人-机器人联合工作:工作成果和员工反应

Yu-Qian Zhu, Kritsapas Kanjanamekanant
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引用次数: 2

摘要

机器人过程自动化(RPA)已被广泛应用于自动化数字任务。然而,由此产生的新型人机共同工作环境尚未得到充分研究。本文研究了RPA部署的深度和广度如何影响员工的工作自主性和工作集约化,以及感知RPA绩效。研究进一步探讨了工作自主性、工作强化和感知RPA绩效如何预测职业倦怠和使用RPA的持续意愿。设计/方法/方法使用从128个RPA用户的在线调查中收集的数据,这些用户的组织已经开始使用RPA,偏最小二乘法用于验证概念模型和分析。分析结果表明,RPA部署的广度和深度对工作强度的影响不同,RPA部署的广度和深度对感知RPA绩效有显著的预测作用。工作集约化增加了员工的职业倦怠,而工作自主性则缓解了员工的职业倦怠。最后,工作自主性和感知RPA绩效都是持续使用RPA意愿的正向预测因子。独创性/价值本研究通过调查共同工作如何影响员工的自主性和工作质量,为文献做出了贡献。通过展示技术部署的广度和深度如何不同地影响员工对工作相关方面的评价,推动了技术部署的研究。第三,通过说明工作自主性等工作资源的重要性,将工作需求-资源模型的适用性扩展到技术部署和持续技术使用文献中。最后,为企业提供了RPA实施策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human-bot co-working: job outcomes and employee responses
PurposeRobotic process automation (RPA) has been widely implemented to automate digital tasks. The resulting new type of human–bot co-working environment, however, has been understudied. This paper investigated how the depth and breadth of RPA deployment impact employees' job autonomy and work intensification, as well as perceived RPA performance. It further examined how job autonomy, work intensification, and perceived RPA performance predict burnout and continuance intention to use RPA.Design/methodology/approachUsing data collected from online survey of 128 RPA users, whose organizations have already gone live on RPA, partial least squares is used in the validation of the conceptual model and analysis.FindingsThe analytical results indicate that RPA deployment breadth and depth affect work intensification differently, and RPA deployment breadth and depth significantly predict perceived RPA performance. While work intensification increases burnout, job autonomy alleviates the burnout of employees. Finally, job autonomy and perceived RPA performance are both positive predictors of continuance intention to use RPA.Originality/valueThis study contributes to the literature by investigating how co-working affects employees' autonomy and quality of work. It also advances the research on technology deployment by showing how deployment breadth and depth differently affect employees' evaluations of work-related aspects. Third, it extends the applicability of job demand-resource model into technology deployment and continuance technology use literature, by illustrating the importance of a job resource such as job autonomy. Finally, it provides firms with RPA implementation strategies.
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