No entrepreneur steps in the same river twice: Limited learning advantage for serial entrepreneurs

Pankaj C. Patel*, Mike Tsionas, Pejvak Oghazi, Vanessa Izquierdo

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review


Deterministic learning is less feasible in high-noise and low-signal entrepreneurship contexts. The empirical evidence on serial entrepreneurs having an advantage over novice entrepreneurs is mixed. Entrepreneurs learn by lowering high noise (w) and increasing the fidelity of a learning outcome (θ). We draw on Jovanovic and Nyarko's (1995) Bayesian learning framework. Assessing learning by doing across fifteen combinations of the number of businesses and the industry distance among founded firms, our findings are bleak. Learning in successive businesses is a high-noise (w) and low-signal (θ) environment, where the progress ratio, or the ratio of total learning to initial learning, is close to 1. In launching businesses in multiple industries, these learning challenges are slightly higher. Overall, learning by doing is noisy and delivers limited improvements in business duration.

Original languageEnglish
Peer-reviewed scientific journalJournal of Business Research
Pages (from-to)1038-1052
Number of pages15
Publication statusPublished - 03.2022
MoE publication typeA1 Journal article - refereed


  • 512 Business and Management
  • Bayesian learning
  • Learning by doing
  • Serial entrepreneurs


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