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Determining the factors of m-wallets adoption. A twofold SEM-ANN approach

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  • Imdadullah Hidayat-ur-Rehman
  • Saeed Alzahrani
  • Mohd Ziaur Rehman
  • Fahim Akhter

Abstract

M-wallets are comparatively more advantageous and convenient than conventional payment systems as m-wallets allow users to avoid cash. The present research uses the diffusion of innovation theory as the base theory to propose a research model by incorporating constructs like convenience, perceived security, personal innovativeness, and perceived trust to investigate the determinants of consumers’ intention-to-use m-wallets. A twofold approach comprising of Structural Equation Modelling—Artificial Neural Network (SEM-ANN) was used: First, partial least squares structural equation modelling (PLS-SEM) was employed to determine the significant determinants of intention-to-use. Second, the ANN approach was applied as robustness to corroborate the outcomes of PLS-SEM and to estimate the relative importance of the SEM-based significant determinants. Our findings confirmed that compatibility, ease of use, observability, convenience, relative advantage, personal innovativeness, perceived trust, and perceived security are the key elements that influence the intention-to-use m-wallets. Moreover, we ascertained that perceived security is the most influential predictor of intention-to-use. The outcomes of ANN have complemented the findings of PLS-SEM, but some differences were also exhibited in the order of influential factors. The study brings to fore significant insights and a set of suggestions for the companies carrying out the development, execution, and marketing of M-wallet services.

Suggested Citation

  • Imdadullah Hidayat-ur-Rehman & Saeed Alzahrani & Mohd Ziaur Rehman & Fahim Akhter, 2022. "Determining the factors of m-wallets adoption. A twofold SEM-ANN approach," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-24, January.
    • Handle: RePEc:plo:pone00:0262954
    DOI: 10.1371/journal.pone.0262954
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    2. Ashish Ashok Uikey & Zericho Marak & Dhoha Alsaleh & Ruturaj Baber, 2024. "Decoding Intentions to Purchase Organic Food Products in an Emerging Economy via Artificial Neural Networks," Post-Print hal-04861233, HAL.

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