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Modeling the synergy level in a vertical collaborative supply chain through the IMP interaction model and DEA framework

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  • Edgar Alfonso
  • Dusko Kalenatic
  • Cesar López

Abstract

This work develops a mathematical programming model that characterizes the main variables present in the interaction dynamics of each agent in a collaborative vertical logistical system, such as a supply chain, and measures the synergy level of such system. The model is based on the interaction model developed by the IMP (Industrial Marketing and Purchasing) group and also on the DEA (Data Envelopment Analysis) framework. The basics of these two approaches allow modeling of the characteristics of an agent as well as the collaborative relationships with other agents within the chain. The model was validated using information of supply chain of leather and its products, classified by DANE (Departamento Nacional de Estadistica—Colombia) as the sector CIIU323. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Edgar Alfonso & Dusko Kalenatic & Cesar López, 2010. "Modeling the synergy level in a vertical collaborative supply chain through the IMP interaction model and DEA framework," Annals of Operations Research, Springer, vol. 181(1), pages 813-827, December.
    • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:813-827:10.1007/s10479-010-0694-1
    DOI: 10.1007/s10479-010-0694-1
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    References listed on IDEAS

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    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    3. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
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    Cited by:

    1. Zhongbao Zhou & Mei Wang & Hui Ding & Chaoqun Ma & Wenbin Liu, 2013. "Further study of production possibility set and performance evaluation model in supply chain DEA," Annals of Operations Research, Springer, vol. 206(1), pages 585-592, July.
    2. Cinaroglu, Songul, 2021. "Changes in hospital efficiency and size: An integrated propensity score matching with data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    3. Sebastian Lozano & Belarmino Adenso-Diaz, 2018. "Network DEA-based biobjective optimization of product flows in a supply chain," Annals of Operations Research, Springer, vol. 264(1), pages 307-323, May.

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