A Hybrid, Data-Driven Causality Exploration Method for Exploring the Key Factors Affecting Mobile Payment Usage Intention

Several methodologies for academically exploring causality have been addressed in recent years. The decision-making trial and evaluation laboratory (DEMATEL), one of the multiple criteria (MCDM) techniques, relies on expert judgements to construct an influential network relation map (INRM), revealing mutual causes effects dimensions presentation results a visual manner. interactional impacts may be evaluated without considering presumed hypotheses. DEMATEL has successfully utilized assist complex problems various contexts. However, there is controversy about reliance upon judgements, which could subjective. Thus, this study seeks overcome dispute by developing data-driven, concept-based novel hybrid model authors call SEM-DEMATEL. first constructs direct between indicators based structural equation modeling (SEM) then utilizes confirm interdependence among variables identify their effects. Finally, empirical key factors affecting mobile payment usage intention further conducted demonstrate feasibility, validity, reliability SEM-DEMATEL research approach. that perceived value influencing indicator m-payment intention, objectivity efficiency are compared.