Models of causal inference: : Imperfect but applicable is better than perfect but inapplicable

• Autores: Florian Ellsaesser, Eric W. K. Tsang, Jochen Runde
• Localización: Strategic management journal, ISSN 0143-2095, Vol. 35, Nº 10, 2014, págs. 1541-1551
• Idioma: inglés
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• Resumen

  • We assess a recent paper by Durand and Vaara (2009) that advances causal graph modeling as a tool for inferring causes in strategy research. We focus on the Markov condition, a key assumption on which causal graph modeling is based, and show why this condition is invariably violated in strategic management in general and the resource-based view of the firm in particular. We then introduce vector space modeling as a quantitative alternative to causal graph modeling, and consider how improved methods of causal inference might enhance our ability to test some of the central propositions of the resource-based view.