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Online health communities (OHCs) are platforms that help health consumers to communicate with each other and obtain social support for better healthcare outcomes. However, it is usually difficult for community members to efficiently find appropriate peers for social support exchange due to the tremendous volume of users and their generated content. Most of the existing user recommendation systems fail to effectively utilize the rich social information in social media, which can lead to unsatisfactory recommendation performance. The purpose of this study is to propose a novel user recommendation method for OHCs to fill this research gap.

This study proposed a user recommendation method that utilized the adapted matrix factorization (MF) model. The implicit user behavior networks and the user influence relationship (UIR) network were constructed using the various social information found in OHCs, including user-generated content (UGC), user profiles and user interaction records. An experiment was conducted to evaluate the effectiveness of the proposed approach based on a dataset collected from a famous online health community.

The experimental results demonstrated that the proposed method outperformed all baseline models in user recommendation using the collected dataset. The incorporation of social information from OHCs can significantly improve the performance of the proposed recommender system.

This study can help users build valuable social connections efficiently, enhance communication among community members, and potentially contribute to the sustainable prosperity of OHCs.

This study introduces the construction of the UIR network in OHCs by integrating various social information. The conventional MF model is adapted by integrating the constructed UIR network for user recommendation.

The aim of this study was to investigate the impact of the transactive memory system (TMS) on green innovation and examine the mediation role of the social network at all hierarchical levels.

Three hypotheses were examined by performing regression analyses on survey data from manufacturing firms in China. Especially, the nested sets of data from 389 individual observations nested in 53 work teams, including individual level and collective level have been investigated.

The study results show that the TMS has a positive effect on green innovation. Furthermore, the results indicate that at the team level, structure holes' mediation in this relationship is stronger than degree centrality; at the individual level, weak ties mediation in the relationship of specialization and green innovation is stronger than strong ties, conversely, strong ties mediation in the relationship of credibility and green innovation is stronger than weak ties.

This study expands previous research by highlighting the significance of multilevel social network elements in the context of the TMS and sustainable development and enriches the present research on green innovation.

The purpose of this paper is to investigate users' knowledge and use of social networking sites and folksonomies to discover if social tagging and folksonomies, within the area of independent music, aid in its information retrieval and discovery. The sites examined in this project are MySpace, Lastfm, Pandora and Allmusic. In addition, the ways in which independent record labels utilise social networking sites for promotion are investigated.

Three groups of participants were surveyed using questionnaires. These groups were music concert attendees, people who responded to online postings to social networking sites, and independent record companies. In addition interviews were held with digital music experts.

The results suggest that respondents use social networking sites for music discovery but are not generally aware of folksonomic approaches to music discovery. When users do use and contribute to the folksonomy, most respondents were found to tag for personal retrieval purposes rather than attempting to aid the retrieval purposes of the population of site users as a whole. The four record labels unanimously agreed that social networking sites are having a major impact on independent music discovery. Digital distribution has a major impact on independent record labels. It facilitates discovery but at the same time digital distribution creates new promotional dilemmas.

The project is small scale but the research area is a relatively novel one, and the results are interesting enough to share more generally in the hope that this project will stimulate further research activity in this area.

Maturana and Varela (1980, p. 78f) provided the following definition of autopoiesis: “An autopoietic machine is a machine organized (defined as a unity) as a network of processes of production (transformation and destruction) of components that produces the components which: (i) through their interactions and transformations continuously regenerate and realize the network of processes (relations) that produced them and (ii) constitute it (the machine) as a concrete unity in the space in which they (the components) exist by specifying the topological domain of its realization as such a network.” This definition shows that for Maturana and Varela, autopoietic systems are systems that define, maintain, and reproduce themselves. The notion of machine that they employ in the definition might seem a bit misleading because we tend to think of machines as mechanistic and nonliving, but Maturana and Varela (e.g., 1987) in later publications have preferred to speak of autopoietic organizations.

As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge management of distributed agile team (DAT). This study aims to explore the comprehensive antecedents of TMS establishment in DATs and considers how TMS establishment is affected by herding behavior under the artificial intelligence (AI)-related knowledge work environment that emerges with technology penetration.

The data derived from 177 students of 52 DATs in a well-known Chinese business school, which were divided into 26 traditional knowledge work groups and 26 AI-related task groups to conduct a random comparative experiment. The ordinary least squares method was used to analyze the conceptual model and ANOVA was used to examine the differences in herding behavior between the control groups (traditional knowledge work DATs) and treatment groups (DATs engaged in AI-related knowledge work).

The results showed that knowledge diversity, professional knowledge, self-efficacy and social system use had significantly positive effects on the establishment of TMS. Interestingly, the authors also find that herding behavior may promote the process of establishing TMS of the new team, and this effect will be more significant when AI tasks are involved in team knowledge work.

By exploring the comprehensive antecedents of the establishment of TMS, this study provided a theoretical basis for knowledge management of DATs, especially in AI knowledge work teams. From a practical perspective, when the DAT is involved in AI-related knowledge works, managers should appropriately guide the convergence of employees’ behaviors and use the herding effects to accelerate the establishment of TMS, which will improve team knowledge sharing and innovation.

Although there are a number of studies on the factors affecting the continuance usage intention for social network services (SNS), the studies on the integrated model encompassing SNS qualities (information, system, and service quality, and hedonic value, which are gratifications for SNS usage), flow, relationship quality (which are trust and satisfaction), and continuance intention are almost non-existent. Based on Bagozzi’s self-regulation framework, the IS success model, uses and gratification theory, and flow theory, the purpose of this paper is to examine the qualities and hedonic value of SNS, which have an influence on flow experience and relationship quality which are posited to affect the continuance usage intention.

This study used an e-mail survey method to collect 460 questionnaires for the final sample. The sample of the study includes college students or job workers who have experience in using SNS. Various user categories in terms of gender, school degree, occupation, usage years, and daily time of usage were included.

The study results show that system, service quality, and hedonic value have an impact on flow experience, information and service quality, and hedonic value influence the relationship quality of SNS. The flow experience and relationship quality while using SNS affect the continuance usage intention of SNS. This results show that the consideration of various SNS qualities, hedonic value, flow experience, and relationship quality is necessary to actively explore the factors for continuance usage intention for SNS.

IS managers trying to understand reuse intent can use surveys on information, system, and service quality, and hedonic value. Practitioners should constantly incorporate and develop various activities or useful applications to allow people to reach out to each other, to reinforce users’ attention, interaction, and increase social connections, trust, satisfaction, and further intensify users’ intention to use, increasing SNS value. The findings explain a mechanism through which SNS users’ continuance intention is built. Understanding this mechanism provides valuable information for practitioners to understand the qualities driving SNS users’ intention to revisit SNS.

This study sheds light on the existing literature on website usage that focuses on the design qualities as this paper has combined website quality perspective, i.e., information, system, and service quality, and hedonic value, and the flow and relationship perspective to investigate how these constructs would affect users’ intention to continuously use SNS. On the basis of four theories, Bagozzi’s self-regulation framework, IS success model, users and gratification theory, and flow theory, this study extended the previous studies on SNS by adding information, system, and service quality, hedonic value, flow and relationship quality as second-order constructs affecting continuance intention.

The purpose of this paper is to investigate enterprise social media systems and quantified gender and status influences on emotional content presented in these systems.

Internal social media messages were collected from a global software company running an enterprise social media system. An indirect observatory test using Berlo’s “source–message–channel–receiver” model served as a framework to evaluate sender, message, channel and receiver for each text. These texts were categorized by gender and status using text analytics with SAP SA to produce sentiment indications.

Results reveal women use positive language 2.1 times more than men. Senior managers express positive language 1.7 times more than non-managers, and feeling rules affect all genders and statuses, but not necessarily as predicted by theory. Other findings show that public messages contained less emotional content, and women expressed more positivity to lower status colleagues. Men expressed more positivity to those in higher positions. Many gender and status stereotypes found in face-to-face studies are also present in digital enterprise social networks.

Limitations include generalizability: all data were collected from a single enterprise social media system.

Managers establishing codes of conduct for social media use will find this research useful, particularly when promoting awareness of emotional expressiveness in online venues with subordinate colleagues.

This study offers a behavioral measurement approach free from validity issues found in self-reported surveys, direct observations and interviews. The collected data offered new perspectives on existing social theories within a new environment of computerized, enterprise social media.

In a competitive business environment, organizations must leverage their resources efficiently in order to provide system‐wide solutions and maintain the standards all customers expect. To do so, the resources must be integrated; however, the integration of information and resources within organizations has thus far not produced satisfactory results. In contrast, it has been found that efficient, ongoing and timely transfer of information is conducted over the internet. This research seeks to examine whether the use of internet technology within organizations can indeed enhance and streamline the ability of employees to function as fractals in complex organizations.

The research is a qualitative study, allowing for the examination of behavior in the organizational reality as is, by analyzing interviews and observations of over 60 employees in different organizations.

It is found that the ability of a digital social network to create immediate system‐wide solutions, together with a management approach that transforms the organization into a complex adaptive system, allows employees to behave as fractals – i.e. to share applied‐knowledge, to take responsibility for performance and management of the processes, to update their superiors, and to develop self‐management abilities at the local level.

Social networks in organizations should be viewed as a shared “knowledge” system. Use of the network is “natural” and less rational and synchronized up front. However, it must be backed by a relevant management culture that enables all employees to serve as fractals in a complex adaptive system. In this manner, employees can contribute personally to work processes, determine their needs, and receive credit.

The purpose of this paper is to focus on understanding how social influence and personality of individuals differentiate between users’ social network fatigue and discontinuance behavior. Furthermore, the most common discontinuance behavior among users was investigated.

The research model was tested with the data from 163 Instagram users based on online and offline surveys. The partial least squares method was used to test the proposed hypotheses of this study.

The results indicate that social influence affects users’ discontinuance behavior and social network fatigue. Social network fatigue is greater in users with higher reported social influence compared to those with a lower one. Moreover, in response to social network fatigue, users prefer to keep their activities under control instead of switching to alternative social network sites (SNSs) or a short break in social network activities.

By achieving a better understanding of users’ feeling and behaviors, social network providers may codify their strategies more efficiently.

The study is novel in exploring users’ SNS fatigue and their discontinuance behavior by integrating social influence and personality. The authors defined a new concept of effect of social influence on social network fatigue. Additionally, the authors examined which discontinuance behaviors in individuals were more prevalent.

Crowdsourcing food delivery represents great potential for future development and expansion of the restaurant business. Accordingly, job performance and retention of delivery workers are critical for success. Therefore, this paper aims to investigate how to enhance crowdsourced delivery workers’ job performance and intent to continue working by applying the sociotechnical systems theory.

The data analysis was conducted using responses obtained from crowdsourced food delivery workers. A structural equation model was developed to verify the hypothesized relationships. To test the proposed moderating roles of a three-dimensional concept of social capital within the research model, multi-group analyses were implemented.

This study confirmed the significant relationships between crowdsourcing risks related to workers’ low job commitment and technical systems, attributing to reduced job performance and intent to continue working. Results documented that social systems including networks, trust and shared vision mitigated the negative impact of the perceived difficulty and complexity of technical systems and job performance.

Although technology has contributed significantly to the effectiveness of online food delivery, the literature has mainly focused on its benefits and has ignored the critical aspects derived from a virtual and technology-based workplace. This gap was addressed by verifying the important roles of social factors (networks, trust and shared visions) in reducing the negative impacts of technology-driven risks (perceived difficulty of task requirements and technology complexity) within the crowdsourcing food delivery context.