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Under the sunlight of social commerce, few concepts have blossomed like value co-creation. But when blurred strategies are implemented, the opportunity to wilt a brand is high. To avoid the miscues and the controversies, an ascendant step is to engage consumers with social commerce sites. The purpose of this paper is to propose three antecedents to engage consumers with social commerce sites, namely, social support, social commerce value and social commerce information sharing, and the effect of brand engagement on the intention of brand co-creation.

This study used survey data from 234 Iranians with experience using social commerce sites. Variance-based structural equation modeling using the partial least squares path modeling approach was adopted to analyze the structural model.

The authors found that social support, social commerce value and social commerce information sharing positively foster brand engagement. The study also revealed that brand engagement is a significant predictor of brand co-creation intention.

The study is the first study that considers and explains brand engagement from social support theory, social commerce value theory and social commerce information exchange. Also, the study shows how consumers can be an integral part of a brand. Unlike other studies which were done in industrialized countries, this study was employed in Iran.

As sharing economy has become increasingly popular, researchers from various disciplines begin to pay more attention to this important phenomenon. However, the current literature is fragmented and lacks a framework to integrate previous studies and guide future research. This study aims to systematically review the literature to better understand what one knows and what one need to know about sharing economy and provide a road map for future research in the context of sharing economy.

A systematic review was conducted with EBSCO and science direct database. In total, 91 studies were identified.

The review shows that previous studies focus on different stakeholders, including consumers, peer service providers, platform providers, and competitors. The authors further identify the main topics and limitations of the literature (integrated into a framework) and provide possible directions for future studies. For example, the authors find that few studies have examined individual and technical factors. The findings also show that consumers’ other activities and outcomes have received little attention. To address these limitations, future studies that examine how individual and technical characteristics influence sharing economy’s usage intention/behaviors are suggested. The authors also suggest future studies to explore other activities during the process of sharing economy services.

The framework and directions provided can further the sharing economy research by addressing important gaps in the current literature.

This review identifies many opportunities for researchers to better understand the phenomenon of sharing economy.

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.

Although recent years have shown increasing popularity of e-commerce worldwide, there is still a lack of studies comprehensively exploring trust issue in e-commerce. Based on trust transfer theory and signaling theory, the purpose of this paper is to present an integrated research model to test the relationships between trust dimensions and e-loyalty, interactions among trust dimensions, as well as antecedents of different trust dimensions.

Data were collected through a web-based survey in Chinese markets and structural equation modeling with partial least squares was used to analyze the data.

The results identified that three trust dimensions all have significant impacts on e-loyalty, and relationships existed in different trust dimensions. Moreover, information quality and security protection are important factors determining institutional trust while store reputation is the most salient factor determining interpersonal trust.

This research contributes to the body of knowledge on trust by exploring the nature of trust with a multidimensional scale. Another theoretical contribution is the provision of a comprehensive understanding of the trust antecedents in e-commerce. Furthermore, this research benefits the companies doing e-businesses by allowing them to better understand how to improve consumers’ trust in the online environment and thus to retain and attract more loyal customers and succeed in online businesses.

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

The purpose of this paper is to build a comprehensive structural model to demonstrate the interrelationships of factors influencing social networking service (SNS) fatigue and to identify the varying degrees of influence.

A total of 14 factors influencing SNS fatigue are identified through an extensive literature review. Interpretive structural modeling (ISM) and Matrice d'Impacts Croisés Multiplication Appliqué à un Classement (MICMAC) analysis are employed to build a hierarchical model and classify these factors into four clusters.

The results revealed that ubiquitous connectivity and immediacy of feedback are key factors contributing to SNS fatigue through their strong influence on other factors. Privacy concern, impression management concern and work–life conflict lead directly to SNS fatigue. In contrast, system feature overload and system pace of change are relatively insignificant in generating SNS fatigue.

This study represents an initial step toward comprehensively understanding the interrelationships among the factors leading to SNS fatigue and reveals how determinants of SNS fatigue are hierarchically organized, thus extending existing research on SNS fatigue. It also provides logical consistency in the ISM-based model for SNS fatigue by grouping identified factors into dependent and independent categories. Moreover, it extends the applicability of the integration of the ISM and MICMAC approaches to the phenomenon of SNS fatigue.

Despite the various benefits of social networking services (SNSs), users have begun to experience fatigue in recent years, as evidenced by a decline in active user numbers. This relatively new phenomenon has only recently received significant managerial and academic attention. The antecedents of SNS fatigue are still unclear in the literature. The purpose of this paper is to identify the key factors causing SNS fatigue, based on a socio-technical approach.

The authors empirically tested this research model with 424 SNS users via an online survey. Structural equation modeling with partial least squares was used to analyze the data.

The results showed that the social factors of social comparison, social interaction overload, social surveillance and social information overload, and the technical factor of system complexity are significantly related to SNS fatigue.

This research benefits SNS providers by allowing them to better understand how to effectively design social networking platforms to retain and attract more users. It also benefits users by providing guidance on how to actively manage their own behavior to avoid potential negative outcomes induced by SNS usage.

This study focuses on the “dark side” of SNS from the perspective of fatigue, extending existing research on technostress. It also extends the applicability of the socio-technical approach to the phenomenon of SNS fatigue. Moreover, it enriches SNS fatigue research by addressing the importance of both social and technical factors in causing SNS fatigue.

The purpose of this paper is to explore in depth how Web 2.0 (focusing on social media) contributes to create a better communication channel to provide information, support and assistance to patients. Social relationships of individuals on the Internet through social media have created added value for many industries. This phenomenon can be an opportunity for the health care industry, which has encountered huge challenges such as increasing demands, budget cuts, growing numbers of patients and more demanding patient expectations. Web 2.0 and social media have the potential value to make possible an increase in the productivity of modern health care and a reduction in cost to the central government. Social media introduces better channels of communication with patients to increase the value of e-health. Social media are building more social communities that empower patients to share their personalized health information and treatments.

Grounded on social support and transaction cost theories, this paper evaluates the current potential of social media to discuss values it can offer for the overall benefit of the health care industry.

The results show how the social relationship of individuals provides online social support and reduction of cost through social media, leading to the development of modern health care. Implications and limitations are discussed at the end of the paper.

The analysis results indicated that social media provides strong social support for patients who seek help online. Informational support and emotional support have been confirmed as two main dimensions of social support in online health care. It makes a contribution to the health care literature by extending it to online health care support in the context of social media. It may inform and provide some initial understanding to guide future research. In addition, this study indicates that social support theory and transaction cost are appropriate theoretical foundations for studies of online health care. This finding is very valuable, as it helps researchers to advance the understanding of how social media support online health care.

The emergence of Web 2.0 opened a new route for education to use the values derived from this development. The future of e-learning is social learning, where individuals can learn online due to the facility of social media. Social media such as online communities are places for social interactions between users. These social interactions are the way forward and can drive social support in an online context. This paper aims to explore the impact of these interactions

This study uses social support theory to explore the impact of social interactions on the internet on learning and education. The research uses a case study and investigates the health industry.

The paper explains the development in e-learning through social media and the emerging concept of social learning.

The contribution of this research is to emphasise social relationships of individuals in the internet and social interaction in online communities which enhance their learning qualities. The research drawn on social support theory describes social learning as a future for e-learning.