International Journal of Hospitality Management, Год журнала: 2024, Номер 126, С. 104052 - 104052
Опубликована: Дек. 27, 2024
Язык: Английский
International Journal of Hospitality Management, Год журнала: 2024, Номер 126, С. 104052 - 104052
Опубликована: Дек. 27, 2024
Язык: Английский
International Journal of Hospitality Management, Год журнала: 2025, Номер 126, С. 104105 - 104105
Опубликована: Янв. 15, 2025
Язык: Английский
Процитировано
5Asia 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
10Journal of Hospitality Marketing & Management, Год журнала: 2024, Номер unknown, С. 1 - 23
Опубликована: Июль 29, 2024
Using machine learning, we examined customers' opinions about the metaverse in hospitality industry (encompassing hotels, restaurant, gaming, virtual events, tours and travel). A total of 8,855 tweets were collected from Twitter (now called X), learning algorithms such as sentiment analysis topic modeling performed using Python libraries to capture important topics related applications. Nearly two thirds (60.9%) contained a mostly positive general toward use metaverse. Six emerged modeling: sightseeing, travel, business blockchain. Despite numerous studies on proper integration metaverse, VR AR, best our knowledge, this is one first conducted determine customer experience social media data.
Язык: Английский
Процитировано
7Journal of Hospitality Marketing & Management, Год журнала: 2025, Номер unknown, С. 1 - 32
Опубликована: Янв. 30, 2025
Язык: Английский
Процитировано
1International Journal of Hospitality Management, Год журнала: 2024, Номер 123, С. 103913 - 103913
Опубликована: Сен. 13, 2024
Язык: Английский
Процитировано
6International Journal of Hospitality Management, Год журнала: 2024, Номер 124, С. 103957 - 103957
Опубликована: Окт. 22, 2024
Язык: Английский
Процитировано
6Arthroscopy The Journal of Arthroscopic and Related Surgery, Год журнала: 2025, Номер unknown
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0International Journal of Hospitality Management, Год журнала: 2025, Номер 128, С. 104163 - 104163
Опубликована: Март 19, 2025
Язык: Английский
Процитировано
0International 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
0Journal of Hospitality Marketing & Management, Год журнала: 2025, Номер unknown, С. 1 - 39
Опубликована: Март 26, 2025
Язык: Английский
Процитировано
0