E-Business. Digital Empowerment for an Intelligent Future

Frontmatter

Bibliometric Analysis on the Research Hotspots of Recommender Systems

Abstract

Research on the hot topics and future development trends of recommender system is of great significance for improving the accuracy of recommendation results and saving users’ time. A total of 867 SCI and SSCI literatures related to recommender system were selected from the Web of Science database from 2013 to July 2022. The visual knowledge graph analysis tool CiteSpace was used to analyze the temporal and spatial distribution characteristics, knowledge basis, research hotspots and frontiers of personalized recommendation technology research from five dimensions: literature growth trend, regional distribution, literature co-citation relationship, keyword co-occurrence and emergence. The participation of Chinese and American researchers are much higher than that of other countries and the exchange and cooperation between countries need to be strengthened. The research focuses on the application of algorithm in recommender system, improvement of collaborative filtering algorithm, model construction, social network and neural network. The research frontiers include feature extraction of users and projects, machine learning and attention mechanism.

Jiangping Wan, Siting Lin, Jing Zhang

Research on Knowledge Sharing Efficiency Evaluation of Open Innovation Community: A Case of Xiaomi Community

Abstract

Under the platform economy, more and more enterprises attract users to participate in innovation by means of Open Innovation Communities (OIC) and improve organizational performance through knowledge sharing. How to evaluate the efficiency of knowledge sharing scientifically is of great significance. In this paper, a total of 61 “circles” datum of the Xiaomi community were acquired as examples and divided into categories, and they were evaluated the knowledge sharing efficiency using the three-stage DEA model. The results showed that environmental factors and random interference had a strong impact on the efficiency of knowledge sharing in the community of enterprises. The comprehensive technical efficiency of 91.67% of the “circles” decreased significantly after adjustment, mainly due to low scale efficiency. The number of users featured posts, the number of fans, employee participation and the percentage of authenticated users had a positive impact on the efficiency of knowledge sharing in the community, and the number of user posts and community size had a negative impact on the efficiency of the community knowledge sharing. Finally, it discussed countermeasures and suggestions to improve the efficiency of knowledge sharing in the enterprise-hosted community from three aspects: community scale, community incentive system, and personalized service.

Jian Tian, Xuefeng Gao

Stock Price Overvaluation and Digital Transformation Investment of Listed SMEs: Impact Analysis and Path Testing

Abstract

Based on the investment perspective, this paper takes the data of listed companies on China's SME Board from 2013 to 2019 as a research sample, and conducts an impact analysis and path test on the relationship between stock price overvaluation and investment in digital transformation of listed SMEs. Overall, the results of this paper support the equity financing channel hypothesis that overvaluation of stock prices promotes the capital investment of digital transformation of listed SMEs, but does not support the rational catering channel hypothesis. The research conclusions of this paper provide reference ideas for promoting the digital transformation investment of listed SMEs in China.

Weiwei Gan, Wenbin Qu, Dian Su

A Tripartite View on Performance Matrices of Live Commerce

Abstract

Live commerce is a novel form of social commerce in which streamers engage following fans through real-time interactions and deliver vivid presentation of products. We propose a tripartite view of the core elements in the live commerce context, including streamers as sellers, following fans as consumers, and streaming videos of product demonstration, that potentially affect live commerce performance matrices in terms of sales volume, sales efficiency, and fan growth number. We analyzed an archival data of 373 livestreaming shopping shows with 34925 products collected during Double 11 Day of 2020 on Taobao Live, one of the largest live commerce platforms in China. The empirical analysis reveals that: (1) streamers’ social capital positively affected sales volume and sales efficiency, but negatively impacted fan growth number; (2) following fans’ engagement promoted sales volume, sales efficiency, and fan growth number; (3) products’ live demonstration increased sales volume, decreased sales efficiency, but did not affect fan growth number. Our research offers nuanced understandings of how the three elements of streamers, fans, and product streaming videos affect performance matrices of live commerce.

Ruihao Li, Qian Wang, Xinlin Yao, Xixi Li, Xiangbin Yan

Synergizes HeXie Management Framework with Program Management Approach for Industry 4.0 Transformation

Abstract

This dissertation explores the methodology for building intelligent manufacturing factories in medium and small-sized enterprises. Synergising HeXie management theory with a program management approach increases the industry 4.0 project success rate. Eventually, help those SMEs to achieve their strategic goals as a practical contribution. Also, the article optimises HeXie management theory from a conception to an applicable implementation model for Industry 4.0 projects.

Since Germany proposed the concept of Industry 4.0, there has been research in academia and industry to explore the technology of Industry 4.0 and the improved competitiveness of enterprises. Some articles explain that SMEs will have more challenges in transitioning to Industry 4.0 than large ones. The HXMT management theory generated for the CCAU (complexity, change, ambiguity, and uncertainty) environment could be suitable for integrating the oriental and occidental wisdom through coupling various project and program management methods. This article will use a Chinese semiconductor company's business case to validate the HXMT theme's effectiveness. Project management skills are a critical sub-factor of HeXie coupling to affect project management success significantly. Moreover, sustainability is a vital He-principal factor which impacts project success.

This article is an exploratory dissertation validating that the HeXie management model improves the success rate of Industry 4.0 projects by integrating technology elements and non-technology enablers, especially in Chinese SMEs.

Xin Wang

Big Data-Based Recommendation Algorithm in E-commerce Personalized Marketing

Abstract

E-commerce recommendation algorithm is the core of the entire recommendation system, which plays a very important role in e-commerce personalized marketing. Its recommendation accuracy and efficiency directly affect the overall performance of the recommendation system. E-commerce recommendation algorithm based on data mining technology, in-depth analysis of various user data especially user access data, get each user’s hobbies, interests and specific buying behavior characteristics. This paper analyzes the related technologies and algorithms of e-commerce recommendation system, and proposes the architecture of e-commerce recommendation system based on user behavior data. In order to meet the requirements of recommendation accuracy and real-time performance, the recommendation module designed in this paper is mainly composed of three modules: content-based recommendation module, collaborative filtering algorithm-based recommendation module and user behavior-based recommendation module, and the functions and technologies of each part are specifically analyzed. Finally, a personalized marketing scenario is created to evaluate the effect of the recommendation system.

Shujun Li, Li Li, Yiwen Cui, Xueyan Wu

How Digital Change and Innovation in the Workplace Affect Front-Line Employee Retention: A Cross-Sectional Study Based on the Aged Care Industry

Abstract

In order to understand the retention of front-line employees in the process of digital technology change and innovation, this study uses the information system continuation theory and job demand-resource theory to build a framework, and conducts a cross-sectional survey of the post-use stage of digital technology. The focus is on the relationship between digital technology quality factors and continued trust, distrust, job engagement, job burnout and retention intentions. The results showed that continued trust in digital technology was the strongest predictor of retention intention. Job burnout and distrust were not important to retention intentions. The results also show that the quality factor of digital technology is an important antecedent of continued trust and distrust.

Ying Wang, Yuting Feng, Changyong Liang

A Case Study of Collaborative Learning Within a Digitalization Learning Environment

Abstract

The Covid-19 epidemic ushered in a new era of hybrid learning. After the Covid-19 pandemic, information technology (IT) acceptance is no longer a problem. And given that it is the “postdigital”, technology-related constructs should be updated and devoted to creating a lifelong agile learning environment (LE). The research question is how to manage collaborative learning (CL) activities through online integrated platforms to better serve outcome-based education (OBE). This research reviews the digital transformation advancement in learning management systems and points out that the digitalization LE breeds postdigital learning, which is based on IT “affordance” and well organization and distribution of course resources. When led by OBE, this paper employs qualitative synthesis research and to foster personal development summarizes the appropriate method for managing CL activities as student-centered lifelong learning, organization of role-based activities, and all-around assessment. Finally, the findings are a conceptual framework for student-centered learning within digitalization LE and an illustration of a curriculum with a customized Feishu of ByteDance performing CL. The contribution involves learning in less structured environments, such as an advanced enterprise collaboration and management platform, which prompts creative and innovative approaches to uncertainty and change. As a result, the practical implication facilitates students to find both their will and their own creative and exploratory ways of lifelong learning.

Xiaoxia Wang

A Study on the Influence Mechanism of Self-sacrificial Leadership on Employee Engagement-Based on Dual Identity Perspective

Abstract

The self-sacrificial leader, who puts the collective interest first and is willing to postpone or sacrifice personal interests in order to achieve organizational goals, plays an important role in maintaining smooth operations and overcoming corporate crises in today’s complex and changeable information age. The effective enhancement of employee engagement can also bring positive impact to individuals and organizations. Based on social identity theory, this paper will explore the mechanism of self-sacrificial leadership on employee engagement and its dimensions from the perspective of dual identity: leader identification and organizational identification. The findings show that: Self-sacrificial leadership can positively influence employee engagement. Leader identification and organizational identification are the mediating variables in the path of the influence of self-sacrificial leadership on employee engagement, and the mediating effect of leader identification is more significant. Leader identification can influence organizational identification, and the multiple mediating effect is significant in the path of the influence of self-sacrificial leadership on employee engagement. Cognitive engagement, affective engagement and behavioral engagement are all consistent with the above hypotheses when used as dependent variables.

Tingting Wang, Fengqin Diao

Impact of Data Breach on IT Investment: Moderating Role of Buyer-Supplier Relationship

Abstract

Data breach is a typical IT failure in the process of digitalization, and it helps firms recognize their shortages of IT security capabilities, influencing their IT investment. Drawing from failure learning theory, this study analyzes the influences of data breach on the firm’s IT investment and examines the moderating effect of firms’ position in the buyer-supplier relationship. Based on data from Compustat, PRC, ITRC, and CI Tech databases in 2009–2016, this study uses a fixed-effect model to analyze the relationships among data breach, buyer-supplier relationship, and firm’s IT investment. This study finds that a data breach increases a firm’s IT investments. When a firm plays a role as a dependent supplier in the supply chain, the positive effect of data breach on IT investment is weakened. However, when a firm’s position in the buyer-supplier relationship is a principal customer, the positive effect of data breach on IT investment is strengthened. Our findings provide practical guidance for firms to better understand and respond to data breaches and improve their IT security capabilities.

Meirong Zhou, Miao Hu, Shenyang Jiang

The Influence of Benefit Appeals in CSR Communication on Consumers’ Willingness to Co-creation

Abstract

Based on the background of corporate social responsibility (CSR) communication, this study aims to explore the role of different types of CSR interest appeal information (self-benefit vs. others-benefit) in CSR communication of different consumers on social media, and mainly discuss consumers’ willingness to participate in CSR co-creation. A total of 288 valid questionnaires were obtained through an online experiment. The moderating effect of consumer values was verified by “floodlight” analysis and the moderated mediating effect of consumer trust was verified by the Process program. Self-enhancement values have a congruent effect with CSR communication benefit appeals. Specifically, benefit appeals characterized by self-benefit generate higher consumer trust and willingness to co-create value among individuals with high self-enhancement values (vs. low self-enhancement values). CSR credibility and brand trust have a continuous mediating effect in the interaction between self-enhancement values and benefits appeals, while the interaction between self-transcendence values and benefits appeals is not significant. Understanding how consumer values influence consumer responses to CSR social media posts with different interest claims can provide marketers with useful guidance on how to creatively segment customers and curate appropriately targeted messages to effectively connect with consumers on CSR campaigns.

Xiaoping Liu, Yingqian Liang, Shiyu Wang

The Influence of Marketing Stimuli and Contextual Factors on Consumers’ Intention to Make Impulse Purchases in Live E-Commerce

Abstract

Impulse purchase is a prevalent consumer behaviour, and consumers’ willingness to consume on impulse is even stronger in live e-commerce context. Based on the S-O-R model, the study explores the mechanism of the factors influencing consumer’s impulse purchase intention in live e-commerce from five dimensions: price discounts and time limits of marketing stimuli, interaction, opinion leaders, atmospheric cues of contextual factors. Meanwhile, a structural equation model is constructed in combination with flow theory. Data were collected through questionnaires, and SPSS 22.0 and AMOS 21.0 were used to analyse the data of sample. It shows that price discounts, time limits, interaction, opinion leaders and atmospheric cues all positively associate with impulse purchase intentions, with the flow experience playing a mediating role in this process. The results suggest that platforms can design engaging atmospheric cues; operators can innovate live-streaming gameplay and optimise incentives; and consumers should spend rationally according to their actual needs. The study contributes to an understanding of S-O-R theory application in live e-commerce context, and enriches the research on the antecedent variables of impulsive purchase intention and its formation mechanism.

Yi Chen, Wenwen Yue

How Older Adults’ Moments Sharing in SNS Contributes to Their Subjective Well-Being?

Abstract

The purpose of this study is to investigate the effects of older adults’ moment sharing behavior on their hedonic, social, self-esteem gratification, and subjective well-being by using the theory of use and gratification. By adopting a questionnaire survey, 226 valid samples were collected and further analyzed using PLS-SEM, to reveal the antecedents of gratification in social media use and the effect of gratification on older adults’ subjective well-being. Results show that older adults’ moment sharing behavior has positive effect on hedonic, social, self-esteem gratification, and subjective well-being. Social gratification and self-esteem gratification have positive effect on subjective well-being. Social isolation moderates the effects of older adults’ moment sharing behavior on their perceived hedonic, social, as well as self-esteem gratification. This study broadens the research on subjective well-being of older adults by linking their social media use with the theory of use and gratification. This work was supported by the National Social Science Foundation of China (Grant No. 20CGL055).

Ru Zhang, Wenlong Liu, Yi Jiang, Shenghui Sang

Video Going Viral: Subjective Emotional Clash vs. Objective Emotional Assertion

Abstract

As online video has gradually become the main channel for information dissemination and marketing advertising, it is necessary to determine which factors will affect the diffusion of video on the website further. The research goal of this paper is to explore what kind of title can help online videos attract more views. The research takes 49989 videos in bilibili as the research object, analyzes the relationship between the emotional polarity expressed in the title text and the number of views the video gets, and explores the role of personal pronouns play in the relationship. The results show that no matter whether the video titles contain positive or negative emotions, the video titles with higher polarity of these emotions can get more attention. In addition, those video titles that use personal pronouns also get more attention. Simultaneously, the use of personal pronouns moderates the impact of title’s sentiment polarity. The conclusion provides guidance for video publishers who produce content and helps them get more attention.

Jiang Wu, Yaxuan Yang, Pu Sun, Mengxi Zhang

Understanding First-Aid Learning Intention Through Using Social Media: Perceptions from External Emergency Events and Individual Internal Changes

Abstract

Emergency events, such as out-of-hospital cardiac arrest, are China’s leading causes of mortality. However, witnesses of emergencies are seldom trained with first-aid measures before emergency events happens. Relative to traditional offline first-aid training methods, social media greatly enhanced audiences’ interest in first-aid learning in a more entertaining, time-saving, and labor-saving way. Based on Construal Level Theory (CLT), this study aims to understand the impact of external emergencies (past emergencies experience) on individual internal change (psychological distances) and subsequently generate first-aid learning intention through using social media. As emergencies are severe but not widespread, this study only examines social and spatial dimensions of psychological distance (PD) to broaden the application scenarios of CLT. At the same time, we apply prosociality to measure the individual difference. This study conducts a survey in a first-aid popularization account on Sina Weibo. 348 participants, who had never learned first-aid knowledge and skills before, engaged. Results prove that both PDs and prosociality may be impacted by external emergency experiences, then promote related learning intention. This study also finds that prosociality moderates the relationship between spatial distance and related learning intention. This study roots in an emergency context and broadens the application of CLT in first-aid learning. At the same time, since first-aid training is usually hard to grasp and residents usually do not need complex skills to rescue people in emergency events, we applied social media as our learning context in this study to lower the threshold of first-aid education.

Huijing Guo, Xifu Wang, Xiaoxiao Liu, Xiaofeng Ju

Impacts of Analyst Reports’ Descriptions of Corporate Innovative Behavior on Stock Price Synchronicity

Abstract

Using text analysis, in this study, we identified and quantified the textual contents of the enterprise innovation behavior descriptions in analyst reports, and we formed an information content index. Based on the views of information efficiency and noise trading theory, we analyzed the impact of the corporate innovation behavior descriptions in analyst reports on the stock price synchronicity, using the degree of information asymmetry as the moderating factor, and the heterogeneous beliefs of investors and noise trading as the mediating factors. Our empirical research results are as follows: (1) the corporate innovation behavior descriptions in analyst reports can inhibit the stock price synchronicity phenomenon, which is constrained by the degree of information asymmetry; (2) the analyst descriptions of corporate innovation behavior strengthen the heterogeneous beliefs of investors, thereby inhibiting the stock price synchronization; (3) noise trading has no mediating effect between the analyst descriptions of corporate innovation behavior and stock price synchronicity. This study provides favorable evidence for the information intermediary role of analysts, and it enriches the theoretical research on stock price synchronicity. It also provides a new research perspective for the application of text analysis in the fields of finance and accounting, and it enriches the research dimensions of the textual characteristics of analyst reports.

Wei Zhang, Yu-xia Zhao, Chen-guang Li, Yan-chun Zhu, Xue-feng Li

Understanding Users’ Ask Intention on Paid Q&A Platform from the Perspective of Impression Management

Abstract

With the widespread fusion of social media and knowledge economy, paid Q&A platform has become one of the most prominent ways for people to seek knowledge online. More and more users enroll as answerers to answer questions for gaining extra money, so it is necessary for them to find out ways to attract more askers in this competitive market. When investigating influential factors on the ask intention, most previous research focuses on the objective data displayed on answerers’ accounts such as number of followers and price per question, while largely ignores the information that was voluntarily disclosed by answerers. In this regard, we draw from impression management theory to explore the role of answerers’ self-image which is built through active information disclosure in this Q&A process. We constructed a cross-sectional dataset with 9,887 answerers on Weibo Q&A platform to test hypotheses. Using zero-inflated negative binomial model, we find that the congruence between answerers’ self-image and their provided knowledge has a significant positive impact on knowledge seekers’ ask intention. Particularly, the larger the congruence between those actively disclosed text information (i.e., biography) and picture information (i.e., avatar) and provided knowledge, the higher the askers’ willingness to ask questions. Managerial implications on paid Q&A platforms are thus provided.

Peiyao Liang, Mingyue Zhang, Baojun Ma

How Do We Trust AI Service? Exploring the Trust Mechanism in AI Service

Abstract

AI services have been widely used by consumers, and trust is a key factor impact them to continuously use AI services. However, due to the intelligent feature, trust in AI service is different from other trust. So, we explore how do users trust AI services and willingly continue to use them. In this paper, we have two studies: in Study 1, we encode user comments of AI service products according to grounded theory, and identify the multilevel dimensions of AI service trust antecedent (AISTA); in Study 2, we use empirical data collected through a survey to develop and test an AI service trust mechanism model based on Study 1. The results indicate that anthropomorphism, perceived intelligence-interactivity, service adaptation and coolness influence affect-based and cognition-based trust to different degrees, thus promoting the continuous use behavior of AI services. This paper extends the research scope of trust literature and contributes to the practice of AI product design.

Ao Chen, Jinlin Wan

A Study into Sponsorship Disclosure on Video Sharing Platforms: Evidence from Bilibili

Abstract

Sponsorship disclosure is becoming increasingly important in the marketing field and its business value deserves further exploration. This paper investigates how different types of sponsorship disclosure affects consumers’ purchase intention through influencer trust in the context of video sharing platforms with evidence from Bilibili. Notably, as a distinguished feature of Bilibili, the differences between bullet screen and traditional user comments in their impacts on sponsorship disclosure and customer purchase intention are compared in terms of consumers’ interactivity with the social media influencers. Based on the knowledge persuasion model and signaling theory, the results indicate that influencer trust mediates the relationship between sponsorship disclosure and consumers’ purchase intention both for general and specific sponsorship disclosure, and interactivity positively moderates the relationship between sponsorship disclosure and consumers’ purchase intention only for general sponsorship disclosure.

Chenwei Li, Huijin Lu

How Restaurant Attributes Affect Customer Satisfaction: A Study Based on Sentiment Analysis, Neural Network Modelling and Kano Model Classification

Abstract

The study aims to understand how the various attributes of restaurant affect its customer satisfaction. Different with prior literature with heavy reliance on self-reported data, we investigated 17 representative restaurant attributes extracted from online reviews, modeled the relationship between restaurant attributes and customer satisfaction leveraging neural network, and classified the attributes into five categories based on kano model. The findings show that, among the 17 attributes, waiter’s attitude and taste of food are most important for a high customer satisfaction. This study could help restaurant allocate its resources with greater efficiency and improve customer satisfaction.

Huijin Lu, Huidan Tan, Chenwei Li, Xiaobo Xu

A Method for Recommending Resources Across Virtual Academic Communities Based on Knowledge Graph and Prompt Learning

Abstract

In the era of big data, virtual academic communities are flourishing and resources are growing explosively. As a result, heterogeneous fragmentation of resources and massive disorder have created constraining problems, which exacerbate the “knowledge island” effect among academic communities and challenge researchers to acquire knowledge effectively. To solve these problems, we propose a method for recommending resources across virtual academic communities (MRRVAC) based on knowledge graph and prompt learning. Firstly, we use the knowledge graph to link resources in different communities, which enables resources to be transferred between communities. Secondly, prompt learning is used to acquire the potential knowledge of knowledge graph. The final recommendation list of academic resources is obtained by training the prompt template with the improved P-tuning method and using it to mine the injected knowledge in the model. Finally, data experiments were conducted on the datasets of two virtual academic communities, Zhihu and ScienceNet. The results show that the average improvement over the original method in HR and NDCG is 0.296% and 0.271%, which validates the effectiveness of the method.

Zhihao Chen, Jun Yin, Shilun Ge, Nianxin Wang

How Industrial Supportive Policies Drive the Corporation Attention Shifting: A Case Study of BYD from New Energy Vehicles Industry

Abstract

Policies in emerging economies, as environmental factors, have played an important role in promoting the disruptive technology industry development such as new energy vehicle. From Attention-based view, this paper explores how industrial supportive policies drive corporation attention from policy orientation to market orientation by strategy response in a case study of BYD. This paper establishes a three-dimensional framework of “motivate-regulate-shift” and identifies the two phases of China’s NEV industrial supportive policy. Based on these, we open the black box of corporate attention shifting: Driven by the changing of policies, firms’ regulation in every aspect from strategic direction and organizational restructuring to personnel allocation, resource acquisition and allocation promotes their attention focus to market orientation, which is an inside-out and gradually permeable shifting process. Further, all these strategic responses motivated by policies promote companies’ ability to improve their innovation R&D and output results. The finding provides lessons for NEV corporations to become more policy sensitive and more innovative R&D emphasized in disruptive technologies industry.

Yankun Pan, Meilian Ye, Zhen Zhu, Shiwei Yu

Optimal Platform Intrusion and Supplier Selection Strategy Oriented by Fresh Agriculture Product Supply Chains of Different Power-Structure

Abstract

In light of the growing prevalence of online channels, e-commerce platforms have increasingly collaborated with suppliers or rural cooperatives to open self-operated stores, with the aim of maximizing profits. However, given the regional variation in supply chain dynamics, suppliers and rural cooperatives may not always occupy the same position in the supply chain, leading to simultaneous challenges of channel conflicts and power imbalances. About the channel intrusions by e-commerce platforms, this study introduces one fresh-product supply chain of one producer, one provider and one B2C e-commerce platform and studies the optimal strategy for enterprises in the fresh-product pricing and channel selection with a theoretical model construction. Results from the study show that e-commerce platforms in any model will support the weaker side in the supply chain for much more profits. At the same time, rural cooperatives and suppliers will actively cooperate with e-commerce platforms’ opening self-run stores. The theoretical value of this study lies in its insights into the optimal strategies for supply chain enterprises in the face of e-commerce platform intrusion and power-structure competition. The practical value of the research lies in its provision of guidance for e-commerce platforms to support the weaker party in the supply chain and to actively cooperate with rural cooperatives in launching self-run stores. However, further research is needed to explore optimal strategies for enterprises under different power structures and information asymmetry.

Zhenhai Tan, Chunnian Liu, Lan Yi

Investment Risk Analysis and Countermeasure in Five Central Asian Countries for Chinese Investors

Abstract

With rapid progress of the “Belt and Road” initiative, China has become a capital exporter. More and more Chinese investors are increasing their overseas investment. Thus, investment risk assessment is very important. Central Asia is a key hub connecting the Europe and China. Cooperation between Chinese and Central Asian countries have bilaterally promoted rapid economic development. For Central Asian countries, there are many investment risk points. But in a comprehensive way, the main influencing factors include economic condition, debt ability, social environment, legal system and political factor. In order to improve the investment efficiency, this paper uses analytic hierarchy process to study the investment risks of the five Central Asian countries, and puts forward some countermeasures. Generally speaking, Central Asian countries are generally suitable for overseas investment. Kazakhstan and Uzbekistan have lower risk level. Tajikistan and Turkmenistan have moderate risk level since infrastructure construction in the two countries is imperfect. The investment risk of Kirghiz Tanzania is slightly higher. In order to reduce investment risks, China should promote RMB internationalization so as to facilitate overseas trade and investment. Strengthening policy communication can consolidate and expand the positive role of multilateral trade agreements. In addition, learning from advanced international experience, China can build a financial insurance system to reduce investment risk.

Lili Ta

How Knowledge Characteristics and Platform Characteristics Drive Users’ Purchase Intention of Online Paid Health Knowledge?

Abstract

In the knowledge economy era, access to health knowledge via online health platforms has become increasingly popular. This paper aims to explore the impact of relevant characteristics on users’ intention of paying for health knowledge. Based on the perceived value theory and S-O-R model, we propose the research model consisting of knowledge characteristics and platform characteristics as stimuli, perceived value as organism, and purchase intention as response. A total of 432 valid questionnaires is collected, and analyzed using SmartPLS3.0 software. Our results show that regarding knowledge characteristics, knowledge rarity has no significant influence on perceived value, and knowledge personalization positively affects utilitarian value and hedonic value; regarding platform characteristics, both platform information quality and platform service quality positively influence utilitarian value and hedonic value; both utilitarian value and hedonic value have positive effects on purchase intention. And the partial mediation role of perceived value is tested. Research findings and implications are discussed as well.

Yuanlu Li, Jiaxin Xue, Zhaohua Deng

An Empirical Study on the Impact of Government Microblogs on Online Engagements During the Covid-19 Outbreak

Abstract

While government microblogs show increasing significance as a bridge connecting the government and the people, its role has become more prominent during the covid-19 outbreak, when the government released all kinds of official information in a timely manner and obtained public participation and feedback. Two important aspects to measure online participation are likes and comments, and the content topic of posts is an important influencing factor in online engagement studies. However, except for a few case studies, few researches have been conducted to provide an objective insight into the content topics of government blogs based on amass data in the context of the epidemic, and subsequently studies the impact of content topics on engagements. This paper analyzes the overall release pattern of government microblogs during pandemic in China by extracting 9 topics through LDA model based-on datasets from Sina Weibo. With a 5W-framework, we empirically confirm the relationship between content topics and public engagement with negative binomial analysis beyond the limitations of previous studies focusing only on some local factors. The results show that in general government releases focus mainly on the topics of epidemic science and uplifting spirits. However, information about police and public interaction and important instructions receives more discussion and likes, while news about treatment progress and praise of uplifting spirits receive little attention. Contributions to the literature and practice are discussed.

Anqi Nie, Hao Jiang, Jiayi Xu, Jing Fan

The Concept and Connotation of Enterprise Digital Transformation

Abstract

In the era of digital economy, the digital transformation of enterprises is a key strategic choice for the survival and development of enterprises. This paper gives the definition of enterprise digital transformation based on the subject, technology, scope and expected results through literature induction and comparison. This paper expounds the research status of digital transformation in the view of technological innovation and application, process, results and industrial application. The future development direction is also predicted. Digital transformation is defined as the application of digital technology by enterprises (subject) to build a digital world with full perception, full link, full scene and full intelligence (the technologies involved), and then optimize and reconstruct the business of the physical world, innovate and reshape the traditional management model, business model (scope), and finally achieve business success (expected results). Enterprise digital transformation is an inevitable product driven by internal and external factors. Relevant research on technological innovation and application mainly focuses on the cross-system transformation of enterprises. Process research focuses on transformation process and realization path, etc. Results research focuses on the impact of digital transformation on production efficiency and organizational performance, as well as possible data security problems. The industrial application perspective mainly provides practical cases and data.

Jiangping Wan, Siting Lin, Qingchen Wu

Research Hotspots and Frontier Analysis of Digital Marketing in China

Abstract

Digital marketing is the main marketing method and development trend of enterprises in the era of digital economy. The study of digital marketing is of great significance to the practice of digital economy in China. This paper takes the digital marketing papers published by CNKI database from 2012 to 2022 as the research object, analyzes the authors, publishing institutions and keywords, shows the temporal and spatial distribution characteristics and research hotspots of digital marketing research in China, and tracks the most cutting-edge research issues by the CiteSpace tool to draw a visual knowledge graph. The development momentum of digital marketing in China is good, but it needs to be strengthened the cooperative relationship between authors and institutions. The research hot topic is mainly the strategy research in different fields, which needs to be further deepened. The focus of future research is mainly on community, intelligence, diversification and virtual reality.

Jiangping Wan, Qingchen Wu, Qianling Feng

Study on Spatio-Temporal Topic-Sentiment Synergy Model and Visualization of Online Public Opinion on Public Health Emergency

Abstract

Public health emergencies can generate online public opinion on social media platforms such as Weibo. Existing studies show that both temporal and spatial factors have an impact on public opinion, topic and sentiment mining of public health emergency microblogs can realize the monitoring, prediction and guidance of public opinion considering the temporal and spatial factors. Taking the outbreak period of the Delta variant in three different regions of China in 2021 as the research object, this paper constructed a model based on the Latent Dirichlet Allocation (LDA) model, improved SnowNLP lib and sentiment map. Data processing, topic mining and sentiment calculation were carried out to realize the synergistic analysis of topic and sentiment. Results illustrate that this model can reveal the law of online public opinion evolution and sentimental intensity, that online public opinion is influenced by spatial and temporal factors, especially that small cities with smaller volume and attention need to be focused on the observation and guidance of public opinion.

Yuhan Lu, Ziming Zeng

The Impact of Blockchain on the Credit Risk of Supply Chain Finance: A Tripartite Evolutionary Game Analysis

Abstract

In light of the reality that supply chain finance is plagued by credit risk, this study constructs a tripartite evolutionary game model involving financial institution, small and medium-sized enterprise (SME), and core enterprise to analyze the credit risk in the case of accounts receivable factoring. The micro-mechanism of how blockchain mitigates the credit risk of supply chain finance is analyzed by comparing the changes in the system’s evolutionary stability strategy before and after the introduction of blockchain. Numerical simulation is also conducted to verify the system’s evolutionary stability strategy. The results reveal that whether the traditional supply chain finance business produces credit risk depends on the amount of accounts receivable, the income obtained by SME and core enterprise when maintaining the stability of the supply chain, and the default income and default cost of both. After the introduction of blockchain, a strict regulatory environment increases the default cost of enterprises in the supply chain. Therefore, the system strictly converges to the Pareto-optimal solution of financial institution accepting financing applications, core enterprise repayment, and SME compliance. In addition, the decrease in the amount of accounts receivable held by a single SME can accelerate the convergence of the tripartite evolutionary game to equilibrium after the introduction of blockchain. Thus, blockchain can effectively mitigate the credit risk that financial institutions face while conducting supply chain finance business. Our research provides theoretical support for optimizing credit risk management in supply chain finance using blockchain.

Zhichao Liu, Lubin Wang, Jiayi Gu

Backmatter