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This systematic literature review aims to provide a comprehensive and structured synthesis of the existing knowledge about chatbots in healthcare from both a theoretical and methodological perspective.

To this end, a systematic literature review was conducted with 89 articles selected through a SPAR-4-SLR systematic procedure. The document for this systematic review was collected from Scopus database. The VoSviewer software facilitates the analysis of keyword co-occurrence to form the fundamental structure of the subject field.

In addition, this study proposes a future research agenda revolving around three main themes such as (1) telemedicine, (2) mental health and (3) medical information.

This study underscores the significance, implications and predictors of chatbot usage in healthcare services. It is concluded that adopting the proposed future direction and further research on chatbots in healthcare will help to refine chatbot systems to better meet the needs of patients.

Notwithstanding their potential benefits especially for individuals with low health literacy, users are still somewhat skeptical about the reliability of healthcare chatbots. The present study aims to address this challenge by investigating strategies to enhance users’ cognitive and emotional trust in healthcare chatbots. Particularly, this study aims to understand the effects of chatbot design cues in increasing trust and future chatbot use intention for low health literacy users.

We conducted two experimental studies with a final sample of 327 (Study 1) and 241 (Study 2). Three different chatbots were developed (Chatbot design: Bot vs Male-doctor vs Female-doctor). Participants were asked to have a medical consultation with the chatbot. Participants self-reported their health literacy scores. The PROCESS model 7 was used to analyze the hypotheses.

The results showed that the female-doctor cues elicited greater cognitive and emotional trust, whereas the male-doctor cues only led to greater cognitive trust (vs bot-like cues). Importantly, this study found that users’ health literacy is a significant moderating factor in shaping cognitive and emotional trust. The results indicated that both the female and male-doctor cues’ positive effects on cognitive trust were significant for those with lower levels of health literacy. Furthermore, the positive effect of the female-doctor cues on emotional trust was also significant only for those whose health literacy level was low. The increased cognitive and emotional trust led to greater future intention to use the chatbot, confirming significant moderated mediation effects.

Despite the strong economic and educational benefits of healthcare chatbots for low health literacy users, studies examining how healthcare chatbot design cues affect low health literate users surprisingly remained scarce. The results of this study suggest that healthcare chatbots can be a promising technological intervention to narrow the health literacy gap when aligned with appropriate design cues.

Social networking services (SNS) empower users with a robust capability to connect with others and manage their social relationships. However, as the size of users’ social networks increases, coupled with the inherent boundary-spanning technical features of SNS, users are faced with unprecedented role stresses. This, in turn, leads to maladaptive lurking decisions. This study delves into the mechanism of this technology-induced decision-making process among SNS users.

Survey data were collected from 491 Chinese WeChat Moment users. The model and hypotheses testing were conducted using SmartPLS 4.0.

Our findings indicate that both social network size and boundary spanning have a positive influence on role conflict and role overload. Both role conflict and role overload significantly contribute to SNS fatigue, which further intensifies users’ lurking intention. Furthermore, SNS fatigue fully mediated the relationship between role conflict and lurking intention, and partially mediated the relationship between role overload and lurking intention.

Our study offers a fresh viewpoint for comprehending lurking behaviors on SNS, furnishing practical insights for platform providers. Additionally, it paves the way for future research into the deeper mechanisms driving SNS lurking behaviors, by providing a novel construct (i.e. boundary spanning) to distinguish and measure the unique social environment of SNS.

Food quality and safety issues have always been imperative topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality. How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

The paper aims to analyze the differences in product quality levels and market participants’ profits before and after the use of blockchain-driven traceability technology in the food agricultural product supply chain (SC) in the dynamic game frameworks of supplier-led and retailer-led modes, respectively, and explores the willingness, social welfare and consumer surplus of each member of the agricultural product SC to participate in the blockchain. Besides, We investigate the SC performance improvement with the mechanism of central centralized decision-making and revenue-sharing contract, compared to the SC performance in dynamic games.

The results are obtained as follow: The adoption of blockchain traceability technology can help improve the quality of food agricultural products, consumer surplus and social welfare, but the application and popularization of technology is hindered by traceability technology installment costs. Compared with the supplier leadership model, retailer-led food quality level, customer surplus and social welfare are higher.

How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

Food quality and safety issues have always been hot topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality.

The research results enrich the theories related to food safety and quality, and provide a valuable reference for food enterprises involved in the decision-making exploration of blockchain technology.

Based on the characteristics of blockchain technology, the demand function is adjusted and the product loss risk of channel members is transferred through a Stackelberg game SC composed of agricultural products suppliers and retailers.

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  We introduce two features of blockchain: quality trust and product information tracking.

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  The willingness of each member of the supply chain to use blockchain for product traceability was explored.

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  The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

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  The cost of blockchain technology is a barrier to its adoption.

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  Blockchain brings higher consumer surplus and social welfare.

We introduce two features of blockchain: quality trust and product information tracking.

The willingness of each member of the supply chain to use blockchain for product traceability was explored.

The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

The cost of blockchain technology is a barrier to its adoption.

Blockchain brings higher consumer surplus and social welfare.

This research applies the stimulus-organism-behavior-consequence framework to explore how blockchain-enabled traceability influences trust in organic food producers and retailers, which impacts consumers’ purchase behaviors and subsequent outcomes.

Using a purposive sample of 5,326 Vietnamese consumers, multiple linear and polynomial regression with response surface analysis were employed to examine the hypotheses.

Blockchain-enabled traceability significantly enhances trust in both producers and retailers, which congruently and incongruently influences organic food purchase behaviors. This behavior also drives consumers’ word-of-mouth and repurchase intentions. Serial mediation analysis confirms blockchain’s impact through trust and purchase behaviors.

Stakeholders should adopt blockchain to boost transparency and trust, which increases consumer engagement. Policymakers can support this transition through regulations and incentives to enhance food security and sustainability.

This study expands on blockchain research by applying the stimulus-organism-behavior-consequence framework in the organic food supply chain, showing how blockchain-enhanced trust synergistically affects consumers’ purchase behaviors, word-of-mouth and repurchase intentions.

This study explores the effects of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention from the perspective of flow experience.

The survey data for this study were collected from the QQ fan group of virtual streamers between November 26th 2022 and December 5th 2022. The authors survey 274 viewers who have experience of watching virtual streaming and employ the partial least squares structural equation model to test the research hypotheses.

Among the characteristics of virtual streamers, interactivity significantly influences users’ perceived enjoyment and concentration, while vividness only affects perceived enjoyment. In addition, the novelty of the virtual scene has a notable impact on users’ perceived enjoyment and concentration, whereas aesthetic appeal serves as an important indicator solely for concentration. Furthermore, the virtual streamer image-scene fit also affects users’ perceived enjoyment and concentration. Finally, perceived enjoyment and concentration equally contribute to users' watching intention.

This study explores the impact of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention, which enriches the research on user behavioral intention in virtual streaming. Additionally, this study attempts to combine the stimulus-organism-response (S-O-R) model and flow theory in the field of virtual streaming, expanding the research areas. Finally, this study also provides valuable insights for virtual streamers and virtual streaming platforms. By enhancing their virtual personas and optimizing their streaming strategies, virtual streamers can more effectively retain users and maintain audience engagement. Meanwhile, virtual streaming platforms can gain a deeper understanding of user preferences, enabling them to launch high-quality events that sustain user popularity. These efforts collectively contribute to the advancement of the virtual streaming industry.

This study adopts the stimulus–organism–response model to examine relationships between the retail environment and customers’ emotions (i.e. pleasure and arousal), prestige sensitivity and word-of-mouth (WOM) intentions towards two luxury retailers: Luxury Brand A and Luxury Brand B.

Data were obtained from a sample of 135 Chinese customers who had purchased Luxury Brand A and 130 Chinese customers who had purchased Luxury Brand B directly from each retailer. The relationships between these two retailers were compared via partial least squares–Henseler’s multi-group analysis (MGA).

Findings indicated that pleasure and arousal did not play mediating roles between the retail environment and WOM intention for either customer group. Prestige sensitivity did not moderate customers’ emotions about Luxury Brand A or Luxury Brand B. Altruism served as a moderator between emotions (i.e. pleasure/arousal) and WOM intention regarding Luxury Brand B but was not a significant moderator for Luxury Brand A. Additionally, MGA suggested non-significant differences between Luxury Brands A and B. Implications for the luxury retail literature and luxury marketers are provided accordingly.

This study is one of the earliest to examine the moderating roles of price sensitivity and altruism on associations between the retail environment and customers’ emotions, prestige sensitivity, and WOM intentions in a luxury retail context. An MGA of customers for Luxury Brand A and Luxury Brand B was innovatively performed to evaluate the proposed framework.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.

National spirit, as a powerful legitimacy trait, shapes the consistency of a firm’s financial decisions, employee engagement and sustainability strategies. Combining this with resource-based view (RBV) theory, the study empirically examines the dual impact of national spirit on corporate environmental, social and governance (ESG) performance.

This paper utilizes data from Chinese A-share listed companies from 2009 to 2022 and employs machine learning methods to construct enterprise-level indicators of national spirit. In addition, the paper scrapes nearly 3 million ESG-related online news articles from the Baidu news website and uses machine learning methods to measure media ESG attention and sentiment.

The findings reveal that national spirit significantly enhances corporate ESG performance, operating through both internal and external channels: promoting social financing and boosting employee morale. Further analysis indicates that the positive influence of national spirit on corporate ESG performance is more pronounced in private enterprises, companies facing higher levels of credit constraints and firms in polluting industries. Additionally, managerial shortsightedness weakens the sustainable value of national spirit, while external media ESG attention and regional ESG governance efforts further strengthen this effect. Furthermore, different dimensions of national spirit exhibit varying impacts on corporate ESG performance.

This study provides new insights for promoting sustainable development systems in emerging economies and understanding the role of national spirit in corporate social responsibility investments.

This paper shifts the study of national spirit from macro-level cultural analyses to a micro-level perspective. It bridges gaps in the literature by providing empirical evidence on the role of national spirit as a soft resource that influences corporate financial behavior and employee morale. This study provides new insights into promoting sustainable development systems in emerging economies and understanding the role of national spirit in corporate social responsibility investments.

The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the factors that influence the viewership of online films. Therefore, this study aims to use the signaling theory to investigate how signals of varying qualities affect online movie viewership, considering both signal transmission costs and prices.

This study uses a sample of 1,071 online movies released on the iQiyi from July 2020 to July 2022. It uses OLS regression and instrumental variable method to examine the impact of various quality indicators on the viewership of online movies, as well as the moderating effect of price.

After conducting a thorough analysis of this study, it can be deduced that the varying impacts on online movie viewership are attributed to disparities in signal transmission costs. Specifically, star influence and rating exhibit a positive effect on the viewership of online movies, whereas the number of raters has a detrimental impact. Furthermore, there exists an “inverted U-shaped” relationship between the number of reviews and online movie viewership. Additionally, within the consumer decision-making process, both price-cost and price-quality relationships coexist. This is evident as prices negatively affect online movie viewership but positively moderate the relationship between rating, number of reviews and online movie viewership.

The research findings of this study offer valuable insights for online film producers to effectively leverage quality signals and pricing, thereby capturing market attention and enhancing film profitability.