Modelling of strategic managerial decisions in the system of marketing logistics of enterprise
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DOIhttp://dx.doi.org/10.21511/im.15(2).2019.05
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Article InfoVolume 15 2019, Issue #2, pp. 58-70
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Integrated decisions in the system of the marketing logistics are the main resource for providing the efficient management of the value chain. Moreover, there is not a sufficient number of methodological approaches, which could use in complex the principles of the integrated modelling of decisions in the operational systems “procurement marketing – supply logistics” and “sales marketing – distribution logistics”. Considering that fact, the methodology of selecting strategic alternatives based on the integrated modeling in separate marketing logistics chains and in stage-by-stage formation of the supply chain participants has been developed in the article. The research is based on the application of the AHP method and the method of planning “dual sourcing” (70/30) for grounding the selection of the supply strategy at the market of material resources; methods of optimal planning according to Bayes criterion, linear programming and logistics modelling – for grounding the selection of the managerial decisions on the strategy of distributing the ready produce. The research covers, firstly, grounding the essence of the marketing logistics through the systemic approach to identification of its main and servicing business processes; secondly, improvement in the process of planning decisions in the procurement marketing system by adding the procedure of the logistical selection of the hierarchical estimation with a different degree of advantages in alternative supply strategies; thirdly, formation of the cascade integrated approach toward selection of the alternative distribution channels for the finished produce by estimating the complex marketing effect and application of the logistical model of optimal distribution.
- Keywords
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JEL Classification (Paper profile tab)C61, M11, M31
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References39
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Tables4
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Figures2
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- Figure 1. Business processes in the system of the marketing logistics of an enterprise
- Figure 2. Algorithm of the multi-criteria model of the strategic solution on selecting the suppliers at the market of the material resources
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- Table 1. Matrix of the logistic evaluation of criteria for choosing the suppliers at the market of the material resources
- Table 2. Modelling of the strategic decision on choosing the main suppliers at the market of material resources (“dual sourcing”)
- Table 3. Decision on selecting the main channels of distributing canned vegetable produce by the complex effect of the marketing mix (“4P”)
- Table 4. The project of the logistical decision on distributing the vegetable produce by sales channels in different months of 2019 (expected annual average loading of the production capacities)
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- Afshar, A., & Haghani, A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-Economic Planning Sciences, 46(4), 327-338.
- Arsovski, S., Todorovic, G., Lazić, Z., Arsovski, Z., Ljepava, N., & Aleksic, A. (2017). Model for selection of the best location based on fuzzy AHP and Hurwitz methods. Mathematical Problems in Engineering, 1-13.
- Barker, T. J., & Zabinsky, Z. B. (2011). A multicriteria decision making model for reverse logistics using analytical hierarchy process. Omega, 39(5), 558-573.
- Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018). Agribusiness supply chain risk management: A review of quantitative decision models. Omega, 79, 21-42.
- Bogodistov, Y., Presse, A., Krupskyi, O. P., & Sardak, S. (2017). Gendering dynamic capabilities in micro firms. RAE Revista de Administracao de Empresas, 57(3), 273-282.
- Castillo, C. N., Degamo, F. K., Gitgano, F. T., Loo, L. A., Pacaanas, S. M., Toroy, N., Ocampo, L., Sia, L., & Ocampo, C. O. (2017). Appropriate criteria set for personnel promotion across organizational levels using analytic hierarchy process (AHP). International Journal of Production Management and Engineering, 5(1), 11-22.
- Christopher, M. (1972). Logistics in its marketing context. European Journal of Marketing, 6(2), 117-123.
- Christopher, M., & Peck, H. (2011). Marketing logistics (2nd ed.) (157 p.). New York: Routledge.
- Elberegli, M. A. (2018). An integrated framework for improving supply chain performance (Doctoral dissertation). Sheffield Hallam University.
- Feduzi, A., Runde, J., & Zappia, C. (2017). De Finetti and Savage on the normative relevance of imprecise reasoning: A reply to Arthmar and Brady. History of Economic Ideas, 25(1), 211-223.
- Ficken, F. A. (2015). The simplex method of linear programming. Republication of the edition published by Holt, Rinehart and Winston. New York: Courier Dover Publications.
- Formentini, M., Ellram, L. M., Boem, M., & Da Re, G. (2018). Finding true north: Design and implementation of a strategic sourcing framework. Industrial Marketing Management, 77, 182-197.
- Gilboa, I. (2015). Rationality and the Bayesian paradigm. Journal of Economic Methodology, 22(3), 312-334.
- Hoseini Shekarabi, S. A., Gharaei, A., & Karimi, M. (2018). Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation. International Journal of Systems Science: Operations & Logistics.
- Jeanpert, S., & Paché, G. (2016). Integration process in multichannel management: from consumer decisions to supply chain strategy. Supply Chain Forum: An International Journal, 17(4), 231-245.
- Majercakova, E., & Majercak, P. (2015). Application of Clarke-Wright method for solving routing problem in distribution logistics. Logi-Scientific Journal on Transport and Logistics, 6(1), 90-99.
- Menukhova, T., & Vyushkova, A. (2017). Using of Regionalization Techniques to Select Optimal Routes Based on Criteria of Road Features. Transportation Research Procedia, 20, 436-442.
- Khalili, S. M., Jolai, F., & Torabi, S. A. (2016). Integrated production-distribution planning in two-echelon systems: a resilience view. International Journal of Production Research, 55(4), 1040-1064.
- Khmarskyi, V., & Pavlov, R. (2017). Relation between marketing expenses and bank’s financial position: Ukrainian reality. Benchmarking: An International Journal, 24(4), 903-933.
- Lecouteux, G. (2018). Bayesian game theorists and non-Bayesian players. The European Journal of the History of Economic Thought, 25(6), 1-44.
- Li, Y., Jiang, X., Zhu, H., He, X., Peeta, S., Zheng, T., & Li, Y. (2016). Multiple measures-based chaotic time series for traffic flow prediction based on Bayesian theory. Nonlinear Dynamics, 85(1), 179-194.
- Namdar, J., Li, X., Sawhney, R., & Pradhan, N. (2018). Supply chain resilience for single and multiple sourcing in the presence of disruption risks. International Journal of Production Research, 56(6), 2339-2360.
- Ni, N., Howell, B. J., & Sharkey, T. C. (2018). Modeling the impact of unmet demand in supply chain resiliency planning. Omega, 81, 1-16.
- Ponis, S. T., Gayialis, S. P., Tatsiopoulos, I. P., Panayiotou, N. A., Stamatiou, D. R. I., & Ntalla, A. C. (2015). An application of AHP in the development process of a supply chain reference model focusing on demand variability. Operational Research, 15(3), 337-357.
- Ramanathan, U. (2013). Aligning supply chain collaboration using Analytic Hierarchy Process. Omega, 41(2), 431-440.
- Rouquet, A., Henriquez, T., & Paché, G. (2018). Omni-Channel Strategies: An Exploratory Typology to Better Understand Logistical Dimensions. IUP Journal of Supply Chain Management, 15(4), 7-26.
- Saaty, R. W. (1987). The analytic hierarchy process-what it is and how it is used. Mathematical modelling, 9(3-5), 161-176.
- Safaei, A. S., Farsad, S., & Paydar, M. M. (2018). Robust bi-level optimization of relief logistics operations. Applied Mathematical Modelling, 56, 359-380.
- Sawik, T. (2016). Integrated supply, production and distribution scheduling under disruption risks. Omega, 62, 131-144.
- Shen, Y., & Willems, S. P. (2014). Modeling sourcing strategies to mitigate part obsolescence. European Journal of Operational Research, 236(2), 522-533.
- Siddh, M. M., Soni, G., Jain, R., & Sharma, M. K. (2018). Structural model of perishable food supply chain quality (PFSCQ) to improve sustainable organizational performance. Benchmarking: An International Journal, 25(7), 2272-2317.
- Spillan, J. E., Mintu-Wimsatt, A., & Kara, A. (2018). Role of logistics strategy, coordination and customer service commitment on Chinese manufacturing firm competitiveness. Asia Pacific Journal of Marketing and Logistics, 30(5), 1365-1378.
- Subramanian, C., Chandrasekaran, M., & Govind, D. S. (2010). Analyzing the buyer supplier relationship factors: an integrated modeling approach. International Journal of Management Science and Engineering Management, 5(4), 293-302.
- Vasylieva, N. (2018). Ukrainian Agricultural Contribution to the World Food Security: Economic Problems and Prospects. Montenegrin Journal of Economics, 14(4), 215-224.
- Velychko, O. (2014a). Development of infrastructural objects of providing logistics in the system of storing plant cultivation produce. Economic Annals-XXI, 1-2(1), 110-113.
- Velychko, O. (2014b). Integrated modeling of solutions in the system of distributing logistics of a fruit and vegetable cooperative. Business: Theory and Practice / Verslas: Teorija ir Praktika, 15(4), 362-370.
- Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289.
- Yatsiv, I., & Kolodiichuk, V. (2017). Formation of social responsibility of large agricultural land users in Ukraine. Economic Annals-XXI, 168, 11-12.
- Ye, F., & Li, Y. (2014). An extended TOPSIS model based on the possibility theory under fuzzy environment. Knowledge-Based Systems, 67, 263-269.