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Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

This study aims to investigate the effect of social influence and value-driven mobile marketing activities on consumers’ acceptance of mobile marketing offers.

The method used is survey questionnaire. A proposed model was tested by using structural model analysis and data gathered from 356 Mexico consumers and 346 US consumers.

The study shows the number of peers and providing information are the main predictor variables of consumer acceptance of mobile marketing offers in both countries. These results suggest that social value factors are important variables for explaining consumers’ responses to mobile marketing offers across two countries characterized by dissimilar macro-environmental conditions.

The study’s overall implication about standardization vs adaptation is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. One limitation in this study is the use of a convenience sample of undergraduate college students. This study did not control for different types of mobile phones and the screen sizes of mobile phones.

The overall implication of standardization vs adaptation from the study results is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries.

Unlike previous studies where the emphasis is to explicate the effect of value-oriented mobile activity, this study examines the combined effect of social influence and value-driven mobile activities on acceptance of mobile marketing.

By building and examining an integral model, the principal objectives of this research are to systematically explore how indirect and direct network externalities lead to user loyalty toward WeChat through the mediating effect of perceived gratifications.

The data were collected through an online survey of 688 young people in Mainland China. To empirically assess the conceptual model, zero-order correlation analyses and structural equation modeling were carried out utilizing web-based data.

Path analysis results demonstrate that indirect network externalities and direct network externalities exert a significant impact on users' hedonic gratifications and utilitarian gratifications. Moreover, the study discovers the significant mediating influences of utilitarian gratifications on the association between indirect network externalities and user loyalty.

Theoretically, this article may extend the scope of diverse studies on the association between network externalities and perceived gratifications and offer fresh insights into how mobile social media could actually improve user loyalty through enhancing perceived values among younger generation. Practically, this research assists mobile social media practitioners in retaining users and gaining competitive advantages over rival applications.

Although the extraordinary growth of WeChat has successfully become the dominant media by which individuals develop interpersonal network and contact with others, the roles of perceived gratifications between network externalities and user loyalty toward WeChat have not yet been investigated in depth. These obtained outcomes not only enrich the existing literature regarding the relationship between network externalities and affective response, but also offer fresh insights to mobile social media designers, marketers and users.

This study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.

This study proposed and validated a stickiness formation model following the cognitive–affective–conative framework. Data were collected from surveys of 1,240 mobile app users and analyzed using structural equation modeling. Multigroup analysis was applied to contrast the stickiness formation process among apps of different social levels.

This study revealed a causal link between cognitive, affective and conative factors. It found partial mediation effects of trust in the association between perceptions and satisfaction, and the full mediation role of satisfaction and personal investment (PI) in the effects of subjective norm (SN) on stickiness. The multigroup analysis results suggested that social media affordances benefit stickiness through increased PI and strengthened effects of SN on PI. However, it damages stickiness through increased perceived privacy risk (PPR), decreased trust and strengthened effects of PPR on trust.

This study contributes to both stickiness scholars and practitioners, as it builds a model to understand the stickiness formation process and reveals the effects of the “go social” strategy. The novelty of this study is that it examined social influences, considered privacy issues and revealed two mediation mechanisms. The findings can guide the improvement of mobile app stickiness and the application of the “go social” strategy.

The unstoppable and exponential growth of social media use has given rise to concerns about the consequent effects on users. Among the major concerns are the psychological consequences, which have received considerable academic attention. The current mixed-methods research aims to examine women's social media use and its effects on their psychological well-being in a patriarchal culture, namely Pakistan.

This study employs a mixed-method research methodology. The quantitative section collected data from 240 women and used structural equation modelling to test the proposed hypotheses. Thematic analysis was used to analyse the in-depth interviews with ten women.

The integration of the findings revealed increased use of social media by women and its beneficial effects (communication and socialisation, escapism and self-presentation), though qualitative findings revealed the cultural implications and obstacles that women face (online anonymity and digital asylum). The study calls attention to women's social media usage patterns and the resulting effects on women's psychological well-being in a low-income country with a patriarchal social structure.

Most research remains limited to Western societies and young populations. The situation is somewhat different in developing economies with traditionally preserved cultures compared to Western societies. This study uniquely examines the influence of social media on psychological well-being in a developing country with a special cultural context.

This study aims to investigate the potential impact and passenger perceptions of integrating multimedia books within airline services, aiming to elucidate the evolving landscape of in-flight entertainment and reading experiences.

A quantitative research methodology was used, using a structured questionnaire distributed to presenters at the International Federation of Library Associations.

Analysis revealed varying passenger interest in multimedia books, with approximately 57.7% displaying engagement, while 40.4% demonstrated limited interest or none. However, a notable majority (60.6%) preferred multimedia books over traditional print books during flights. Furthermore, 90.4% perceived a positive impact of multimedia books on flight reading experiences, leading to increased satisfaction (81.7%) and a high likelihood of recommending airlines offering such content (91.3%).

The study's limitations include a specific focus on International Federation of Library Associations and Institutions (IFLA) World Library and Information Congress (WLIC) presenters, potentially limiting broader generalisations. Further research might explore the preferences of a wider demographic range and incorporate qualitative aspects to deepen understanding. Airlines could leverage multimedia books to enhance passenger satisfaction, attract diverse audiences and foster cultural inclusivity within in-flight entertainment.

This study contributes insights into the evolving landscape of in-flight entertainment, emphasising the significant potential and positive impact of integrating multimedia books within airline services. It underscores the importance of catering to diverse passenger preferences and enhancing overall satisfaction during air travel.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

In light of the stimulus-organism-response (SOR) theoretical paradigm, this paper explores how information relevance and media richness affect social network exhaustion and, moreover, how social network exhaustion ultimately leads to health anxiety and COVID-19-related stress.

The conceptual model is explicitly analyzed and estimated by using data from 309 individuals of different ages in mainland China. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were utilized to validate the proposed hypotheses through the use of online data.

The findings suggest that information relevance is negatively associated with social network exhaustion. In addition, social network exhaustion is a significant predictor of health anxiety and stress. Furthermore, information relevance and media richness can indirectly influence health anxiety and stress through the mediating effect of social network exhaustion.

Theoretically, this paper verifies the causes and consequences of social network exhaustion during COVID-19, thus making a significant contribution to the theoretical construction and refinement of this emerging research area. Practically, the conceptual research model in this paper may provide inspiration for more investigators and scholars who are inclined to further explore the different dimensions of social network exhaustion by utilizing other variables.

Although social network exhaustion and its adverse consequences have become prevalent, relatively few empirical studies have addressed the deleterious effects of social network exhaustion on mobile social media users’ psychosocial well-being and mental health during the prolonged COVID-19. These findings have important theoretical and practical implications for the rational development and construction of mobile social technologies to cultivate proper health awareness and mindset during the ongoing worldwide COVID-19 epidemic.

While travelling, tourists like to use mobile technology to share their travel experiences. This study aims to understand how the social value gained by tourists from sharing a travel experience with mobile technology affects their satisfaction with the travel experience through onsite mobile sharing behaviour.

A second-order hierarchical model is constructed to examine the moderated mediating role of onsite mobile sharing behaviour in improving tourists’ travel satisfaction. Through systematic sampling, 304 responses were collected at ten attraction points in Guangzhou and Shenzhen, China.

The results show that, compared with self-centred values (self-presentation and self-identification), other-centred values (building social connection and reciprocity) contribute more to forming social values of sharing. In addition, onsite mobile sharing behaviour partially mediates and moderates the effect of social values on travel satisfaction.

This study applies the social capital theory to identify the value gained by sharing travel experiences and empirically evaluates the impact of these values on the overall value of sharing travel experiences. This study also contributes to tourism research by examining the moderated mediating role of onsite mobile sharing behaviour in improving travel satisfaction. This study helps destination marketing to make strategies to motivate tourists to use mobile technology to share their travel experiences while travelling.

We propose a machine learning based methodology to deal with data collected from a mobile application asking users their opinion regarding fashion products. Based on different machine learning techniques, the proposed approach relies on the data value chain principle to enrich data into knowledge, insights and learning experience.

Online interaction and the usage of social media have dramatically altered both consumers’ behaviors and business practices. Companies invest in social media platforms and digital marketing in order to increase their brand awareness and boost their sales. Especially for fashion retailers, understanding consumers’ behavior before launching a new collection is crucial to reduce overstock situations. In this study, we aim at providing retailers better understand consumers’ different assessments of newly introduced products.

By creating new product-related and user-related attributes, the proposed prediction model attends an average of 70.15% accuracy when evaluating the potential success of new future products during the design process of the collection. Results showed that by harnessing artificial intelligence techniques, along with social media data and mobile apps, new ways of interacting with clients and understanding their preferences are established.

From a practical point of view, the proposed approach helps businesses better target their marketing campaigns, localize their potential clients and adjust manufactured quantities.

The originality of the proposed approach lies in (1) the implementation of the data value chain principle to enhance the information of raw data collected from mobile apps and improve the prediction model performances, and (2) the combination consumer and product attributes to provide an accurate prediction of new fashion, products.