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Applying Random Coefficient Models to Strategy Research: Identifying and Exploring Firm Heterogeneous Effects

Author

Listed:
  • Juan Alcácer

    (Strategy Unit, Harvard Business School, Boston, Massachusetts 02163)

  • Wilbur Chung

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • Ashton Hawk

    (Leeds School of Business, University of Colorado, Boulder, Boulder, Colorado 80309)

  • Gonçalo Pacheco-de-Almeida

    (Strategy and Business Policy, École des Hautes Études Commerciales de Paris, 78351 Jouy-en-Josas Cedex, France)

Abstract

Strategy aims at understanding the differential effects of firms’ actions on performance. However, standard regression models estimate only the average effects of these actions across firms. Our paper discusses how random coefficient models (RCMs) may generate new insights about firm heterogeneity and its effects on performance in empirical settings in strategy. RCMs allow testing for and predicting firm-specific coefficients, thereby distinguishing between effects that have a significant mean versus significant variance. RCMs may also be used to explore the sources of firm heterogeneous effects. We develop a simulation test bed using synthetic data sets to show that RCMs are more precise at allocating firm heterogeneous effects to model slopes and intercepts than standard regression models. We also discuss RCMs’ possible limitations due to sample size requirements, nonconvergence problems, and potentially restrictive assumptions. Overall, RCMs allow strategy researchers to test and build new theories at a more granular level.

Suggested Citation

  • Juan Alcácer & Wilbur Chung & Ashton Hawk & Gonçalo Pacheco-de-Almeida, 2018. "Applying Random Coefficient Models to Strategy Research: Identifying and Exploring Firm Heterogeneous Effects," Strategy Science, INFORMS, vol. 3(3), pages 533-553, September.
    • Handle: RePEc:inm:orstsc:v:3:y:2018:i:3:p:533-553
    DOI: 10.1287/stsc.2018.0064
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