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The purpose of current study aims to provide a different perspective on customer-based brand equity (CBBE) and integrate this with previous brand equity theory to contribute to the brand equity literature.

Proposed hypotheses were verified using structural equation modelling (SEM) with multiple datasets. Study 1 collected data from 574 foreign tourists and 624 domestic tourists of culinary tourism. Study 2 used 1,020 customers from anti-epidemic restaurants, and Study 3 investigated 464 hotel customers’ perceptions of customer-based brand equity.

Building on the mediation-moderation model, the present study posits that perceived quality relates to brand loyalty through brand image and brand awareness of using 2,682 participants. Specifically, we argue that this indirect relationship exhibits a difference moderated pattern in which motivation and hedonic function are most likely to benefit from revisit destinations for tourists when they are moderate. We further explored the new anti-epidemic concepts of COVID-19 and identified restaurant operation as an important moderator that influences customer image of restaurant revisit.

Until now, no tourism and hospitality studies have addressed these unsolved problems in an integrated manner. This study was to investigate the brand equity development process.

The present study’s aims are twofold: 1) to contribute to theory development by accounting for both personality and trust in the conceptualization of technology acceptance using the technology acceptance model (TAM) as the theoretical framework; and 2) to explore the influence of ChatGPT-integrated chatbots on tourism behavior.

The target population for this study was travelers who previously used technology (website/ app) to plan their holiday abroad. An online survey questionnaire created with Google Forms was distributed via a panel company (iPanel). A screening question was included to filter out respondents who have not previously used technological means to plan their holiday abroad. A panel company (iPanel) was hired to collect data from a convenience sample of 305 Israeli tourists who met the above criterion between August 22 and 27, 2023, and were at least 18.

A significant and positive relationship was observed between trust in ChaptGPT and perceived usefulness. Furthermore, a significant and positive association was observed between perceived ease of use and intentions to use ChatGPT-integrated chatbots to plan future holidays. Post hoc analyses suggest that perceived ease of use mediates the relationship between extraversion and trust, trust mediates the relationship between perceived ease of use and perceived usefulness and age moderates the relationship between perceived ease of use and behavioral intentions.

Data was collected from a convenience sample of Israeli travelers. Hence, generalizations to other countries, nationalities and cultures should be treated carefully; the study is cross-sectional and thus represents respondents’ beliefs and behavioral intentions at a particular time; and the study is based on one of several theoretical frameworks that can be used to conceptualize behaviors associated with using AI by tourists.

The findings of the present study point to the importance of accounting for tourists’ personal factors, such as personality and age, in developing AI products in the tourism industry. chief executive officers and relevant shareholders would benefit from conducting market research to obtain insights into the factors that may enhance or hamper tourists’ adoption of AI-based technology for planning their holidays abroad.

Previous work falls short of accounting for personality traits and trust in a single model using the TAM framework. To the best of the authors’ knowledge, this is the first study empirically investigating tourism behavior related to ChatGPT based chatbots as a tool to plan future holidays abroad. Furthermore, the possible role of age as a moderating variable was overlooked in past research.

本研究的目标有两个：1）采用技术接受模型作为理论框架, 通过考虑技术接受概念化中的个性和信任来促进理论发展; 2）探讨ChatGPT集成的聊天机器人对旅游行为的影响。

本研究的目标人群是以前使用技术（网站/应用程序）计划出国度假的旅行者。使用 Google Forms 创建的在线调查问卷通过小组公司 (iPanel) 分发。其中包含一个筛选问题, 以筛选出之前未使用技术手段计划出国度假的受访者。聘请了一家调查公司（iPanel）来收集 305 名以色列游客的便利样本数据, 这些游客在 2023 年 8 月 22 日至 27 日期间符合上述标准, 且年龄至少为 18 岁。

在 ChaptGPT 的信任度和感知有用性之间观察到显着且积极的关系。此外, 观察到易用性与使用集成 ChatGPT 的聊天机器人来计划未来假期的意向之间存在显着且正相关的关系。事后分析表明, 感知的易用性调节了外向性和信任之间的关系; 信任调节感知易用性和感知有用性之间的关系, 年龄调节感知易用性和行为意愿之间的关系。

以前的工作未能在单个模型中使用技术接受模型框架来解释个性特征和信任。这是第一项实证研究, 调查与 ChatGPT 集成聊天机器人相关的旅游行为, 作为规划未来出国度假的工具。此外, 过去的研究忽视了年龄作为调节变量的可能作用。

1）数据是从以色列旅行者的便利样本中收集的。因此, 应该谨慎对待对其他国家、民族和文化的概括; 2）该研究是横断面的, 因此代表了受访者在特定时间的信念和行为意愿; 3）该研究基于几个理论框架之一, 该框架可用于概念化游客使用 ChatGPT 集成聊天机器人来计划未来出国度假的意向。

本研究的结果表明, 在开发用于旅游业的基于 ChatGPT 的聊天机器人时, 考虑游客的个人因素（例如个性和年龄）的重要性。首席技术官和相关股东将受益于进行市场研究, 以深入了解可能增强或阻碍游客采用基于 ChatGPT 的聊天机器人来规划未来出国度假的因素。

Los objetivos del presente ossib son dos: 1) contribuir al ossibleo de la teoría incorporando la personalidad y confianza en la conceptualización de la aceptación de la tecnología empleando el Modelo de Aceptación de la Tecnología como marco teórico; 2) analizar la influencia de los chatbots integrados en ChatGPT en el comportamiento turístico.

La población objetivo de este ossib fueron los viajeros que anteriormente utilizaban tecnología (página web/aplicación) para planificar sus vacaciones en el extranjero. Se distribuyó un cuestionario online creado con Google Forms a través de una empresa de paneles (iPanel). Se incluyó una pregunta de selección para filtrar a los encuestados que no habían utilizado previamente medios tecnológicos para planificar sus vacaciones en el extranjero. Se contrató a una empresa de paneles (iPanel) para recopilar datos de una muestra de conveniencia de 305 turistas israelíes que cumplieron el criterio anterior entre el 22 y el 27 de ossib de 2023, y con una edad ossib de 18 años.

Se identificó una relación ossibleon y ossible entre la confianza en ChaptGPT y la utilidad percibida. Además, se evidenció una asociación ossibleon y ossible entre la facilidad de uso percibida y la intención de ossible chatbots integrados en ChatGPT para planificar futuras vacaciones. Los análisis post-hoc sugieren que la facilidad de uso percibida media la relación entre la ossibleon y la confianza; la confianza media la relación entre la facilidad de uso percibida y la utilidad percibida, y la edad modera la relación entre la facilidad de uso percibida y las intenciones de comportamiento.

1) los datos se recopilaron de una muestra de conveniencia de viajeros israelíes. Por tanto, las generalizaciones a otros países, nacionalidades y culturas deben tratarse con cuidado; 2) el ossib es transversal y, por tanto, representa las creencias y las intenciones de comportamiento de los encuestados en un momento determinado; 3) el ossib se basa en uno de los diversos marcos teóricos que pueden emplearse para conceptualizar la intención de los turistas de ossible chatbots integrados en ChatGPT para planificar futuras vacaciones en el extranjero.

Los resultados del presente ossib señalan la importancia de tener en cuenta los factores personales de los turistas, como la personalidad y la edad, en el ossibleo de chatbots basados en ChatGPT para su uso en la industria turística. Los directores de tecnología y los stakeholders relevantes se beneficiarían de investigación de mercado para obtener información sobre los factores que pueden mejorar o dificultar la adopción de chatbots basados en ChatGPT por parte de los turistas para planificar futuras vacaciones en el extranjero.

Los trabajos anteriores no tienen en cuenta los rasgos de personalidad y la confianza en un único modelo utilizando ossible TAM. Este es el primer ossib que investiga empíricamente el comportamiento turístico relacionado con los chatbots basados en ChatGPT como herramienta para planificar las futuras vacaciones en el extranjero. Además, en investigaciones anteriores no se ossible el ossible papel de la edad como variable moderadora.

Logistics and supply chain management (L&SCM) scholars and practitioners have devoted extensive efforts to advancing green logistics practices (GLPs), yet the intersection between the two domains in relation to the topic remains underexplored. To accelerate GLPs’ development amid the escalating climate crisis, this research examines this intersection by comparing the responsiveness of academia and practice to the call for green logistics over time.

To compare between academia and practice, we combined a systematic literature review on the development of GLPs in L&SCM journals (N = 122) with a content analysis of annual and sustainability reports published by the four major global logistics service providers (LSPs: DHL, DB Schenker, UPS and FedEx; N = 156) over the past three decades.

This research reveals that all the GLPs covered in the L&SCM literature have already been applied and reported by practitioners, both consistently and over a significant period of time. Academic progress, in turn, is delayed by slow-paced empirical methods, elevated research quality standards, prolonged funding and recruitment processes, and extended peer-review intervals. Further, a tendency toward reactive knowledge creation rather than proactive knowledge transfer is evident, obscuring the role of L&SCM scholars in steering the industry’s green advancement.

Recommendations are offered to L&SCM authors, editors, reviewers and university departments to advance pracademic endeavors in green logistics research and increase its responsiveness to global events.

This is one of the first studies to scrutinize the intersection between academia and practice on the evolution of GLPs. The revealed gaps prompted us to suggest a transformative paradigm for academia-practice collaborations targeting the L&SCM discipline at large, combining a bold proactive research stream aimed at knowledge transfer with a more traditional reactive stream aimed at knowledge creation.

The present research aims to explore the drivers of generative artificial intelligence (GEN AI)-based innovation adoption in the hospitality industry in Jordan.

To address the research gap and achieve the research work objectives, the Technology-Organization-Environment (TOE) lens and the structural equation modeling (SEM) approach were employed to analyze the sample data collected (n = 221) from the hospitality industry.

The findings indicate that relative advantage, top management support, organizational readiness, organizational culture, competitive pressures, government regulations support and vendor support significantly influence the GEN-AI-based innovation adoption, while the technological complexity is negatively associated with GEN-AI-based innovation adoption. Furthermore, the results showed there is no significant effect of cost on GEN-AI-based innovation adoption.

The paper analyses the TOE framework in a new technological setting. The paper also provides information about how GEN-AI-based innovation adoption may influence hospitality industry performance. Overall, this article provides new insights into the literature concerning AI technologies and through the TOE lens.

The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.