Please use this identifier to cite or link to this item: https://openscholar.ump.ac.za/handle/20.500.12714/389
Title: Social welfare and bank performance: evidence from a stochastic neural hybrid MCDM approach.
Authors: Maredza, Andrew.
School of Development Studies
Keywords: COPRAS.;Multi-criteria decision-making.;TOPSIS.;SWARA.;Banking performance.;Social welfare.
Issue Date: 2021
Publisher: Emerald Publishing Limited
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.
Description: This is an EarlyCite article.
URI: https://openscholar.ump.ac.za/handle/20.500.12714/389
DOI: 10.1108/JES-05-2021-0236
Appears in Collections:Journal articles

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