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Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm

Mushang Lee () and Yu-Lan Huang ()
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Mushang Lee: Department of Accounting, Chinese Culture University, Taipei 11114, Taiwan
Yu-Lan Huang: Graduate Institute of International Business Administration, Chinese Culture University, Taipei 11114, Taiwan

Sustainability, 2020, vol. 12, issue 8, 1-1

Abstract: Until now, the works regarding the relationships between corporate operating performance and corporate social responsibility (CSR) could not reach a conclusive result (positive, natural, and negative). This circumstance can be attributed to two main reasons: (1) inadequate performance measurement and (2) ignoring the multi-dimensional nature of CSR. To combat this, we provided a hybrid decision framework that consisted of two main procedures: (1) performance measurement via linear programming algorithm and (2) CSR’s multi-dimensional nature extraction via text mining. By joint utilization of a linear programming algorithm and text mining, we could gain more insights from the outcome. The proposed decision framework, tested by real cases, is a promising alternative method for performance prediction. Managers can take this model as a roadmap and allocate resources to suitable places, as well as reach the goal of sustainable development.

Keywords: corporate social responsibility; decision-making; performance; text mining (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2020
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