Reputation-Damaging Events Over a Long Time Horizon: An Event-System Model of Substantive Reputation Repair

• Published in: Journal of management
• Main Authors: Vassallo, Jarrod P., Seo, Yeonji, (Shaz) Ansari, Shahzad
• Format: Journal Article
• Language: English
• Published: 29.02.2024
• ISSN: 0149-2063; 1557-1211
• DOI: 10.1177/01492063231224353

Current models of substantive reputation repair primarily focus on isolated reputation-damaging events (RDEs) and corresponding responses by firms within short time frames. Nevertheless, evidence suggests that firms encounter numerous RDEs over extended periods while only sporadically and intermittently engaging in top-down substantive repair. To investigate this event-response asynchrony, we adopt an event system theory (EST) approach and conduct a qualitative study of a multinational firm. Over a 10-year period, we analyzed 47 RDEs that eventually prompted top management to initiate substantive repair. Our findings reveal that top managers perceive reputation management as a complex system comprising self-correcting subsystems that follow recurring adaptive event cycles. These cycles consist of iterations, transitioning from routine business-as-usual activities managing most RDEs (foreloops) to nonlinear, transformative responses to certain events (backloops). As long as these cycles are deemed effective, top managers refrain from substantive repair, intervening only when they identify a subsystem breakdown. Consequently, our event-system model of substantive reputation repair elucidates event-response asynchrony in two phases: (1) top managers’ confidence in the hierarchy of adaptive event cycles leads them to purposefully avoid most RDEs, and (2) the convergent intersection of three specific event chain patterns gradually establishes a shared narrative among top managers, triggering top-down substantive repair. By employing EST, we not only provide novel insights into how firms manage reputations but also enhance the explanatory power of EST by illuminating event cycle dynamics.