Search results

Online medical teams (MTs), involving collaboration between remote healthcare workers, can provide comprehensive and rapid healthcare to patients. The growth in MTs is continuing, with popularity growing among doctors and patients, but some MTs disband, which could break the continuity of healthcare services provided. We aim to address this pressing issue by exploring the effects of team diversity and leadership types on team status (i.e. team disbandment (TD)). This paper systematically investigates the influences of team diversity, including separation, variety and disparity diversity and the effects of leadership types, including strong, equal and weak types.

A data set consisting 1,071 online MTs was collected from the Good Doctor website, a leading Chinese online health community (OHC), on January 10, 2018. The data captured included 206 teams which disbanded after 3 months collaboration. Logistic regression and maximum likelihood estimation (MLE) were used to examine their effects.

The results show that variety diversity, related to departments, positively affects TD, but disparity diversity, referring to clinician titles, negatively affects TD. Separation diversity, in terms of team member attitudes, exerts a negligible influence on disbandment. Although strong and equal leadership types negatively influence TD, they are seen to strengthen the positive effect of variety diversity, suggesting stable structure combinations of strong or equal-type leadership and low department diversity, as well as the match of weak-type leadership and high department diversity.

This paper extends the current understanding of virtual teams and OHCs by examining the role of leadership types and team diversity, and their influencing role on team status. The pairwise combinations are obtained to effectively reduce the disbandment probability of medical teams operating in OHCs, which could help platform managers, team founders and those connected with MTs deal with the team-disbandment crisis, providing both theoretical and practical implications to healthcare providers and researchers alike.

As more firms adopted AI-related services in recent years, AI service failures have increased. However, the potential costs of AI implementation are not well understood, especially the effect of AI service failure events. This study examines the influences of AI service failure events, including their industry, size, timing, and type, on firm value.

This study will conduct an event study of 120 AI service failure events in listed companies to evaluate the costs of such events.

First, AI service failure events have a negative impact on the firm value. Second, small firms experience more share price declines due to AI service failure events than large firms. Third, AI service failure events in more recent years have a more intensively negative impact than those in more distant years. Finally, we identify different types of AI service failure and find that there are order effects on firm value across the service failure event types: accuracy > safety > privacy > fairness.

First, this study is the initial effort to empirically examine market reactions to AI service failure events using the event study method. Second, this study comprehensively considers the effect of contextual influencing factors, including industry type, firm size and event year. Third, this study improves the understanding of AI service failure by proposing a novel classification and disclosing the detailed impacts of different event types, which provides valuable guidance for managers and developers.

In China, healthcare services have historically been expensive and difficult to access, with resources being unfairly distributed, often being centralized in large hospitals in major cities. In rural regions, hospitals often suffer from limited supplies, including human capital and equipment. E-health technologies have received significant attention from governments and citizens, with online healthcare communities (OHCs) providing easier communication between patients and doctors. Although doctors play a pivotal role in the success of OHCs, they are often unsure how to attract patients, with limited research focusing on this. The purpose of this paper is to explore how doctors can take initiatives in OHCs, from the joint perspectives of individual effort (i.e. intrapersonal factor) and identity in medical teams (MTs) (i.e. interpersonal factor), based on attribution theory.

Hierarchical linear regression was conducted on data from 3,170 doctors participating in 865 online MTs, to examine the effects of individual effort and identity in MTs on individual performance. Individual effort included central effort (log-in frequency to OHC) and peripheral effort (articles published on doctors' homepages). Identity in MTs was represented as the identity of team leader and multiple team membership (MTM).

This study found that the main variables – central and peripheral effort, and leader and MTM identity – all had significant and positive impacts on the service quantity (SQ) of both written and telephone consultations. Although positive effects could be experienced in most conditions that were congruent with the logic of identity theory, the interaction terms demonstrated complex influences. Specifically, leader identity did not moderate the effect of article effort in written consultation, while MTM identity could not moderate the relationship between frequency effort and SQ in telephone-consultation services. Further, the leader identity negatively moderated the relationship between article effort and SQ in telephone consultations. Thus, for doctors with the leader identity, the impact of article effort on SQ was weaker. In summary, both aspects were proved to play important roles in individual SQ.

This study provides empirical findings through focusing on the SQ of both written and telephone consultations in OHCs, thereby enabling healthcare providers to take initiatives and ultimately improve the efficiency and provision of delivered healthcare services. It is worth mentioning that doctors possessing the identity of team leader should be cautious that the more articles published by them may not lead to envisaged telephone-consultation performance, according to the negative moderating effect of leader identity on the relationship between article effort and SQ during telephone consultations.

This study contributes to the OHC literature by investigating how doctors' efforts and identity in OHCs affect individual performance, based on attribution theory and identity theory. Further, we provide healthcare practitioners with an improved understanding of these dimensions to improve autonomy regarding service provision in OHCs.

This study analyzes the evolution of topics related to COVID-19 on Chinese social media platforms with the aim of identifying changes in netizens' concerns during the different stages of the pandemic.

In total, 793,947 posts were collected from Zhihu, a Chinese Question and Answer website, and Dingxiangyuan, a Chinese online healthcare community, from 31 December, 2019, to 4 August, 2021. Topics were extracted during the prodromal and outbreak stages, and in the abatement–resurgence cycle.

Netizens' concerns varied in different stages. During the prodromal and outbreak stages, netizens showed greater concern about COVID-19 news, the impact of COVID-19 and the prevention and control of COVID-19. During the first round of the abatement and resurgence stage, netizens remained concerned about COVID-19 news and the prevention and control of the pandemic, however, less attention was paid to the impact of COVID-19. During later stages, popularity grew in topics concerning the impact of COVID-19, while netizens engaged more in discussions about international events and the raising of spirits to fight the global pandemic.

This study contributes to the practice by providing a way for the government and policy makers to retrospect the pandemic and thereby make a good preparation to take proper measures to communicate with citizens and address their demands in similar situations in the future.

This study contributes to the literature by applying an adapted version of Fink's (1986) crisis life cycle to create a five-stage evolution model to understand the repeated resurgence of COVID-19 in Mainland China.

This article aims to explore the factors influencing patients' distrust toward doctors in online health community.

This study leveraged the distrust construct model and socio-technical systems theory to establish a research model. The authors used the survey method to validate the research model by developing and distributing questionnaires to online health community users. 518 valid responses were collected.

The data analysis results showed that patients' distrusting beliefs were significantly related to their distrust toward doctors in online health communities. Meanwhile, social factors included perceived egoism and lack of expertise; whereas technical factors included no structural assurance, and lack of third-party recognition.

This study not only provides a solid and comprehensive theoretical understanding of patient distrust toward doctors in online health communities but also could serve as the basis to relieve the distrust between patients and doctors in online health communities, or even in the offline environment.

The purpose of this research is to investigate how postpartum mothers conduct self-disclosure on social media may obtain social support and therefore improve their depressive mood.

The authors extract variables of self-disclosure by manual coding postpartum mothers' 835 posts from a parenting social media in China. The ordinary least squares model and the binary logistic regression model are used to test the proposed hypotheses.

The study suggests that both mothers' superficial level disclosure and personal level disclosure positively affect online social support received, and the effect of personal level disclosure on social support is much greater than that of superficial level disclosure. Online social support received is related to the content of the post and reduces mothers' depressive mood. The authors further find that the association between personal level disclosure and depressive mood is fully mediated by social support.

The data are collected from a parenting social network. Although it is the major parenting social media with the most users in China, the generalizability of this model and the findings to other social media need additional research.

This study offers implications for researchers and practitioners with regard to social media uses and impacts, which also has important implications for policy and interventions for the mental health of mothers.

This paper makes theoretical contributions to the literature of social penetration theory and social support by (1) dividing self-disclosure into superficial level disclosure and personal level disclosure according to the intimacy of self-disclosure; (2) empirically investigating the direct effect of online self-disclosure on social support and the mediating effect of social support between online self-disclosure and mothers' depressive mood.

Sharing project information is critical for the success of medical crowdfunding campaigns. However, few users share medical crowdfunding projects on their social networks, and the sharing behavior of medical crowdfunding projects on social networking sites has not been well studied. Therefore, this study explored the factors and potential mechanisms influencing users’ sharing behaviors on networking sites.

A research model was developed based on the attribution-affect model of helping and social capital theory. Data were collected using a longitudinal survey. Partial least squares structural equation modeling was used to analyze the collected data. We conducted post hoc analyses to validate the results of the quantitative analysis.

The analysis results verified the effects of perceived external attribution, perceived uncontrollable attributions, and perceived unstable attributions on sympathy and identified the effect of sympathy and social characteristics of medical crowdfunding users on sharing behavior.

This research provides a comprehensive theoretical understanding of users’ sharing behavior characteristics and provides implications for enhancing the efficiency of medical crowdfunding activities.

The purpose of this paper is to investigate trends in the dimensions of low, medium, and high knowledge management (KM) capability of business process outsourcing (BPO) firms. It also explores the trends in BPO performance with different levels of KM capabilities of BPO firms. Moreover, the study determines how firm characteristics, such as size, age, industry, and outsourcing age, affect KM capability.

A survey was employed to collect data on managers from 605 firms. K-means cluster analysis was performed on the aggregate measures of the four KM capability dimensions and BPO performance to reveal trends. Subsequently, MANOVA was used to evaluate the effects of four firm characteristics on KM capability, and individual ANOVA tests were performed to examine the specific differences among the four dimensions.

Among the four dimensions of KM capability, knowledge application is the most significant. Knowledge protection is the second highest in terms of expressing the profile for low KM capability firms, but the lowest among the four dimensions of KM capability for medium and high KM capability firms. Each dimension of KM capability affects BPO performance positively. Firm size, age, industry, and outsourcing age differentially affect the dimensions of KM capability.

This study presents a theoretical model of firm characteristics, KM capability, and BPO performance. Through the model, ideas are offered: firms with high KM capability significantly differ from those with low and medium KM capabilities; different firms exhibit different KM capabilities; developing knowledge application capability should be the priority in managing BPO; and improving KM capability is an effective means to enhance BPO performance.

Although the health information seeking behavior of consumers through the internet has received great attention, limited attempt has been made to integrate both the health information seeking behavior and the usage behavior in a mobile online context. The purpose of this paper is to explore the factors that influence consumer mobile health information seeking (MHIS) and usage behavior based on information quality, perceived value, personal health value, and trust.

A survey was conducted to collect data. A two-step approach of structure equation modeling based was used to test the measurement model and hypothesis model.

Information quality, perceived value, and trust were found to have positive effects on both the intention to seek and to use health information, and that the intention to seek affects the intention to use. Among the three components of perceived value, the utilitarian and epistemic values were found to have significant effects on intention to seek. In addition, the current health status of health consumers moderates the relationships between MHIS and usage intention and their determinants.

Studies have primarily focussed on online health information seeking behavior, whereas a few of these studies have examined the seeking behavior intention and the usage behavior intention in a general model. The results indicate that health information usage behavior intention is closely related to the seeking behavior intention in the mobile context, which enriches the research on the relationship between information seeking and its outcomes. Furthermore, this study highlights the impact of information quality, perceived value, and trust on the intention to seek, and the impacts of information quality and trust on the intention to use, which have been overlooked in previous studies on MHIS.

This paper aims to develop and estimate a logit model of whether homeownership could be promoted by participation in and use of the Housing Provident Fund (HPF) program, with a focus on factors that influence the use of HPF loans.

This paper develops and estimates a logit model of whether homeownership could be promoted by participation in and use of the HPF program, with a focus on factors that influence the use of HPF loans.

The results show that coefficients of marital status, educational level, age, duration of employment and employer are significantly related to the use of HPF loan for homeownership.

Because of the chosen research approach, the research results may lack generalizability.

The research findings provide a better understanding of homeowners’ characteristics.

To manage the HPF program effectively, it is important for government to have a better understanding of the underlying demand for homeownership, especially with respect to the different demographic variables and accessibility to HPF loans and the HPF.