A Data Envelopment Analysis-Based Methodology Adopting Assurance Region Approach for Measuring Corporate Social Performance

• Published in: Social indicators research Vol. 148; no. 3; pp. 863 - 892
• Main Authors: Wu, Tai-Hsi, Chih, Hsiang-Lin, Lin, Mei-Chen, Wu, Yi Hua
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.04.2020; Springer Nature B.V
• Subjects: Data analysis; Data envelopment analysis; Human Geography; Microeconomics; Misconduct; Original Research; Public Health; Quality of Life Research; Research methodology; Social action; Social Sciences; Sociology; Data envelopment analysis (DEA); Corporate social responsibility; KLD; Assurance region; Performance measurement; Corporate social performance
• ISSN: 0303-8300; 1573-0921
• DOI: 10.1007/s11205-019-02228-3

Many research papers calculate corporate social performance (CSP) with the net score method, i.e., by subtracting the number of concerns from the number of strengths. Although widely adopted, this method implies, perhaps mistakenly, that each indicator is of equal importance and that however serious the social misconduct a firm may have engaged in, it can be completely offset by some positive social action. The method also implies that a given firm that has done both a lot of harm and a lot of good will have CSP similar to that of another firm that has done little harm and little good. In this study, however, we question the appropriateness of the net score method in terms of its ability to truly reflect CSP and truly identify the real effects of CSP on various characteristics. We therefore propose a data envelopment analysis-based methodology that adopts the assurance region approach for evaluating CSP, through which various CSP indicators are converted into a single composite measure of CSP. Our findings show that our proposed methodology consistently performs better than the net score method in evaluating CSP.