Advertisement

Environmental and economic issues arising from the pooling of SMEs’ supply chains: case study of the food industry in western France

  • Shenle Pan
  • Eric Ballot
  • Frédéric Fontane
  • Driss Hakimi
Article

Abstract

Supply chains pooling is an emergent strategy for improving logistical performance. The pooling concept consists in transferring the effort of coordination for consolidating independent operators’ flows towards an ad hoc pooled system. This organisation results from a design of a pooled logistics network by merging different supply chains to share transport and logistics resources in order to improve logistics performance. In this case study, the pooling concept is applied to a collection of small and medium-sized western France food suppliers serving the same retail chain. In order to demonstrate the efficiency of the pooling, the existing transport organisation was compared to various pooling scenarios. The methodology consisted in accessing a current situation through a survey of the flow of goods at one of the main distribution centre of the studied supply network, then comparing this situation with three other pooling scenarios. Using supply network optimisation models, these scenarios were assessed considering cost and CO2 emission levels. This study demonstrates the interest of transport pooling in the case independent shipping networks of Small and Medium Enterprises compared to the partially know existing strategies adopted by logistics service providers for less than truckload shipments. Moreover, it suggests that there is no dominant supply organisation and that transport pooling is a new stimulus for network design. These results also bring new research perspectives for generalisation of pooling and gain sharing within large coalitions.

Keywords

Supply chains pooling Sustainability Supply network design problem CO2 emissions Transport 

Notes

Acknowledgments

We appreciate the support of the French Enterprises and Entrepreneurs Federation (FEEF) in this research. We also thank the Agence de l’environnement et de la maîtrise de l’énergie (ADEME).

References

  1. Ahuja RK, Magnanti TL et al (1993) Network flows: theory, algorithms, and applications. Prentice Hall, New JerseyzbMATHGoogle Scholar
  2. Apte UM, Viswanathan S (2000) Effective cross docking for improving distribution efficiencies. Int J Logist 3(3):291–302CrossRefGoogle Scholar
  3. Audy J-F, D’Amours S et al (2012) An empirical study on coalition formation and cost/savings allocation. Int J Prod Econ 136(1):13–27CrossRefGoogle Scholar
  4. Ballot E, Fontane F (2010) Reducing transportation CO2 emissions through pooling of supply networks: perspectives from a case study in French retail chains. Prod Plan Control 21(6):640–650CrossRefGoogle Scholar
  5. Bektas T, Laporte G (2011) The pollution-routing problem. Transp Res Part B Methodol 45(8):1232–1250CrossRefGoogle Scholar
  6. Bertazzi L, Speranza MG et al (1997) Minimization of logistic costs with given frequencies. Transp Res Part B Methodol 31(4):327–340CrossRefGoogle Scholar
  7. Blumenfeld DE, Burns LD et al (1985) Analyzing trade-offs between transportation, inventory and production costs on freight networks. Transp Res Part B Methodol 19(5):361–380CrossRefMathSciNetGoogle Scholar
  8. Campbell JF (1996) Hub location and the p-hub median problem. Oper Res 44(6):923–935CrossRefzbMATHMathSciNetGoogle Scholar
  9. Campbell JF, Ernst AT et al (2005) Hub arc location problems: part I: introduction and results. Manage Sci 51(10):1540–1555CrossRefzbMATHGoogle Scholar
  10. Chopra S, Meindl P (2004) Supply chain management: strategy, planning and operation. Prentice Hall, New JerseyGoogle Scholar
  11. CITEPA (2011) Emissions dans l’air en France métropolitaine—substances relatives à l’accroissement de l’effet de serre. CITEPA, ParisGoogle Scholar
  12. CNAM et ANIA (2007) Enquête nationale «La Logistique dans les PME-PMI de l’agroalimentaire», synthèse des résultats. C. N. d. A. e. M. a. A. N. d. I. Alimentaires, ParisGoogle Scholar
  13. Croxton KL, Gendron B et al (2003a) A comparison of mixed-integer programming models for nonconvex piecewise linear cost minimization problems. Manage Sci 49(9):1268–1273CrossRefzbMATHGoogle Scholar
  14. Croxton KL, Gendron B et al (2003b) Models and methods for merge-in-transit operations. Transp Sci 37(1):1–22CrossRefGoogle Scholar
  15. Croxton KL, Gendron B et al (2007) Variable disaggregation in network flow problems with piecewise linear costs. Oper Res 55(1):146–157CrossRefzbMATHMathSciNetGoogle Scholar
  16. Cruijssen F, Salomon M (2004) Empirical study: order sharing between transportation companies may result in cost reductions between 5 to 15 percent. CentER Discussion Paper: 2004-80Google Scholar
  17. Cruijssen F, Cools M et al (2007) Horizontal cooperation in logistics: opportunities and impediments. Transp Res Part E Logist Transp Rev 43(2):129–142CrossRefGoogle Scholar
  18. Daganzo CF (2005) Logistics systems analysis. Springer, BerlinGoogle Scholar
  19. Daskin MS (1995) Network and discrete location: models, algorithms, and applications. Wiley, LondonCrossRefzbMATHGoogle Scholar
  20. De Boissieu C (2006) Rapport du Groupe de travail “Division par quatre des émissions de gaz à effet de serre de la France à l’horizon 2050” sous la présidence de Christian de Boissieu. Paris, Ministère de l’Ecologie et du Développement Durable, Ministère de l’Economie, des Finances et de l’IndustrieGoogle Scholar
  21. Ergun Ö, Kuyzu G et al (2007) Shipper collaboration. Comput Oper Res 34(6):1551–1560CrossRefzbMATHGoogle Scholar
  22. Eurostat (2007) Panorama of transport. Office for Official Publications of the European Communities, BelgiumGoogle Scholar
  23. Frisk M, Göthe-Lundgren M et al (2010) Cost allocation in collaborative forest transportation. Eur J Oper Res 205(2):448–458CrossRefzbMATHGoogle Scholar
  24. Groothedde B, Ruijgrok C et al (2005) Towards collaborative, intermodal hub networks: a case study in the fast moving consumer goods market. Transp Res Part E Logist Transp Rev 41(6):567–583CrossRefGoogle Scholar
  25. Guéret C, Prins C et al (2002) Applications of optimization with Xpress-MP. Dash Optimization Ltd, ParisGoogle Scholar
  26. Günther H-O, Seiler T (2009) Operative transportation planning in consumer goods supply chains. Flex Serv Manuf J 21(1):51–74. doi: 10.1007/s10696-010-9060-5 Google Scholar
  27. Hall RW (1987) Consolidation strategy: inventory, vehicles and terminals. J Bus Logist 8(2):57–73Google Scholar
  28. Harrison A, van Hoek RI (2005) Logistics management and strategy. Prentice Hall, New JerseyGoogle Scholar
  29. Hickman J, Hassel D et al (1999) Methodology for calculating transport emissions and energy consumption (Report for the Projet MEET). Transport Research Laboratory, EdinburghGoogle Scholar
  30. Joumard R (1999) Methods of estimation of atmospheric emissions from transport: European scientist network and scientific state-of-the art COST 319 final report. Bron, INRETS, p 158Google Scholar
  31. Kameshwaran S, Narahari Y (2007) Nonconvex piecewise linear knapsack problems. Eur J Oper Res 192(1):56–68CrossRefMathSciNetGoogle Scholar
  32. Kara I, Laporte G et al (2004) A note on the lifted Miller-Tucker-Zemlin subtour elimination constraints for the capacitated vehicle routing problem. Eur J Oper Res 158(3):793–795CrossRefzbMATHMathSciNetGoogle Scholar
  33. Langevin A, Mbaraga P et al (1996) Continuous approximation models in freight distribution: an overview. Transp Res Part B Methodol 30(3):163–188CrossRefGoogle Scholar
  34. Léonardi J, Baumgartner M (2004) CO2 efficiency in road freight transportation: status quo, measures and potential. Transp Res Part D 9(6):451–464CrossRefGoogle Scholar
  35. Ljungberg D, Gebresenbet G (2005) Mapping out the potential for coordinated goods distribution in city centres: the case of Uppsala. Int J Transp Manag 2(3–4):161–172Google Scholar
  36. McKinnon A (2000) Sustainable distribution: opportunities to improve vehicle loading. UNEP Industry and Environment, October–December 2000, pp 26–30Google Scholar
  37. McKinnon A, Ge Y et al (2003) Analysis of transport efficiency in the UK food supply chain. L. R. Centre and S. o. M. a. Languages. Edinburgh, p 38Google Scholar
  38. Meuffels W, Fleuren H et al (2010) Enriching the tactical network design of express service carriers with fleet scheduling characteristics. Flex Serv Manuf J 22(1):3–35. doi: 10.1007/s10696-010-9066-z
  39. O’Kelly ME, Miller HJ (1994) The hub network design problem: a review and synthesis. J Transp Geogr 2(1):31–40CrossRefGoogle Scholar
  40. Özener OÖ, Ergun Ö et al (2011) Lane-exchange mechanisms for truckload carrier collaboration. Transp Sci 45(1):1–17. doi: 10.1287/trsc.1100.0327 Google Scholar
  41. Pan S, Ballot E et al (2010) The reduction of greenhouse gas emissions from freight transport by pooling supply chains. Int J Prod Econ (in press). Accepted Manuscript. doi: 10.1016/j.ijpe.2010.04.041
  42. Piecyk MI, McKinnon AC (2010) Forecasting the carbon footprint of road freight transport in 2020. Int J Prod Econ 128(1):31–42CrossRefGoogle Scholar
  43. Pooley J, Stenger AJ (1992) Modeling and evaluation shipment consolidation in a logistics system. J Bus Logist 13(2):153–174Google Scholar
  44. Toth P, Vigo D (2002) Models, relaxations and exact approaches for the capacitated vehicle routing problem. Discrete Appl Math 123(1–3):487–512CrossRefzbMATHMathSciNetGoogle Scholar
  45. Tyan JC, Wang F-K et al (2003) An evaluation of freight consolidation policies in global third party logistics. Omega 31(1):55–62CrossRefGoogle Scholar
  46. Ubeda S, Arcelus FJ et al (2011) Green logistics at Eroski: a case study. Int J Prod Econ 131(1):44–51CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Shenle Pan
    • 1
  • Eric Ballot
    • 1
  • Frédéric Fontane
    • 2
  • Driss Hakimi
    • 3
  1. 1.Centre de Gestion Scientifique (CGS)Mines ParisTechParis Cedex 06France
  2. 2.Centre de CAO-Robotique (CAOR), Mathématiques et SystèmesMines ParisTechParis Cedex 06France
  3. 3.Interuniversity Research Center on Enterprise Networks, Logistics and Transportation (CIRRELT), Faculty of Administration SciencesUniversité LavalQuebecCanada

Personalised recommendations