The Impact of CSR's Multi-dimensions on Performance Assessment: A Joint Utilization of Latent Topic Modelling and Support Vector Machine

This study examines the impact of corporate social responsibility (CSR) news reports on corporate operating performance forecasting using a large database of publicly-listed electronics firms in Taiwan. By executing latent topic modelling, we can break down CSR news reports into multiple dimensions and then examine which dimension(s) affects operating performance. To offer decision-makers with a comprehensive, overarching view of the corporate’s operations, the data envelopment analysis (DEA), that can handle multiple input and multiple output variables simultaneously, was conducted to generate the performance rank. The analyzed results were then fed into support vector machine (SVM) to construct the model for performance forecasting. The inherent parameters were decided by harmony search (HS) algorithm. The proposed approach, supported by real samples, can assist both internal and external stakeholders in allocating scarce resources to specific CSR dimensions to enhance a corporate’s growth potential as well as to achieve a win-win situation.

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