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Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

The aim of this study is to investigate how social media users' experience of seeking emergency information affects their engagement intention toward emergency information with a reciprocity framework integrated with information adoption model.

Drawing on reciprocity theory, indebtedness theory, and information adoption model, an integrative research model is developed. This study employs a questionnaire survey to collect data of 325 social media users in China. Structural equation modeling analyses are conducted to test the proposed theoretical model.

Social media users' experience of seeking emergency information has a strong effect on their perceived information usefulness and indebtedness, while perceived information usefulness further influences community norm, indebtedness, and engagement intention. The authors also found that perceived information usefulness mediates the relationships between experience of seeking emergency information and community norm/indebtedness.

This study offers a new perspective to explain social media users' engagement intention in the diffusion of emergency information. This study contributes to the literature by extending the theoretical framework of reciprocity and applying it to the context of emergency information diffusion. The findings of this study could benefit the practitioners who wish to leverage social media tools for emergency response purposes.

With the increasing awareness of sustainability and its importance around the world, corporate social responsibility (CSR) in Africa also requires attention. Based on the stakeholder theory, this study aims to determine the relationship between CSR information received by small and medium-sized enterprises (SMEs) and CSR's diffusion and the mediating role of environmental awareness in Angola as a country representative of the African context.

The empirical study analyzes managers' perceptions of 131 SMEs in Angola. The partial least squares structural equation modeling (PLS-SEM) is the method to assess the relationship between CSR information and its diffusion and the mediating role of environmental awareness SMEs in Angola.

The authors found strong evidence that CSR diffusion, and disclosure as one of CSR's related actions, heavily depends on the information received and managed by the firm. The authors also confirmed that environmental awareness puts pressure on SMEs to increase the SMEs' diffusion efforts.

The study points out the role of managers in promoting a responsible orientation of businesses in Angola for preserving the environment and improving the competitive success of SMEs.

The social, economic and legal contexts of Angola are vulnerable. The findings raise concerns about whether governments and regulatory efforts improve the development of the strategies toward social responsibility of African firms and whether these firms also increase the role of SMEs in producing positive outcomes through CSR.

The results of this study contribute to a better understanding of the features of the strategic orientation of SMEs in Angola, necessary to enhance CSR and protect the environment. The conclusions highlight the potential role of managers in promoting a culture of ethics, social innovation and successful competition change in businesses.

This paper aims to explore the determinants causing fake information proliferation on social media platforms and the challenges to control the diffusion of fake news phenomena.

The authors applied the systematic review methodology to conduct a synthetic analysis of 37 articles published in peer-reviewed journals retrieved from 13 scholarly databases.

The findings of the study displayed that dissatisfaction, behavior modifications, trending practices to viral fake stories, natural inclination toward negativity and political purposes were the key determinants that led individuals to believe in fake news shared on digital media. The study also identified challenges being faced by people to control the spread of fake news on social networking websites. Key challenges included individual autonomy, the fast-paced social media ecosystem, fake accounts on social media, cutting-edge technologies, disparities and lack of media literacy.

The study has theoretical contributions through valuable addition to the body of existing literature and practical implications for policymakers to construct such policies that might prove successful antidote to stop the fake news cancer spreading everywhere via digital media. The study has also offered a framework to stop the diffusion of fake news.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

The purpose of this paper is to examine the factors that influence enterprise resource planning (ERP) effectiveness within the context of emergency service organizations. Drawing on information systems (IS) effectiveness, ERP implementation and job satisfaction literature, the authors posit that user involvement, top management involvement and training satisfaction are the antecedents to perceived job satisfaction, and perceived job satisfaction leads to ERP effectiveness in emergency service organizations.

Survey methodology is used for collecting data for this research, and the PLS-SEM technique is used for analysis.

Results indicate users will be more satisfied with their training if their inputs are taken into account during their training and the top management is actively involved during the training process. Further, if the users perceive that they are adequately trained, they will be more satisfied with their jobs in using ERP, which will also lead to more effective ERP usage in emergency service operations.

The focus of this study is on a single emergency service organization and thus may not be generalizable to other sectors. The authors extend ERP research to the context of emergency service organizations and thus add to the literature on ERP and emergency services. They conceptualize perceived job satisfaction to integrate roles, teamwork, supervisor and their perception regarding their potential to grow in the organization.

The managerial contribution of this research is to identify the motivational aspects and provide practical insights into the effective use of ERP systems for emergency service organizations. From a managerial perspective, the study provides a framework for both IS and emergency service providers/executives to understand and evaluate the factors that help them use ERP effectively in their firms.

This study extends the knowledge of ERP systems. While most of the ERP research focuses on implementation, the authors’ focus is on the effective use of ERP in emergency service organizations. They focus on identifying key factors that are important to using ERP effectively, specifically in emergency service organizations.

Drawing upon social cognitive theory, this study aims to investigate the potential predictors and consequences of social media health-misinformation seeking behavior during the coronavirus (COVID-19) pandemic.

Using a sample of 230 international students studying at Wuhan University and Beijing Language and Cultural University, China, this study employs structural equation modeling to analyze the collected data.

The results indicate that personal factors such as lack of health information literacy, environmental factors, information overload and social media peer influence have a significant effect on behavior, namely social media health-misinformation seeking behavior, which further influences outcomes, namely social media users' anxiety during the COVID-19 pandemic. In addition, both lack of health information literacy and social media peer influence have significant and direct effects on social media users' anxiety. However, the direct effect of information overload on social media users' anxiety is insignificant.

First, this study contributes to the literature on the individuals' social media health-misinformation seeking behavior, its precursors and its consequences, specifically on their mental healthcare during a pandemic situation. Second, this research is one of the pioneer studies that extend social cognitive theory to the context of social media health-misinformation seeking behavior and users' anxiety relationship.

As the application of crowdsourcing contests grows, leveraging the participation of superstars (i.e. solvers who have outstanding performance records in a crowdsourcing platform) becomes an emergent approach for managers to solve crowdsourced problems. Although much is known about superstars’ performance implications, it remains unclear whether and how their participation affects the size of a contest crowd for a crowdsourcing contest. Based on social contagion theory, this paper aims to examine the impact of superstars’ participation on the crowd size and studies how this impact varies across solvers with different heterogeneity in terms of skills, exposure and cultural proximity with superstars in crowdsourcing contests.

This paper uses secondary data from one crowdsourcing platform that includes 6,587 innovation contests to examine superstars’ main and contextual effects on the crowd size of a contest.

Our results reveal that superstars’ participation positively affects the crowd size of a contest in general. This finding suggests that social contagion is a fundamental mechanism underlying crowd formation in crowdsourcing contests. Our results also indicate that in contests that involve multiple superstars, superstars’ effect on crowd size becomes negative when we simultaneously consider other solvers’ heterogeneity in terms of skills, exposure and cultural background, and this negative effect will be intensified by increases in the skill gap, extent of exposure and cultural proximity between superstars and other solvers in the same contest.

Our research enhances the understanding of the influence of superstars and the mechanism underlying the emergence of contest crowds in crowdsourcing contests and contributes knowledge to better understand social contagion in a competitive setting. The results are meaningful for sourcing managers and platform supervisors to design contests and supervise crowd size in crowdsourcing contests.