Exploring patterns of corporate social responsibility using a complementary K-means clustering criterion

Zina Taran () and Boris Mirkin ()
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Zina Taran: Delta State University
Boris Mirkin: National Research University Higher School of Economics

Business Research, 2020, vol. 13, issue 2, No 6, 513-540

Abstract: Abstract Companies’ objectives extend beyond mere profitability, to what is generally known as Corporate Social Responsibility (CSR). Empirical research effort of CSR is typically concentrated on a limited number of aspects. We focus on the whole set of CSR activities to identify any structure to that set. In this analysis, we take data from 1850 of the largest international companies via the conventional MSCI database and focus on four major dimensions of CSR: Environment, Social/Stakeholder, Labor, and Governance. To identify any structure hidden in almost constant average values, we apply the popular technique of K-means clustering. When determining the number of clusters, which is especially difficult in the case at hand, we use an equivalent clustering criterion that is complementary to the square-error K-means criterion. Our use of this complementary criterion aims at obtaining clusters that are both large and farthest away from the center. We derive from this a method of extracting anomalous clusters one-by-one with a follow-up removal of small clusters. This method has allowed us to discover a rather impressive process of change from predominantly uniform patterns of CSR activities along the four dimensions in 2007 to predominantly single-focus patterns of CSR activities in 2012. This change may reflect the dynamics of increasingly interweaving and structuring CSR activities into business processes that are likely to be extended into the future.

Keywords: Corporate social responsibility; Quantitative patterns; Cluster analysis; K-means; Anomalous cluster; CSR trends (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s40685-019-00106-9

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