影响旅游业人工智能价值共创的因素:文献综述

IF 5.8 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM
Konstantinos Solakis, V. Katsoni, A. Mahmoud, Nicholas Grigoriou
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引用次数: 13

摘要

这是一项一般性综述研究,旨在明确通过人工智能(AI)和自动化在酒店和旅游业中影响价值共同创造(VCC)过程的关键基于客户的因素和技术。设计/方法/方法本研究采用基于理论的一般文献综述方法来探讨旅游业中影响VCC的关键客户因素和技术。通过回顾相关文献,作者总结了一个理论框架,假设人工智能驱动的旅游业中VCC的决定因素。本文将客户的感知、态度、信任、社会影响、享乐动机、拟人化和先前经验确定为通过使用人工智能进行VCC的基于客户的因素。服务机器人、支持人工智能的自助服务亭、聊天机器人、跨时空旅游和新现实、机器学习(ML)和自然语言处理(NLP)是影响VCC的技术。本研究的结果为未来的研究提供了一个理论框架,阐明了人类和人工智能的因素,以扩展预测旅游业VCC的模型。原创性/价值很少有研究考察通过自动化和人工智能影响消费者参与VCC过程的相关因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors affecting value co-creation through artificial intelligence in tourism: a general literature review
PurposeThis is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.Design/methodology/approachThe study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.FindingsThis paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.Research limitations/implicationsThe results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.Originality/valueFew studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.
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来源期刊
Journal of Tourism Futures
Journal of Tourism Futures HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
15.70
自引率
6.00%
发文量
64
审稿时长
34 weeks
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