31S A8U SMALL BUSINESS OWNER-MANAGERS AND CORPORATE MANAGERS: A COMPARATIVE STUDY OF ACHIEVEMENT MOTIVATION, RISK TAKING PROPENSITY AND PREFERENCE FOR INNOVATION DISSERTATION Presented to the Graduate Council of the University of North Texas in Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY By Wayne H. Stewart, Jr., B.S.B.A., M.B.A. Denton, Texas May, 1995
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31S A8U
SMALL BUSINESS OWNER-MANAGERS AND CORPORATE MANAGERS:
A COMPARATIVE STUDY OF ACHIEVEMENT MOTIVATION,
RISK TAKING PROPENSITY AND PREFERENCE FOR INNOVATION
DISSERTATION
Presented to the Graduate Council of the
University of North Texas in Partial
Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
By
Wayne H. Stewart, Jr., B.S.B.A., M.B.A.
Denton, Texas
May, 1995
31S A8U
SMALL BUSINESS OWNER-MANAGERS AND CORPORATE MANAGERS:
A COMPARATIVE STUDY OF ACHIEVEMENT MOTIVATION,
RISK TAKING PROPENSITY AND PREFERENCE FOR INNOVATION
DISSERTATION
Presented to the Graduate Council of the
University of North Texas in Partial
Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
By
Wayne H. Stewart, Jr., B.S.B.A., M.B.A.
Denton, Texas
May, 1995
WgtjO
Stewart, Wayne H. Jr., Small business owner-managers and
corporate managers: A comparative study of achievement
motivation, risk taking propensity and preference for
innovation. Doctor of Philosophy (Management), May, 1995,
Fischer & Reuber, 1992). Given these observations,
psychological characteristics are the focus of the
investigations in this study.
The central problem which is addressed in this study is
to investigate the psychological predispositions of small
business owner-managers and corporate managers to determine
if there are any distinctive differences. Specifically,
three commonly identified psychological driving forces are
investigated to determine if small business owner-managers
and corporate managers exhibit significant differences.
8
These psychological characteristics are risk taking
propensity, achievement motivation and preference for
innovation. The fundamental research question in this study
is:
Do the psychological predispositions, as evidenced by achievement motivation, risk taking propensity and preference for innovation, differentiate between individuals* decisions to become a corporate manager or small business owner-manager?
Subordinate research questions include:
1. Do risk taking, achievement motivation and preference for innovation interact in their association with the decision to become a small business owner-manager?
2. Do individual demographic factors, age, education, gender and race, as well as the type of organization, influence the association between psychological predisposition and the ownership of a small business?
3. Because of potential variation in types of small business owner-managers, are there differences in the achievement motivation, risk taking propensity and preference for innovation among subsamples of small business owner-managers which are based upon founding motivations and planning practices?
Theoretical Basis for the Research
A host of research has been devoted to developing
psychological theories of the entrepreneur. Elements of
between managers and professionals in Poland. Here the
managers scored higher in need for achievement than did the
professionals.
McClelland posited that a high need for achievement
predisposes a young person to seek out an entrepreneurial
position in order to attain more achievement satisfaction
than could be derived from other types of positions.
Alternatively, a manager tends to be high in need for power
and lower in need for achievement (McClelland & Winter,
1969). McClelland suggested that those individuals with a
high level of need for achievement tended to exhibit a
certain pattern of role behavior, including:
1. Risk-taking as a function of skill, not of chance,
29
2. Energetic and/or novel instrumental activity,
3. Assumption of individual responsibility,
4. Knowledge of results of decisions, /
5. Money as a measure of results and
6. Anticipation of future possibilities.
Subsequently, McClelland distilled these outcomes associated
with achievement motivation into three main traits: assumes
personal obligation for finding solutions to problems, sets
moderate goals and takes calculated risks to achieve them
and desires explicit feedback pertaining to performance.
McClelland (1965) sought to confirm the 1961 results
with a longitudinal study. McClelland had tested the need
for achievement of 58 students at Wesleyan University in
late 1947. In 1961, the occupational status of 55 of those
students was available. At least for U.S. white college
educated males, the results corroborated the theory that
individuals with a high need for achievement tend to
gravitate toward business occupations of an
"entrepreneurial" nature. McClelland concluded that need
for achievement is a fairly stable personality
characteristic.
Additionally, McClelland attempted to cross-validate
the findings with a sample of 158 additional students to
whom the Thematic Apperception Test (TAT) had been
administered in 1950 and 1951. The results confirmed the
findings that males who were high in achievement motivation
30
tended to seek entrepreneurial business occupations. There
are methodological concerns here, however, because the
testing of need for achievement of the groups was different,
using different and variable procedures, and the latter
group may not have had time to settle into a preferred
occupational position.
Despite the ubiquitous influence of McClelland on
subsequent researchers, some have questioned his findings.
Frey (1984) critiqued the McClelland thesis on a number of
grounds, including empirical validity, particularly noting
that the need for achievement had been assessed from content
analyses of small samples of literature and other artifacts
of culture. Frey also argued that the samples were biased
in terms of size and population representativeness, and that
the interpretation of the data does not confirm that social
factors have a circumscribed impact on the relationship
between need for achievement and entrepreneurial activity.
Also, the TAT has been criticized for low predictive
validity (Klinger, 1966) and low test-retest reliability
(Entwisle, 1972; Miner, 1980). Moreover, these studies did
not actually link need for achievement with the founding or
ownership of a business, the classical hallmark of the
entrepreneur.
Despite the potential limitations on its usefulness,
the work of McClelland has spurred a flurry of analyses
which have included achievement motivation as a variable in
31
studies of the entrepreneur. Selected summaries of these
studies are provided in Table 1. Because of the variation
in samples and instrumentation in this line of research,
care has been taken to explicitly include these
considerations in displaying these studies. The studies
presented here demonstrate the myriad of samples and
instruments used in the study of the achievement motivation
of entrepreneurs. Many researchers subsequent to the work
of McClelland have demonstrated a positive relationship
between achievement motivation and entrepreneurship.
Hornaday and Bunker (1970) undertook a pilot study of
20 males as the first step in a research program to
systematically determine the importance of several
characteristics which had been suggested in previous
research, and to identify and assess additional
characteristics which could be important in identifying the
successful entrepreneur. The researchers used a structured
interview and three objective instruments to gather data.
For the purposes of the study, success was defined as an
individual who had started a business and continued for a
period of at least five years. Using the Edwards Personal
Preference Schedule (EPPS), the researchers found that male
entrepreneurs scored considerably higher than norms on the
achievement scale. Yet, because of the small sample size,
inconsistencies in the selection and application of tests,
and no statistical analysis, the reported results must be
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36
considered inconclusive.
Following the work of Hornaday and Bunker (1970),
Hornaday a,nd Aboud (1971) supplemented the original Hornaday
and Bunker sample with an additional 4 0 "successful"
entrepreneurs to examine the characteristics of successful
entrepreneurs. The authors defined successful entrepreneurs
as those who had founded a new business venture which had
been established for at least five years and had at least
eight employees. Hornaday and Aboud also used a scale from
the EPPS to measure the need for achievement in white and
black men. The results indicated that compared to men in
general, entrepreneurs are significantly higher on scales
reflecting need for achievement. Additionally, on self-
evaluation scales, the entrepreneurs ranked themselves
significantly above average on need for achievement. No
significant difference was discovered by race, and gender
differences were not analyzed.
Subsequently, Komives (1972) posited that entrepreneurs
are high in achievement and decisiveness compared to
population norms. Investigating 20 high technology
entrepreneurs who tended to be successful, Komives
ascertained that these entrepreneurs were indeed high in
achievement motivation and decisiveness compared to
population norms. These findings were inconsistent with an
earlier, comparable study. Schrage (1965), using
McClelland's TAT, found that a sample of 22 research and
37
development scientists did not rank consistently high in
need for achievement. There was no apparent comparison
group. Wainer and Rubin (1969) questioned the validity of
Schrage's findings when they reanalyzed the data with the
same protocols. Nevertheless, resolution of these
discrepant findings is arduous because the studies of both
Komives and Schrage are limited by small sample sizes, and
each used different measures of achievement motivation.
Based upon a study of a group of 29 black
businesspeople who were owners or managers of small
businesses, Durand and Shea (1974) posited that individuals
with high achievement motivation tended to engage in more
business-related activity than those with a low need to
achieve. For the study, the measure of business activity
was adapted from Timmons' (1968) study of entrepreneurial
activities. The results indicated that individuals with a
high achievement motive participated in more entrepreneurial
activities than those with a low achievement motive.
A couple of researchers have investigated the
achievement motivation of business founders in other
countries. Ahmed (1985) studied the achievement motivation
of a group of immigrants from Bangladesh who had founded a
business in the United Kingdom. While not specifically
stated, it appears that those labelled non-entrepreneurs in
this study were managers. Ahmed discovered that
38
entrepreneurs had a higher achievement motivation than did
non-entrepreneurs.
Nandy (1973) studied business founders in two Indian
subcultures in Calcutta. The sample included individuals
who had been in business for at least five years, and
individuals who lived in the area for at least five years
but were not in business. The results indicated that need
for achievement was positively correlated with entry into
enterprise, but was not related to entrepreneurial
competence. Perry, Meredith and Cunnington (1986) also
identified a higher level of achievement motivation of
entrepreneurs compared to the general population of
Australia.
The aforementioned studies of achievement motivation
were primarily limited to men although gender differences
may be significant (Mehrabian, 1968). In a review of the
literature, Watkins (1982) cited only one study of the
motivation of female entrepreneurs. This study was
conducted by Schwartz (1976) of female founders, and
indicated that achievement was a primary motivation. A
couple of subsequent studies have specifically analyzed
women.
Waddell (1983) found no significant differences in the
achievement motivation of female business owners and female
managers, but the female business owners were higher in
achievement motivation than were female secretaries. In a
39
study of 122 minority and nonminority females, DeCarlo and
Lyons (1979) found that female entrepreneurs, defined as
business owners, scored significantly higher on achievement
motivation than did females from the general population.
Also, nonminority female entrepreneurs placed a higher value
on support, recognition, independence and achievement than
did the minority females.
Other studies have shown that need for achievement is
not the most important variable for predicting the
likelihood of starting a business. Frequently, researchers
have studied students who are assumed to be aspiring, or
students who intended to become entrepreneurs and those who
did not, and found that achievement motivation did not
distinguish between the two groups. Sexton and Bowman
(1983) used the Personality Research Form (PRF-E) to analyze
401 college students. Using a sample of general business
majors, non-business majors and entrepreneurship majors, the
authors found that entrepreneurship majors did not score
significantly differently than other students on achievement
motivation. Yet, the question of whether students' majors
are an appropriate surrogate for aspiring entrepreneurs
limits the usefulness of this study. Some entrepreneurship
majors may not found a business, and some non-
entrepreneurship majors may ultimately found businesses.
40
Potentially more conclusive results were provided by Hull,
Bosley and Udell (1980).
Hull et al. (1980) surveyed business school alumni who
had founded a business and others who had not. The business
owners were subdivided into those who had participated in
start-up and those who had not. The researchers also
categorized the non-business owners into three groups based
upon the likelihood of establishing a business. Hull et al.
found that need for achievement did not indicate a
difference in the likelihood of starting a business. There
were no significant differences among any of the groups.
Comparative Studies of Small Business Owner-Managers
and Corporate Managers. Notably, relatively few studies
have actually been conducted which compare small business
owner-managers and corporate managers on achievement
motivation, 'and the results are mixed. Singh (1970), using
a modified TAT, found no significant differences in
achievement motivation among eight subgroups of Indian
managers and business owners. Cromie and Johns (1983)
compared entrepreneurs, defined as those who had started a
business, with middle and upper level managers in Ireland.
While entrepreneurs scored slightly higher than managers on
achievement motivation, the difference was not statistically
significant. Despite the findings of these two studies, the
preponderance of evidence suggests that entrepreneurs are
higher in achievement motivation than are managers.
41
Schere (1982), using the Manifest Needs Questionnaire,
discerned that entrepreneurs were significantly higher in
achievement motivation than were middle and top level
managers. These results confirmed the findings of Hines
(1973), who investigated a group of businesspeople in New
Zealand. The researcher discovered that the entrepreneur,
someone who owns a business, had higher need for achievement
scores than did the engineers, accountants or middle
managers. Lachman (1980) identified a discriminant
function, including 14 achievement motivation items, which
successfully discriminated between individuals who started a
new enterprise and those who were general managers and
presidents of firms. Subsequent studies have corroborated
the hypothesis that entrepreneurs are higher in achievement
motivation than are managers (Ray, 1981/1982; Begley & Boyd,
1987a). These findings tend to support the McClelland and
Winter (1969) proposition that managers who work for someone
else tend to be high in need for power and significantly
lower on need for achievement than entrepreneurs.
Achievement Motivation and Entrepreneurial Success.
In addition to studies of the correlations between
achievement motivation and the decision to become an
entrepreneur, some researchers have pursued the
investigation of potential associations between achievement
motivation and performance. These studies are outlined in
Table 2. A host of studies have demonstrated that
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achievement motivation is associated with entrepreneurial
success. Perhaps the most fundamental indicator of
entrepreneurial success is the founding of the business.
Kemelgor (1985) discovered that aspiring entrepreneurs who
had been successful in venture start-up were higher in
achievement motivation than were aspiring entrepreneurs who
had failed in start-up. Potentially, this relates to the
Durand and Shea (1974) findings concerning the business
activities of those who are higher in achievement
motivation.
Wainer and Rubin (1969), using the TAT, determined that
a high need for achievement and need for power were
correlated with higher firm performance; however, need for
achievement alone provided superior predictive efficiency.
The link between achievement motivation and firm performance
was corroborated by Morris and Fargher (1974), who found
that the achievement motivation and creativity of Australian
owner-managers were associated with firm performance.
Higher scores on either variable were associated with
success, and low scores on both were associated with static
or declining businesses.
Begley and Boyd (1987a) studied the psychological
characteristics of entrepreneurs (founders) and small
business managers (nonfounders) which were predicted to be
associated with firm performance. Founders scored
significantly higher than nonfounders on achievement
46
motivation, risk taking propensity and tolerance for
ambiguity. In terms of performance, a high need for
achievement was associated with high return on assets.
Smith and Miner (1984, 1985) studied fast- and slow-
growth entrepreneurs. Successful entrepreneurs, those
labeled fast-growth, scored significantly higher on need for
achievement motives than did the slow-growth entrepreneurs
and non-entrepreneurs. There were no significant
differences between the slow-growth entrepreneurs and non-
entrepreneurs. Smith, Bracker and Miner (1987) extended
these research findings by discovering a significant
positive correlation between achievement and measures of
company success. Despite these results, a caveat to this
series of research efforts should be noted. All three
studies used Miner's (1982) limited domain theory of
individual behavior which is based upon McClelland's (1961)
theory of need for achievement. While the two theories may
be linked, and both use projective measures of achievement,
direct comparison of investigations is not possible (Smith &
Miner, 1985).
The study of the relationship between need for
achievement and successful entrepreneurial activity has been
cross-culturally extended. Singh (1978), in a longitudinal
study of farmers in India, found that farmers who had a
relatively high need for achievement continued to produce
more agricultural output than did farmers with a low need
47
for achievement. Singh (1978) posited that achievement
motivation was a stable characteristic. Also, Sutcliffe
(1974) investigated need for achievement and entrepreneurial
success of Palestinian farmers in Jordan and Israel. The
researcher measured successful entrepreneurial behavior by
assessing agricultural innovativeness and income. The need
for achievement did not differentiate between successful and
unsuccessful farmers. In a study of Australian
entrepreneurs, Perry, Meredith and Cunnington (1986)
concluded that achievement motivation is important for
venture creation, but does not affect subsequent growth.
Carsrud and 01m (1986) posited that the reason for the
inconsistent results was that achievement motivation is a
multidimensional construct, but researchers have frequently
used unidimensional instruments for measurement. The
researchers reported the results of two studies which used
the Work and Family Orientation Inventory (WOFO), which has
three subscales. In the first study, all three WOFO scales
were strong predictors of sales for male business owners who
were in the one to forty-nine percent ownership category.
In the second study, no predictive ability of the WOFO was
demonstrated for female business owners.
Summary of Achievement Motivation. In summary, the
achievement motivation of the entrepreneur has been widely
but inconclusively investigated. While it appears that
entrepreneurs exceed managers in achievement motivation, the
48
findings are equivocal. Brockhaus and Horwitz (1986)
concluded that a definitive relationship between achievement
motivation and entrepreneurship had not been demonstrated.
The assumption that the entrepreneur is higher in
achievement motivation than the corporate manager has not
been demonstrated. Johnson (1990) suggested that the
inconclusiveness of the theorized relationship was a
function of the variability of the samples, different
operationalizations of the achievement motive and convergent
validity problems in instrumentation. It should be noted
that the cross-cultural studies of achievement motivation
are also susceptible to methodological concerns such as
conceptual equivalency, particularly with the use of
projective measures of achievement motivation. Johnson
concluded that the lack of definitive empirical results was
more likely a result of flawed research methodology than the
absence of a positive relationship.
Maybe the most pervasive limitation in this stream of
research has been the variability and the absence of
demonstrated validity, particularly convergent validity, of
the measures of achievement motivation. Evidence suggests
that achievement motivation measures suffer from poor
construct validity and cannot be used interchangeably. For
instance, Weinstein (1969) reported only two statistically
significant correlations in 21 analyses of pairs of
achievement measures. Fineman (1977) found only 22
49
significant correlations in 78 analyses of achievement
measures. In addition to low intercorrelation of measures,
Klinger (1966) raised concerns over the low internal
consistency and minimal test-retest reliabilities of the
measures, a concern reiterated by Weinstein (1969). Of
particular concern is the TAT. McClelland (1961)
acknowledged that situational differences from occasion to
occasion reduced the reliability of the TAT, as did the
sensitivity of product-moment correlations to large shifts
in score. Entwisle (1972), noting the unreliability of the
TAT, actually warned against its further use. According to
Entwisle, studies using the EPPS may be more useful because
the EPPS is more reliable than the TAT.
Sampling frames have also been problematic. VanderWerf
and Brush (1989) suggested that it was tempting to conclude
that there was no relationship between entrepreneurship and
achievement motivation. Instead, the authors scrutinized
the sample selection criteria of the Schrage (1965), Wainer
and Rubin (1969) and Begley and Boyd (1987a) studies. When
recategorized, the results of the studies which attempted to
correlate the achievement motivation of the entrepreneur
with company growth rate neatly followed the expectations of
an a priori investigation. Nonetheless, the research
linking achievement motivation with new venture creation is
more conclusive than that which links achievement motivation
to entrepreneurial performance (Herron & Robinson, 1993).
50
Clearly, more research is necessary to prove a definitive
link between achievement motivation and entrepreneurship.
Propensity for Risk Taking
Interest in decision making processes has led
researchers to study individual orientations toward risk in
decision making scenarios (Kusyszyn, 1973). Much of the
research in risk orientation is based upon the premise that
an individual's risk orientation is pervasive, affecting
perceptions and behaviors. Studies generally support the
notion that risk taking is predispositional and not simply a
compared centralized branch bank managers (categorized as
less entrepreneurial) and decentralized managers (labelled
more entrepreneurial). These studies appear to have been
comparing different types of managers, not comparing
entrepreneurs with any other group.
Subsequent studies have produced mixed conclusions.
Summaries of this research stream are presented in Table 3.
Again, because of the variation in samples and
instrumentation, careful attention has been given to
outlining the studies for the purpose of comparison. Some
studies have indicated no significant differences in the
risk taking propensities of entrepreneurs as compared to the
general population. The most widely cited studies are those
of Brockhaus.
Brockhaus and Nord (1979) analyzed 31 entrepreneurs who
had initiated a new venture within the past three months, 31
managers who had transferred to another organization and 31
managers who had been promoted in their organizations during
the same period of time. Using the CDQ, the authors found
no significant differences in risk taking propensity among
the three groups. Moreover, there were no differences in
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risk taking between any of the three groups and population
norms as reported by Kogan and Wallach.
Brockhaus (1980a), using the Kogan-Wallach Choice
Dilemmas Questionnaire (CDQ), discovered that risk taking
propensity failed to distinguish entrepreneurs from
managers. Both groups evinced moderate levels of risk
taking. The results substantiated the Brockhaus (1976)
findings that entrepreneurs did not differ in their
propensity for risk taking from the general population, nor
from managers. Furthermore, Brockhaus (1980b), using the
same instrument, also discovered that risk taking propensity
failed to distinguish between successful and unsuccessful
entrepreneurs.
Ray (1986) raised concerns over the findings of
Brockhaus (1980a), noting two problems: (1) the variability
in the Brockhaus sample and (2) the problems associated with
the Wallach and Kogan questionnaire. Ray suggested that
because of the variability in the sample, issues of socio-
economic class, type of firm and education level could have
limited the validity and generalizability of the Brockhaus
results. Moreover, according to Ray, the CDQ is
ethnocentric and relies on projected assessments of risk
which may not provide a valid indication of an
entrepreneur's risk taking behavior.
Other researchers have questioned the CDQ. Cartwright
(1971) criticized the practice of summing the scores on
59
individual CDQ items because the CDQ does not measure a
unitary disposition. Therefore, because the CDQ cannot be
assumed to measure a general disposition to take risks, its
use for such purposes may be misleading. In fact, Brockhaus
(1980a) had summed the scores on the individual items of the
CDQ, leading one to query the validity, or at least, the
meaning of the findings. Cartwright cautioned that the
significance of research findings is contingent upon the
meaning that can be attributed to the choices.
Higbee (1971) raised additional concerns about the CDQ.
Higbee determined that people classified as high or low risk
takers on the CDQ did not differ in their actual risk taking
behavior on tasks. Potentially, this is because respondents
are asked to make decisions for another person, not for
themselves (Shaver & Scott, 1991). Higbee suggested that
the CDQ might be a more appropriate indicator of
anticipated, rather than actual, riskiness under complex
decision making conditions. Yet, this evaluation may not
even be correct given that choice shift makes the CDQ
theoretically inappropriate for measuring risk taking
propensity (Shaver & Scott, 1991). Notably, all of the
aforementioned studies used the CDQ, raising the dilemma
that the results are an artifact of measurement.
Nonetheless, other researchers, using different measures of
risk taking, have supported the supposition that
60
entrepreneurs are not significantly unique in their
propensity for risk taking.
Peacock (1986) used an adaptation of the Opinion
Questionnaire to measure risk taking. The researcher found
no significant differences in the risk taking patterns of
successful and unsuccessful entrepreneurs. Both groups
evidenced moderate risk taking patterns.
Masters and Meier (1988) discerned that owners of small
businesses and the managers of small businesses did not
significantly differ with regard to risk taking propensity,
and there were no significant differences in risk taking
among males and females. In another study, Litzinger (1965)
studied the motel industry and found that the two groups,
motel owner-operators and managers in five Arizona cities,
did not differ in terms of riskiness per se, nor in the
propensity of risk preference toward taking extreme or
intermediate risks. Litzinger, however, assessed risk using
an investment risk scenario, and the reliability and
validity of the measurement was not demonstrated. In fact,
the author stated that the risk weights "provided a rough
relative measure to distinguish relative risks inherent in
the various categories" (p. 270).
Others have discovered a higher propensity for risk
taking among entrepreneurs, particularly when confronted
with business risk (Ray, 1986), but moderated by business
experience, age, education and type of business (Schwer &
61
Yucelt, 1984). Colton and Udell (1976), in a study of
university alumni, discerned that risk taking, along with
creativity and flexibility, is a better indicator of the
likelihood of starting a business than is achievement
motivation. Research has also shown that entrepreneurs
evince low uncertainty avoidance irrespective of culture
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70
marketing and planning, tend to exhibit more innovative KAI
between these two sets of psychological constructs are also
tested.
Chapter Summary
Provided in this chapter was a review of the three
primary psychological constructs which are most prevalent in
theorizing about the entrepreneur. These constructs are
achievement motivation, risk taking propensity and
innovativeness. In addition to examining linkages among the
psychological constructs, a review of the effects of
individual and firm demographic characteristics upon the
98
entrepreneurial decision was provided. Concluding the
literature review was a presentation of different types of
small business owner-managers. Based upon the review of the
literature, the research framework was presented, followed
by explication of the hypotheses for the study.
CHAPTER III
RESEARCH PROCEDURE AND METHODOLOGY
Smith, Gannon and Sapienza (1989) offered several
factors for consideration by entrepreneurship researchers in
selecting a research approach. These factors included the
objective of the research. One hallmark of a good research
hypothesis is that it suggests which form of research design
is likely to be most appropriate (Emory, 1985). The nature
of the hypotheses for this study suggests that the most
advantageous research design is a survey. In view of these
considerations, a questionnaire composed of individual and
firm demographic questions, and scales pertaining to
achievement motivation, preference for innovation and risk
taking propensity was assembled.
This chapter is devoted to outlining the methodological
elements and procedures of the study. Particular emphasis
is placed on the elements of sampling, instrumentation and
analysis. An overview of the methodological procedures is
provided in Table 6.
The Sample and Procedure
Proper sampling is particularly crucial in this study
because of the aforementioned problems associated with the
definition of an entrepreneur. Gartner (1989) cautioned
99
100
Table 6
Summary of Major Elements of Research Procedures
Procedural Element Description
Sampling
Instrumentation
Dependent Variable Categorization
Data Analysis
Convenience sample where sampling was conducted by graduate business students, resulting in a sample of 767 owner-managers of small businesses and corporate managers.
Instrument contains the Achievement Motivation Scale of the Personality Research Form (Jackson, 1967), the Risk Taking and Innovation Scales of the Jackson Personality Inventory (Jackson, 1976) and questions pertaining to individual and firm demographics and owner goals and planning practices.
Small business owner-managers classified as either entrepreneurs or small business owners (Carland et al., 1984) and firms classified as small or large businesses using the Small Business Administration definitions. Both categorized by a panel of experts.
First step is a confirmatory factor analysis of the small business owner-manager categorization using owner goals and planning practices (Carland et al., 1984). Second step is a hierarchical set multi-nomial LOGIT regression analysis to evaluate the research model and test hypotheses.
101
that careful selection of samples of entrepreneurs and non-
entrepreneurs assists in identifying and controlling for
variation. Gartner believed that careful attention to
sampling was imperative for research in entrepreneurial
traits so that the sample would most appropriately represent
the types of individuals who are to be investigated.
Graduate business students selected the participants of
the study on a convenience basis. The students primarily
solicited responses from employers, employers of their
parents, acquaintances or individuals with whom they had
some other form of contact. The questionnaire was
administered to a total of 767 owner-managers of small
businesses and managers of large organizations.
Participants in the study came from 20 states; however, most
respondents lived in the Southeast United States.
Although the sample is convenience in nature, there are
several benefits from this sampling technique. First, the
sample was not anonymous and the data set was controlled.
Respondents were asked to give their names, addresses and
telephone numbers. Also, the respondents were asked for a
statement of the philosophy of the organization and about
the goals of the organization. Asking for this information
dramatically reduced the likelihood that a participating
student would personally complete the survey. Moreover,
because the respondents were typically approached by people
whom they knew, it is probable that the questionnaires were
102
more likely to be completed by the intended persons, an
obvious advantage over a mail survey. Given these
conditions, the researcher is confident of the integrity of
the data. The questionnaires were examined upon submission,
and most incomplete questionnaires were returned for
completion.
Second, the rate of response was greater than that of
the typical mail survey. It has been noted that surveys of
entrepreneurs, in particular, produce notoriously low
response rates (Gasse, 1982; Aldrich, 1992). Less than one
in twenty individuals who were approached refused to
participate in the study, indicating that individuals
participated in the survey who might not otherwise have
responded. Therefore, while still existent, nonresponse
bias is not as problematic as with the typical mail survey.
Also, because responses were checked for completeness as
they were submitted, item nonresponse error was also
dramatically minimized. Only 20 of the 7 67 completed
surveys had missing data.
Third, the technique engendered the ability to generate
a large sample size. The central limit theorem (Mason,
1982) suggests that the level of confidence of a sample of
this size approaches that of a random sample. Also, the
size of the sample improves statistical power. Using a
conservative estimate of effect size, that labelled 'small'
by Cohen (1988), the statistical power is between .96 and
103
.98 for an alpha level of .05, and between .88 and .92 for
an alpha level of .01.
One particular disadvantage of the sampling technique
should be noted. Jackson (1967) pointed out that the
Personality Research Form could be given in a variety of
situations, but the best results would be achieved by using
standardized supervised group or individual testing
conditions because the test was standardized under these
conditions. Jackson felt that standardization under these
conditions would yield the most reliable results, and
cautioned that in other circumstances, it was important to
impress upon subjects the seriousness of the purpose of the
testing and to emphasize care in completing the test. While
the basic purpose of the study was specified in a cover
letter which accompanied the questionnaire, no other control
over respondent conditions could be achieved.
Another issue is the appropriateness of the sample.
VanderWerf and Brush (1989) surmised that sampling from
different populations has hindered empirical research in
entrepreneurship. This has been largely due to the
aforementioned definitional dilemma in the field.
VanderWerf and Brush advanced a set of criteria for sample
specification including criteria for business unit variation
and for individual variation. For business units, these
criteria included the age, size and industry. For
individuals, the criteria included roles in founding,
104
ownership and management of the business. While no a priori
selection criteria were used for this sample because there
were no lists or groups identified, data concerning these
criteria, plus additional variables, were gathered. This
information will allow for the investigation of potential
moderator variables (Hunter, Schmidt & Jackson, 1983) and
will provide the parameters for the dependent variables in
the study.
Despite attentiveness to the sampling frame, it is
possible that this sample of small business owner-managers
and managers could be patently different from the target
population of small business owner-managers. As suggested
by Gartner et al. (1989), a comparison will be made between
the subjects of this sample to other research samples that
provide comparable sample size and statistics concerning the
makeup of the sample. These comparisons should provide
additional insight about the sampling frame.
One of the objectives is to maximize the external
validity of the study. Neale and Liebert (1986) described
two types of external validity, population and ecological
validities. In terms of population validity, the intent is
to generalize the findings to the population of small
business owner-managers. The population validity is
hampered in this study by the use of a convenience sample.
Nevertheless, because of the size of the sample and the
central limit theorem (Mason, 1982) the sample approaches
105
that of a random sample. With regard to ecological
validity, because the sample is drawn primarily from the
Southeastern U.S., generalizing across geographic areas is
limited. Yet, the comparison with other entrepreneur
research populations, the size and demographic breadth of
the sample, and the relative geographic dispersion of the
sample should maximize the generalizability of the results
within the constraints of the study (Neale & Liebert, 1986).
It is frequently assumed that personality and
entrepreneurial motivation and competence do not vary across
cultures, but this assumption may not be valid (Nandy,
1973). De Vos (1968) and McGrath et al. (1992) cautioned
that this assumption of cross-cultural consistency may be
untenable. In light of this evidence, the results cannot be
extrapolated to other cultures.
Instrumentation
Instrumentation, always an important element of a
survey design, has been a crucial issue in the study of the
psychological characteristics of the entrepreneur. Thus,
careful attention must be devoted to the instrumentation for
the study. One issue of concern in instruments for
psychological measurement is response sets (Cronbach, 1946,
1950), which is a moniker for a host of biases such as
acquiescence, evasiveness, tendency to guess and working for
speed instead of accuracy. Cronbach (1946) provided a
detailed examination of the potential deficiencies of a
106
survey design. The major criticism was the potential bias
which the researcher introduces in the design of
questionnaires. Cronbach believed that by defining the
questions, response sets and the conditions for
participation, the researcher may introduce systematic forms
of bias into the study. Moreover, there may also be
problems associated with the research participants.
Respondent error is also of concern, and includes a
number of considerations. Sletto (1937) first identified
the phenomenon of acquiescence response set in which the
respondents tend to more frequently endorse favorable
statements and not endorse negative statements. Also, there
is a tendency on the part of respondents to endorse strong
statements rather than weak statements (Webb, Campbell,
Schwartz & Sechrest, 1971). The perception of the social
desirability of the respondent vis-a-vis the question
(Zikmund, 1994) may also be problematic. Additionally, one
of the significant concerns in a survey is nonresponse error
because those who respond to the survey may be statistically
different from those who do not (Zikmund, 1994). In short,
all of these potential threats to the usefulness of the
research are potential limitations inherent in the research
methodology which must be addressed.
Achievement Motivation
Hermans (1970) emphasized the need for objectivity in
measuring need for achievement, stating that measurement had
107
been the most difficult problem in studies in the area of
achievement motivation. One of the major issues has been
the use of projective measures which treat achievement
motivation as an unconscious variable, versus questionnaire
measures which treat the construct as conscious. Sherwood
(1966) found no significant differences between projective
and self-report measures of achievement motivation as
predictors of behavior; both are useful measures of the
motives underlying behavior. There is no clear theoretical
case for treating achievement motivation as an exclusively
unconscious variable (Fineman, 1977). Holmes and Tyler
(1968) indicated that achievement motivation is a conscious
phenomenon, and therefore, amenable to direct self-report.
Thus, a concerted effort was made to choose a measurement
instrument for achievement motivation which would maximize
reliability and validity. The Achievement Scale of the
Personality Research Form (Jackson, 1967) was used to
measure achievement motivation.
Jackson's (1967) Personality Research Form-F (PRF) is
based on the 20 manifest needs described by Murray (1938).
It is intended to yield scores for personality traits which
are broadly relevant to the functioning of the individual in
a wide array of situations. The PRF was chosen because of
its use in previous research and the rigorous process by
which the scales were developed and validated (Jackson,
1974). Wiggins (1973) stated that the PRF is the only
108
multitract personality inventory where the development was
guided explicitly by the substantive, structural and
external considerations of the construct viewpoint.
The PRF is composed of bipolar scales for each of the
twenty personality characteristics and two validation
scales, labeled desirability and infrequency. Because a low
score could indicate the absence of a trait or the presence
of the trait's opposite, some traits may be in theoretical
opposition. The PRF dimensions were conceived, both
theoretically and in measurement, as bipolar. The bipolar
construction reduces the likelihood of confusion and the
redundancy in the use of alternative concepts to define
essentially the same dimension (Jackson, 1967). Defining
both ends of a dimension with test items helps specify what
was being measured, and assists in controlling for response
biases such as acquiescence (Cronbach, 1946, 1950; Jackson &
Messick, 1958; Jackson, 1967).
Methods were used in the construction of the PRF to
reduce the role of response styles. Acquiescence was
suppressed by using equal numbers of true and false keyed
items. Moreover, the attention to content saturation in the
construction of the scales has been demonstrated to reduce
the role of acquiescence (Clunis & Jackson, 1966). High
differential content saturation and selection of items on
the basis of relatively low correlations with desirability
also reduce the potential for response bias. Each item was
109
analyzed for response consistency and was found to correlate
more highly with its own total scale than with a
desirability scale, indicating that each item is more
saturated with content variance than with desirability
variance (Jackson, 1967). This technique maximized
reliability and discriminant measurement.
The PRF also includes an Infrequency Scale directed at
identifying careless or non-purposeful responses (Sechrest &
Jackson, 1963). High scores on Infrequency are unlikely for
reasons other than non-purposeful responding. The
Infrequency scale will be examined for all cases, and when
the score exceeds 4, the case will be examined for errors in
responding as suggested by Jackson (1967).
The definition of achievement motivation used for this
study is as follows:
Achievement motivation, or the need for achievement, is evident in an individual who: aspires to accomplish difficult tasks; maintains high standards; works toward the attainment of distant goals; responds positively to competition; or is willing to put forth effort to attain excellence (Jackson, 1967).
Reliability and Validity of the PRF. Two properties of
reliability, homogeneity and stability, should be examined
in psychological testing (Jackson, 1967; Rosenthal & Rosnow,
1991). Jackson (1967) reported estimates of homogeneity
which were derived from item analysis statistics. In a
study of 142 students, the Kuder-Richardson formula 20 value
for the achievement scale was .93. In a sample of New
Jersey male high school students (N = 71), the Kuder-
110
Richardson formula 20 value for achievement was .73. A
sample of 202 college students produced a Kuder-Richardson
formula 20 value of .72. The author also reported odd-even
reliability of .77 (N = 192). These values represent an
acceptable level of internal consistency.
In terms of stability over time, Bentler (1964/1967)
administered the PRF to male and female students in three
California colleges on two occasions, separated by a one
week interval. Bentler found a test-retest reliability
score of .80 for achievement. Jackson (1967) postulated
that this reliability could be considered a lower bound
estimate because the testing conditions were not identical
and the estimate of reliability, the intraclass correlation,
is generally smaller in size than the simple
intercorrelation. Jackson (1967) also evaluated parallel
form reliability over two testing sessions separated by two
weeks (N = 135). The test-retest reliability for
achievement was .80. While these indicators of stability
are good, one concern in these studies is the relatively
short periods of time between tests because recall could
have a significant influence on the retest score (Fineman,
1977) .
Convergent and discriminant validation of the PRF
Scales has been undertaken. Jackson (1967) reported a
series of PRF validation studies which used trait
attribution data to evaluate convergent validity. Judges
Ill
were presented with a list of traits exemplifying the
variables in the PRF, and carefully phrased definitions for
each of the personality traits. Each judge was asked to
rate each person being judged on a nine point scale
concerning the degree to which the trait was present or
absent. The pooled ratings were used as a consensus of the
degree to which a given trait was present. Subjects were
also asked to indicate the presence or absence of each trait
in themselves from a rating form containing 660 adjectives.
The first study used two samples of university students
at two different California universities. For achievement,
behavior ratings were .53 (N = 40) and .52 (N = 51). Self
ratings were .55 and .42, respectively. A second study by
Jackson and Guthrie (1968) of 202 students at a Pennsylvania
university produced behavior ratings for achievement of .46
and self ratings of .65. All of the above validity
coefficients were significant at the alpha .01 level.
Jackson pointed out that these results: were based on
cross-validational data, were complete, represented a
predicted correlation and were free from any form of
statistical adjustment.
Another validation study was undertaken by Kusyszyn
(1968), who correlated PRF scale scores with judgments of
the degree to which the subject possessed a particular
trait. Here the subjects were 94 members of five
fraternities. For the group which lived together, the
112
validity coefficient for achievement was .52 (.62 when
corrected for attenuation) and .44 for the total sample (.50
when corrected for attenuation). All of these statistics
were significant at an alpha level of .01. All of the above
correlations exceed .40, which indicates acceptability,
given that several of the most important effects in
psychology are of a size between .30 and .40 (Funder & Ozer,
1983), and a prediction based on a correlation of .40 will
be correct more than twice as often as it is wrong
(Rosenthal & Rubin, 1982) .
Funder and Dobroth (1987) addressed a pertinent issue
in the aforementioned studies of validity, the degree to
which judgments of traits might or might not be accurate.
The authors identified three sources of differential
accuracy: individual differences between judges, individual
differences among persons being judged and the possibility
that some traits can be judged more accurately than others.
Funder and Dobroth's study indicated that a trait will most
easily be visible when the trait is readily tied to
confirming or disconfirming behaviors, the behavior is
apparent in many occasions, only a few confirming behaviors
are necessary to indicate the trait, and the trait seems
subjectively easy to judge. Achievement motivation seems to
fit readily with these criteria.
In studying the discriminant validity of the PRF,
Jackson reported the use of multimethod factor analysis,
113
which orthogonalizes those portions of the multitrait-
multimethod correlation matrix common to a given method of
measurement (Jackson, 1966). The result of this technique
is a correlation matrix where only heteromethod validity
coefficients are obtained because the monomethod values have
been replaced by zeros. Jackson maintained that by using
this technique, method variance common only to a single
method of measurement cannot intrude to determine common
factors. When a rotation to simple structure is performed,
the factors which result are interpretable as being due
primarily to the correlation of traits across different
methods of measurement, rather than as a result of artifacts
of the method of measurement.
Jackson and Guthrie (1968) applied multimethod factor
analysis to the evaluation of the convergent and
discriminant validity of the PRF scales. Self and peer
rating of traits of the characteristics were obtained for a
sample of 202 subjects who had also taken the PRF. Using
the varimax criterion, the PRF scales loaded on the
appropriate factor. The self ratings, peer ratings, and PRF
scores of achievement all loaded on one factor with factor
loadings of .82, .61, and .83 respectively. The authors
concluded that the results of the factor analysis provided
substantial evidence for the convergent and discriminant
validity of the PRF scales. Furthermore, it is possible to
treat each PRF scale as distinct.
114
Convergent validity has been further demonstrated for
the PRF. Edwards, Abbott and Klockars (1972) demonstrated
that the Edwards Personal Preference Schedule was
significantly correlated with the PRF on achievement
motivation. Mehrabian (1969) found that the Mehrabian
1978). In fact, Wiggins (1973) referred to the PRF as the
best example of a large scale personality inventory. It is
believed that this achievement motivation instrument is the
most well suited for this study.
Risk Taking Propensity and Preference for Innovation
Risk taking propensity and preference for innovation
were measured using the Risk Taking Scale and Innovation
Scale of the Jackson Personality Inventory (JPI) (Jackson,
115
1976). The JPI is a structured personality inventory which
includes 16 personality variables, 15 of which are
substantive, and the last addresses validity. The
construction and features of the JPI parallel those of the
PRF. The JPI consists of 320 true-false statements, each
scale containing ten true-keyed and ten false-keyed
statements. As with the PRF, Jackson (1976) advised that
this design minimized the role of acquiescence response set,
and permitted definition of each pole of bipolar scale
dimensions with positively-worded content.
The JPI was developed for use on populations of average
or above average ability. Jackson (1976) proposed that the
JPI is most appropriate for studies of personality in a
variety of settings, particularly those which investigate
the personality correlates with particular occupations, and
is appropriate for business and industry. Given these
suggested applications, the instrument is appropriate for
the purpose of this study. Moreover, Dyer (1985) stated
that the development of the JPI was rigorous and painstaking
and the results have been generally praised.
The Risk Taking Scale of the JPI allows examination of
four relatively independent components of risk taking:
social, physical, monetary and ethical. While assessing all
four elements of risk taking, the scale tends to weight
monetary risk taking more heavily than the other three types
(Jackson, 197 6). In terms of theoretical approach, the Risk
116
Taking Scale is comparable to Palmer's (1971) definition of
risk taking, which involves the willingness to commit to a
decision which could lead to success or failure and
accompanying rewards and penalties. The following is a
description of the high scorer on the Risk Scale (Jackson,
1976):
Enjoys gambling and taking a chance; willingly exposes self to situations with uncertain outcomes; enjoys adventures having an element of peril; takes chances; unconcerned with danger.
The Innovation Scale of the JPI is a measure of the
predisposition to be innovative. In this sense, innovation
on the JPI is conceptually synonymous with creativity. The
Innovation Scale is highly similar to several personality-
type indicators of creative personality style (Goldsmith,
1987). The following is a definition of the high scorer on
the Innovation Scale (Jackson, 1976):
A creative and inventive individual, capable of originality of thought; motivated to develop novel solutions to problems; values new ideas; likes to improvise.
Reliability and Validity of the JPI. Research has
verified the reliability and validity of the JPI for
measuring generalized risk taking. For risk taking
propensity, Jackson (1977) tested the internal consistency
reliability with two samples of male and female college
students in California and Pennsylvania (N=82 and N=307,
respectively). For several reasons, reliability was
estimated using Bentler's coefficient theta. Because risk
117
taking was composed of four facets, physical, monetary,
social and ethical risk taking, Jackson argued that
coefficient theta was more appropriate because, unlike
coefficient alpha, coefficient theta is not restricted to an
assumption of a single unidimensional attribute. In cases
of departure from unidimensionality, alpha will yield an
underestimate of the lower-bound reliability (Bentler,
1972). Nonetheless, Jackson did calculate alpha
coefficients for the purposes of comparison.
For the Risk Taking Scale, Bentler's coefficient theta
was .93 for the California sample and .91 for the
Pennsylvania sample. Coefficient alpha was .81 for the
California sample and .84 for the Pennsylvania sample. The
internal consistency reliability of the Innovation Scale
produced values of .94 and .93, respectively, using
Bentler's coefficient theta, and .83 and .87, respectively,
using coefficient alpha. Jackson argued that these scores
were relatively high and that they attest to the value of
content saturation in the construction of the test.
Other studies have supported the reliability of the two
scales. Goldsmith (1987) reported alpha values of .85 for
innovation and .81 for risk taking in a sample of 96
undergraduate business students. Begley and Boyd (1987b)
reported an alpha value for risk taking of .784. Howell and
Higgins (1990) discovered an alpha of .84 for both risk
taking and innovation.
118
Testing for validity (N = 70), Jackson (1976) reported
multitrait-multimethod matrix correlations with the
completion of an adjective checklist, with self ratings and
with peer ratings. For the Risk Taking Scale, the
convergent validities were .74, .73 and .52, respectively.
For the Innovation Scale, the convergent validities were
.79, .72 and .37, respectively. All of the validity
coefficients were significant at an alpha level of .01.
Jackson also used a revised multimethod factor analysis
technique. The results indicated that the predicted
measures were highly loaded on their respective factors,
supporting convergent and discriminant validity at the
factorial level.
A second study reported by Jackson (1976) involved
correlations between JPI scale scores, self ratings and
roommate ratings for 116 college females. The correlations
with self ratings and peer ratings were .65 and .43,
respectively, for risk taking and .75 and .23, respectively,
for innovation. Jackson attributed a portion of the
relatively lower peer correlations to the reduced
reliability of a single judge. Nonetheless, all of the
aforementioned correlations were significant at an alpha
level of .01. Notably, neither scale was significantly
correlated with measures of acquiescence or desirability.
Jackson provided additional evidence of validity by
presenting correlations between the JPI and a number of
119
other instruments, including the Bentler Psychological
Inventory, the Bentler Interactive Psychological Inventory,
the Personality Research Form and the Minnesota Multiphasic
Personality Inventory. The correlations provided additional
evidence of discriminant and convergent validity.
Additional support has been shown for the reliability and
validity of the JPI (Jackson, Hourany & Vidmar, 1972; Sexton
& Bowman, 1984b).
Demographics
Demographic data concerning both the individual and the
firm were gathered. These variables included the education,
age, race and gender of the respondents. Owners were asked
how they acquired the business, the age of the venture and
the type of organization it represented. Strategic
questions addressed owner goals and perceptions of the
business, the relationship of the business to their families
and the practice of strategic planning.
Jackson (1971) stated that "to construct psychological
measures in disregard for sources of method variance is to
court disaster" (p. 240). This principle is evident in
Jackson's construction of the PRF and JPI. In both
instruments, the careful attention to scale construction is
justified by the weight of contemporary writing (Dyer,
1985). Despite the attention to scale construction in the
PRF and JPI, self-report data can be problematic.
120
Verification of the data concerning demographics, goal
and purpose is arduous because of the size of the sample and
a lack of knowledge of other organizational members.
Neither are the self-report measures of the psychological
variables verifiable by independent means. The potential
problem of common method variance arises when interpreting
correlations among these self-report measures (Campbell &
Fiske, 1959), particularly single source bias where the
measures are generated from a single source (Podsakoff &
a where Factor 1 is small business owners Factor 2 is entrepreneurs Factor 3 is managers
134
percent of the total explained variance. Moreover, the
communalities (h-) show considerable overlap with the
factors in what they measure. The proportion of variance in
the variables which is accounted for by scores in the
factors is particularly high for unwritten plans (h =
.9702), a goal of profit and growth (h = .8562) and a goal
of producing family income (hf = .8022). Also of interest
are the factor scores. Although there is no known
statistical test that can be used to establish the
significance level of a rotated factor loading, a commonly
accepted cutoff level is a factor score with an absolute
value which is greater than .30 (Comrey & Lee, 1992) which
is considered a rigorous level (Child, 1970). The values
which exceed this criterion are underlined in Table 8 and
are the basis for the following identification of the
factors.
No plan (.800) and family income (.867) load on the
first factor. Theory suggests that this factor be labelled
small business owners because it corresponds with minimal
strategic planning and a goal orientation focused on family
income. The second factor is characterized by high loadings
of unwritten plans (.980) and profit and growth (.562),
however, profit and growth also loads on the third factor.
This makes distinctions between factors two and three less
definitive. Written plans (.855) loads on factor three.
Research indicates that planning in small businesses tends
135
to be less frequent and formalized than planning in large
businesses (Shuman & Seegar, 1986). For this reason, factor
two is labelled entrepreneurs, corresponding with a greater
emphasis on strategic planning, although informal, and a
goal orientation focused on profit and growth. The third
and final factor, labelled managers, is characterized by a
high degree of formalized strategic planning and a profit
and growth orientation.
The results of the confirmatory factor analysis
indicate that the three identified dimensions correspond
with proposed theory and the categorization criteria which
were used to define the dependent variable. Furthermore,
while these results do not provide conclusive support for
the Carland et al (1984) definitions, the factor analysis
does provide partial validation of those definitions because
it evinces internal consistency. The goals and planning
behaviors of entrepreneurs and small business owners
appeared to allow differentiation between the two groups in
this data set. Yet, some caveats are prudent here.
Although the size of this sample (N = 767) increased
the reliability of the correlation coefficients (Guertin &
Bailey, 1970), caution is in order when factor analyzing
dichotomous variables because they are less reliable and
subject to distortion (Comrey & Lee, 1992). Also, only a
small number of variables were included in the analysis.
More dependable factor results are produced with the
136
inclusion of more variables (Comrey & Lee, 1992). Also, the
correctness of an interpretation which is based on factor
analytic results should be confirmed by evidence outside the
factor analysis itself (Comrey & Lee, 1992). For these
reasons, the results of this analysis must be considered
tentative.
Model Determination and Predictive Efficacy
The primary analysis in this research entails modelling
the research framework and performing a series of
hierarchical set multinomial LOGIT regressions. The first
step was to determine the appropriate entry of variables
into the model for analysis. The intention was to hold
constant the effects of the demographic characteristics of
the individuals and the type of industry of the organization
so that these variables would not confound the analysis of
the primary variables of interest in the study. For this
reason, the individual demographic variables, age,
education, race and gender, were entered as a set into the
model in step 1 of the analysis. Subsequently, in step 2,
the variables comprising the type of organization,
wholesale, retail, manufacturing, service and construction,
were entered into the model as a set.
The next phase was to enter the primary independent
variables. Given that there are three variables of interest
and no conclusive theory to guide the order of entry, six
models were created which encompassed every possible order
137
of entry. In these models, each of the main variables was
entered singularly so that each comprised a set. Finally,
both of the interaction terms were entered, again in both
possible orders.
All of the models were significant (alpha = .05)
overall, as were the steps which included the covariates and
the main independent variables. For the purposes of
discussion, the model which has the most conceptual appeal
is presented. Based upon the literature, the sequence of
achievement motivation, preference for innovation and risk
taking is a theoretically appealing order of variable entry
into the model. McClelland (1961) believed that achievement
motivation was established very early in life and its
presence led to a preference for tasks requiring
originality. The originality may beget additional risk.
The significance of the overall model and the
individual steps are shown in Table 10. The McFadden's Rho-
squared, a global test of the significance of the predictor
set, is the first statistic of interest in the table. It is
a statistic which is roughly comparable to the coefficient
of determination in ordinary least squares regression,
however, McFadden's Rho-squared tends to be much lower.
Values of McFadden's Rho-squared between .20 and .40 are
generally considered very satisfactory (Hensher & Johnson,
1981). At each step, McFadden's Rho-squared is significant
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partialled model, .245, indicating a satisfactory model.
Given that the model is significant, it can be concluded
that at least one of the predictors has a significant impact
on at least one of the LOGITs (Demaris, 1992).
The next area of concern is the significance of the
sets of variables. The steps were tested for predictive
impact using the G-Statistic which is twice the difference
in the log likelihoods of the new and previous steps (Hosmer
& Lemeshow, 1989). The G-statistic has a Chi-square
distribution with the degrees of freedom equal to the number
of parameters in the new step. Using this statistic, steps
1 through 5 are significant. Steps 6 and 7, which are
composed of the interaction terms, are not significant.
These tests of the steps now provide the latitude to test
the individual predictors within the significant steps.
Analysis of Predictors
In addition to the analysis of the predictive efficacy
of the model, it is important to analyze and present the
predictive capabilities of each individual independent
variable. The fact that the overall model is significant
allows the testing of individual variables within the sets
that are significant. In a hierarchical set regression
analysis, it is appropriate to test the estimates for
significance as they come into the model if the overall set
is significant (Cohen & Cohen, 1983). This technique allows
140
for the testing of the proposed hypotheses. The estimates
attained for the variables as the set enters the analysis
represent the total effects of the variables and the fully
partialled model indicates the direct effects of the
variables (Cohen and Cohen, 1983) .
The analysis was constructed so that the reference
group is the corporate managers. Two separate LOGIT
regressions were estimated at each step of the analysis.
The first LOGIT compares the entrepreneurs to the managers.
The second LOGIT compares the small business owners to the
managers. A comparison of the two LOGITs to each other,
thereby comparing entrepreneurs and small business owners,
is provided later in the analysis.
The results of the hierarchical set multinomial LOGIT
regression are displayed in Table 11. In addition to the
estimates (B) for each variable, the standard error (SE), t-
statistic (t), p-value (g) and the change in estimate
(change in B) is provided for each step. In each step, the
LOGIT for the entrepreneur (Entrep) is provided first,
followed by the LOGIT for the small business owners (SBO).
It should also be noted that the p-values for the variables
achievement motivation, risk taking and innovation have been
cut in half to conduct the one-tailed tests suggested by the
directional hypotheses incorporating those variables.
Additionally, the p-values are presented to three decimal
points as provided by Systat. P-values marked by * are
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150
significant at an alpha value of .05, while p-values marked
by ** are signficant at an alpha value of .10.
Tests of Individual Demographics and Type of Organization
The first area of interest in assessing the
significance of the predictors is the covariates which
represent the control variables. The only variable which is
significant in the set of individual demographic predictors
for entrepreneurs is education. Entrepreneurs exhibit a
significantly lower (t = -2.69, p =.007) education level
when compared to managers. Alternatively, small business
owners had scores significantly different from managers in
two of the variables. Small business owners were also
significantly less educated than managers (t = -4.09, p <
.0001), as well as older than managers (t = 5.17, p <
.0001). No significant differences in race or gender were
found for either group relative to managers.
Two of the organization type variables were significant
in the second step. Both entrepreneurs (t = 3.223, p =
.001) and small business owners (t = 3.20, p = .001) are
significantly more likely to be involved in retail
organizations than are managers. Conversely, managers are
significantly more likely than both entrepreneurs (t = -
3.02, p = .002) and small business owners (t = -6.41, p <
.0001) to be associated with organizations involved in
manufacturing.
151
Also of interest are the changes in the estimates for
age and education when the type of organization was entered
into the analysis. The values of the estimates for age in
the entrepreneur group and the estimates for both age and
education in the small business owner group increased in
step 2. This indicates suppression with these variables and
the set of variables representing the type of organization.
Hypothesis Tests
The primary focus of the research was to test the
proposed hypotheses concerning the differences in the three
groups with respect to the psychological constructs of
interest. A summary of the results of the tests of the
hypotheses is provided in Table 12. Following is a
discussion of the tests for each of the hypotheses.
Differences Between Entrepreneurs and Managers.
Hypotheses la, 2a and 3a posited that entrepreneurs would
exhibit higher scores on achievement motivation, risk taking
and preference for innovation, respectively, than would
corporate managers. Achievement motivation was strongly
significant (t = 4.26, p < .0001) in discriminating between
the two groups. Entrepreneurs also exhibited a
significantly higher level of preference for innovation (t =
3.54, p < .0001), as well as a significantly higher
propensity for risk taking (t = 4.86, p < .0001) as compared
to managers. These results support hypotheses la, 2a and
3a.
152
Table 12
Summary of Tests of the Hypotheses
Hypothesis Results
Hla: Entrepreneurs will demonstrate a greater S need for achievement than will corporate managers.
Hlb: Small business owners will demonstrate a NS greater need for achievement than will corporate managers.
Hlc: Entrepreneurs will demonstrate a greater S need for achievement than will small business owners.
H2a: Entrepreneurs will exhibit a higher risk S taking propensity than will corporate managers.
H2b: Small business owners will exhibit a higher S risk taking propensity than will corporate managers.
H2c: Entrepreneurs will exhibit a higher risk taking S propensity than will small business owners.
H3a: Entrepreneurs will display a higher preference S for innovation than will corporate managers.
H3b: Small business owners will display a higher NS preference for innovation than will corporate managers.
H3c: Entrepreneurs will display a higher preference S for innovation than will small business owners.
S = Supported NS = Not Supported
153
The parameter estimates also changed as variables were
added to the analysis. For instance, when preference for
innovation was added to the model, the estimate for
achievement motivation fell, but remained significant.
Also, when risk taking was added to the model, the estimates
for both preference for innovation and achievement
motivation dropped again, but also remained significant.
These declines in the estimates of the previously entered
variables suggests redundancy among the variables. This is
not unexpected given the high intercorrelations among these
three variables.
When the interaction term for achievement motivation
and risk taking was added to the model, the estimates for
both risk taking and achievement motivation increased, and
they remained significant. The estimate for preference for
innovation did not change; however, the P-Value for
innovation was pushed upward. Moreover, when the preference
for innovation and risk taking interaction was added to the
analysis, a marked change occurred in the innovation
variable. The main effect for preference for innovation, as
previously shown, was significant. Yet, upon the entry of
the interaction term, preference for innovation became
nonsignificant (t = .77, p = .22). This suggests that some
of the importance that was originally attached to the main
effect of preference for innovation is actually attributable
154
to the interaction between preference for innovation and
risk taking.
Differences Between Small Business Owners and Managers.
Hypotheses lb, 2b and 3b posited that small business owners
would exhibit higher scores on achievement motivation, risk
taking and preference for innovation, respectively, than
would corporate managers. The results support only one of
these hypotheses. No significant differences between small
business owners and managers were found for achievement
motivation (t = .20, jo = .422), nor for preference for
innovation (t = .97, g = .165). Yet, the results supported
the hypothesis that small business owners tend to exhibit
higher risk taking than do managers (t = 3.78, p < .0001).
Some interesting changes occurred in the estimates of
the variables as new variables were entered into the
analysis. For example, the estimated coefficient for
achievement increased when preference for innovation was
added to the model, indicating suppression. When risk
taking was added, the estimated coefficients for both
achievement motivation and preference for innovation fell.
This suggests redundancy vis-a-vis these two variables and
risk taking.
The addition of the two interaction terms also produced
interesting results in this LOGIT. Although neither the
step nor the interaction term for risk taking and
achievement motivation is significant, when it was added to
155
the analysis, the main effect for risk taking became
nonsignificant (t = .84, p = .202). This phenomenon
suggests that some of the variance which was attributed to
risk taking in the previous step is actually attributable to
the interaction of risk taking with achievement motivation.
This may indicate a lesser importance for risk taking in
small business owners due to the effect of the interaction.
The interaction term for risk taking and preference for
innovation was significant at alpha = .10 (t = .01, p =
.085), but the step was not significant, disallowing any
interpretation of the interaction term. Yet, when this
interaction was included in the final step, the estimate for
the main effect of preference for innovation increased and
became significant (t = -1.72, p = .043). This would
suggest that the pure effect of preference for innovation is
negative for small business owners. Also, the introduction
of this interaction changed the signs of the estimates for
both preference for innovation and risk taking, indicating a
confounding effect.
Differences Between Entrepreneurs and Small Business
Owners. Hypotheses 3a, 3b and 3c predicted that
entrepreneurs would exhibit higher scores on achievement
motivation, risk taking and preference for innovation,
respectively, than would small business owners. The testing
of this stream of hypotheses requires a comparison of the
156
two groups through a series of Wald tests. The results of
the Wald tests are provided in Table 13.
Age is the only significant difference in entrepreneurs
and small business owners (Chi2 = 5.75, p = .016) in terms
of the set of individual demographic variables. This test
indicates that the entrepreneurs were, on average, younger
than the small business owners. No significant differences
were found with regard to gender, education nor race among
the two groups. Neither were any significant differences
indicated between the two groups with regard to the type of
organization.
The entrepreneurs and small business managers did
differ on the main independent variables. Entrepreneurs
displayed significantly higher scores on achievement
motivation than did the small business owners (Chi2 = 10.75,
E < .0001). This finding supports hypotheses lc. Also,
entrepreneurs evinced significantly higher scores on risk
taking than did the small business owners (Chi2 = 5.42, p =
.020). Additionally, entrepreneurs were also higher on
preference for innovation than were the small business
owners (Chi2 = 9.56, p = .002). These findings provide
support for hypotheses 3a, 3b and 3c.
Wald tests are also included for the two interaction
terms, although neither of the steps (6 and 7) for the
interaction terms were significant. The results also show
that neither of the interaction terms is significant in
157
Table 13
Results of Wald Tests Across Entrepreneurs
and Small Business Owners8
Step Variables Chi2 E
1 age 5.75 .016* education . 10 .754 white .68 .408 black .15 .695 gender .03 .859
a one degree of freedom for each test * significant at alpha=.05
158
predicting a difference between entrepreneurs and small
business owners.
Elasticities. Elasticities are another tool for
assessing the predictive efficacy of the variables in the
model. Elasticities indicate the percentage change in the
probability of being classified in a given group given a
percentage change in the value of a given predictor. The
individual variable elasticities are shown in Table 14. The
elasticities for each variable are taken from the step where
the variable was introduced to the model, thereby producing
an elasticity coefficient for the total effect of the
variable.
According to the elasticities, the best predictor of
being classified as an entrepreneur is achievement
motivation. A given percentage change in the value of
achievement motivation produces the largest percentage
change in the probability of being classified as an
entrepreneur. The elasticities for the preference for
innovation and risk taking variables also indicate good
classification power.
Chapter Summary
The results of the analysis of the data for this study
were presented in this chapter. The analysis of the data
was multifaceted. An analysis of the characteristics of the
sample indicated that the sample is comparable to other
research samples, and is likely indicative of the
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population. Also, a confirmatory factor analysis of the
criteria used to categorize the dependent variable was
conducted. The results of this factor analysis can be
considered as a partial validation of the theory predicting
differences among small business-owner managers, and
provides an impetus for partitioning them into two groups,
entrepreneurs and small business owners.
The crux of the analysis involved determining and
evaluating a hierarchical set multinomial LOGIT regression
model, and testing the hypotheses. A model with significant
predictive efficacy was produced. Support was found for
including age, education and type of business as covariates.
The testing of the hypotheses suggested that
entrepreneurs are significantly higher in their achievement
motivation, preference for innovation and risk taking
compared to both small business owners and corporate
managers. Support was also evident for small business
owners having a higher risk taking propensity than corporate
managers. Interaction terms for achievement motivation and
risk taking, and preference for innovation and risk taking
were not statistically significant. The best model,
therefore, would exclude these interaction terms. Yet,
while the tests of the interactions did not indicate
moderation, the evidence did suggest that the interaction
terms were confounders.
CHAPTER V
EVALUATION OF RESULTS
The final chapter is devoted to a discussion of the
results of the study. Elements of this discussion include
an explanation of the results and the implications of the
findings. Furthermore, both the methodological and
practical limitations of the research are delineated and
analyzed. Finally, both methodological directions and topic
areas for future research are suggested.
Discussion of Results
While many of the expectations conveyed in the
hypotheses were supported, the results did not support all
of the hypotheses. In terms of the entrepreneurs, the
findings were consistent with the majority of the
literature. It is with the small business owners, who were
expected to be more like the entrepreneurs than like the
managers, where inconsistencies are apparent. The following
discussion of the results is organized around the variables
of interest in the study.
The individual and firm demographics were primarily
included in the study to control for extraneous sources of
variance. Nonetheless, these variables provided some
interesting insights into individuals in the three
161
162
categories. The entrepreneurs tended to be younger than the
small business owners in this study. Entrepreneurs have
typically been found to be younger when compared to other
groups. Nevertheless, the fact that entrepreneurs are
younger than the small business owners is somewhat
surprising, given the discussion of the experience factor in
entrepreneurship. Much attention has been focused on the
backgrounds of small business owner-managers, and experience
is typically one of the factors associated with
entrepreneurial success. It appears questionable how
significant the experience factor is in new venture creation
and/or growth if the entrepreneur is relatively youthful to
the point of diminished meaningful business experience.
It is interesting to speculate how the age difference
might affect the planning and goals in the organizations
which are owned by these two types of individuals. It is
possible that the relative youth of the entrepreneurs is a
factor in determining their goals of profit and growth for
their organizations. The older, maybe more entrenched,
small business owners could be in a stage in their lives
which engenders a focus on more constrained goals such as
family income. Stability appears to be more important to
the small business owners and this possibility is also
reflected in their risk profiles. The higher propensity for
risk taking in the entrepreneurs may also be a partial
163
determinant of a focus on profit and growth, rather than the
relatively more conservative goal of family income.
Both the entrepreneurs and the small business owners
are less educated than the managers. This result is
relatively predictable. In most organizations, an education
is a prerequisite to assuming managerial positions.
Alternatively, a lack of education may be a barrier to
becoming a business owner only if it affects the ability to
acquire the necessary capital to enter the business.
Moreover, for managers, the additional time spent on
education might influence an individual's desire for
stability rather than the risks associated with new venture
creation. In fact, education could conceivably influence a
manager's perceptions of risk and risk taking propensity,
making the relatively more predictable managerial position
more psychologically comfortable.
The results concerning the types of business in which
the individuals were involved are also straightforward. The
entrepreneurs and small business owners were mostly
associated with firms engaged in retail businesses. The
managers were more likely to be associated with
manufacturing organizations. The capital requirements
demanded by participation in manufacturing organizations may
largely preclude their establishment by owner-managers.
Retail organizations are potentially less restrictive for
the owner-managers to enter. Education may also influence
164
the type of organization because owning and operating a
manufacturing firm would probably demand more education,
particularly in technical areas.
The nucleus of the study was the investigation of the
psychological constructs. Many of the assertions made in
the literature were confirmed in this study. It appears
that the psychological constructs in this study are elements
of the entrepreneurial vision of the small business owner-
manager. A key element of entrepreneurship is opportunity.
These psychological constructs appear to be important to the
process of seeking and exploiting entrepreneurial
opportunities. Moreover, the results point to marked
differences in the psychological profiles of the small
business owner-managers.
As hypothesized, the entrepreneurs were higher in
achievement motivation, risk taking propensity and
preference for innovation than were the managers. This is
consistent with the classical profile of the entrepreneur.
The archetypal portrait of the entrepreneur is an individual
who is highly driven to succeed. This motivation is also
connected with a particular risk taking posture. The
entrepreneur assumes the risk of the initiation and
operation of the organization. Concomitantly, the
entrepreneur sparks innovation by mutating the economic
characteristics of products, markets or industries. Decades
of research and theorizing about the entrepreneur indicate
165
the confluence of these factors in distinguishing
entrepreneurs from their corporate counterparts. The
results of this study reinforce this conceptualization of
the entrepreneur as an achieving, creative risk taker.
Notably, this profile of those generally labeled as
entrepreneurs is not consistent across both of the types of
small business owner-managers in this study. Small business
owners present a different portrait. The only
characteristic which differentiated the small business
owners from the managers was the small business owners1
relatively higher proclivity toward taking risks. This
outcome suggests that, more than any other factor, it is
risk taking that distinguishes the small business owner-
manager from the corporate manager. There is a measure of
riskiness inherent in business ownership which is not
necessarily present in the managerial role. This propensity
to take more risks appears to delineate between the choice
of business ownership and the choice to assume a managerial
position.
The differences exhibited between the small business
owners and the entrepreneurs provide the most interesting
outcome of the research. Not only did the entrepreneurs
differ dramatically from managers, but they also differed
from small business owners. Small business owners are less
risk oriented and are not as highly motivated to achieve as
are entrepreneurs. Small business owners also lack the same
166
degree of innovativeness as entrepreneurs. Given the
relative significance of innovativeness in entrepreneurs, it
would appear that creativity necessitates extended risk
because it entails coping with the potential outcomes which
are associated with untried venues. Small business owners
appear to lack this coalition of creativity and risk taking.
These findings logically coincide with the differences
in the goals of small business owners and entrepreneurs.
Psychological antecedents appear to influence
entrepreneurial aspirations. Small business owner-managers
have goals which are related to their personalities.
Entrepreneurs exhibit the psychological profile that is
consistent with their goals of growth and profit, and the
use of systematic planning. It is intuitively appealing
that high achievement motivation, high risk taking and a
proclivity to innovate are coupled with an emphasis on
profit and growth. Alternatively, the psychological
predispositions and actions of small business owners are
more attuned to their personal goals and family income. The
small business owner appears to be a conceptual link between
the entrepreneur and the manager, exhibiting characteristics
that are likened more to the manager than to the
entrepreneur. These findings have a plethora of
implications.
167
Theoretical Contributions and Implications
If confirmed by future research, these findings have
important implications. From a theoretical perspective, if
indeed the individual entrepreneur is the most salient unit
of analysis in entrepreneurship research and theory
(Lachman, 1980; Mitton, 1989; Herron & Sapienza, 1992), then
a more complete understanding of the entrepreneur is a
necessary antecedent to the development of a more complete
understanding of the process of entrepreneurship. These
results reinforce the assumption that human volition is
essential to a model of entrepreneurship (Bygrave & Hofer,
1991). The results of this study suggest that a personal
predisposition toward entrepreneurship may be the foundation
for a more rigorous, robust model of the entrepreneurial
process.
This research lies at the crux of two major theoretical
debates. For decades, disagreement has existed in the field
of psychology concerning the determinants of behavior. This
debate has been the genesis of a parallel flurry of
contention in the field of entrepreneurship concerning
whether to study the entrepreneur or the behaviors of the
entrepreneur. The results of this study suggest that
studying traits and behaviors may not be mutually exclusive.
This study incorporates elements of both perspectives.
While the focus was on identifying the significance of
personality constructs, the inclusion of goals and planning
168
practices in the study links psychological antecedents with
individual behavior. The results provide numerous insights
into the nature of different types of small business owner-
managers relative to corporate managers.
Individuals who evidence the significant
characteristics and behaviors will not necessarily found new
ventures. It is likely that there are triggering events
which cause an entrepreneurial predisposition to be realized
into action. Yet, a more complete understanding of the
entrepreneur, coupled with a broader theoretical framework,
provides the basis for understanding which triggering events
are significant and how they bear upon the individual.
Numerous types of entrepreneurs have been identified by
researchers, but the literature is mixed concerning the
validity and usefulness of distinguishing between different
types of small business owner-managers. The results of this
study suggest that taxonomies of entrepreneurial types could
be useful in more fully understanding the entrepreneur.
Furthermore, this analysis lends credence to those who argue
that the distinctions which have been made between
entrepreneurs and small business owners are more than a
question of semantics. This study suggests that a profit
and growth orientation, and the utilization of strategic
management practices do differentiate entrepreneurs from
small business owners. Risk propensity, achievement
motivation and preference for innovation, variables
169
ubiquitous in their connections with the entrepreneur, are
also useful in making this distinction.
The results of this study also reinforce the
differentiation that is made between entrepreneurship and
small business management (Luchsinger & Bagby, 1987).
Luchsinger and Bagby discussed the potential for firms
headed by entrepreneurs to be larger and associated with
higher profit potential and higher risk than the
conventional small business. Given the entrepreneurs'
psychological predisposition, goals and planning practices,
their association with larger, growth oriented firms is not
a surprising outcome. The confluence of factors associated
with small business owners would tend to link them with
organizations which are more static. The more these two
groups of owner-managers are understood, the more likely it
will be to meaningfully circumscribe the areas of
entrepreneurship and small business management.
Potentially the most important implication from this
study is for research methodology in entrepreneurship. To
be complete, research definitions of entrepreneurs must
extend beyond new venture creation. It is important to
fully circumscribe the sampling frame. Incomparable
sampling frames may be the reason for the morass of
inconsistencies in this line of research. One sample of
small business owner-managers may be markedly different than
another sample. This makes comparability of research
170
problematic and hinders theoretical development in the
field. Hence, by launching into a study of small business
owner-managers, it behooves the conscientious researcher to
fully describe the sampling frame. Only in this way may a
clear, acceptable definition of the entrepreneur actually be
developed. A distinct operational definition of the
entrepreneur would serve to enhance theoretical rigor by
improving methodological precision, particularly in defining
the characteristics of appropriate sampling frames.
The results of this study indicate the value of
studying the entrepreneur. A myriad of characteristics have
been associated with the entrepreneur. Additional
characteristics may be important in predicting or indicating
entrepreneurial endeavors. If the characteristics can be
successfully linked with entrepreneurial behaviors, the
potential for learning how to enhance the practice of
entrepreneurship and its success would be greatly improved.
In summary, this study may be the first step in the
reconciliation of the inconsistent findings of past
research, and may thus lead to progression in the field of
study. Moreover, an individual's psychological
characteristics will affect behaviors in the business, and
presumably, the outcomes of the business. Additionally, the
predictors of entrepreneurship identified here can be used
to enhance both theory and practice through additional
171
research. These findings suggest a multitude of additional
directions for supplementary research.
Limitations of the Research
As with all research, there are potential limitations
associated with this study. It is important to acknowledge
the limitations of the research. These limitations are of
two genres: limitations imposed by the research problem and
limitations associated with the research methodology. Of
these two types, the limitations of primary concern are
those which are methodological in character, particularly
those inherent in a survey design and the concomitant
reliance on self-report data. This concern is due to the
fact that methodological limitations might restrict the
usefulness of the research.
Methodological Limitations
The analysis of the methodological limitations is
primarily guided by the work of Cook and Campbell (1979) and
the applications to correlational research provided by
Mitchell (1985). The methodological issues are presented
according to the major categories of research validity.
Specifically, these areas include construct validity,
statistical conclusion validity, internal validity and
external validity. Notably, these validity issues are
interrelated. Issues in the research which overlap one or
172
more of these areas of validity will be analyzed primarily
under the area where the issue is most applicable.
Statistical Conclusion Validity. There are potential
issues associated with the findings given the specified
alpha level and the obtained variances. Of paramount
importance is the lack of control over the administration of
the questionnaire and the conditions during response. The
lack of standardization in implementing the questionnaire is
a problem, as are sources of possible error variance due to
factors associated with the settings of the respondents.
Both factors could contribute to increased error variance.
While the potential for these effects is recognized, they
are not believed to be significant for this study due to the
relatively high reliability, both internal consistency and
stability, of the measures and the acceptable reliability
estimates in this study.
Other factors associated with statistical conclusion
validity do not appear problematic. The size of the sample
afforded high statistical power in the testing of the
hypotheses. Nonetheless, significant differences between
small business owners and managers were not obtained for
risk taking propensity and preference for innovation. A
post hoc power analysis indicated that the failure to find
significance in these hypotheses was not a function of the
sample size for an effect size of .10. Therefore, the
validity of these findings appears satisfactory.
173
The logistic regression model is robust with regard to
the violation of most assumptions. The utilization of sets
and protected t-tests reduced the error rate problem and the
potentially biasing effects of multicolinearity in the
independent variables. Finally, appropriate model
specification resulted in model parsimony and a reduction in
the potential bias of the estimates.
There are limitations associated with the confirmatory
factor analysis. While the theoretical guidelines for the
analysis were supported, statistical hypothesis testing was
not possible. This limits the definitiveness of the factor
analysis. Although, it should be recognized that
substantive interpretation of the factors is not necessarily
dependent upon statistical significance because a
statistically significant factor may not always be
identified correctly in terms of the empirical phenomena
(Anderson, Basilevsky & Hum, 1983) . Nonetheless, the factor
results should be subsequently verified by second-order
factor analysis (Kerlinger, 1986) and more sophisticated
confirmatory factor techniques which use covariance
structure analysis (Comrey & Lee, 1992).
Internal Validity. There is a possibility that there
is an alternative explanation of the identified
relationships between the variables in this study. As with
any cross-sectional, correlational design, there was a lack
of control over the independent variables. It is possible
174
that spurious relational patterns have been identified and
that the direction of potential causal influence was
misconstrued, presenting a host of speculative rival
plausible hypotheses.
One area of obvious concern is selection. The
researcher had no control over who completed the survey. It
is conceivable that those respondents who participated in
the study were patently different from those who did not
participate. Most of the respondents had some personal
association with the individual who sought their
participation in the study. This may have introduced bias
into the study through the convenience method of sampling.
Alternatively, the method of data collection produced a high
response rate. Because nonresponse was low for a survey
design, it minimizes the potential distortions introduced by
the special characteristics of the respondents. Although
nonresponse was minimized in this study, it is still an area
of concern. It is feasible that selection may have
adversely influenced the internal validity of the study.
Nonetheless, potentially of more concern are alternative
hypotheses resulting from possible confounds.
A large number of uncontrolled variables are inherent
in the phenomenon itself, as well as the research
circumstances. The potential interaction of these variables
is unpredictable. Despite this situation, the lack of
control over the potential confounds may not be problematic
175
in this study for a couple of reasons. The first reason is
the model specification for the study. Individual
demographic factors which might have affected the
hypothesized relationships were included in the design of
the study and controlled. The second explanation is the
diversity and size of the sample.
The sample includes individuals from a large variety of
situations, thereby including individuals with different
amounts and combinations of the uncontrolled variables. By
mixing them all, chance imbalances may have been cancelled
(Isaac & Michael, 1990), thereby exerting some level of
control over extraneous variables. The size of the sample,
approaching that of a random sample, is likely to have
positively influenced the internal validity of the study, as
well as enhancing the external validity of the findings.
Nonetheless, the lack of control over the variables remains
a potential limitation and poses the most significant threat
to internal validity.
Construct Validity. Another issue is the degree to
which the operationalized variables in this study measure
the constructs of interest. Response sets, hypothesis
guessing and common method variance represent the most
important potential threats to construct validity in this
study. Notably, the instruments used in this research were
carefully constructed to maximize content saturation and to
avoid problems associated with response sets. Also, the
176
instruments have repeatedly been demonstrated to have
divergent and convergent validity. Additionally, the
privacy of the response situation would tend to minimize the
likelihood of evaluation apprehension (Dillman, 1983). For
these reasons, it is not believed that instrumentation poses
a vital question of validity in this study.
Hypothesis guessing on the part of the respondents
could also present a construct validity problem. While
hypothesis guessing is possible, it is not probable given
the nature of the study. Moreover, the instrumentation is
such that hypothesis guessing would not likely result in
serious concerns about validity. Potentially of more
significance is common method variance.
Only one method of measuring each of the variables of
interest was used, precluding triangulation on the referent.
Moreover, the data for the independent and dependent
variables were collected from the same respondents, sparking
concerns about single source bias. Under these
circumstances, any defect in the source contaminates all
motivation could be a salient issue in these circumstances.
Also, differences in risk taking and innovativeness may also
produce conflict in venture teams. More research is
necessary to identify the psychological associations with
conflict and the means of resolving those conflicts.
191
Psychological factors might also influence venture team
performance.
Modes of Business Entry. There are several means by
which an individual might become the owner-manager of a
venture. These vehicles to ownership include founding the
business, buying the business, franchising or inheriting the
business. Research suggests that there may be individual
differences which affect these different avenues to
ownership. Begley and Boyd (1986, 1987) discovered that
founders score significantly higher than nonfounders in
achievement motivation and risk taking propensity.
Comparable evidence has also been shown by Hull et al.
(1980), who found that owners who had taken part in creating
the business had a higher risk taking propensity than those
who were owners, but had not taken part in the creation of
the business. The need for achievement was not a
distinguishing factor between the two groups. More research
is necessary to determine how psychological factors are
associated with modes of ownership. Understanding more
about differences in individuals who pursue business
ownership through different modes may produce results that
are useful in fostering entrepreneurship.
Planning in Small Businesses. Robinson and Pearce
(1984) noted that planning in small businesses was not well
understood. The planning process in small firms, its
antecedents and outcomes remains imperfectly understood.
192
Yet, formal planning improves performance in small firms
(Schwenk & Shrader, 1993). Planning in small firms is
dominated by the owner-manager, and evidence suggests that
the characteristics of the owner-manager influence planning.
Carland, Carland and Aby (1989) found that owners of small
businesses who had formal plans had higher achievement
motivation, higher risk taking propensity and higher
preference for innovation than did those who planned
informally or did not plan at all. This suggests that
psychological factors influence the existence and nature of
planning in small firms. Moreover, evidence suggests that
the entrepreneur's personality affects information sources
(Welsch & Young, 1982) which might influence the content of
strategic decisions.
The study of strategic management processes in small
organizations in indispensable. Those labelled
entrepreneurs in this study engaged more extensively in
strategic planning than did the small business owners. It
is important to learn more about how psychological factors
influence the process and outcomes of strategic thinking in
small organizations. If entrepreneurs are more strategic in
their planning, much is to be learned from the process of
planning in these organizations, and the commensurate
effects on performance. Investigations of this type could
produce fruitful research in both entrepreneurship and
193
strategic management, and be invaluable to the foundation of
our economic system, the entrepreneur.
Chapter Summary
The purpose of this study was to determine if the
achievement motivation, risk taking propensity and
preference for innovation differed between small business
owner-managers and corporate managers. The observed
differences were discussed in the chapter. Moreover, the
implications of the research, both methodological and
theoretical, were detailed.
There are limitations associated with this research.
Both theoretical and methodological limitations were
discussed. Of the two types of limitations, the
methodological limitations are of primary concern. The
discussion of these limitations entailed scrutiny of the
statistical conclusion, construct, internal and external
validities of the study. It is believed that the potential
areas of concern do not pose significant threats to the
usefulness of the research.
Finally, directions for additional research were
proposed. The extended areas for subsequent inquiry are
aimed at identifying and refining components of the
entrepreneurial personality, and determining how the factors
influence entrepreneurial behaviors and outcomes.
Inculcating entrepreneurial behaviors in all organizations
194
may be the key to responding to the competitive challenges
with which modern organizations must contend.
APPENDIX
QUESTIONNAIRE
195
196
Major Elements of the Questionnaire
The following questions were asked of all respondents:
Company name and address
Type of company: [ ]retail, [ ]wholesale, [ ]manufacturing, [ ]construction or [ ]service
Sales range: [ ]less than $100,000, [ ]$100,000-$500,000, [ ]$501,000-$1,000,000 or [ ]over $1,000,000
Number of employees: [ ]under 10, [ ]10-50, [ ]51-100, [ ] 101-250 or [ ]over 250
Respondent1s sex, age and race
How many years of formal education have you had?
Date business was established
How many levels of management are there in this business?
The following questions were asked of all small business owner-managers:
Were you a principal in the establishment of this business? [ ]yes or [ ]no. If no, [ ]did you buy it or [ ]inherit it?
Is this the first business which you have started? [ ]yes or [ ]no. If no, how many other businesses have you owned?
What were your principal purposes for establishing this business? [ ]Profit and growth, or [ ]provide family income
Do you have a written plan for the development and growth of the business? [ ]yes or [ ]no. If no, do you have a formal unwritten plan for development and growth? [ ]yes or [ ]no
All respondents were also asked to complete the Achievement Scale of the PRF and the Risk Taking and Innovation Scales of the JPI.
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