While the direct influence of CEO tenure on firm performance has been examined in the strategy literature, the underlying channels of influence have remained largely unexplored. This article draws upon the career seasons paradigm, learning perspectives, and marketing literature to examine whether firm-employee and firm-customer relationships are the pathways through which CEO tenure influences firm performance. Results from the analysis of a large data set reveal that: (1) CEO tenure has a positive and linear association with firm-employee relationship strength but an inverted U-shaped association with firm-customer relationship strength;(2) industry uncertainty intensifies these associations; and (3) firm-employee and firm-customer relationship strength mediate the effects of CEO tenure on firm performance. These findings have implications for a more balanced and nuanced view of CEO tenure. 1 We acknowledge an anonymous reviewer for suggesting this CEO learning-focused logic for the divergent effects of CEO tenure on employee and customer relations and firm performance.

Content platforms (e.g., newspapers, magazines) post several stories daily on their dedicated social media pages and promote some of them using targeted content advertising (TCA). Posting stories enables content platforms to grow their social media audiences and generate digital advertising revenue from the impressions channeled through social media posts’ link clicks. However, optimal scheduling of social media posts and TCA is formidable, requiring content platforms to determine what to post; when to post; and whether, when, and how much to spend on TCA to maximize profits. Social media managers lament this complexity, and academic literature offers little guidance. Consequently, the authors draw from literature on circadian rhythms in information processing capabilities to build a novel theoretical framework on social media content scheduling and explain how scheduling attributes (i.e., time of day, content type, and TCA) affect the link clicks metric. They test their hypotheses using a model estimated on 366 days of Facebook post data from a top 50 U.S. newspaper. Subsequently, they build an algorithm that allows social media managers to optimally plan social media content schedules and maximize gross profits. Applying the algorithm to a holdout sample, the authors demonstrate a potential increase in gross profits by at least 8%.

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