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A Bayesian operationalization of the resource‐based view

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  • Mark H. Hansen
  • Lee T. Perry
  • C. Shane Reese

Abstract

This paper argues that the gap between the theoretical utility and the practical utility of the resource‐based view (RBV) may be narrowed by operationalizing the theory more consistently with Penrose's original framework. The operationalization proposed here is a twofold approach. First, the RBV may be enhanced by the explicit recognition of Penrose's two classes of resources, namely, administrative resources and productive resources. This distinction suggests a focus on the administrative decisions of managers that lead to economic performance. Second, we argue that the RBV is a theory about extraordinary performers or outliers—not averages. Therefore, the statistical methods used in applying the theory must account for individual firm differences, and not be based on means, which statistically neutralize firm differences. We propose a novel Bayesian hierarchical methodology to examine the relationship between administrative decisions and economic performance over time. We develop and explain a measure of competitive advantage that goes beyond comparisons of economic performance. This Bayesian methodology allows us to make meaningful probability statements about specific, individual firms and the effects of the administrative decisions examined in this study. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Mark H. Hansen & Lee T. Perry & C. Shane Reese, 2004. "A Bayesian operationalization of the resource‐based view," Strategic Management Journal, Wiley Blackwell, vol. 25(13), pages 1279-1295, December.
  • Handle: RePEc:bla:stratm:v:25:y:2004:i:13:p:1279-1295
    DOI: 10.1002/smj.432
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    11. Jérémy Tantely Ranjatoelina & Anne-Ryslène Zaoual, 2016. "The inclusion of wasted resources. The case of a work integration social enterprise [Inclure des ressources délaissées. Le groupe Vitamine T, un spécialiste de l’insertion]," Post-Print hal-01987174, HAL.
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    15. Yalcinkaya, Goksel & Aktekin, Tevfik & Yeniyurt, Sengun, 2020. "Out with the old: A Bayesian approach to estimating product modification rates," Journal of Business Research, Elsevier, vol. 118(C), pages 141-149.
    16. Renata Konadu & Samuel Owusu‐Agyei & Theophilus A. Lartey & Albert Danso & Samuel Adomako & Joseph Amankwah‐Amoah, 2020. "CEOs' reputation, quality management and environmental innovation: The roles of stakeholder pressure and resource commitment," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2310-2323, September.
    17. Antonio Arbelo & Marta Arbelo-Pérez & Pilar Pérez-Gómez, 2022. "Are SMEs less efficient? A Bayesian approach to addressing heterogeneity across firms," Small Business Economics, Springer, vol. 58(4), pages 1915-1929, April.
    18. Yu, Xiaoyu & Wang, Xinchun, 2021. "The effects of entrepreneurial bricolage and alternative resources on new venture capabilities: Evidence from China," Journal of Business Research, Elsevier, vol. 137(C), pages 527-537.
    19. Kraude, Richard & Narayanan, Sriram & Talluri, Srinivas, 2022. "Evaluating the performance of supply chain risk mitigation strategies using network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1168-1182.

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