Star entrepreneurs on digital platforms: Heavy-tailed performance distributions and their generative mechanisms
This study extends emerging theories of star performers to digital platforms, an increasingly prevalent entrepreneurial context. It hypothesizes that the unique characteristics of many digital platforms (e.g., low marginal costs, feedback loops, and network effects) produce heavy-tailed performance...
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| Vydáno v: | Journal of business venturing Ročník 39; číslo 1; s. 106347 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Inc
01.01.2024
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| Témata: | |
| ISSN: | 0883-9026, 1873-2003 |
| On-line přístup: | Získat plný text |
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| Abstract | This study extends emerging theories of star performers to digital platforms, an increasingly prevalent entrepreneurial context. It hypothesizes that the unique characteristics of many digital platforms (e.g., low marginal costs, feedback loops, and network effects) produce heavy-tailed performance distributions, indicating the existence of star entrepreneurs. Using longitudinal data from an online learning platform, proportional differentiation is identified as the most likely generative mechanism and lognormal distribution as the most likely shape for distributions of entrepreneurial performance in digital contexts. This study contributes theory and empirical evidence for non-normal entrepreneurial performance with implications for scholars and practitioners of digital entrepreneurship.
•Heavy-tailed performance distributions in digital contexts signify star entrepreneurs.•Low marginal costs, positive feedback loops, and network effects drive heavy tails.•Lognormal distributions characterize entrepreneurial performance on digital platforms.•Proportional differentiation is a key generative mechanism of star entrepreneurs.•Platform characteristics such as knowledge intensity can influence tail extremity. |
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| AbstractList | This study extends emerging theories of star performers to digital platforms, an increasingly prevalent entrepreneurial context. It hypothesizes that the unique characteristics of many digital platforms (e.g., low marginal costs, feedback loops, and network effects) produce heavy-tailed performance distributions, indicating the existence of star entrepreneurs. Using longitudinal data from an online learning platform, proportional differentiation is identified as the most likely generative mechanism and lognormal distribution as the most likely shape for distributions of entrepreneurial performance in digital contexts. This study contributes theory and empirical evidence for non-normal entrepreneurial performance with implications for scholars and practitioners of digital entrepreneurship.
•Heavy-tailed performance distributions in digital contexts signify star entrepreneurs.•Low marginal costs, positive feedback loops, and network effects drive heavy tails.•Lognormal distributions characterize entrepreneurial performance on digital platforms.•Proportional differentiation is a key generative mechanism of star entrepreneurs.•Platform characteristics such as knowledge intensity can influence tail extremity. |
| ArticleNumber | 106347 |
| Author | Gala, Kaushik Schwab, Andreas Mueller, Brandon A. |
| Author_xml | – sequence: 1 givenname: Kaushik orcidid: 0000-0001-7849-2349 surname: Gala fullname: Gala, Kaushik email: kgala@iastate.edu – sequence: 2 givenname: Andreas orcidid: 0000-0002-7968-1907 surname: Schwab fullname: Schwab, Andreas – sequence: 3 givenname: Brandon A. surname: Mueller fullname: Mueller, Brandon A. |
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| Keywords | Entrepreneurial performance L26 Digital platforms D31 Star entrepreneurs M13 Lognormal performance distributions Proportional differentiation |
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| SubjectTerms | Digital platforms Entrepreneurial performance Lognormal performance distributions Proportional differentiation Star entrepreneurs |
| Title | Star entrepreneurs on digital platforms: Heavy-tailed performance distributions and their generative mechanisms |
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