IJAT Vol.18 No.1 pp. 135-145
doi: 10.20965/ijat.2024.p0135

Research Paper:

A Discrete-Event Simulation Study of Multi-Objective Sales and Operation Planning Under Demand Uncertainty: A Case of the Ethiopian Automotive Industry

Yigedeb Abay ORCID Icon, Toshiya Kaihara ORCID Icon, and Daisuke Kokuryo ORCID Icon

Graduate School of System Informatics, Kobe University
1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo 657-8501, Japan

Corresponding author

July 21, 2023
October 16, 2023
January 5, 2024
sales and operation planning, supply chain planning, multi-objective, discrete-event simulation, Ethiopian automotive industry

Sales and operation planning is one of the major categories of supply chain planning that enables the balancing of demand with supply through the integration of internal functions as well as external supply chain members. The major issues are its large scale, dynamic, multi-objective nature and presence of uncertain parameters. Handling uncertainty, extending the level of integration, enhancing collaboration, and contextualization of the models already developed in different industrial situations are the gaps identified in the literature. This research aims to develop a discrete-event simulation model from the literature in the context of the Ethiopian automotive industry and extend the level of collaboration to suppliers and customers. The industry’s sales and operation planning process is surveyed to develop the model as a decision support system that can be utilized for understanding the system behavior, evaluation of manufacturing flexibility, and inventory control policies. The research findings demonstrate that the customer service level and total profit can be significantly improved through the proposed joint primary and negotiated backup supply policy with price revision. Managerial implications that are expected to improve the technical capability of Ethiopian automotive industries are also highlighted.

Cite this article as:
Y. Abay, T. Kaihara, and D. Kokuryo, “A Discrete-Event Simulation Study of Multi-Objective Sales and Operation Planning Under Demand Uncertainty: A Case of the Ethiopian Automotive Industry,” Int. J. Automation Technol., Vol.18 No.1, pp. 135-145, 2024.
Data files:
  1. [1] J. Olhager, “Evolution of operations planning and control: From production to supply chains,” Int. J. Prod. Res., Vol.51, Nos.23-24, pp. 6836-6843, 2013.
  2. [2] P. Jonsson and J. Holmström, “Future of supply chain planning: Closing the gaps between practice and promise,” Int. J. Phys. Distrib. Logist. Manag., Vol.46, No.1, pp. 62-81, 2016.
  3. [3] J. A. Grimson, and D. F. Pyke, “Sales and operations planning: An exploratory study and framework,” Int. J. Logist. Manag., Vol.18, No.3, pp. 322-346, 2007.
  4. [4] H. Dittfeld, K. Scholten, and D. P. Van Donk, “Proactively and reactively managing risks through sales & operations planning,” Int. J. Phys. Distrib. Logist. Manag., Vol.51, No.6, pp. 566-584, 2021.
  5. [5] J. Singhal and K. Singhal, “Holt, Modigliani, Muth, and Simon’s work and its role in the renaissance and evolution of operations management,” J. Oper. Manag., Vol.25, No.2, pp. 300-309, 2007.
  6. [6] J. Olhager, M. Rudberg, and J. Wikner, “Long-term capacity management: Linking the perspectives from manufacturing strategy and sales and operations planning,” Int. J. Prod. Econ., Vol.69, No.2, pp. 215-225, 2001.
  7. [7] T. Wallace and B. Stahl, “The demand planning process in executive S&OP,” J. Bus. Forecast., Vol.27, No.3, pp. 19-23, 2008.
  8. [8] D. F. Pereira, J. F. Oliveira, and M. A. Carravilla, “Tactical sales and operations planning: A holistic framework and a literature review of decision-making models,” Int. J. Prod. Econ., Vol.228, 107695, 2020.
  9. [9] L. L. Lim, G. Alpan, and B. Penz, “Reconciling sales and operations management with distant suppliers in the automotive industry: A simulation approach,” Int. J. Prod. Econ., Vol.151, pp. 20-36, 2014.
  10. [10] D. Näslund and H. Hulthen, “Supply chain management integration: A critical analysis,” Benchmarking: An Int. J., Vol.19, Nos.4/5, pp. 481-501, 2012.
  11. [11] S. H. Goh and S. Eldridge, “Sales and operations planning: The effect of coordination mechanisms on supply chain performance,” Int. J. Prod. Econ., Vol.214, pp. 80-94, 2019.
  12. [12] Y. Feng, S. D’Amours, and R. Beauregard, “Simulation and performance evaluation of partially and fully integrated sales and operations planning,” Int. J. Prod. Res., Vol.48, No.19, pp. 5859-5883, 2010.
  13. [13] Y. Nemati, M. Madhoshi, A. S. Ghadikolaei, “The effect of sales and operations planning (S&OP) on supply chain’s total performance: A case study in an Iranian dairy company,” Comput. Chem. Eng., Vol.104, pp. 323-338, 2017.
  14. [14] J. Mula, R. Poler, J. P. García-Sabater, and F. C. Lario, “Models for production planning under uncertainty: A review,” Int. J. Prod. Econ., Vol.103, No.1, pp. 271-285, 2006.
  15. [15] R. P. Burrows III, “Demand driven S&OP: A sharp departure from the traditional ERP approach,” J. Bus. Forecast., Vol.26, No.3, pp. 4-13, 2007.
  16. [16] S. C. Graves, “Uncertainty and production planning,” K. G. Kempf, P. Keskinocak, and R. Uzsoy (Eds.), “Planning Production and Inventories in the Extended Enterprise: A State of the Art Handbook, Vol.1,” pp. 83-101, Springer, 2011.
  17. [17] E. M. Frazzon, A. Albrecht, M. Pires, E. Israel, M. Kück, and M. Freitag, “Hybrid approach for the integrated scheduling of production and transport processes along supply chains,” Int. J. Prod. Res., Vol.56, No.5, pp. 2019-2035, 2019.
  18. [18] A. M. Sánchez and M. P. Pérez, “Supply chain flexibility and firm performance: A conceptual model and empirical study in the automotive industry,” Int. J. Oper. Prod. Manag., Vol.25, No.7, pp. 681-700, 2005.
  19. [19] L. L. Lim, G. Alpan, and B. Penz, “A simulation-optimization approach for sales and operations planning in build-to-order industries with distant sourcing: Focus on the automotive industry,” Comput. Ind. Eng., Vol.112, pp. 469-482, 2017.
  20. [20] R. Aiassi, S. M. Sajadi, S. M. Hadji-Molana, and A. Zamani-Babgohari, “Designing a stochastic multi-objective simulation-based optimization model for sales and operations planning in built-to-order environment with uncertain distant outsourcing,” Simul. Model. Pract. Theory, Vol.104, 102103, 2020.
  21. [21] M. Narasimha, R. Rejikumar, and K. Sridhar, “Need for strengthening automobile industry in Ethiopia,” Int. J. of Mod. Eng. Res., Vol.3, No.3, pp. 1442-1446, 2013.
  22. [22] G. Sisay, D. Kitaw, F. Ebinger, and K. Jilcha, “Developing integrated continuous improvement model for competitiveness of Ethiopian automotive industry,” Eur. Online J. Nat. Soc. Sci., Vol.10, No.2, pp. 223-247, 2021.
  23. [23] H. Rashidi, “Discrete simulation software: A survey on taxonomies,” J. of Simul., Vol.11, No.2, pp. 174-184, 2017.
  24. [24] S. V. Sridharan, W. L. Berry, and V. Udayabhanu, “Measuring master production schedule instability under rolling planning horizons,” Decis. Sci., Vol.19, No.1, pp. 147-166, 1988.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Feb. 19, 2024