Big data analytics application in multi-criteria decision making: the case of eWallet adoption

Naysary, Babak; Malekzadeh, Mehdi; Tacneng, Ruth; Tarazi, Amine

doi:10.2139/ssrn.4076471

Cited by 2 publications

(3 citation statements)

References 37 publications

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“…Then, the author used AHP analysis to assess the relative importance of the clusters and find the optimal framework for choosing an e-wallet provider. According to the results, Usefulness is the most crucial factor for users while considering the e-wallet, followed by Risk, Ease of use, Customer service, User interface, Trust, Promotional reward, Associated costs, Interoperability and Security [10].…”

Section: Customer Satisfaction With Digital Wallet Services and Its M...mentioning

confidence: 99%

“…The majority of the studies have employed Partial Least Squares (PLS) SEM, while two models have been built using multiple linear regression [26,32]. One study has also employed a Business Intelligence technique (clustering) and soft computing method (Analytical Hierarchy Process-AHP) [10]. The salient features of the e-wallets adoption models described above are summarized in Table 2.…”

Section: Comparison Of Existing Models For Customer Satisfaction Towa...mentioning

confidence: 99%

“…The available set of methods for customer satisfaction research has been enriched by big data, sentiment analysis, fuzzy logic, regression analysis, neural networks or their combinations [10][11][12], and it now enables the discovery of new dependencies.…”

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confidence: 99%

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Customer Attitude toward Digital Wallet Services

Ilieva

Yankova

Dzhabarova

et al. 2023

Systems

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The goal of this study is to examine and identify the factors influencing customer attitude toward and intention to use digital wallets (electronic wallets, e-wallets) during and after the COVID-19 pandemic. A total of 257 correctly fulfilled questionnaires from an online survey were summarized. The main features of e-wallet payment systems were classified with a focus on consumer satisfaction via the integration of classic and modern data analysis methods. Structural Equation Modeling (SEM) was preferred to reveal the dependencies between the variables from e-wallets users’ perspective. The designed model can discover and explain the underlying relationships that determine the e-wallets’ adoption mechanism. The obtained results lead to specific recommendations to stakeholders in the value chain of payment processing. Financial regulatory authorities could employ the presented results in planning the development of payment systems. E-commerce marketers could utilize the proposed methodology to assess, compare and select an alternative way for order payment. E-wallet service providers could establish a reliable multi-criteria system for the evaluation of digital wallet adoption. Being aware of the most important components of e-wallets value, managers can more effectively run and control payment platforms, enhance customer experience, and thus improve the company’s competitiveness. As the perceived value of customer satisfaction is subjective and dynamic, measurements and data analysis should be conducted periodically.

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Section: Customer Satisfaction With Digital Wallet Services and Its M...mentioning

confidence: 99%