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This study aims to deepen our understanding of how chatbots’ empathy influences humans–AI relationship in frontline service encounters. The authors investigate the underlying mechanisms, including perceived anthropomorphism, perceived intelligence and psychological empowerment, while also considering variations between different stages of the customer journey (before and after purchase).

Data collection was conducted through an online survey distributed among 301 customers who had experience using AI-based service chatbot in frontline service encounters in China. The hypotheses were examined through structural equation modeling and multi-group analysis.

The findings of this study revealed the positive impacts of emotional and cognitive empathy on humans–AI relationship through perceived anthropomorphism, perceived intelligence and psychological empowerment. Furthermore, this study verified the moderating effect of the customer journey stages, such that the impacts of anthropomorphism and intelligence on humans–AI relationship displayed more strength during the pre- and post-purchase phases, respectively.

This research offers practical implications for companies: recognize and enhance empathy dimensions in AI-based service chatbot to empower human–AI relationships; boost customer empowerment in human–AI interactions; and tailor anthropomorphic features in the pre-purchase stage and improve problem-solving capability in the post-purchase stage to enrich user experiences.

This study extends relationship marketing theory and human–AI interaction frameworks by investigating the underlying mechanisms of the effect of two-dimensional empathy on human–AI relationship. This study also enriches service design theories by revealing the moderating effect of customer journey stages.

The main purpose of this study is to investigate the impact of state capital participation (SCP) on the corporate environmental engagement (CEE) of privately controlled listed firms in China.

We use a sample of 20,133 firm-year observations from 2009 to 2021. We use three different measures to proxy corporate environmental engagement and two different measures to proxy for state capital participation. We employ a difference-in-difference regression model to estimate the effect of state capital participation on corporate environmental engagement.

Using a sample of 20,133 firm-year observations from 2009 to 2021, we find that SCP significantly increases corporate expenditure on environmental protection, corporate environmental performance and ESG ratings. Specifically, SCP increases environmental investment capacity and attracts more media coverage, online attention and analysts’ following, which leads to better environmental engagement. Further analyses show that after state shareholders exit privately controlled firms, CEE deteriorates, while private capital injection in state-owned firms has no significant impact on CEE. The positive effect of SCP is stronger in privately controlled firms with local government ownership, a larger number of state shareholders, longer state shareholder holding periods, those without politically connected managers and firms operating in heavy pollution industries. Lastly, we show that minority government ownership reduces firm-level toxic emissions and enhances financial performance.

We enrich the literature on the role of minority state ownership in corporate financial and environmental performance.

We enrich the literature on the role of minority state ownership in corporate financial and environmental performance. In light of the escalating environmental concerns and the growing emphasis on corporate environmental responsibility, this study highlights the beneficial role of minority government ownership in driving environmental performance. By providing resources and attracting external scrutiny, the government, as a minority shareholder, can significantly enhance the environmental engagement of privately controlled firms.

To investigate the influence of vehicle operation speed, curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.

Taking a small-radius curve of a high-speed railway as the research object, field measurements were conducted to obtain track parameters and wheel–rail profiles. A coupled vehicle-track dynamics model was established. Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.

Key service parameters affecting wheel–rail creepage were identified, including the matching relationship between curve geometry and vehicle speed and rail profile parameters. The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis, leading to the establishment of parameter optimization criteria.

This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves. A response surface-based parameter-creepage relationship model was established, and a multi-parameter coordinated optimization strategy was proposed. The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.

A transmission tower usually experiences bolt loosening under long-term alternating cyclic load, which may lead to collapse of the tower in extreme operating conditions. The paper aims to propose a data-driven identification method for bolt looseness of complicated tower structures based on reduced-order models and numerical simulations to perceive and evaluate the health state of a tower in operation.

The equivalent stiffnesses of three types of bolt joints under various loosening scenarios are numerically determined by three-dimensional finite element (FE) simulations. The order of the FE model of a tower structure with bolt loosening is reduced by means of the component modal synthesis method, and the dynamic responses of the reducer-order model under calibration loads are simulated and used to create the dataset. An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed.

An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed and the applicability of the model is investigated. It is shown that the proposed method has a high identification accuracy and strong robustness to data noise and data missing. Meanwhile, the method is less dependent on the number and location of sensors and is easier to apply in real transmission lines.

This paper proposes a data-driven identification method for bolt looseness of a complicated tower structure based on reduced-order models and numerical simulations. Non-linear relationships between equivalent stiffness of bolted joints and bolt preload depicting looseness are obtained and reduced-order model of tower structure with bolt looseness is established. Finally, this paper investigates applicability of identification model for bolt looseness.

This paper aims to compare the differences between single- and multi-person interactions in virtual tourism, underpinned by the stimulus-organism-response (S-O-R) framework and media richness theory (MRT).

In this study, quantitative data gathered from questionnaires applied to 558 individuals was analyzed by using partial least squares structural equation modeling. The moderating role of interaction type was tested through multigroup analysis (MGA).

The results showed that vividness positively influenced telepresence, perceived attractiveness and authentic experiences; telepresence positively affected authentic experiences and perceived attractiveness; and authentic experiences and perceived attractiveness positively impacted willingness to visit in both interaction groups. A difference was detected between the two groups in that perceptions of media vividness were more easily transformed into a willingness to visit through telepresence in the multi-person interaction group. Interaction type moderated the effect of vividness on telepresence. The vividness of the media had a more significant effect on telepresence among those who participated in virtual tourism together.

In this study, a model was developed to explain how media vividness affected willingness to visit by considering the relationships between telepresence, authentic experiences and perceived attractiveness in virtual reality, as well as the social interaction aspect.

本研究旨在比较虚拟旅游中单人和多人互动的差异, 基于刺激-有机体-反应（S-O-R）框架和媒介丰富度理论（MRT）。

本研究对 558 名受试者的问卷调查数据进行了定量分析, 采用 PLS-SEM 模型分析, 并通过多群组分分析（MGA）测试了互动类型的调节作用。

研究结果显示, 生动性对临场感、感知吸引力和真实体验有正向影响; 临场感对真实体验和感知吸引力有正向影响; 真实体验和感知吸引力对参观意愿有正向影响。两组之间的差异在于, 在多人互动组中, 媒介生动性更容易通过临场感转化为参观意愿。互动类型调节了生动性对临场感的影响, 参与虚拟旅游的多人群体中, 媒介的生动性对临场感的影响更为显著。

本研究构建了一个模型, 解释了在虚拟现实中, 媒介生动性如何通过临场感、真实体验和感知吸引力的关系影响参观意愿, 同时考虑了社会互动的因素。

The main purpose of this study is to examine the effect of corporate digital transformation on bond credit spreads. Additionally, it also explores the two potential channels, information asymmetry and default risk, through which digital transformation can influence bond credit spreads.

We use the bond issuance data of Chinese listed companies over the period 2008–2020. Corporate digital transformation of these companies is measured with textual analysis of the management discussion and analysis part of annual reports. We employ a panel regression model to estimate the effect of digital transformation on bond credit spreads.

We find robust evidence that companies with higher digital transformation experience lower bond credit spreads. We further observe that credit spread reduction is higher for firms that are smaller, non-state-owned, have lower credit ratings and have less analyst coverage. We also find evidence that digital transformation reduces credit spreads by reducing the information asymmetry between firms and investors with enhanced information transformation mechanisms and lowering corporate default risk by strengthening operating efficiency.

To the best of our knowledge, this study is the first attempt to understand the impact of corporate digital transformation on bond credit spreads. Our findings help to understand the effect of digital transformation on firms’ credit worthiness and access to capital.

This study aims to provide a timely review of hospitality and tourism live streaming (HTLS) research, aiming to understand the intellectual foundation in the past and identify opportunities for future research.

This study collected 56 papers from journals in the Social Science Citation Index database or the Australian Business Deans Council journal quality list and adopted a hybrid systematic literature review combining bibliometric analysis and the theory-context-characteristics-method framework-based approach. Additionally, a cross-tabulation analysis was conducted to compare the research on two specific forms of HTLS – tourism e-commerce live streaming (TEcLS) and travel live streaming.

The study found that the current research lacks in-depth theoretical insights, focuses on China as the national context and viewers as the research subject, mainly uses online surveys and lacks first-order knowledge. Moreover, it identified five research themes, including the impact of HTLS on viewer behavior, purchase behavior in HTLS and introduction of HTLS, within which eight categories of research constructs, such as viewer-related, streamer-related and relationship-related, are applied.

In terms of research, the study reveals various gaps in the existing literature and provides potential research directions to advance the field. As for practice, it offers valuable strategies for practitioners to optimize their marketing efforts using HTLS.

This study provides an up-to-date review of the HTLS field through a systematic and reproducible method. It offers critical discussions and suggestions for academic research and industry practices.

The mounting health misinformation on social media triggers heated discussions about how to address it. Anchored by the influence of presumed influence (IPI) model, this study investigates the underlying process of intentions to combat health misinformation. Specifically, we analyzed how presumed exposure of others and presumed influence on others affect intentions to practice pre-emptive and reactive misinformation countering strategies.

Covariance-based structural equation modeling based on survey data from 690 Chinese participants was performed using the “lavaan” package in R to examine the proposed mechanism.

Personal attention to health information on social media is positively associated with presumed others’ attention to the same information, which, in turn, is related to an increased perception of health misinformation’s influence on others. The presumed influence is further positively tied to two pre-emptive countermeasures (i.e. support for media literacy interventions and institutional verification intention) and one reactive countermeasure (i.e. misinformation correction intention). However, the relationship between presumed influence and support for governmental restrictions, as another reactive countering method, is not significant.

This study supplements the misinformation countering literature by examining IPI’s tenability in explaining why individuals engage in combating misinformation. Both pre-emptive and reactive strategies were considered, enabling a panoramic view of the motivators of misinformation countering compared to previous studies. Our findings also inform the necessity of adopting a context-specific perspective and crafting other-oriented messages to motivate users’ initiative in implementing corrective actions.

The growing prevalence of digitalisation in economies has brought attention to the significance of digital transformation and its potential to enhance the competitiveness of enterprises within the emerging market. Nevertheless, it is important to note that disruptive changes are not limited to the organisational level, as they also have broader implications for the environment, society and institutions. The incorporation of technology into the field of education, often known as educational technology (EdTech), has undergone a significant evolution in recent times, fundamentally transforming the methods and processes of teaching and learning. This chapter delves into the multifaceted landscape of digital transformation in the field of EdTech from the perspective of sustainable development, elucidating the wide range of opportunities and challenges that consumer, educators, institutions and technology providers and various stakeholders face when they embark on this journey. Further, this chapter also sheds light on how to overcome the challenges faced by the stakeholders in digital transformation of EdTech for quality education.

Online games are highly popular Internet applications. Some games enable players to save game progress and accumulate experiences or changes to avatars during gameplay, whereas some other games do not, requiring players to restart from the beginning each time. That is, games differ in avatar accumulability. However, we do not know whether games should be designed to permit avatar accumulability or not and how it affects players’ gameplay experience and therefore game outcomes, indicating gaps. Research addressing these gaps can inform game makers in designing games that effectively strengthen their players’ game loyalty.

We used social identity theory (SIT) to construct a theoretical model. To test this model, three waves of survey data were gathered from the same 778 participants.

These findings uniquely indicate that avatar accumulability fosters avatar identification and increases players’ focused immersion, thus increasing players’ loyalty.

Game providers could include game features that enable players to accumulate their avatars’ in-game skins, levels, items (weapons and equipment) and experience points. This accumulability can help strengthen players’ game loyalty.

Overall, our study extends SIT by adding a new trigger (avatar accumulability) and two novel consequences of avatar identification (image protection and focused immersion) in avatar-related systems (games or gamified systems). The new trigger offers an actionable means to apply SIT, while the novel consequences verify the value of applying SIT to study online games.