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Security education, training and awareness (SETA) programs are the key to addressing “people problems” in information systems (IS) security. Contrary to studies using conventional methods, the present study leveraged an “event” lens and dimensionalized employees' perceptions into three sub-dimensions: perceived novelty, perceived disruption and perceived criticality. Moreover, this research went a step further by examining how pedagogical and communication approaches to a SETA program affect employees' perceptions of the program. This study then investigated whether – and if so, how – these approaches impact employees' perceptions of the SETA program and their subsequent commitment to it.

Utilizing a factorial-based scenario survey, this study empirically tested a model of the above relationships via covariance-based structural equation modeling.

The results of this research showed that pedagogical approaches were more effective than communication approaches and that employees' perceptions of the SETA program accounted for a large variance in their commitment to SETA.

First, this research deepens understanding of the protection of information assets by elaborating on the different approaches that organizations can take to encourage employees' commitment to SETA. Second, the study enriches the SETA literature by theorizing a SETA program as an organizational “event”, which represents a major shift from the conventional approach. Third, the study adds to the theoretical knowledge of the event lens by extending it to the SETA context and investigating the relationship among three event strength components.

Artificial intelligence (AI) applications pose a potential threat to users' data security and privacy due to their high data-dependence nature. This paper aims to investigate an understudied issue in the literature, namely, how users perceive the threat of and decide to use a threatening AI application. In particular, it examines the influencing factors and the mechanisms that affect an individual’s behavioral intention to use facial recognition, a threatening AI.

The authors develop a research model with trust as the key mediating variable by integrating technology threat avoidance theory, the theory of planned behavior and contextual factors related to facial recognition. Then, it is tested through a sequential mixed-methods investigation, including a qualitative study (for model development) of online comments from various platforms and a quantitative study (for model validation) using field survey data.

Perceived threat (triggered by perceived susceptibility and severity) and perceived avoidability (promoted by perceived effectiveness, perceived cost and self-efficacy) have negative and positive relationships, respectively, with an individual’s attitude toward facial recognition applications; these relationships are partially mediated by trust. In addition, perceived avoidability is positively related to perceived behavioral control, which along with attitude and subjective norm is positively related to individuals' intentions to use facial recognition applications.

This paper is among the first to examine the factors that affect the acceptance of threatening AI applications and how. The research findings extend the current literature by providing rich and novel insights into the important roles of perceived threat, perceived avoidability, and trust in affecting an individual’s attitude and intention regarding using threatening AI applications.

Very little or no study has explored the predictors of behaviour and traits that determine digital entrepreneurship (DE) success. In response, the purpose of this paper is to present a research model that takes information technology (IT) culture as a theoretical lens and personal innovativeness and experience in IT projects as theoretical constructs to predict behaviour and traits that explain DE success.

Based on the literature review, the authors propose hypotheses and a research model. The authors tested the model using structural equation modelling (SEM), by surveying a sample of digital entrepreneurs operating in the Yabacon Valley, Lagos, Nigeria.

The results indicate that IT culture is an essential predictor of achieving DE success. The results also suggest that an entrepreneur's innovativeness in IT and experience in IT projects have significant negative and positive moderating effects on the relationship between IT culture and achieving DE success.

This paper taps into a new setting – DE context – by exploring the moderation effects of an entrepreneur's innovativeness in IT and experience in IT projects on the link between their IT culture and achieving a successful DE outcome.

This model offers managers an understanding of how IT culture and personal innovativeness and experience in IT work together to achieve DE success. Meanwhile, it sheds some light on managers to treat individuals with different levels of experience differently.

The authors theorise IT culture, personal innovativeness and experience in IT and show their effects on DE success, thus making an essential contribution to the information systems (ISs) and entrepreneurship research and practice. Moreover, the authors provide a novel methodology to conceptualise IT culture as a second-order hierarchical reflective construct by giving evidence that partial least squares (PLS) path modelling can assess a hierarchical model with moderating effects. This study answers scholars' call to construct more accurate explanations of innovation outcomes in an increasingly digital world.

The purpose of this paper is to investigate why users are willing to diffuse healthcare knowledge in social media by drawing on the communicative ecology theory (CET) and prior research on interpersonal communication.

This paper conducts a large-scale scenario-based online survey in WeChat (the most popular social media platform in China) to test the proposed research model and hypotheses. The final data set consists of 1,039 useful responses from WeChat users.

The results indicate that interestingness, emotionality and institution-based trust are the strongest antecedents in predicting healthcare knowledge-diffusing likelihood, followed by usefulness, source credibility and positivity. Further, the relationship between institution-based trust and healthcare knowledge-diffusing likelihood is partially mediated by source credibility.

Healthcare practitioners who seek to motivate individuals to disseminate healthcare knowledge need to phrase or frame healthcare knowledge in a way that draws greater interest, evokes stronger emotion, increases perceived usefulness or reflects positively on themselves. Healthcare organizations should also pay attention to strengthening users’ trust in the platform and source-related information that can indicate source authority.

This study is one of the first to investigate the dissemination of healthcare knowledge in the context of social media (WeChat in particular). Compared with other types of information, healthcare knowledge is more scientific and professional to the extent that most laypersons do not have relevant expertise to directly evaluate whether the content is credible and of high quality. Rather, their sharing likelihood is dependent more on other factors than perceived information quality and credibility; those factors include platform-related factors that may play an important role but has been overlooked in prior literature on interpersonal communication. By combining CET with interpersonal communication-related research and including institution-based trust as an important determinant of healthcare knowledge dissemination, this study provides a comprehensive analysis of healthcare knowledge diffusion process.

As a sociotechnical system, the metaverse has sparked heated discussion. However, concerns abound that the concept is “old wine in a new bottle” used for capital hype. The mixed definitions of the metaverse and unclear relationships between its technical features and user behaviors have greatly impeded its design and application. Therefore, the authors aim to sort out the metaverse definition and properties, analyze its technical features in various contexts and unveil the mechanisms leading to user behaviors.

The authors conduct a literature review on the definition, technical features and user behaviors of/in the metaverse.

First, the authors identify two main categories of the metaverse definition and find a mixed conceptualization. Second, the authors present technologies and technical features in the diverse contexts of the metaverse. Third, the authors summarize the effect of technical features on user behaviors from a sociotechnical perspective.

The authors analyze the definition, technical features, user behaviors of the metaverse and their theoretical foundations. Based on these findings, the authors propose a theoretical framework unveiling how social and technical elements affect user behaviors in the metaverse. In conclusion, the study offers a research agenda for future studies.

With the rapid development of paid online social question and answer (Q&A) communities, monetary social functions have been introduced and have potential benefits for both platforms and users. However, these functions' impact on knowledge contribution remains uncertain. This study proposes a conceptual model based on the stimulus–organism–response framework, according to which monetary and non-monetary social functions can help nurture short-term and long-term relationships among community users, and thereafter improves social identity and knowledge-sharing intentions.

This study selects Zhihu, a famous online social Q&A community in China, and conducts an online survey to collect data from its frequent users. A sample of 286 valid questionnaires was collected to test our research model by using a structural equation modeling method. In addition, a bootstrapping approach is used to test the mediation effect.

Results indicate that monetary social functions help nurture short-term and long-term relationships among community users. However, non-monetary social functions only affect short-term relationships directly. Short-term and long-term relationships both have a positive relationship with social identity and thereafter improve users' knowledge-sharing intentions.

This study focuses on users' knowledge-sharing intentions in Q&A communities from the perspective of social. Specifically, we separated social functions in Q&A platforms into monetary and non-monetary ones and explored their impact on the development of short-term and long-term relationships. Results demonstrate the importance of monetary social functions and explain how monetary and non-monetary social functions affect users' knowledge-sharing intentions in different approaches.

The purpose of this study is to investigate the relationship between social media and sensing capability for supply chain management (SCM) from an environmental scanning perspective. The authors consider upstream supply and downstream customer markets as two aspects of social media-enabled environmental scanning (SMES). The moderating effects of three uncertainties are explored.

The data were collected from 178 supply chain professionals through a survey. Generalized estimating equations (GEE) were used to analyze the data.

SMES in both supply and customer markets enhance sensing capability. Interestingly, the results reveal an accelerating effect on sensing by the incremental effort of SMES-supply. However, that of SMES-customer leads to a decelerating outcome for sensing. Also, uncertainties, especially the demand- and technology-related, play a series of interacting effects according to SMES levels.

This research contributes to the literature of operations and supply chains regarding social media strategies and dynamic capabilities. It opens the black box of environmental scanning behavior on social media and adds new knowledge on the dynamic influence of such behavior toward organizational sensing capability for SCM. In addition, further understanding on supply chain uncertainty as a moderator is also strengthened through this research.

This research is the first to empirically uncover the effect of social media on sensing capability for SCM through the lens of environmental scanning. The results support the employment of social networking for improving supply and demand sensing.

The WeChat mini-program is a new channel for the delivery of online and mobile services, including electronic government services. Given the distinguishing characteristics and new business model of WeChat mini-programs, additional studies of mini-program-based government services are warranted. The purpose of this paper is to identify the factors that determine user adoption and usage of government WeChat mini-programs (GWMPs).

An empirical study was conducted through an online survey of Chinese GWMPs users. The proposed model was tested by analyzing the collected data using the covariance-based structural equation modeling approach.

The findings show that trust in government, trust in WeChat, trust in GWMPs and perceived convenience have significant effects on the usage of GWMPs.

This study contributes to the understanding of the GWMPs and mini-program-based government phenomenon. Theoretical implications for future e-government research as well as practical suggestions for GWMPs operators are also discussed.

This study aimed to explore consumers' continuance intention to use a fitness and health app by applying two theoretical models: the expectation–confirmation model (ECM) and the investment model (IM).

An online survey was administered to consumers who are currently using fitness and health apps (N = 342). Structural equation modeling (SEM) was conducted using Amos 22.0 software to examine the hypothesized relationships in the research model.

Results revealed that users' continuance intention was significantly predicted by the two models. Within the ECM, the positive and significant relationships among variables were found. Moreover, users' satisfaction and investment size had positive impacts on their commitment, which, in turn, positively affected the intention. Also, confirmation of expectations had a positive impact on investment size.

The integrated model helps better understand fitness and health app users' decision-making process from the perspective of relationship commitment and suggests practical implications for health and fitness app providers.