The dark side of fairness: how perceived fairness in service robot implementation leads to employee dysfunctional behavior

大裂谷 失调家庭 业务 服务(商务) 营销 公共关系 心理学 天文 政治学 物理 心理治疗师
作者
Taeshik Gong
出处
期刊:Journal of Services Marketing [Emerald Publishing Limited]
被引量:3
标识
DOI:10.1108/jsm-09-2024-0508
摘要

Purpose The purpose of this study is to explore the unexpected effects of perceived fairness in the implementation of service robots on employee dysfunctional behavior within the hospitality industry. Contrary to the conventional view that perceived fairness always leads to positive outcomes, this study examines how fairness perceptions can increase negative behaviors through unmet expectations, overconfidence in job security and complacency. The moderating role of transformational leadership is also investigated to understand how it can mitigate these negative effects. Design/methodology/approach This study collected data from 400 employees in the hospitality sector who have experienced the integration of service robots in their work environment. Using quantitative analysis techniques, the relationships between perceived fairness, employee dysfunctional behavior, unmet expectations, overconfidence, complacency and transformational leadership were examined. Findings The findings reveal that perceived fairness in service robot implementation can unexpectedly lead to increased employee dysfunctional behavior, particularly when it results in unmet expectations, overconfidence and complacency. However, transformational leadership was found to significantly moderate these effects, reducing the likelihood of dysfunctional behaviors by realigning employee perceptions and expectations with organizational objectives. Originality/value This study contributes to the service marketing literature by challenging the assumption that perceived fairness always yields positive outcomes, highlighting the potential for fairness to produce unintended negative consequences in service robot implementation. It also identifies transformational leadership as a key factor in mitigating these effects, offering practical insights for hospitality managers on how to ensure successful integration of service robots by actively managing employee expectations and behaviors.
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