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Despite the extensive adoption of radio-frequency identification (RFID) technology across many industry supply chains, the extent of adoption in healthcare is far behind the earlier expectation. The purpose of this study is to better understand the current RFID adoption in healthcare by looking beyond the existing body of work using both the task-technology fit (TTF) framework and network externalities theories.

A survey is employed in this study, and the structural equation modeling (SEM) technique is used to test the hypotheses of the proposed model.

The findings are twofold. First, both TTF and network externalities exert a positive impact on the RFID adoption in the healthcare sector; and second, no synergistic effect can be found between these two for further increasing the adoption. This is different from what the extant research found on other technology adoptions across various supply chains.

This paper provides contributions to both researchers and practitioners. For researchers, this study enriches the body of knowledge of RFID adoption by being the first to apply the network externalities and TTF theories to predict the adoption of RFID in healthcare. For healthcare practitioners, to make the RFID adoption easier and more effective, any initial applications of RFID tools should be centered on those for which there is a more natural application. Further, for those who propose an RFID adoption should start with a product that has a sizable adoption community; this may help persuade senior management to make the adoption decision.

The purpose of this paper is to identify the factors that influence people to play socially interactive games on mobile devices. Based on network externalities and theory of uses and gratifications (U&G), it seeks to provide direction for further academic research on this timely topic.

Based on 237 valid responses collected from online questionnaires, structural equation modeling technology was employed to examine the research model.

The results reveal that both network externalities and individual gratifications significantly influence the intention to play social games on mobile devices. Time flexibility, however, which is one of the mobile device features, appears to contribute relatively little to the intention to play mobile social games.

This research successfully applies a combination of network externalities theory and U&G theory to investigate the antecedents of players’ intentions to play mobile social games. This study is able to provide a better understanding of how two dimensions – perceived number of users/peers and individual gratification – influence mobile game playing, an insight that has not been examined previously in the mobile apps literature.

While the sizable body of research focusses on various psychological effects of enterprise social media (ESM), research connecting the link between ESM and cyberslacking is still very sparse. Drawing inspiration from the social bonding theory, the authors have proposed a moderated mediation model to explain how ESM affordances reduce cyberslacking, mediated significantly by workplace social bonding when the perceived co-worker involvement is high.

Utilising a sample of 384 respondents, the study tested the model fit and hypothesised relationships with AMOS and PROCESS MACRO.

The findings show that workplace social bonding mediates the relationship between ESM affordances and cyberslacking. The results are also consistent with the moderated mediation model as the mediation is significant when the perceived co-worker involvement is high, and the mediation is insignificant when the moderator is low/moderate.

Considering the potential behavioural dynamics of ESM artefacts, the authors have introduced self-expression (via microblogging), recognition (from paralinguistic digital affordances) and network externality as ESM affordances. Alongside the existing measures to reduce employee deviance, the proposed model with the above-mentioned affordances can be investigated in detail by the future research community.

In light of the findings, the study demonstrates that ESM can be treated as a mechanism to keep cyberslacking at bay. The results offer significant implications for managers, who lookout for innovative and soft strategies to reduce cyberslacking in the workplace.

Instead of implementing strict policies to kerb cyberslacking, this study proposes an alternative and an interesting model by introducing ESM as a strategic tool in reducing cyberslacking. The paper argues that ESM, being a potential tool for employee engagement and bonding, may offset the employees' tendency to involve in cyberslacking.

This paper aims to identify the effects of social learning and network externalities by conditioning on product quality and early sales momentum. This approach is demonstrated using film sales data.

This study used econometric modeling approach.

It was found that both social learning and network externalities have significant and comparable impacts on film choice. We show that the relative effects of network externalities and social learning in the film market are robust to different momentum and quality definitions and to alternative estimation methods.

Scholars have long argued that social learning plays a key role in new product diffusion. In some product categories, consumer choice may also be influenced by network externalities, meaning that purchasing popular products may provide the consumer utility above and beyond that derived from product usage directly. We propose a novel identification approach to help quantify the relative magnitude of these two effects on new product sales.

The purpose of this study is to propose a synthetic post-adoption model based on the expectation-confirmation model (ECM) and flow theory to examine whether the fit factor, network factors and psychological factors as antecedents to end-users’ beliefs can affect their continuance intention of the robo-advisor.

This study used the research model based on ECM and flow theory to examine the effects of the fit factor, network factors and psychological factors on end-users’ beliefs and continuance intention of the robo-advisor. Sample data were collected from end-users at three financial services companies in Taiwan. A total of 450 questionnaires were distributed and 360 (80.0%) usable questionnaires were analyzed using structural equation modeling.

This study proposes a solid research model that based on ECM and flow theory, three types of factors, namely, fit factor, network factors and psychological factors, as antecedents to end-users’ continuance intention of the robo-advisor have been examined and this study’s results strongly support the research model with all hypothesized links being significant.

It is particularly worth mentioning that a synthetic post-adoption model can be proposed in this study by introducing the fit factor extracted from task-technology fit model, network factors originated from the theory of network externalities and psychological factors derived from uses and gratifications theory as antecedents to perceived usefulness, confirmation, satisfaction and continuance intention referred in ECM and flow experience derived from flow theory. Thus, this study’s research model and findings can reveal deep insights into the evaluation of determinants in the field of end-users’ continuance intention of the robo-advisor.

Lead users are essential participants in crowdsourcing innovation events; their continuance intention significantly affects the success of the crowdsourcing innovation community (CIC). Although researchers have acknowledged the influences of network externalities on users' sustained participation in general information systems, limited work has been conducted to probe these relationships in the CIC context; particularly, the predictors of lead users' continued usage intention in such context are still unclear. Hence, this paper aims to explore the precursors of lead users' continuance intention from a network externalities perspective in CIC.

This work ranked users' leading-edge status to recognize lead users in the CIC. And then, the authors proposed a research model based on the network externalities theory, which was examined utilizing the partial least squares (PLS) technique. The research data were collected from an online survey of lead users (n = 229) of a CIC hosted by a China handset manufacturer.

Results revealed that the number of peers, perceived complementarity and perceived compatibility significantly influence lead users' continuance intention through identification and perceived usefulness.

This work contributes to the crowdsourcing innovation research and provides views regarding how lead users' sustained participation can be developed in the CICs. This work also offers an alternative theoretical framework for further research on users' continued intention in open innovation activities.

The purpose of this paper is to explore the determinants of continuance intention of social networking site (SNS) users through a new perspective and discuss how to retain SNS users.

The author proposed a research model by integrating network externalities and social support. Three dimensions of social support and two types of network externalities were analyzed, respectively, to explore the direct and indirect effects on continuance intention. Online questionnaires were adopted to collect data, and 513 valid samples were analyzed by structural equation modeling approach.

The findings show that network externalities have a significant indirect effect on user’ continuance intention through the mediation effects of social support, and among the three dimensions of social support, network management plays a more important role on continuance intention.

The findings suggest that network externalities can trigger the function of social support to keep the “stickiness” of SNS users, and network management is the key dimension of online social support. Some other theoretical and practical implications are also provided.

The study is novel in exploring users’ continuance intention of SNSs by integrating social support and network externalities. Meanwhile, the author also intends to compare the effect of different dimensions of social support on SNS usage and discuss their internal relationships.

This study's purpose is to propose an integrated post-adoption model based on expectation-confirmation model (ECM) and cognitive absorption (CA) theory to examine whether network factors, gamification factor, and quality factors as antecedents to end-users' beliefs can affect their continuance intention of the robo-advisor.

A total of 600 questionnaires were distributed in three sample banks in Taiwan, and sample data for this study were collected from these three banks' customers who had experience in using these banks' own robo-advisor to make their investment decisions. Consequently, 381 useable questionnaires were analyzed using structural equation modeling in this study, with a useable response rate of 63.5%.

This study proposes a solid research model that based on ECM and CA theory, three types of factors, network factors, gamification factor, and quality factors, as antecedents to end-users’ continuance intention of the robo-advisor have been examined, and this study's results strongly support the research model with all hypothesized links being significant.

This study contributes to end-users' continuance intention of the robo-advisor based on ECM, CA theory, theory of network externalities, gamification, and updated DeLone and McLean IS success model, and reveals deep insights into the evaluation of determinants in the field of end-users' continuance intention of the robo-advisor. Hence, it is especially worth mentioning that three types of determinants (i.e. network factors, gamification factor, and quality factors) are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into account in this study's research model development of end-users' continuance intention of the robo-advisor to acquire a more all-round and robust analysis.

Massively multiplayer online role-playing games (MMORPGs) create quasi-real social systems in which players can interact with one another, and quasi-real economic systems where players can consume and trade in-game items with virtual currency. The in-game currency price, an important indicator of a virtual economy, is highly contingent on players’ behavioral interaction in MMORPGs. The purpose of this paper is to adopt a network perspective to examine how topological characteristics of social networks in an MMORPG, namely, network externalities, density, and closure, would exert impacts on the in-game currency price.

Players’ behavioral data were collected from a popular MMORPG in China on a weekly basis for 52 weeks. With a time series analytical approach, the empirical model for the price function of in-game currency was estimated with vector autoregression.

The results show that the number of core avatars and network density are positively associated with in-game currency price, while network closure has a negative effect on in-game currency price. However, in-game currency price is found to have no significant relationship with the trade volume of the currency.

This study fills in an important research gap by investigating factors influencing the in-game currency price of MMORPGs from a network perspective, which contributes to the existing literature of network effects and advances our understanding about how players’ interaction will influence the dynamics of a virtual economy. The findings could offer useful insights for online game companies to better understand their players’ social interaction and consumption behavior.

The purpose of the studies was to test if extent of prior social media activity could predict likelihood that a consumer would post reviews on a new review website.

Two online surveys were conducted presenting scenarios in which users were asked about prior social media activity, the number of social networks they belonged to in study one, and how actively they had posted reviews in study two. These questions were followed by descriptions of new review websites, a general local merchant review website in study one and a local restaurant review website in study two.

Although demographics did a poor job of predicting who would post reviews on the new review websites, prior active social media use and review posting did modestly predict intention to post reviews on the new review websites.

This is not an experimental study and so causality cannot be claimed. Descriptively, although the results were consistent in two studies using different stimuli, other factors might prove to be better predictors of active user‐generated content for other types of sites.

The findings suggest a simple and effective way for two‐sided platform managers to identify potential active reviewers so that they can target them through marketing strategies to encourage their essential participation and less‐active users can be similarly targeted to encourage modest use.

No other studies can be found that focus on this aspect of managing two‐sided platforms. The results might be important for managers of other similar websites that depend on user‐generated content for their value.