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In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

The potential growth in cryptocurrencies has raised serious ethical and religious issues leading to a new investment rethinking. This paper aims to identify the influence of religiosity on cryptocurrency acceptance through an extended technology acceptance model (TAM) model.

In the first phase, this research develops a conceptual model that extends the theory of the TAM by integrating the religiosity component. In the second phase, the proposed model is tested using search volume queries in daily frequencies from 01/01/2018 to 31/12/2022 and structural equation modeling (SEM).

The empirical results demonstrate a significant positive effect of religiosity on the intention to use cryptocurrency, the users' perceived usefulness (PU) and ease of use (PEOU). Besides, the authors note that PEOU positively influences the intention. Furthermore, religiosity indirectly affects the intention through the PEOU and positively impacts the intention through the PU. In the same way, PEOU has a considerable indirect effect on the intention through PU.

This study has practical and theoretical contributions by providing insights into the cryptocurrency acceptance factors. In other words, it contributes to the literature by extending TAM models. Practically, it helps managers determine factors affecting the intention to use cryptocurrencies. Therefore, they can adjust their industry according to the suitable characteristics for creating successful projects.

Identifying the effect of religiosity on cryptocurrency users' choices and decisions has a social added value as it provides an understanding of the evolution of psychological variants.

The findings emphasize the importance of integrating big data to analyze users' attitudes. Besides, most studies on cryptocurrency acceptance are investigated based on one kind of religion, such as Christianity or Islam. Nevertheless, this paper integrates the effect of five types of faith on the users' intentions.

This study aims to understand the learner behaviour of millennials for Massive Open Online Courses (MOOCs) in the post-adoption stage by extending the theory of Unified Theory of Acceptance and User Technology 2 (UTAUT2) with expectancy confirmation model (ECM) along with personal innovativeness as the exogenous, satisfaction as a mediating and continued intention as an endogenous construct.

This study applied a cross-sectional research design by using a survey method to collect primary data with a structured questionnaire. Convenience sampling was used to collect data from millennial MOOC users, and partial least square structural equation modelling method was applied for data analysis.

The results indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation influence satisfaction. Similarly, performance expectancy, hedonic motivation, personal innovativeness and satisfaction influence the continued intention for MOOCs.

In terms of limitations, the study applied a cross-sectional research design that could lead to data collection bias. Similarly, the study used convenience sampling as the authors did not have access to the participant list of users from MOOC platforms.

The research highlights various insights to all the stakeholders on improving MOOC satisfaction and enhance the continued intention for millennial learners.

The findings of this research bridge this gap by examining the post-adoption usage behaviour of MOOCs by extending the baseline model of UTAUT2 with personal innovativeness and integrating it with ECM.

Research on technology acceptance of online entertainment with age, gender and cultural factors as moderator, is rarely conducted. Previous research predominantly focused on age or gender as moderator, neglecting the influence of cultural factors. Therefore, this study aims to investigate acceptance of online entertainment technology, incorporating age, gender and cultural factors as moderator.

Data were collected through a survey comprising 1,121 individuals aged 14–24 years from three cities in Indonesia. The proposed theoretical model examined the causal effect of acceptance and moderating effects due to individual gender, age, power distance, individualism, feminism and uncertainty avoidance (AU). Subsequently, structural equation modeling was used to evaluate the theoretical model, and the results confirmed several findings from previous research.

The findings confirmed the positive direct impact of habit and price value (PV) on behavioral intention and hedonic motivation, as well as social influence on habit. The recent findings derived from the moderating effect analysis showed that age, individualism and feminism played a moderating role in the effects on individual intention due to habit. Additionally, gender and AU moderated the effects on individual habits due to hedonic motivation.

This research contributes to the limited knowledge of technology acceptance of online entertainment, and also integrates the causal effects of individual intention due to habit, PV, hedonic motivation and social influence, considering the moderating role of culture, age and gender. Consequently, the investigation provides valuable insights into the literature by presenting evidence of age, gender and cultural differences in acceptance. Furthermore, it offers practical guidance to online entertainment application developers on designing applications to satisfy consumers of different ages, genders and cultures.

This research empirically studies consumers' continued intention to use mobile food delivery applications (apps) during the post-pandemic era in Saudi Arabia.

Using the unified theory of adoption and use of technology 2 (UTAUT2) as a theoretical model, this study collected data from a survey of 304 Saudi Arabian consumers. Structural equation modelling (SEM) was used to examine the proposed model and its hypotheses.

Social influence and performance expectancy (PE) had the strongest effects on the intention to continue using mobile food delivery apps in the post-pandemic era. In addition, effort expectancy (EE) significantly influenced PE regarding the adoption of food delivery apps. Meanwhile, EE was not an important predictor of the continued intention to use mobile food delivery apps in Saudi Arabia.

This study enriches the literature on consumers' continued intention to use food delivery apps in the post-pandemic era, a subject that has rarely been studied. In addition, this study expands the theoretical potential of the UTAUT2 model by examining the role of trust in continued intention and the effect of PE on EE in the adoption of food delivery apps during the post-pandemic era in Saudi Arabia.

This study aims to identify the determinants that influence citizen’s behavioural intention and continuous usage intention of smart mobility services in Indian smart cities with the help of an extended technology acceptance model.

This study uses a quantitative methodology to analyse the data collected from 509 residents of smart cities in India. The study used the partial least squares structural equation modelling approach to test the proposed hypotheses.

The study highlights the importance of perceived usefulness and ease of use in influencing citizens’ attitudes and intentions towards smart mobility services. Positive attitudes significantly impact behavioural intentions, which, in turn, link to continuous usage intentions.

This study contributes to the existing body of knowledge on smart cities and technology adoption, specifically in the area of smart mobility. The study’s findings will help service providers and policymakers to develop more robust strategies for the future.

This study aims to examine the factors influencing consumers’ intentions to use QR code menus in the post-COVID-19 pandemic using the unified theory of acceptance and use of technology and rational choice theory as the theoretical foundations.

Using a survey method, 200 data are collected from consumers who had used QR code menus in the past. Partial least squares structural equation modelling is used to analyse the data.

Our findings show that performance expectancy, effort expectancy, social influence, habit and perceived privacy protection have a significant positive influence on intentions. However, facilitating conditions, hedonic motivation and perceived privacy risk do not have a significant influence on intentions.

This study further extends the work of previous studies by using the unified theory of acceptance and use of technology model, with additional two new predictors, namely perceived privacy protection and perceived privacy risk, to understand consumers’ intentions to use QR code menus.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

The purpose of this research is to examine, from the self-efficacy standpoint, the factors that influence medical tourists' use of social media for travel planning. To that end, this study presents a conceptual framework for evaluating medical tourists' online behaviour and empirically tests the model's validity by examining various dimensions of self-efficacy.

A sample of 224 people who searched for medical tourism information online was used in this study. Partial least squares structural equation modelling (PLS-SEM) was employed to test the proposed model with data from an online questionnaire survey.

The findings suggest that sources of self-efficacy reinforce one's belief in the ability to use social media for medical travel planning purposes. According to the structural model analysis results, with the exception of social persuasion (SP), all of the proposed factors were significant sources of self-efficacy.

The findings can assist medical tourism providers in optimising online searches for medical travel information, as well as medical tourism destination marketers in directing the tourism providers' marketing efforts towards the use of social media to target potential medical tourists more efficiently and on a larger scale.

This study is being conducted in response to a significant knowledge gap in identifying the factors that influence medical tourists' online behaviour. This information can help medical tourism destination marketers gain a competitive advantage by using social media to target potential medical tourists more effectively and on a larger scale.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.