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Drawing on the social learning theory, the purpose of this paper is to examine the antecedents and consequences of users’ excessive online social gaming. Specifically, the authors develop a model to propose that observational learning and reinforcement learning mechanisms together determine excessive online social gaming, which further foster adverse consequences.

The model is empirically validated by a longitudinal survey among users of a popular online social game: Arena of Valor. The empirical data are analyzed using component-based structural equation modeling approach.

The empirical results offer two key findings. First, excessive online social gaming is determined by observational learning factors, i.e. social frequency and social norm, and reinforcement learning factors, i.e. perceived enjoyment and perceived escapism. Second, excessive online social gaming leads to three categories of adverse consequences: technology-family conflict, technology-work conflict and technology-person conflict. Meanwhile, technology-family conflict and technology-work conflict further foster technology-person conflict.

This study contributes to the literature by developing a nomological framework of excessive online social gaming and by extending the social learning theory to excessive technology use.

In light of the recent increase in the scholarly attention given to meaningful engagement with gamified information systems (IS), this research explores the definition and measurement of meaningful engagement as well as its role in predicting employees’ knowledge contributions via gamified knowledge management systems (KMSs).

The authors conducted two empirical studies. Study 1 develops a measure of meaningful engagement and evaluates its validity and reliability. Drawing on the literature on user engagement and work gamification theory, Study 2 places meaningful engagement in a nomological network and assesses the construct’s utility for predicting the quantity and quality of knowledge contributions via a gamified KMS.

The results show that meaningful engagement encompasses five specific dimensions: intense involvement, sense of meaning, self-discovery, pursuit of excellence, and personal expressiveness. The results also indicate that fostering meaningful engagement, which goes beyond hedonic and instrumental engagement, is essential to enhance the quality and quantity of knowledge contribution.

This research contributes to the literature on gamification by drawing scholarly attention to meaningful engagement as a parsimonious yet powerful construct that complements the notions of hedonic and instrumental engagement with KMSs. Although previous studies have highlighted the significance of meaningful engagement with gamified IS, little effort has been made to develop a scale to measure meaningful engagement. The scale the authors have developed will help researchers precisely measure users’ meaningful engagement and systematically examine its role in gamified systems compared to that of other forms of engagement. The study also has practical implications, as the results can inform future design strategies to enable the successful implementation of gamified KMSs that facilitate knowledge contribution in the workplace.

The development of new constructs is the starting point for theoretical development. This research responds to the call to conceptualize meaningful engagement with gamified IS.

Drawing on the control agency theory and the network effect theory, the purpose of this paper is to examine the effect of privacy assurance approaches, network externality and technology complementarity on consumers’ self-disclosure in mobile payment (MP) applications. The authors identify four types of privacy assurance approaches: perceived effectiveness of privacy setting, perceived effectiveness of privacy policy, perceived effectiveness of industry self-regulation and perceived effectiveness of government legislation. The research model considers how these privacy assurance approaches influence privacy concerns and consumers’ self-disclosure in MP applications under boundary conditions of network externality and technology complementarity.

An online survey with 647 sample users was conducted to empirically validate the model. The target respondents were current consumers of a popular MP application. The empirical data were analyzed by a structural equation modeling approach.

The empirical results reveal several major findings. First, privacy assurance approaches can effectively decrease privacy concerns, which ultimately formulates consumers’ self-disclosure in MP applications. Second, network externality and technology complementarity weaken the effect of perceived effectiveness of privacy setting on privacy concerns. Third, network externality and technology complementarity strengthen the relationship between perceived effectiveness of government legislation and privacy concerns, while they have non-significant interaction effect with perceived effectiveness of privacy policy and industry self-regulation on privacy concerns.

MP providers and stakeholders can harness the efficacy of privacy assurance approaches in alleviating privacy concerns and promoting consumers’ self-disclosure in MP applications.

The authors’ work contributes to the information privacy literature by identifying effective privacy assurance approaches in promoting consumers’ self-disclosure in MP applications, and by highlighting boundary conditions of these privacy assurance approaches.

As digital spaces for team collaboration, virtual worlds bring considerable verisimilitude to technology-mediated social interaction and change the process of traditional team learning. The purpose of this study is to understand how to promote collaborative learning in virtual worlds by leveraging the power of we-intention to participate in virtual worlds. The authors further use the valence–instrumentality–self-efficacy–trust model (VIST) model as a means of understanding the formation of we-intention to participate in virtual worlds, during which behavioral desire serves a bridging role.

The authors tested the research model using the data gathered from 298 users of a prominent form of virtual world, i.e. massively multiplayer online role-playing games. The authors used the structural equation modeling approach and the partial least squares technique for data analysis.

Results show that the four factors of the VIST model (i.e. valence on team goals, instrumentality of contribution, self-efficacy in team tasks and trust in team members) all positively influence we-intention to participate in virtual worlds through behavioral desire for team actions. We-intention to participate in virtual worlds further exerts a stronger positive effect on collaborative learning in virtual worlds, compared with I-intention to participate in virtual worlds.

This work advances the information systems literature by introducing a relevant and important concept, i.e. we-intention, to explain collaborative learning in virtual worlds. This study especially compared the effect of we-intention and I-intention on collaborative learning in virtual worlds. The results of this work also provide practitioners with insights into the role of we-intention in promoting collective actions in virtual worlds.

Online disinhibition is one of the key factors leading to the occurrence of cyberaggression, cyberbullying and various forms of deviant behaviors in the online environment. To understand the composition of online disinhibition, this study aims to conceptualize online disinhibition and develop a measurement instrument for online disinhibition.

We followed a rigorous procedure to develop and validate the multidimensional instrument of online disinhibition in three phases: item generation, measurement development and instrument testing.

We developed a 23-item online disinhibition scale and identified six key dimensions: dissociative anonymity, invisibility, asynchronicity, solipsistic introjections, dissociative imagination and minimization of authority.

The online disinhibition instrument is an accessible and easily administered measure that can be used as a checklist for systems designers and administrators to evaluate the level of online disinhibition among users. It offers systems design information on how to prevent and combat online deviant behaviors on platforms.

This work provides a rich conceptualization of an online disinhibition instrument that can serve as a springboard for future work to understand online deviant behaviors. The newly developed measurement instrument of online disinhibition also adds to the repository of rigorous research scales in this area.

Existing research has long considered e-loyalty as a key to the success of online shopping. The purpose of this paper is to advance the theoretical understanding of e-loyalty by exploring the roles of coupon proneness and value consciousness in the context of online shopping platforms.

The authors empirically tested the research model using a sample of 537 users of an online shopping platform in a longitudinal setting.

The results provided support to all the hypotheses in the research model; particularly, the authors found that coupon proneness and value consciousness play important roles in explaining e-loyalty. They both exhibited significant moderating effects on the relationship between loyalty intentions and repurchase behaviors. The impact of trust on loyalty intentions was also examined.

The authors believe that this study will shed light for practitioners and enable researchers to deepen their understanding of e-loyalty in online shopping platforms.

The research better explains the gap between two important price-tactics-related variables (including coupon proneness and value consciousness); and further examines their roles in determining customers’ repurchase behaviors in the context of online shopping, which is not well examined in previous studies.

Digital technologies have diffused into many personal life domains. This has created many new phenomena that require systematic theorizing, testing and understanding. Such phenomena have been studied under the Digitization of the Individual (DOTI) umbrella and have been discussed in the DOTI pre-International Conference on Information Systems workshop for the last three years (from 2015 to 2017). While prior years have focused on a variety of issues, this year (2018) we decided to put special emphasis on negative effects of the DOTI, i.e., “the dark side” of the DOTI.

This manuscript reports on a panel of three experts (in alphabetical order: John D’Arcy, Hamed Qahri-Saremi and Monideepa Tarafdar) who presented their past research in this domain, as well as their outlook for future research and methodologies in research on the DOTI.

The authors introduce the topic, chronicle the responses of the panelists to the questions the authors posed, and summarize and discuss their response, such that readers can develop a good idea regarding next steps in research on the dark side of the DOTI.

The authors introduce the topic of the dark sides of DOTI and point readers to promising research directions and methodologies for further exploring this relatively uncharted field of research.

This paper reports the panel discussion on the topic of artificial intelligence (AI) and robots in our lives. This discussion was held at the Digitization of the Individual (DOTI) workshop at the International Conference on Information Systems in 2019. Three scholars (in alphabetical order: Ting-Peng Liang, Lionel Robert and Suprateek Sarker) who have done AI- and robot-related research (to varying degrees) were invited to participate in the panel discussion. The panel was moderated by Manuel Trenz.

This paper introduces the topic, chronicles the responses of the three panelists to the questions the workshop chairs posed and summarizes their responses, such that readers can have an overview of research on AI and robots in individuals' lives and insights about future research directions.

The panelists discussed four questions with regard to their research experiences on AI- and robot-related topics. They expressed their viewpoints on the underlying nature, potential and effects of AI in work and personal life domains. They also commented on the ethical dilemmas for research and practice and provided their outlook for future research in these emerging fields.

This paper aggregates the panelists' viewpoints, as expressed at the DOTI workshop. Crucial ethical and theoretical issues related to AI and robots in both work and personal life domains are addressed. Promising research directions to these cutting-edge research fields are also proposed.

The purpose of this paper is to explore the concept of user engagement in the context of online brand communities. A research model is proposed to explain how brand loyalty is developed through user engagement.

The research model was empirically tested with an online survey study of 185 current Facebook users.

Results revealed that user engagement influenced brand loyalty both directly and indirectly through online community commitment. Users tend to focus on the benefits (rather than the costs) derived from the usage when they engage in an online brand community.

The selection of respondents is bound to the Hong Kong area, while Facebook members are globally distributed. In addition, this study involved a cross-sectional design instead of investigating the development of brand loyalty from a long-term perspective.

The results inform e-marketers the importance of user engagement behaviors for building brand loyalty through online communities. Strategies that encourage members to engage in online brand communities on social networking sites such as Facebook are also provided.

The concept of user engagement in online brand communities is still poorly understood, underscoring the need for theoretically based research of user engagement. This paper enriches the knowledge in the area of brand engagement by presenting a research model that introduces the concept of user engagement in social media research and empirically examines its role in building brand loyalty in online brand communities.

The purpose of this paper is to examine the factors associated with user satisfaction in the social network sites (SNSs), and to explore the moderating effects of gender on user satisfaction.

A research model was built upon the expectation disconfirmation model (EDM) with a focus on SNSs specific motivations (i.e. relationship maintenance and entertainment). The model was tested empirically with 221 experienced Facebook users using an online survey.

The research model explained 40.5 percent of the variance in user satisfaction. In addition, the results showed that entertainment plays a more important role in determining user satisfaction with SNSs for male users, while relationship maintenance is more important in determining user satisfaction with SNSs for female users.

The current study enriched the theoretical understanding of user satisfaction in the context of SNSs. Particularly, perceptions and disconfirmations about the use of SNSs were identified and empirically tested. Furthermore, gender differences in terms of SNSs usage were empirically demonstrated.

The present study is one of the first few studies that attempts to explain user satisfaction with SNSs as well as examine the role of gender with a theoretical foundation. It complements the empirical research in the IS literature that addresses new social communication technologies.