Consumers acceptance of service robots in hotels: A meta-analytic review DOI

Nusaiba Begum,

Mohd. Nishat Faisal,

Rana Sobh

и другие.

International Journal of Hospitality Management, Год журнала: 2024, Номер 126, С. 104052 - 104052

Опубликована: Дек. 27, 2024

Язык: Английский

Understanding tourist barriers and personality influences in embracing generative AI for travel planning and decision-making DOI Creative Commons
Siamak Seyfi, Myung Ja Kim, Amin Nazifi

и другие.

International Journal of Hospitality Management, Год журнала: 2025, Номер 126, С. 104105 - 104105

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

3

Investigating factors influencing AI customer service adoption: an integrated model of stimulus–organism–response (SOR) and task-technology fit (TTF) theory DOI
Ali Vafaei Zadeh, Davoud Nikbin,

Sing Sing Wong

и другие.

Asia Pacific Journal of Marketing and Logistics, Год журнала: 2024, Номер unknown

Опубликована: Окт. 29, 2024

Purpose Artificial intelligence (AI) customer service has grown rapidly in recent years due to the emergence of COVID-19 and growth e-commerce industry. Therefore, this study employs integration stimuli–organism–response (SOR) task-technology fit (TTF) frameworks understand factors that affect individuals’ intentions towards AI adoption Malaysia. Design/methodology/approach The utilised a survey-based research approach investigate data were collected by conducting an online survey targeting individuals aged 18 or above who had prior interaction experience with human agents but not yet adopted service. A sample 339 respondents was used evaluate hypotheses, adopting partial least squares structural equation modelling as symmetric analytic technique. Findings PLS-SEM analysis revealed social influence anthropomorphism have positive direct relationship emotional trust. Furthermore, communicative competence, technology characteristics perceived positively correlated TTF. Moreover, trust significantly impacts adoption. In addition, readiness moderates association between task Practical implications provides insights individuals, organisations, government educational institutions improve features its development Originality/value originality is found SOR theory TTF affecting Additionally, it incorporates moderating variables during analysis, adding depth findings. This introduces new perspective on impact offers valuable for practitioners seeking formulate effective strategies promote

Язык: Английский

Процитировано

6

Generative artificial intelligence in hospitality and tourism: future capabilities, AI prompts and real-world applications DOI
Mahmoud Ibraheam Saleh

Journal of Hospitality Marketing & Management, Год журнала: 2025, Номер unknown, С. 1 - 32

Опубликована: Янв. 30, 2025

Язык: Английский

Процитировано

0

Facing the next chapter of smartness: Designing smarter hospitality customer experience with artificial intelligence of things (AIoT) DOI
Hsuan Hsu

International Journal of Hospitality Management, Год журнала: 2025, Номер 128, С. 104163 - 104163

Опубликована: Март 19, 2025

Язык: Английский

Процитировано

0

Two decades of research on customer satisfaction: future research agenda and questions DOI
Robin Nunkoo, Anuj Sharma, Kevin Kam Fung So

и другие.

International Journal of Contemporary Hospitality Management, Год журнала: 2025, Номер unknown

Опубликована: Март 21, 2025

Purpose This paper aims to review two decades of research on customer satisfaction identify key topics, their prevalence and changes in each topic’s relative popularity over time. It also addresses interdisciplinarity studies. Design/methodology/approach The data set comprises 1,316 journal articles published between 2000 2023. authors used structural topic modeling extract defining themes research. analyzed the references cited these sources assess studies’ interdisciplinarity. Findings analysis revealed 10 conceptually distinct topics with varying degrees evolutionary paths. noted that numerous academic disciplines, such as general business, marketing, psychology, information systems statistics, have influenced Practical implications study’s findings provide valuable insights for tourism hospitality industries. Practitioners can refer results understand trends consumer behavior. For example, emerging transformative service suggest issues well-being should be considered when designing products. Originality/value Using modeling, extracted unbiased from a larger compared prior reviews tracked topics’ evolution. In addition, found evidence how various fields shaped study applies fresh approach theory development examines previously intractable problems. point questions merit investigation.

Язык: Английский

Процитировано

0

Promoting sustainable hospitality: examining the impact of voice assistant recommendations on customer engagement in pre-travel decision-making: moderating effects of use purpose and cultural orientation DOI Creative Commons
Han-Ling Jiang,

Lin-Hua Lu,

Tsunwai Wesley Yuen

и другие.

Journal of Hospitality Marketing & Management, Год журнала: 2025, Номер unknown, С. 1 - 39

Опубликована: Март 26, 2025

Язык: Английский

Процитировано

0

Artificial intelligence (AI) technology, its applications and the use of AI powered devices in hospitality service experience creation and delivery DOI
Doğan Gürsoy

International Journal of Hospitality Management, Год журнала: 2025, Номер unknown, С. 104212 - 104212

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

How Not to Collaborate with Large Language Models: The Current Impossibility of Social Cognition with AI Systems DOI
Robin L. Zebrowski

Oxford University Press eBooks, Год журнала: 2025, Номер unknown

Опубликована: Апрель 3, 2025

Abstract Since the public unveiling of OpenAI’s ChatGPT in 2022, there have been calls to embrace large language models as collaborators knowledge-creation. The claim is that bots can replace other human and enhance thinking individuals various tasks jobs, but often with a focus on academic work. Such divided communities, some calling for wide this technology (including integrating it into classes unintuitive areas, such writing humanities classes), while others call total abolition Generative AI. This article argues facts about what are how they work (their ontology) preclude possibility them being genuine participants social cognition. While avoiding traditional starting points computational/representational theories mind analyze questions AI cognition, focuses instead 4E approaches, endorsing explaining enactive claims nature participatory sense-making. It also includes discussion contributing factors may mislead us these systems, anthropomorphism fine distinctions between interaction Once an examination cognition enactivist-centered presented, concludes rejection collaboration model humans models, much weaker merely tools, not particularly good ones if task knowledge creation.

Язык: Английский

Процитировано

0

Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem DOI

Michael J. Ormond,

Eric H Garling,

J. Woo

и другие.

Arthroscopy The Journal of Arthroscopic and Related Surgery, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Consumers’ willingness to use the Metaverse for information search: An investigation of the underlying mechanism and critical determinants DOI
Doğan Gürsoy, Fabiola Sfodera, Niccolò Piccioni

и другие.

International Journal of Hospitality Management, Год журнала: 2024, Номер 124, С. 103957 - 103957

Опубликована: Окт. 22, 2024

Язык: Английский

Процитировано

3