Social welfare and bank performance: evidence from a stochastic neural hybrid MCDM approach

Andrew Maredza, Peter Wanke, Jorge Antunes, Roberto Pimenta, Aaron Tan

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Purpose: This paper investigates the endogenous relationships between banking performance and social welfare in Southern African Development Community (SADC) countries. Design/methodology/approach: A comprehensive three-stage multi-criteria decision-making (MCDM) approach based on alternative informational assumptions is applied. Findings: Results indicate that banking performance is paradoxically associated with stagnant economic activity and higher wealth concentration for the minority. The authors found that SADC banking performance promotes higher Human Development Index (HDI) standards possibly via efficient financial intermediation, dissemination of best managerial practices and other forms of positive spillovers in these countries. Originality/value: This paper contributes to the MCDM literature by simultaneously exploring the key concepts of “utility functions” (using COPRAS) and “distance to ideal solutions” (using TOPSIS) in mapping and explaining the feedback and cause-effect processes between banking performance and social welfare that may exist. Another distinctive aspect is related to the computation of bias-free criteria weights, using a robust SWARA order-rank based on information entropy. Finally, this paper is concerning the endogeneity measurement, using a novel stochastic structural relationship non-linear programme.

Original languageEnglish
Number of pages22
JournalJournal of Economic Studies
Early online date23 Sep 2021
DOIs
Publication statusE-pub ahead of print - 23 Sep 2021

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