Understanding consumer participation in managing ICT waste: Findings from two-staged Structural Equation Modeling-Artificial Neural Network approach.

For environmental management, the role of consumers is extremely important in the settings of reverse logistics. Though it is a manufacturer's extended responsibility to handle the waste however by becoming the supplier of the end of life products, consumers' participation needed to be encouraged and hence require proper attention. For the said purpose, the present study is conducted whereby crucial determinants of consumer reversing behavior were identified and analyzed by the help of a unique two-staged methodology of partial least square-structural equation modeling and artificial neural network. The data comprised of 746 collected by the survey from ICT users whereby the findings reported to have significant relationships of return intention and reversing behavior with their determinants. Moreover, the aforementioned unique methodology helps in generating more robust results as findings from ANN reported to have moral norm as most important variable which according to PLS-SEM was second most significant construct, whereas attitude was found to be second most important as per ANN which according to PLS-SEM is the most significant construct. Nevertheless, the study offers insights which contributes in the literature of environmental management, reverse logistics, and consumer behavior. Lastly, based on the findings, the managerial implications and recommendations are accordingly discussed.