A copula-based exponential probabilistic model for factor-dependence social sustainability assessment

Abstract

Social bottom line has been acknowledged as a significant indicator for sustainability index measurement in the supply chain management. The use of resources sourced at national and regional levels as prime factors for modeling sustainability using independent variables has been widely corroborated. However, the application of statistical-based models for appraising supply chain sustainability performance resolutely through challenge-capacity dependency is scanty. An exponential probabilistic copula-based model is proposed for measuring corporate social sustainability using complex criteria drawn from the five stakeholder parameters. The article considers majorly challenge-capacity factor dependency through correlation, joint probability and a Farlie-Gumble-Morgenstern dependent-factor copula-based model. Four tracking indices-sustainability perturbation index (SPI), sustainability percent solvency (SPS), sustainability percent insolvency (SPIS) and sustainability anticipated improvement (SAI)-are introduced to panoramically examine the solvency of the sustainability and the priority for improvement. A healthcare system case studied with five stakeholder parameter-supplier, patients, patient relatives, employee and Government. For the factor dependency case, the sustainability indexes for the parameters show enhanced values over the factor-independent case. An aberration noticed due some negative correlation is resolved by the tracking indices. The tracking indices indicate the aggregated social sustainability is highly insolvent with 28.98% SPS, 71.20% SPIS for factor-dependent case and 0% SPS, 100% SPIS for factor-independent case. The SAI of 42.04% and - 100%, respectively, for factor dependence and factor independence provides insight into the pre-eminence of the factor dependence, thereby positioning the decision-makers for prioritizing sustainability improvement. Therefore, ignoring factor dependency produces misleading highly volatile sustainability indexes.