Studying the Moderating Effect of a Respondent’s Locality in M-commerce Adoption Intention
University of Delhi
University of Delhi
University of Delhi
Introduction: The present research was conducted at the University of Delhi in 2018.
Problem: With the increase in usage of internet technology through wireless devices, the relevance of m-commerce has amplified. In a developing country like India, the rural and urban population is not equally divided on the use of m-commerce and this demands a detailed study regarding this problem.
Objective: The study aims to determine the factors that influence the m-commerce adoption intention of customers and how the effect varies over rural and urban populations.
Methodology: This study combines the TAM and UTAUT model to consider the determinants as perceived ease of use, perceived usefulness, perceived risk, perceived cost, social interaction, and facilitating conditions, taking the endogenous variable as intention to adopt m-commerce.
Results: The results of PLS-SEM accepted the hypotheses underlying the model and also validated the moderating role played by a respondent’s locality over the intention to adopt m-commerce.
Conclusion: The proposed model was validated by using PLS-SEM approach on a sample size of 200 collected from the urban and rural areas of Delhi NCR. Moreover, the moderating effect of a respondent’s locality was observed over adoption intention.
Originality: With the advancement in technological infrastructure and improvement in mobile data facilities, customers have shown enthusiasm towards making online transactions using their phones. The advantage of mobile commerce over computer based electronic commerce is its mobility. Extant research has shown interest in studying the adoption intention of mobile commerce, based on determinants from the TAM or UTAUT model or their combinations. This study combines both models to choose the determinants of mobile adoption intention.
Limitation: Further studies can be conducted by considering other combinations of determinants and extending the model to incorporate the loyalty measures.
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