Important factors which predict entrepreneur’s perception in business risk

  • Received April 20, 2019;
    Accepted May 28, 2019;
    Published June 19, 2019
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  • Article Info
    Volume 17 2019, Issue #2, pp. 415-429
  • Cited by
    8 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

This paper seeks to examine the role of factors originated from outside (economic, political, competitive environment and relationships) and within (entrepreneur’s attitude) the organization on the business risk perceived by entrepreneurs. To test the hypothetical relationships, an ordinal regression with two link functions was applied on an original dataset of 641 small and medium-sized enterprises (SMEs) operating in Slovakia and Czech Republic. The analysis revealed that not only economic factors can predict business risk, but along with them are political and competitive environments, relationship with supply chain actors and entrepreneur’s attitude. Consistent with prior research, it is found that an unstable economic environment leads the business to expose themselves to business risk. Also, a friendly regulation framework and quality education contribute significantly to reducing the level of risk. The research triggers the interest of policymakers who design policies aimed at improving the business environment by reducing the level of risk that firms face in doing business. Also, this paper is useful for managerial perspective, since entrepreneur attitude was found to be a predictor of business risk.

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    • Table 1. Descriptive statistics of the dependent variable and Mann-Whitney test
    • Table 2. Mean, standard deviation, Pearson correlation and Cronbach’s alpha
    • Table 3. Link functions
    • Table 4. Mean and standard deviation by risk levels for each construct
    • Table 5. Model fit, goodness-of-fit and test of parallel lines for two types of ordinal regressions
    • Table 6. Results of ordinal regression – link function: cauchit
    • Table 7. Results of ordinal regression – link function: complementary log-log