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Discovering Hidden Associations among Environmental Disclosure Themes Using Data Mining Approaches

Author

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  • Ece Acar

    (Department of Business Administration, Faculty of Business, Yasar University, Izmir 35100, Turkey)

  • Görkem Sarıyer

    (Department of Business Administration, Faculty of Business, Yasar University, Izmir 35100, Turkey)

  • Vipul Jain

    (Operations and Supply Chain Management, Wellington School of Business and Government, Wellington 6012, New Zealand)

  • Bharti Ramtiyal

    (Department of Management Studies, Graphic Era (Deemed to be University), Dehradun 248002, India)

Abstract

Environmental concerns play a crucial role in sustainability and public opinion on supply chains. This is why, how, and to what extent the firms experience environmental-related actions and inform their stakeholders, which is under discussion by most researchers. This paper aims to leverage data mining and its capabilities by applying association rule mining to the environmental disclosure context. With the aim of extracting hidden relationships between environmental disclosure themes for BIST 100 firms serving the Turkish supply chain, this research implements a novel association rule mining approach and uses the Apriori algorithm. With this purpose, the environmental information of BIST 100 firms was collected manually from sustainability reports; the raw data were processed; and the following seven themes identified the representing firms’ disclosure items: environmental management, climate change, energy management, emissions management, water management, waste management, and biodiversity management. The results indicate various hidden relations between the sector and disclosures, allowing us to generate sector-based rules between environmental disclosure themes.

Suggested Citation

  • Ece Acar & Görkem Sarıyer & Vipul Jain & Bharti Ramtiyal, 2023. "Discovering Hidden Associations among Environmental Disclosure Themes Using Data Mining Approaches," Sustainability, MDPI, vol. 15(14), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11406-:d:1200276
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