Ostracism is a negative social event that diminishes employees’ sense of power. Drawing on power dependence theory, this study investigates how employees’ prior engagement in crafting either social or structural job resources differentially moderates this relationship. We hypothesize that employees who previously increased social resources experience a weaker negative impact of ostracism on power, whereas those who increased structural resources experience a stronger effect. An experiment study supported these hypotheses. This research advances the ostracism, job crafting, and power literatures by showing how pre-ostracism job crafting behaviors can either mitigate or exacerbate ostracism’s negative effects on sense of power.

Analyzing Korean listed firms from 2014 to 2022, we report that 1) firms are less likely to issue sustainability reports following environmental rating downgrades, and 2) when they do, they include less green terminology in the reports. Notably, these disclosure patterns are only salient for firms with multiple downgrades (i.e., when multiple ESG raters issue downgrades). Interestingly, downgraded firms with more green terminology reduce carbon emissions to a lesser degree than those with less green terminology. Our results suggest that downgraded firms’ reactive disclosures are more of a strategic response than a demonstration of genuine commitment to environmental improvement.

This study examines how AI explanations affect human-AI collaborative decision-making. We test whether explainable AI (XAI) improves accuracy, speed, confidence, and reliance when distinguishing correct from incorrect AI suggestions. Using call center agents in three conditions―human only, human with AI, and human with XAI―we evaluate decisions made with classifiers and LIME-based explanations. Results show that explanations significantly increase decision accuracy, reduce overreliance on AI, and promote appropriate non-reliance. These findings emphasize the critical role and applicability of AI explanations in human-AI collaboration and contribute practical insights into designing AI assistants.