Investigating the factors affecting the intention to separate e-waste among mobile phone repairers in an emerging economy: A hybrid structural equation modelling and artificial neural network approach.

Abstract

The growing number of mobile phone users on a global scale has led to enormous amounts of electronic waste (e-waste) being generated annually. Insufficient knowledge of e-waste separation causes individuals to dispose of e-waste along with other waste. As a result, this cannot be used in the recycling process. The aim of this study is to determine the elements that significantly impact the intention of mobile phone repairers to carry out separation of e-waste. The integrated model incorporates Self-Determination Theory (SDT) factors (viz., amotivation, external regulation, identified regulation, intrinsic motivation, introjected regulation and integrated regulation) and Institutional Theory (IT) factors (viz., coercive pressure, mimetic pressure and normative pressure). Empirical data were collected through a printed questionnaire survey, with a total of 198 valid respondents. Moreover, this research utilized a hybrid data analysis method, using partial least squares structural equation modelling and artificial neural network to assess the model. The findings of this study indicate that all the SDT and IT factors are supported, except coercive pressure. This research adds to the existing body of knowledge on e-waste separation by shedding light on the problem from the viewpoint of mobile phone repairers, offering useful information to governments and waste recycling companies to understand the intentions of repairers with respect to e-waste separation and formulate such strategies that can enhance the involvement of repairers in e-waste separation activities.