Next Article in Journal / Special Issue
Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain
Previous Article in Journal
A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model
Previous Article in Special Issue
A Sustainable Two-Echelon Logistics Model with Shipment Consolidation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics

1
Department of Informatics, Faculty of Engineering, Kindai University, 1 Takaya Umenobe, Higashi-Hiroshima 739-2116, Japan
2
Department of Informatics, The University of Electro-Communications, 1-5-1 Chofugaoka, Tokyo 182-8585, Japan
3
Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8511, Japan
4
Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA
*
Author to whom correspondence should be addressed.
Logistics 2023, 7(2), 32; https://doi.org/10.3390/logistics7020032
Submission received: 31 December 2022 / Revised: 3 May 2023 / Accepted: 12 May 2023 / Published: 1 June 2023

Abstract

Background: Since global warming is a crucial worldwide issue, carbon tax has been introduced in the global supply chain as an environmental regulation for the reduction of greenhouse gas (GHG) emissions. Costs, GHG emissions, and carbon tax prices differ in each country due to economic conditions, energy mixes, and government policies. Additionally, multiple countries have signed a Free Trade Agreement (FTA). While FTAs result in their economic benefit, they also increase the risk of carbon leakage, which increases GHG emissions in the global supply chain due to relocation production sites from a country with stricter emission constraints to others with laxer ones. Method: This study proposes a mathematical model for decision support to minimize total costs involving carbon taxes with FTAs. Results: Our model determines suppliers, factory locations, and the number of transported parts and products with costs, FTAs, carbon taxes, and material-based GHG emissions estimated using the Life Cycle Inventory (LCI) database. The FTA utilization on the global low-carbon supply chain is examined by comparing the constructed supply chains with and without FTAs, and by conducting sensitivity analysis of carbon tax prices. Conclusions: We found that FTAs would not cause carbon leakage directly and would be effective for reducing GHG emissions economically.
Keywords: low carbon emission; global supply chain; custom duty; Asian life cycle inventory (LCI) database; mathematical modeling low carbon emission; global supply chain; custom duty; Asian life cycle inventory (LCI) database; mathematical modeling

Share and Cite

MDPI and ACS Style

Kinoshita, Y.; Nagao, T.; Ijuin, H.; Nagasawa, K.; Yamada, T.; Gupta, S.M. Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics. Logistics 2023, 7, 32. https://doi.org/10.3390/logistics7020032

AMA Style

Kinoshita Y, Nagao T, Ijuin H, Nagasawa K, Yamada T, Gupta SM. Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics. Logistics. 2023; 7(2):32. https://doi.org/10.3390/logistics7020032

Chicago/Turabian Style

Kinoshita, Yuki, Takaki Nagao, Hiromasa Ijuin, Keisuke Nagasawa, Tetsuo Yamada, and Surendra M. Gupta. 2023. "Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics" Logistics 7, no. 2: 32. https://doi.org/10.3390/logistics7020032

APA Style

Kinoshita, Y., Nagao, T., Ijuin, H., Nagasawa, K., Yamada, T., & Gupta, S. M. (2023). Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics. Logistics, 7(2), 32. https://doi.org/10.3390/logistics7020032

Article Metrics

Back to TopTop