Modelling and Evaluating Trust in Mobile Commerce: A Hybrid Three Stage Fuzzy Delphi, Structural Equation Modeling, and Neural Network Approach. Issue 16 (2nd October 2022)

• Record Type: Journal Article
• Authors: Khaw, Khai Wah; Alnoor, Alhamzah; Al-Abrrow, Hadi; Chew, XinYing; Sadaa, Abdullah Mohammed; Abbas, Sammar; Khattak, Zeeshan Zaib
• Is Part Of: International journal of human-computer interaction. Volume 38:Issue 16(2022)
• Page Start: 1529
• Page End: 1545
• Publication Date: 2022-10-02
• Subjects: Human-computer interaction -- Periodicals; 004.01905
• DOI: 10.1080/10447318.2021.2004700
• Languages: English
• ISSNs: 1044-7318

Abstract

ABSTRACT: With the spread of m-commerce usage around the globe, mobile commerce can become the primary approach for many users in transactions. Such a method is considered an innovative way for the financial wallet but with some encumbrances. Trust in mobile commerce is one of the challenges yet to receive in-depth studies regarding linear and non-compensatory relationships. This study aims to evaluate the determinants of trust in mobile commerce using hybrid three-stage Fuzzy Delphi-Structural Equation Modeling (SEM)-Artificial Neural Network (ANN) approach. A hybrid approach was performed on 344 users mobile-commerce activities. The results of this study provide valuable insights for mobile commerce firms to come up with effective plans that increase customer trust in mobile commerce. Practically, the relative importance of specific determinants of trust in mobile commerce contributes to providing deep insight into the factors of customer trust in mobile commerce. The proposed model predicts 94.80% trust in mobile commerce with social presence and social support theories. A novel perspective was provided in this study to encourage e-marketing among consumers to persuade customers to trust mobile commerce.