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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.

 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
   TEST NAME     Effect Size      Noncent.       Power
    (All)               .069       14.638            .93
   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
   Boxs M =                             7.65869
   F WITH (10,175842) DF =              .74926, P =   .678 (Approx.)
   Chi-Square with 10 DF =             7.49305, P =   .678 (Approx.)
   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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