How to design a value-based Chatbot for the manufacturing industry: An empirical study of an internal assistance for employees

Patrick Berger, Joerg von Garrel
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Abstract

Abstract With regard to AI as a key technology, this scientific paper deals with the identification of user drivers on the purchase decision of a cooperative AI (as explainable AI—XAI), as well as the analysis of the willingness to pay in the context of value-based pricing. Besides the economic dimension with regard to usefulness and usability of the system, the focus is mainly on the (innovative) explainable character. The analysis is carried out by a choice-based conjoint analysis (CBC) using the example of an intelligent assistance system for employees that supports internal business processes and workflows in business organizations. For this purpose, fictitious purchase offers were created under which decision-makers in manufacturing business organizations in Germany made simulated purchase decisions. The analysis shows that the target group attach great utility value to transparency in the sense of explanatory content, in addition to a high degree of interactivity and a high level of reliability.
如何为制造业设计一个基于价值的聊天机器人:对员工内部协助的实证研究
本文将人工智能作为一项关键技术,研究了协作式人工智能(可解释的AI - xai)购买决策的用户驱动因素识别,以及基于价值定价背景下的支付意愿分析。除了关于系统的有用性和可用性的经济维度外,重点主要放在(创新的)可解释性上。该分析由基于选择的联合分析(CBC)执行,该分析使用了支持业务组织内部业务流程和工作流的员工智能辅助系统的示例。为此,我们创建了虚拟的采购报价,德国制造业企业的决策者在虚拟报价下做出了模拟的采购决策。分析表明,除了高度的互动性和高水平的可靠性外,目标群体对解释性内容意义上的透明度具有很高的实用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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