E-payments in the post-COVID-19: navigating uncertainty and forecasting trends

Mohamad Ahmadian

Journal of Economic Studies, 2025, vol. 53, issue 1, 31-46

Abstract: PurposeThis study aims to investigate the impact of the COVID-19 pandemic on electronic payments and to predict future trends in this sector using advanced grey forecasting models. It seeks to fill the research gap in understanding how digital payment behaviors have evolved post-pandemic, particularly focusing on the Iranian market.Design/methodology/approachThe research employs grey forecasting models, including grey model (GM(1,1)), rolling grey model (RGM(1,1)), unbiased GM (1,1), modified unbiased GM (1,1), discrete grey model (DGM(1,1)) and grey Verhulst, to analyze the e-payment indicators in the next three financial periods. Data were collected on electronic transactions and payment behaviors, and various forecasting models were compared to assess their accuracy and applicability.FindingsThe study finds that the unbiased GM (1,1) and modified unbiased GM (1,1) models offer superior accuracy in predicting electronic payment trends compared to the other models. These models are particularly effective in scenarios with limited data, showcasing their robustness in forecasting future trends in digital payments.Originality/valueThis research contributes original insights into the post-pandemic evolution of electronic payments, highlighting the effectiveness of grey forecasting techniques in emerging markets. It provides valuable information for policymakers and financial institutions, aiding in strategic planning and policy development related to digital transactions.

Keywords: COVID-19; Electronic payment; Forecasting; Grey systems (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jespps:jes-11-2024-0745

DOI: 10.1108/JES-11-2024-0745

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