The Paradox of Mobile Money Adoption among Ghana’s PETTY Traders: A Two-Stage PLS-SEM-ANN Approach

Dodoo R. N. A., Xin F., Mangudhla T., Boadi E. B., Dimen L., Nuta A. C.

SAGE Open, vol.15, no.4, 2025 (SSCI, Scopus) identifier

  • Nəşrin Növü: Article / Article
  • Cild: 15 Say: 4
  • Nəşr tarixi: 2025
  • Doi nömrəsi: 10.1177/21582440251378112
  • jurnalın adı: SAGE Open
  • Jurnalın baxıldığı indekslər: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ERIC (Education Resources Information Center), Directory of Open Access Journals
  • Açar sözlər: artificial neural network, Makola traders, Mobile Money, trust, UTAUT
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Bəli

Qısa məlumat

Over the past decade, mobile money services have rapidly expanded in developing economies, yet research on their adoption by petty traders remains limited. This study investigates the factors influencing the intention to use MTN Mobile Money (MTN MoMo) among Makola traders in Ghana. Using a two-stage PLS-SEM artificial neural network (ANN) predictive analytic approach, the study first applied PLS-SEM to test hypotheses, followed by ANN to detect nonlinear effects. A total of 945 questionnaires were collected, revealing that performance expectancy, effort expectancy, social influence, price value, and trust significantly influence traders’ intentions to use MTN MoMo. Additionally, both intention to use and facilitating conditions significantly predict the actual usage of MTN MoMo. Model B indicates differences in the ranking of price value, trust, and intention to use between the PLS-SEM and ANN models, suggesting hidden attributes may influence these relationships. These findings benefit policymakers and service providers committed to advancing digital financial inclusion and economic development. Theoretically, the study extends UTAUT2 in the context of MoMo, a neglected research area. Methodologically, it is the first to apply the UTAUT2 model using the hybrid PLS-SEM-ANN approach in Ghana.