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The purpose of this article is to examine the antecedents and consequences of organizational silence and employee silence to determine whether these two concepts should be distinguished rather than used interchangeably in research.

This study conducted a systematic literature review of 79 studies on organizational silence and 113 on employee silence, leading to three major findings.

First, this study shows that organizational silence is a collective phenomenon and employee silence occurs at the individual level; therefore, indicating they should be treated as two distinct concepts. Second, both types of silence are influenced by contextual factors (internal and external) and leadership. Third, organizational silence impacts both individual and organizational outcomes, whereas employee silence mainly affects an individual’s psychological health and performance.

This research clarifies the distinction between organizational silence and employee silence, offering guidance for researchers on how to approach these concepts. It also highlights the critical need to address workplace silence and the potential harm it may cause to both organizational and individual well-being if left unaddressed. Furthermore, this research supports organizational leaders and human resource developers in fostering a healthier work culture, improving performance and driving continuous improvement.

This study aims to identify the key characteristics of tourism live streamers (TLSers) that influence target consumers and examine how these characteristics enhance destination brand value by stimulating consumer emotional engagement and value co-creation behaviors.

A questionnaire survey was conducted with 552 respondents who had viewed tourism live streaming in China. The data were analyzed using structural equation modeling.

The results revealed that TLSers’ expertise had the strongest influence on consumers and positively affected their attachment, trust, participation and citizenship behaviors and perceived destination brand value. Attractiveness and trustworthiness exerted positive but weaker effects on these variables.

This study contributes to the theoretical development of live-streaming research by demonstrating the distinct impacts of TLSer characteristics. Furthermore, this study expands the application of the social exchange theory and value co-creation in tourism research.

本研究旨在确定影响目标消费者的旅游直播主（TLSers）的关键特征, 并检验这些特征如何通过激发消费者情感参与和价值共创行为来增强目的地品牌价值。

对在中国观看过旅游直播的552名受访者进行了问卷调查, 采用结构方程建模分析数据。

研究结果显示, TLSers的专业知识对消费者影响最大, 并积极影响他们的情感依恋、信任、参与和公民行为, 以及感知的目的地品牌价值。吸引力和可信度对这些变量的影响较弱但也是积极的。

本研究通过展示TLSer特征的独特影响, 对直播研究的理论发展做出了贡献。此外, 本研究扩展了社会交换理论和价值共创在旅游研究中的应用。

Metaverse is going to change the landscape in every field, sector, and business. This chapter aims to explore the role of marketing in the metaverse focusing on each sector and business. This chapter has adopted bibliometrics analysis to explore the importance of metaverse marketing. The results suggest that the publication and citation of articles have seen a huge jump from 2022 onwards. Keyword co-occurrence analysis shows that metaverse with blockchain, marketing, education, and virtual reality (VR) are hot words in the upcoming time. Metaverse marketing shows that innovation, mixed reality, and extended reality will change the landscape of marketing. Analysis suggests that China, the United States, South Korea, and India are the top contributing countries in the research of metaverse. By understanding the implications of the metaverse on purchaser conduct and promoting systems, organizations can draw in the main interest group and gain esteem in this new advanced scene.

Because the food service industry is more dependent on customer contact and human resources than other industries, it is crucial to understand the factors influencing employee job satisfaction to ensure that employees provide satisfactory service to customers. However, few studies have incorporated employee reviews of job portals into their research. Many job seekers tend to trust company reviews posted by employees on job portals based on the information provided by the company itself. Thus, this study utilized company reviews and job satisfaction ratings from employees in the food service industry on a job portal site, Job Planet, to conduct mixed-method research.

For qualitative research, we applied the Latent Dirichlet Allocation (LDA) model to food service industry company reviews to identify 10 job satisfaction factors considered important by employees. For quantitative research, four algorithms were used to predict job satisfaction ratings: regression tree, multilayer perceptron (MLP), random forest and XGBoost. Thus, we generated predictor variables for six cases using the probability values of topics and job satisfaction ratings on a five-point scale through LDA and used them to build prediction algorithms.

The analysis showed that algorithm accuracy performed differently in each of the six cases, and overall, factors such as work-life balance and work environment have a significant impact on predicting job satisfaction ratings.

This study is significant because its methodology and results suggest a new approach based on data analysis in the field of human resources, which can contribute to the operation and planning of corporate human resources management in the future.

The purpose of this study was to develop and test a research model that explored leader psychological capital (LPsyCap) as a predictor of follower creative performance (FCRP). The model also investigated follower job crafting (FJC) and follower knowledge collecting (FKC) and follower knowledge donating (FKD) behaviors as the multiple mediators of the trickle-down effect of LPsyCap on FCRP in a sequential manner.

Data were obtained from hotel employees in Korea. The hypotheses were tested using structural equation modeling with the user-defined estimands function.

LPsyCap boosted employees’ FCRP. FJC and FKC behaviors mediated the trickle-down effect of LPsyCap on FCRP in a sequential manner. As predicted, FKC behavior parallelly mediated the effect of FJC on FCRP.

Hotel firms should boost a workplace that would encourage employees to redefine and redesign their jobs. To achieve this, the presence of structural (e.g. learning new things in the workplace) and social (e.g. supervisor coaching) job resources and challenging job demands (e.g. willingly taking on additional tasks) would pay dividends.

This paper is one of its kind focusing on unexplored parallel and sequential multiple mediation effects that highlight FJC and FKC as the two potential mediators in the association between LPsyCap and FCRP.

Considering the limited understanding of determinants influencing the adoption of smart mobile tourism app (SMTA) featuring augmented reality (AR) and big data analytics (BDA), privacy concern (PC) and the risk of privacy information disclosure (PI) have threatened SMTA adoption. This study aims to propose an expanded consumer acceptance and use of information technology (UTAUT2) model by including new contextual components, integrated with privacy calculus theory (PCT) model to examine the determinants influencing behavioural intention (BI) to use SMTA.

Personal innovativeness (IN) and privacy information disclosure (PI) are incorporated in UTAUT2 model to determine its effect on SMTA featuring AR and BDA technologies from smart perspective. Both privacy concern (PC) and privacy risk (PR) derived from PCT model are also included to determine its influences on an individual's willingness to disclose privacy information for better-personalised services. We collected responses from 392 targeted participants, resulting in a strong response rate of 84.66%. These responses were analysed statistically using structural equation modeling in both SPSS 22.0 and SmartPLS 3.0.

Findings showed that personal innovativeness (IN), habit (HT) and performance expectancy (PE) significantly affect behavioural intention (BI) while privacy concern (PC) significantly affect privacy information disclosure (PI) to use SMTA. In contrast, effort expectancy (EE), hedonic motivation (HM) and privacy information disclosure (PI) had no significant effects on behavioural intention (BI) while privacy risk (PR) had no significant effects on privacy information disclosure (PI) to use SMTA.

The study findings help tourism practitioners in better comprehending recent trends of SMTA adoption for establishing targeted marketing strategies on apps to improve service quality. In addition, it enables app development companies acquire app users’ preferences to enhance their app development for leading app usage.

This study investigated the impacts of the technology acceptance model (TAM) determinants and image congruence on attitude and, in turn, behavioral intentions. In addition, the differences between the US and Korean consumers in terms of the predictors of attitude were assessed.

The data were collected via an online survey from 342 South Korean and 353 American consumers who patronized a restaurant within a three-month timeframe.

The findings revealed that two dimensions of TAM and three sub-factors of self-image congruence positively affected customer attitude toward face recognition (FR) payment. Customer attitude also significantly influenced behavioral intentions toward FR payment. Lastly, the cultural differences between the Korean and American consumers played significant moderating roles in the relationships between perceived usefulness and attitude as well as between actual self-image congruence and attitude.

No prior empirical research has incorporated cultural differences into the FR payment acceptance model. Unlike previous research, the current study included cultural differences as a moderator of the relationships between the five predictors (i.e. two predictors from TAM and three dimensions of self-image congruence) and attitude toward FR payment in the research model.

With recent advances in artificial intelligence, the hospitality industry has introduced the concept of unmanned smart hotels staffed by service robots instead of human employees. Research is needed to understand consumers’ receptivity to such an innovation. This paper examines factors associated with consumers’ potential resistance to using automated service hotels via two sequential studies. Given that younger generations of consumers are typically early adopters of advanced technology and innovative services, our sampling approach focused on this consumer group.

Two studies were conducted. Study 1 proposed and empirically tested a theoretical model. Results revealed that attitude, subjective norms and perceived behavioral control each positively influenced individuals’ intentions to use unmanned smart hotels. In Study 2, we further investigated aspects informing perceived security, a key variable in the use of unmanned smart hotels.

Findings showed how people’s beliefs about unmanned smart hotels and security control assurances led to perceived security. These perceptions were shaped by perceived physical risks, privacy concerns, website design and hotel reputation. Overall, this research provides theoretical and practical implications for various stakeholders associated with unmanned smart hotels.

Findings of this study suggested that managers of unmanned smart hotels should design user-friendly, secure processes and offer comprehensive support resources to enhance customer experience and usage.

The findings provide a holistic understanding of consumers’ receptivity to unmanned smart hotels.

This paper aims to examine the impact of metaverse experiences on customers’ offline behavioral intentions: How do customers’ visits to a hospitality business’s virtual property in the metaverse affect their intentions to visit the physical property in the real world?

Based on the general learning model and social cognitive theory, this research hypothesizes the positive impact of metaverse experiences on customers’ visit intentions and explores two boundary conditions for positive impact: user–avatar resemblance and servicescape similarity. Two experimental studies were conducted.

Metaverse experience has a significant impact on customers’ visit intentions, and this impact is moderated by user–avatar resemblance and servicescape similarity.

This research addresses the call for empirical studies regarding the effects of metaverse experience on people’s behavioral intentions.

As one of the earliest empirical studies on the marketing effects of the metaverse, this research provides a basis for future metaverse studies in the hospitality field.