Evaluation and Classification of Mobile Financial Services Sustainability Using Structural Equation Modeling and Multiple Criteria Decision-Making Methods
| Autor: | Yongan Xu, Komi Mawugbe Amedjonekou, Levente Kovács, Komlan Gbongli |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Geography Planning and Development Population mobile financial services (mfs) Analytic hierarchy process TJ807-830 Management Monitoring Policy and Law TD194-195 Structural equation modeling Renewable energy sources 0502 economics and business GE1-350 structural equation modeling (sem) education Sustainable development education.field_of_study Environmental effects of industries and plants Renewable Energy Sustainability and the Environment business.industry 05 social sciences Information technology TOPSIS trust Multiple-criteria decision analysis perceived risk technique for order preference by similarity to ideal solution (topsis) Risk perception multiple-criteria decision-making (mcdm) Environmental sciences Risk analysis (engineering) Sustainability Multiple criteria analytic hierarchy process (ahp) 050211 marketing business 050203 business & management |
| Zdroj: | Sustainability, Vol 12, Iss 4, p 1288 (2020) Sustainability Volume 12 Issue 4 |
| ISSN: | 2071-1050 |
| Popis: | Despite the fast emergent of smartphones in day-to-day activity, the sustainable development of mobile financial services (MFS) remains low partially due to online consumer&rsquo s trust and perceived risk. This research broadens the trust and the perceived risk at the multi-dimensional for understanding and prioritizing alternatives of MFS decision. A combined methodology structural equation modeling (SEM) with two multiple criteria decision-making (MCDM) methods such as a technique for order of preference by similarity to ideal solution (TOPSIS) and analytic hierarchy process (AHP) were applied for data analysis. The two steps SEM-TOPSIS techniques were adopted through a two-types survey on datasets consisting of 538 MFS users, and 74 both experienced MFS users and experts in Togo. The SEM is used for causal relationships and assigning weights for the TOPSIS input. TOPSIS was applied for providing MFS alternative classification, in which the results were compared with prior research using the SEM-AHP technique on the given population. The results via SEM revealed particularly strong support for the dispositional trust and perceived privacy risk. Trust has a negative relationship with perceived risk. Except for perceived time risk, all the antecedents of perceived risk and trust validated the proposed relationship. The findings of TOPSIS uncovered that mobile money transfer (MMT) remains the core application used, followed by mobile payment (MP) and mobile banking (MB) and, therefore, consistent with AHP. However, the TOPSIS technique is better suited to the problem of MFS selection for this study field. This research offers a novel and practical modeling and classification concept for researchers, companies&rsquo managers, and experts in the areas of information technology. The implications, limitations, and future research are provided. |
| Databáze: | OpenAIRE |
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