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Technology use and availability in entrepreneurship: informal economy as moderator of institutions in emerging economies

The Journal of Technology Transfer volume 41, pages 506–529 (2016)Cite this article

Abstract

This paper investigates the contextual influences of institutions on the use of latest available technologies by early stage entrepreneurs in emerging economies. Hypotheses are developed and then tested using multi-level modeling techniques on a dataset covering entrepreneurs in 20 emerging economies. We utilized 10,431 individual-level responses from the Global Entrepreneurship Monitor survey from 2002 to 2008 and complemented it with data on country-level institutions such as the size of a country’s informal economy, intellectual property rights (IPR) regimes obtained from the Index of Economic Freedom and inward foreign direct investment (FDI) from the World Bank Group. Results on the direct effects suggest that levels of FDI negatively influences the use of latest technology by entrepreneurs in emerging economies, while the moderation effects of informal economy suggest that as its size increases (1) the negative effects IPR on the use of latest technology by entrepreneurs strengthens, and (2) the negative effects of FDI on the use of latest technology strengthens. These findings support the overall proposition that the size of a country’s informal economy is an important moderator of institutional influences on technology use by entrepreneurs in emerging economies. More generally, the study proposes that institutions may not have the same effects on entrepreneurs in emerging economies that might be expected in developed countries, suggesting that future research should take the level of socio-economic development of a country into account when theorizing the role of institutions.

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Fig. 1
Fig. 2

Notes

  1. Data from only 20 countries were usable for all the variables and controls included in the regression models.

  2. In unreported robustness checks, we isolated nascent and new entrepreneurs following which we replicated our analyses on each of the two samples. We did not observe significant loss of generalizability of our findings. We chose to adhere to GEM’s operationalization of “early stage” entrepreneurs as nascent or new entrepreneurs and used them in a combined sample in all our analyses.

  3. In unreported robustness checks, we replaced the IPR index obtained from the Heritage Foundation with those from the World Economic Forum’s (2011) Global Competitive Index (GCI) Report, Fraser institute’s “Economic Freedom of the World” report (Gwartney et al. 2012) and GEM National Expert Survey. Our findings were generalizable across all of these sources but we chose to use IPR index from the Heritage Foundation because it offered data on IPR for the maximum number of countries common to the GEM survey.

  4. We used xtlogit—STATA 12.0 as the statistical software tool.

  5. Temporal variance in dependent variable was insignificant relative to country specific variance.

  6. To be able to meaningfully interpret and express graphically the interaction terms we use beta coefficients of the logistic regressions and not the odds ratios.

  7. Low and high informal economy in Figs. 1 and 2 represent (Mean − 1.5 S.D.) and (Mean + 1.5 S.D.).

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Authors and Affiliations

  1. College of Business Administration, Kansas State University, 101 Calvin Hall, Manhattan, KS, 66503, USA

    Saurav Pathak

  2. School of Business and Economics, Michigan Technological University, 1400, Townsend Drive, Houghton, MI, 49931, USA

    Emanuel Xavier-Oliveira & André O. Laplume

Authors
  1. Saurav Pathak
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  2. Emanuel Xavier-Oliveira
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Correspondence to Saurav Pathak.

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Pathak, S., Xavier-Oliveira, E. & Laplume, A.O. Technology use and availability in entrepreneurship: informal economy as moderator of institutions in emerging economies. J Technol Transf 41, 506–529 (2016). https://doi.org/10.1007/s10961-015-9423-x

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Keywords

  • Technology use in entrepreneurship
  • Institutions
  • Informal economy
  • Emerging economies
  • Multi-level modeling

JEL Classification

  • L26
  • O34
  • P33