Unveiling a novel model for promoting mobile phone waste management with a social media data analytical approach

Abstract

With the enormous growth of the population, the intense improvement of the electronic industry, and the ever-incrementing use of mobile phones in today's life, the proper disposal of waste mobile phones has been of paramount importance. Consequently, the tremendous volume of end-of-life (EOL) mobile phones worldwide calls for a sustainable management system to decide on waste mobile phone recovery to minimize the cost and environmental impact. This paper presented a decision problem, namely, EOL option determination, to decrease mobile phone waste. Thus, this study suggests a decision support system (DSS) for the iPhone mobile phone (a subset of the electronics industry) in the EOL phase. Customers’ pervading use of social media has led to these platforms being used as a rich data source to extract information. Thus, the proposed DSS analyzes the Twitter databases, collecting mobile phone defect information from the customers. We suggest an ontology-based text mining and a data mining-based technique through the self-organizing map (SOM) for information discovery from the Twitter data. Finally, a multi-objective mathematical model based on sustainability dimensions is developed to correct EOL decisions based on the defective mobile phone components analyzed from Twitter data. The proposed DSS helps manufacturers when a product is returned and decide for proper EOL processes. This study provides a novel insight and can serve as a valuable reference for solving waste management problems using social media data.