رویکرد AHP-TOPSIS فازی به اولویت بندی راه حل ها برای موانع لجستیک معکوس Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers

1. Introduction Over the last decade environmental issues have become an important issue in various industries including the electronics industry due to an increase in environmental awareness, enforced legislation, industrial ecology and corporate citizenship (Prakash & Barua, 2015). The policy and decision makers have to consider environmental issues in each activity of their organization along their supply chain (Kannan, Jabbour, & Jabbour, 2014). Many companies have applied reverse logistics (RL) concept to their policies and strategies for sustainability development which focused on the reduction of waste and created value from return of used products (Sirisawat, Kiatcharoenpol, Choomrit, & Wangphanich, 2016). Rogers and Tibben-Lembke (1998), explained that RL is the process of planning, implementing, and controlling the efficient, cost effective flow of raw materials, in-process inventory, finished goods and related information from the point of consumption to the point of origin for the purpose of recapturing value or proper disposal. RL focuses on maximizing value from the returned item or minimizing the total RL cost from the backward flow of materials (Kannan, Pokharel, & Kumar, 2009). According to law and legislation, it forced producers to take care of their End of Life (EOL) products and the Waste Electrical and Electronic Equipment (WEEE) directive (directive 2002/96/EC) enforced electronics manufacturers to efficiently manage the return and proper disposal of packaging or used products (Govindan, Soleimani, & Kannan, 2015; Nikolaou, Evangelinos, & Allan, 2013). Even though the RL concept is widely used in many companies, it still has a lots of barriers that make RL practices difficult and unsuccessful. Each barrier cannot be solved at the same time and might require different solutions or treatment (Prakash & Barua, 2015; Sharma, Panda, Mahapatra, & Sahu, 2011). Hence, priority and ranking of barriers and solutions is needed to solve such barriers. Previous research has studied and introduced some barriers, drivers and also solutions for RL practices in many countries (Abdulrahman, Gunasekaran, & Subramanian, 2014; Govindan, Kaliyan, Kannan, & Haq, 2014; Prakash & Barua, 2015; Rahman & Subramanian, 2012; Ravi & Shankar, 2005; Sharma et al., 2011; Zaabi, Dhaheri, & Diabat, 2013). However, the study of barriers and solutions in Thailand’s electronics industry remains unstudied. This research focuses on the identification of barriers in Thailand’s electronics industry and ranks solutions to solve its barriers. Electronics companies or other related Thai industries could use the results from the ranking of solutions to solve RL practices barriers and also develop efficient and appropriate policies and strategies for their companies to improve competitiveness. A hybrid of decision making methods was used for prioritizing and ranking of solutions. And fuzzy approach was used to manage the vagueness and uncertainty of the human options in which human judgment in decision making has often been unclear and difficult to estimate with exact numerical values (Patil & Kant, 2014).