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Browsing knowledge documents in a peer-to-peer (P2P) environment is difficult because knowledge documents in such an environment are large in quantity and distributed over different peers who organize the documents according to their own views. This paper aims to propose a method for constructing a personal knowledge map for a peer to facilitate knowledge browsing and alleviate information overload in P2P environments.

The research presents a method for constructing a personal knowledge map. The method adopts an ontology-concept-tree-based classification algorithm to recognize a peer’s personal knowledge structure and construct a personal knowledge map, and uses a self-organizing map algorithm to cluster and visualize the knowledge documents. The correctness of the created knowledge map is evaluated with a collection of abstracts of academic papers.

The method for constructing a personal knowledge map is the main finding of this research. The evaluation shows that the created knowledge map is good in quality.

The proposed method provides a way for P2P platforms to understand their users’ knowledge background, as well as to improve the P2P platform environment. However, the proposed method will not help a peer when he has nothing in his individual knowledge document repository (i.e. the “cold start” problem). The method also requires a relatively good ontology base for a P2P document sharing system to use the method effectively.

It is novel that the proposed method organizes the knowledge documents related to a peer’s knowledge background into a personal knowledge map. Moreover, the created knowledge map combines the advantages of a hierarchical display and a map display. It has values for a distributed P2P environment to facilitate users’ knowledge browsing and to alleviate information overload.

Short-form video advertisements have recently gained popularity and are widely used. However, creating attractive short video advertisements remains a challenge for sellers. Based on the visual-audio perspective and signaling theory, this study investigated the impacts of three visual features (number of shots, pixel-level image complexity and vertical versus horizontal formats) and two audio features (speech rate and average spectral centroid) on user engagement behavior.

We conducted a field study on TikTok. To test our various hypotheses, we used regression analysis on 2,511 videos containing product promotion information posted by 60 sellers between January 1, 2020 and November 20, 2021.

For visual variables, the number of shots and pixel-level image complexity were found to have nonlinear (inverted U-shaped) relationships with user engagement behavior. The vertical video form was found to have a positive effect on comments and shares. In the case of audio variables, speech rate was found to have a significant positive effect on shares but not on likes and comments. The average spectral centroid was found to have significant negative influences on likes and comments.

This study provides specific suggestions for sellers who create short-form videos to improve user engagement behavior.

This study contributes to the literature on short-form video advertising by extending the potential drivers of user engagement behavior. Additionally, from a methodological perspective, it contributes to the literature by using computer vision and speech-processing techniques to analyze user behavior in a video-related context, effectively overcoming the limitations of the widely adopted survey method.

Previous studies overemphasize the negative effects of social media usage (SMU) within organizations and underestimate its positive influences on employees' behavior. This study attempts to link employees' social media use at work to their creativity performance.

Based on the bounded generalized reciprocity theory and unbounded indirect reciprocity (UIR) theory, the authors developed a research model. To test the model, the authors collected a set of 172 paired data of organizations and employees from 31 knowledge-intensive enterprises in China to test the hypothesis.

This research found that the social, cognitive and hedonic uses of social media all directly affect employee creativity. Relational energy fully mediates the effects of the cognitive and hedonic usages on creativity. Moreover, job autonomy moderates the effects of the relationships among the social, cognitive and hedonic uses on employee creativity.

The conclusions not only enriched authors’ understanding of the effectiveness of interpersonal interaction but also extended the research boundary of the relationship between SMU and employee creativity.

With the widespread collection and utilization of user data, privacy security has become a crucial factor influencing online engagement. In response to the growing concern about privacy security issues on social media, this research aims to examine the key causes of social media users' privacy calculus and how the balance between perceived privacy risks and benefits affects users' privacy concerns and their subsequent willingness to disclose personal information.

The characteristics of the privacy calculus were extracted through partially structured interviews. A research model derived from privacy calculus theory was constructed, and latent variable modeling was employed to validate the proposed hypotheses.

Information sensitivity, experiences of privacy violations, social influence and the effectiveness of privacy policies influence users' privacy calculus. Privacy risk positively influences privacy concerns. Personal information disclosure willingness is positively influenced by privacy benefits and negatively influenced by privacy concerns, with both paths moderated by social media identification.

This study explores the key antecedents of users' privacy calculus and how these factors influence privacy concerns and subsequent willingness to disclose information on social media. It offers new insights into the privacy paradox observed within social media by validating the moderating role of social media identification on users' information disclosure willingness.

Internet search is a $120bn business that answers lists of search terms or keywords with relevant links to Internet webpages. Only a few companies have sufficient scale to compete and thus economics of the process are paramount. This study aims to develop a detailed industry-specific modeling of the economics of internet search.

The current research develops a stochastic model of the process of Internet indexing, search and retrieval in order to predict expected costs and revenues of particular configurations and usages.

The models define behavior and economics of parameters that are not directly observable, where it is difficult to empirically determine the distributions and economics.

The model may be used to guide the economics of large search engine operations, including the advertising platforms that depend on them and largely fund them.

Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.

Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.

Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.

The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

This study explores whether and how Internet usage improves the subjective health of middle-aged and older adults by analyzing the mediating role of social engagement and heterogeneity of different living arrangements.

Based on data from the China Health and Retirement Longitudinal Study, the ordinary least squares (OLS) method is adopted to explore the relationship between Internet usage and the subjective health of middle-aged and older adults. Propensity score matching method (PSM) is used to alleviate self-selection bias in the samples. The bootstrap method is adopted to test the mediating role of social engagement, and generalized structural equation modeling (GSEM) is employed to resolve endogeneity. A permutation test is adopted to examine the heterogeneous effects of Internet usage on different living arrangements.

Internet access can help relieve depression among middle-aged and older adults and enhance their self-rated health, leading to perceived changes in health status. However, Internet usage is not directly associated with health satisfaction among middle-aged and older adults. Nevertheless, Internet usage can enhance middle-aged and older adults' subjective health by facilitating social engagement and significantly influences middle-aged and older adults living with their children.

This study reveals the underlying role of Internet usage among older adults and provides insights for governments and families to help middle-aged and older adults actively adapt to a digital society and improve their health.

This study argues that to drive users' continuance use behaviors, it is necessary to satisfy their desire for a meaningful experience when using information systems (IS). Therefore, this research explores the influencing mechanism by which gamified IS (immersive-related interaction, achievement-related interaction, and social-related interaction) impacts users' perceived benefits and continuance intention.

In this research, 367 users of Ant Forest are investigated in two waves through random sampling and the use of a structural equation model with SmartPLS 3.0 software.

The research results reveal the following: (1) both achievement-related interaction and social-related interaction can affect the user's continuance intention, while the direct impact of immersive-related interaction on the user's continuance intention is not supported; (2) users' perceived self-benefits fully mediate the relationships between achievement-related interaction and social-related interaction and users' continuance intention; and (3) perceived social benefits fully mediate the relationships between achievement-related interaction and social-related interaction and users' continuance intention.

This study supports the retention effects of gamification design on users' continuance intention by evocating users' dual perceived benefits.

The purpose of this paper is to investigate the impact of product description and involvement on purchase intention in a cross-border e-commerce (CBEC) setting from a psychological perspective.

This study proposes a research model of purchase intention in CBEC based on the involvement theory and commitment-involvement theory. The research model was tested using the covariance-based structural equation modeling technique. Data were collected from consumers on a popular CBEC platform in China.

A high-quality product description has no significant positive effect on purchase intention, but it has significant positive effects on product cognitive involvement, product affective involvement, platform enduring involvement and platform situational involvement. In addition, product affective involvement, platform enduring involvement and platform situational involvement all have significant positive effect on purchase intention, but this effect is not significant in the relationship between product cognitive involvement and purchase intention.

This study calls for sellers to optimize product descriptions on CBEC platforms in order to attract more buyers and generate more profits.

This study integrates two theories of involvement into the research model in the CBEC context. Based on this model, the authors analyzed how product description affects purchase intention under the joint influence of two involvement factors.

The purpose of this paper is to develop and test a model of the uncertainties and benefits influencing the repurchase intentions of buyers in cross-border e-commerce (CBEC).

The authors draw on the valence framework to hypothesize effects of positive valences (utilitarian benefits) along with negative valences (pre- and post-contractual uncertainties) on buyers’ repeat purchase intentions. Data were collected using an online survey from 378 international B2C buyers on a CBEC platform in China.

Results explain 51.4 percent of the variance and reveal that overall value, as determined by monetary saving, convenience and product offerings as positive valences, exerts the strongest effect on repeat purchase intention. However, negative valences remain significant, and are particularly salient for female shoppers.

The authors extend the valence theory into the study of repeat purchase behavior and contribute to much needed literature on why consumers return to repurchase from a CBEC platform.

Repeat purchase and loyalty of online consumers is essential for success of e-commerce providers. The results help online providers competing in international markets understand how buyers form repurchase intentions based on their evaluations of both value and uncertainty.

Buyer behavior in CBEC has received relatively less attention than domestic e-commerce. This paper is among the first to examine how both positive and negative valences combine to effect repurchase intention of international buyers in CBEC.