Evaluation and Classification of Mobile Financial Services Sustainability Using Structural Equation Modeling and Multiple Criteria Decision-Making Methods

Abstract

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’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’ managers, and experts in the areas of information technology. The implications, limitations, and future research are provided.

Intention to Use Accounting Platforms in Romania: A Quantitative Study on Sustainability and Social Influence

“…Perceived risk refers to the risk that users believe they may have when certain accounting platforms do not guarantee the security of their data or transactions. In other words, perceived risk negatively influences attitudes [40,41] and the intention to use information technology [42] or remote payment systems [43,44]. In our research, risks were considered essential because they are considered a precedent for users' intention to use information technologies.…”

Mobile perceived trust mediation on the intention and adoption of FinTech innovations using mobile technology: A systematic literature review

“…Past studies found that trust significantly impacts consumer behaviour (intention and adoption) in uncertain environments (To & Trinh, 2021). Furthermore, Gbongli et al (2020) confirmed that customer's trust positively impacts customer's intention to use electronic banking.…”

An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

“…In literature, scholars have paid close attention to the methodology mentioned above due to its ability to handle complex situations. Supplier selection [61], material selection [62], personnel selection [63], technology selection [64], performance measurement [65], and financial decision making [66] are a few examples of MCDM applications. The decision about the problem described above is based on a set of factors, sub-factors, and alternatives.…”

“…Following the sensitivity analyses, a comparison with the existing literature was performed. Although a few studies [7,45,65,102] addressed the selection of m-banking technologies, none of them addressed human judgement of uncertainty when making a decision. The proposed fuzzy model, which employs fuzzy-BWM and fuzzy-TOPSIS to select m-banking applications, is unique in that it takes into account human uncertainty when selecting m-banking applications.…”