推荐规模和旅游参与在评估旅游目的地推荐服务中的作用:人工智能和旅游专家的比较

IF 5.3 3区管理学 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM

Journal of Hospitality and Tourism Technology Pub Date : 2023-03-07 DOI:10.1108/jhtt-01-2022-0013

W. Jang, Soojin Kim, JungWon Chun, A. Jung, Hany Kim

{"title":"推荐规模和旅游参与在评估旅游目的地推荐服务中的作用:人工智能和旅游专家的比较","authors":"W. Jang, Soojin Kim, JungWon Chun, A. Jung, Hany Kim","doi":"10.1108/jhtt-01-2022-0013","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis study aims to understand how travelers evaluate travel destination recommendations received from either artificial intelligence (AI) or human travel experts (TEs) based on the size of recommendation and their travel involvement.\n\n\nDesign/methodology/approach\nThis study used a 2 (agent type: AI vs TE) × 2 (size of recommendation: small vs large) × 2 (travel involvement: low vs high) between-subjects design.\n\n\nFindings\nWhen AI recommends destinations, less-involved travelers perceive the recommendations as more credible and trust the system when AI offers larger recommendations than smaller ones. Meanwhile, when TEs offer recommendations, travelers consider the recommendations as equally credible and similarly trust the system, regardless of the recommendation size and travel involvement.\n\n\nOriginality/value\nThis study sheds light on the design of human-centered AI travel destination recommendation services.\n","PeriodicalId":51611,"journal":{"name":"Journal of Hospitality and Tourism Technology","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Role of recommendation sizes and travel involvement in evaluating travel destination recommendation services: comparison between artificial intelligence and travel experts\",\"authors\":\"W. Jang, Soojin Kim, JungWon Chun, A. Jung, Hany Kim\",\"doi\":\"10.1108/jhtt-01-2022-0013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis study aims to understand how travelers evaluate travel destination recommendations received from either artificial intelligence (AI) or human travel experts (TEs) based on the size of recommendation and their travel involvement.\\n\\n\\nDesign/methodology/approach\\nThis study used a 2 (agent type: AI vs TE) × 2 (size of recommendation: small vs large) × 2 (travel involvement: low vs high) between-subjects design.\\n\\n\\nFindings\\nWhen AI recommends destinations, less-involved travelers perceive the recommendations as more credible and trust the system when AI offers larger recommendations than smaller ones. Meanwhile, when TEs offer recommendations, travelers consider the recommendations as equally credible and similarly trust the system, regardless of the recommendation size and travel involvement.\\n\\n\\nOriginality/value\\nThis study sheds light on the design of human-centered AI travel destination recommendation services.\\n\",\"PeriodicalId\":51611,\"journal\":{\"name\":\"Journal of Hospitality and Tourism Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2023-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hospitality and Tourism Technology\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1108/jhtt-01-2022-0013\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hospitality and Tourism Technology","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/jhtt-01-2022-0013","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}

引用次数: 0

摘要

目的本研究旨在了解旅行者如何根据推荐的规模和他们的旅行参与程度来评估从人工智能（AI）或人类旅行专家（TE）那里收到的旅行目的地推荐。设计/方法论/方法本研究使用了2（代理类型：AI与TE） × 2（推荐大小：小与大） × 2（旅行参与度：低与高）受试者之间的设计。发现当人工智能推荐目的地时，参与度较低的旅行者认为这些推荐更可信，当人工智能提供的推荐比小的推荐更大时，他们会信任系统。与此同时，当TE提供建议时，无论建议规模和旅行参与程度如何，旅行者都会认为这些建议同样可信，并同样信任该系统。创意/价值本研究揭示了以人为中心的人工智能旅行目的地推荐服务的设计。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Role of recommendation sizes and travel involvement in evaluating travel destination recommendation services: comparison between artificial intelligence and travel experts

Purpose This study aims to understand how travelers evaluate travel destination recommendations received from either artificial intelligence (AI) or human travel experts (TEs) based on the size of recommendation and their travel involvement. Design/methodology/approach This study used a 2 (agent type: AI vs TE) × 2 (size of recommendation: small vs large) × 2 (travel involvement: low vs high) between-subjects design. Findings When AI recommends destinations, less-involved travelers perceive the recommendations as more credible and trust the system when AI offers larger recommendations than smaller ones. Meanwhile, when TEs offer recommendations, travelers consider the recommendations as equally credible and similarly trust the system, regardless of the recommendation size and travel involvement. Originality/value This study sheds light on the design of human-centered AI travel destination recommendation services.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Hospitality and Tourism Technology HOSPITALITY, LEISURE, SPORT & TOURISM-

CiteScore

8.40

自引率

12.80%

发文量

期刊介绍： The Journal of Hospitality and Tourism Technology is the only journal dedicated solely for research in technology and e-business in tourism and hospitality. It is a bridge between academia and industry through the intellectual exchange of ideas, trends and paradigmatic changes in the fields of hospitality, IT and e-business. It covers: -E-Marketplaces, electronic distribution channels, or e-Intermediaries -Internet or e-commerce business models -Self service technologies -E-Procurement -Social dynamics of e-communication -Relationship Development and Retention -E-governance -Security of transactions -Mobile/Wireless technologies in commerce -IT control and preparation for disaster -Virtual reality applications -Word of Mouth. -Cross-Cultural differences in IT use -GPS and Location-based services -Biometric applications -Business intelligence visualization -Radio Frequency Identification applications -Service-Oriented Architecture of business systems -Technology in New Product Development