Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion

Chun-Che Huang, Wen-Yau Liang (), Roger R. Gung and Pei-An Wang
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Chun-Che Huang: Department of Information Management, National Chi Nan University, 1 University Road, Nantou 545, Taiwan
Wen-Yau Liang: Department of Information Management, National Changhua University of Education, 1, Jin-De Road, Changhua 511, Taiwan
Roger R. Gung: Department of Business Analytics & Operations Research, University of Phoenix, 4025 S Riverpoint Parkway, Phoenix, AZ 85040, USA
Pei-An Wang: Department of Information Management, National Chi Nan University, 1 University Road, Nantou 545, Taiwan

Sustainability, 2023, vol. 15, issue 20, 1-19

Abstract: As developing economies become more industrialized, the energy problem has become a major challenge in the twenty-first century. Countries around the world have been developing renewable energy to meet the Sustainable Development Goals (SDGs) of the United Nations (UN) and the 26th UN Climate Change Conference of the Parties (COP26). Leaders of enterprises have been made aware of the need to protect the environment and have been practicing environmental marketing strategies and green information systems (GISs) as part of ESG practices. With the rapid growth of the available data from renewable electricity suppliers, the analyses of multi-attribute characteristics across different fields of studies use data mining to obtain viable rule induction and achieve adaptive management. Rough set theory is an appropriate method for multi-attribute classification and rule induction. Nevertheless, past studies for Big Data analytics have tended to focus on incremental algorithms for dynamic databases. This study entails rough set theory from the perspective of the decrement decay alternative rule-extraction algorithm (DAREA) to explore rule induction and present case evidence with managerial implications for the emerging renewable energy industry. This study innovates rough set research to handle data deletion in a Big Data system and promotes renewable energy with valued managerial implications.

Keywords: rough set theory; Big Data; renewable energy; decrement algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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