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TABLE 6
Effects Of Motivation On Success 204 cases accepted. 0
cases rejected because of out-of-range factor values. 137
cases rejected because of missing data.
CELL MEANS AND STANDARD DEVIATIONS
Variable .. INCOME
FACTOR
CODE
Mean Std.
Dev.
N
PSHPULL
1 (push)
3.690
1.923 113
PSHPULL
2 (pull)
4.143
1.841 91
For entire
sample
3.892
1.896 204
Variable .. EMPLTRND Mean
Std. Dev. N
PSHPULL
1 (push)
3.142
1.558 113
PSHPULL
2 (pull)
3.582
1.564 91
For entire
sample
3.338
1.572 204
Variable .. SATISFY Mean
Std.
Dev.
N
PSHPULL
1 (push)
2.487
.917 113
PSHPULL
2 (pull)
3.000
1.085 91
For entire
sample
2.716
1.026 204
Variable ..
$SATISFY
Mean Std.
Dev.
N
PSHPULL
1 (push)
2.788
1.095 113
PSHPULL
2 (pull)
3.198
1.222 91
For entire
sample
2.971
1.169 204
MULTIVARIATE EFFECT SIZE AND OBSERVED POWER at .1000
Level
TEST NAME Effect
Size
Noncent. Power
(All)
.069
14.638
.93
UNIVARIATE HOMOGENEITY OF VARIANCE TESTS
Variable .. INCOME Bartlett-Box F(1,118586)
= .18632, P= .666
Variable .. EMPLTRND Bartlett-Box F(1,118586)
= .00163, P= .968
Variable .. SATISFY Bartlett-Box F(1,118586) =
2.83049, P= .093
Variable .. $SATISFY Bartlett-Box F(1,118586) =
1.19740, P= .274
MULTIVARIATE TEST FOR HOMOGENEITY OF
DISPERSION MATRICES
Boxs M
=
7.65869
F WITH (10,175842) DF
=
.74926, P = .678 (Approx.)
Chi-Square with 10 DF
=
7.49305, P = .678 (Approx.)
EFFECT .. .MOTIVATE
Multivariate Tests of Significance (S = 1, M = 1, N
= 98 1/2 ) (Note.. F statistics are exact)
Test
Name
Value Exact
F Hypoth.
DF Error DF
Sig. of F
Wilks
. 93148
3.65942
4.00
199.00
.007
Univariate F-tests with (1,46) D. F.
Variable Hypoth. SS
Error SS Hypoth.
MS Error
MS
F Sig. of
F Power
INCOME
10.32530
719.30215
10.32530
3.56090
2.89963 .090 . 1785
EMPLTRND
9.79538
491.86638
9.79538
2.43498
4.02277 .046 .63378
SATISFY
13.27972
200.23009
13.27972
.99124 13.39710
.000 97711
$SATISFY
8.48131
268.84222
8.48131
1.33090
6.37261 .012 80504
governmentally organized ?association?, however, as indicated
in the interviews, many entrepreneurs perceive no benefit to
themselves or their business from this association; they see it
as yet another vehicle for the government to collect additional
taxation from businesses. Some entrepreneurs, however,
stated that while the chamber was not a benefit, their contacts
within the university system and with professional colleagues
contributed to their business abilities. The data supports
the indications derived from the interviews, revealing a split
distribution of professional and personal networks.
4% of the respondents indicate no contact either through
associations or with other professionals, 40% indicate minimal
contact with the mandated chamber, 15% limited contact beyond the
association, and 41% indicate high levels of personal and
professional contact, including multiple association memberships
and frequent professional interaction. The data
reveals a significant based upon
the motivational orientation of the
entrepreneur (F value = 4.14710, sig. =
.043), showing that pull-motivated entrepreneurs utilize
associations and professional contacts to a greater extent than
push-motivated entrepreneurs.
Pull-motivated and push-motivated entrepreneurs also exhibit
differing levels of technology in their ventures.
Entrepreneurs have frequently been defined in terms of the
innovation of technology (e.g. Bird, 1989), or categorized
according to their level of technology (e.g. Armington, et al.,
1984). While policy initiatives frequently focus on
attracting and developing innovative high-technology enterprise
through R&D promotion and assistance, entrepreneurial
researchers seldom measure levels of technology. Within
this study, three separate measures were utilized to yield a
single indicator of the firm?s level of technology. One was
a self-reporting question, wherein 50.5% of the valid responses
classified themselves as low-technology, 9% as mid-level
technology, and 40.5% as high-technology. The second means
of assessment measured the utilization of computers or other
forms of technology within the business on a 5 point likert
scale, with no utilization being a 1 and complete utilization
being a 5. The third measure is based on the percentage of
employees that are trained as engineers, scientists, or are
engaged in research and development work (Armington, et al.,
1984). These three measures were standardized and
combined to form a composite measure of level of
technology. As suggested by the exploratory study
(Solymossy, 1996), this measure is significantly influenced by
the nature of the motivation, (F value = 3.83564, sig =
.052). During interviews, several entrepreneurs stated that
they had departed from their field of training when forced to
begin a business (e.g. chemical engineering background; bed &
breakfast venture, or railroad engineer; restaurant venture).
This was supported by the data, which suggests that negative
situational influences may result in an entrepreneur seeking
lower-level technology ventures.
The entrepreneurs' confidence in the future of their businesses
likewise demonstrates a significant difference based upon
motivational orientation (F value = 4.01740, sig. = .047),
offering an intuitively reasonable indication that internally
motivated entrepreneurs exhibited higher levels of
confidence. This also of-fers indirect support to the
arguments for efficacy as a measure of entrepreneurial
orientation (Boyd and Vozikis, 1994), implying that having been
forced into entrepreneurship by environ-mental factors beyond the
individual?s control, the “pushed” entrepreneur remains
sensitive to the future potential of situational factors again
being beyond their control and adversely affecting the business.
Interpretation of the effects upon networking, technology, and
confidence is tentative, however, due to a low power (.64) caused
by 187 cases being deleted due to missing data points.
Multivariate analysis of 9 variables using 154 observa-tions,
while acceptable according to some scholars (e.g. Katchigan,
1982), will adversely affect power, thereby reducing statistical
confidence (Pehazur and Pedhazur, 1991; Tabachnick and
Fidell, 1989)
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