Faculty Publications
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Item Predicting the Determinants of Augmented Reality Technologies in E-commerce Applications: A SEM and ANN Modeling(Springer Science and Business Media Deutschland GmbH, 2025) Anand, K.; Sheena, S.Augmented reality (AR) technologies are the most promising technologies for e-commerce applications. This study has used the UTAUT theory, extending with privacy risk, which may impact the user’s decision to try AR features in e-commerce apps. The paper investigated factors using a two-stage approach comprising of Structural Equation Model (SEM) and an Artificial Neural Network (ANN). The validation of the model is performed with the IBM SPSS AMOS 24 and IBM SPSS 25 software. The results revealed performance expectancy as a noteworthy determinant through the analysis. Further privacy risks involved while using AR features of online shopping apps negatively impact the influence on the choice of the users to try out the technology. The proposed model has explained the user behavioral intention with 36.7%, whereas using ANN has predicted with an accuracy of 48.9%, indicating the model has high predictive power. This study’s theoretical and practical insights will contribute to developing and refining augmented reality systems in e-commerce applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item An empirical examination of user’s adoption of AR in e-commerce apps in a developing country: evidence from India(Emerald Publishing, 2025) Anand, K.; S, S.Purpose The e-commerce industry is witnessing rapid growth by offering convenience in shopping. However, it fails to provide a virtual experience of the products, creating excessive product returns and posing challenges to the companies, customers and environment. The use of augmented reality (AR) bridges the gap between the customers and products. The purpose of this study is to explore the customer perspective towards adopting AR in online shopping, which can reduce excessive product returns, creating sustainable business practices. Design/methodology/approach Online survey was used in the data collection process. A total of 1,029 valid responses collected via judgement sampling were analysed using covariance-based structural equation modelling with AMOS software. Findings Trust is significantly influenced by performance expectancy, effort expectancy, social influence and facilitating conditions. Likewise, performance expectancy, hedonic motivation and trust significantly affect behavioural intention. Meanwhile, effort expectancy, social influence, facilitating conditions on behavioural intention and hedonic motivation on trust were found to have an insignificant influence. Practical implications This study investigates users’ behavioural intention towards AR in online shopping apps using the Unified Theory of Acceptance and Use of Technology (UTAUT2) with trust in the Indian context, providing valuable insights into implementing AR technology and enhancing the realism of virtual product experiences. Originality/value This study aims to investigate users’ behavioural intention by providing a research model that extends the UTAUT2 model, including trust. The objective is to analyse the factors influencing the adoption of a novel technology in a developing country, specifically in the Indian context. © 2025 Emerald Publishing Limited