SUPPLY CHAIN COORDINATION: SCIENTIFIC AND METHODOLOGICAL APPROACHES

  • Yurii Senyk Western Ukrainian National University
Keywords: logistics coordination, transport and warehouse services, material flow, logistics service, logistics of business processes

Abstract

Progress and modernization of the productive forces of society have changed mainly the nature of economic relations and brought the ideology of service to the fore. Despite the growing interest in logistics, several issues still need to be solved regarding the peculiarities of forming the logistics services market and creating integrated logistics transport and forwarding systems. The critical task of logistics integration is to increase the degree of coordination of end-to-end material flows at all stages of their advancement, each of which has its characteristics. The logistics of transport and forwarding services bring maximum strategic benefit when all its functional links work on the integration principles. It is necessary to focus on the efficiency of the entire integrated logistics system in general, increasing the efficiency of the functioning of each link. The critical task of logistical support for transport and forwarding works is to increase the level of coordination of the end-to-end flow process at all stages of its passage. The critical task of managing integrated business processes is their logistical coordination. The primary task of supply chain coordination is to ensure maximum process optimization and minimize system changes over time. The developed system should adapt to unplanned changes and system modernization while maintaining or increasing its efficiency. An effective tool for building a transport chain and regulating it is signing a contract that will ensure the centralized work of structurally unrelated transport participants. The contractual approach allows you to dynamically change your orders in different periods, which ensures the efficient work of both the manufacturer and the buyer, who, in the case of ordering, for example, packaging materials or ingredients, can focus on changes in the end consumer's demand and effectively use their resources. With the development of computer technology and programming, the prognostic method of finding the optimal solution to the problem of product supply as a simulation is increasingly coming to the fore.

References

Sirias D., Mehra S. Quantity discount versus lead time-dependent discount in an inter-organizational supply chain. International Journal of Production Research. 2005. Vol. 43(16). Р. 3481¬3496.

Klastorin T.D., Moinzadeh K., Son J. Coordinating orders in supply chains through price discounts. IIE Transactions. 2002. Vol. 34(8). P. 679¬689.

Mishra A.K. Selective discount for supplier–buyer coordination using common replenishment epochs. European Journal of Operational Research. 2004. Vol. 153(3). P. 751-756.

Weng Z.K. The power of coordinated decisions for short-life-cycle products in a manufacturing and distribution supply chain. IIE Transactions. 1999. Vol. 31(11). P. 1037¬1049.

Cachon G.P. Managing supply chain demand variability with scheduled ordering policies. Management Science. 1999. Vol. 45 (6). P. 843-856.

Das T.K., Teng B.S. A resource based theory of strategic alliance. Journal of Management. 2000. Vol. 26 (1). P. 31¬61.

Bahinipati B.K., Kanda A., Deshmukh S.G. Coordinated supply management: review, insights, and limitations. International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management. 2009. Vol. 12:6. P. 407¬422.

Tsay A. The quantity flexibility contract and supplier-customer incentives. Management Science. 1999. Vol. 45(10). P. 1339¬1358.

Giannoccaro I., Pontrandolfo P. Supply chain coordination by revenue sharing contracts. International Journal of Production Economics. 2004. Vol. 89(2). P. 131-139.

Wang Q., Tsao D. Supply contract with bidirectional options: the buyer’s perspective. International Journal of Production Economics. 2006. Vol. 101(1). P. 30¬52.

Tibben-Lembke R.S. N-period contracts with ordering constraints and total minimum commitments: optimal and heuristic solutions. European Journal of Operational Research. 2004. Vol. 156(2). P. 353¬374.

Spinler S., Huchzermeier A. The valuation of options on capacity with cost and demand uncertainty. European Journal of Operational Research. 2006. Vol. 171(1). P. 915¬934.

Corbett C.J., DeCroix G.A. Shared-savings contracts for indirect materials in supply chains: channel profits and environmental impacts. Management Science. 2001. Vol. 47 (7). P. 881¬893.

Chen J., Xu L. Coordinated ordering decisions for short life cycle products with uncertainty in delivery time and demand. IEEE Transactions on Systems, Man, and Cybernetics. 2001. Vol. 31 (6). P. 524-532.

Sterman J. Modelling managerial behaviour: misperceptions of feedback in a dynamic decision making experiment. Management Science. 1989. Vol. 35(3). P. 321¬339.

Lee H.L, Padmanahan V., Whang S. Information distortion in a supply chain: the bullwhip effect. Management Science. 1997. Vol. 43(4). P. 546¬559.

Owens S.F., Levary R.R. Evaluating the impact of electronic data interchange on the ingredient supply chain of a food processing company. Supply Chain Management. An International Journal. 2002. Vol. 7(4). P. 200-211.

Hieber R., Hartel I. Impacts of SCM order strategies evaluated by simulation-based ‘beer game’ approach: the model, concept, and initial experiences. Production Planning & Control. 2003. Vol. 14 (2). P. 122¬134.

Jansen D.R. Simulation model of multi-compartment distribution in the catering supply chain. European Journal of Operational Research. 2001. Vol. 133 (1). P. 210¬224.

Manzini R. Simulation performance in the optimisation of the supply chain. Journal of Manufacturing Technology Management. 2005. Vol. 16(2). P. 127¬144.

Lin F.-R., Huang S.-H., Lin S.-C. Effects of information sharing on supply chain performance in electronic commerce. IEEE Transactions on Engineering Management. 2002. Vol. 49(3). P. 258¬268.

Brandolese A., Cartegni E., Cigolini R. Improving productivity by using strategic inventories: theoretical issues and field results. International Journal of Production Research. 2001. Vol. 39 (18). P. 4179¬4196.

Gjerdrum J., Shah N., Papageorgiou L.G. A combined optimization and agent-based approach to supply chain modelling and performance assessment. Production Planning & Control. 2001. Vol. 12(1). P. 81¬88.

Ng C.T., Li L.Y.O., Chakhlevitch K. Coordinated replenishments with alternative supply sources in two-level supply chains. International Journal of Production Economics. 2001. Vol. 73(3). P. 227¬240.

Jansen D.R. Simulation model of multi-compartment distribution in the catering supply chain. European Journal of Operational Research. 2001. Vol. 133 (1). P. 210¬224.

Sirias D., Mehra S. (2005). Quantity discount versus lead time-dependent discount in an inter-organizational supply chain. International Journal of Production Research, vol. 43(16), рр. 3481¬3496.

Klastorin T.D., Moinzadeh K., Son J. (2002). Coordinating orders in supply chains through price discounts. IIE Transactions, vol. 34(8), рр. 679¬689.

Mishra A.K. (2004). Selective discount for supplier–buyer coordination using common replenishment epochs. European Journal of Operational Research, vol. 153(3), рр. 751¬756.

Weng Z.K. (1999). The power of coordinated decisions for short-life-cycle products in a manufacturing and distribution supply chain. IIE Transactions, vol. 31(11), рр. 1037¬1049.

Cachon G.P. (1999). Managing supply chain demand variability with scheduled ordering policies. Management Science, vol. 45 (6), рр. 843-856.

Das T.K., Teng B.S. (2000). A resource based theory of strategic alliance. Journal of Management, vol. 26 (1), рр. 31¬61.

Bahinipati B.K., Kanda A., Deshmukh S.G. (2009). Coordinated supply management: review, insights, and limitations. International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, vol. 12:6, рр. 407¬422.

Tsay A. (1999). The quantity flexibility contract and supplier-customer incentives. Management Science, vol. 45(10), рр. 1339¬1358.

Giannoccaro I., Pontrandolfo P. (2004). Supply chain coordination by revenue sharing contracts. International Journal of Production Economics, vol. 89(2), рр. 131¬139.

Wang Q., Tsao D. (2006). Supply contract with bidirectional options: the buyer’s perspective. International Journal of Production Economics, vol. 101(1), рр. 30-52.

Tibben-Lembke R.S. (2004). N-period contracts with ordering constraints and total minimum commitments: optimal and heuristic solutions. European Journal of Operational Research, vol. 156(2), рр. 353¬374.

Spinler S., Huchzermeier A. (2006). The valuation of options on capacity with cost and demand uncertainty. European Journal of Operational Research, vol. 171(1), рр. 915¬934.

Corbett C.J., DeCroix G.A. (2001). Shared-savings contracts for indirect materials in supply chains: channel profits and environmental impacts. Management Science, vol. 47 (7), рр. 881¬893.

Chen J., Xu L. (2001). Coordinated ordering decisions for short life cycle products with uncertainty in delivery time and demand. IEEE Transactions on Systems, Man, and Cybernetics, vol. 31 (6), рр. 524¬532.

Sterman J. (1989). Modelling managerial behaviour: misperceptions of feedback in a dynamic decision making experiment. Management Science, vol. 35(3), рр. 321¬339.

Lee H.L, Padmanahan V., Whang S. (1997). Information distortion in a supply chain: the bullwhip effect. Management Science, vol. 43(4), рр. 546¬559.

Owens S.F., Levary R.R. (2002). Evaluating the impact of electronic data interchange on the ingredient supply chain of a food processing company. Supply Chain Management. An International Journal, vol. 7(4), рр. 200¬211.

Hieber R., Hartel I. (2003). Impacts of SCM order strategies evaluated by simulation-based ‘beer game’ approach: the model, concept, and initial experiences. Production Planning & Control, vol. 14 (2), рр. 122¬134.

Jansen D.R. (2001). Simulation model of multi-compartment distribution in the catering supply chain. European Journal of Operational Research, vol. 133 (1), рр. 210¬224.

Manzini R. (2005). Simulation performance in the optimisation of the supply chain. Journal of Manufacturing Technology Management, vol. 16(2), рр. 127¬144.

Lin F.-R., Huang S.-H., Lin S.-C. (2002). Effects of information sharing on supply chain performance in electronic commerce. IEEE Transactions on Engineering Management, vol. 49(3), рр. 258¬268.

Brandolese A., Cartegni E., Cigolini R. (2001). Improving productivity by using strategic inventories: theoretical issues and field results. International Journal of Production Research, vol. 39 (18), рр. 4179¬4196.

Gjerdrum J., Shah N., Papageorgiou L.G. (2001). A combined optimization and agent-based approach to supply chain modelling and performance assessment. Production Planning & Control, vol. 12(1), рр. 81¬88.

Ng C.T., Li L.Y.O., Chakhlevitch K. (2001). Coordinated replenishments with alternative supply sources in two-level supply chains. International Journal of Production Economics, vol. 73(3), рр. 227¬240.

Jansen D.R. (2001). Simulation model of multi-compartment distribution in the catering supply chain. European Journal of Operational Research, vol. 133 (1), рр. 210¬224.

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Published
2023-07-31
How to Cite
Senyk , Y. (2023). SUPPLY CHAIN COORDINATION: SCIENTIFIC AND METHODOLOGICAL APPROACHES. Digital Есопоmу and Economic Security, (7 (07), 153-159. https://doi.org/10.32782/dees.7-25