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作者：Martin, Xavier; Cuypers, Ilya R. P.
作者单位：Tilburg University; Singapore Management University; Tilburg University
摘要：Research SummaryWhen can a firm make fine-grained adjustments to misaligned subsidiary governance? We examine whether and under what conditions a firm will adapt the equity stake it owns in a subsidiary, enabling improved alignment of the stake with the uncertainty in the local environment. We predict that the rate of adaptation of misaligned equity stakes depends on the experiential and vicarious learning from which the firm can draw, and that these learning effects are contingent on possessi...
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作者：Souder, David; Shaver, J. Myles; Harris, Jared; Alrashdan, Abdullatif
作者单位：University of Connecticut; University of Minnesota System; University of Minnesota Twin Cities; University of Virginia; Kuwait University
摘要：Research SummaryWe discuss two research design considerations that jointly influence the choice of financial performance metrics in strategy research: (a) expected temporal payoff of the strategic choice and (b) source of variation invoked in the research design (i.e., within-firm vs. between-firm comparisons). We map existing performance metrics commonly used in the research literature to these considerations, and highlight the lack of performance metrics well suited for the combination of st...
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作者：Andrei, Alina G.; Benischke, Mirko H.; Martin, Geoffrey P.
作者单位：Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; University of Melbourne; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC
摘要：We integrate behavioral agency research and the five-factor model of personality to re-visit investment analysts' efficacy as a mechanism for reducing agency costs. We highlight the role of personality in shaping how CEOs respond to analyst recommendations, leading to boundary conditions for the efficacy of analysts as external monitors. We theorize that the extent to which a CEO perceives a threat from more positive analyst recommendations is contingent upon their personality, which shapes th...
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作者：Greenberg, Jason; Sands, Daniel B.; Cattani, Gino; Porac, Joseph
作者单位：Cornell University; University of London; University College London; New York University
摘要：Research Summary We investigate the extent to which the increasing availability of ratings information has affected heterogeneity in firm performance and, if so, what market segments are responsible for these changes. A unique dataset was constructed with restricted-access government data to examine these questions in the context of the New York City restaurant industry between 1994 and 2013. We find that firms serving tourist and expensive price point market segments experienced increasing sa...
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作者：Sohn, Eunhee; Seamans, Robert; Sands, Daniel B.
作者单位：University System of Georgia; Georgia Institute of Technology; New York University; University of London; University College London; New York University
摘要：Research Summary This article explores how technology adoption can shape innovative activity. We study this issue within the historical context of the introduction and expansion of airmail across the United States between 1918 and 1935 using archival material and a novel dataset of early 20th century patents. A joint qualitative and quantitative investigation indicates that local individual and corporate actors applied diverse pools of knowledge and intensified their work with aviation innovat...
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作者：Hyde, Steven J.; Bachura, Eric; Bundy, Jonathan; Gretz, Richard T.; Sanders, Wm. Gerard
作者单位：Boise State University; University of Texas System; University of Texas at San Antonio; Arizona State University; Arizona State University-Tempe; University of Texas System; University of Texas at San Antonio; Nevada System of Higher Education (NSHE); University of Nevada Las Vegas; Boise State University
摘要：Research Summary Organizations are punished by analysts and investors when material deceit by their CEO is uncovered. However, few studies examine analysts' responses to deceptive CEOs before their deceit is publicly known. We use machine learning (ML) models to operationalize the likelihood of CEO deception as well as analysts' suspicion of CEO deception on earnings calls. Controlling for analysts' suspicion of deception, we show that analysts are prone to assigning superior recommendations t...
