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This paper proposes a novel geometric mean (GM) optimization-based boosting algorithm (GMOPTBoost) to improve the performance of boosting ensembles applied to solve the class imbalance problem in bankruptcy prediction. GMOPTBoost derives the best prediction by applying Gaussian gradient descent method to find the set of weights assigned to base classifiers to optimize GM. The main findings are as follows. First, the class imbalance problem has a negative effect on the performance. As IR values increase, the performances of boosting ensembles decreases. Second, GMOPTBoost makes a significant contribution to performance improvements of AdaBoost ensembles trained on imbalanced datasets.

As a result of mental health is gradually being valued when psychological illness such as depression gradually enter the public's field of vision, there is an increasing demand for high-quality and influential popular science articles on depression. However, the fact of uneven quality of online popular science articles on depression increase difficulty for the public to distinguish good one. The quality evaluation of popular science article can be regard as influence prediction. We construct a heterogeneous information network to integrate data from social platform and medical platform. And a heterogeneous graph neural network model based on the heterogeneous information network is proposed to predict the influence of popular science articles on depression. This research can help people select high-quality psychology popular science articles easily. It contributes to extend the influence scope of popular science articles and improve the mental health literacy of the whole people.

In modern economy, any firm cannot sustain by itself. Whatever the type of a firm, it is tangled up with other firms in any relation of supply and demand, partnership or competition, etc. In 2021, for example, chip shortage caused by the spread of COVID-19 and the sanction on Chinese chipmakers stroke the global automotive industry. As a result, major car original equipment manufacturers (OEMs) such as GM, Ford, Toyota, and many others stopped their production, which serially stopped their automotive component supplier’s production as well. However, the business magazine Forbes warns the worse situation with the messages “Battery scarcity could dwarf chip shortage impact on global auto sales” and “The semiconductor shortage will cut a total of 8.1 million cars from global production between 2021 and 2023, while between 2022 and 2029, 18.7 million rechargeable electric cars will be lost because of battery cell shortages” (Winton 2021). Due to the interdependence between firms, if any disruption erupts in the industry, its ripple effect impacts the cross-over in a multi-tiered value chain (Cachon and Lariviere, 2001). In 2010s, electric vehicle industry emerged by strong environment regulations and the hyper growth of the industry pioneers who are strongly based on information technology (IT), such as Tesla. Actually, automotive industry including electric vehicle is no longer limited to manufacturing, but is growing rapidly through a complex value chain combined with advanced IT technologies. Therefore it is highly required to understand the complex pattern and sustainability of the highly entangled system. In this research we investigate how the electric vehicle industry emerges and the resilience of the value chain changes. To tackle the research question, we introduce the novel methodological framework based on complex network theory and agent based model approach. From the empirical data on electric vehicle value chain of 6 years, we apply the framework to address the evolution of the industry using weighted network analysis (Figure 1). We found that the electric vehicle industry becomes more heterogeneous structure (Figure 2). This means that the companies. In complex network theory, the heterogeneous network structure has been well known to have the properties of “double-edge swords” in the robustness of the system, that is, it is usually very robust, but the collapse of a few central firms can cause whole system to collapse with a huge ripple effect (Albert et al. 2000). With the understandings of structural properties of electric vehicle value chain network, we examine the resilience of the network with introducing the agent based simulation model. From our simulation results, as year goes, the electric vehicle value chain becomes less resilient. Furthermore, from the result of the distinction between individual firm’s impact of unweighted and weighted aspect, we found some firm’s influence would be underestimated when one only consider the unweighted network properties. Our novel approach based on weight network analysis and agent based modeling would more capture the characteristics of electric vehicle industry and shed light on understanding systemic risks due to the individual firm’s disruption.

This study analyzed the Korean-Chinese translation error factors of machine translation services such as Papago and Google translate through self-attention path visualization. Self-Attention is a key method of the Transformer and Bert NLP model and recently widely used in machine translation. The study analyzes the difference in the Attention path between ST (source text) and ST' which meaning does not change and the translation output appears more accurately. Understanding these attention path pattern differences and each translation result TT (target text), and TT', the study summarized three types of errors: symbols missing error, grammar error, and multiple meaning words error. The study analyzed using the xlm-ReBerta multilingual NLP model provided by exBERT, for self-attention visualization, and suggesting some suggestions for error resolution. Through the study, it was found that the cause of translation error can be well identified using the Self-Attention visualization method, and through the explanation, machine translation algorithm developers can use it to improve service quality, and researchers can more understand machine translation algorithms.

This study aims to examine the effects of key elements of exhibitors’ satisfaction on positive behavior intention in the metaverse environment of a trade show context. We set word of mouth and willingness to return as predictive behavioral intention regressed by satisfaction - satisfaction with selfperformance and satisfaction with metaverse environment (immersion), in detail. To collect data, a virtual metaverse trade show environment is created based on Gather Town, a metaverse platform for conference meetings. This work-inprogress paper contains detail information on research motivation, hypotheses, environment settings, and empirical study plans. Data will be collected from multiple companies participating in the International Sourcing Fair 2021 in Seoul. We expect that this study will introduce a new way of predicting exhibitor’s business innovation through the application of metaverse trade shows without any hurdle of the Pandemic.

This paper aims to build predictive models for Airbnb Rating using the Big Data systems, which is distributed parallel computing systems. We use Machine Learning algorithms to build models to predict a rating of the Airbnb listing. The Airbnb ratings can help hosts improve the listing and the hospitality to gain more potential customers. On the other hand, the guests can make a decision based on the ratings that previous guests provided. It is essential to understand customer experience and its role in forming customer rating behavior. The overall ratings provided by customers are reflections of their experiences with a product or service. We use Two-Class Classification models to predict if the listing has a high or low rating based on the features of the listing. We compare the results and the performance of rating prediction models. The comparison is illustrated in terms of the accuracy metrics and computing time.

The goal of our research is to offer theoretical propositions to delve into the current phenomenon of an organization’s adoption or implementation of metaverse platforms or services. Our study attempted to employ the theoretical underpinnings of the goal contagion theory, dynamic capabilities, big blur effect, and the theory of organizational creativity. The current study suggests aspects of such theorybased organizational behaviors and tendencies which may affect the adoption or implementation willingness toward metaverse platforms and services. A theoretical research model and propositions are illustrated and discussed.

Recently many content consumers watch professionally produced video/TV content over mobile-based streaming services using the Over-the-Top (OTT) platforms. The current study is aimed to understand the users’ perception of mobile TV streaming services through the lens of the sociocognitive method. Using cognitive mapping stemmed from social representation theory, our study explores the core and peripheral user perceptions toward mobile TV streaming services. We collected words or short phrases that best describe the mobile TV streaming services from 432 users. Then, the data were coded and analyzed to create a cognitive map through the similarities calculation and identifying the core/peripheral perceptions. Finally, we interpret the structure of the cognitive map that reflects the mobile TV users’ perceptions. The findings of this study reveals certain aspects of the mobile TV streaming services are more or less appreciated through which we provide a strategic guide to the industry.

This study is to focuses on a user’s attitude toward augmented reality games. Based on the Technology Acceptance Model (TAM) and Flow theory, continuous usage intention was set as a dependent variable, and immersion was set as a mediating variable. As independent variables, spatial presence, perceived interactivity, perceived pleasure, and sickness were set. Besides, this study strived to compare and analyze Korean and Chinese Data. The results of this study were as follows. First of all, Korean users had a significant effect on spatial presence, perceived pleasure, and immersion. Spatial presence and perceived pleasure had also mediated effects on continuous usage intention through immersion. However, perceived interactivity and sickness did not affect immersion and even no mediating effect to continuous usage intention. In the case of Chinese users, spatial presence, perceived interactivity, and perceived pleasure were grouped into one variable. This variable influenced immersion and also had mediated effect on continuous usage intention. However, sickness, like Korean users, did not affect the set path. This study had implications to analyze user perspective using immersion, which was found a significant variable in previous research. In addition, this study found similarities and characteristics through a comparative analysis between Korean and Chinese users indirectly.

As of October 2021, the COVID-19 pandemic is still raging around the world and people’s lifestyles have also been changed. COVID-19 can spread through minute droplets, which makes it easy to transmit (especially the Delta variant). For most of 2020, vaccines were not available and the most effective way is to control the spread of the virus was social distancing and quarantine. Social distancing is very important to mitigate the spread of COVID-19 and population density becomes a crucial factor. Another way to deal with this coronavirus pandemic is vaccination. Wealthy countries, which have more healthcare expenditure, begin to develop vaccines in 2020 or invest in pharmaceutical companies to secure the supply of vaccines. Healthcare expenditures are closely related to a country’s GDP. This research studies the impact of GDP and population density on the spread and control of COVID-19.

A new coronavirus, COVID-19, was discovered in Wuhan, China, in December 2019. This new coronavirus spreads like wildfire and becomes a global pandemic. As of October 2021, more than 241 million people are infected, and around 5 million are dead. The pandemic has disrupted our lives and world economies. Different countries have responded to the pandemic in different ways with varying results. While various policies can lead to different results, many factors can affect the spread and severity of the COVID-19 pandemic. This research investigates the effects of Information and Communication Technologies (ICT) and healthcare expenditures on the COVID-19 pandemic.

During the pandemic lockdowns from 2020-2021, businesses operated on digital platforms when mobility and logistics limited the travel and transport of products and services. For Malaysia, the digital economy in 2018 contributed to 18.5% of the economy, which was equivalent to MYR267.7 billion in DGP. Leveraging on the success of the digital economy, village cooperatives, and cottage industries should emulate the trend in e-business. The qualitative study using interviews as the primary data collection showed that these entities based in rural areas could profit if the ICT infrastructure is in place. For now, internet access is the main impediment to embracing the digital economy through online business. The study is significant as the village cooperatives, and cottage industries contribute to a significant percentage of Malaysia’s economic growth. In today’s Information Era, the local industries must be part of the global commerce since we are heading towards the endemic phase.

COVID-19 has triggered researchers to explore the topic which can be shown by the number of publications since the pandemic has started. However less is known about how COVID-19 acts as catalyst in the subject area of information system publication. Information system research itself is a unique interdisciplinary topic allowing broader view. This research seeks to add a deeper insight about how COVID-19 becomes the trigger on research specifically on the specific topic. By using extracted SCOPUS database in the area of Information System combined with bibliometric analysis, this article seeks presents study of COVID-19 literature in the domain of Information System to identify current research trends. We further expect to highlight the connection of COVID-19 role and the astounding number of research trend specifically on the topic of information system.

The emergence of public health events has a devastating impact on the health of people. However, it is still unclear whether the outbreak of public health emergency event would influence the people’s health behaviors in online health communities. In this study, we collect the data of users’ physical activities and content-generation activities from a large online health community in China from January 2019 to April 2021, in which period COVID-19 had outbroken in China. Through adopting an interrupted time-series strategy, we find that users expend greater effort on improving the physical activity level as compared with the time before the COVID-19. The burst of COVID-19 makes people pay more attention to their health and improve their health awareness. Furthermore, we observe that after the COVID-19, users are more likely to share contents on the community. Our results have implications for public health and online community management.

The fast diffusion of Internet has changed the way in which individuals interact in various contexts. The education sector is also part of this transformation. Universities, for example, have been gradually investing in technologies before the COVID-19, but it was this pandemic the event that boosted the worldwide adoption of these platforms. Recent reports show that mobility stands as one of the main benefits of remote classes, while the lack of functionalities related to community interaction may stand as an important roadblock for their adoption. Considering that e-learning platforms will be critical for higher education in this new context, even after the pandemic, it is important to understand the factors that lead to a continued use of these systems. The present research focuses on the effect of mobility convenience and features related to virtual communities. Results are expected to provide theoretical and practical implications.

With high vaccination rates, living with COVID strategy is considered in the major economics. However, there is a lack of detailed research on how the deeply suppressed travel intention will manifest under the new normal. In response, we propose a model to predict the pent-up intention of travel in the future., Specifically, we apply the thought suppression concept, in the integrated framework of feelings-as-information theory and the extended construct-negotiation framework that includes learned helplessness. This study analyzes not only the current impact of travel constraints with learned helplessness, but also feelings toward travel-related content online and willingness to negotiate with the constraints will be analyzed. We expect these new attempts would provide meaningful implications on online travel content providers or travel marketers online.

Misinformation – content that lacks truth, but the motivation of falsehood is uncertain – on social media during a health pandemic presents a major concern for public health. Recently, the vast volume of news and information around COVID-19, which the World Health Organization refers to as “infodemic,” has led to an unprecedented increase of health misinformation woven into the online narrative about the pandemic. Online narratives, particularly on social media platforms, are critical objects of inquiry as narratives are fundamental to how people construct socially shared belief systems, and that can be the primary means to spread health misinformation online. Specifically, in the case of COVID-19, false social media narratives about the origin or unapproved or untested remedies can influence public health attitudes and behavior, potentially costing billions of dollars and numerous lives. For instance, the Centers for Disease Control and Prevention reports a sharp increase in poisoning cases related to cleaners and disinfectants in the US after the COVID-19 outbreak. While social media sites assume responsibility for moderating the platforms towards more meaningful and trustworthy content (for instance, see the joint statement from Facebook, Twitter, Google, YouTube, and others to combat fraud and misinformation about COVID-19), several fact-checking organizations across the world are also devoting their efforts to publish an evidence-based analysis of online narratives to convince audiences of its inauthenticity. However, there is a lack of research on how health misinformation could potentially impact individuals’ attitudes towards the pandemic. To that end, in this study, we develop a topology of health misinformation to understand the health behaviors of individuals.

Since the beginning of the COVID-19 pandemic, various research has been conducted regarding racial discrimination. However, only a few research has focused on the discrimination against the Asian population that escalated due to the pandemic. This study addresses the negative sentiment towards the Asian population during the coronavirus pandemic. The research analyzes considerable amounts of Tweets from Verified Twitter accounts and Media channels’ accounts to compare the reactions of racially targeted tweets and racially oriented tweets. The study attempts to discover the effect of those verified accounts on general user sentiments towards Asian population. The study finds that negative sentiments of Tweets do not actually lead to racist behaviors.

Seventy-one percent of the entire Philippine population are active social media users. The biggest group user are the Filipinos in the 18-24 age range (Gen Z). As social media becomes more universal, consumers are acquiring information from diverse channels (Rauniar et al. 2014). Information like the latest technology, your favorite K-pop celebrity, and many more. Social media platforms allow users to have conversations, share information and create web content. Billions of people around the world use social media to share information and make connections. On a personal level, social media allows us to communicate with friends and family, learn new things, develop our interests, and be entertained. Also, with the ever-growing wave of Korean culture influence, beauty industry has also widened its market in the country. Moreover, with the increase of internet, social media, and Korean culture awareness in the Philippines, its usage of SM shifted from entertainment to product placement platform and online shopping. In modern times, public consumption behavior tends to revolve around social media rather than mass media (Aksoy et al. 2013). This study aims to explore the factors of young Filipinos social media purchase by investigating whether purchase decision of Korean beauty products is supported social media usage (i.e. watching Korean drama and Korean celebrity endorsement online).

In this paper, we present an e-book recommendation system using topic-modeling based on Latent Dirichlet Allocation (LDA) that is a probabilistic model increasingly used in various textual data analysis. Through the generated topics, we found the latent themes of the topics by estimating probability distributions for the topics in eBooks and words. We also address the basic concept of micro-segmentation used mainly in customer marketing field, which ensures that a variety of eBooks are recommended to users. The primary aim of our proposed method is to integrate the effective and efficient techniques with only using textual data of eBooks to improve recommendation performance in Content-Based Filtering (CBF) recommendation when it is unable to rely on the Collaborative Filtering (CF) utilizing ratings and reviews data obtained from a user's own past information. The experiment demonstrates the robustness of the presented method, and also shows that the method provides explainable recommendation results.

Due to the nature of live commerce, which has the characteristics of both live streaming and e-commerce, it is necessary to distinguish between the viewing intention to watch the live commerce and the purchase intention to purchase the product in the live commerce. Therefore, this study intends to examine the influence of the host, system, and service attributes of live commerce on viewing intentions and purchase intentions from the perspective of the generation MZ. This study assumes that the host attributes of live commerce will have a positive affect on viewing intention, the system attributes of live commerce will have a positive affect on purchase intention, and the service attributes of live commerce will have a positive effect on the viewing intention and purchase intention. In order to verify this, a survey will be conducted targeting the generation MZ.

China has now become the largest live commerce market and the COVID-19 has catalyzed live commerce into the next level. TikTok is a platform that is popular with short video sharing and the largest number of daily active users in the world. After its live commerce function was first introduced in 2019, TikTok has become among the top three live commerce platforms in China within just a few years. With the COVID-19 pandemic, the growth speed of TikTok live commerce exponentially increases and its potential seems unlimited. Although consumers’ (watchers’) impulse buying is considered one of main success factors, the specific mechanism on how their impulse buying is influenced has not been clearly investigated. Therefore, based on the S-O-R framework, this study identifies influencer (i.e., attractiveness, expertise, and interactivity) and platform characteristics (i.e., guidance shopping, visibility, and metavoicing) as stimuli factors and examines their impacts on the likeliness of impulse buying (response) through flow experiences (i.e., enjoyment and concentration) as organism factors in Chinese individual live commerce context using the TikTok platform. With survey responses from 324 Chinese consumers who have used TikTok live commerce at least once within six months, research hypotheses were tested using the structural equation modeling (SEM) technique. Research findings show that, with the exception for interactivity and metavoicing, most stimuli factors have an impact on enjoyment and concentration, and both flow-related experiences also influence consumers’ likeliness of impulse buying. This research would enrich the studies on live commerce and expand the S-O-R framework in the context of live commerce. It is expected that this study will provide many practical implications for managers as well.

Live streaming commerce has gained popularity over the recent years, shifting users’ shopping patterns from traditional shopping experiences to the users’ striving towards real-time interactions. Drawing upon the stimulus–organism–response (SOR) framework, this study investigates environmental stimuli effects, with the focus on environment-consumer and streamer-consumer interactions, from a live streaming commerce context on viewers’ internal states (enjoyment, psychological distance, trust) and the response (purchase intention). The data were collected through a survey for the respondents that have used the live streaming commerce before. The PLS SEM method was used to verify the relationships proposed in the model. The theoretical and managerial implications are discussed.

At present, the world economic situation is complex, and the epidemic has dealt a huge blow to global economic development. In this context, it is particularly important for China's economic construction to accelerate a pattern with the domestic circulation as the main body and the mutual promotion of domestic and double cycles between China and international cycles. From the perspective of the industrial chain, China is still in the middle and low end of the value chain, and the overall export competition and trade volume are low. Strengthening China's industrial chain with the help of regional economic integration is an important way to promote the "dual circulation", which can simultaneously stimulate the vitality of the two domestic and international markets, promote each other, and enhance the ability to resist risks. Among them, the Regional Comprehensive Economic Partnership Agreement (RCEP) has become a crucial platform for regional cooperation for China to build a current "dual circulation" development pattern. The development of digital economy relies on the rapid changes of digital technology. With this in-depth development of digital technology and the growing development trend of the digital economy, we are still deeply troubled by the data leakage, data abuse, digital security, network security and other technical issues, which also creates our trust in the digital economy. Studying the digital trust problem is also an indispensable step towards in achieving a healthy, efficient and sustainable digital ecological environment. Although scholars have conducted extensive studies on supply chain services in cross-border transactions and the development trend of the digital economy, the related research results have failed to address the following issues. First of all, due to cultural differences and customs, consumers in different countries often show differences in consumption behaviors. Therefore, it is necessary to conduct a comparative study on consumers in different countries to understand their behavioral preferences and differences. Secondly, most of the current literature on trust issues in cross-border transactions mainly focuses on consumer privacy and information security. It is necessary to sort out the framework of supply chain services and explore consumers' choice strategies when facing different types of services. Finally, scholars often focus on one or several types of influencing factors and ignore the interaction and influence of different types of factors. Therefore, this topic believes that in the current research, the trust relationship management model for the inclusive development of digital trade in the regional integration environment has not been constructed wholly and systematically, and many essential components have not been included in the research framework, which restricts the further development of the research in this field. So, this project will carry out analysis in five dimensions, from the technology and development of the digital economy, the reshaping of services and consumption, the acceptance of the customer, the labor market and ethical and moral safety, to deconstruct the connotation and the pattern of digital economy. This can not only describe the development picture and mechanism of digital economy in each dimension, but also try to clarify the relevance and influence among the dimensions. This project takes the trust of different stakeholders in the digital economy as the entry point. Also, it takes the users and enterprises under regional integration as the research objects to explore the specific factors affecting the trust behavior of the surrounding destiny community. The research process focuses on analyzing the trust management model in the overseas development of Zhejiang enterprises and exploring the changes that RCEP will bring to the overseas development. This project conducted an empirical study based on questionnaires, using a structural equation model through which the measurement and structural models were evaluated. The project verifies information reliability through empirical studies, examines the trust transfer function of trusted third parties in the digital environment through laboratory experiments, and analyzes the factors that moderate trust transfer by relying on partial least squares multigroup analysis. Ultimately, this topic realizes the evaluation of the effectiveness and overall effectiveness of the trust model. The study results verify that RCEP will strongly support Zhejiang enterprises' foreign development, and at the same time, identify some challenges faced by some Zhejiang enterprises in the process of foreign development. Also, the results will be beneficial to discover some new ideas to promote economic development further with RCEP. The research described in this paper was supported by a grant from the National Undergraduate Innovation and Entrepreneurship Training Program (File No. 202110337048).

The mutual aid economy mainly comes from the sharing economy. The “mutual aid economy” model of taking out personal idle funds to share with others to obtain the most significant economic benefits is an area that the international community is currently striving to explore. After the establishment of the "Mutual Insurance Commune", parallel to the development of the digital economy and the significant improvement of the material living standards, the mutual aid economy with unique advantages has been experiencing rapid growth in China. Because China has a large population and a large base of the bottom poor groups, the traditional insurance business can no longer meet the needs of these groups. In this context, the network mutual assistance platform bred by the combination of the Internet and the traditional insurance industry has ushered in a development boom. In recent years, however, the Internet mutual aid platform is under a contentious and intensified debate，which has a great relationship with the standard use of funds. Some network mutual aid platforms put forward that they have the right to manage the mutual aid funds stored on the platform, but there is no clear limit on the scope of use. In addition, the information disclosure of some platforms is not transparent enough, which makes the use of mutual aid funds standardized to become a major problem, which severely limits the development of network mutual aid platforms. A lot of news of “xx mutual assistance platform shutting down” has shaken the rationality and longevity of the network mutual aid platform. In addition, due to China's unique domestic political environment and policies, for example, in September this year, The State Council issued the notice of "normalization of collective procurement of medicines”, which will reduce the potential population of mutual insurance and have a certain impact on its development. These show that its stable development has hidden risks that it cannot ignore. Since the closure of Fun in Funding and Water Droplets Mutual Aid in March of this year, two leading mutual-aid platforms, the credibility of the mutual aid economy, the sustainability of online mutual-aid platforms, and the future of mutual aid are all doubtful and faint. Factors such as establishing the trust relationship between the platform and the consumer, the financing of the risk of entering and exiting the risk, the breadth, depth and timeliness of mutual assistance behaviour challenge the survival and development of network mutual assistance platforms. It also means that the transformation and upgrading of the traditional insurance industry in the Internet age is not smooth. However, on the other hand, online mutual aid platforms have the following advantages: First, mutual aid platforms have outstanding social benefits, which can maximize the benefits of social resources. Second, the fund scale of the network platform is relatively small, and the funding object is scattered. Third, the mutual aid platform's motivational orientation to pursue benefits makes its risks more controllable than other platforms. Also，the introduction of the "Blockchain" technology enhances the transparency and reliability of the mutual assistance mechanism. In the process of mutual-treasure operation, the integration of blockchain technology realizes the establishment of mutual-treasure advantages. This study believes that if we can correctly guide network mutual aid, it can become a new model in financial and insurance innovation. The study aims to provide constructive suggestions to promote the transformation and development of the network mutual aid platform and achieve high-quality development of the mutual aid economy in China. According to the development status of low threshold, high security, low intermediate cost and high self-propagation of mutual aid economy and network mutual aid platform at home and abroad, taking “Xianghubao”, a domestic “late start, fast development, “strong strength” network mutual assistance platform, as the research object. This study focuses on building a trust relationship between the network mutual aid platform and consumers in the mutual aid economy from the normative perspective of using technology and controlling mutual aid funds. Employing semi-structured interviews, questionnaires and data modelling and analysis, the study has explored the prerequisites for the rise and prosperity of the mutual aid economy include increasingly abundant idle resources, the establishment of collaborative network platforms, mutual aid value consensus, industry environment，then offers a deep analysis towards the mutual trust mechanism between the enterprise and the user within “Xianghubao”, to further probe into the logical and critical elements which impact on building the relationship of trust between the network mutual aid platform and consumers in mutual aid economy. Also, the "Blockchain" technology is introduced to enhance the transparency and reliability of the mutual assistance mechanism. Based on the study, the company can make corresponding countermeasures from the four dimensions of internal management, trusted products, risk control, and mutual trust between customers to deal with the reformation and the closure of “Xianghubao”. The research described in this paper was supported by a grant from the Zhejiang Province Undergraduate Innovation and Entrepreneurship Training Program (File No. S202110337116).

With an increasing need of contactless service after the outbreak of COVID-19 pandemic, a tele-operated robot started being deployed in a variety of service contexts. Interestingly, this emerging trend has opened opportunities for elderly and disabled people to participate in social activities through a tele-operated robot. Capturing this phenomenon, the objective of this study is, by taking an operator’s perspective, to identify what aspects of a teleoperated robot can allow elderly and disabled people to participate in social activities and explore how these aspects can enhance their work engagement and performance. To address this, we propose a research model based on representation theory. The model will be examined by online survey targeting 40 disabled people who are currently working as staff via a tele-operated robot in the avatar robot café in Tokyo, Japan.

The global pandemic has enormously changed people's consumption activities and business ecosystems. One of the most notable changes is the increase in contactless services due to social distancing, including kiosk orders at restaurants and coffee shops and cashier-free small stores. However, these services are still experimental or uncomfortable for some users, and this becomes the challenge for the transition to a digital society. In the context of the current New Normal state, where the untact interactions in response to the pandemic are highlighted, research on the concept of such non-face-to-face communications is still lacking. Therefore, this study uses the affordance theory to (1) define four types of untactification affordances in non-face-to-face shopping, and (2) determine how these types of affordance affect users' shopping engagement and continuous use intention. For this purpose, this study plans to collect and analyze data from users of F5 Future Store, a famous cashier-free convenience store brand in China.

Founded on social network theory, this study will recruit 168 patients in an online health community as the research subject, and uses Poisson regression model to investigate the impact of network structure characteristics on user participation behavior. This study contributes to the body of knowledge in the online medical field and provides practical implications to the managers of online health platforms.

Safety issue is the decisive key to service commercialization for autonomous vehicles. This study examines the relationship between perceived safety and the quality of the journey in AI-based self-driving taxi services. The results will provide scholarly and practical implications to enhance AI-based self-driving taxi services.

Improving patient information disclosure is the premise to ensure treatment effect. This study explores the effects of different interaction modes (human doctor, AI doctor, and the combination of the two) and different degrees of privacy concerns on patients’ self-disclosure behavior. The research results will provide academic and practical implications for improving the application of artificial intelligence in telemedicine services.