Synthetic WOM? The Emergence of Generative Artificial Intelligence-Induced Recommendations DOI
Dušan Mladenović, Moein Beheshti, Tomaž Kolar

и другие.

Journal of Computer Information Systems, Год журнала: 2024, Номер unknown, С. 1 - 18

Опубликована: Окт. 25, 2024

This paper examines how Generative Artificial Intelligence (GAI) influences word-of-mouth (WOM) in travel and hospitality, focusing on synthetic WOM (syWOM). It explores GAI-driven reshapes traveler interactions decision-making an experience-centric industry. Using a literature review conceptual analysis approach1, this study the integration of GAI tools, such as ChatGPT, to enhance experiences. The presented highlights GAI's potential inducing syWOM its effects perceptions behaviors. Additionally, it addresses emerging role WOM, emphasizing need for further research impact planning engagement. presents fresh view interaction with travel, aiming inform future practical applications personalized

Язык: Английский

An empirical analysis of eWOM valence effects: Integrating stimulus-organism-response, trust transfer theory, and theory of planned behavior perspectives DOI
Muhammad Dliya'ul Haq, Ting‐Hsiang Tseng, Hsiang‐Lan Cheng

и другие.

Journal of Retailing and Consumer Services, Год журнала: 2024, Номер 81, С. 104026 - 104026

Опубликована: Авг. 14, 2024

Язык: Английский

Процитировано

10

The restaurant delivery problem with uncertain cooking time and travel time DOI
Guiqin Xue, Zheng Wang, Yong Wang

и другие.

Computers & Industrial Engineering, Год журнала: 2024, Номер 190, С. 110039 - 110039

Опубликована: Март 3, 2024

Язык: Английский

Процитировано

8

Does eWoM matter in s-commerce? A comparatives study between Kuwait and United Arab Emirates DOI Creative Commons
Hasan A. Abbas, Kamel Rouibah, Nabeel Al-Qirim

и другие.

Global Knowledge Memory and Communication, Год журнала: 2025, Номер 74(11), С. 140 - 162

Опубликована: Янв. 24, 2025

Purpose This study aims to explore the antecedent factors that directly and indirectly influence electronic word of mouth (eWoM) for social commerce (s-commerce) in two developing countries (e.g. Kuwait United Arab Emirates [UAE]) by extending cognitive theory. Design/methodology/approach uses a previous robust model (Rouibah et al. , 2021) as theoretical background investigate compares antecedents (trust Instagram, perceived risks) on eWoM s-commerce through mediation three mediators (perceived enjoyment, value customer satisfaction) among countries. Data was collected from ( n = 1,132) UAE 190). Different statistical analyses structured equation modeling-based analysis moment structure are used test robustness research model. Findings found satisfaction be most important factor mediates effect independent both Surprisingly, enjoyment has no effect, trust Instagram risks considered imperative positive feedback. Research limitations/implications One limitation this is author does not focus difference between effects textual graphical information customers’ decisions buying merchandise. Another focuses UAE. Other Gulf Cooperation Council also growing exponentially, mobile internet penetration rates booming; they could trigger more studies whether differences occur all them. Practical implications The first implication it its field extend eWoM. To best author’s knowledge, compared online unique because authors examine six using platform opposed other platforms. Social third ones have applied different subjects e-commerce such tourism marketing but concentrated less s-commerce, where in-depth needed much theories explain human behavior. Originality/value Furthermore, these focused intention use (Dincer Dincer, 2023; X. Hu, Chen, Davison, Liu, 2022; Zhou 2023). However, attention actual use.

Язык: Английский

Процитировано

0

One out of five stars! Negative restaurant attributions post-dissatisfactory delivery DOI
Deniz Kuter,

Gülden Asugman

International Journal of Hospitality Management, Год журнала: 2025, Номер 128, С. 104167 - 104167

Опубликована: Март 22, 2025

Язык: Английский

Процитировано

0

The review sentiment garden: Blossoming loss aversion and diminishing sensitivity across time and crisis DOI
Abhinav Sharma, Seunghun Shin, Juan Luis Nicolau

и другие.

International Journal of Hospitality Management, Год журнала: 2025, Номер 129, С. 104170 - 104170

Опубликована: Март 27, 2025

Язык: Английский

Процитировано

0

Instant Logistics Service DOI
Poshan Yu, Y. XIA, Jean-Yves Le Corre

и другие.

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 223 - 250

Опубликована: Апрель 2, 2025

As e-commerce thrives, instant logistics is crucial for food delivery. This study commences with an in-depth analysis and literature review of “Instant Logistic”, Food Delivery”, “Evaluation Instant Delivery Service Level”. Noting the absence a comprehensive service-level evaluation system delivery, it identifies main influencing factors like “delivery timeliness”, “quality”, “standardization”, “reliability” via reports. Using questionnaire surveys, correlation, multiple-linear regression analyses, determines factors' weights in service evaluation. A Robustness test validates model. research refines system, guiding delivery-scenario assessment. Its findings offer theoretical practical insights optimizing boosting customer satisfaction, fostering industry's sustainable growth.

Язык: Английский

Процитировано

0

Triadic service failure and recovery: a literature review and guide to avenues for future research DOI
Lifei Bai, Tianshu Chu, Xiaorong Fu

и другие.

Nankai Business Review International, Год журнала: 2025, Номер unknown

Опубликована: Апрель 18, 2025

Purpose This study addresses the gap in understanding of triadic service failure and recovery (TSFR). It systematically assess TSFR domain by analyzing research trends, identifying gaps proposing avenues for future investigation. Design/methodology/approach systematic literature review analyzes 72 articles published between 2000 2024 related to TSFR. used a bibliometric analysis approach examine trends identify patterns existing literature. An “actor-context-tie” lens, complemented theoretical was adopted unpack complexities interactions knowledge gaps. Findings The reveals limitations prevalent theories applied highlights increasing actor plurality within transactions, diversified contexts emergence increasingly networked relationships. delineates structure knowledge, observes an evolving stemming from inadequacy dyadic models addressing complexity limited explanatory power framework. Originality/value provides first comprehensive overview TSFR, charting revealing through lens. offers objective assessment field proposes three directions, aiming revitalize interest provide novel dynamics.

Язык: Английский

Процитировано

0

Exploring the social diffusion effects of green consumption: Evidence from green innovative products DOI
Zhihao Wang, Wei Li, Mengxin Wang

и другие.

Journal of Retailing and Consumer Services, Год журнала: 2024, Номер 79, С. 103893 - 103893

Опубликована: Май 7, 2024

Язык: Английский

Процитировано

3

It’s all your fault! restaurant vs. platform blame attribution in food delivery service failures DOI
Sarah Lefebvre, Marissa Orlowski, Laura Boman

и другие.

British Food Journal, Год журнала: 2024, Номер 126(8), С. 3037 - 3050

Опубликована: Июль 15, 2024

Purpose While third-party food delivery continues to increase in popularity, surveys suggest nearly a quarter of deliveries suffer from service failures. With the limited research on delivery, we explore important questions (1) where customers place blame case failures with (i.e. platform or restaurant) and (2) does this depend type failure? Drawing attribution theory, signaling an exploratory study, demonstrate that typically perceive such mishaps be responsibility restaurant rather than itself. We also examine effect visible failure preventative actions taken by re-order intention. Design/methodology/approach conducted two online scenario-based studies customer failure. First, study approach (N Study1 = 512 ) was provide additional support for hypothesis development. An experiment Study2 252 then hypothesized effects. Findings results attribute as wrong items, missing cold food, leaking containers restaurants over platforms. Second, experimental inclusion observable cue indicating action, time-stamp information when order received packaged increases intention through underlying mechanism attribution. Originality/value contribute underexplored area our understanding scenarios. Further, practical method shift away are outside establishment’s control.

Язык: Английский

Процитировано

2

Synthetic WOM? The Emergence of Generative Artificial Intelligence-Induced Recommendations DOI
Dušan Mladenović, Moein Beheshti, Tomaž Kolar

и другие.

Journal of Computer Information Systems, Год журнала: 2024, Номер unknown, С. 1 - 18

Опубликована: Окт. 25, 2024

This paper examines how Generative Artificial Intelligence (GAI) influences word-of-mouth (WOM) in travel and hospitality, focusing on synthetic WOM (syWOM). It explores GAI-driven reshapes traveler interactions decision-making an experience-centric industry. Using a literature review conceptual analysis approach1, this study the integration of GAI tools, such as ChatGPT, to enhance experiences. The presented highlights GAI's potential inducing syWOM its effects perceptions behaviors. Additionally, it addresses emerging role WOM, emphasizing need for further research impact planning engagement. presents fresh view interaction with travel, aiming inform future practical applications personalized

Язык: Английский

Процитировано

0