF VARIANCE Source Sum of Squares DF Mean Square F p Regression 854.535 3 284.845 Ratio .000 Residual 1350.686 100 13.507 21.089 The levels of correlation between the independent variables which were discovered by the Pearson correlation suggest that there may be multicollinearity in the model. Consequently. the independent variables were collapsed into a single number by adding the individual scores together, and another analysis was conducted. This process allows one to remove any multicol linearity. The results of this regression are shown in the following exhibit REGRESSION ANAI.YSIS N=105 Dependent Variable: Entrepreneurship Drive R Square: 0.378 Variable Coefficient Std Coef Tolerance T p Constant 10.316 Error 0.000 . 7.452 .000 Inn+Risk+Ac 0.286 1.331 0.615 .I OOE+01 7.880 .000 h 0.036 ANALYSIS OF VARIANCE Source Sum of Squares DF Mean Square F p Regression 834.493 I 834.493 Ratio .000 Residual 1370.729 102 13.439 62.097 As the exhibit reveals, the new regression has a virtually identical R'. but the F ratio for the entire model is much higher, almost three times as high, as for the earlier regression. Further, the t statistic for the combined variable is also much higher, twice as high, as the highest t statistic produced in the previous regression. If multicol linearity exists in the model, it does not aflect the validity of the model, nor does it reduce the proportion of variance which the model explains. 9 Ofcourse,the model is not without problems. First, the R'f the model leaves a great deal of variance in the dependent variable unexplained. Earlier investigations into the diversity of the data set demonstrated that other factors influence entrepreneurial drive. Graduate students in this study displayed higher entrepreneurial drives than undergraduates. That may have been a function of a higher level of self confidence or some other, unknown reason. Males displayed higher entrepreneurial drive, higher preference for innovation, and higher risk taking propensity than females. That may result from cultural or other factors, but it does suggest that sex will play a role in the entrepreneurship model. There may be other limiting factors in the eAicacy of this model. Among these are measurement problems relating to the appropriateness of entrepreneurial drive as a proxy for potential entrepreneurship. CONCLUSIONS AND IMPLICATIONS OF THE RESEARCH In conclusion, the model of potential entrepreneurship developed in this paper paints a valid and useful portrait of the student participants. That model can be expressed as follows: Potential Entrepreneurship = f(Achievement, Innovation, Risk Taking) The Iindings of this study are not generalizable to the greater population of potential entrepreneurs due to sample size and potential sample bias. Nevertheless, the findings show an interesting relationship which merits further study. Using the students in this study, the authors were able to construct a model of potential entrepreneurship which was simultaneously appealing from a classical perspective, from a visual perspective, and from a statistical perspective. This model suggests that potential entrepreneurship as forecast by the strength of one' entrepreneurial drive, is a function of the interaction between the need for achievement, risk taking propensity and preference for innovation. All of these characteristics have strong appeal as classical descriptors of entrepreneurship and they performed well from a statistical and visual perspective. If the results of this investigation are supported by future research, the findings will suggest that need for achievement is a necessary, but not a sufficient requirement to explain entrepreneurship. The same is true for preference for innovation and risk taking potential. In fact, there are other, as yet undisclosed, factors which are necessary but not sufficient in explaining potential entrepreneurship. By far the most valuable implication of this finding has to do with entrepreneurship education. Entrepreneurship students must develop an intrinsic achievement motivation in order to do well. That is well known and is one of the underlying supports for the academic grading system. However, the idea that potential entrepreneurs may display a higher risk taking propensity suggests that educators need to incorporate risk taking into the entrepreneurshipcurriculum. A potential act ofentrepreneurship does not guarantee success. Ifentrepreneu ship students are more prone to risk taking behavior than their counterparts in other majors, we, as educators, must ensure that we impress upon them the need to carefully evaluate entrepreneurial actions. If we teach risk assessment and we emphasize the need for rational and calculated behavior, we may prevent a hasty and ill advised decision in the future. 10 Perhaps the most exciting aspect of the model derived in this study is the role of innovation. Entrepreneurship researchers have long recognized the role of innovation in entrepreneursand entrepremurial acts. This model suggests that the same role exists even in potential entrepreneurs. Further, as educators, we know that techniques for enhancing and cultivating one's creativity and innovative posture are well established. These techniques have been practiced in psychology and education for more than 30 years (ke., Lowenfeld, 1958; Fromm, 1959; Maltzman, 1960; Hallman, 1963; Torrance, 1966; Torrance k Myers, 1970; Parnes, 1 982). Clearly, we need to incorporatecreativity into the entrepreneurshipcurriculunt We can design educational experiences which will help to protect our potential entrepreneursfrom their risk taking propensities. We can also design educational experiences which will help them to enhance their individual creativity. As entrepreneurship educators, we need to invest the time and energy in a personal program of study which will help us to design and implement both types of educational experiences. The former can help protect our students from failure; the latter can help propel our students to success. ll REFERENCES Barbato, RJ. & Durlabhj i, S. 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