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

摘要

Companies’ objectives extend beyond mere profitability, to what isgenerally known as Corporate Social Responsibility (CSR). Empirical researcheffort of CSR is typically concentrated on a limited number of aspects. We focus onthe 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 conventionalMSCI database and focus on four major dimensions of CSR: Environment, Social/Stakeholder, Labor, and Governance. To identify any structure hidden in almostconstant average values, we apply the popular technique of K-means clustering.When determining the number of clusters, which is especially difficult in the case athand, we use an equivalent clustering criterion that is complementary to the square-error K-means criterion. Our use of this complementary criterion aims at obtainingclusters that are both large and farthest away from the center. We derive from this amethod of extracting anomalous clusters one-by-one with a follow-up removal ofsmall clusters. This method has allowed us to discover a rather impressive processof change from predominantly uniform patterns of CSR activities along the fourdimensions in 2007 to predominantly single-focus patterns of CSR activities in2012. This change may reflect the dynamics of increasingly interweaving and structuring CSR activities into business processes that are likely to be extended intothe future.