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Supply Chain Risks in Supply Chain Performance

  • Liliana Avelar-SosaEmail author
  • Jorge Luis García-Alcaraz
  • Aide Aracely Maldonado-Macías
Chapter
Part of the Management and Industrial Engineering book series (MINEN)

Abstract

As previously mentioned, the goal of this book is to assess the effects of manufacturing practices and risk factors on supply chain performance. This chapter introduces a series of structural equation models to assess the relationships between three types of supply chain risk factors—supply risks, demand risks, production process risks—and supply chain performance indices. The models are measured and tested as described in the methodology chapter.

References

  1. Alonso-Ayuso A, Escudero LF, Guignard M, Weintraub A (2017) Risk management for forestry planning under uncertainty in demand and prices. Eur J Oper Res.  https://doi.org/10.1016/j.ejor.2017.12.022CrossRefzbMATHGoogle Scholar
  2. Altendorfer K (2017) Relation between lead time dependent demand and capacity flexibility in a two-stage supply chain with lost sales. Int J Prod Econ 194:13–24.  https://doi.org/10.1016/j.ijpe.2017.05.007CrossRefGoogle Scholar
  3. Arıkan E, Fichtinger J, Ries JM (2014) Impact of transportation lead-time variability on the economic and environmental performance of inventory systems. Int J Prod Econ 157:279–288.  https://doi.org/10.1016/j.ijpe.2013.06.005CrossRefGoogle Scholar
  4. Avelar-Sosa L, García-Alcaraz JL, Castrellón-Torres JP (2014) The effects of some risk factors in the supply chains performance: a case of study. J Appl Res Technol 12:958–968.  https://doi.org/10.1016/S1665-6423(14)70602-9CrossRefGoogle Scholar
  5. Bhattacharyya K, Guiffrida AL (2015) An optimization framework for improving supplier delivery performance. Appl Math Model 39:3771–3783.  https://doi.org/10.1016/j.apm.2014.12.004MathSciNetCrossRefGoogle Scholar
  6. Bhattacharyya K, Datta P, Offodile OF (2010) The contribution of third-party indices in assessing global operational risks. J Supply Chain Manag 46:25–43.  https://doi.org/10.1111/j.1745-493X.2010.03204.xCrossRefGoogle Scholar
  7. Briskorn D, Zeise P, Packowski J (2016) Quasi-fixed cyclic production schemes for multiple products with stochastic demand. Eur J Oper Res 252:156–169.  https://doi.org/10.1016/j.ejor.2016.01.016CrossRefzbMATHGoogle Scholar
  8. Chaharsooghi SK, Heydari J (2010) LT variance or LT mean reduction in supply chain management: which one has a higher impact on SC performance? Int J Prod Econ 124:475–481.  https://doi.org/10.1016/j.ijpe.2009.12.010CrossRefGoogle Scholar
  9. Chen J, Sohal AS, Prajogo DI (2013) Supply chain operational risk mitigation: a collaborative approach. Int J Prod Res 51:2186–2199.  https://doi.org/10.1080/00207543.2012.727490CrossRefGoogle Scholar
  10. Chopra S, Reinhardt G, Dada M (2004) The effect of lead time uncertainty on safety stocks. Decis Sci 35:1–24.  https://doi.org/10.1111/j.1540-5414.2004.02332.xCrossRefGoogle Scholar
  11. Delbufalo E (2015) Subjective trust and perceived risk influences on exchange performance in supplier–manufacturer relationships. Scand J Manag 31:84–101.  https://doi.org/10.1016/j.scaman.2014.06.002CrossRefGoogle Scholar
  12. Germain R, Claycomb C, Dröge C (2008) Supply chain variability, organizational structure, and performance: the moderating effect of demand unpredictability. J Oper Manag 26:557–570.  https://doi.org/10.1016/j.jom.2007.10.002CrossRefGoogle Scholar
  13. Giri BC (2011) Managing inventory with two suppliers under yield uncertainty and risk aversion. Int J Prod Econ 133:80–85.  https://doi.org/10.1016/j.ijpe.2010.09.015CrossRefGoogle Scholar
  14. He J, Ma C, Pan K (2017) Capacity investment in supply chain with risk averse supplier under risk diversification contract. Transp Res Part E: Logist Transp Rev 106:255–275.  https://doi.org/10.1016/j.tre.2017.08.005CrossRefGoogle Scholar
  15. Ho W, Xu X, Dey PK (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur J Oper Res 202:16–24.  https://doi.org/10.1016/j.ejor.2009.05.009CrossRefzbMATHGoogle Scholar
  16. Hong YS, Huh WT, Kang C (2017) Sourcing assemble-to-order inventories under supplier risk uncertainty. Omega 66:1–14.  https://doi.org/10.1016/j.omega.2015.06.011CrossRefGoogle Scholar
  17. Huber J, Gossmann A, Stuckenschmidt H (2017) Cluster-based hierarchical demand forecasting for perishable goods. Expert Syst Appl 76:140–151.  https://doi.org/10.1016/j.eswa.2017.01.022CrossRefGoogle Scholar
  18. Izar Landeta JM, Ynzunza Cortés CB, Zermeño Pérez E (2015) Cálculo del punto de reorden cuando el tiempo de entrega y la demanda están correlacionados. Contaduría y administración 60:864–873CrossRefGoogle Scholar
  19. Jian M, Fang X, Jin L-Q, Rajapov A (2015) The impact of lead time compression on demand forecasting risk and production cost: a newsvendor model. Transp Res Part E: Logist Transp Rev 84:61–72.  https://doi.org/10.1016/j.tre.2015.10.006CrossRefGoogle Scholar
  20. Johansson A, Pejryd L, Christiernin LG (2016) Production support model to manage market demand volatility risks. Procedia CIRP 57:664–668.  https://doi.org/10.1016/j.procir.2016.11.115CrossRefGoogle Scholar
  21. Jüttner U, Peck H, Christopher M (2003) Supply chain risk management: outlining an agenda for future research. Int J Logist Res Appl 6:197–210.  https://doi.org/10.1080/13675560310001627016CrossRefGoogle Scholar
  22. Kourentzes N, Rostami-Tabar B, Barrow DK (2017) Demand forecasting by temporal aggregation: using optimal or multiple aggregation levels? J Bus Res 78:1–9.  https://doi.org/10.1016/j.jbusres.2017.04.016CrossRefGoogle Scholar
  23. Lockamy A, McCormack K (2010) Analysing risks in supply networks to facilitate outsourcing decisions. Int J Prod Res 48:593–611.  https://doi.org/10.1080/00207540903175152CrossRefzbMATHGoogle Scholar
  24. Mokhtar S, Bahri PA, Moayer S, James A (2017) A novel decision-making approach for supplier selection under risks. In: Espuña A, Graells M, Puigjaner L (eds) Computer aided chemical engineering, vol 40. Elsevier, ‎Amsterdam, pp 1267–1272.  https://doi.org/10.1016/B978-0-444-63965-3.50213-0CrossRefGoogle Scholar
  25. Mosaad SAA, Issa UH, Hassan MS (2018) Risks affecting the delivery of HVAC systems: Identifying and analysis. J Build Eng 16:20–30.  https://doi.org/10.1016/j.jobe.2017.12.004CrossRefGoogle Scholar
  26. Mumtaz U, Ali Y, Petrillo A (2018) A linear regression approach to evaluate the green supply chain management impact on industrial organizational performance. Sci Total Environ 624:162–169.  https://doi.org/10.1016/j.scitotenv.2017.12.089CrossRefGoogle Scholar
  27. Neeraj A, Neha G (2015) Measuring retail supply chain performance: theoretical model using key performance indicators (KPIs). Benchmark Int J 22:135–166.  https://doi.org/10.1108/BIJ-05-2012-0034CrossRefGoogle Scholar
  28. Quigley J, Walls L, Demirel G, MacCarthy BL, Parsa M (2018) Supplier quality improvement: the value of information under uncertainty. Eur J Oper Res 264:932–947.  https://doi.org/10.1016/j.ejor.2017.05.044MathSciNetCrossRefzbMATHGoogle Scholar
  29. Schmenner RW (2004a) Service businesses and productivity. Decis Sci 35:333–347.  https://doi.org/10.1111/j.0011-7315.2004.02558.xCrossRefGoogle Scholar
  30. Schmenner W (2004b) Service businesses and productivity. Decis Sci 35:333–347.  https://doi.org/10.1111/j.0011-7315.2004.02558.xCrossRefGoogle Scholar
  31. Shepherd C, Günter H (2011) Measuring supply chain performance: current research and future directions. In: Fransoo JC, Waefler T, Wilson JR (eds) Behavioral operations in planning and scheduling. Springer, Berlin, pp 105–121.  https://doi.org/10.1007/978-3-642-13382-4_6CrossRefGoogle Scholar
  32. Singh A (2014) Supplier evaluation and demand allocation among suppliers in a supply chain. J Purch Supply Manag 20:167–176.  https://doi.org/10.1016/j.pursup.2014.02.001CrossRefGoogle Scholar
  33. Song J-S, Zhang H, Hou Y, Wang M (2009) The effect of lead time and demand uncertainties in (r, q) inventory systems. Oper Res 58:68–80.  https://doi.org/10.1287/opre.1090.0711MathSciNetCrossRefzbMATHGoogle Scholar
  34. Srai JS, Badman C, Krumme M, Futran M, Johnston C (2015) Future supply chains enabled by continuous processing—opportunities and challenges, May 20–21, 2014 continuous manufacturing symposium. J Pharm Sci 104:840–849.  https://doi.org/10.1002/jps.24343CrossRefGoogle Scholar
  35. Sucky E (2009) The bullwhip effect in supply chains—An overestimated problem?. Int J Prod Econ 118(1):311–322.  https://doi.org/10.1016/j.ijpe.2008.08.035CrossRefGoogle Scholar
  36. Tanaka K, Akimoto H, Inoue M (2012) Production risk management system with demand probability distribution. Adv Eng Inform 26:46–54.  https://doi.org/10.1016/j.aei.2011.07.002CrossRefGoogle Scholar
  37. Thun J-H, Hoenig D (2011) An empirical analysis of supply chain risk management in the German automotive industry. Int J Prod Econ 131:242–249.  https://doi.org/10.1016/j.ijpe.2009.10.010CrossRefGoogle Scholar
  38. Torres-Ruiz A, Ravindran AR (2018) Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. J Clean Prod 172:4478–4493.  https://doi.org/10.1016/j.jclepro.2017.10.304CrossRefGoogle Scholar
  39. Türk S, Özcan E, John R (2017) Multi-objective optimisation in inventory planning with supplier selection. Expert Syst Appl 78:51–63.  https://doi.org/10.1016/j.eswa.2017.02.014CrossRefGoogle Scholar
  40. Vahidi F, Torabi SA, Ramezankhani MJ (2018) Sustainable supplier selection and order allocation under operational and disruption risks. J Clean Prod 174:1351–1365.  https://doi.org/10.1016/j.jclepro.2017.11.012CrossRefGoogle Scholar
  41. Wagner SM, Bode C (2008) An empirical examination of supply chain performance along several dimensions of risk. J Bus Logist 29:307–325.  https://doi.org/10.1002/j.2158-1592.2008.tb00081.xCrossRefGoogle Scholar
  42. Wagner Stephan M, Bode C (2011) An empirical examination of supply chain performance along several dimensions of risk. J Bus Logist 29:307–325.  https://doi.org/10.1002/j.2158-1592.2008.tb00081.xCrossRefGoogle Scholar
  43. Wang F, Fang X, Chen X, Li X (2016) Impact of inventory inaccuracies on products with inventory-dependent demand. Int J Prod Econ 177:118–130.  https://doi.org/10.1016/j.ijpe.2016.04.019CrossRefGoogle Scholar
  44. Wu C, Zhao Q, Xi M (2017) A retailer-supplier supply chain model with trade credit default risk in a supplier-Stackelberg game. Comput Ind Eng 112:568–575.  https://doi.org/10.1016/j.cie.2017.03.004CrossRefGoogle Scholar
  45. Yan X, Liu K (2009) An inventory system with two suppliers and default risk. Oper Res Lett 37:322–326.  https://doi.org/10.1016/j.orl.2009.04.007MathSciNetCrossRefzbMATHGoogle Scholar
  46. Yan B, Jin Z, Liu Y, Yang J (2018) Decision on risk-averse dual-channel supply chain under demand disruption. Commun Nonlinear Sci Numer Simul 55:206–224.  https://doi.org/10.1016/j.cnsns.2017.07.003MathSciNetCrossRefGoogle Scholar
  47. Zhao Y, Cao H (2015) Risk management on joint product development with power asymmetry between supplier and manufacturer. Int J Proj Manag 33:1812–1826.  https://doi.org/10.1016/j.ijproman.2015.08.008CrossRefGoogle Scholar
  48. Zheng S, Negenborn RR (2015) Price negotiation between supplier and buyer under uncertainty with fixed demand and elastic demand. Int J Prod Econ 167:35–44.  https://doi.org/10.1016/j.ijpe.2015.05.024CrossRefGoogle Scholar
  49. Zsidisin GA (2003) A grounded definition of supply risk. J Purch Supply Manag 9:217–224.  https://doi.org/10.1016/j.pursup.2003.07.002CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Liliana Avelar-Sosa
    • 1
    Email author
  • Jorge Luis García-Alcaraz
    • 1
  • Aide Aracely Maldonado-Macías
    • 1
  1. 1.Department of Industrial Engineering and Manufacturing, Institute of Engineering and TechnologyUniversidad Autónoma de Ciudad JuárezCiudad JuárezMexico

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