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Perspective—Chance Explanations in the Management
Jerker Denrell, Christina Fang, Chengwei Liu
To cite this article:
Jerker Denrell, Christina Fang, Chengwei Liu (2015) Perspective—Chance Explanations in the Management Sciences.
Organization Science 26(3):923-940. http://dx.doi.org/10.1287/orsc.2014.0946
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Vol. 26, No. 3, May–June 2015, pp. 923–940
ISSN 1047-7039 (print) ISSN 1526-5455 (online) http://dx.doi.org/10.1287/orsc.2014.0946 © 2015 INFORMS
Chance Explanations in the Management Sciences
Warwick Business School, University of Warwick, Coventry, CV4 7AL, United Kingdom, email@example.com
Department of Management, Stern School of Business, New York University, New York, New York 10012, firstname.lastname@example.org
Warwick Business School, University of Warwick, Coventry, CV4 7AL, United Kingdom, email@example.com
We propose that random variation should be considered one of the most important explanatory mechanisms in themanagement sciences. There are good theoretical reasons to expect that chance events strongly impact organizational behavior and outcomes. We argue that models built on random variation can provide parsimonious explanations of several important empirical regularities in strategic management and organizational behavior. The reason is that random variation in a structured system can give rise to systematic patterns at the macro level. Here, we define the concept of a chance explanation; describe the theoretical mechanisms by which random variation generates patterns at the macro level; outline how key empirical regularities in management can be explained by chance models; and discuss the implications of chance models for theoretical integration, empirical testing, and management practice.
Keywords : randomness; luck; chance; theoretical mechanisms; null models
History : Published online in Articles in Advance December 19, 2014. 1. Introduction
Management scholars often consider chance and randomness as a nuisance to be eliminated. Chance may be the null hypothesis, but the null hypothesis is usually only included as a straw man to be rejected (Starbuck 1994). Randomness, according to this conventional view, is due to measurement error or unobserved heterogeneity and should be eliminated through improved measurement or controlled for with proper statistical methods.
The main goal is to understand the systematic, i.e., nonrandom, forces that really interest management scholars.
Hence attributing an event or pattern to chance and randomness hardly counts as a proper explanation.
We argue instead that theory development that relies on randomness as its first principle can offer a theoretically rich and empirically fruitful paradigm in the management sciences. Random variation offers a parsimonious explanation of several important empirical regularities in management. Random variation deserves to be taken seriously as a theoretical mechanism of considerable generality and with strong empirical support.
The purpose of this paper is to develop this argument and promote what could be called “the random school of thought” in the management sciences.
The idea that random variation can explain regularities in organizational behavior is not novel. Several management scholars have stressed that behavior by and within organizations is likely to contain a random element (Aldrich 1979, Barney 1986, Fichman 1999, March 2010, Nelson and Winter 1982, Starbuck 1994) and have examined how models relying on chance variation can explain patterns previously attributed to systematic effects (Alchian 1950, Barney 1997, Denrell 2004,
Levinthal 1991, Mancke 1974, March and March 1978,
Powell 2003). Yet the theoretical unity and empirical richness of models relying on randomness is seldom appreciated. The reason is, in part, that these contributions are scattered across many different subdisciplines.
Even management scholars who believe randomness is important may not be aware of the wide range of chance explanations that exist. Moreover, because the focus is usually on a particular application (such as strategy, career patterns, or organizational learning), the underlying mechanism is not always explicated. As a result, 923
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Denrell, Fang, and Liu: Perspective 924 Organization Science 26(3), pp. 923–940, © 2015 INFORMS readers are unlikely to appreciate the theoretical unity that exists amid the diverse applications.