Last-Mile Delivery for Consumer Driven Logistics

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Transportation Research Procedia 39 (2019) 74–83 www.elsevier.com/locate/procedia

Green Cities 2018 Green Cities 2018

Last-Mile Delivery for Consumer Driven Logistics Last-Mile Delivery for Consumer Driven Logistics a

Andrii Galkinaa*, Larysa Obolentsevaaa, Iryna Balandinaaa, b Andrii Galkin Obolentseva , Iryna Balandina Euvgen Kush*aa,, Larysa Volodymyr Karpenko Paula Bajdorcc , b Euvgen Kush , Volodymyr Karpenko Paula Bajdor

O. M. Beketov National University of Urban Economy in Kharkiv, 17, Baganova str., Kharkiv 61001, Ukraine National Automobile andofHighway University, 25, Yaroslav Mudrii str., Kharkiv 61004, Ukraine O. M. Beketov National University Urban Economy in Kharkiv, 17, Baganova str., Kharkiv 61001, Ukraine c b University Technology, Dabrowskiego 69, 42-201 Poland Ukraine Kharkiv Czestochowa National Automobile andofHighway University, 25, Yaroslav MudriiCzestochowa, str., Kharkiv 61004, c Czestochowa University of Technology, Dabrowskiego 69, 42-201 Czestochowa, Poland

a bKharkiv

Abstract Abstract Nowadays, one of the main tasks of logistics is the effective movement of material flow from the producer to the end user. Modern Nowadays, one of the taskstoofsolving logistics is the problems effective movement material flowlogistics from thesystem. producer to at thethe endsame user.time, Modern scientific methods aremain devoted various at differentofstages of the But, the efficiency of the functioning on last mile delivery stages is considered isolated system. to the problems of same increasing scientific methods are devotedoftologistics solving systems various problems at different of the logistics But, at the time, the efficiency of the functioning of end-consumer. logistics systems on last deliverybetween is considered isolated to the flow problems of increasing the overall efficiency including the There is anmile interaction the costs of material distribution, consumer overall efficiency including the end-consumer. is an to interaction the costs of material flow distribution, expenses and traffic flow movement costs in the There city related purchases.between The demand influence on distribution channel ofconsumer material flows in logistics systems is presented. The proposed approach can be used evaluating a logistics system’schannel overallof efficiency expenses and traffic flow movement costs in the city related to purchases. Thefor demand influence on distribution material flows in logistics systemsPractical is presented. be used for evaluating a logistics system’s considering the demand. adviceThe for proposed improvingapproach logisticscan systems according to consumer’s influence are overall given. efficiency considering the demand. Practical advice for improving logistics systems according to consumer’s influence are given. © 2018 The Authors. Published by Elsevier B.V. © 2019 The Authors. Published by Elsevier B.V. © 2018 The Authors. by Elsevier B.V. This is open access article the license (https://creativecommons.org/licenses/by-nc-nd/4.0/) (https://creativecommons.org/licenses/by-nc-nd/4.0/) This is an an open accessPublished article under under the CC CC BY-NC-ND BY-NC-ND license This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Green Green Logistics Logistics for for Greener Greener Cities Cities 2018. 2018. Selection and peer-review under responsibility of the scientific committee of Selection and peer-review under responsibility of the scientific committee of Green Logistics for Greener Cities 2018. Keywords: end-consumer, logistics channel, NPV, demand, modelling Keywords: end-consumer, logistics channel, NPV, demand, modelling

1. Introduction 1. Introduction Up-to-date, last-mile delivery is one of the important functions that take place in commercial companies. Rational Up-to-date, deliveryplays is one the important that takeofplace in reliability, commercialefficiency, companies. Rational management oflast-mile these processes anof important role infunctions the distribution goods, supporting management of of these processes plays an important role inlogistics the distribution goods, reliability, efficiency, supporting necessary level service, etc. Producer’s product price, tools andofdemand requirements are influencing the necessary level of service, Producer’s product logisticsefficiency tools and(Filina-Dawidowicz, demand requirements&are influencing choice of last-mile deliveryetc. methods, and as result,price, their overall Postan, 2016). the choice of last-mile delivery methods, and as result, their overall efficiency & Postan, 2016). The gradual transformation of the market into consumer-oriented, which is(Filina-Dawidowicz, relevant today for developing countries, The gradual transformation of the market into(Renko, consumer-oriented, whichbuyers is relevant fortodeveloping countries, leads to stereotypes and traditional evolution 2011). As a result, havetoday started demand high service leads to stereotypes and traditional evolution (Renko, 2011). As a result, buyers have started to demand high service * Corresponding author. Tel.: 38-093-196-5004. address:author. [email protected] * E-mail Corresponding Tel.: 38-093-196-5004. E-mail address: [email protected] 2352-1465 © 2018 The Authors. Published by Elsevier B.V. This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 2352-1465 © 2018 Thearticle Authors. Published by Elsevier B.V. Selection under responsibility of the scientific of Green Logistics for Greener Cities 2018. This is an and openpeer-review access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Green Logistics for Greener Cities 2018. 2352-1465  2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Green Logistics for Greener Cities 2018. 10.1016/j.trpro.2019.06.009

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levels for lower prices (Popa & Duica, 2010); a tendency for a decrease in stock in households (Bajdor & Grabara 2014) has been revealed; the increase of automobilization levels significantly changes the behavior of visiting shops (Foltyński, 2016); penetration of computers means of transmission and processing of information expands the ability to search for products from your own house (Popa, 2013). As a consequence, we see the refusing of customary purchases and the rising of e-purchases (Russo & Comi, 2012). All these changes lead logistics systems distribution via mixed and omni-channels ways, which have different efficiencies for each case. Logistics processes are generally aimed at searching for bottlenecks and optimization (Gajewska, 2013), as well as at integration of all components as a system (Olkhova, et. al., 2017). The literature most widely covers the application of logistic methods to the formation of logistics channels (Galkin, 2015), management of transport and warehouse functions (Hounwanou, Gondran & Gonzalez-Feliu, 2016; Litomin et. al., 2015) and means of production, reverse flow management (Bajdor & Brzeziński, 2018), etc. The efficiency of the functioning of logistics systems on last-mile delivery is still not developed. The retail market's development drives to its adaptation to changing requests and effectively meeting the demand (Pashkevich, Shubenkova, Makarova, & Sabirzyanov, 2018). Such situations requires improvements of methods and models for assessing the joint efficiency of the logistics systems and end-consumer interactions (Galkin, Dolia, Davidich, 2017). The purpose of this paper is to find optimal solutions for last-mile delivery according to joint efficiency of endconsumers and logistics. The research was carried out with the following stages: • • • • •

Technological description of functioning logistics channels; Assessing the joint efficiency of end-consumers and logistics Collecting the data and variation range set; Simulation of modeling; Make conclusions on obtained results.

2. Technological description of functioning logistics including end-consumers According to (Galkin, 2015), there are two main ways of taking goods to the consumer (distribution channels): direct, or through intermediaries (Fig. 1). The number of intermediate levels between the producer and the consumer characterizes the

goods’ logistics channels (LC). In fact, they consist of independent participants of MF movement. Here considering 3 main distribution channels: • • •

Direct – B2C First level (through retail) – B2B2C; Second level (through wholesaler and retailer) – B2B2B2C

P R O D U C E R

Transport

Transport

E N D

Retailer Wholesaler

Transport

Retailer

C O N S U M E R

Fig. 1 – Schemes of delivery

All managing functions of MF in the LC is divided among its participants: producer, wholesalers, retailers, endconsumer and freight carriers on the links producer – wholesalers and wholesalers – retailers. All or part of these functions can be taken over by; specialized intermediaries perform the other. To cover their costs, intermediaries

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3

charge the producer a fee. The costs of the LC affect the final cost to the consumer. Thus, the issue of who should perform the various functions of the distribution channel is a matter of relative efficiency. In the event of the possibility of more efficiently performing the functions of the channel is rebuilt. Table 1 provides information on the scheme of supply and distribution of duties among the participants of the distribution channel (business / client), which in the future will be used as a basis for the model of costs and revenues of LC.

B

B

B B

B B

B/C B/C B/C

Stocks

Delivery to

end-consumer

retailer

Warehousing at

at retailer

Delivery to retailer B B

Loading \ Unloading

at wholesaler

Loading \ Unloading

at wholesaler

at wholesaler

B

Warehousing

B B/C B B B B B

Loading \ Unloading

B2C B2B2C B2B2B2C

Loading

Packaging

Direct First level (throw retail) Second level (throw wholesaler and retailer)

Distribution scheme

Logistics channel

Delivery to wholesaler

Table 1 – Distribution of technological operations in the LC (source: own developed)

B/C C C

B – business; C – client; B/C – business or client depends on situation

The volume of MF at LC in the period t can be found: Qмit =

Q р  N рм  K ррм  k zр , 1000

(1)

рм

where Q р – average purchase amount per end-consumer, kg; K р – number of days of functioning of LC in period м t, days; k zр – factor taking into account the annual increase in demand; N р – number of end-consumers, buyers. The number of deliveries in RN for the period t is determined by: м N пкt =

Qp , Qпкм

(2)

Qпкм – delivery volume per shipment, t; n – number of days in the period.

The required amount of vehicles is proposed to be determined from the terms of their required quantity to maintain the maximum possible period requirements: Q  T TC Аnt = O мitTC t TC , Tt  qн _ i   с _ i

(3)

where Аnt – the required number of vehicles for servicing the material flow, units; Tt – operation period of time for TC which it is necessary to carry out the given amount of transportations, h.; Tt – the turnover time, h.; TC TC qн _ i – carrying capacity, t;  с _ i – load factor. Further calculation is made according to developed mathematical model of the joint efficiency of end-consumers and logistics. O

3. Assessing the joint efficiency of end-consumers and logistics The criterion for choosing "alternative entrepreneurship" (Halkin, et. al, 2017), the production of goods and services, is based on the desire to spend the same amount of means of production to achieve more effective results. This approach represents the value of a project that is evaluated from the point of view of "lost or missed opportunity" to engage in other available alternative activities that involve the same time or resources (Stępień, et. al., 2016). The

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efficiency of the logistic system, taking into account the final consumption system, can be represented as (Kush, Y., et. al., 2018): Еt jw = Dt jw − Сt jw − Θtsoc ,

(4) LS

LS

where D – Revenues of the logistics system from the realization of the MF, USD; С – the functioning costs of soc the LC, USD; Θt – cost value of society as a result of the purchase process, USD. The research of buyers influence on the LC operation is made using methods of economic-mathematical modeling and project analysis. The income, expenses and performance are calculated precisely for the distribution channel. Revenues of the distribution channel can be found by the following dependence: МF , D LS = Qмit  Psell

(5)

МF

where Psell – the price of selling goods, USD/kg. The management of the costs of the logistics system involves not only carrying the MF from the original to the final consumer, but also accounting and managing the costs of its customers. The cost expression of society's expenses because of the process of resettlement was proposed earlier in (Galkin, Dolia, Davidich, 2017):

Θtsoc = Θ1jw_ t + Θ2jw_ t + Θ3jw_ t ,

(6)

jw

jw

Where Θ1 _ t – monetary expression of time spent on the goods purchase in j – shop by i-th consumers, USD; Θ2 _ t jw – costs spent on the goods purchase in j – shop by i-th consumers, USD; Θ3 _ t – fatigue and energy cost in monetary terms for visiting j – shop by i-th consumers, USD. Time spent on the purchases can be measured in value terms. Recently, in countries with a developing and developed economy, improvement of various forms of after-sales services to customers, for e.g., and E-commerce. Therefore, it could be two purchase options: first, when the buyer purchase and delivers the goods in a customary way, and the second, when Internet purchase, which price includes the delivery cost. External costs on purchase related to its time, energy, money on the route spent on this process (Waters, 2003). Therefore, the full price for the customer of the product includes the cost of moving from the place of residence (work) to the store and the cost of his time to purchase the goods, the cost of time. The expenses of the project of using delivery technology B2C, B2B2C, B2B2B2C, w-th consignment for the period t are evaluated accordance to (Galkin, 2015):

Сt jw = K t jw + U t jw + Рt jw + H t jw ,

(7)

jw jw where K t – investments for the billing period t, USD; U t – operating costs for the organization of production jw jw for the accounting period t, USD; Рt – payments on borrowed capital for the billing period t, USD; H t – basic taxes and fees for the billing period t , USD. Operating costs of the LC can be defined as the sum of the following major items of expenditure:

jw jw , U t jw = U TCjw _ t + UWH _ t + U RN _ t

(8)

U W H _ t – the where U TC _ t – the transportation costs for the j-th delivery technology, w-th consignment, USD; jw U wholesaler costs of the wholesaler (WH) for the j-th delivery technology, w-th consignment, usd; RN _ t – expenses of RN for the j-th delivery technology, w-th consignment, USD. Transportation costs in LC for options of different amount of transport participants (TC) «B2C», «B2B2C», «B2B2B2C», w-ої consignment for the period t found as: jw

jw

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U ТСjw _ t

B 2Cw B 2Cw B 2Cw U ТС _ t = lТС1  TТС1  , = U ТСB 2_Bt2Cw = lТСB 22Bw  TТСB 22Cw + lТСB 23Cw  TТСB 23Cw  B 2 B 2 B 2Cw = lТСB 24Bw  TТСB 24Cw + lТСB 25Bw  TТСB 25Bw + lТСB 26Cw  TТСB 26Cw U ТС _ t

5

(9)

where lТС1 , lТС 2 , lТС 3 , lТС 4 , lТС 5 , lТС 6 – the total paid mileage for the j-th delivery technology B2C, B2B2C, B 2 Cw B 2 Cw B 2 Cw B 2 Cw B 2 Bw B 2 Cw B2B2B2C, w-th consignment for period t, km; TТС1 , TТС 2 , TТС 3 , TТС 4 , TТС 5 , TТС 6 – transportation cost per km for the j-th delivery technology "B2C", "B2B2C", "B2B2B2C", w-th consignment for period t, USD/km; B 2 B 2Cw B 2 B 2 B 2Cw UТСB 2Cw ,UТС _ t – transportation costs for the j-th delivery technology B2C, B2B2C, B2B2B2C, w-th _ t ,UТС _ t consignment, USD; Expenses of the WH for the j-th delivery technology, w-th consignment: B 2 Cw

B 2 Bw

B 2 Cw

B 2 Bw

B 2 Bw

B 2 Cw

jw B 2 B 2 B 2Cw B 2 B 2 B 2Cw B 2 B 2 B 2Cw B 2 B 2 B 2Cw , U WH + U unloading + U pack , _ t = U loading_ t _ t + U stor _ t _t

(10)

Costs of packing operation at the WH in LC «B2B2B2C»: jw B 2 B 2 B 2Cw B 2 B 2 B 2Cw , U pack  Т pack _ t = Qmit _t

(11)

jw B 2 B 2 B 2Cw where Qmit – the amount of MF in LC via «B2B2B2C» technology, ton.; Т pack _ t – the cost of packaging of one ton of MF, USD./ton. Costs of warehouse storage operation in LC:

jw B 2 B 2 B 2Cw B 2 B 2 B 2Cw , U stor  Т stor _ t = Qmit _t

(12)

jw

де Т stor _ t – storage cost of ton of material flow, USD / ton. Costs for loading operations in WH: B 2 B 2 B 2Cw w , U loading = Qмit  Т навн _t _t

(13)

сB2 B 2 B 2Cw

where Т loading_ t – the cost of loading of one ton of MF, USD / t. Costs for unloading operations in WH: B 2 B 2 B 2Cw B 2 B 2 B 2Cw , U unloading _ t = Q мit  Т unloading_ t

(14)

B 2 B 2 B 2Cw

where Т unloading_ t – the cost of unloading of one ton of MF, USD/ton. jw The cost of maintaining inventory U stock_ t j-th delivery technology, w-th consignment and period t: jw U stock _t

B 2Cw

B 2 B 2Cw

B 2 B 2 B 2Cw

B 2 Cw B 2 Cw B 2 Cw B 2 Cw U stock _ t = U ord _ t + U reserv _ t + U hold _ t ,  B 2 B 2Cw , B 2 B 2 Cw B 2 B 2 Cw B 2 B 2 Cw = U stock _ t = U ord + U reserv _t _ t + U hold _ t +,  B 2 B 2 B 2Cw B 2 B 2 B 2 Cw B 2 B 2 B 2 Cw B 2 B 2 B 2 Cw , = U ord + U reserv + U hold U stock _ t _t _t _t

(15)

where U ord _ t , U ord _ t , U ord _ t – the order expenses for the j-th delivery technology B2C, B2B2C, B2B2B2C, B 2Cw B 2 B 2Cw B 2 B 2 B 2Cw w-th consignment for the period t, USD; U reserv _ t , U reserv _ t , U reserv _ t – the reserve stock for delivery technology «B2C»,

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B 2 B 2Cw

79

B 2 B 2 B 2Cw

– the holding stock «B2B2C», «B2B2B2C», w-th consignment for the period t, USD; U hold _ t , U hold _ t , U hold _ t expenses in LC transit for delivery technology «B2C», «B2B2C», «B2B2B2C», for the period t, USD. Expenses for orders in period t: jw jw jw , U ord _ t = Cord _ t  N пкt

(16)

jw

where Cord _ t – expenses for one order for j-th delivery technology, w-th consignment for period t, USD. The holding cost of maintaining the stock evaluated as: jw jw jw U hold = C produc  Qmit  k ir  t hold ,

(17)

jw

where thold – average time of stocks "on the way", days; C produc – selling price of a unit of goods from the manufacturer according to the delivery technology B2C, B2B2C, B2B2B2C, w-th consignment, USD; kir – annual interest rate for using a loan, %. jw Reserving stock expenses at stock ( U reserv _ t ) in period t is evaluated as: jw

jw jw jw , U reserv _ t = C produc  Qmit  kir  k reserv

(18)

jw

where k reserv – average reserving time at stock, days Expenses of RN for j-th delivery technology, w-th consignment: jw B 2 B 2Cw B 2 B 2 B 2Cw U RN = U RN = Qmit  k RN , _ t = U RN _ t _t

(19)

where U RN _ t – RN expenses by technology «B2B2C»; U RN _ t – RN expenses by technology «B2B2B2C»; k – factor consider costs of selling one kilogram of MF, USD/kg. The payment of borrowed capital is proposed to be determined in accordance with the loan scheme used (Roslavcev, 2010): B 2 B 2Cw

B 2 B 2 B 2Cw

RN

jw jw , Рt jw = Рprin _ t + Р%t

(20)

jw where Р prin _ t – the volume of loan repayments in period t for j-th delivery technology, w-th consignment, USD; Р%jwt – the amount of interest payments for the use of credit funds in period t, USD. Payments value of principal part of credit in period t is evaluated as:

jw Р prin _t =

jw jw ( KTCjw _ t + KWH _ t + K RN _ t ) ,

(21)

т pbjw _ ord

jw where KТС _ t – the amount of borrowed capital for TC for the j-th delivery technology, w-th consignment, USD; jw KWH _ t – the amount of borrowed capital for the WH for the j-th delivery technology, w-th consignment, USD; K RNjw _ t – the amount of borrowed capital for RN for the j-th delivery technology, w-th consignment, USD т pbjw _ ord – the period in which credit funds are attracted (the avaregy time of payback to producer for MF from retailer), month. Value of interest of credit in period t:

jw jw P%jwt = (( KTCjw _ t + KWH _ t + K RN _ t ) − (

jw jw ( K TCjw _ t + KWH _ t + K RN _ t )

т

jw pb _ ord

 (t −1))) 

k

т

ir jw pb _ ord

100

,

(22)

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The main taxes in LC evaluated by: jw , H t jw = Н tIT _ jw + Н VAT

(23)

IT _ jw

– profit tax for the j-th delivery technology, w-th consignment for period t, USD; where Н t jw Н VAT _ t – VAT payments for the j-th supply technology, w-th shipment period t, USD; The amount of payments for VAT in the period t is evaluated as (Roslavcev, 2010): jw jw jw Н VAT − U рtjw − U пtjw − Р prin _ t = ( Dt _t ) 

 H VAT . 100

(24)

Income tax for the period t (Roslavcev, 2010):

H

IT _ jw t

0, H tIT _ jw  0 ,  =  H IT _ jw  H IT _ jw t IT  H , 0  t 100 

(25)

where H t – profit of LC which is submitted before taxation in period t, USD; H IT – tax rate on profit, %. The profit for taxation in the period t is evaluated as: IT _ jw

jw jw . H tIT _ jw = Dt jw − U t jw − HVAT _ t − Р%t

(26)

4. Collecting the data and variation range set The range of data variation is presented in table. 2. Table 2. A range of varying of mathematical models’ factors (source: own developed) № Title of Models’ factor

Dimension

The value of factor

1

The total paid mileage of transportation

km

50

2

The time period specified in traffic performance in period

days

30

3

The cost of transportation services for the carriage of MF

USD/km

7,5

4

Load capacity of vehicle

ton

0,1 – 60

5

Average reserving time at stock

days

10

6

Average time of stocks "on the way",

days

10

7

The cost of unloading of one ton of MF

USD/ton

1

8

The cost of packaging of one ton of MF

USD/ton

0,1

9

Average reserving time at stock

days

3

10

Storage cost of ton of material flow

USD/ton

1

11

Average purchase amount per end-consumer

kg

2

12

Number of days of functioning of LC in period t

days

180

13

Factor taking into account the annual increase in demand

-

1,15

14

Number of end-consumers,

buyers

25

15

The price of selling goods

USD

30

16

The amount of borrowed capital for TC

USD

1000

17

The amount of borrowed capital for the WH

USD

2000

18

The amount of borrowed capital for RN

USD

1500

19

The period in which credit funds are attracted (the average time of payback to producer for MF from retailer)

month

24

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№

Title of Models’ factor

Dimension

Cont. tab.2 The value of factor

20

Tax rate on profit

%

25

22

VAT payments

USD

20

23

Annual interest rate for using a loan

%

1,5

24

Factor consider costs of selling one kilogram of MF at RN

USD/kg

0,5

25

Expenses for one order

USD

5

26

Transportation cost per km

USD/km

1

5. Simulation Fragments of automation of calculations in the Excel environment are shown in Fig. 2. Individual spreadsheets are intended to input the output data, and to calculate the costs and revenues of the distribution channels. The automated calculation (determination) of the characteristics of the expense and revenue part for a separate distribution channel for the period t is developed, as well as calculation of the value of the criterion of the efficiency of each participant's work and the system as a whole.

Fig. 2. Example of work in Excel (source: own developed)

To automate the calculation of the model's performance, the software product Microsoft-Excel was used. Automation of calculations allows us to determine the value of the criteria for the effectiveness of the system and its individual participants, as well as to monitor other parameters of the model. As a result, of the calculations and comparison of costs, revenues and time-to-income ratios, we have calculated the NPV for each distribution channel and the total volume of cargo delivery from 0.1 to 60 tons. The results of the calculation are presented in Table. 3 According to the efficiency criterion, we choose the maximum ELS value of joint efficiency in each period that corresponds to the delivery technology: the distribution channel and the supply side. Table 3 – Joint efficiency of using delivery technologies by criterion ELS (source: own developed) ELS Delivery amount Direct First level Second level Maximum ELS for delivery technology 0,1 -200718 -205934 -104130 -104130 0,5 244495,7 237165,5 34890,46 244495,7 2 333707,2 330308,2 179288,2 333707,2 5 329794,3 334257,6 146187,6 334257,6 10 200209,9 223633 -38447 223633 20 -323571 -265204 -614064 -265204 60 -1882784 -1719585 -2610417 -1719585 Maximum ELS for delivery technology 333707,2 334257,6 179288,2 -

Based on the received calculations of the distribution channel by the amount of the batch of delivery and delivery technology, it is possible to conclude that in the necessary to use first level channel under proposed conditions (Fig. 3). The quantity of deliver analyses shows a different result – its better use 5 tons lots and direct channel (Fig.4).

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The maximum value for the entire of the project is: 1200743.00 USD.

Fig. 3. Change the efficiency depending on the choice of the distribution channel (source: own developed)

Fig. 4. Changing efficiency depending on the choice of delivery batch in the distribution channel (source: own developed)

The forms of goods’ promotion to the consumer are determined primarily by the nature of the product itself, the place and conditions of its production, consumption and logistics abilities. Direct communication is used more in B2B option, when a large part of the MF is procured in large batches or in the case of purchases of unique products (Renko, 2011). Direct forms of sales are usually based on the transfer of goods on schedules and involve the provision of additional forms of service and benefits, e.g., lower shipping prices (Olkhova, et. al, 2017). Compliance with the schedule of deliveries, facilitates the shortening of inventories and the needs for additional storage capacity. In cases, when sales of products are carried out on long-term contracts, this leads to the strengthening of production links and overall sales reliability (Galkin, 2017). When servicing end-consumers with B2C technologies, it takes a lots attention to customer service, which makes it necessary to have provided large sales, and cost per order, which we can see in Fig. 3. The end-consumer, in this case, can't achieve the lowest price, and external cost would be higher, because of a long time spent moving to producer and back, or using small party delivery. This scheme will be more effective with increasing bundles per order. To the services of intermediary wholesale enterprises, manufacturers of products to expand the markets for the sale of goods and reduce costs. In cases of territorial dispersion of the market to the supplier company it’s unprofitable to supply products through direct links with consumers because of the significant distribution costs of sales. The wholesaler, accumulating incoming goods of different nomenclature, sells them, getting a part of the profit from the joint sale. As a result of such sales organization, suppliers are able to sell their products to a wider range of consumers. The producer resorts to the intermediaries’ services while the organization an additional channel for the implementation of the same product in individual markets need. Therefore, by struggling with competitors on new markets through intermediaries, the firm can set prices lower than in its traditional market. Thus, it increases the sales and receives at the expense of this profit in a larger amount. Consumers of products are interested in services of wholesale intermediary enterprises. As a result, faster delivery of goods to the consumer not only speeds up time from the time of order to destination of the goods. They also has the opportunity to plan the arrival of products and often direct it to the production process, bypassing the warehouse, which significantly reduces the costs of the formation of stocks, their storage and costs associated with the presence of goods in the warehouse. 6. Conclusions The article presents an approach for estimating the consumer's influence on the material flow in the logistics system. The approach takes into account the parameters of consumers and the logistics system and is an extension of knowledge regarding the use of a consumer-oriented approach in the logistics system. The obtained results can be used in planning and organizing the functioning of the logistics and system. For today, one of the main tasks of logistics is the effective distribution of material flow from the manufacturer to the end user. Modern scientific methods are devoted to solving various problems at different stages of the logistics system. But not many of them present models of the interactions of end-consumers and logistics systems. At the same time, there is association between the distribution channel choice and total costs of end-consumers and profit of logistics channel. The paper is continuing previous research on this topic (Galkin, 2015 and Galkin, Dolia, & Davidich, 2017) and provides modeling for 3 logistics channels and simulating efficiency results on this theme. Using this

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