Search results

Considering the limited understanding of determinants influencing the adoption of smart mobile tourism app (SMTA) featuring augmented reality (AR) and big data analytics (BDA), privacy concern (PC) and the risk of privacy information disclosure (PI) have threatened SMTA adoption. This study aims to propose an expanded consumer acceptance and use of information technology (UTAUT2) model by including new contextual components, integrated with privacy calculus theory (PCT) model to examine the determinants influencing behavioural intention (BI) to use SMTA.

Personal innovativeness (IN) and privacy information disclosure (PI) are incorporated in UTAUT2 model to determine its effect on SMTA featuring AR and BDA technologies from smart perspective. Both privacy concern (PC) and privacy risk (PR) derived from PCT model are also included to determine its influences on an individual's willingness to disclose privacy information for better-personalised services. We collected responses from 392 targeted participants, resulting in a strong response rate of 84.66%. These responses were analysed statistically using structural equation modeling in both SPSS 22.0 and SmartPLS 3.0.

Findings showed that personal innovativeness (IN), habit (HT) and performance expectancy (PE) significantly affect behavioural intention (BI) while privacy concern (PC) significantly affect privacy information disclosure (PI) to use SMTA. In contrast, effort expectancy (EE), hedonic motivation (HM) and privacy information disclosure (PI) had no significant effects on behavioural intention (BI) while privacy risk (PR) had no significant effects on privacy information disclosure (PI) to use SMTA.

The study findings help tourism practitioners in better comprehending recent trends of SMTA adoption for establishing targeted marketing strategies on apps to improve service quality. In addition, it enables app development companies acquire app users’ preferences to enhance their app development for leading app usage.

Past research has shown there is a relationship between body image, sexual behavior, and pleasure. However, the majority of this research has centered on heterosexual participants. In this analysis, the author considers how this relationship between body image, sexual behavior, and pleasure may look within women and genderqueer individuals who are all AFAB (assigned female at birth) with 26 out of 30 participants identifying as LGBTQIA+. The author examines perceptions of body size, body hair, and genitals to consider how intersections of social structures – specifically internalized sexism, racism, and misogyny – influence the participants’ experience of sexual interactions. Both resistance and embodiment of traditional gender norms, even as queer women and genderqueer individuals, were examined in these narratives. The majority of the moments where traditional gender norms are examined describe situations when the participants were sexually interacting with cis-gendered men.

Exploring historically significant and often eerie locations, dark tourism has surged in popularity lately. With advancing technology, online platforms have become influential tools that amplify the dark tourism encounter. This research delves into how online platforms contribute to enriching the dark tourism experience. It addresses the effective utilization of online media to improve exploration, understanding, and engagement with dark tourism destinations.

The research questions focus on how online platforms enhance exploration and interpretation, their impacts on visitor understanding and emotional engagement, and their facilitation of community engagement and knowledge sharing within dark tourism.

Employing a mixed-methods access, in addition to literature review, qualitative interviews, and quantitative surveys, the study adopts a theoretical framework integrating destination management, digital marketing, and visitor experience theories.

This empirical study adds to the existing literature on how online platforms influence dark tourism, providing practical insights for destination managers and platform developers to enhance visitor experiences and engagement at dark tourism destinations.

Algorithmic monitoring has been widely applied to the practice of platform economy as a management means. Despite its benefits, negative effects of algorithmic monitoring are gradually emerging.

Based on moral disengagement theory, this research aims to investigate how algorithmic monitoring might affect gig workers’ attitudes and behaviors. Specifically, we explored the effect of algorithmic monitoring on gig workers’ unethical behavior. A three-wave survey was conducted online, and the sample consisted of 318 responses from Chinese gig workers.

The results revealed that algorithmic monitoring positively affected unethical behavior through displacement of responsibility, and the individualistic orientation of gig workers moderated this relationship. However, the relationship between moral justification and algorithmic monitoring was not significant.

This research contributes to the algorithmic monitoring literature and examines its impact on gig workers’ unethical behavior. By revealing the underlying mechanism and boundary conditions, this research furthers our understanding of the negative influences of algorithmic monitoring and provides practical implications.