Dummy Constructs? Binomial Categorical Variables as Representations of Constructs: CEO Duality Through Time. (January 2013)

• Record Type: Journal Article
• Authors: Gove, Steve; Junkunc, Marc
• Is Part Of: Organizational research methods. Volume 16:Number 1(2013)
• Page Start: 100
• Page End: 126
• Publication Date: 2013-01
• Subjects: reliability and validity -- measurement design -- research design -- reliability of dichotomous variables -- content validity -- construct validation procedures -- dummy variable -- CEO duality; Organization -- Research -- Methodology -- Periodicals; Organizational sociology -- Research -- Methodology -- Periodicals; Management -- Research -- Methodology -- Periodicals; 302.350721
• DOI: 10.1177/1094428112472000
• Languages: English
• ISSNs: 1094-4281

Abstract

CEO duality describes the governance structure when a firm's chief executive officer also holds the position of chairman of the board. Duality is central to theoretical perspectives on corporate governance and top management, yet duality's relationship with numerous outcomes is characterized by nonsignificant coefficients and bivariate correlations hovering near zero. We argue and present evidence that CEO duality represents a "dummy construct"—an intentionally pejorative assessment on the widespread use of binomial categorical "dummy" variables to represent complex constructs. While we highlight CEO duality, the use of dummy variables as constructs is common in research. We review CEO duality as a construct and assess typical approaches to its measurement. When compared to actual patterns of duality within organizations, we find that current operationalizations are lacking due to a lack of attention to temporal considerations. This raises questions about the construct validity of current conceptualizations of CEO duality. Actual patterns suggest constructs and theoretical perspectives not previously considered. We present a taxonomy of CEO duality archetypes and offer suggestions on the incorporation of time for studies using dummy variables.