Bias in composite indexes of CSR practice: An analysis of CUR matrix decomposition

Abstract

AbstractThe main objective of this research is to propose the best aggregate index of corporate social responsibility practice at the organisational level. To achieve this, we analyse the consistency of the different aggregated measures that researchers use in their analyses through a robust statistical technique, the CUR matrix, framed in the big data environment for selecting individuals. Accordingly, we use an international sample of 2,675 large listed companies. The results show that the CUR leverage identifies greater consistency of the different aggregate measures of CSR, confirming its coherence with a correlation analysis. In this sense, it is possible to affirm that the composite indexes used in academia do not introduce any bias into the analysis of CSR practices. In addition, we demonstrate the utility of this technique to identify the most powerful companies, analysing their CSR commitment at the country and industry levels, namely, Norsk Hydro in the metal and mining industry in Norway, Stora Enso in forestry and paper in Finland, Akzo Nobel in chemical products in the Netherlands, BMW in automobiles and parts in Germany, Generali in finance in Italy, Novartis in pharmaceuticals in Switzerland, the BT Group in telecommunications in the United Kingdom and Inditex in textiles in Spain. Moreover, the results of the CUR study confirm that companies adapt to the demands or pressures from the stakeholders in different areas of interest, which are specific to each country and industry. The availability of these data allows the identification of the structural drivers of their growth and the establishment of priorities that allow the design of more effective sustainable development momentum policies.