1

4

3

3

3

2

3

2

4

6

3

3

3

4

5

Q4. Other process stakeholders are satisfied with the process outcomes

2

3

2

2

2

1

2

1

1

3

4

3

2

2

5

Process Enhancement

Q5. You have nothing significant to suggest for current process to enhance it.

2

3

2

3

3

2

3

1

0

2

2

1

4

3

4

Q6. Amount of activities in process is currently optimal

2

3

2

4

3

3

2

2

3

3

2

3

6

3

6

Q7. Your activities create enough value for the company.

4

6

4

5

5

3

7

5

2

3

3

3

4

3

6

Q8. You are currently satisfied with routine you are involved in.

4

3

2

1

1

2

3

2

2

1

1

1

1

2

3

Table 7.

Respondents' answers before project implementation (2)

Category	Question	Respondents	Parameters
		16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	Mean	St. Dev
Process Efficiency	Q1. Current process is done the best way possible.	2	2	2	3	7	2	3	7	7	3	3	5	6	1	1	3	3,097	1,873
	Q2. Your working time distributed efficienly.	2	2	2	3	2	1	3	5	3	5	3	1	2	3	2	2	2,323	0,929
	Q3. Sunk costs can't be further mitigated easily.	4	4	2	2	2	3	4	7	3	3	5	6	2	6	2	3	3,452	1,411
	Q4. Other process stakeholders are satisfied with the process outcomes	3	3	2	3	4	3	3	5	3	1	3	3	2	4	2	3	2,645	1,033
Process Enhancement	Q5. You have nothing significant to suggest for current process to enhance it.	2	3	2	1	2	3	2	1	2	1	3	3	1	3	3	2	2,226	0,940
	Q6. Amount of activities in process is currently optimal	3	2	4	2	1	5	3	4	2	3	3	6	3	2	3	2	3,065	1,243
	Q7. Your activities create enough value for the company.	3	3	6	3	7	2	5	2	1	3	4	3	3	6	4	7	4,032	1,596
	Q8. You are currently satisfied with routine you are involved in.	3	3	2	2	3	4	1	2	2	2	2	4	2	1	3	2	2,161	0,919

As it seemed, employees are not generally satisfied with current state of processes in warehousing - both efficiency and process-wise. Main complains are towards uneven working time distribution and stakeholders' dissatisfaction. During private conversation with employees, author found out that main concerns of stakeholders were overall about product shelf life left on the consumer part and speed of operations in logistics department overall. At the same time employees consider their own impact on value creation inside the company as moderate (while other points lied mostly in range from 2 to 3). Results above clearly depict need in actual changes in processes, not even digitalization introduction in warehousing processes.

Second questionnaire iteration was conducted in almost a month after project realization.

Table 8.

Respondents' answers after project implementation (1)

Category	Question	Respondents
		1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
Process Efficiency	Q1. Current process is done the best way possible.	3	3	4	3	4	5	5	6	4	6	2	4	5	6	6	6	4	4	4	5
	Q2. Your working time distributed efficiently.	5	5	4	4	4	5	5	4	5	3	4	6	5	6	4	5	4	5	5	4
	Q3. Sunk costs can't be further mitigated easily.	4	3	4	5	5	4	4	4	4	3	4	4	7	5	6	6	2	5	5	4
	Q4. Other process stakeholders are satisfied with the process outcomes	5	3	6	4	1	6	7	2	3	5	5	5	4	4	4	5	6	6	5	3
Process enhancement	Q5. You have nothing significant to suggest for current process to enhance it.	4	3	4	3	4	6	4	3	5	5	4	5	6	2	6	6	5	6	7	1
	Q6. Amount of activities in process is currently optimal	3	5	4	5	4	4	4	3	4	4	4	5	3	4	3	3	4	3	5	2
	Q7. Your activities create enough value for the company.	5	4	7	6	5	4	4	3	5	3	5	2	4	3	5	3	5	5	4	2
	Q8. You are currently satisfied with routine you are involved in.	3	3	2	2	1	1	1	2	4	4	1	1	1	3	4	2	3	1	5	4

Table 9.

Respondents' answers after project implementation (2)

Category	Question	Respondents
		21	22	23	24	25	26	27	28	29	30	31	32	33	Mean	St. Dev
Process Efficiency	Q1. Current process is done the best way possible.	4	7	5	5	6	4	5	2	4	5	4	7	5	4,606	1,229
	Q2. Your working time distributed efficiently.	5	4	2	4	5	4	5	5	3	4	4	5	4	4,424	0,818
	Q3. Sunk costs can't be further mitigated easily.	5	4	5	4	4	4	4	5	6	3	5	4	4	4,394	0,983
	Q4. Other process stakeholders are satisfied with the process outcomes	4	4	5	4	3	4	6	3	5	5	4	5	3	4,364	1,275
Process enhancement	Q5. You have nothing significant to suggest for current process to enhance it.	3	4	4	3	1	1	4	5	4	3	5	3	7	4,121	1,572
	Q6. Amount of activities in process is currently optimal	5	5	5	4	3	1	5	5	4	4	5	3	3	3,879	0,977
	Q7. Your activities create enough value for the company.	3	4	5	4	4	5	4	5	3	3	4	6	3	4,152	1,131
	Q8. You are currently satisfied with routine you are involved in.	2	3	3	3	3	1	1	3	3	2	4	3	1	2,424	1,155

Even if time periods used for sampling were different - second take was done during the time in between holidays, it is not much affected overall results due to two main factors:

· Company establish discipline among rank-and-file employees;

· Amount of working days in both samplings was identical.

From the results of survey conduction, seems obvious that project realization positively affected almost all the aspects in the list of asked questions - from perceived time expenditure to overall process management. But, in overall, direct comparison of means does not give correct answer. Thus, parametrical tests are required to determine the result. For preliminary calculations, which show pattern of answers - mean (1) and standard deviation (2) (sigma) are needed.

(1)

where: xi - parameter value for particular respondent;

n - sample size.

(2)

where: xi - parameter value for particular respondent;

- estimated mean value for particular parameter.

Paired t-test with equal variances is definitely the way to go in the case of questionnaire results precise identification. Accordingly, all 8 hypotheses (3), connected to questions, are almost the same. Main hypothesis (H0) states that there is no significant difference between means of two samples. Alternative hypothesis (Ha) is `there is a significant difference in favor of situation after project realization".

 (3)

To check hypothesis properly, there must be acquired two estimates - critical point and statistic (4). In this case of means comparison, critical point is distributed in Student. Degrees of freedom are equal to: df = 33+31-2 = 62 (Schechtman & Sherman, 2007). With 95% confidential interval and df = 62, critical point becomes closer to 1,67 (MIT Mathematics, 2017).

(4)

where: - estimated mean for sample 1;

- estimated mean for sample 2;

- standard deviation for sample 1;

- standard deviation for sample 2;

- sample size for sample 1;

- sample size for sample 2.

Overall results for hypothesis testing shown in the table below.

In almost all the cases, main hypotheses were accepted, except two questions: "Your activities create enough value for the company" and "You are currently satisfied with routine, you are involved in" - results for these statements are negative - project does not significantly change perception of created value by customer and routine. Both cases can be explained even from the point of psychology: employee does not want show that he is not creating enough cash flow, but quite quick to blame routine activities, while "Process enhancement" is proven to have been influenced significantly by project implementation in general, two aspects does not differ enough to achieve same result.

In terms of consistency and overall applicability of equal-means two-sample t-test for the Likert-type categories, quick equal variance F-test was computed:

For particular sample sizes, critical point is equal to 1,83 with 95% probability (SOCR, 2002). Looking up to tables 6 - 10 makes clear that maximum statistics will be 1,61 in comparison of 2nd question between two samples. Therefore, for all pairs, main hypothesis is accepted = there is no significant difference between variances of two sample in any case.

Table 10.

Results of checking hypothesis

Category	Question	Crit. Alpha	Criteria	Hypothesis accepted?	Crit. Alpha	Criteria	Hypothesis accepted?
Process Efficiency	Q1. Current process is done the best way possible.	2	-3,79	Yes	1,67	- 4,903	Yes
	Q2. Your working time distributed efficiently.	2	-9,58	Yes
	Q3. Sunk costs can't be further mitigated easily.	2	-3,08	Yes
	Q4. Other process stakeholders are satisfied with the process outcomes	2	-5,94	Yes
Process enhancement	Q5. You have nothing significant to suggest for current process to enhance it.	2	-5,89	Yes	1,67	-2,17	Yes
	Q6. Amount of activities in process is currently optimal	2	-2,90	Yes
	Q7. Your activities create enough value for the company.	2	-0,34	No
	Q8. You are currently satisfied with routine you are involved in.	2	-1,01	Yes

In general, implementation of optimizing software for warehousing of Agroholding Vyborgec has overall positive influence on employees' perception of their work routine during participation in processes, directly connected with operations affected by project. Employees report that in terms of sheer efficiency and process quality, warehousing acquired overall improvement with optimizing application introduction after first month of operation.

Financial modelling of application implementation

Open-source and inside financial data was used to create financial model of given application implementation project realization within logistics department of Agroholding Vyborgec. Due to the fact of future cash flow unavoidable uncertainty, there are several assumptions, which are required to complete model with actual state of available information:

1. Unit of production is considered to be on of the following: a kilogram of weighted product; a pack of a product (600-1 000 gram); a 5-pack of green (from 50 to 200 gram in each pack);

2. Production plan is taken from operation department and include given 10% yearly growth in production, distributed on each month, which is justified by ongoing investment projects of Vyborgec, and seasonal drops and peaks in vegetables consumption month by month (for example, in average 40% drop in sales is expected during winter in comparison with summer);

3. As it is calculated during first month of optimization application implementation, there are four significant sources of economy: conveyor transferring time save (about 3 minutes in average); time save in staying inside warehouse (2 hours in average); shipment packaging time save (10 min in average); lesser spoilage (about 9,5% of average inventory instead of 10,5% marked before).

4. Cash flow is projected on a monthly basis.

5. Project cash flow is projected on three-year time horizon (same approach as in Vyborgec).

Also, one of the preliminary steps was to calculate discount rate. Similar to Vyborgec's standards, ROE, adjusted on inflation ratio can be used as a discount rate. ROE was calculated based on financial statement and P&L. Inflation rate was taken from Vedomosty (Vedomosty, 2018) as corrected forecast of Russian Ministry of Economic Development.

Table 11.

Discount rate calculation based on stated assumptions

Parameter	Y1	Y2	Y3
Discount rate (Yearly)	14,06%	13,52%	13,74%
Inflation expectations	4,30%	3,80%	4,00%
Avg ROE (3y)	9,36%	9,36%	9,36%

Table 12.

Financial model of released project in Agroholding Vyborgec (1). First 10 months, savings amount calculated

Month #	0	1	2	3	4	5	6	7	8	9	10
Approx. stock amount at warehouse	683 499	688 949	729 165	790 978	846 675	867 650	788 546	758 705	691 921	624 024	518 000
Units transferred to warehouse (production amount)	-	1 931 835	2 043 264	2 215 025	2 369 445	2 426 556	2 203 881	2 119 092	1 931 298	1 740 643	1 443 956
Units shipped from warehouse	-	1 926 385	2 003 048	2 153 212	2 313 748	2 405 580	2 282 986	2 148 933	1 998 082	1 808 540	1 549 980
Incremental time save from transferring procedures per unit (hours/unit)	-	0,0500	0,0500	0,0500	0,0500	0,0500	0,0500	0,0500	0,0500	0,0500	0,0500
Incremental time save of being in storage for particular pallete (hours/unit)	-	2,0000	2,0000	2,0000	2,0000	2,0000	2,0000	2,0000	2,0000	2,0000	2,0000
Incremental time save of acquring proper pallete for shipping (hours/shipping)	-	0,1670	0,1670	0,1670	0,1670	0,1670	0,1670	0,1670	0,1670	0,1670	0,1670
Average costs of transferring to warehouse per unit/hour	-	0,0028	0,0028	0,0028	0,0028	0,0028	0,0028	0,0028	0,0028	0,0028	0,0028
Average costs of storaging per unit/hour	-	0,0009	0,0009	0,0009	0,0009	0,0009	0,0009	0,0009	0,0009	0,0009	0,0009
Average costs of shipping preparation per hour	-	0,0042	0,0042	0,0042	0,0042	0,0042	0,0042	0,0042	0,0042	0,0042	0,0042
Spoilage percentage decrease	-	0,0100	0,0100	0,0100	0,0100	0,0100	0,0100	0,0100	0,0100	0,0100	0,0100
Average operation margin per unit shipped - unit salvage value	-	0,2810	0,2810	0,2810	0,2810	0,2810	0,2810	0,2810	0,2810	0,2810	0,2810
Savings from transferring	-	271	287	311	333	341	310	298	271	245	203
Savings from warehousing	-	3 146	3 329	3 612	3 866	3 962	3 601	3 464	3 159	2 849	2 365
Savings from shipment preparation	-	1 356	1 410	1 516	1 629	1 693	1 607	1 513	1 406	1 273	1 091

As it is clear, main source of savings is a combination of warehousing processes and spoilage economy. (up to 70%). Economical effect of optimization application is calculated as incremental difference between parameters mean before and after project release. Spreadsheets of average time save in all the cases are not available for publishing. All the calculations were done by author with help of quality control systems by assessing time stamps on each checkpoint for particular pallet.

While table 12 provides insight on income part of cash flow, table 13 shows costs of project incurred at the preparation stage and afterwards.

Table 13.

Financial model of released project in Agroholding Vyborgec (2). First 10 months, costs

Month #	0	1	2	3	4	5	6	7	8	9	10
Investments amount	75 000	-	-	-	-	-	-	-	-	-	-
Licence for basic software	20 000	-	-	-	-	-	-	-	-	-	-
Customization costs	25 000	-	-	-	-	-	-	-	-	-	-
Equipment purchase	30 000	-	-	-	-	-	-	-	-	-	-
Maintenance costs	0	1 051	1 051	1 051	1 051	1 051	1 051	1 051	1 051	1 051	1 051
Education costs	-	26	26	26	26	26	26	26	26	26	26
Training hours	-	8	8	8	8	8	8	8	8	8	8
Cost of 1 hour	-	3	3	3	3	3	3	3	3	3	3
Troubleshooting costs	-	525	525	525	525	525	525	525	525	525	525
Amortization costs	-	500	500	500	500	500	500	500	500	500	500
Corporate tax 20%	0	744	795	877	955	989	893	845	757	663	522

Project has three main sources of costs: beginning investments, maintenance and tax deduction, which will affect overall financial result, if Vyborgec will continue to generate profit. Cash-flow and other key parts of a model will be presented on yearly basis for full length of 3 years.

Maintenance costs include wage of support specialist, costs of external experts who will conduct some trainings in average 1-2 times a week. Amortization costs is calculated with assumption of same linear calculation model applies to the equipment purchase.

Table 14.

Short version of financial model

Year #	Y1	Y2	Y3
Amount at warehouse	714 256	785 682	821 039
Units transferred to warehouse	24 179 621	26 389 467	28 801 276
Units shipped from warehouse	24 148 864	26 318 041	28 765 920
Transferring savings	3 397	3 708	4 047
Warehousing savings	39 509	43 460	47 609
Shipment preparation savings	16 999	18 525	20 248
Investments	75 000	0	0
Maintenance costs	12 615	12 458	12 458
Corporate tax	9 458	10 647	11 889
CF	-37 168	42 588	47 557
DCF	-39 624	35 029	47 557

While company suffers stable amount of losses every period, savings are overcoming losses and give positive cash-flow to the company.

Table 15.

Efficiency indicators of project assessment

Indicator	Amount
NPV	29 818
PI	0,40
PP	23 months
DPP	26 months
IRR	26,80%

NPV was calculated as a sum of positive cashflows along the planning horizon of a project and investment amount. Indicator shows positive score, which tells that project is profitable and economically justified. But, due to the necessity of using units instead of actual currency - rubles, this absolute amount cannot be interpreted, which leaves us with other four indicators. PI is 40%, which shows great case of gain 40% of extra profit over paying cost of capital. Payback periods are varying from 2 to 2,2 years, which is a great result for business, operating mostly on fixed assets and does not achieving fast turnover over time.

Internal rate of return shows considerably good performance, surpassing discount rates more than on 12%, giving opportunity to earn 12% annually over the cost of capital.

3.2 Process state after improvements and recommendations

In terms of process enhancement, optimization application drove several changes in preciously described algorithm (Figure 7):

Figure 7. State of Agroholding Vyborgec process after project implementation3

1. Information lists were changed for bar-code lists to create "stamp" for scanners all over the distribution center to read and write data about any particular bulk which got into distribution center;

2. While guidance inside distribution center is still manual, number of mistakes will decrease due to unambiguous information bar-code keeping inside about route set for the bulk;

3. Storing process of particular bulk is dependent on particular product shelf time and determine actual place, closer to shipping terminals;

4. Employee, armed with scanner, is able to identify needed bulks for particular shipment faster and without mistakes, previously lead to spoilage and losses.

While overall success of changed processes inside distribution center is supported by financial indicators calculation and overall employee perception, there is still a plenty room for improvement:

1. Packing lists and shipment registers are still printed to complete relationships with client in terms of product and payment acceptance and liabilities clearance;

2. Manual bulk steering inside the distribution center still exists and seemed to be unoptimized from the point of additional personnel costs;

3. Production volumes are not responding demand fluctuations inside the month, which still creates space for products spoilage;

As overall positively continuing project, introduction of optimizing application for Agroholding Vyborgec warehousing and logistics needs several improvements to be implemented, based on revelations from previous paragraphs:

· Introduction of storing space with functions of increasing shelf life or product diversification (i.e. introduction of freezed vegetables) according to the fact that current spoilage ratio is still depleting about 9,5% of company's revenue;

· Continue business process optimization with help of "spaghetti diagram" or other instrument to determine most efficient way of moving goods inside distribution center in addition to full automatization of transferring process inside the distribution center;

· Enhancement of application itself is also mandatory: interface is slightly more user-friendly than in MS Excel, analytical reports are not included, other paperwork is not omitted - introduction of digital systems of document exchange with clients and other departments is a clear next step for Agroholding Vyborgec to improve warehousing and logistics operations.

Conclusion

Looking at the big picture of Russian economy current state will reveal strong need in acquiring additional competitive advantages not only inside the market, but also in international operations. Digitalization may support traditional methods of obtaining competitive advantage or company overall sustainability: fixed assets renovation, operation shrinking and simple cost-cutting. Holistic effect of warehousing application usage can not only decrease unit costs, improve quality control state or optimize assets capacity utilization, but also provide company with corporate culture establishing by showing employees that assuring process effectiveness it one of the company values. That fact alone may construct the foundation of internal projects execution, driven mainly by employees, not managers.

For Agroholding Vyborgec, one of the main benefits of research competition is the knowledge about project effectiveness on various levels, from plain financial numbers to the feeling of actual warehousing employees who will embrace changes in their everyday routine. Level of that embracement will be depicted by qualitative data analysis. Multicriterial estimation will give edge for Vyborgec to tune future digitalization implementation activities or perform better change management processes in other fields of management.

Possible future research options for the topic may lie in the field of studying effects of digitalization in yearly time perspective (2-3 years after implementation) or in implementing consimilar approach in other Agroholding Vyborgec operations like HR or Marketing to find additional way to improve company financial performance.

From the point of research objectives - all of them were accomplished by this paper:

· Current state of warehousing optimization topic is given through prism of internet-of-things and overall digitalization;

· State-of-art of Agroholding Vyborgec thoroughly described, analyzed and used to create framework for measuring project effectiveness;

· Data collected, processed; relevant methods used and indicators calculated to provide overall conclusion on the optimization application solution effectiveness;

· Business processes compared, various recommendation, based on the previous analysis are provided.

Answering research problem: with help of literature review, author came to conclusion that under given data and circumstances, project financial effectiveness and qualitative assessment of state by process participants are sufficient to determine project effectiveness. While project pays back investments made during approximately two-year time period, positive NPV, which creates additional 40% income over three years above required rate of return, clearly states that from financial point of view, project is profitable and will have overall positive take on company warehousing and logistics operations. In the same time, employees responded with assertive perception of being a part of warehousing processes after project implementation.

References

1. Comodity.ru. (2012). Duration of storage of fresh vegetables and potatoes. Retrieved from http://www.comodity.ru/ispolzrasten/vegetablestoring/15.html;

2. Dцrnhцfer, M., Schrцder, F., & Gьnthner, W. (2016). Logistics performance measurement system for the automotive industry. Logistics Research, 9(1);

3. EazyStock. EazyStock - Inventory Optimization Software. Retrieved from: https://www.eazystock.com/;

4. Ereshko, F., Kulba, V., & Medennikov, V. (2018). Integration of the digital platform of agrarian and industrial complex into digital platforms of allied industries. Aic: economics, management, (10), 34-45;

5. Garcнa-Arca, J., Gonzбlez-Portela Garrido, A., & Prado-Prado, J. (2016). "Packaging Logistics" for improving performance in supply chains: the role of meta-standards implementation. Production, 26(2), 261-272;

6. Gartner IT Glossary. What Is Big Data? - Gartner IT Glossary - Big Data. Retrieved from: https://www.gartner.com/it-glossary/big-data/;

7. GasBuddy. Never pay full price at the pump. Retrieved from: https://www.gasbuddy.com/;

8. Graeml, A., & Peinado, J. (2011). Measuring Logistics Performance: the Effectiveness of Mmog/Le as Perceived by Suppliers in the Automotive Industry. Journal Of Operations And Supply Chain Management, 4(1), 1;

9. Hammond, S., Brown, J., Burger, J., Flanagan, T., Fristoe, T., & Mercado-Silva, N. et al. (2015). Food Spoilage, Storage, and Transport: Implications for a Sustainable Future. Bioscience, 65(8), 758-768;

10. Hawkeyelogs.com. Hawk Eye - Home. Retrieved from: https://www.hawkeyelogs.com/;

11. Hanebeck, H. & Tracey, B. (2003). The role of location in supply chain management: how mobile communication enables supply chain best practice and allows companies to move to the next level. International Journal of Mobile Communications, 1(1/2), 148. Retrieved from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.206.42&rep=rep1&type=pdf;

12. Hector, T., & Ruthven, G. (2012). The development of a performance measurement system for the South African container shipping industry. Journal Of Transport And Supply Chain Management, 6(1);

13. Interfax. (2015). In Russia, the law on personal data came into force.Retrieved from https://www.interfax.ru/business/463850;

14. ISSEK HSE (2017). HSE completed S&T Foresight Study for the Agricultural Sector 2030. Retrieved from https://issek.hse.ru/en/news/201482469.html;

15. Keller, S. & Keller, B. (2014). The definitive guide to warehousing. Upper Saddle River, NJ: Pearson, 1-13. Retrieved from: http://ptgmedia.pearsoncmg.com/images/9780133448900/samplepages/0133448908.pdf;

16. Kurt, O., Kalem, G., Vayvay, O. & Kalender, Z. (2016). The Role of Mobile Devices and Applications in Supply Chains. International Journal of Economics and Management Systems, 1(1), 94-103. Retrieved from: https://www.iaras.org/iaras/filedownloads/ijems/2016/007-0013.pdf;

17. Mimouni-Chaabane, A., & Volle, P. (2010). Perceived benefits of loyalty programs: Scale development and implications for relational strategies. Journal Of Business Research, 63(1), 32-37;

18. MIT Mathematics (2017). t-Distribution Table. Retrieved from: http://math.mit.edu/~vebrunel/Additional%20lecture%20notes/t%20(Student%27s)%20table.pdf;

19. Moskalev S. (2015). Assessment of the construction of the regional market of meat products and marketing activity of the economic entities on items (on the example of the pskov region). Journal "economics, accounting and land resources", udc 338, 137-143;

20. Mudda, S., Giddi, C., & PVGK, M. (2017). A study on the digitization of supply chains in agriculture - an Indian experience. Journal Of Agricultural Informatics, 8(1), 45-55.;

21. Probation Journal (1997). Measuring Effectiveness, 44(2), 80-85;

22. Russia Today. Russia's agriculture sector booming despite or thanks to international sanctions. (2017). Retrieved from https://www.rt.com/business/385285-russia-agriculture-flourishes-sanctions/;

23. Schechtman, E., & Sherman, M. (2007). The two-sample -test with a known ratio of variances. Statistical Methodology, 4(4), 508-514;

24. Servicemax.com. Work Order Software, Tracking & Management Systems. Retrieved from: https://www.servicemax.com/products/work-order-management;

25. Stank, T., Goldsby, T., Vickery, S., & Savitskie, K. (2003). Logistics service performance: estimating its influence on market share. Journal of business logistics, 24(1), 27-55.;

26. Statistics Online Computational Resource. (2002). F-Distribution Tables. Retrieved from: http://socr.ucla.edu/Applets.dir/F_Table.html#FTable0.05;

27. Trukhachev, V., Sklyarov, I., & Sklyarova, Y. (2018). The influence of rouble devaluation on sustainable development of the agrarian sector of russian economy in the conditions of the international sanctions. Russian Agrarian Economy Journal, (5), 65-70. doi: 10.32651/2070-0288-2018-5-65-70

28. VAN DER VORST, J. (2006). Performance measurement in agri-food supply-chain networks. Quantifying The Agri-Food Supply Chain, 15-26;

29. Vartanova, М., & Drobot Е. (2018). Prospects for the digitalization of agriculture as a priority direction for import substitution. Journal Of International Economic Affairs, 8(1), 1;

30. Vedomosti. Ministry of Economic Development has worsened the forecast for 2018-2019. (2018). Retrieved from: https://www.vedomosti.ru/economics/articles/2018/09/05/780064-minekonomrazvitiya;

31. Vorotnikov I., Kolotyrin K., Vlasova O., Petrov K. (2017). Optimization of agricultural products storage and marketing on the basis of logistics. Revista Espacios. Vol. 38;

32. Yuqiang, C., Jianlan, G. & Xuanzi, H. (2010). The Research of Internet of Things' Supporting Technologies Which Face the Logistics Industry. 2010 International Conference on Computational Intelligence and Security;

33. Wen L. (2005). The role of transportation in logistics chain. Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 1657 - 1672, 2005;

34. Business Petersburg (2017). Vyborzhets will invest 3 billion rubles in the production of mushrooms. Retrieved from https://www.dp.ru/a/2017/03/31/Viborzhec_vlozhit_3_mlrd;

35. Business Petersburg. (2017). "Agrofirm Vyborzhets" will invest 8 billion rubles to increase capacity. Retrieved from https://www.dp.ru/a/2017/11/14/Agrofirma_Viborzhec_vlozh;

36. Ministry of mass-communication and digital development of Russian Federation (2015). Processing and storage of personal data in the Russian Federation. Changes from September 1, 2015. Retrieved from: https://digital.gov.ru/ru/personaldata/;

The Federal State Statistics Service (2018). Home: Federal State Statistics Service. Retrieved from http://www.gks.ru/

Appendices

Appendix 1.

Financial Statement of Agroholding Vyborgec for 2016 - 2017 (1)

Наименование	Величина
ОКПО	23377011
ИНН	4703006839
Код единицы измерения (384 - тыс.руб, 385 - млн.руб)	384
11103 Нематериальные активы на конец отчетного года	312
11104 Нематериальные активы на конец предыдущего года	448
11503 Основные средства на конец отчетного года	4956783
11504 Основные средства на конец предыдущего года	3204816
11903 Прочие внеоборотные активы на конец отчетного года	2745
11904 Прочие внеоборотные активы на конец предыдущего года	1688
11003 Итого внеоборотных активов на конец отчетного года	4959840
11004 Итого внеоборотных активов на конец предыдущего года	3206952
12103 Запасы на конец отчетного года	440967
12104 Запасы на конец предыдущего года	276856
12203 Налог на добавленную стоимость по приобретенным ценностям на конец отчетного года	5030
12204 Налог на добавленную стоимость по приобретенным ценностям на конец предыдущего года	23037
12303 Дебиторская задолженность на конец отчетного года	706091
12304 Дебиторская задолженность на конец предыдущего года	505877
12403 Финансовые вложения (за исключением денежных эквивалентов) на конец отчетного года	174944
12503 Денежные средства и денежные эквиваленты на конец отчетного года	247239
12504 Денежные средства и денежные эквиваленты на конец предыдущего года	11423
12603 Прочие оборотные активы на конец отчетного года	6883
12604 Прочие оборотные активы на конец предыдущего года	5672
12003 Итого оборотных активов на конец отчетного года	1581154
12004 Итого оборотных активов на конец предыдущего года	822865
16003 БАЛАНС (актив) на конец отчетного года	6540994
16004 БАЛАНС (актив) на конец предыдущего года	4029817
13103 Уставный капитал (складочный капитал, уставный фонд, вклады товарищей) на конец отчетного года	51
13104 Уставный капитал (складочный капитал, уставный фонд, вклады товарищей) на конец предыдущего года	51
13403 Переоценка внеоборотных активов на конец отчетного года	115196
13404 Переоценка внеоборотных активов на конец предыдущего года	123421
13703 Нераспределенная прибыль (непокрытый убыток) на конец отчетного года	632130
13704 Нераспределенная прибыль (непокрытый убыток) на конец предыдущего года	584877
13003 ИТОГО капитал на конец отчетного года	747385
13004 ИТОГО капитал на конец предыдущего года	708357
14103 Долгосрочные заемные средства на конец отчетного года	4489790
14104 Долгосрочные заемные средства на конец предыдущего года	2465769

Financial Statement of Agroholding Vyborgec for 2016 - 2017 (2)

Наименование	Величина
14503 Прочие долгосрочные обязательства на конец отчетного года	61
14504 Прочие долгосрочные обязательства на конец предыдущего года	261
14003 ИТОГО долгосрочных обязательств на конец отчетного года	4489851
14004 ИТОГО долгосрочных обязательств на конец предыдущего года	2466030
15103 Краткосрочные заемные обязательства на конец отчетного года	378436
15104 Краткосрочные заемные обязательства на конец предыдущего года	401442
15203 Краткосрочная кредиторская задолженность на конец отчетного года	896340
15204 Краткосрочная кредиторская задолженность на конец предыдущего года	434989
15303 Доходы будущих периодов на конец отчетного года	6943
15304 Доходы будущих периодов на конец предыдущего года	3520
15403 Оценочные обязательства на конец отчетного года	22039
15404 Оценочные обязательства на конец предыдущего года	15479
15003 ИТОГО краткосрочных обязательств на конец отчетного года	1303758
15004 ИТОГО краткосрочных обязательств на конец предыдущего года	855430
17003 БАЛАНС (пассив) на конец отчетного года	6540994
17004 БАЛАНС (пассив) на конец предыдущего года	4029817
21103 Выручка за отчетный год	2307374
21104 Выручка за предыдущий год	1835105
21203 Себестоимость продаж за отчетный год	1439070
21204 Себестоимость продаж за предыдущий год	900703
21003 Валовая прибыль (убыток) за отчетный год	868304
21004 Валовая прибыль (убыток) за предыдущий год	934402
22103 Коммерческие расходы за отчетный год	250902
22104 Коммерческие расходы за предыдущий год	602294
22203 Управленческие расходы за отчетный год	210965
22204 Управленческие расходы за предыдущий год	145488
22003 Прибыль (убыток) от продаж за отчетный год	406437
22004 Прибыль (убыток) от продаж за предыдущий год	186620
23203 Проценты к получению за отчетный год	3025
23204 Проценты к получению за предыдущий год	1725
23303 Проценты к уплате за отчетный год	144802
23304 Проценты к уплате за предыдущий год	117875
23403 Прочие доходы за отчетный год	318900
23404 Прочие доходы за предыдущий год	293250
23503 Прочие расходы за отчетный год	521521
23504 Прочие расходы за предыдущий год	322172
23003 Прибыль (убыток) до налогообложения за отчетный год	62039
23004 Прибыль (убыток) до налогообложения за предыдущий год	41548
24103 Текущий налог на прибыль за отчетный год	23011
24104 Текущий налог на прибыль за предыдущий год	27572
24003 Чистая прибыль (убыток) за отчетный год	39028
24004 Чистая прибыль (убыток) за предыдущий год	13974
25003 Совокупный финансовый результат периода за отчетный год	39028
25004 Совокупный финансовый результат периода за предыдущий год	13974
32005 Величина капитала на 31 декабря предыдущего года (Добавочный капитал)	123421
32007 Величина капитала на 31 декабря предыдущего года (Нераспределенная прибыль)	584877
32008 Величина капитала на 31 декабря предыдущего года (ИТОГО)	708357

Financial Statement of Agroholding Vyborgec for 2016 - 2017 (3)

Наименование	Величина
33107 Увеличение капитала - всего (Нераспределенная прибыль (непокрытый убыток))	47253
33108 Увеличение капитала - всего (ИТОГО)	47253
33117 Чистая прибыль (Нераспределенная прибыль (непокрытый убыток))	39028
33118 Чистая прибыль (ИТОГО)	39028
33127 Переоценка имущества (Нераспределенная прибыль (непокрытый убыток))	8225
33128 Переоценка имущества (ИТОГО)	8225
33205 Уменьшение капитала - всего (Добавочный капитал)	8225
33208 Уменьшение капитала - всего (ИТОГО)	8225
33225 Переоценка имущества (Добавочный капитал)	8225
33228 Переоценка имущества (ИТОГО)	8225
33003 Величина капитала на 31 декабря отчетного года (Уставный капитал)	51
33005 Величина капитала на 31 декабря отчетного года (Добавочный капитал)	115196
33006 Величина капитала на 31 декабря отчетного года (Резервный капитал)	8
33007 Величина капитала на 31 декабря отчетного года (Нераспределенная прибыль (непокрытый убыток))	632130
33008 Величина капитала на 31 декабря отчетного года (ИТОГО)	747385
36003 Чистые активы на 31 декабря отчетного года	754328
36004 Чистые активы на 31 декабря предыдущего года	711877
41103 Поступления - всего за отчетный год	5357282
41113 От продажи продукции, товаров, работ и услуг за отчетный год	3895541
41193 Прочие поступления за отчетный год	26136
41203 Платежи - всего за отчетный год	5453252
41213 Поставщикам (подрядчикам) за сырье, материалы, работы, услуги за отчетный год	1698309
41223 В связи с оплатой труда работников за отчетный год	331808
41233 Проценты по долговым обязательствам за отчетный год	269229
41243 Налога на прибыль организаций за отчетный год	31976
41293 Прочие платежи за отчетный год	10526
41003 Сальдо денежных потоков от текущих операций за отчетный год	-95970
42103 Поступления - всего за отчетный год	3072
42113 От продажи внеоборотных активов (кроме финансовых вложений) за отчетный год	263
42143 Дивидендов, процентов по долговым финансовым вложениям и аналогичных поступлений от долевого участия в других организациях за отчетный год	2809
42203 Платежи - всего за отчетный год	1645991
42213 В связи с приобретением, созданием, модернизацией, реконструкцией и подготовкой к использованию внеоборотных активов за отчетный год	1645991
42003 Сальдо денежных потоков от инвестиционных операций за отчетный год	-1642919
43103 Поступления - всего за отчетный год	3376400
43113 Получение кредитов и займов за отчетный год	3150690
43203 Платежи - всего за отчетный год	1416761
43233 В связи с погашением (выкупом) векселей и других долговых ценных бумаг, возврат кредитов и займов за отчетный год	1416761
43003 Сальдо денежных потоков от финансовых операций за отчетный год	1959639
44003 Сальдо денежных потоков за отчетный период	220750
44903 Величина влияния изменений курса иностранной валюты по отношению к рублю за отчетный год	15066

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