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  2. Vol 6, No 6 (2022)
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Understanding and Predicting the Determinants of Consumers’ Acceptance and Usage of M-commerce Application: Hybrid SEM and Neural Network Approach

Odai Enaizan, Ashraf Saleh, Bilal Eneizan, Mohammad Almaaitah, Asaad Alsakarneh

Abstract


In m-commerce, privacy and security are major concerns. Existing research has examined the privacy and relationship, security, and intention to use. However, the determinants of privacy and security in mobile commerce remain largely unexplored. A study based on UTAUT2 and trust examines the factors that influence mobile commerce privacy and security. By using the approach of hybrid SEM/ANN analysis, it is possible to detect non-linear and non-compensatory relationships. According to linear and compensatory models, the absence of one determinant can be compensated for by another. The decision-making process of consumers is actually quite complex, and non-compensatory or linear models tend to simplify it. The sample is collected by using a mobile commerce application in order to gather 890 datasets on mobile commerce consumers. Findings: (1) Two determinants of M-commerce acceptance and use had an explicit and significant positive effect. Security and individual are two of these factors. (2) Privacy concerns have a severe negative impact on M-commerce acceptance and use. (3) Trust is found to partially mediate the effect on behavioral intentions of Security Factors (SCF), Privacy Factors (PRF), and Individual Factors (INF) on m-commerce in Jordan (INTENTION). According to the integrated model, m-commerce offers 71% privacy, security, and trust.

 

Doi: 10.28991/ESJ-2022-06-06-018

Full Text: PDF


Keywords


Privacy; Security; Acceptance; Mobile Commerce; Application; Neural Network Approach.

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DOI: 10.28991/ESJ-2022-06-06-018

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