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Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

The emergence of virtual reality (VR) has the potential to revolutionize various industries, including tourism, as it delivers a simulated environment that closely emulates real-life experiences. Therefore, this study aims to explore how the factors, i.e. enjoyment, emotional involvement, flow state, perceived privacy risk, physical risk and cost, influence the customers’ intention to use VR for tourism.

This study integrates the technology acceptance model, hedonic consumption theory with other factors, including cognitive response, authenticity, perceived privacy risk, perceived physical risk, perceived cost and perceived presence. Partial least squares structural equation modelling approach was used to test the proposed research model.

The finding based on the sample of 252 respondents revealed that authenticity is the most influential factor impacting behavior intention followed by perceived cost, attitude, cognitive response and enjoyment. Also, the study supported the moderating impact of personal innovativeness between attitude and behavioral intention to use VR for tourism.

The findings of the study offers practical implications for service providers, site managers, destination marketers, tourist organizations and policymaker to develop more effective strategies for offering VR services for tourism.

This study enriches the current understanding of VR adoption in context of tourism with empirical evidences.