An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies

Abstract

To stay competitive in a business environment, continuous performance evaluation based on the triple bottom line standard of sustainability is necessary. There is a gap in addressing the computational expense caused by increased decision units due to increasing the performance evaluation indices to more accuracy in the evaluation. We successfully addressed these two gaps through (1) using principal component analysis (PCA) to cut the number of evaluation indices, and (2) since PCA itself has the problem of merely using the data distribution without considering the domain-related knowledge, we utilized Analytic Hierarchy Process (AHP) to rank the indices through the expert’s domain-related knowledge. We propose an integrated approach for sustainability performance assessment in qualitative and quantitative perspectives. Fourteen insurance companies were evaluated using eight economic, three environmental, and four social indices. The indices were ranked by expert judgment though an analytical hierarchy process as subjective weighting, and then principal component analysis as objective weighting was used to reduce the number of indices. The obtained principal components were then used as variables in the data envelopment analysis model. So, subjective and objective evaluations were integrated. Finally, for validating the results, Spearman and Kendall’s Tau correlation tests were used. The results show that Dana, Razi, and Dey had the best sustainability performance.

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

“…The IWQI is a dimensionless parameter ranging from 0 to 100. Following [72], irrigation water quality was classified into four classes based on IWQI value: null (85-100), low (70)(71)(72)(73)(74)(75)(76)(77)(78)(79)(80)(81)(82)(83)(84)(85), moderate (55-70), high (40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55), and severe restriction (0-40).…”

“…Principal component analysis (PCA) can convert multiple parameters into comprehensive indicators based on dimensional reduction and can decrease the calculation complexity of using many variables in a conventional statistical analysis [50][51][52][53][54]. In pervious study, various multivariate statistical analyses were applied to assess the river water quality based on using 13 parameters, and the cluster analysis (CA) method was used to group the 12 months of monitoring into three periods, as well as to group 18 sampling sites into three groups [55].…”

COVID-19 and urban vulnerability in India

“…However, AHP has certain advantages like it helps integrate the ‘domain-related knowledge’ into the model ( Gharizadeh Beiragh et al, 2020 ) and as a corollary to that, it helps take cognizance of the contextuality of the space under investigation ( Dos Santos et al, 2019 ). It is because of its ‘simplicity, ease of use, and great flexibility [that] the AHP has been studied extensively’ ( Gharizadeh Beiragh et al, 2020 ) and motivated us to induct it in our study. Besides, it is widely used in social science and health research.…”

A Literature Review of the Concepts of Resilience and Sustainability in Group Decision-Making

“…On such accounts, it can be remarked that both aspects (resilience and sustainability) play a key role in strategic decision-making. Studying multiple economic, environmental and social indices increased recently [15] and, in the most recent years, researchers have started to consider combinations of political, socio-economic and environmental aspects in decision-making [16] in both the production and service sectors [17]. Implementing this new concept of decision-making could be fruitful in parallel with the sustainability agenda.…”