Development of the controlling system in the management of dairy clusters

Authors

DOI:

https://doi.org/10.15587/1729-4061.2017.108591

Keywords:

strategic and operational controlling, mathematical procedures for controlling, dairy cluster, regional management

Abstract

The present research focuses on the development of mathematical procedures for controlling the regional management over product clusters. In order to improve mathematical support for the strategic controlling, we modified the rating assessment by applying business, technological, and social indicators of a dairy sector, due to which it becomes possible to run a quantitative external analysis of efficiency of the regional management. Mathematical procedures of operational controlling allowed us to identify the reserves of internal environment in the activities of regional clusters of the dairy sector. The first option of controlling is formalized by the model of finding the shortest paths to spread innovations from the regional leaders of dairy clusters. The second reserve of controlling is based on modeling the optimal cost-cutting by the criterion of maximal increase in profitability under conditions of using own feed crops. The third reserve of controlling was confirmed by the rank statistical tests related to improving productivity due to the effect of large-scale production of milk. Article contains results of practical approbation of the proposed system of mathematical procedures for controlling regional management over dairy clusters.

Author Biographies

Natalia Vasylieva, Dnipropetrovsk State Agrarian and Economic University S. Yefremova str., 25, Dnipro, Ukraine, 49600

Doctor of Economic Sciences, Professor, Head of Department

Department of Informative Systems and Technologies 

Oleksandr Velychko, Dnipropetrovsk State Agrarian and Economic University S. Yefremova str., 25, Dnipro, Ukraine, 49600

Doctor of Economic Sciences, Associate Professor, Head of Department

Department of Management and Law 

References

  1. Kavallari, A., Fellmann, T., Gay, S. H. (2014). Shocks in economic growth = shocking effects for food security? Food Security, 6 (4), 567–583. doi: 10.1007/s12571-014-0368-y
  2. Grafton, R. Q., Daugbjerg, C., Qureshi, M. E. (2015). Towards food security by 2050. Food Security, 7 (2), 179–183. doi: 10.1007/s12571-015-0445-x
  3. Headey, D., Ecker, O. (2013). Rethinking the measurement of food security: from first principles to best practice. Food Security, 5 (3), 327–343. doi: 10.1007/s12571-013-0253-0
  4. State Statistics Service of Ukraine. Agriculture in Ukraine. Statistics (2017). Available at: http://www.ukrstat.gov.ua/
  5. Lueg, R., Radlach, R. (2016). Managing sustainable development with management control systems: A literature review. European Management Journal, 34 (2), 158–171. doi: 10.1016/j.emj.2015.11.005
  6. Dutta, S. K., Lawson, R. A., Marcinko, D. J. (2016). A management control system to support corporate sustainability strategies. Advances in Accounting, 32, 10–17. doi: 10.1016/j.adiac.2015.12.001
  7. Durendez, A., Ruiz-Palomo, D., Garcia-Perez-de-Lema, D., Dieguez-Soto, J. (2016). Management control systems and performance in small and medium family firms. European Journal of Family Business, 6 (1), 10–20. doi: 10.1016/j.ejfb.2016.05.001
  8. Pondeville, S., Swaen, V., De Ronge, Y. (2013). Environmental management control systems: The role of contextual and strategic factors. Management Accounting Research, 24 (4), 317–332. doi: 10.1016/j.mar.2013.06.007
  9. O’Grady, W., Morlidge, S., Rouse, P. (2016). Evaluating the completeness and effectiveness of management control systems with cybernetic tools. Management Accounting Research, 33, 1–15. doi: 10.1016/j.mar.2016.02.003
  10. Bedford, D. S., Malmi, T., Sandelin, M. (2016). Management control effectiveness and strategy: An empirical analysis of packages and systems. Accounting, Organizations and Society, 51, 12–28. doi: 10.1016/j.aos.2016.04.002
  11. Godfray, H. C. J., Garnett, T. (2014). Food security and sustainable intensification. Philosophical Transactions of the Royal Society B: Biological Sciences, 369 (1639), 20120273–20120273. doi: 10.1098/rstb.2012.0273
  12. Dusan, S., Ladislav, M., Jan, B. (2016). Assessment of milk production competitiveness of the Slovak Republic within the EU-27 countries. Agricultural Economics (Zemědělská Ekonomika), 62 (10), 482–492. doi: 10.17221/270/2015-agricecon
  13. Kroupova, Z. Z. (2016). Profitability development of Czech dairy farms. Agricultural Economics (Zemědělská Ekonomika), 62 (6), 269–279. doi: 10.17221/131/2015-agricecon
  14. Bakucs, Z., Ferto, I. (2016). Empirical tests of sale theories: Hungarian milk prices. Agricultural Economics (Zemědělská Ekonomika), 61 (11), 511–521. doi: 10.17221/168/2014-agricecon
  15. Looijen, A., Heijman, W. (2013). European agricultural clusters: how can European agricultural clusters be measured and identified? Economics of Agriculture, 60 (2), 337–353. Avaikabke at: http://ageconsearch.umn.edu/record/152812/files/10%20-%20Looijen_%20Heijman.pdf
  16. Vasylieva, N. K., Vinichenko, I. I., Katan, L. I. (2015). Economic and mathematical evaluation of Ukrainian agrarian market by branches. Economic Annals-XXI, 154 (9-10), 41–44. Available at: http://soskin.info/userfiles/file/2015/9-10_2015/Vasylieva_Vinichenko_Katan.pdf
  17. Vasylieva, N. (2016). Cluster models of households’ agrarian production development. Economic Annals-ХХI, 158 (3-4(2)), 13–16. doi: 10.21003/ea.v158-03
  18. Spicka, J., Smutka, L., Selby, R. (2016). Recent areas of innovation activities in the Czech dairy industry. Agricultural Economics (Zemědělská Ekonomika), 61 (6), 249–264. doi: 10.17221/128/2014-agricecon
  19. Bedford, D. S. (2015). Management control systems across different modes of innovation: Implications for firm performance. Management Accounting Research, 28, 12–30. doi: 10.1016/j.mar.2015.04.003
  20. Velychko, O. (2015). Integration of SCOR-Modeling and Logistical Concept of Management in the System of Internal Transportation of Milk Cooperative. Mediterranean Journal of Social Sciences. doi: 10.5901/mjss.2015.v6n1s2p14
  21. Krpalkova, L., Cabrera, V. E., Kvapilik, J., Burdych, J. (2016). Dairy farm profit according to the herd size, milk yield, and number of cows per worker. Agricultural Economics (Zemědělská Ekonomika), 62 (5), 225–234. doi: 10.17221/126/2015-agricecon
  22. Velychko, O. (2014). Fundamental Basis and Connection of Modern Entrepreneurial Logistics and SCM. Review of European Studies, 6 (4). doi: 10.5539/res.v6n4p135
  23. Vasylieva, N. (2013). Forecasting of prices in the field of crops-growing in Ukraine and regions. Economic Annals-XXI, 11-12 (2), 26–29. Available at: http://soskin.info/userfiles/file/2013/11-12%202013%20EX/11-12(2)/Vasylieva.pdf
  24. Vasylieva, N., Pugach, A. (2017). Economic assessment of technical maintenance in grain production of Ukrainian agriculture. Bulgarian Journal of Agricultural Science, 23 (2), 198–203. Available at: http://www.agrojournal.org/23/02-04.pdf
  25. FAO. Food and Agriculture Organization of the United Nations. Statistics Division (2017). Available at: http://www.fao.org/faostat/en/#data
  26. Main Statistics Office in Dnipropetrovsk region. Agriculture in Dnipropetrovsk region. Statistics (2017). Available at: http://dneprstat.gov.ua/
  27. World’s Top Exports. World’s Top Exported Fresh Food Products (2017). Available at: http://www.worldstopexports.com/top-milk-exporting-countries/
  28. The World Bank. Arable land (% of land area). Statistics (2014). Available at: http://data.worldbank.org/indicator/AG.LND.ARBL.ZS

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Published

2017-08-31

How to Cite

Vasylieva, N., & Velychko, O. (2017). Development of the controlling system in the management of dairy clusters. Eastern-European Journal of Enterprise Technologies, 4(3 (88), 20–26. https://doi.org/10.15587/1729-4061.2017.108591

Issue

Section

Control processes