Assessing the impact of parameters for the last mile logistics system on creation of the added value of goods

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.142523

Keywords:

last mile logistics, transportation route, transportation cost, added value, variability

Abstract

stock load along the same transportation system. The criterion evaluates the level of gain in the added value of goods as a result of the delivery of goods within a retail network under condition of minimizing the cost of transporting one ton. We have designed an extreme plan for the full­factor experiment with three levels of parameter variation. It was determined that demand for transportation within a retail chain in a big city is discrete in character. A statistical analysis of the volumes of a transportation order has allowed us to draw a conclusion on the possibility to describe a given magnitude using a binomial distribution law. An experiment was conducted using a service polygon of the retail chain’s customers in a large city. Based on 9 constructed alternative last mile logistics systems, we investigated the influence of transportation demand variability on forming the levels of vehicles’ load along routes. The statistical data received provided the basis for calculating the cost of transporting one ton of cargo and estimating the size of the excessive added value to goods. We have assessed the level of variability in the size of the total and the mean added value of goods. It was determined that the transportation process within a retail chain can generate a gain in the total added value across the entire chain amounting to 444.5 percent (12 routes within a transportation system) with the mean value for one multi­stop route of 37.03 percent. We present assessment of the effective area of the last mile logistics, which is guaranteed under condition for a slight fluctuation in the level of vehicles’ load. This corresponds to the value for a variation coefficient of the rolling stock load in the range from 0 to 10 percent. Along with this, it has been established that the most sensitive to fluctuations in the volume of order is the rolling stock of small and medium cargo capacity.

Author Biographies

Alexander Rossolov, О. М. Beketov National University of Urban Economy in Kharkiv Marshala Bazhanova str., 17, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of Transport Systems and Logistics

Nadezhda Popova, Kharkiv Institute of Trade and Economics of Kyiv National University of Trade and Economics Otakara Yarosha lane, 8, Kharkiv, Ukraine, 61045

Doctor of Economics Science, Associate Professor

Department of Marketing

Denis Kopytkov, Kharkiv National Automobile and Highway University Yaroslava Mudroho str., 25, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of Transport Technologies

Halyna Rossolova, PJSC “Kharkiv Tile Plant” Moskovskyi ave., 297, Kharkiv, Ukraine, 61106

Head of Department

Department of Planning and Control

Helen Zaporozhtseva, Kharkiv National Automobile and Highway University Yaroslava Mudroho str., 25, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of Road Traffic Organization and Safety

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Published

2018-09-18

How to Cite

Rossolov, A., Popova, N., Kopytkov, D., Rossolova, H., & Zaporozhtseva, H. (2018). Assessing the impact of parameters for the last mile logistics system on creation of the added value of goods. Eastern-European Journal of Enterprise Technologies, 5(3 (95), 70–79. https://doi.org/10.15587/1729-4061.2018.142523

Issue

Vol. 5 No. 3 (95) (2018): Control processes

Section

Control processes

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Copyright (c) 2018 Alexander Rossolov, Nadezhda Popova, Denis Kopytkov, Halyna Rossolova, Helen Zaporozhtseva

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