CEO Departure Type and Subsequent Workforce Restructuring: An Exploratory Study of Tech-Sector S&P Firms, 2010–2024

Abstract:

This study examines whether the reason a chief executive officer departs a firm—involuntary dismissal, voluntary resignation, or retirement—is associated with subsequent workforce restructuring among technology-sector companies in the S&P 1500. The current research merges a CEO departure database (restricted to 2010–2019 departures) with a publicly listed firm layoff register for 2020–2024, yielding 1,354 firm observations of which 22 experienced a confirmed workforce reduction. A penalised maximum likelihood logistic estimator is applied to correct for rare-event bias at the 1.62% event rate. Three findings emerge. First, firms whose most recent CEO was involuntarily dismissed face approximately 2.7 times the layoff odds of firms whose CEO retired voluntarily (OR = 2.669, 95% CI [1.124, 6.339], p = 0.026). Second, voluntarily resigned CEOs’ former firms also face elevated layoff odds relative to retired CEOs (OR = 4.689, 95% CI [1.132, 19.431], p = 0.033), though this estimate rests on only two events. Third, departure year recency adds no significant incremental prediction within the 2010–2019 window (OR = 1.106, p = 0.233). An ordinary least squares robustness check confirms the dismissal result (b = 0.044, p = 0.048). The Kruskal–Wallis test on restructuring scale across departure types is significant (H = 6.76, p = 0.034). The study explicitly notes limitations: the layoff register covers primarily technology and digital-economy firms rather than the full S&P 1500, confirmed matches represent a technology-sector subsample, and the 22-event count constrains inferential precision. These findings are offered as exploratory associations suitable for replication with administrative layoff records providing comprehensive S&P 1500 coverage.