解析接触客户的员工对人工智能系统的厌恶机制:来自建议反应理论的视角

IF 9.1 1区 管理学 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM
Yong Yang, Yue Li, Xinyuan Zhao, Rob Law, Hongjin Song
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引用次数: 0

摘要

基于建议响应理论的视角,本研究旨在探讨人类管理者和人工智能(AI)系统对酒店行业客户接触员工对AI系统的厌恶程度的影响。研究考察了建议内容特征(有效性、可行性和实施局限性)和建议提供方式(面相性和可理解性)对客户接触员工厌恶人工智能系统的中介作用。设计/方法/方法进行2个基于场景的实验(实验1 = 499,实验2 = 300)。实验1比较了不同顾问类型(人类经理与人工智能系统)对员工对人工智能系统的厌恶程度的影响。实验2考察了建议内容特征(有效性、可行性和实施局限性)和建议传递(面相性和可理解性)的中介作用。调查结果显示,员工倾向于优先考虑人类经理的建议,而不是人工智能系统的输出。建议内容特征(有效性、可行性和实施局限性)和建议传递方式特征(表面性和可理解性)在顾问类型特征与员工厌恶AI系统的关系中起中介作用。这些发现有助于理解人工智能系统厌恶,并为酒店业与人工智能技术互动的客户接触员工的管理实践提供理论见解。独创性/价值本研究的主要贡献在于,通过探索顾问类型特征影响AI系统厌恶的双重中介(建议内容特征和建议交付),丰富了员工对AI系统厌恶的文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unraveling the mechanisms of AI system aversion among customer-contact employees: a perspective from advice response theory

Purpose

Based on the advice response theory perspective, this study aims to investigate the effects of human managers and artificial intelligence (AI) systems on customer-contact employees’ aversion to AI systems in the hospitality industry. It examined the mediating role of advice content characteristics (efficacy, feasibility and implementation limitations) and advice delivery (facework and comprehensibility) on customer-contact employees’ aversion to AI systems.

Design/methodology/approach

Two scenario-based experiments were conducted (Nexperiment 1 = 499 and Nexperiment 2 = 300). Experiment 1 compared the effects of different advisor types (human managers vs AI systems) on employees’ aversion to AI systems. Experiment 2 investigated the mediating role of advice content characteristics (efficacy, feasibility and implementation limitations) and advice delivery (facework and comprehensibility).

Findings

The results showed employees tended to prioritize advice from human managers over output from AI systems. Moreover, advice content characteristics (efficacy, feasibility and implementation limitations) and advice delivery (facework and comprehensibility) played mediating roles in the relationship between advisor type characteristics and employees’ aversion to AI systems.

Practical implications

These findings contribute to the understanding of AI system aversion and provide theoretical insights into management practices involving customer-contact employees who interact with AI technology in the hospitality industry.

Originality/value

The primary contribution of this study is that it enriches the literature on employee aversion to AI systems by exploring the dual mediators (advice content characteristics and advice delivery) through which advisor type characteristics affect AI system aversion.

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来源期刊
CiteScore
16.90
自引率
31.50%
发文量
239
期刊介绍: The International Journal of Contemporary Hospitality Management serves as a conduit for disseminating the latest developments and innovative insights into the management of hospitality and tourism businesses globally. The journal publishes peer-reviewed papers that comprehensively address issues pertinent to strategic management, operations, marketing, finance, and HR management in the field of hospitality and tourism.
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