A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption

By Alain Yee-Loong Chong. Expert systems with applications, 2013

398 citations recorded by the source corpus.

The advancement in wireless and mobile technologies has presented tremendous business opportunity for mobile-commerce (m-commerce). This research aims to examine the factors that influence consumers' m-commerce adoption intention. Variables such as perceived usefulness, perceived ease of use, perceived enjoyment, trust, cost, network influence, and variety of services were used to examine the adoption intentions of consumers. Data was collected from 376 m-commerce users. A multi-analytic approach was proposed whereby the research model was tested using structural equation modeling (SEM), and the results from SEM were used as inputs for a neural network model to predict m-commerce adoption. The result showed that perceived usefulness, perceived enjoyment, trust, cost, network influence, and trust have significant influence on consumers' m-commerce adoption intentions. However, the neural network model developed in this research showed that the best predictors of m-commerce adoption are network influence, trust, perceived usefulness, variety of service, and perceived enjoyment. This research proposed an innovative new approach to understand m-commerce adoption, and the result for this study will be useful for telecommunication and m-commerce companies in formulating strategies to attract more consumers.

Subfields: Information Systems and Management, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/497b19f70050713fcdcb4ee9266d22650224d9c1

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Citations in the corpus

Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology (2018, background): “In various cultural contexts, Performance Expectancy has been found to exhibit a significant positive relationship with the Behavioral Intention to adopt m-commerce (Chong, 2013; Lai & Lai, 2014).”
A meta-analysis of antecedents and consequences of trust in mobile commerce (2020, background): “Thus, various scholars emphasized the relevance of trust over the years in predicting consumers ’ intention to use and adopt m-commerce (Blaise, Halloran, & Muchnick, 2018; Chong, 2013).”