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Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

The purpose of this study is to investigate (1) how managers respond to stock price crashes, (2) why they respond and (3) how their responses affect shareholders.

This study employs a panel regression with various firm-level controls and firm- and year-fixed effects. The sample is comprised of 101,532 firm-year observations with 11,727 unique firms from 1950 to 2019. Using mutual fund flow redemption pressure as an exogenous variable to stock price crashes, the paper provides further evidence of the causality of documented findings.

Management becomes more focused on improving transparency, raising investment efficiency, reducing agency conflicts and regaining the trust of shareholders by investing in social capital and employee welfare. These actions increase firm value. This study also suggests that management undertakes these actions out of concern for their tenure of employment.

The catalysts of stock price crashes are well documented, but much less is known about what happens following stock price crashes. This study provides more insights into the understanding of corporate crisis management practices following adverse events.

Using a mobile phone is increasingly becoming recognized as very dangerous while driving. With a smartphone, users feel connected and have access to information. The inability to access smartphone has become a phobia, causing anxiety and fear. The present study’s aims are as follows: first, quantify the association between nomophobia and road safety among motorists; second, determine a cut-off value for nomophobia that would identify poor road safety so that interventions can be designed accordingly.

Participants were surveyed online for nomophobia symptoms and a recent history of traffic contraventions. Nomophobia was measured using the nomophobia questionnaire (NMP-Q).

A total of 1731 participants responded to the survey; the mean age was 33 ± 12, and 43% were male. Overall, 483 (28%) [26–30%] participants received a recent traffic contravention. Participants with severe nomophobia showed a statistically significant increased risk for poor road safety odds ratios and a corresponding 95% CI of 4.64 [3.35-6.38] and 4.54 [3.28-6.29] in crude and adjusted models, respectively. Receiver operator characteristic (ROC)-based analyses revealed that NMP-Q scores of = 90 would be effective for identifying at risk drivers with sensitivity, specificity and accuracy of 61%, 75% and 72%, respectively.

Nomophobia symptoms are quite common among adults. Severe nomophobia is associated with poor road safety among motorists. Developing screening and intervention programs aimed at reducing nomophobia may improve road safety among motorists.

Large supermarket chains are adopting customer-service robots to improve service delivery in physical stores. Successful deployment of these robots depends on shoppers' willingness to interact with them, requiring an understanding of influencing factors. This study, grounded in the Cognitive-Affective-Normative (CAN) theory, seeks to systematically explore the factors influencing Gen Z shoppers' willingness to interact with customer-service robots.

A hybrid approach combining Structural Equation Modeling (SEM) and Necessary Condition Analysis (NCA) was employed to analyze survey data collected from 945 Gen Zs in the Czech Republic.

The results from SEM highlight significant cognitive, normative, and affective factors that influence the intention of Gen Z shoppers to interact with a customer-service robot. Specifically, cognitive factors such as effort and performance expectancy, along with normative factors like subjective norms, emerged as critical determinants. Furthermore, affective factors such as technology anxiety and positive emotions significantly influence users' readiness to use customer-service robots for service requests. The study also underscores that positive emotions, effort expectancy, performance expectancy, and subjective norms are vital prerequisites for interacting with customer-service robots.

The originality of this work lies in its two significant contributions to the burgeoning field of SRs in retail literature. First, it extends the CAN theory to the context of SRs among Gen Z shoppers in Czechia, thereby enriching the existing literature on SRs in retail. Second, by employing a hybrid analytical approach, our research offers both empirical and methodological advancements, providing rigorous insights crucial for enhancing the understanding of the pivotal factors influencing shoppers' interactions with SRs in physical store environments.

Secret consumption refers to consumption of a product in a private situation, with the intent or behavior of hiding the consumption from others. This study contributes to the secret consumption literature by identifying the antecedents of secret consumption along with the explaining mechanism and boundary condition.

An online study with experiment design was conducted to examine the impact of extroversion/introversion, self-presentation and product scarcity on secrete consumption.

The results show that consumer extraverted disposition and the self-presentation motive negatively influence secret consumption intention and suggest this relationship is explained by the self-presentation need. The findings also revealed that perceived product scarcity attenuated the negative impact of extraversion and self-presentation on secret consumption intention.

The findings provide interesting insights into advertising and retailing. In recognizing that secret consumption is a prevalent phenomenon in consumer behavior that may improve actual consumer product evaluation and preference, retailers or brand managers may encourage consumers to consume secretly.

This empirical study is a first attempt to explore the antecedents, mediating mechanism and boundary condition of consumer intention to engage in secrete consumption. The findings of the study provide important implication to theoretical development and managerial applications in advertising and retailing.

This paper explores the similarities and differences in privacy attitudes, trust and risk beliefs between younger and older adults on social networking sites. The objective of the article is to ascertain whether any notable differences exist between younger (18–25 years old) and older (55+ years old) adults in how trust and risk are influenced by privacy concerns upon personal information disclosure on social media.

A Likert scale instrument validated in previous research was employed to gather the responses of 148 younger and 152 older adults. The scale was distributed through Amazon Mechanical Turk. Data were analyzed through partial least squares structural equation modeling.

No significant differences were found between younger and older adults in how social media privacy concerns related to trust and risk beliefs. Two privacy concern dimensions were found to have a significant influence on perceptions of risk for both populations: collection and control. Predictability and a sense of control are proposed as two conceptual approaches that can explain these findings.

This article is the first one to explore age differences in privacy concerns, trust and risk on social media employing conceptual developments and an instrument specifically tailored to the social media environment. Based on the findings, several strategies are suggested to keep privacy concerns on social media at a minimum, reduce risk perceptions and increase users' trust.

The aim of this study is to assess the mediating effect of source appearance (SA) and self-influencer congruence (SIC) on the relationship between visual content (VC) and customer engagement (CE) towards mobile advertisement.

This study uses a quantitative approach to test the proposed model based on the stimulus–organism–response (SOR) theory. The non-probability purposive sampling technique was used to collect data from Pakistani mobile users through a self-administered questionnaire.

The study results prove that VC alone cannot generate mobile users’ engagement. SA is the key in this regard, which has a relatively higher importance compared to SIC. Furthermore, the serial mediation effect of SA and SIC on CE shows that attractive sources are likely to induce higher SIC and subsequent CE.

The results reveal that without a pleasing SA and positive SIC, mobile users skip the ads by perceiving them to be irritating or interruptive. Mobile ads might cost relatively less, but the advertisers should understand the significance of the SA toward minimizing the mobile advertising skepticism.

Advertisers can enhance the user’s engagement on mobile devices by addressing both the SA and SIC in their VC. The combined effect of both the SA and SIC on CE has not been assessed before. Furthermore, this study has used the SOR mechanism to examine CE.

El objetivo general de esta investigación es evaluar el efecto mediador de la apariencia de la fuente (SA) y la congruencia del auto-influencer (SIC) en la relación entre el contenido visual (CV) y el compromiso del cliente (CE) hacia la publicidad móvil.

Este estudio utiliza un enfoque cuantitativo para probar el modelo propuesto basado en la teoría estímulo-organismo-respuesta (SOR). Se utilizó la técnica de muestreo intencional no probabilístico para recoger datos de usuarios de móviles paquistaníes mediante un cuestionario autoadministrado.

Nuestros resultados demuestran que el contenido visual por sí solo no puede generar el compromiso de los usuarios de móviles. La apariencia de la fuente es la clave a este respecto, que tiene una importancia relativamente mayor en comparación con la congruencia del auto-influencer. Además, el efecto de mediación en serie de SA y SIC en CE muestra que es probable que las fuentes atractivas induzcan un mayor SIC y el consiguiente compromiso del cliente.

Los resultados revelan que sin una SA agradable y una SIC positiva, los usuarios de móviles omiten los anuncios al percibirlos como irritantes o interruptores. Los anuncios para móviles pueden costar relativamente menos, pero los anunciantes deben comprender la importancia de la apariencia de la fuente para minimizar el escepticismo de la publicidad móvil.

Los anunciantes pueden mejorar la participación del usuario en los dispositivos móviles abordando tanto la AS como el SIC en sus contenidos visuales. Hasta ahora no se había evaluado el efecto combinado de la AS y el SIC en el CE. Además, este estudio ha utilizado el mecanismo del SOR para examinar el engagement del cliente.

本研究的总体目标是评估源外观（SA）和自我影响者一致性（SIC）对移动广告视觉内容（VC）和客户参与（CE）之间关系的中介效应。

本研究采用定量方法来检验基于刺激-有机体-反应（SOR）理论提出的模型。研究采用了非概率目的性抽样技术, 通过自填问卷的方式向巴基斯坦移动用户收集数据。

我们的研究结果证明, 仅靠视觉内容并不能引起移动用户的参与。在这方面, 源外观是关键, 与自我影响者一致性相比, 源外观的重要性相对更高。此外, SA 和 SIC 对 CE 的串联中介效应表明, 有吸引力的信息源可能会诱发更高的 SIC 和随后的客户参与。

研究结果表明, 如果没有令人愉悦的SA和积极的SIC, 移动用户就会认为广告具有刺激性或干扰性, 从而跳过广告。移动广告的成本可能相对较低, 但广告商应了解广告源外观对减少移动广告怀疑的重要性。

广告商可以通过在视觉内容中同时考虑广告联盟和广告投放中心这两个因素, 提高用户在移动设备上的参与度。之前从未有人评估过 “SA “和 “SIC “对消费者参与度的综合影响。此外, 本研究还使用了 SOR 机制来考察客户参与度。

This study aims to identify, review and synthesize existing literature on key theories, drivers and barriers affecting consumer adoption or resistance to artificial intelligence (AI) in the hospitality sector.

This study aims to conduct a complete literature review of the accrued knowledge generated so far on AI in the hospitality sector. To attain the overall objectives of this study, we used the systematic literature review (SLR) method. This method systematically handles the diversity of knowledge in a specific topic to answer precise research questions. It also generates new visions through a synthesis of the literature, to identify the knowledge gaps, set the new directions for the future researcher and provide sufficient guidance to inform the policy and practice.

The findings of this study are presented in three sections, as follows: descriptive analysis, content analysis and synthesized framework. The findings highlighted the state-of-the-art mapping of the existing research in terms of publication frequency over time and across publication outlets, key theories, methods and geographies. In addition, literature on consumer adoption (or resistance) of AI in hospitality is content analyzed to highlight key drivers and barriers. Moreover, this review critically evaluates extant literature and sets future agendas by postulating specific research questions for further knowledge development in this field of study.

The SLR focused on consumer adoption or resistance to use AI in hospitality literature. The future researcher may include additional streams to get better results.

The study findings will help multiple stakeholders to understand the underlying causes of customer resistance or barriers to the intention to use/adopt AI services in the hotel sector. Furthermore, study results will allow them to better analyze the relationship between customer barriers, intents or consumer decision behaviors.

First, this study provides a comprehensive synthesis of the literature on the consumer adoption or resistance of AI in hospitality. This study categorizes the existing diversified literature in two main themes – drivers and barriers – to present a simplistic picture of the existing literature. Second, the review highlights the gaps and limitations in existing research and provides guidance for future scholars. Third, the key contribution of this review is the development of a unified framework on the consumer adoption or resistance of AI in the hospitality sector. That is, this study puts forward the behavioral reasoning theory framework and suggests that future research using this lens will immensely contribute to existing literature. Finally, this study facilitates the practitioners to understand the key motivating and hindering factors affecting the adoption and resistance behavior.

The purpose of this study is to explore whether five factors drawn from the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 significantly influence customers' intention to use hotel in-room voice assistants (VAs). It further examined culture as a moderator of the relationships between the five factors and customers' intention to use.

The authors collected data from US and Singapore to examine cultural differences in customer acceptance of in-room VAs. All hypotheses were tested via structural equation modeling and multi-group analysis.

The results showed that performance expectancy, social influence and hedonic motivation significantly affected customers' intentions to use in-room VAs, while effort expectancy and facilitating conditions did not. The results confirmed that culture did not play a substantial role in moderating the relationships between these factors and intentions to use.

This study established that the instrument and structural paths in the research model were equivalent across two samples from different countries. The findings may not generalize to other countries as the data arises from customers in the US and Singapore.

The findings provide important implications for hotel operators and vendors seeking to enhance customer acceptance of in-room voice technology.

This study addresses the gaps of extant research by developing and testing a research model to better understand the influential factors of in-room VA adoption within the hotel domain.