Barriers analysis for reverse logistics in Thailand’s palm oil industry using fuzzy multi-criteria decision-making method for prioritizing the solutions

  • Patchara Phochanikorn
  • Chunqiao TanEmail author
  • Wen Chen
Original Paper


The palm oil industry faces significant pressure because of the environmental problems from the plantation process and the palm oil milling process in their supply chain, which is due to the constraints of natural resources and the growing ecological awareness among customers. Reverse logistics (RL) has been considered as a systematic approach for the palm oil industry to improve the environmental impact. However, there are more barriers which cannot be detected in the RL. Therefore, this study proposes robust and flexible strategies for overcoming such barriers by focusing on identifying and ranking the solutions on RL adoption in Thailand’s palm oil industry. We use a fuzzy multi-criteria decision-making (MCDM) methods based on fuzzy analytical network process (ANP) and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to prioritize related solutions and strategies. Firstly, fuzzy ANP is applied to identify the weighting of each barrier using pairwise comparison, while the final ranking of the solution on RL adoption is obtained through VIKOR. This model will help business analysis and supply chain managers formulate both short-term and long-term, flexible decision strategies for successfully managing and implementing RL adoption in the supply chain scenarios. In addition, sensitivity analysis is used to illustrate the method, and comparisons with other existing methods is also presented in this study.


Reverse logistics barriers Thailand’s palm oil industry Fuzzy ANP VIKOR 



This work was partly supported by National Natural Science Foundation of China (no. 71671188), and Natural Science Foundation of Hunan Province, China (no. 2016JJ1024).


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Business School of Central South UniversityChangshaChina
  2. 2.PetroChina Marketing CompanyBeijingChina

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