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This study aims to examine the influence of perceived organizational support (POS) on boundary-spanning behaviors (BSBs) among frontline employees in the hospitality industry. It also considered perceived supervisory support (PSS) as a moderating factor within a conceptual model.

Data were gathered from 651 full-time hospitality employees across 12 hotels in China. The analysis of the data used confirmatory factor analysis and structural equation modeling.

The findings revealed that POS influences hospitality boundary spanners’ BSBs, specifically external representation (ER), internal influence (II) and service delivery (SD). In addition, PSS moderates the relationship between POS and these frontline employees’ behaviors.

This study offers practical strategies for hospitality professionals to enhance frontline employees’ BSBs and foster supportive workplaces that drive employee excellence. These strategies encompass cultivating a supportive organizational culture, implementing supportive measures, fostering a sense of belonging among employees and ensuring supervisors’ well-being and competence in supporting their teams during daily interactions. These actions effectively motivate customer-contact employees to excel in their performance.

Fostering a helpful attitude in frontline employees is crucial for service firms’ success. Hospitality organizations must provide support to achieve this. Few studies have explored how organizational support contributes positively to the BSBs of customer-contact employees. This study goes beyond oversimplification and delves into the nuanced interplay between perceived support (POS and PSS) and hospitality frontline employees’ BSBs, focusing on ER, II and SD. The moderated mediating model enhances the understanding of support dynamics in the organizational context.

This study aims to investigate guests’ experience and perceptions in smart hotels, with a primary focus on the human−robot experience.

Utilizing a thematic analysis using the inductive-deductive approach, 546 reviews from Chinese smart hospitality guests, sourced from Ctrip, were examined.

This study identified five highest-level categories reflecting guests’ perceptions of smart hotels service with themes and subthemes of utilitarian gratification (smart servicescape and smart service quality), sensual gratification (novelty and coolness), social gratification (social presence and social interaction), experiential gratification (functional and emotional experiential value) and satisfaction.

This research enriches the current understanding of guests’ experience within smart hotels, focusing on the human−robot interaction. The findings offer insightful implications for the enhancement of smart hotels, specifically in terms of smart facility offerings, service delivery and overall customer experience.

本研究旨在调查顾客在智能酒店的体验和感知, 重点关注人机交互体验。

利用归纳-演绎方法进行主题分析, 对来自携程网的546份中国智能酒店客人评论进行了审查。

本研究确定了五个最高级别的类别, 反映了客人对智能酒店服务的感知, 涵盖了实用满足（智能服务环境和智能服务质量）、感官满足（新奇和酷炫）、社交满足（社交存在和社交互动）、体验满足（功能性和情感体验价值）和满意度的主题和子主题。

这项研究丰富了对智能酒店客人体验的当前理解, 重点关注人机交互。研究结果为智能酒店的提升提供了深刻的启示, 特别是在智能设施提供、服务交付和整体客户体验方面。

Customer referral programs (CRPs) are popular; however, they often generate low referral rates. The authors propose that certain CRP referral tasks may hinder consumers’ referral likelihood. This study aims to explore the effects of referral tasks (communication content and approach) on customers’ referral likelihood on social platforms and the role of self-construal.

This study establishes a theoretical model based on online social platforms and conducts three scenario-based experiments. The authors obtain data from consumers on Sojump platform and test the hypotheses using analysis of variance (ANOVA) analysis and mediation analysis in SPSS. The valid sample sizes for these three experiments are 288, 203 and 214, respectively.

Three experimental studies indicate that communication content and approach have a significant effect on referral likelihood. Furthermore, the effect of communication content on referral likelihood depends on the communication approach. Self-construal plays a moderating role in the effect of communication content and approach on perceived social costs.

CRPs typically involve tasks and rewards; consumers are asked to complete a referral task and then receive a reward. Both tasks and rewards can affect an individual’s willingness to participate; however, existing studies on CRP focus primarily on the reward component. To the best of the authors’ knowledge, this is the first study to systematically investigate the role of referral tasks (communication content and approach) in CRPs. The authors extend the related research by examining the impact of referral tasks on consumers’ willingness to recommend. In addition, this study introduces self-construal into CRPs research.

In order to make the construction industry develop in the direction of greening, this paper analyzes whether the application of intelligent technology in prefabricated buildings can achieve carbon emission reduction, starting from the problems of weak technology and insufficient encouragement policies in the prefabricated building industry. It also designs dynamic and adjustable incentives for the smart transformation of prefabricated buildings and makes recommendations to facilitate the transformation of assembly manufacturers into “smart factories”.

This paper takes the intelligent technology for carbon reduction, energy efficiency and policy design in the prefabricated buildings industry as the starting point. Based on in-depth expert interviews and questionnaire survey data, a linear multiple regression model is used to establish an association network of intelligent technology in the production and transportation, construction, operation and maintenance, demolition and scrapping stages. On this basis, an evolutionary game theory is used to construct a smart transformation and carbon reduction utility game model between the government and manufacturers, and relevant suggestions for smart empowerment of green construction development technology combinations and policy settings are proposed.

An assembly manufacturing plant with smart empowerment is an important way to achieve green and sustainable development in the construction industry. Among them, BIM and IoT have made a greater impact on carbon emission reduction of prefabricated buildings in all stages of the whole life cycle. The government’s proposed energy efficiency incentives and environmental tax amount will effectively increase companies' motivation for smart transformation of prefabricated buildings. However, when the environmental tax amount is low, the government should strengthen the regulation of the industry in order to increase the speed of smart transformation of assembly manufacturers. Therefore, a reasonable setting of the environmental tax rate and energy-saving incentives and flexible adjustment of the regulatory efforts can maximize the functional utility of the government in the process of smart transformation.

This paper focuses on the impact of intelligent technologies on the overall carbon emissions of the industry and provides an evolutionary analysis of the strategic game between the government and assembly manufacturers, the main players in the smart transformation process of prefabricated buildings. However, smart technologies for different categories of assembly manufacturing plants and strategic options for a wider range of stakeholders have not been examined in depth.

Different from existing research, this study focuses on exploring the strategic game between the government and assembly manufacturers in the smart transformation of prefabricated buildings. It provides an innovative explanation of the connection between intelligent technology and carbon emissions. The study develops an evolutionary game model for both parties, addressing the research gap on the combined effects of policy incentives and intelligent technology on carbon reduction and efficiency improvement in the prefabricated buildings industry. This research not only offers practical reference for the government in designing incentive mechanisms and establishing regulatory systems but also provides feasible practical guidance for the smart transformation and carbon reduction efforts of assembly manufacturing plants.

This study aims to identify the key factors that influence household pro-environmental behaviors (HPEBs) and explore the differences caused by the same influencing factors between household waste management behavior (HWM) and household energy-saving behavior (HES).

A meta-analysis was conducted on 90 articles about HPEBs published between 2009 and 2023 to find the key factors. HPEBs were further categorized into HWM and HES to investigate the difference influenced by the above factors on two behaviors. The correlation coefficient was used as the unified effect size, and the random-effect model was adopted to conduct both main effect and moderating effect tests.

The results showed that attitude, subjective norms, and perceived behavioral control all positively influenced intention and HPEBs, but their effects were stronger on intention than on HPEBs. Intention was found to be the strongest predictor of HPEBs. Subjective norms were found to have a more positive effect on HES compared to HWM, while habits had a more positive effect on HWM. Furthermore, household size was negatively correlated with HWM but positively correlated with HES.

The same variables have different influences on HWM and HES. These results can help develop targeted incentives to increase the adoption of HPEBs, ultimately reducing household energy consumption and greenhouse gas emissions and contributing to the mitigation of global warming.

As the complexity and uncertainty of infrastructural megaprojects challenge traditional management models, there is an increasing focus on value co-creation as an organizational strategy to streamline management. However, the role of value co-creation behavior in facilitating the value realization process remains underexplored. This study examines how justice perception (distributive, procedural and interactional justice) improves contractor value co-creation behavior, focusing on the mediating role of psychological ownership.

Ten hypotheses in the proposed research model were tested through partial least squares structural equation modeling using 199 valid questionnaires from China.

The results show that contractor value co-creation behavior is directly and positively influenced by procedural, distributive and interactional justice and indirectly influenced by them through the underlying psychological mechanism of psychological ownership.

The findings fill a knowledge gap by examining the effect of justice perception on contractor value co-creation behavior based on social exchange theory. Discovering justice perception will contribute to contractor value co-creation behavior, and psychological ownership mediates this relationship.

The purpose of this study is to investigate the effects of different bullet screen types (functional vs social) on the continuous watching intention of consumers, as well as the influence mechanism. In addition, this study analyses the moderating role of consumer motivational orientation on the above effects.

First, objective data were obtained through the crawler to test the proposed hypotheses. An objective data analysis (417 group sample) was conducted to analyse the relationship between the percentage of social bullet screens and consumers sustained growth ratio to indirectly test the primary effect. Second, a questionnaire survey was conducted to test (176 questionnaires) the mediating role of perceived social crowding. Finally, a simulated online contextual experiment (340 participants) is conducted to explore the moderating role of consumer motivational orientation.

First, functional bullet screens produce higher continuous watching intention and lower perceived social crowding than social bullet screens. Second, perceived social crowding mediates the relationship between bullet screen type and continuous watching intention. Third, consumers' motivational orientation type (task-motivated vs recreation-motivated) moderates the relationship among bullet screen type, perceived social crowding and continuous watching intention.

The results of this study shed light on the differential impact of different types of bullet screens (functional and social) on consumers' continuous watching intentions, which makes up for the lack of research on the content of bullet screens in the field of livestreaming. Meanwhile, compared with the previous positive psychological research perspective, this study explores the intermediate mechanism of bullet screen type on consumers' continuous watching intention through a negative psychological perspective, which helps e-commerce companies and streamers better understand the differential impact of different bullet screens. Finally, this study explores the joint influence effect of bullet screen and consumer motivation type, which fills the theoretical research gap of consumer motivation orientation type in the category of live-streaming.

This paper aims to explain the causal complexity between ecosystems of doing business and living standards based on the theoretical model of the ecosystem of doing business proposed by Li (2019) and Du et al. (2020). By integrating ecological theory, transaction cost theory and institutional logics theory, this study explored effective ecosystems of doing business that achieve high living standards and explained the interpretive mechanisms behind different ecosystems of doing business. Moreover, this study also analyzed whether there were any necessary elements that lead to high living standards and discussed how the interactions between these elements influence carrying capacity and transaction costs from government logic and market logic, thus affecting living standards.

In this study, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) were combined to analyze the data from the 2020 China City Statistical Yearbook, covering the main socioeconomic statistical data of cities at all levels in 2019.

This study found that no individual factor of the ecosystems of doing business was necessary to achieve high living standards, but the high level of human capital, innovation capacity, financial access and market demand play a significant role in achieving high living standards. Furthermore, two effective types of ecosystems of doing business lead to high living standards, namely, market dominance (government’s “invisible hand” or “nudging hand”) and government–market logic mutualism/symbiosis (government’s “helping hand”).

First, this work found that individual elements were not a necessary condition for high living standards, not only in kind but also in degree, complementing fsQCA with NCA, which indicates that environmental elements can be substituted by others. Second, this study considered the complex effects and explained the mechanisms behind different ecosystems of doing business, drawing on ecological theory, transaction cost theory and institutional logics theory from a configurational perspective. This study deepened the theories’ applications in the field of living standards and further discussed the elements interactions. Third, this study introduced configurational perspective and QCA into living standards research and adopted a mixed method that combines fsQCA and NCA to analyze the causal complexity between ecosystems of doing business and people’s living standards.

In the realm of open innovation (OI) networks, coopetition—where competition and cooperation coexist—plays a pivotal role in shaping the dynamics between diverse projects. This dual relationship is crucial for the propagation of knowledge and the bolstering of the network's overall resilience. While competition drives the quality of products and services, thereby reinforcing network resilience, cooperation facilitates knowledge diffusion, which is essential for the network's robustness.

We delve into the interplay between coopetition intensity and network resilience through the lens of knowledge diffusion. Our methodology begins with a sensitivity analysis to gauge the direct effects of coopetition on resilience. This is followed by a principal component analysis to identify the key determinants of coopetition intensity among projects. Finally, we utilize linear regression and moderation analysis to explore the mediating role of knowledge diffusion in the resilience of OI networks.

Our work is grounded in network theory, which provides a robust theoretical framework for understanding project coopetition and knowledge diffusion within the OI paradigm. This research not only offers a nuanced understanding of coopetition's impact on OI network resilience but also highlights the significance of knowledge diffusion as a critical mediating variable.

1) Identifies the significant influences in project coopetition (competition and cooperation). (2) Puts the conceptual framework and calculation method of the open innovation network resilience based on the project coopetition and knowledge diffusion. (3) Explores the moderating role of knowledge diffusion in project coopetition influencing open innovation networks resilience. (4) Measures the influence of project coopetition relationship on open innovation network resilience from the perspective of knowledge diffusion. (5) Encourages project management to consider the portfolios of coopetition.

This study aims to explain the privacy paradox, wherein individuals, despite privacy concerns, are willing to share personal information while using AI chatbots. Departing from previous research that primarily viewed AI chatbots from a non-anthropomorphic approach, this paper contends that AI chatbots are taking on an emotional component for humans. This study thus explores this topic by considering both rational and non-rational perspectives, thereby providing a more comprehensive understanding of user behavior in digital environments.

Employing a questionnaire survey (N = 480), this research focuses on young users who regularly engage with AI chatbots. Drawing upon the parasocial interaction theory and privacy calculus theory, the study elucidates the mechanisms governing users’ willingness to disclose information.

Findings show that cognitive, emotional and behavioral dimensions all positively influence perceived benefits of using ChatGPT, which in turn enhances privacy disclosure. While cognitive, emotional and behavioral dimensions negatively impact perceived risks, only the emotional and behavioral dimensions significantly affect perceived risk, which in turn negatively influences privacy disclosure. Notably, the cognitive dimension’s lack of significant mediating effect suggests that users’ awareness of privacy risks does not deter disclosure. Instead, emotional factors drive privacy decisions, with users more likely to disclose personal information based on positive experiences and engagement with ChatGPT. This confirms the existence of the privacy paradox.

This study acknowledges several limitations. While the sample was adequately stratified, the focus was primarily on young users in China. Future research should explore broader demographic groups, including elderly users, to understand how different age groups engage with AI chatbots. Additionally, although the study was conducted within the Chinese context, the findings have broader applicability, highlighting the potential for cross-cultural comparisons. Differences in user attitudes toward AI chatbots may arise due to cultural variations, with East Asian cultures typically exhibiting a more positive attitude toward social AI systems compared to Western cultures. This cultural distinction—rooted in Eastern philosophies such as animism in Shintoism and Buddhism—suggests that East Asians are more likely to anthropomorphize technology, unlike their Western counterparts (Yam et al., 2023; Folk et al., 2023).

The findings of this study offer valuable insights for developers, policymakers and educators navigating the rapidly evolving landscape of intelligent technologies. First, regarding technology design, the study suggests that AI chatbot developers should not focus solely on functional aspects but also consider emotional and social dimensions in user interactions. By enhancing emotional connection and ensuring transparent privacy communication, developers can significantly improve user experiences (Meng and Dai, 2021). Second, there is a pressing need for comprehensive user education programs. As users tend to prioritize perceived benefits over risks, it is essential to raise awareness about privacy risks while also emphasizing the positive outcomes of responsible information sharing. This can help foster a more informed and balanced approach to user engagement (Vimalkumar et al., 2021). Third, cultural and ethical considerations must be incorporated into AI chatbot design. In collectivist societies like China, users may prioritize emotional satisfaction and societal harmony over privacy concerns (Trepte, 2017; Johnston, 2009). Developers and policymakers should account for these cultural factors when designing AI systems. Furthermore, AI systems should communicate privacy policies clearly to users, addressing potential vulnerabilities and ensuring that users are aware of the extent to which their data may be exposed (Wu et al., 2024). Lastly, as AI chatbots become deeply integrated into daily life, there is a growing need for societal discussions on privacy norms and trust in AI systems. This research prompts a reflection on the evolving relationship between technology and personal privacy, especially in societies where trust is shaped by cultural and emotional factors. Developing frameworks to ensure responsible AI practices while fostering user trust is crucial for the long-term societal integration of AI technologies (Nah et al., 2023).

The study’s findings not only draw deeper theoretical insights into the role of emotions in generative artificial intelligence (gAI) chatbot engagement, enriching the emotional research orientation and framework concerning chatbots, but they also contribute to the literature on human–computer interaction and technology acceptance within the framework of the privacy calculus theory, providing practical insights for developers, policymakers and educators navigating the evolving landscape of intelligent technologies.