Lean performance evaluation of dairy cow farming processes with mathematical model development

Authors

DOI:

https://doi.org/10.58423/2786-6742/2023-3-54-64

Keywords:

lean management, lean controlling, agrobusiness, performance evaluation, fuzzy logic

Abstract

Management sciences, especially controlling, are undergoing extensive changes. Various mathematical-statistical and IT solutions help organizations develop their systems and extract relevant information from data structures, thereby supporting effective decision-making and organizational operations. Agriculture is a special sector, but management functions apply here too, and modern tools and methods support the implementation of efficient operations. Dairy farming is a particularly important sector in agriculture, where controlling systems are developed in response to special requirements. The controlling activity of the sector is significantly influenced by the development of digitalization, which has resulted in the monitoring of processes and organizational performance evaluation becoming more extensive and detailed. Lean management is also an excellent method for increasing the efficiency of processes and organizational performance in the agricultural sector, which can be used to optimize processes, identify unnecessary activities and ensure appropriate task control. In this way, controlling systems must take into account the importance of lean management and contribute to the performance evaluation of organizational lean. In our study, we develop a lean performance evaluation model through an extended case study, which is suitable for evaluating the lean performance of the examined dairy farm. We used a fuzzy triangular function to evaluate the performance of enterprises, which represents the value of the given parameter with a triangular distribution. With dynamically growing and usable data, the model is able to provide continuous feedback on organizational lean operation and possible intervention points.

Author Biographies

Gergő Thalmeiner, Hungarian University of Agriculture and Life Sciences

PhD, аssociate Professor

Sándor Gáspár, Hungarian University of Agriculture and Life Sciences

PhD, аssociate Professor

Márk Tóth, Hungarian University of Agriculture and Life Sciences

PhD, аssociate Professor

References

Anthony R. N., Govindarajan, V. (2006): Management Control Systems 12th Edition. New York: McGraw-Hill Education.

Babbie, E. (2012) The Practice of Social Research, 13th Edition, New York: Wadsworth Publishing. pp. 52-61. ISBN 978-1133049791

Barta, Á. - Molnár, M. (2021) Forecasting oil price based on online occurrence. Modern Science, 1, 5-11. p.

Bayou M. E., Korvin A. (2008): Measuring the leanness of manufacturing systems—A case study of Ford Motor Company and General Motors. In: J. Eng. Technol. Manager, 25, 287–304. p. DOI: https://doi.org/10.1016/j.jengtecman.2008.10.003

Caicedo Solano N. E., García Llinás G. A., Montoya‐Torres, J. R. (2019): Towards the integration of lean principles and optimization for agricultural production systems: a conceptual review proposition. Journal of the Science of Food and Agriculture, 100, 453–464. p. DOI: https://doi.org/10.1002/jsfa.10018

Chege, S. M. - Wang, D. (2020) The impact of entrepreneurs’ environmental analysis strategy on organizational performance. Journal of Rural Studies, 77, 113-125. p. DOI: https://doi.org/10.1016/j.jrurstud.2020.04.008

Giangiacomo, G. (2017): Vagueness and formal fuzzy logic: Some criticisms. In: Logic and Logical Philosophy, 26 (4) 431–460. p.

Havasi I., Benő D. (2012): Hagyományos és Fuzzy nem Felügyelt osztályozás összehasonlítása vegetációs index példáján. In: Tájökológiai Lapok, 10 (1), 115–123. p. DOI: https://doi.org/10.56617/tl.3777

Horváth, P. (2011): Controlling. München: Vahlen. DOI: https://doi.org/10.15358/9783800644551

Melin, M., Barth, H. (2018): Lean in Swedish agriculture: strategic and operational perspectives. Production Planning & Control, 1–11. p. DOI: https://doi.org/10.1080/09537287.2018.1479784

Schnellbach, P. - Reinhart, G. (2015): Evaluating the effects of energy productivity measures on lean production key performance indicators. Procedia CIRP, 25, 492-497. p. DOI: https://doi.org/10.1016/j.procir.2014.07.094

Sütő D. (2017): A controlling fejlődéstörténete, helye és szerepe a gazdálkodó szervezetekben. In: International Journal of Engineering and Management Sciences, 2 (4) 466-477. p. DOI: https://doi.org/10.21791/IJEMS.2017.4.37.

Székely, Cs. (2016): A magyar mezőgazdaság stratégiai kérdései. Gazdálkodás, 16-30. p.

Zadeh L. A. (1965): Fuzzy sets. In: Information and Control, 8 (3) 338–353. p. DOI: https://doi.org/10.1016/S0019-9958(65)90241-X

Zadeh L. A. (1978): PRUF—a meaning representation language for natural languages. In: International Journal of Man-Machine Studies, 10 (4), 395-460. p. DOI: https://doi.org/10.1016/S0020-7373(78)80003-0

Zéman, Z., Tóth, A. (2017): Stratégiai pénzügyi controlling és menedzsment. Budapest: Akadémiai Kiadó.

Downloads

Published

2023-09-10

Issue

Section

National and regional economy