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Synergistics and Collaboration in Supply Chains: An Integrated Conceptual Framework for Simulation Modeling of Supply Chains

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Developments in Information & Knowledge Management for Business Applications

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 377))

Abstract

In this research, the author explores the approaches to simulation of supply chains’ strategic development specifically focusing on formation of cooperation strategies between supply chain partners. The objective of this paper is to suggest a conceptual scheme and stratification approaches that enable creation of a model reflecting polysystemic representation of the supply chain. The following base levels of the supply chain representation are considered: object-based, configuration/network-based, process-based, and logistics coordination levels. In the field of supply chains transformation and strategic development there is a strong need in concurrent and aligned usage of different supply chain representations. That defines the approach to building generic supply-chain representation based on composite simulation models. Depending on addressable tasks of supply chain analysis and synthesis, process and system dynamic simulation models of different degrees of detail may be used. Agent-based modeling is used to model interorganizational coordination between supply chain partners.

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References

  1. Shapiro, J.F.: Modeling the supply chain. Pacific Grove, CA: Wadsworth Group (2001)

    Google Scholar 

  2. Min, H., Zhou, G.: Supply chain modeling: past, present, and future. Comput. Ind. Eng. 43, 231–249 (2002)

    Article  Google Scholar 

  3. Tako, A.A., Robinson, S.: The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decis. Support Syst. 52, 802–815 (2012)

    Article  Google Scholar 

  4. Oliveira, J.B., Lima, R.S., Montevechi, J.A.B.: Perspectives and relationships in supply chain simulation: a systematic literature review. Simul. Model. Pract. Theory 62, 166–191 (2016)

    Article  Google Scholar 

  5. Kersten W., Saeed, M.A.: A SCOR Based Analysis of Simulation in Supply Chain Management. In: Proceedings 28th European Conference on Modeling and Simulation. Brescia, Italy (2014)

    Google Scholar 

  6. Castilho, J.A., Lang, T.E. and Peterson, D.K., Volovoi V.: Quantifying variability impacts upon supply chain performance. In: Proceedings of the 2015 Winter Simulation Conference, 1892–1903 (2015)

    Google Scholar 

  7. Fayez, M.S., Rabelo, L., Mollaghasemi, M.: Ontologies for supply chain simulation modeling. In: Proceedings of the 2005 Winter Simulation Conference, 2364–2370. IEEE, Orlando, FL. (2005)

    Google Scholar 

  8. Hennies, T., Reggelin, T., Tolujew, J., Piccut, P.A.: Mesoscopic supply chain simulation. J. Comput. Sci. 5, 463–470 (2014)

    Article  Google Scholar 

  9. Jain, S., Sigurðardóttir, S., Lindskog, E., Andersson, J., Skoogh, A., Johansson, B.: Multi-resolution modeling for supply chain sustainability analysis. In: Proceedings of the 2013 Winter Simulation Conference, 1996–2007 (2013)

    Google Scholar 

  10. Kim, W.S.: Effects of a trust mechanisms on complex adaptive supply networks: an agent-based social simulation study. J. Artif. Soc. Soc. Simul. 12(4), 2 (2009)

    Google Scholar 

  11. Long, Q.: A multi-methodological collaborative simulation for inter-organizational supply chain networks. Knowl.-Based Syst. 96, 84–95 (2016)

    Article  Google Scholar 

  12. Lychkina, N.: Simulation of dynamic supply chains. Logist. Supply Chain Manage. 6(89), 137–152 (2018)

    Google Scholar 

  13. Ponte, B., Costas, J., Puche, J., S.de la Fuente, D., Pinoa, R.: Holism versus reductionism in supply chain management: an economic analysis. Decision Supp. Syst. 86, 83–94 (2016)

    Google Scholar 

  14. Terlunen, S., Horstkemper, D., Hellingrath, B.: Adaption of the discrete rate-based simulation paradigm for tactical supply chain decisions. In: Proceedings of the 2014 Winter Simulation Conference, 2060–2071 (2014)

    Google Scholar 

  15. Palma-Mendoza, J.A.: Hybrid DES/SD simulation conceptual framework for supply chain analysis. Int. J. Data Sci. Geneva 2(3), 246–259 (2017)

    Article  Google Scholar 

  16. Chatfield, D.C., Harrison, T.P., Hayya, J.C.: SISCO: an object-oriented supply chain simulation system. Decis. Support Syst. 42(1), 422–434 (2006)

    Article  Google Scholar 

  17. Krejci, C.: Hybrid simulation modeling for humanitarian relief chain coordination. J. Hum. Logist. Supply Chain Manage. 5(3), 325–347 (2015)

    Article  Google Scholar 

  18. Persson, F., Bartoll, C., Ganovic, A., Lidberg, M., Nilsson, M., Wibaeus, J., Winge, F.: Supply chain dynamics in the SCOR Model—A simulation modeling approach. In: Proceedings of the 2012 Winter Simulation Conference, 1–12. Berlin (2012)

    Google Scholar 

  19. Behdani, B.: Evaluation of paradigms for modeling supply chains as complex socio-technical systems. In: Proceedings of the 2012 Winter Simulation Conference, 3794–3808 (2012)

    Google Scholar 

  20. Ramanathan, U.: Performance of supply chain collaboration—a simulation study. Expert Syst. Appl. 41(1), 210–220 (2014)

    Article  Google Scholar 

  21. Poniszewska-Maranda, A., Matusiak, R., Kryvinska, N., Yasar, A-UI-H.: A real-time service system in the cloud. J. Ambient Intell. Hum. Comput. 11, 961–977 (2020)

    Google Scholar 

  22. Angerhofer, B.J., Angelides, M.C.: A model and a performance measurement system for collaborative supply chains. Decis. Support Syst. 42, 283–301 (2006)

    Article  Google Scholar 

  23. Arvitrida, N.I., Robinson, S., Tako, A.A.: How do competition and collaboration affect supply chain performance. An agent based modeling approach. In: Proceedings of the 2015 Winter Simulation Conference, 218–229 (2015)

    Google Scholar 

  24. Sergeyev, V.: Supply Chain Management: Bachelor and Master Degree. Uright, Moscow (2014)

    Google Scholar 

  25. Bek, M., Bek, N., Buzulukova, E., Sheresheva, M.: Research Methodology of Network Organization. Higher School of Economics Publishing, Moscow (2011)

    Google Scholar 

  26. Choi, T.Y., Hong, Y.: Unveiling the structure of supply networks: case studies in Honda, Acura and Daimler Crysler. J. Oper. Manag. 20, 469–493 (2002)

    Article  Google Scholar 

  27. Dyer, J.H., Singh, H.: The relational view: cooperative strategy and sources of interorganizational competitive advantage. Acad. Manag. Rev. 23, 660–670 (1998)

    Article  Google Scholar 

  28. Radaev, V.: Relational exchange in supply chains and its constitutive elements. J. Econ. Sociol. 16, 81–99 (2015)

    Article  Google Scholar 

  29. Baratt, M.: Understanding the meaning of collaboration in the supply chain. Supply chain Manage. Int. J. 9(1), 30–42 (2004)

    Article  Google Scholar 

  30. Fugate, B., Sahin, F., Menzer, J.T.: Supply chain management coordination mechanisms. J. Bus. Logist. 27(2), 129–161 (2006)

    Article  Google Scholar 

  31. Lejeune, M.A., Yakova, N.: On characterizing the 4 C’s in supply chain management. J. Oper. Manag. 23(1), 81–100 (2005)

    Article  Google Scholar 

  32. Sergeyev. V., Lychkina, N.: Agent-based modelling and simulation of inter-organizational integration and coordination of supply chain participants. 2019 IEEE 21st Conf. Bus. Inform. (CBI). 2, 436–444 (2019)

    Google Scholar 

  33. Janamanchi, B., Burns, J.R., Liu, S.: Performance metric optimization advocates CPFR in supply chains: a system dynamics model based study. Cogent Bus. Manage. 3(1) (2016)

    Google Scholar 

  34. Sari, K.: On the benefits of CPFR and VMI: a comparative simulation study. Int. J. Prod. Econ. 113(2), 575–586 (2008)

    Article  Google Scholar 

  35. Lychkina, N.: Synergistics and development processes in socio-economic systems: search for effective modeling constructs. Bus. Inf. 1, 66–79 (2016)

    Article  Google Scholar 

  36. Hoshovska, O., Poplavska, Z., Kryvinska, N., Horbal, N.: Considering random factors in modeling complex microeconomic systems. Mathematics. 8(8), 1206 (2020)

    Article  Google Scholar 

  37. Lychkina, N.: Innovative paradigm of simulation and their application in management consulting, logistics and strategic management. Logist. Supply Chain Manage. 5, 28–41 (2013)

    Google Scholar 

  38. Lychkina, N.: Simulation Modeling of Economic Processes. NFRA-M, Moscow (2014)

    Google Scholar 

  39. Barnett, M.W., Miller, C.J.: Analysis of the virtual enterprise using distributed supply chain modeling and simulation: an application of e-SCOR. 2000 Winter Simulat. Conf. (WSC) 1, 352–355 (2000)

    Google Scholar 

  40. Herrmann, J.W., Lin, E., Pundoor, G.: Supply chain simulation modeling using the supply chain operations reference model. In: Proceedings of the ASME 2003 Design Engineering Technical Conference, 1–9 Chicago, Illinois, USA (2003)

    Google Scholar 

  41. Fredrik, P.: SCOR template—a simulation based dynamic supply chain analysis tool. Int. J. Prod. Econ. 131(1), 288–294 (2011)

    Article  Google Scholar 

  42. Ntabe, E.N., LeBela, L., Munsona, A.D., Santa-Eulalia, L.A.: A systematic literature re-view of the supply chain operations reference (SCOR) model application with special attention to environmental issues. Int. J. Prod. Econ. 169, 310–332 (2015)

    Article  Google Scholar 

  43. Persson, F.: SCOR template—a simulation based dynamic supply chain analysis tool. Int. J. Prod. Econ. 131(1), 288–294 (2011)

    Article  Google Scholar 

  44. Šitova, I., Pečerska, J.: A concept of simulation-based SC performance analysis using SCOR metrics. Info. Technol. Manage. Sci. 20, 85–90 (2017)

    Google Scholar 

  45. Kryvinska, N., Bickel, L.: Scenario-based analysis of IT enterprises servitization as a part of digital transformation of modern economy. J. Appl. Sci. 10(3), 1076 (2020)

    Article  Google Scholar 

  46. Forrester, J.: Industrial Dynamics. MIT Press (1961)

    Google Scholar 

  47. Sterman, J.D.: Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill (2000)

    Google Scholar 

  48. Morecroft, J.: Strategic Modelling and Business Dynamics. A Feedback Systems Approach. Wiley (2007)

    Google Scholar 

  49. Pidd, M.: Computer Simulation in Management Science. Wiley (1998)

    Google Scholar 

  50. Warren, K.: Strategic Management Dynamics. Wiley, USA (2008)

    Google Scholar 

  51. Bhattacharjee, S., Cruz, J.: Economic sustainability of closed loop supply chains: A holistic model for decision and policy analysis. Decis. Support Syst. 77, 67–86 (2015)

    Article  Google Scholar 

  52. Crowe, J., Mesabbah, M., Arisha, A.: Understanding the dynamic behaviour of three echelon retail supply chain disruptions. In Proceedings of the 2015 Winter Simulation Conference, 1948–1959 (2015)

    Google Scholar 

  53. Langroodi, R.R.P., Amiri, M.: A system dynamics modeling approach for a multi-level multi-product, multi-region supply chain under demand uncertainty. Expert Syst Appl. 51, 231–244 (2016)

    Article  Google Scholar 

  54. Grubic, T., Fan, I.-S.: Supply chain ontology: review, analysis and synthesis. Comput. Ind. 61, 776–786 (2010)

    Article  Google Scholar 

  55. Idiatullin, A.R., Lychkina, N.N.: Instrumental implementation of enterprise architecture models based on ontologies. Bus.-Inform. 5, 31–42 (2011)

    Google Scholar 

  56. Scheuermann, A., Leukel, J.: Supply chain management ontology from an ontology engineering perspective. Comput. Ind. 65, 913–923 (2014)

    Google Scholar 

  57. Lauriera, W., Poels, G.: Invariant conditions in value system simulation models. Decis. Support Syst. 56, 275–287 (2013)

    Article  Google Scholar 

  58. Lychkina, N.: Strategic development and dynamic models of supply chains: search for effective model constructions. In: Bi, Y., Kapoor, S. and Bhatia, R (eds.) Lecture Notes in Networks and System: Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016, 2, 175–185. Springer, London (2018)

    Google Scholar 

  59. Kumar, S., Nottestad, D.A.: Supply chain analysis methodology—leveraging optimization and simulation software. OR Insight. 26, 87–119 (2013)

    Article  Google Scholar 

  60. Rabelo, L., Eskandari, H., Shaalan, T., Helal, M.: Value chain analysis using hybrid simulation and AHP. Int. J. Prod. Econ. 105(2), 536–547 (2007)

    Article  Google Scholar 

  61. Santa-Eulalia, L.A., Halladjian, G., D’Amours, S., Frayret, J.M.: Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: a systematic literature review. J. Indust. Eng. Manage. 4, 624–668 (2011)

    Google Scholar 

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Correspondence to Natalia Lychkina .

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Lychkina, N. (2022). Synergistics and Collaboration in Supply Chains: An Integrated Conceptual Framework for Simulation Modeling of Supply Chains. In: Kryvinska, N., Poniszewska-Marańda, A. (eds) Developments in Information & Knowledge Management for Business Applications . Studies in Systems, Decision and Control, vol 377. Springer, Cham. https://doi.org/10.1007/978-3-030-77916-0_20

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