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Urban villages are prevalent informal settlements within Chinese cities, arising from urban expansion. These areas frequently face systematic demolition during urban renewal due to their disorderly layout and outdated appearance. Urban village renovation (UVR) entails balancing diverse interests and navigating complex conflicts, particularly within China’s dual property rights system encompassing urban and rural land. The purpose of this study is to avoid the fierce interest conflict of UVR.

This study utilized the theoretical framework of value co-destruction. Initially, text mining and literature analysis were employed to identify concept nodes and interaction relationships. Subsequently, the structural equation model (SEM) was used to verify the causal model. Finally, the fuzzy cognitive map (FCM) was developed to dynamically simulate value co-destruction scenarios within UVR across various hypothetical situations.

The concept nodes influencing value co-destruction in UVR form a complex system with multiple levels. This includes three cause nodes and one result node. Among these, actor-to-actor emerges as a primary and underlying cause influencing value co-destruction in these projects. Furthermore, strategies for UVR should prioritize integrated interventions that enhance actor-to-actor relationships.

This study introduced a novel mixed methodology aimed at systematically simulating the dynamic process of value co-destruction during UVR. It also provided a fresh perspective on reverse assessment to mitigate the prevalent interest conflicts in UVR, thereby contributing to theoretical advancements and practical strategies for UVR.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

In online purchase for dietary supplements, due to the lack of professional advice from pharmacists, electronic word-of-mouth (eWOM) has become an important source of information for consumers to make purchase decisions. How can firms use eWOM resources to increase sales? The purpose of this paper is to provide practical methods for firms by exploring the effects of eWOM on sales and developing a sales prediction model based on eWOM.

The data came from 120 dietary supplements on Tmall.com. The authors extracted the product sales as dependent variable and 11 eWOM factors as independent variables. The multicollinearity was tested by using variance inflation factor and least absolute shrinkage and selection operator. The multiple linear regression was used to investigate the effects of eWOM on sales. Drawing on white- and black-box approaches, six models were developed. Comparing the root mean square error, the authors selected the optimal one as their target sales prediction model.

Product ratings, total reviews and favorites are positively and strongly associated with sales. Questions and additional reviews have negative effects on sales. The random forest model has the best prediction performance.

The research focuses on eWOM of dietary supplement. First, the authors show that easily accessible eWOM from online platforms can be used to evaluate effects and predict sales. Second, the authors introduce white- and black-box models through machine learning to assess eWOM. Firms could use the described models to foster their marketing initiatives.

Sharing co-owned information on social network platforms has become a common and inevitable phenomenon. However, due to the uniqueness of co-owned information, the privacy calculus theory based on a single information owner cannot explain co-owned information disclosure. Therefore, this study tries to investigate the underlying mechanism of users’ co-owned information disclosure from a collective privacy calculus perspective.

Through a survey of 740 participants, covariance-based structural equation modeling (CB-SEM) was used to verify the proposed model and hypotheses.

The results show that personal benefit, others’ benefit and relationship benefit promote users’ co-owned information disclosure by positively affecting personal distributive fairness and others’ distributive fairness perception. Meanwhile, personal privacy risk and others’ privacy risk prevent users’ co-owned information disclosure by negatively affecting personal distributive fairness and others’ distributive fairness perception. Besides, others’ information ownership perception enhances the positive effect of others’ distributive fairness perception on co-owned information disclosure intention. Furthermore, others’ information ownership strengthens the mediating role of others’ distributive fairness.

The findings of this study enrich the research scope of information disclosure and privacy calculus theory and help social network platform developers design collective privacy protection functions.

This study develops a collective privacy calculus model to understand users’ co-owned information disclosure on social network platforms, confirming the mediating role of collective distributive fairness and the moderating role of others’ information ownership perception in the process of collective privacy calculus.

This study examines the functions of informal communication in organizations. Informal communication can be characterized as any interaction within an organization in which two or more individuals assume personal roles rather than their professional roles and in which employees do not intend to solve work-related problems. Despite its central role in organizations, a comprehensive understanding of the specific functions of informal communication within workplace dynamics is lacking.

We reviewed existing literature to identify the functions of informal communication and then surveyed employees (N = 1,380). We asked them to indicate their agreement with statements measuring the functions of informal communication that we derived from the literature.

Using exploratory factor analysis, we identified four core functions: stress management and recreation, nurturing private relationships, fostering a sense of belonging and connectedness and facilitating information exchange and coordination. We then examined how these core functions related to job-related and sociodemographic characteristics. Our findings underscore the importance of informal communication in organizations, particularly in facilitating the development and maintenance of social relationships as well as information exchange and coordination, both of which play critical roles in organizational success.

This study is among the first to systematize the functions of informal communication in organizations and to empirically extract core functions that can be used for further research. It is also highly relevant to practitioners of organizational management and organizational communication.

Live streaming commerce has emerged as an essential strategy for vendors to effectively promote their products due to its unique content presentation and real-time interaction. This study aims to investigate the influence of viewer-streamer interaction and viewer-viewer interaction on consumer trust and the subsequent impact of trust on consumers' purchase intention within the live streaming commerce context.

A survey questionnaire was conducted to collect data, and 403 experienced live streaming users in China were recruited. Covariance-based structural equation modeling (CB-SEM) was used for data analysis.

The results indicated that viewer-streamer interaction factors (i.e., personalization and responsiveness) and viewer-viewer interaction factors (i.e., co-viewer involvement and bullet-screen mutuality) significantly influence trust in streamers and co-viewers. Additionally, drawing on trust transfer theory, trust in streamers and co-viewers positively influences trust in products, while trust in co-viewers also positively influences both trust in streamers and products. Furthermore, all three forms of trust positively impact consumers' purchase intentions.

This study enriches the extant literature by investigating interaction-based trust-building mechanisms and uncovering the transfer relationships among three trust targets (streamers, co-viewers and products). Furthermore, this study provides some practical guidelines to the streamers and practitioners for promoting consumers’ trust and purchase intention in live streaming commerce.

As a high-reward strategy to differentiate social platforms, value co-creation is increasingly becoming a tool to enhance customers' social attachment. However, there is still a lack of academic understanding of the value co-creation that enables users to build social attachment with social platforms. To address this challenge, we develop and then examine a theoretical model grounded in value co-creation theory considering the relationship between value co-creation and social attachment, and also explore the mediating effect of user experience and the moderating effect of self-disclosure.

This study takes representative social platform users as the research object, chooses Questionnaire Star as the platform for questionnaire distribution and collection and collects 531 eligible data through the snowball sampling questionnaire method. And then, MPLUS7.4 is used to analyze the data and thus examine our proposed theoretical model.

The results of structural equation modeling analysis suggest that two dimensions of value co-creation (i.e. initiated value co-creation and spontaneous value co-creation) affect social attachment not only directly but also indirectly (i.e. the mediating role of user experience) and that self-disclosure moderates the impact of value co-creation affecting social attachment.

This study verifies the impact of different dimensions of value co-creation toward social platforms on social attachment, showing that value co-creation plays an important role in developing users' social attachment and provides practical implications for promoting the sustainable development of social platforms and building users' psychological well-being.

Free knowledge sharing in the online health community has been widely documented. However, whether free knowledge sharing can help physicians accumulate popularity and further the accumulated popularity can help physicians attract patients remain unclear. To unveil these gaps, this study aims to examine how physicians' popularity are affected by their free knowledge sharing, how the relationship between free knowledge sharing and popularity is moderated by professional capital, and how the popularity finally impacts patients' attraction.

The authors collect a panel dataset from Hepatitis B within an online health community platform with 10,888 observations from April 2020 to August 2020. The authors develop a model that integrates free knowledge sharing, popularity, professional capital, and patients' attraction. The hierarchical regression model is used to for examining the impact of free knowledge sharing on physicians' popularity and further investigating the impact of popularity on patients' attraction.

The authors find that the quantity of articles acted as the heuristic cue and the quality of articles acted as the systematic cue have positive effect on physicians' popularity, and this effect is strengthened by physicians' professional capital. Furthermore, physicians' popularity positively influences their patients' attraction.

This study reveals the aggregation of physicians' popularity and patients' attraction within online health communities and provides practical implications for managers in online health communities.

The purpose of this paper is to emphasize the needs to understand the barrier and determinant factors in knowledge sharing (KS), to find the common ones and subsequently to build a general framework that can be referred to in designing a KS tool that addresses the common factors.

The approach comprises of two major steps which are to survey the past literature to determine the most common barriers and determinant factors from various unique KS domains and to qualify the factor as the common one based on its presence in at least three to five KS domains. The grounded theory is used to analyze the past literature and to perform categorization.

This paper helps in the summarization of categories and subcategories of barriers and determinants and demonstration on the mapping between them.

This paper has not proved the actual use of the framework in building a KS tool based on the framework.

The common factors are based on at least 60 references of KS implementation such that it is useful for large area of application domains that require building KS tools.

This paper presents the understanding on the common factors and association between the barriers and determinants in building the general framework in which the application of the framework is demonstrated using actor network theory.