Abstract
The competitive ability of agricultural production is mostly defined by the technical and technological potential of its manufacturing. Projects, programs, and portfolios are considered as technological systems in agricultural modeling. The systemic view can determine tasks of analysis and synthesis of these systems. The action of eight main factors can be determined on the basis of their effective reflection. The exposure of the system of principal occurrences affirms the availability of the cause-effect relationships between them. The stochastic character of the activity of agrometeorological conditions as for the course of mechanized and technological processes and agricultural projects demands using the method of their statistical modeling. Results of this modeling are functional indexes of projects, programs, and portfolios. Their cost and energetic value can prove rational (optimal) parameters of technical and technological equipment, and make many managerial decision problems.
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References
O. Sivakovska, M. Rudinets, M. Poteichuk, Agricultural management on the basis of information technologies. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska 9(3), 82–85 (2019). https://doi.org/10.35784/iapgos.239
S. Bushuev, N. Bushueva, I. Babaev, Creative Technology Management Projects and Programs: Monograph (Sammit-Kniga, Kyiv, 2010), p. 768
E. Marris, Agronomy: five crop researchers who could change the world. Nature 456, 563–568 (2008). https://doi.org/10.1038/456563a
N. Serdiuchenko, R. Saydak, Prognostication of corn capacity with the use of remote sensing data. Melior. Water Manag. 101, 41–50 (2014)
O. Sidorchuk, Engineering of machine systems: Monograph. (Kyiv: National Science Center “Institute of Agricultural Engineering and Electrification”, 2007), p. 263
The Standard for Portfolio Management (Project Management Institute, Four Campus Boulevard, Newton Square, PA, 2006), p. 53
M. Schindler, Harvesting project knowledge: a review of project learning methods and success factors. Int. J. Proj. Manag. 21, 219–228 (2003)
O. Sidorchuk, Planning of mechanized grain harvesting works and projects: Monograph. (Kyiv: National Science Center “Institute of Agricultural Engineering and Electrification”, 2012), p. 171
O. Sivakovska, Approval configuration products and their projects (according to decision support systems in the crop production). Thesis, 2016, p. 201
O. Shmatko, N. Stratiienko, R. Maneva, The formation of the project team for vertically integrated structure of the agroholding. Bull. NTU “HPI” 3(1225), 65–70 (2017)
T. Williams, Learning from projects. J. Oper. Res. Soc. 54, 443–451 (2003)
Organizational Project Management Maturity Model (PMI, Knowledge Foundation, Newton Square, PA, 2003), p. 150
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Sivakovska, O., Korobchuk, L., Redko, O., Redko, R., Zabolotnyi, O. (2022). Modeling and Management of the Technical and Technological Potential for the Agriculture Sector. In: Knapčíková, L., Peraković, D., Behúnová, A., Periša, M. (eds) 5th EAI International Conference on Management of Manufacturing Systems. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-67241-6_7
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DOI: https://doi.org/10.1007/978-3-030-67241-6_7
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