供应链规划中的自动化与人工互动

Larysa Shchekhovska
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引用次数: 0

摘要

自动化正在改变供应链规划(SCP)流程,以技术解决方案取代人工任务。自动化在提高效率的同时,也给人类与自动化系统之间的互动带来了行为上的挑战。本研究探讨了 SCP 流程中的决策者在与自动化需求预测系统和人类计划人员互动时,如何学会纠正错误。借鉴心理学和行为学理论,我们研究了交互类型(自动化系统与人工)对学习的影响,学习的具体表现为随着时间推移绩效的提高。此外,我们还分析了这种关系是否会受到人类决策者的认知心理特征(对技术的积极态度、技术焦虑/依赖)和社会心理特征(基于主观规范的社会影响、基于形象的社会影响)的调节。我们的文章引入了自动化与人的互动,提供了关于绩效的时间学习视角,并整合了认知和社会心理调节因素,从而为供应链管理研究做出了贡献。文章就如何通过管理社会心理影响因素促进有效的人机协作提出了见解。还讨论了局限性和未来的研究机会,包括文化背景和人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interaction Between Automation and Humans in Supply Chain Planning
Automation is transforming supply chain planning (SCP) processes, replacing human tasks with technological solutions. While automation offers efficiency gains, the interaction between humans and automated systems presents behavioral challenges. This study investigates how decision-makers in SCP processes learn to correct errors when interacting with automated demand forecasting systems versus human planners. Drawing from psychology and behavioral theories, we examine the effects of interaction type (automated system vs. human) on learning, operationalized as performance improvement over time. Further, we analyze whether this relationship is moderated by cognitive psychological traits (positive attitude towards technology, technology anxiety/dependence) and socio-psychological traits (social influence based on subjective norms, social influence based on image) of the human decision-maker. Our article contributes to supply chain management research by introducing automation-human interaction, providing a temporal learning perspective on performance, and integrating cognitive and socio-psychological moderators. Insights are offered on how to facilitate effective human-automation collaboration by managing socio-psychological influences. Limitations and future research opportunities, including cultural contexts and artificial intelligence, are discussed.
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