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Active participation is critical to the survival and development of the multiplayer online battle arena (MOBA) game community. However, this issue has not received much attention in the information systems literature. To address this issue, we develop a tripartite model that accounts for the roles of behavioral dedication, constraint, obligation mechanisms on active participation in the MOBA community.

The research model is empirically validated by online survey data among 971 users of a popular MOBA community.

The results show that perceived enjoyment, perceived escapism, and affective commitment are key behavioral dedication factors, which further promote active participation in the MOBA community. In addition, past investment, self-efficacy for change, and calculative commitment are important behavioral constraint factors, which ultimately influence active participation in the MOBA community. Finally, subjective norm, group norm, social identity, and normative commitment are influential behavioral obligation factors, which in turn facilitate active participation in the MOBA community.

This study contributes to the theoretical understanding of active participation in the MOBA community and offers practical guidance for promoting active participation in the community.

The advancements of mobile technologies and devices have greatly facilitated the extension of online services from web to mobile environments. Drawing on the categorization theory, the purpose of this paper is to explore the impact of perceived entitativity on users’ web-mobile service extension behavior. The research model considers how perceived entitativity serves as a category cue to link the category- and piecemeal-based processing and shape users’ adoption of extended mobile services.

An online survey (n=552) was conducted to empirically test the model. The data were analyzed by structural equation modeling approach.

The results offer two major findings. First, performance expectancy, perceived controllability and subjective norm are important antecedents of users’ usage intention. Second, perceived entitativity has three types of effects on usage intention: it exerts a direct and positive influence on usage intention; it indirectly facilitates usage intention through increasing PE and perceived controllability; and it moderates the relationship between subjective norm and usage intention.

This study contributes to the literature by taking into account the interplay of category- and piecemeal-based processing to understand consumers’ web-mobile service extension behavior.

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.

The engagement–addiction dilemma has been commonly observed in the information technology (IT) industry. However, this issue has received limited research attention in the information system (IS) discipline. Drawing on the stimulus–organism–response (SOR) framework, this study explores the engagement–addiction dilemma in the use of mobile games and highlights the impacts of game design features, namely, mobile user interface and mobile game affordance.

The research model was empirically validated using a longitudinal survey data from 410 mobile game users in China.

The empirical results offer several key findings. First, mobile user interface and mobile game affordance positively affect telepresence and social presence, which lead to meaningful engagement and mobile game addiction. Second, a high-quality of mobile user interface positively moderates the effects of mobile game affordance on telepresence and social presence.

This study contributes to the literature by theorizing and empirically testing the impacts of game design features on the engagement-addiction dilemma.

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.

A wealth of studies have identified numerous antecedents to online self-disclosure. However, the number of competing theoretical perspectives and inconsistent findings have hampered efforts to obtain a clear understanding of what truly influences online self-disclosure. To address this gap, this study draws on the antecedent-privacy concern-outcome (APCO) framework in a one-stage meta-analytical structural equation modeling (one-stage MASEM) study to test a nomological online self-disclosure model that assesses the factors affecting online self-disclosure.

Using the one-stage MASEM technique, this study conducts a meta-analysis of online self-disclosure literature that comprises 130 independent samples extracted from 110 articles reported by 53,024 individuals.

The results reveal that trust, privacy concern, privacy risk and privacy benefit are the important antecedents of online self-disclosure. Privacy concern can be influenced by general privacy concern, privacy experience and privacy control. Furthermore, moderator analysis indicates that technology type has moderating effects on the links between online self-disclosure and some of its drivers.

First, with the guidance of the APCO framework, this study provides a comprehensive framework that connects the most relevant antecedents underlying online self-disclosure using one-stage MASEM. Second, this study identifies the contextual factors that influence the effectiveness of the antecedents of online self-disclosure.

Crowdsourcing platforms have emerged as an innovative way to generate ideas and solving problems. However, promoting sustained participation among crowdworkers is an ongoing challenge for most crowdsourcing platform providers. Drawing on self-determination theory, this study investigates the impacts of job autonomy on crowdworkers' sustained participation intention.

A survey of 212 crowdworkers from a leading crowdsourcing platform in China was conducted to empirically validate the model.

The empirical results lead to several key findings. First, the taxonomy of job autonomy in crowdsourcing contains three archetypes: work-scheduling autonomy, work-task autonomy, and work-method autonomy. Second, work-scheduling autonomy and work-method autonomy have more significant positive effects on temporal value than work-task autonomy, and this increase in temporal value increases crowdworkers' sustained participation intention. Third, work-task autonomy exerts a stronger influence on hedonic value than work-scheduling autonomy or work-method autonomy, and this increase in hedonic value also increases crowdworkers' sustained participation intention.

This study extends the crowdsourcing literature by examining the formation of crowdworkers' sustained participation and highlighting the role of differential effects of multidimensional job autonomy on crowdworkers' sustained participation. We believe that this study provides actionable insights into measures that promote crowdworkers' sustained participation in the crowdsourcing platform.

Crowdworkers' sustained participation is critical to the success and sustainability of the online crowdsourcing community. However, this issue has not received adequate attention in the information systems research community. This study seeks to understand the formation of crowdworker sustained participation in the online crowdsourcing community.

The research model was empirically tested using online survey data from 212 crowdworkers in a leading online crowdsourcing community in China.

The empirical results provide several key findings. First, there are two different types of sustained participation: continuous participation intention (CPI) and increased participation intention (IPI). Second, extrinsic motivation and intrinsic motivation positively influence crowdworker CPI and IPI. Third, community commitment negatively moderates the effects of extrinsic motivation on CPI and IPI, while it positively moderates the effects of intrinsic motivation on CPI and IPI.

This study has significant implications for research on online crowdsourcing community and provides practical guidance for formulating persuasive measures to promote crowdworker sustained participation in the community.

Drawing from the spillover effect literature, the purpose of this paper is to investigate the spillover effect in consumers’ web-mobile payment extension behavior. The authors figure out two categories of factors associated with the spillover effect: relevant schema and schematic fit. Cognitive trust and emotional trust in web payment are used to capture relevant schema, while perceived similarity and perceived business tie are proposed to denote schematic fit in the web-mobile payment extension context.

An online survey (n =552) was conducted to empirically test the model. The data were analyzed by structural equation modeling approach.

The results show that relevant schema and schematic fit factors positively influence perceived value of mobile payment (MP), which facilitates consumers’ behavioral intention of MP.

This study contributes to the extant literature by theoretically identifying the key factors of the spillover effect and empirically investigating its role during the web-mobile service extension process.

Building upon uncertainty reduction theory, this work aims to explore how four uncertainty reduction factors (i.e. online property review, online textual description, online visual description and online instant messenger) mitigate property quality uncertainty and property fit uncertainty, which further influence Airbnb use intention.

This work tests the proposed research model using a structural equation modeling approach with 335 Airbnb users.

The findings reveal that the online property review, online textual description, online visual description and online instant messenger can efficiently mitigate property quality uncertainty and property fit uncertainty, which ultimately influence Airbnb use intention.

This study provides useful insights on mitigating property uncertainty in the peer-to-peer (P2P) accommodation platforms. Researchers are encouraged to investigate the boundary conditions that influence the effectiveness of uncertainty reduction strategies in alleviating property uncertainty.

P2P accommodation service providers are suggested to take actionable uncertainty reduction strategies to mitigate property uncertainty in online P2P accommodation platforms.

First, this study advances research on P2P accommodation by identifying two key types of property uncertainty, namely, property quality uncertainty and property fit uncertainty. Second, this study extends research on P2P accommodation by proposing contextualized passive, active and interactive uncertainty reduction strategies in mitigating property uncertainty. Third, this study extends uncertainty reduction theory to the P2P accommodation context. Fourth, this study enriches uncertainty reduction theory by verifying the mediating effects of property quality uncertainty and property fit uncertainty.