摘要
随着平台经济快速发展,如何减少平台工作者服务偏差行为、促进其服务质量整体提升,成为理论界和实践界共同关注的热点问题。算法控制作为平台企业高度依赖的新型管理手段,其对平台工作者服务偏差行为的影响尚无清晰一致的研究结论,亟待探索其间的复杂关系及作用机理。本研究基于工作要求-资源模型,提出算法控制可以视作一种兼具工作资源和工作要求双重属性的管理实践,通过对平台工作者情绪耗竭和目标承诺双重竞争性中介影响其服务偏差行为,且服务型领导在其中起到调节作用。本研究采用日记法对112名平台工作者进行了连续7天的追踪调研,研究发现:算法控制一方面通过加剧平台工作者的情绪耗竭,进而增加其服务偏差行为;另一方面,又通过提升平台工作者的目标承诺,进而减少其服务偏差行为。服务型领导不仅能够削弱算法控制通过情绪耗竭对平台工作者服务偏差行为的促进作用,还可以强化算法控制通过目标承诺对平台工作者服务偏差行为的抑制作用。本研究不仅加深了对算法控制与平台工作者服务偏差行为之间关系的辩证认识,也为平台企业通过算法-人工双重管理实践减少平台工作者服务偏差行为提供了理论依据。
As the platform economy transitions into a new stage of high-quality development,reducing customer-directed deviant behavior among platform workers and enhancing their overall service quality have become focal points of interest for both theoretical and practical discussions. It is noteworthy that despite the substantial body of research dedicated to exploring management practices that can effectively curb customer-directed deviant behavior,these studies predominantly focus on traditional employment groups. For the emerging cohort of platform workers,whose management models have undergone significant transformation,algorithmic control has become a highly relied-upon management practice for platform enterprises.In this context,it is crucial to understand whether and how algorithmic control influences the customerdirected deviant behavior of platform workers.However,existing research has not directly addressed this issue,making it difficult to reliably predict the relationship between algorithmic control and customer-directed deviant behavior,or to provide effective guidance for management practices. Therefore,clarifying the impact of algorithmic control on customerdirected deviant behavior and exploring the complex relationships and mechanisms involved are of significant theoretical and practical importance.This study posits that the job demands-resources(JD-R) model provides a theoretical basis for deeply explaining the complex relationship between algorithmic control and platform workers' customer-directed deviant behavior. The JD-R model suggests that job demands and job resources influence employee behavior through both depletion and gain pathways.Specific resources can act as “moderators,” buffering the negative effects of job demands and enhancing the positive effects of other job resources.Algorithmic control includes strict monitoring and rigorous assessments as demands but also provides intelligent guidance and real-time feedback as resources,making it a management practice that embodies both job resources and job demands. Based on this,the study introduces emotional exhaustion and goal commitment as parallel mediators and considers servant leadership as the boundary condition. By constructing a moderated competition intermediary model,the study aims to reveal the double-edged sword effect of algorithmic control on platform workers' customer-directed deviant behavior and its underlying mechanisms.To validate the theoretical model of this study,a diary method was employed to track the activities of 112 platform workers over 7 consecutive days,resulting in 720 valid data points. Multi-level confirmatory factor analysis and path analysis were conducted to analyze the data. The results show that algorithmic control,on one hand,increases platform workers' customer-directed deviant behavior by exacerbating their emotional exhaustion.On the other hand,it reduces such behavior by enhancing their goal commitment.Additionally,servant leadership can not only weaken the promoting effect of algorithmic control on platform workers' customer-directed deviant behavior through emotional exhaustion,but also strengthen the inhibitory effect of algorithmic control on such behavior through goal commitment.This study adopts a dialectical perspective to explore the impact mechanism and boundary conditions of algorithmic control on customer-directed deviant behavior among platform workers. It reconciles conflicting viewpoints on the advantages and disadvantages of algorithmic control,thereby uncovering its multifaceted effects.The study also enhances the understanding of the antecedents and formation mechanisms of customer-directed deviant behavior within this context.Furthermore,it examines how the interplay between algorithmic control and human management practices influences platform workers' work psychology and behavioral performance.The findings offer valuable insights for platform companies aiming to effectively develop,implement,and optimize algorithmic management strategies to manage customer-directed deviant behavior among their workforce.
作者
林彦梅
刘洪
王三银
LIN Yan-mei;LIU Hong;WANG San-yin(School of Business,Nanjing Normal University,Nanjing,Jiangsu,210023,China;School of Business,Nanjing University,Nanjing,Jiangsu,210008,China;School of Business Administration,Nanjing University of Finance and Economics,Nanjing,Jiangsu,210046,China)
出处
《经济管理》
CSSCI
北大核心
2024年第8期173-188,共16页
Business and Management Journal ( BMJ )
基金
国家自然科学基金青年项目“并购传闻对企业并购决策行为的影响研究”(72202094)
教育部人文社会科学基金青年项目“双职工夫妻工作家庭边界渗透的互动机制及其联合效应研究”(20YJC630078)
国家社会科学基金重大项目“我国就业量质协调发展的动态监测与保障体系研究”(20&ZD128)。
关键词
算法控制
服务偏差行为
服务型领导
工作要求-资源模型
algorithmic control
customer-directed deviant behavior
servant leadership
job demands-resources model
作者简介
林彦梅,女,副教授,管理学博士,研究领域为组织行为与人力资源管理,电子邮箱:mymy161@163.com;通讯作者:刘洪,男,教授,博士生导师,研究领域为组织行为与人力资源管理,电子邮箱:liuhong@nju.edu.cn;王三银,男,副教授,硕士生导师,管理学博士,研究领域为组织行为与人力资源管理,电子邮箱:wsynju@163.com。
