A Sustainability Comparison of Traditional Supply Chains and Physical Internet Supply Chains Using Simulation

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Date

2019

Authors

Nazlıcan GÖZAÇAN
Özgür KABADURMUŞ

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GOLD

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No

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Average
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Average
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Average

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Abstract

Sustainability is one of the most important topics that should be considered by every sector because ithelps to reduce the harmful environmental effects of operations. Supply chain operations have significantimpacts on environmental social and economic issues and therefore sustainable supply chains havebecome an important issue for the companies. Also Physical Internet (PI) is one of the recent researchtopics in supply chain literature and it helps to provide sustainability. The contribution of this study to theliterature is the comparison of traditional supply chain and PI structures with simulation in terms ofsustainability. The simulation models are tested on realistic but hypothetical case studies. Each simulationmodel consists of three echelons (supplier distribution center and retailer) and is developed by usingARENA 14.0 software. The PI and the traditional are compared according to carbon emissions and theresults are discussed in detail. The results show that the emission level of PI is significantly lower than theemission level of traditional supply chain structures. Also larger vehicle capacity reduces the total carbonemissions in both traditional supply chains and PI due to the reduced number of trips.

Description

Keywords

Yeşil- Sürdürülebilir Bilim ve Teknoloji-Endüstri Mühendisliği, Yeşil, Sürdürülebilir Bilim Ve Teknoloji, Endüstri Mühendisliği, Engineering, Logistics;Physical Internet;Simulation;Supply Chain Management;Sustainability, Mühendislik

Fields of Science

0502 economics and business, 05 social sciences, 0211 other engineering and technologies, 02 engineering and technology

Citation

1. Carter C.R. and Rogers D.S. 2008. A framework of sustainable supply chain management: moving toward new theory. International journal of physical distribution & logistics management 38(5) 360- 387.2. Fekpe E. & Delaporte Y. 2018. Sustainability integration and supply chain performance of manufacturing small and medium size enterprises. African Journal of Economic and Management Studies. 10(2) 130-147.3. Montreuil B. 2012. Physical Internet Manifesto version 1.11. 1. CIRRELT Interuniversity Research Center on Enterprise Networks Logistics and Transportation 2-3.4. Montreuil B. 2011. Toward a Physical Internet: meeting the global logistics sustainability grand challenge. Logistics Research 3(2-3) 71-87.5. Meller R. D. Montreuil B. Thivierge C. & Montreuil Z. 2012. Functional Design of Physical Internet Facilities: A Road-Based Transit Center. Progress in Material Handling Research: 2012 (22).6. Hakimi D. Montreuil B. Sarraj R. Ballot E. & Pan S.Simulating a Physical Internet enabled mobility web: the case of mass distribution in France. In 9th International Conference on Modeling Optimization & SIMulation-MOSIM'12 2012 pp. 10-p.7. Furtado P. Fakhfakh R. Frayret J. M. & Biard P. Simulation of a Physical Internet—Based transportation network. In Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM) 2013 pp. 1-8.8. Sarraj R. Ballot E. Pan S. Hakimi D. & Montreuil B. 2014. Interconnected logistic networks and protocols: simulation-based efficiency assessment. International Journal of Production Research 52(11) 3185-3208.9. Pan S. & Ballot E. 2015. Open tracing container repositioning simulation optimization: a case study of FMCG supply chain. In Service Orientation in Holonic and Multi-agent Manufacturing 281- 291.10. Pan S. Nigrelli M. Ballot E. Sarraj R. & Yang Y. 2015. Perspectives of inventory control models in the Physical Internet: A simulation study. Computers & Industrial Engineering 84 122-132.11. Yang Y. Pan S. & Ballot E. 2015. A model to take advantage of Physical Internet for vendor inventory management. IFACPapersOnLine 48(3) 1990-1995.12. Merkuryev Y. A. Petuhova J. J. Van Landeghem R. & Vansteenkiste S. Simulation-based analysis of the bullwhip effect under different information sharing strategies. In Proceedings 14th European Simulation Symposium. Germany Dresden. 2002 pp. 294– 299.13. Prasoon R. Agarwal M. & Kumar A. 2017. Replenishment Policy in a Two-Echelon Supply Chain: An Analysis Using DiscreteEvent Simulation. International Journal of Business Analytics and Intelligence 5(2) 37.14. Cannella S. Dominguez R. Framinan J. M. & Bruccoleri M. 2018. Demand sharing inaccuracies in supply chains: A simulation study. Complexity.15. Agarwal A. 2018. Validation of Inventory models for Singleechelon Supply Chain using Discrete-event Simulation. arXiv preprint arXiv:1806.07427.16. Banerjee A. Burton J. & Banerjee S. 2003. A simulation study of lateral shipments in single supplier multiple buyers supply chain networks. International Journal of Production Economics 81 103- 114.17. Tiacci L. & Saetta S. 2011. Reducing the mean supply delay of spare parts using lateral transshipments policies. International Journal of Production Economics 133(1) 182-191.18. Tlili M. Moalla M. & Campagne J. P. 2012. The transshipment problem in a two-echelon multi-location inventory system with lost sales. International Journal of Production Research 50(13) 3547-3559.19. Firouz M. Keskin B. B. & Melouk S. H. 2017. An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments. Omega 70 77-93.20. Yan B. & Liu L. 2018. Simulation of multi-echelon supply chain inventory transshipment models at different levels. Simulation 94(7) 563-575.21. Kellner F. & Igl J. 2015. Greenhouse gas reduction in transport: analyzing the carbon dioxide performance of different freight forwarder networks. Journal of Cleaner Production 99 177-191.

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1

Source

Celal Bayar Üniversitesi Fen Bilimleri Dergisi

Volume

15

Issue

4

Start Page

385

End Page

392
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