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Using the analogy of “If you build it, they will come” from the movie Field of Dreams, this study aims to draw on relational signaling and commitment–trust theories to examine the role of different types of trust (cognitive, affective and relational) in the relationship between relational-encounter quality and customer loyalty to service employees and to the organization in the case of an integrated casino resort. The study confirms that building it (trust), they (customers) will come to the casino exhibited in their loyalty to casino hosts and their affiliated casinos.

The study was conducted with very important person (VIP) customers who have a designated VIP host to provide them with personal services at an integrated casino resort in Macau. The questionnaire was distributed to the respondents by VIP hosts using WeChat and Tencent QQ.

The study shows that different types of trust (cognitive, affective and relational) play a significant mediation role in the relationship between relational-encounter quality and the customers’ loyalty to the hosts and their affiliated casinos.

To the best of the authors’ knowledge, this study is the first to investigate the roles of different types of trust (cognitive, affective and relational) in the relational encounter between casino hosts and VIP customers and provides insights into the link between service employees and their firm through the nurturing of the service encounter with the firm’s key accounts.

Most research on sustainable tourism has been devoted to understanding the determinants of tourists' sustainable behavior on a unidimensional construct, overlooking the importance of behavioral costs in sustainable travel behavior. To shed light on this issue, this study aims to quantitatively differentiate sustainable travel behaviors based on behavioral costs and to examine the impact of psychological factors on both low-cost and high-cost sustainable travel behaviors.

A survey of 470 tourists used Rasch analysis to measure the behavioral costs associated with sustainable travel behavior and partial least squares structural equation modeling (PLS-SEM) to test hypotheses.

The results indicate that the value-identity-personal norm model explains more variance in low-cost sustainable travel behaviors than in high-cost sustainable travel behaviors. This supports the central tenet of the low-cost hypothesis and also suggests that values and self-identity factors have a stronger influence on low-cost sustainable travel behavior. However, personal norms have a stronger influence on high-cost behaviors.

This research highlights the importance for tourism and destination managers to distinguish between different categories of sustainable travel behavior and to analyze their determinants separately. This allows for the development of tailored messages for specific groups of tourists based on the psychological drivers of sustainable travel behavior.

This study provides insights into the determinants of sustainable travel behaviors with different behavioral costs and highlights the importance of analyzing different categories of behaviors separately.

This study aims to synthesize the existing serious games designed to promote mental health in adolescents with chronic illnesses.

This study conducted a review following the guidelines of Joanna Briggs Institute and Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. Searches were conducted in databases PubMed, Scopus, Web of Science, Cochrane Library, cumulative index to nursing and allied health literature, PsycINFO, China national knowledge infrastructure Wanfang, VIP Database for Chinese Technical Periodicals and SinoMed from inception to February 12, 2023.

A total of 14 studies (describing 14 serious games) for improving the mental health of adolescents with chronic diseases were included. Of all the included games, 12 were not described as adopting any theoretical framework or model. The main diseases applicable to serious games are cancer, type 1 diabetes and autism spectrum disorder. For interventional studies, more than half of the study types were feasibility or pilot trials. Furthermore, the dosage of serious games also differs in each experiment. For the game elements, most game elements were in the category “reward and punishment features” (n = 50) and last was “social features” (n = 4).

Adolescence is a critical period in a person’s physical and mental development throughout life. Diagnosed with chronic diseases during this period will cause great trauma to the adolescents and their families. Serious game interventions have been developed and applied to promote the psychological health field of healthy adolescents. To the best of the authors’ knowledge, this study is the first to scope review the serious game of promoting mental health in the population of adolescents with chronically ill. At the same time, the current study also extracted and qualitatively analyzed the elements of the serious game.

This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs).

This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms.

The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age.

The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.

With technological innovation elements and the competitive market environment becoming increasingly complex, numerous firms utilize network embeddedness to achieve and sustain innovation. However, empirical research has not conclusively established which form of network embeddedness more effectively facilitates corporate innovation. Drawing on the heterogeneous network resources perspective, this study explores the impact of market network embeddedness, technology network embeddedness and their synergy on the green innovation performance of manufacturing small and medium-sized enterprises (SMEs). Furthermore, it investigates the moderating role of resource orchestration capability in these relationships.

Through an online questionnaire survey of Chinese manufacturing SMEs, 293 sample data were collected, and the hierarchical regression analysis was conducted to test the hypothesis.

The results indicate that market and technology network embeddedness significantly enhance green innovation performance, with the former exerting a more significant impact. Furthermore, the synergy between market and technology network embeddedness positively influences green innovation performance. Additionally, resource orchestration capability strengthens the positive effects of both market and technology network embeddedness on green innovation performance, while the moderating effect of resource orchestration capability on the relationship between the synergy of the two and green innovation performance was insignificant.

The study faced many limitations, such as collecting primary data, which relied on a questionnaire only, using cross-sectional data and examining only manufacturing SMEs.

Based on the heterogeneous network resources perspective and integrating social network theory and resource orchestration theory, this study explores the impact of network embeddedness on the green innovation performance of manufacturing SMEs, which sheds new light on the network embeddedness research framework and also enriches the antecedents of green innovation. In addition, this study provides implications on how manufacturing SMEs effectively utilize network embeddedness and resource orchestration capability to enhance green innovation performance.

This research explores the differential effects of pixel-level and object-level visual complexity in firm-generated content (FGC) on consumer engagement in terms of the number of likes and shares, and further investigates the moderating role of image brightness.

Drawing on a deep learning analysis of 85,975 images on a social media platform in China, this study investigates visual complexity in FGC.

The results indicate that pixel-level complexity increases both the number of likes and shares. Object-level complexity has a U-shaped relationship with the number of likes, while it has an inverted U-shaped relationship with the number of shares. Moreover, image brightness mitigates the effect of pixel-level complexity on likes but amplifies the effect on shares; contrarily, it amplifies the effect of object-level complexity on likes, while mitigating its effect on shares.

Although images play a critical role in FGC, visual data analytics has rarely been used in social media research. This study identified two types of visual complexity and investigated their differential effects. We discuss how the processing of information embedded in visual content influences consumer engagement. The findings enrich the literature on social media and visual marketing.

The Astroworld concert tragedy is used as an example of crisis (mis)management and the potential utility of the 4R model. Although the 4R model has been implemented in high-risk emergency management situations, it is useful in the PR field because of its actionable approach, creating a way for practitioners to prepare for and manage crisis situations.

This is an analysis of the crisis that occurred at Astroworld, spanning preparation, day-of events, casualties and enduring reputational impact. The paper applies the 4R method to the Astroworld tragedy to show how it could have lessened or even prevented the tragedy. Finally, the SCCT model is used to explain why the official post-crisis statements were ineffective.

Social media has heightened the importance of a quick and effective organizational response to risk and crisis situations because poor responses can go viral quickly. However, social media also provides intelligence and crowd sourced information that can inform PR practitioners of emerging crisis scenarios. It is also an underutilized tool for two-way communication during crises.

The 4R approach is beneficial to general practitioners as it simplifies crisis best-practices, something essential for quick action. As our world changes and becomes less predictable, practitioners must have a clear plan to protect their organizations and the public surrounding them. This approach includes reduction, readiness, response and recovery, which are all essential in crisis communication.

The 4R method has not been explored or applied in the PR field. This paper highlights how the model has been utilized in the emergency management field and illustrates the way 4R can serve the PR field.

This paper aims to bridge the extended reality framework and the luxury hospitality literature by providing insights into how immersive technologies using artificial intelligence (AI) can shape luxury value and consumer differentiation.

The authors conducted three experimental studies comparing immersive AI versus traditional hospitality across luxury contexts (hotels, restaurants and spas). Study 1 investigates the effect of immersive AI (vs traditional hospitality) on customers’ behavioral intentions and the need for differentiation using virtual-assisted reality. Study 2 tests the underlying mechanism of the need for differentiation and luxury value in an augmented reality context. Study 3 provides additional support for the proposed underlying mechanism using virtual-assisted reality in luxury hospitality.

The findings reveal that immersive AI (vs traditional) luxury hospitality reduces customers’ behavioral intentions of using such services and perceived luxury value. Moreover, the findings indicate that the intention to use immersive AI (vs traditional) luxury hospitality services is contingent upon customers’ need for differentiation.

The findings have important theoretical and managerial implications for immersive technologies in luxury hospitality. They shed light on the dynamics between integrating immersive AI into luxury hospitality and its impact on customers’ differentiation motives and perceived luxury value. The findings reveal the detrimental effect of using immersive AI (vs traditional hospitality) within this context.

This paper aims to examine the influence of social media communications, particularly firm-generated content (FGC) and consumer-generated content (CGC) on predicting consumer purchase decisions (CPD) through the lens of perceived brand authenticity (PBA). This paper also investigates the moderating influence of brand prestige (BP) and brand familiarity in the luxury hotel sector.

This study collected data from 390 consumers who were regularly using social media platforms, traveled frequently and stayed in luxury hotels. Following stringent data filtering, 371 responses were analyzed via structural equation modeling.

The findings indicate that FGC and CGC significantly strengthened PBA. However, CGC was the effective driver that directly influenced CPD. Likewise, PBA directly and indirectly substantially impacted CPD. Finally, BP’s direct and moderating effects significantly influenced CPD in the luxury hotel sector.

This novel study contributes to signaling theory, social media communications and branding literature in the luxury hotel sector.

This paper aims to investigate the moisture diffusion behavior in a system-in-package module systematically by moisture-thermalmechanical-coupled finite element modeling with different structure parameters under increasingly harsh environment.

A finite element model for a system-in-package module was built with moisture-thermal-mechanical-coupled effects to study the subsequences of hygrothermal conditions.

It was found in this paper that the moisture diffusion path was mainly dominated by hygrothermal conditions, though structure parameters can affect the moisture distribution. At lower temperatures (30°C~85°C), the direction of moisture diffusion was from the periphery to the center of the module, which was commonly found in simulations and literatures. However, at relatively higher temperatures (125°C~220°C), the diffusion was from printed circuit board (PCB) to EMC due to the concentration gradient from PCB to EMC across the EMC/PCB interface. It was also found that there exists a critical thickness for EMC and PCB during the moisture diffusion. When the thickness of EMC or PCB increased to a certain value, the diffusion of moisture reached a stable state, and the concentration on the die surface in the packaging module hardly changed. A quantified correlation between the moisture diffusion coefficient and the critical thickness was then proposed for structure parameter optimization in the design of system-in-package module.

The different moisture diffusion behaviors at low and high temperatures have seldom been reported before. This work can facilitate the understanding of moisture diffusion within a package and offer some methods about minimizing its effect by design optimization.