Research summary: The use of Heckman models by strategy scholars to resolve sample selection bias has increased by more than 700 percent over the last decade, yet significant inconsistencies exist in how they have applied and interpreted these models. In view of these differences, we explore the drivers of sample selection bias and review how Heckman models alleviate it. We demonstrate three important findings for scholars seeking to use Heckman models: First, the independent variable of interest must be a significant predictor in the first stage of a model for sample selection bias to exist. Second, the significance of lambda alone does not indicate sample selection bias. Finally, Heckman models account for sample‐induced endogeneity, but are not effective when other sources of endogeneity are present. Managerial summary: When nonrandom samples are used to test statistical relationships, sample selection bias can lead researchers to flawed conclusions that can, in turn, negatively impact managerial decision‐making. We examine the use of Heckman models, which were designed to resolve sample selection bias, in strategic management research and highlight conditions when sample selection bias is present as well as when it is not. We also distinguish sample selection bias, a form of omitted variable (OV) bias, from more traditional OV bias, emphasizing that it is possible for models to have sample selection bias, traditional OV bias, or both. Accurately identifying the type(s) of OV bias present is essential to effectively correcting it. We close with several recommendations to improve practice surrounding the use of Heckman models. Copyright © 2015 John Wiley & Sons, Ltd.
Despite scholars’ admonitions regarding the use of ratios in statistical analyses, the practice is common in management research. This is particularly true in the area of strategic management, where important variables of interest are operationalized as ratios. In this study, we employ simulations to demonstrate the implications of using ratios in statistical analyses. Our simulations illustrate that ratio variables produce inaccurate parameter estimates and can result in lower levels of statistical power (i.e., the ability to uncover hypothesized relationships). We also find that when an independent or a dependent variable is a ratio, the relationship between the independent and dependent variable fluctuates as the dispersion of the denominator changes. These fluctuations occur even when the correlations between the unscaled variables remain exactly the same. We also find that including ratios in models as control variables influences estimates of relationships between focal independent and dependent variables. This is true even when neither the independent or dependent variable is a ratio. We provide several recommendations for researchers who may be interested in avoiding the pitfalls of ratio variables.
Allocating internal financial capital represents a key task for managers of multidivisional corporations. This has led to a wealth of research and theorizing about capital allocation and whether or not managers allocate capital successfully. However, capital allocation research has diverged in a number of directions that reflect different and often incompatible perspectives, underlying frameworks, and outcomes. The result is a puzzle, wherein scholars have found little consistent substantive relation between capital allocation, business unit characteristics, and firm performance. Through our review, we seek to bring clarity to this puzzle by identifying problems in the literature and by offering a solution. We suggest problems in the literature stem from the disparate approaches scholars have taken when studying capital allocation, including assessments of what constitutes and prevents successful allocation. We begin by organizing these approaches into a framework that highlights key allocation strategies and the primary impediments to allocation success that scholars have used to build their models. We then suggest that managers may employ a number of allocation strategies and that scholars need to recognize that not all corporate managers employ the same strategy. We contend that a resurgence of obtrusive, qualitative, and multilevel studies may help explain why managers Acknowledgments: The authors would like to gratefully acknowledge the comments and suggestions of the coeditors of the special issue-Cathy Maritan and Gwen Lee-as well as two anonymous reviewers.
Management research increasingly recognizes omitted variables as a primary source of endogeneity that can induce bias in empirical estimation. Methodological scholarship on the topic overwhelmingly advocates for empirical researchers to employ two-stage instrumental variable modeling, a recommendation we approach with trepidation given the challenges associated with this analytic procedure. Over the course of two studies, we leverage a statistical technique called the impact threshold of a confounding variable (ITCV) to better conceptualize what types of omitted variables might actually bias causal inference and whether they have appeared to do so in published management research. In Study 1, we apply the ITCV to published studies and find that a majority of the causal inference is unlikely biased from omitted variables. In Study 2, we respecify an influential simulation on endogeneity and determine that only the most pervasive omitted variables appear to substantively impact causal inference. Our simulation also reveals that only the strongest instruments (perhaps unrealistically strong) attenuate bias in meaningful ways. Taken together, we offer guidelines for how scholars can conceptualize omitted variables in their research, provide a practical approach that balances the tradeoffs associated with instrumental variable models, and comprehensively describe how to implement the ITCV technique.
Research Summary: Though research has focused on the ascent and acceptance of female CEOs, the postpromotion circumstances female CEOs face remain unclear. In this study, we focus on a critical postpromotion circumstance: the board chair-CEO relationship. Drawing on the gender stereotype literature, agency theory, and stewardship theory, we posit that firms appointing a female CEO are more likely to adopt a collaboration board chair orientation and less likely to adopt a control orientation. We further predict this effect is attenuated by female board representation. Using a sample of new S&P 1500 CEOs, we find support for our predictions regarding the collaboration orientation but not the control orientation. This research provides some evidence of benevolent sexism in the boardroom, with female directors acting as a countervailing influence. Managerial Summary: Whereas the notion that females encounter a glass ceiling on their path toward CEO is well documented, the conditions female CEOs encounter after promotion are less understood. The relationship between the board chair and the CEO is one important post-promotion condition. Board chairs can focus on monitoring and/or working together with the CEO. We suggest board chairs are more likely to work in close collaboration with female CEOs than with male CEOs. We attribute this to benevolent sexism, which explains that board chairs are more likely to collaborate with female CEOs because they view females as more conducive to, and in need of, this type of relationship. We also suggest this benevolent sexism is less prevalent when there are more females on the board. K E Y W O R D Sagency theory, board chair orientation, CEO gender, corporate governance, stewardship theory Received: 27 February 2017 Revised: 1 | INTRODUCTIONWhen General Motors Co. appointed Mary Barra as chief executive officer (CEO)-becoming the first major U.S. automaker with a female CEO-the Wall Street Journal published an article about the firm's incoming independent board chair, Tim Solso, and his orientation toward the job. According to the article, "Mr. Solso insists his job is to ensure Ms. Barra succeeds as the company's CEO":Mr. Solso makes clear he intends to be a hands-on player as well as a coach, advocate and resource for Mary Barra, the company's new chief executive…"I can take some of the load off management's back," he said. (Bennett & Lublin, 2014, p. B1) The article notes that Solso's statement seems to conflict with his reputation as a strict board monitor who "can be a tough boss and knows how to get his way," having previously engineered the ouster of a CEO while on the board of another firm (Bennett & Lublin, 2014, p. B1). Indeed, the board chair role described above is a clear example of what Krause (2017) identified as the "collaboration" board chair orientation, which consists of advising and guiding the CEO and reducing the CEO's job demands. Based on his history, though, the GM board chair also seems amenable to the "control" board chair orientation, which consi...
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