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Switching to green energy is a crucial step in achieving carbon neutrality. This study aims to explore what motivates people to use green energy and how much more people are willing to pay for green energy.

Grounded on the value–attitude–intention hierarchy, this study proposes that environmental consciousness as a human value influences attitudes including attitude toward environmental issues and attitude toward ecosocial benefits while attitudes, information and knowledge about green energy and quality and price of green energy influence people’s intention to use green energy. Data were collected from 342 Chinese adults.

Results showed that environmental consciousness significantly and positively influenced attitudes while attitude toward environmental issues had the greatest effect on people’s intention to use green energy, followed by quality and price of green energy. About 44% respondents were willing to pay 2.5% to <5% more money for green energy.

This study extended the use of value–attitude–intention hierarchy to investigate what motivates people to use green energy. Specifically, this study demonstrated that quality and price, and knowledge and information also significantly shaped people’s intention to use green energy significantly.

This study aims to investigate the impact of geopolitical risk (GPR) on supply chain concentration (SCC) and the roles of operational capabilities and resources in this relationship.

Secondary longitudinal data from multiple sources is collected and combined to test for a direct impact of GPR on SCC. We further examine the moderating effects of firms’ operational capabilities and resources (i.e. firm resilience, operational slack and cash holding). Fixed-effect regression models are applied to test the hypotheses, followed by a series of robustness tests to check the consistency of the results.

Consistent with the tenets of resource dependence theory, our analysis reveals a significant negative impact of GPR on SCC. Moreover, we find that this adverse effect is attenuated for firms with higher levels of resilience, more operational slack and greater cash holdings. Further analysis suggests that maintaining a diversified supply chain base during heightened GPR is associated with a firm’s improved financial performance.

This study contributes to the supply chain management (SCM) literature by integrating GPR into the supply chain risk management framework. Additionally, it demonstrates the roles of diversification and operational resources in addressing GPR-induced challenges.

The main purpose of this chapter is to study and analyze the impact of metaverse (mixed reality) on health tourism in the major tourist destinations in India and the global market. This chapter is made as a case study with detailed mentions of factors for tourism promotion for metaverse, sustainability, and crisis management. This chapter has tried to explain the role of the metaverse in tourism marketing and the cognitive level of influence the metaverse possesses among tourists which makes them prefer repeated visits. Also, the chapter tried to assess the existing conditions in the tourism industry which positively or negatively impact the health sector due to the role of metaverse. This chapter ends with giving inspirational notes to future researchers to examine the conceptual understanding of metaverse as a major tool for destination tourism emphasizing health, wellness, and happiness.

Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure to Chinese economic policy uncertainty at the individual stock level in large Asian markets.

We estimate the monthly uncertainty exposure (beta) for each stock and then employ the portfolio-level sorting analysis to investigate the relationship between the China’s uncertainty exposure and the future returns of major Asian markets over multiple trading horizons. The raw returns of the high-minus-low portfolios are then adjusted using conventional asset pricing models to investigate whether the relationship is explained by common risk factors. Finally, we check the robustness of the portfolio-level results through firm-level Fama and MacBeth (1973) regressions.

Applying portfolio-level sorting analysis, we reveal that exposure to Chinese uncertainty is negatively related to the future returns of large stocks over multiple trading horizons in Japan, Hong Kong and India. We discover this is unexplained by common risk factors, including market, size, value, profitability, investment and momentum, and is robust to the specification of stock-level Fama and MacBeth (1973) regressions.

Our analysis demonstrates the spillover effects of Chinese economic policy uncertainty across the region, provides evidence of China's emerging economic leadership, and offers trading strategies for managing uncertainty risks.

The findings of the study significantly improve our understanding of stock return predictability in Asian markets. Unlike previous studies, our results challenge the leading role of the US by providing a new intra-regional return predictor, namely, China’s uncertainty exposure. These results also evidence the continuing integration of the Asian economy and financial markets. However, contrary findings for some Asian markets point toward certain market-specific features. Compared with market-level research, our analysis provides deeper insights into the performance of individual stocks and is of particular importance to investors and other market participants.

Drawing on power approach-inhibition theory, this study aims to theorize a cross-level model to examine how team member personal power (i.e. expert power and referent power) impacts shared leadership through activating their taking charge behaviors in R&D teams, as well as the moderating effect of team learning orientation on the relationship between team member taking charge behaviors and shared leadership.

With multisource data collected from 264 employees in 58 R&D teams from 13 companies, this study tested the hypotheses of the cross-level theoretical model using Mplus 7.4.

The results showed that team member expert power was positively related to their taking charge behaviors, which in turn led to shared leadership, while team member referent power was not significantly related to their taking charge behaviors. Furthermore, the positive relationship between team member taking charge behaviors and shared leadership was strengthened by team learning orientation.

This paper offers suggestions regarding how vertical leaders should pay attention to team member power to promote their change-oriented taking charge behaviors and address team learning to strengthen the effect of team member taking charge behaviors on shared leadership.

By echoing the changing focus towards a shared leading process among team members in leadership literature, this paper provides important insights for both scholars and practitioners to understand the role that power plays in activating team member taking charge behaviors which in turn improves shared leadership.

To a large extent, knowledge in government workplaces resides within the hierarchy as it provides unique services to the public. Governments should preserve and pass on valuable and irreplaceable knowledge in providing their services through learning by sharing. Yet, sharing requires time and effort. This study examines the motivations of civil servants to share knowledge and their knowledge-sharing behaviors.

The authors conducted an online survey to collect quantitative data from civil servants in the Hong Kong Government and obtained 104 useable responses to test the eight hypotheses comprising six constructs by structural equation modeling to explore the participants' knowledge-sharing behaviors.

Results indicated that (1) expected contribution was the primary source of motivation behind knowledge sharing; (2) participants engaged more frequently in informal than formal knowledge-sharing activities; and (3) there was a dire need for knowledge sharing focusing on explicit knowledge of work procedures.

The research focuses on motivational factors for knowledge sharing. Despite abundant literature about knowledge sharing in public or governmental organizations, scant studies focus on the motivations behind why expected rewards and expected associations have less significant impacts on the attitude toward knowledge sharing than expected contribution.

This study investigates how virtual reality (VR) travel attributes (e.g. sense and quality of information) influence spectators' flow experience, how emotion and past experience affect enjoyment and examines the impact of flow experience and enjoyment on satisfaction and booking or visiting intention.

The VR tour stimuli were fabricated using scenic views from the National Aquarium in the USA. Participants were equipped with Matterport VR and audio headsets and started their virtual travel. Once the participants completed their VR tours, they were asked to complete the questionnaire. Using the stimulus-organism-response theory, 303 valid responses were analyzed using partial least square structural equation modeling (PLS-SEM).

The results showed that the sense and quality of information in VR travel positively and significantly impacted the flow experience. Moreover, emotions and past experiences positively and significantly influenced the enjoyment of VR travel. Similarly, flow experience and enjoyment positively and significantly affect satisfaction. However, satisfaction with VR-related tourism experiences negatively affects users' bookings and visiting intentions.

This study concludes that, from Thai tourists' perspectives, virtual travel should be used as a solution only during the pandemic because, in the long term it can cause a loss to the business chain in the tourism industry.

To the best of the authors' knowledge, no prior research has examined the influence of past experiences and emotions on satisfaction with VR travel.

The metaverse has garnered increasing attention from researchers and practitioners, yet numerous firms remain hesitant to invest in it due to ongoing debates about its potential financial benefits. Therefore, it is crucial to analyze how the implementation of metaverse initiatives affects firms’ stock market value – an area that remains underexplored in the existing literature. Additionally, there is a significant lack of research on the contingency factors that shape the stock market reaction, leaving a noticeable gap in managerial guidance on the timing and benefits of investments in the metaverse. To narrow these gaps, we examine whether and when the implementation of metaverse initiatives enhances firms’ stock market value.

Based on 73 metaverse implementation announcements disclosed by Chinese listed firms during January 2021–August 2023, we employ an event study approach to test the hypotheses.

We find that metaverse implementation announcements elicit a positive stock market reaction. Moreover, the stock market reaction is stronger for technology-focused announcements and smaller firms, or when public attention to the metaverse is higher. Nevertheless, firms’ growth prospects do not significantly alter the stock market reaction.

This study extends the nascent literature on the metaverse by applying signaling theory to offer novel insights into the signaling effect of metaverse implementation announcements on stock market value and the boundary conditions under which the effectiveness of the signal varies. Besides, it provides managers with important implications regarding how to tailor the investment and information disclosure strategies of the metaverse to more effectively enhance firms’ stock market value.

The main aims of this study were to develop analytical scales for yachting tourism push-pull motivations and constraints, and analyze how these factors may influence the revisit intention of yachting tourists in China.

The analysis was conducted using the PLS-SEM, including the evaluation of measurement models and the structural models. SPSS18.0 and SmartPLS 3.3.5 software were used for statistical analysis.

We conducted a survey of 451 respondents who participate in yachting activities in Dalian, China and identified six push motivational factors (novelty and stimulation, sightseeing and leisure, sports and learning, social relationships, self-esteem and prestige and self-realization), three pull motivational factors (featured activities and services, destination environment, destination facilities) and two constraints (internal and external). Partial least squares structural equation modelling showed that all hypothesized interactions between identified factors were statistically significant and meaningful.

The push-pull-constraint model offers a new interpretation to the traditional push-pull model in theory, and the results contribute to local yacht industry sectors.

This study longitudinally investigated the predictors and mediators of adolescent smartphone addiction by examining the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3, as well as the separate and sequential role of adolescent self-esteem and depression at T2 as mediating factors.

This study used a hierarchical regression and the PROCESS macro (Model 6) to investigate research model by collecting 3,904 parent-adolescent pairs. Panel data were collected from three waves of the Korean Children and Youth Panel Survey (KCYPS).

First, the result showed that parental smartphone addiction at T1 significantly and positively predicted adolescent smartphone addiction at T3. Second, the serial mediation analysis revealed that the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3 was mediated by adolescent self-esteem and depression at T2 independently and serially.

The findings enhance our comprehension of the impact of parental smartphone addiction, adolescent self-esteem and depression, on adolescent smartphone addiction.