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Drawing on the Service Robot Acceptance Model (sRAM) proposed by Wirtz et al. (2018), this study aims to examine how functional and social-emotional antecedents affect relational elements and the critical functions that trust and rapport play in robot acceptance in hotel services. Additionally, this study incorporates customer characteristics into the modified sRAM.

Consistent partial least squares (PLSc) was used to test the proposed model utilizing data collected from 456 Chinese customers.

The results indicated that effort expectancy and performance expectancy positively affect hotel guests’ trust toward and rapport with service robots. However, the effect of social influence on trust and rapport is insignificant. Additionally, perceived humanness and perceived social interactivity positively influence rapport, and perceived social presence positively affects both trust and rapport. Furthermore, trust and rapport positively influence hotel guests’ acceptance of service robots. The results also revealed the moderating role of age.

This study contributes to service robot literature by providing insights into how functional and social-emotional factors affect relational factors and the key role of relational factors in robot acceptance based on the sRAM. This study also advances this body of knowledge by highlighting the moderating effect of age.

基于Wirtz等人（2018）提出的服务机器人接受模型（sRAM）, 本研究旨在探讨功能性和社会-情感性前因如何影响关系元素, 以及信任和融洽在酒店服务中对机器人接受度的关键作用。此外, 本研究将顾客特征纳入修改后的 sRAM 中。

采用一致性偏最小二乘法（PLSc）对来自456名中国顾客的数据进行分析，以验证所提出的模型。

结果表明, 努力期望和绩效期望积极影响酒店客人对服务机器人的信任和融洽。然而, 社会影响对信任和融洽的影响不显著。此外, 感知人性化和感知社会互动积极影响融洽, 感知社会临场感积极影响信任和融洽。此外, 信任和融洽积极影响酒店客人对服务机器人的接受度。结果还揭示了年龄的调节作用。

本研究通过提供关于功能性和社会-情感性因素如何影响关系因素以及关系因素在机器人接受度中的关键作用的见解, 为服务机器人文献做出了贡献。本研究还通过强调年龄的调节效应, 推进了这一知识体系的发展。

This study investigates the direct impact of app attachment on service recovery and customer advocacy and their combined impact on recommendation and purchase intention. The mediating mechanisms of service recovery and customer advocacy between app attachment and customer responses are also tested in the context of food delivery apps (FDAs).

Utilizing a quantitative approach, the authors surveyed 207 responses from users of FDAs who had experienced service failures. Structural equation modeling in Smart PLS 3.0 was used to analyze the data.

The results supported direct effects among all constructs in the model. The main contribution of the study confirms the mediating mechanisms of service recovery and customer advocacy between app attachment and customer responses.

Previous studies have mostly relied on the technology acceptance model (TAM). This theory posits that perceived usefulness and ease of use influence the decision of individuals to use a new technology. Although this theory is valuable in terms of accepting new technologies, it neglects psychological phenomena involving the individual and the technological entity – in this case, the FDA. Thus, our study is unique in applying attachment theory and putting emphasis on the importance of building trust in the relationship between FDAs and their customers. Social exchange theory is applied to explain the importance of overcoming the cost of experiencing a failure through service recovery. Thus, we extend the knowledge regarding psychological individual reactions to mobile technologies in the food context, an important sector within the hospitality market.

FDA managers should invest in developing emotional ties with customers. Specific actions include messaging customers on their birthdays or other festive dates. Short testimonial videos on TikTok or other social media with customers advocating in favor of the company could help spread recommendations and the intentions of other customers using the FDAs. To use these practical recommendations properly, we recommend that FDA managers consider the level of quality service recovery delivered and individuals’ cultures, beliefs and values regarding where the company operates to avoid misunderstandings.

This study is original in proposing a model to FDA operators considering app attachment, service recovery, customer advocacy, recommendation and purchase intention. It further supports the mediating effect of service recovery and customer advocacy between app attachment, recommendation and purchase intention on mobile phones.

This study aims to investigate the impact of Internet use on household financial market participation and portfolio choice.

Based on the Chinese General Social Survey 2017 (CGSS2017), this study empirically explores whether Internet use affects household financial market participation in China with an Endogenous Switching Probit model.

The results show that households using the Internet are more likely to invest in financial markets. Further research shows that households with high Internet use are significantly more likely to participate in financial markets than households with low Internet use. From the perspective of household portfolio choice, Internet use has a certain role in increasing the probability of portfolio diversification. However, among households that have invested in financial markets, those with a high-frequency use of the Internet do not show an impact on portfolio diversification.

This study complements existing research about the impact of Internet use or not on household financial market decisions and portfolio choice, expands the knowledge on the household financial market choice from the respective of the degree of Internet use.

As social networks have developed to be a ubiquitous platform of public opinion spreading, it becomes more and more crucial for maintaining social security and stability by accurately predicting various trends of public opinion dissemination in social networks. Considering the fact that the dissemination of online public opinion is a dynamic process full of uncertainty and complexity, this study establishes a novel conformable fractional discrete grey model with linear time-varying parameters, namely the CFTDGM(1,1) model, for more accurate prediction of online public opinion trends.

First, the conformable fractional accumulation and difference operators are employed to build the CFTDGM(1,1) model for enhancing the traditional integer-order discrete grey model with linear time-varying parameters. Then, to improve forecasting accuracy, a base value correction term is introduced to optimize the iterative base value of the CFTDGM(1,1) model. Next, the differential evolution algorithm is selected to determine the optimal order of the proposed model through a comparison with the whale optimization algorithm and the particle swarm optimization algorithm. The least squares method is utilized to estimate the parameter values of the CFTDGM(1,1) model. In addition, the effectiveness of the CFTDGM(1,1) model is tested through a public opinion event about “IG team winning the championship”. Finally, we conduct empirical analysis on two hot online public opinion events regarding “Chengdu toddler mauled by Rottweiler” and “Mayday band suspected of lip-syncing,” to further assess the prediction ability and applicability of the CFTDGM(1,1) model by comparison with seven other existing grey models.

The test case and empirical analysis on two recent hot events reveal that the CFTDGM(1,1) model outperforms most of the existing grey models in terms of prediction performance. Therefore, the CFTDGM(1,1) model is chosen to forecast the development trends of these two hot events. The prediction results indicate that public attention to both events will decline slowly over the next three days.

A conformable fractional discrete grey model is proposed with the help of conformable fractional operators and a base value correction term to improve the traditional discrete grey model. The test case and empirical analysis on two recent hot events indicate that this novel model has higher accuracy and feasibility in online public opinion trend prediction.

This study aims to answer two questions: (a) what obstacles and opportunities do Chinese female entrepreneurs face when doing business? And (b) how do they negotiate their entrepreneurial careers and gender identities in different gender-segregated markets?

This study uses qualitative research methods of participant observation and in-depth interviews with 41 female entrepreneurs in China and the theoretical lenses of gender role theory and doing gender in entrepreneurship.

The study findings reveal that Chinese female entrepreneurs face different obstacles and opportunities in gender-segregated industries. Their experiences vary in industries that are mainly occupied by males and females. On the one hand, women in female-dominated industries may be supported by a feminine working environment that is coherent with their domestic roles. However, they may also be questioned on the cultural impurity implied in some industries, which harms their class-based feminine virtue. On the other hand, women in male-dominated industries may be challenged and marginalized due to their gender. However, some find ways to turn the disadvantaged feminine characters into favourable conditions and break out of the stereotypical gender constraints in doing business.

This study contributes to the literature on gender and entrepreneurship in general. More specifically, it contributes to the study of doing gender in gender-segregated markets, and it also illustrates women’s gendered opportunities and constraints in Chinese society that are affected by the long-lasting traditional gender norms.

The pandemic has caused severe disruptions and significant losses in various industries. In particular, the nursing service industry has been greatly affected, leading to increased service costs and attrition of nursing service provider (NSP) residents. Although prior studies suggest that outsourcing may mitigate losses from disruptions, there still lacks a detailed analysis of whether and when to adopt such a disruption solution.

This study develops a two-period game-theoretical model to explore the impacts of demand and cost disruptions caused by the pandemic on NSPs’ operational strategies, suppliers’ strategy choices and equilibrium prices and demand.

The results present several novel managerial insights. First, we suggest that higher demand and cost disruptions decrease service demand, but do not necessarily prompt an NSP to outsource nursing services. Interestingly, we find that even when the service cost of the outsourcing strategy is low, the NSP may still insist on the in-house strategy. Additionally, the equilibrium strategy does not always result in lower prices and higher demand.

Our findings provide insightful takeaways for NSPs to cope with the pandemic in the nursing service industry. The results also offer theoretical support for other industries to recover from demand and cost disruptions.

Existing hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.

This study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.

The capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.

The initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

The purpose of this study is to investigate the continuous intention to use blockchain and FinTech innovations, focusing on the direct impact of user trust and perceived risks. It seeks to test how information technology (IT) quality directly affects user-perceived risk and trust and to identify how IT quality can influence FinTech continuance intentions. By examining these relationships, the study provides insights into how improvements in IT quality can mitigate perceived risks and enhance user trust, ultimately fostering sustained use of FinTech and blockchain technologies.

To achieve the purpose of this study, the model and hypotheses were examined based on the partial least squares structural equation modeling (PLS-SEM).

Results revealed that perceived risk is negatively impacted by system quality, while trust is positively impacted by information quality, and the most significant result in the study is continuous-use intention and uncertainty both are impacted by service quality. Also, the study used some control variables, and two of them (i.e. FinTech type and education) showed a positive significant relationship with continuance-use intention.

This study identifies several causal relationships between the continuance-use intention of blockchain and FinTech innovations and various factors, which can provide valuable insights for managers, enabling them to formulate appropriate strategies to foster sustainable growth in FinTech and blockchain. By leveraging these findings, managers can enhance IT quality, reduce perceived risks and build user trust, thereby promoting the ongoing adoption and success of blockchain and FinTech innovations.

The outcomes obtained will help both FinTech providers and researchers elucidate and understand the situation of users’ concerns about the unexpected risks/uncertainty in FinTech transactions can be mitigated through providing a high level of quality IT service and systems. Two main strategies can be merged to be used by FinTech providers/managers, first: trust building, second: risk-mitigating, both strategies can be used in the light of IT innovation and its aspects to meet the sustainable growth of FinTech.

This paper aims to understand how quantum leaders influence employee work behavior through effective tasks.

In this study, 516 questionnaires were collected using the interval data method to explore the triggering mechanisms and paths of emerging quantum leadership on constructive deviance.

The findings indicate that quantum leadership promotes constructive deviance through facilitating recovery experience (affective path), job crafting (task path) and the chained mediation path between the two. Additionally, the moderating effect of openness to experience strengthens the pathways between quantum leadership and recovery experience, and between quantum leadership and job crafting.

This study focuses closely on the mechanism of leadership behavior on employees, neglecting the psychological state and behavior of the leader as a key resource element in the work environment. Quantum leadership emphasizes value-bound characteristics, so the role played by quantum leaders may vary in different cultures and values.

First, this study calls for the organizational management focusing on the advantages of quantum leadership thinking and its positive effects in practice. Second, the mediating mechanisms of recovery experience and job crafting provide insights into how quantum leadership can be used to enhance constructive deviance. Third, this study elucidates how individual responses to organizational environment and leadership style vary in management practices. Our study helps managers better understand how individual characteristics, such as openness to experience, influence managerial behavior.

This study enriches the qualitative research on emerging “quantum” perspectives of leadership, expands the mechanism of employee constructive deviance and highlights the need for organizations to take measures that encourage constructive deviance by their employees, as this can lead to high-quality and long-term growth.

Based on conservation of resources theory, authors revealed the mechanisms by which quantum leadership influences employees’ constructive deviance, confirming the mediating role of recovery experience and job crafting as well as the moderating role of openness to employee experience. We explored the moderating mechanisms of the individual trait of openness to experience in the quantum leadership-to-job crafting and the recovery experience-to-job crafting.

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.

The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.

The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.

The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.