Thai entrepreneurs: an empirical investigation of individual differences, background and scanning behavior.

Box, Thomas M. ; Beisel, John L. ; Watts, Larry R. 等

INTRODUCTION

Thailand, a country of approximately 60 million people, is roughly the size of the state of Texas. It is properly classified as a newly industrialized country (NIC) with significant natural resources. Thailand's economy is dynamic with a Gross Domestic Product of $323 billion and a 7.8% growth rate in 1993. The trade and current account deficits have fallen and the bulk of recent imports has been capital equipment--suggesting an economy poised for further growth (National Trade Data Bank, 1994).

The economic "jewel" in Thailand's crown is the capital city of Bangkok with a population of more than 6 million. Although traffic and air pollution problems abound and the government is still recovering from a military coup four years ago, Bangkok is home to a large and growing number of very successful entrepreneurs. This concentration of entrepreneurs is undoubtedly a factor in the recent rapid growth of the economy (Janssen, 1993; National Trade Data Bank, 1994).

The purpose of this study, perhaps one of the first on-site studies of Thai entrepreneurs, was to attempt to understand how individual differences, background characteristics and scanning behaviors of the entrepreneurs might be related to the performance of their firms. The potential correlates of firm performance were those that have been found to be related to entrepreneurial firm performance in the United States and Canada (Box, Watts, & Hisrich, 1994; Blake and Box, 1994).

BACKGROUND

Need for Achievement (NACH) (McClelland, 1961) and Locus of Control (LoC) (Rotter, 1966) are both individual difference measures that have been frequently used in the studies of entrepreneurial activity (Vesper, 1990). McClelland (1961) found that successful entrepreneurs, in India, had higher NACH scores than less successful entrepreneurs. Box, White and Barr (1993) determined that NACH of the entrepreneur correlated positively, but not significantly, with firm performance. Miller and Droege (1986) found that a CEO's NACH was significantly related to various measures of firm structure, and thereby perhaps related indirectly to firm performance.

Entrepreneurs' and CEOs' LOC has been shown to be related to firm performance (Box, White & Barr, 1993; Govindarajan, 1988; Miller & Toulouse, 1986; Miller, Kets de Vries & Toulouse, 1982). An individual with a "low" LOC score is one who attributes personal success to his or her own efforts and performance. The low LOC individual is described by Rotter (1966) as an "internal." On the other hand, an individual with a "high" LOC score is deemed to be an "external." Externals are those individuals who attribute success and failure to extrinsic events and luck. Successful entrepreneurs tend to score low on the LOC instruments and are thus internals.

Entrepreneurial backgrounds have been extensively studied. The essential thesis in most of this research is that successful entrepreneurs may have common backgrounds with regard to such things as previous start-ups, industry experience levels, experience as part of an entrepreneurial firm's top management team, age, and education. For example, Ronstadt (1988) discovered that entrepreneurs who had previous start-up experience were more satisfied and successful than those in their first venture. Box, Watts and Hisrich (1994) and Box, White and Barr (1993) found that the entrepreneur's years of prior experience in the industry was positively correlated with firm performance. Age and years of formal education have also been shown to correlate positively with entrepreneurial firm performance (Birley & Norburn, 1987; Hisrich & Brush, 1984; Hoad & Rosko, 1964). Finally, environmental scanning intensity has been found to positively correlate with firm performance (Daft, Sormunen & Park, 1988; Watts & Ormsby, 1990).

The literature suggests that NACH and LOC (of the entrepreneur) may be related to firm performance. NACH would be positively correlated and LOC would be negatively correlated if LOC was measured so that "internals" scored low on the instrument. Number of previous start-ups, number of years as a member of an entrepreneurial firm's top management team, prior industry experience, age at founding, years of formal education and intensity of environmental scanning should all be positively correlated with entrepreneurial firm performance.

H1: The entrepreneur's NACH is positively correlated with firm performance.

H2: The entrepreneur's LOC is negatively correlated with firm performance when LOC is measured such that an internal orientation is "low".

H3: The entrepreneur's number of years as a member of an entrepreneurial firm's top management team is positively correlated with firm performance.

H4: The entrepreneur's number of previous start-ups is positively correlated with firm performance.

H5: The entrepreneur's years of prior experience in the firm's industry is positively correlated with firm performance.

H6: The entrepreneur's age at founding is positively correlated with firm performance.

H7: The entrepreneur's years of formal education is positively correlated with firm performance.

H8: The entrepreneur's environmental scanning intensity is positively correlated with firm performance.

RESEARCH METHODOLOGY

The research methodology will be discussed in terms of sample design, variables tested and data analysis employed. Data were collected from a sample of 191 entrepreneurs in Bangkok, Thailand during the Fall of 1994. Entrepreneurs were defined as founders of independently-owned firms that had been in business ten years or less. The survey form, translated and back-translated in Thai, was based on a survey used in two previous studies of American entrepreneurs (Box, Watts & Hisrich, 1994; Box, White & Barr, 1993). The survey forms were distributed and administered by M.B.A. students at Assumption University in Bangkok under the direction of one of the authors. Of the 191 survey forms collected, 187 were usable, a ninety-eight percent response rate. This extraordinarily high response rate was as a result of the fact that the entrepreneurs surveyed were family members or close personal friends of the students conducting the survey.

The entrepreneurs responding to the survey represented a wide sample of SIC code industries and divisions (Standard Industrial Classification Manual, 1988). Of the business divisions listed in the Standard Industrial Classification code, only Business Division B (Mining) was not represented in the sample. The largest percentage (72%) of firms were involved in manufacturing (134 out of 187). A complete breakdown of classifications in shown in Table 1.

As Cameron and Whetten (1983) note, the construct space for organizational effectiveness is unbounded. There is "no single, unambiguous meaning of the construct ...". In this research, it was decided to use three related, but not multicollinear, definitions of effectiveness as dependent variables: average annual increase in employment (EMPGRO), average annual increase in revenue (REVGRO) and average annual increase in profit (PROFGRO). EMPGRO was calculated by subtracting the number of employees on the payroll in the first year of operations from the number on the payroll in 1994 and dividing by the number of years of operations. REVGRO and PROFGRO were calculated in similar fashion for growth in revenue and growth in profit.

Independent variables, as previously noted, included Need for Achievement (NACH), Locus of Control (LOC), the entrepreneur's years as a member of an entrepreneurial firm's top management team (PREEXPR), entrepreneur's number of previous start-ups (PRESTRTS), entrepreneur's years of industry experience before start-up (INDEXP), entrepreneur's age at founding (AGE), entrepreneur's years of formal education (EDUC), and the entrepreneur's environmental scanning intensity (SCAN). Need for Achievement (NACH) was operationalized using Steers and Braunstein's (1981) Manifest Needs Questionnaire. This instrument is Likert-scaled with a theoretical range of one (1) to seven (7). LOC was measured using Lumpkin's (1985) abbreviated LOC questionnaire. This instrument is also a seven-point Likert scale.

PREEXPR, PRESTRTS, INDEXP, AGE, and EDUC were self-report measures. Environmental scanning (SCAN) was assessed using an instrument devised by Miller, Kets de Vries, and Toulouse (1982) with a seven-point Likert scale. Descriptive statistics, including means, standard deviations and ranges for all variables are shown here in Table 2.

Reflecting the difficulties involved with single measures of performance, it was decided to use the following scheme for testing the proposed hypotheses. If an independent variable correlated significantly with all three dependent variables, that hypothesis would be considered to have "strong support." With two variables significantly correlated, the hypothesis would be "supported." With one variable significantly correlated, the hypothesis would be "weakly supported." Correlations, shown in Table 3, were calculated using Pearson product moment correlations.

RESULTS

Based on the correlations (Table 3) we see that neither NACH nor LOC correlate significantly with any of the three measures of performance. Thus we reject both HI and H2. Despite some prior evidence that INDEXP and EDUC (Box, Watts, & Hisrich, 1994) correlate with entrepreneurial firm performance, such was not the case in this research . Thus H5 and H7 are rejected.

Previous experience as a member of an entrepreneurial management team (PREEXPR) correlated positively with EMPGRO (r=.195, p=.01) and REVGRO (r=.245, p=.003). H3 is supported. H4 is weakly supported as PRESTRTS is positively correlated with REVGRO (r=.141, p=.091). AGE was positively correlated with EMPGRO (r=.186, P=.014) and REVGRO (r=.174, p=.037), while SCAN was positively correlated with REVGRO (r=.213, p=.010) and PROFGRO (r=.175, p=.041) thus we have confirmation that H6 and H8 are supported.

DISCUSSION

In summary, we see that Thai entrepreneurs are similar, but certainly not identical to American and Canadian entrepreneurs. One of the more interesting findings, in the negative sense, was that there appeared to be no correlation between firm performance and the individual differences of Thai entrepreneurs. Granted, research findings in the area of LOC and NACH have been mixed (Box, Watts, & Hisrich, 1994; Brockhaus, 1982; Gartner, 1985). Nonetheless, in this study it is possible that the lack of significance, despite the fact that the signs are in the hypothesized direction, may simply be the result of range restriction (in that the standard deviations are relatively small compared to the means). An alternative explanation is that Thais are very homogenous (culturally) whether or not they are involved in entrepreneurial activities.

Previous experience as a member of an entrepreneurial management team, number of previous starts, age and scanning intensity are positively correlated with firm performance and these findings are consistent with a number of previous studies of American and Canadian entrepreneurs. This study has achieved its initial purpose of beginning to understand the Thai entrepreneur. The importance of this understanding is a reflection of the growing economic importance of Thailand in Southeast Asia. Thailand has the potential to eventually become one of the Asian "Baby Tigers." We believe that future research in this area might profitably consider other elements of the Thai entrepreneur's psychological make-up (i.e. his/her individual differences). Also studies that controlled for industry and were more longitudinal in nature would be useful enhancements.

REFERENCES

Birley, S., & Norburn, D. (1987). Owners and managers: The Venture 100 vs the Fortune 500. Journal of Business Venturing, 2, 351-363.

Blake, C.G., & Box, T.M. (1994). Manufacturing entrepreneurs in Mississauga, Ontario: An empirical investigation of firm performance. Journal of Small Business and Entrepreneurship, 11(4), 85-92.

Box, T.M., Watts, L.R., & Hisrich, R.D. (1994). Manufacturing entrepreneurs: An empirical study of the correlates of employment growth in the Tulsa MSA and rural East Texas. Journal of Business Venturing, 9(3), 261-270.

Box, T.M., White, M.A., & Barr, S.H. (1993). A contingency model of new manufacturing firm performance. Entrepreneurship Theory and Practice, 18(2), 31-46.

Brockhaus, R.H. (1982). The psychology of the entrepreneur. In C.L. Kent, D.L. Sexton, & K.N. Vesper, (Eds.), Encyclopedia of entrepreneurship. Englewood Cliffs, NJ: Prentice Hall, 39-57.

Cameron, K.S., & Whetten, D.A. (1983). Organizational effectiveness: A comparison of multiple models. New York: Academic Press.

Daft, R.L., Sormunen, J., & Park, D. (1988). Chief executive scanning, environmental characteristics, and company performance: An empirical study. Strategic Management Journal, 9, 123-139.

Gartner, W.B. (1988). "Who is an entrepreneur?" is the wrong question. American Journal of Small Business, 12(4), 11-32.

Govindarajan, V. (1988). A contingency approach to strategy implementation at the business-unit level: Integrating administrative mechanisms. Academy of Management Journal, 31, 828-853.

Hisrich, R.D., & Brush, C.G. (1984). The women entrepreneur: Management skills and business problems. Journal of Small Business Management. January, 30-37.

Hoad, W.M., & Rosko. P. (1964). Management factors contributing to the success or failure of new, small manufacturers. Ann Arbor, MI: Bureau of Business Research.

Jensen, P. (1993, October). Wheel in the entrepreneurs. Asian Business, p. 76.

Lumpkin, J.R. (1985). Validity of a brief locus of control scale for survey research. Psychological Reports, 57, 655-659.

McClelland, D.C. (1961). The Achieving Society, New York: Free Press.

Miller, D., & Droege, C. (1986). Psychological and traditional determinants of structure. Administrative Science Quarterly, 31, 539-560.

Miller, D., & Toulouse, J.M. (1986). Chief executive personality and corporate structure in small firms. Management Science, 32, 1389-1409.

Miller, D., Kets de Vries, M., & Toulouse, J.M. (1982). Top executive locus of control and its relationship to strategy-making, structure and environment. Academy of Management Journal, 25, 237-253.

National Trade Data Bank (1994). Thailand [Machine-readable data file]. Washington, DC: (Central Intelligence Agency Report No. CI WOFACT WO0233).

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Thomas M. Box, Pittsburg State University

John L. Beisel, Pittsburg State University

Larry R. Watts, Stephen F. Austin State University

TABLE 1
INDUSTRY DIVISIONS

DIVISION DESCRIPTION NUMBER OF FIRMS

 A Agriculture, Forestry and Fishing 4
 C Construction 4
 D Manufacturing 138
 E Transportation 2
 F Wholesale Trade 5
 G Retail Trade 7
 H Finance, Insurance & Real Estate 10
 I Services 21

TABLE 2
VARIABLES AND SELECTED VARIABLE VALUES

 STANDARD
VARIABLE MEAN DEVIATION RANGE

EMPGRO (1) 18.46 36.78 -32.5 to 260
REVGRO (2) 685 1610 -267 to11,040
PROFGRO (2) 105.6 322.2 -80 to 3,150
PRESTRTS 2.433 6.427 0 to 45
PREEXPR (3) 4.706 6.707 0 to 34
AGE (3) 38.267 9.729 21 to 78
EDUC (3) 13.888 3.359 1 to 18
INDEXP (3) 7.47 7.732 0 to 50
NACH 5.646 0.821 3.4 to 7.0
LOC 3.349 0.780 1.7 to 6.0
SCAN 4.275 1.291 1.0 to 7.0

(1) Number of employees/year

(2) $1000/year (Thai Bahts converted to American Dollars)

(3) Years

TABLE 3
PEARSON CORRELATIONS

Hypothesis Variable EMPGRO REVGRO PROFGRO

 H1 NACH .078 .006 .021
 H2 LOC -.050 -.039 .016
 H3 PREEXPR .194 *** .245 *** .102
 H4 PRESTRTS .120 .141 * .082
 H5 INDEXP .011 -.012 .033
 H6 AGE .186 ** .174 ** .093
 H7 EDUC - .015 .000 -.110
 H8 SCAN .080 .213 *** .175 ***

* = p < .10

** = p < .05

*** = p < .01