Pengkun Wu

Conditional autonomous driving still requires drivers to execute accurate and timely responses within the operational constraints of the technology. However, in risk scenarios, driver responses to system alarms are not always effective. Drawing on Arousal Theory, this study examines the impact of risk perception on driver response behaviors and explores the underlying mechanisms. Through an online behavioral experiment, structural equation modeling was employed to analyze the causal relationships among risk perception, arousal level, weather conditions (sunny vs. rainy), user trust, and driver response behaviors. The results show a positive association between risk perception and driver response, with arousal level serving as a mediating factor. Rainy conditions attenuate the positive behavioral responses typically linked to heightened risk perception, whereas user trust amplifies the effect of risk perception on driver response. This study is among the first to integrate arousal mechanisms with contextual moderators in assisted driving contexts. It uniquely demonstrates how environmental stressors (e.g., weather conditions) and human factors (e.g., user trust) differentially moderate the pathway from risk perception to driver response behaviors.

This paper investigates the incentive mechanism for dual-channel healthcare service supply chains, where doctors simultaneously undertake both offline and online medical tasks, based on the common agency theory. Considering the geographical distance between online patients and public hospitals, we construct common agency, game-theoretic models under two scenarios: without spillover effects and with spillover effects. Through analytical solutions, we derive the equilibrium outcomes for both scenarios and conduct comparative and numerical analyses. The findings reveal that as follows: (1) Compared to the scenario without spillover effects, the incentive intensity for offline healthcare increases when spillover effects are considered, and doctors exert higher effort levels in offline healthcare. (2) The incentive intensity for online healthcare may decrease, yet doctors’ effort levels in the online channel do not decline accordingly and may even increase; (3) Non-economic incentives (e.g., online reputation) exhibit a substitution effect on economic incentives; (4) Online reputation not only influences decision-making in the online healthcare channel but also affects decisions in the offline channel through spillover effects. These findings provide valuable insights for public hospitals and online healthcare platforms to optimize incentive structures and for doctors to allocate efforts effectively across dual-channel healthcare services.

Purpose: This study investigates the impact of social media posts on panic buying behavior while also examining the moderating role of the posts’ attention level and exploring the mediating effects of perceived credibility, perceived risk and perceived scarcity. Design/methodology/approach: Building upon the elaboration likelihood model and scarcity theory, this study examines the impacts of numerical presentation and posting account type on panic buying behavior and explores their underlying mechanisms. To test our hypotheses, we conducted two online randomized experiments and employed t-tests and regression analysis as the main analytical methods. Findings: Our findings highlighted the significance of incorporating precise numerical information and utilizing institutional accounts to enhance users’ perceptions of scarcity and credibility, thereby inducing panic buying behavior. Moreover, posts from institutional accounts were also found to amplify users’ perceived risks. Additionally, we discovered that the impacts of both numerical presentation and posting account type were negatively moderated by the posts’ attention level. Originality/value: While previous research has acknowledged the impact of social media posts on panic buying behavior, it has overlooked the identification of specific attributes within these posts that may exert influence as well as neglected to consider the mediating role of user attitudes. This study contributes to the existing literature by elucidating the underlying mechanisms through which three distinct characteristics of social media posts impact panic buying behavior, thereby providing practical insights for effectively managing social media content and mitigating panic buying.

Purpose: This study aims to investigate the impact of physician efforts in online reviews on outpatient appointments, while also examining the moderating effect of physician title. Design/methodology/approach: This study employs the heuristic-systematic model (HSM) to analyze the impact of physician efforts on outpatient appointments. Subsequently, a fixed effect model is employed to examine the research model using an 89-week panel dataset (from April 16, 2018 to December 29, 2019) comprising appointment and online review information pertaining to 8,157 physicians from a prominent online health community in China. Findings: The findings suggest that physicians with lower professional titles exhibit a significantly higher inclination to enhance heuristic information (e.g. attracting helpful votes) compared to those with higher professional title. All physicians can enhance their outpatient appointments by dedicating efforts towards improving systematic review information, but physician title would weaken the relationship. Moreover, the effect of increasing review volume is considerably more substantial than that of increasing review length, which also surpasses the influence of providing managerial response. Originality/value: Unlike previous studies that primarily focus on patients’ perspectives, this paper represents one of the pioneering effects to examine physicians’ engagement in online reviews.

Purpose: This study aims to investigate the impact of news quality on users’ risk perceptions toward online news and its subsequent influence on perceived believability and user engagement in sharing news. Additionally, we explore the moderating effects of fake news awareness and social tie variety.Design/methodology/approach: Drawing upon the social amplification of risk framework, this study investigates the relationship between news quality and users’ news-sharing behaviors, along with its underlying mechanism. An online questionnaire involving 399 eligible participants was employed for hypotheses testing, and the structural equation model served as the main analytical method.Findings: The influence of news quality on users’ news-sharing behavior is sequentially mediated by risk perception and perceived believability. Individuals with a heightened awareness of fake news or a diverse social tie are more inclined to perceive greater risks associated with news-sharing behavior and question news authenticity.Originality/value: This study contributes to the existing literature on users’ news-sharing behaviors by examining the influence of risk perception on the relationship between news quality, perceived believability and users’ news-sharing behavior. Additionally, it explores the moderating effects of fake news awareness and social tie variety. Our findings offer valuable insights into comprehending user inclinations towards news sharing and mitigating the dissemination of fake news.