Enhancing the Measurement of Composite Indicators of Corporate Social Performance
Juan Aparicio () and
Magdalena Kapelko ()
Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2019, vol. 144, issue 2, No 13, 807-826
Abstract The aggregation of multiple metrics of corporate social performance (CSP) poses one of the major problems in CSP research. In this paper we propose a new method to compute a composite indicator of CSP from an efficiency perspective using data envelopment analysis. The new approach makes it possible to appropriately account for both positive and negative aspects of CSP, and also to measure CSP for firms for which some of the metrics are exhibiting zero values. Within the new method, we propose measuring global (metafrontier) CSP inefficiency with regard to all firms in the sample and decomposing it into within-industry CSP inefficiency measured with regard to own industry group and industry gap CSP inefficiency. In this way, we measure inefficiencies due to shortcomings in managerial practices and due to the differences between industries in relation to CSP. Using a sample of United States firms in a variety of economic sectors from 2004 to 2015, as covered by the Kinder, Lydenberg and Domini database, we find considerable potential for improvement in CSP practices, with the most CSP-efficient firms representing mining and manufacturing sectors, and the most inefficient belonging to the construction sector. We also find that CSP inefficiency dropped in the period related to the recent financial crisis.
Keywords: Corporate social responsibility; Data envelopment analysis; Directional distance function; Benefit of the doubt; Bad outputs (search for similar items in EconPapers)
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