Evaluating the environmental protection strategy of a printed circuit board manufacturer using a Tw fuzzy importance performance analysis with Google Trends. (15th October 2020)

• Record Type: Journal Article
• Authors: Chen, Kuen-Suan; Lin, Kuo-Ping; Lin, Li-Ju
• Is Part Of: Expert systems with applications. Volume 156(2020)
• Publication Date: 2020-10-15
• Subjects: Printed circuit board -- Environmental protection -- Fuzzy importance-performance analysis -- Google Trends; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113483
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: This paper develops a new TFIPA-Google analysis method. TFIPA-Google evaluated the environmental protection strategy of a PCB manufacturer. Recovered waste material management system should be a priority. Abstract: Printed circuit boards (PCBs) are very important materials in consumer electronic products. The process of making PCBs usually uses chemicals, and large quantities of water are needed. PCB manufacturers are devoted to improving the process in order to conform to environmental protection rules and regulations. However, evaluating the performance of environmental protection strategies by quantitative methods is very difficult. Therefore, this study attempts to evaluate the environmental protection strategy of a PCB manufacturer using the novel weakest t-norm ( Tw ) fuzzy importance-performance analysis with Google Trends (TFIPA-Google). The TFIPA-Google methodology obtain advantages of Tw operations, IPA, and Google Trends, which can handle uncertainty based on a fuzzy matrix of IPA, reduce fuzzy accumulation using the Tw operators, and analyze social media viewpoints using Google Trends. This empirical example based on the TFIPA-Google method shows that the recovered waste material management system should be a priority for PCB manufacturers. Moreover, the TFIPA-Google method can provide more creditable information, based on Tw operations and volume of Google Trends for decision-makers, than a conventional importance-performance analysis (IPA) model.