Evaluating efforts to build sustainable WEEE reverse logistics network design: comparison of regulatory and non-regulatory approaches

Abstract

Many developing countries such as Turkey are still making an effort on building an infrastructure for waste of electrical and electronic equipment (WEEE) reverse logistic network design (RLND) processes. It is obvious that policies/laws/regulations related to WEEE management provide a sustainable framework for implementation in the RLND. The question is here: Does the implementation of WEEE directives make sense in terms of reducing the total cost of the network in the long term? This study aims to compare regulatory and non-regulatory situations of WEEE RLND in developing countries by formulating two models named as ‘regulatory’ and ‘non-regulatory’. Model 1 is considered as sustainable with economic, environmental and social goals, and the quotas imposed by the environmental directive are taken into consideration as the data of product return amount. In Model 2, only economic goal is considered, and product return amount is forecasted using Artificial Neural Network (ANN). A case study is conducted in a recycling company in order to evaluate performance of the proposed models. This study contributes to the relevant literature by (1) comparing the regulatory and non-regulatory situations RL models explicitly and (2) proposing ANN model to forecast EEE product return or WEEE quantity for non-regulatory situation.

Keywords:

• Artificial neural network (ANN)
• network design for sustainable development
• reverse logistics network design (RLND)
• sustainability
• waste of electrical and electronic equipment (WEEE), developing countries

Acknowledgement

The authors are thankful to TÜBİTAK for supporting their project numbered as 115M551.