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On returns and network configuration in supply chain dynamics

Author

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  • Dominguez, Roberto
  • Cannella, Salvatore
  • Framinan, Jose M.

Abstract

This research focuses on how two common modeling assumptions in the Bullwhip Effect (BWE) literature (i.e., assuming the return of the excess of goods and assuming a serial network) may distort the results obtained. We perform a robust design of experiments where the return condition (return vs. no return) and the configuration of the Supply Chain Network (SCN) (serial vs. divergent) are systematically analyzed. We find an important interaction between these assumptions: the impact of returns on the BWE strongly depends on the SCN configuration. This study highlights the importance of accurately modeling SCNs to properly assess SCNs managers.

Suggested Citation

  • Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2015. "On returns and network configuration in supply chain dynamics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 152-167.
  • Handle: RePEc:eee:transe:v:73:y:2015:i:c:p:152-167
    DOI: 10.1016/j.tre.2014.11.008
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    References listed on IDEAS

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    1. Disney, Stephen M. & Lambrecht, Marc R., 2008. "On Replenishment Rules, Forecasting, and the Bullwhip Effect in Supply Chains," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 2(1), pages 1-80, April.
    2. Zotteri, Giulio, 2013. "An empirical investigation on causes and effects of the Bullwhip-effect: Evidence from the personal care sector," International Journal of Production Economics, Elsevier, vol. 143(2), pages 489-498.
    3. Lalwani, Chandra S. & Disney, Stephen M. & Towill, Denis R., 2006. "Controllable, observable and stable state space representations of a generalized order-up-to policy," International Journal of Production Economics, Elsevier, vol. 101(1), pages 172-184, May.
    4. Geary, S. & Disney, S.M. & Towill, D.R., 2006. "On bullwhip in supply chains--historical review, present practice and expected future impact," International Journal of Production Economics, Elsevier, vol. 101(1), pages 2-18, May.
    5. Machuca, José A. D. & Barajas, Rafael P., 2004. "The impact of electronic data interchange on reducing bullwhip effect and supply chain inventory costs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 40(3), pages 209-228, May.
    6. Mizgier, Kamil J. & Wagner, Stephan M. & Holyst, Janusz A., 2012. "Modeling defaults of companies in multi-stage supply chain networks," International Journal of Production Economics, Elsevier, vol. 135(1), pages 14-23.
    7. Carlo Altomonte & Filippo Di Mauro & Gianmarco I. P. Ottaviano & Armando Rungi & Vincent Vicard, 2012. "Global Value Chains During the Great Trade Collapse: A Bullwhip Effect?," CEP Discussion Papers dp1131, Centre for Economic Performance, LSE.
    8. Towill, Denis R. & Zhou, Li & Disney, Stephen M., 2007. "Reducing the bullwhip effect: Looking through the appropriate lens," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 444-453, July.
    9. Disney, S. M. & Naim, M. M. & Potter, A., 2004. "Assessing the impact of e-business on supply chain dynamics," International Journal of Production Economics, Elsevier, vol. 89(2), pages 109-118, May.
    10. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    11. Trapero, Juan R. & Kourentzes, N. & Fildes, R., 2012. "Impact of information exchange on supplier forecasting performance," Omega, Elsevier, vol. 40(6), pages 738-747.
    12. Sucky, Eric, 2009. "The bullwhip effect in supply chains--An overestimated problem?," International Journal of Production Economics, Elsevier, vol. 118(1), pages 311-322, March.
    13. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    14. Miragliotta, Giovanni, 2006. "Layers and mechanisms: A new taxonomy for the Bullwhip Effect," International Journal of Production Economics, Elsevier, vol. 104(2), pages 365-381, December.
    15. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    16. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    17. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"," Management Science, INFORMS, vol. 50(12_supple), pages 1887-1893, December.
    18. Robert L. Bray & Haim Mendelson, 2012. "Information Transmission and the Bullwhip Effect: An Empirical Investigation," Management Science, INFORMS, vol. 58(5), pages 860-875, May.
    19. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 50(12_supple), pages 1875-1886, December.
    20. Haughton, Michael A., 2009. "Distortional Bullwhip Effects on carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 172-185, January.
    21. Chatfield, Dean C. & Pritchard, Alan M., 2013. "Returns and the bullwhip effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 159-175.
    22. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2004. "The impact of information enrichment on the Bullwhip effect in supply chains: A control engineering perspective," European Journal of Operational Research, Elsevier, vol. 153(3), pages 727-750, March.
    23. Cantor, David E. & Katok, Elena, 2012. "Production smoothing in a serial supply chain: A laboratory investigation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 781-794.
    24. repec:ebd:wpaper:148 is not listed on IDEAS
    25. repec:dau:papers:123456789/11427 is not listed on IDEAS
    26. Rachel Croson & Karen Donohue, 2006. "Behavioral Causes of the Bullwhip Effect and the Observed Value of Inventory Information," Management Science, INFORMS, vol. 52(3), pages 323-336, March.
    27. Nepal, Bimal & Murat, Alper & Babu Chinnam, Ratna, 2012. "The bullwhip effect in capacitated supply chains with consideration for product life-cycle aspects," International Journal of Production Economics, Elsevier, vol. 136(2), pages 318-331.
    28. Ouyang, Yanfeng, 2007. "The effect of information sharing on supply chain stability and the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1107-1121, November.
    29. S Cannella & A P Barbosa-Póvoa & J M Framinan & S Relvas, 2013. "Metrics for bullwhip effect analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(1), pages 1-16, January.
    30. Holweg, Matthias & Disney, Stephen & Holmström, Jan & Småros, Johanna, 2005. "Supply Chain Collaboration:: Making Sense of the Strategy Continuum," European Management Journal, Elsevier, vol. 23(2), pages 170-181, April.
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    Cited by:

    1. Chatfield, Dean C. & Pritchard, Alan M., 2018. "Crossover aware base stock decisions for service-driven systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 312-330.
    2. Dominguez, Roberto & Cannella, Salvatore & Ponte, Borja & Framinan, Jose M., 2020. "On the dynamics of closed-loop supply chains under remanufacturing lead time variability," Omega, Elsevier, vol. 97(C).
    3. Ahmed Shaban & Mohamed A. Shalaby & Giulio Di Gravio & Riccardo Patriarca, 2020. "Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand," Sustainability, MDPI, Open Access Journal, vol. 12(16), pages 1-27, August.
    4. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "Information sharing in supply chains with heterogeneous retailers," Omega, Elsevier, vol. 79(C), pages 116-132.
    5. Cannella, Salvatore & Bruccoleri, Manfredi & Framinan, Jose M., 2016. "Closed-loop supply chains: What reverse logistics factors influence performance?," International Journal of Production Economics, Elsevier, vol. 175(C), pages 35-49.
    6. Cannella, Salvatore & Dominguez, Roberto & Ponte, Borja & Framinan, Jose M., 2018. "Capacity restrictions and supply chain performance: Modelling and analysing load-dependent lead times," International Journal of Production Economics, Elsevier, vol. 204(C), pages 264-277.
    7. Ponte, Borja & Costas, José & Puche, Julio & Pino, Raúl & de la Fuente, David, 2018. "The value of lead time reduction and stabilization: A comparison between traditional and collaborative supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 165-185.
    8. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "OVAP: A strategy to implement partial information sharing among supply chain retailers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 122-136.
    9. Cannella, Salvatore & Dominguez, Roberto & Framinan, Jose M., 2017. "Inventory record inaccuracy – The impact of structural complexity and lead time variability," Omega, Elsevier, vol. 68(C), pages 123-138.

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