Gary A. Ballinger

Using Generalized Estimating Equations for Longitudinal Data Analysis

The generalized estimating equation (GEE) approach of Zeger and Liang facilitates analysis of data collected in longitudinal, nested, or repeated measures designs. GEEs use the generalized linear model to estimate more efficient and unbiased regression parameters relative to ordinary least squares regression in part because they permit specification of a working correlation matrix that accounts for the form of within-subject correlation of responses on dependent variables of many different distributions, including normal, binomial, and Poisson. The author briefly explains the theory behind GEEs and their beneficial statistical properties and limitations and compares GEEs to suboptimal approaches for analyzing longitudinal data through use of two examples. The first demonstration applies GEEs to the analysis of data from a longitudinal lab study with a counted response variable; the second demonstration applies GEEs to analysis of data with a normally distributed response variable from subjects nested within branch offices ofan organization.

Are Disruptive CEO Successions Viewed as a Governance Lapse? Evidence From Board Turnover:

A wealth of governance research has examined CEO successions and the negative organizational consequences that arise when boards are unable to effect smooth leadership transitions. Despite those findings, empirical and anecdotal evidence indicates that disruptive successions are still very common. In this article, we investigate whether disruptive CEO successions are viewed as a governance lapse by the board. We focus specifically on succession processes that involve the use of an interim leader. We leverage established research that shows that the pattern of board turnover observed in the wake of negative events is indicative of whether board behaviors are—in practice—viewed as normative violations. We theorize that audiences will disapprove of boards’ use of interim CEOs and, therefore, expect that these successions will prompt higher rates of board turnover than those observed following noninterim successions. However, we also anticipate that this relationship will be moderated by situational characteristics (e.g., surprise CEO departure, dynamic industry environment) that complicate succession planning and make audiences more accepting of a board’s decision to rely on an interim CEO. Our analysis of 438 successions at publicly traded U.S. firms provides support for these arguments. We discuss the implications of our findings for successions and corporate governance.

Intrinsic motivation and organizational identification among on-demand workers.

On-demand firms provide services for clients through a network of on-demand workers ready to complete specific tasks for a set contractual price. Given such on-demand work is defined by payment on short-term contracts with no obligation for continued employment, there is little reason to believe on-demand workers experience more than extrinsic motivation and a transactional relationship with the on-demand firm. However, using self-determination theory, we argue that to the degree that on-demand work fulfills innate psychological needs individual on-demand workers will develop intrinsic motivation, which further leads to organizational identification with the on-demand firm. Across 2 survey-based studies we find support for this path to organizational identification. This adds to the literature on motivation and identification by strengthening the link between individual needs and the individual–organizational relationship. Implications for theory and for the management of on-demand workers are discussed.

The right friends in the right places: Understanding network structure as a predictor of voluntary turnover.

Research examining the relationship between social networks and employee retention has focused almost exclusively on the number of direct links and generally found that having more ties decreases the likelihood of turnover. The present research moves beyond simple measures of network centrality to investigate the relationship between 2 additional, and theoretically distinct, facets of social capital and voluntary turnover. In 2 organizations, we found consistent evidence of a negative relationship between reputation, as measured by relationships with highly sought-out others (incoming eigenvector centrality) and voluntary turnover. Further, we found that the negative relationship between brokerage (structural holes) and turnover is significant, but only for higher-level employees. The theoretical and practical implications of expanding the suite of social capital measures to understand voluntary turnover are discussed.