Economic Models used by Shipping Decision Makers
Keywords:shipping, management, economic models
Transport economics is the branch of economic science whose object and purpose are to interpret
and substantiate theoretically "and practically" the facts, acts, and economic behaviors that meet the needs of
movement, distribution, and physical distribution of resources of goods, products, goods, and people, by use
of transport capacities. The purpose of this paper is to present different approaches of modeling and
simulation economic processes. It is known that those methods managers can apply a wide range of
management methods and techniques. From the practice of economically developed countries, the manager
uses modeling as an alternative to the exact sciences. Computer-assisted modeling is based on the idea that
man cannot be excluded from running a system. He is the primary source of formulating hypotheses about
system behavior and the only one to include the results of different evolutionary variants in an integrative
appropriate level of business process standardization. Bus Res, 9 (2), pp. 335–375.
Andonie, R., Gârbacea, I. (1995). Algoritmi Fundamentali O Perspectiva C++. Cluj Napoca: Editura Libris.
Carp, D. (2000). Management cantitativ in shipping modelare matematice. București: Editura Didactică și
Cucu, V. (2014). Consideratii privind conceptul de modelare si stimulare. Buletinul Universitatii Nationale de
Aparare ”Carol I”, pp. 39- 43.
Dănescu, T., Spătăcean, I.-O., Popa, M.-A., & Sîrbu, C.-G. (2021). The Impact of Corporate Governance
Mechanism over Financial Performance: Evidence from Romania. Sustainability, 13(19), pp.1-14.
Frankel, E. G. (2006). Strategic decision making in shipping. Marine Policy, 16 (2), pp.123-132.
Frankel, E. G. (2007). Hierarchical logic in shipping policy and decision-making. Maritime Policy and
Management, 19 (3), pp. 211- 221.
Hâncu, D., Florescu, M. (2006). Modelarea si simularea proceselor economice, Editura Fundaţiei România de
Isbăsoiu, E. C. (2021). Numerical modeling and simulation in various processes. Annals of Spiru Haret
University, Economic Series, pp. 99-106.
Medio, A. (n.d.). (2009). Mathematical models in economics. UDINE, Italy: Encyclopedia of Life Support
Systems Vol.III (EOLSS).
Moffat, M. (2021). What Is Mathematical Economics?. ThoughtCo, Retrieved from:
Nicolescu, O. (1992). Management. Bucuresti: Editura Didactica si Pedagogica Bucuresti.
Nikulina, T.N., Zhirnova, I.S., Stupina, A.A. and Zhirnov, A.A. (2019). Mathematical modeling of economic
processes in complex systems (on the example of Krasnoyarsk municipality). Journal of Physics:
Conference Series, doi:10.1088/1742-6596/1353/1/012118.
Polumiienko, S., Gorda, S,. (2017). Game-theoretical resource model of balanced technological development.
Mathematical modeling in economy, No.3-4, pp.4-9.
Popa, C., Hăulică, D. (2008). Organizarea transporturilor navale, Ed. Academiei Navale Mircea cel Bătrân,
Prazak P., Kovarnic, J. (2019). Nonlinear Phenomena in Cournot Duopoly Model. Modelling of Economic
Systems, 6 (3), 30, pp. 29-32.
Rădulescu, I. C. (2015). Rezolvarea unor probleme de optimizare multi-obiectiv bazată pe algoritmi evolutivi.
Revista Română de Informatică şi Automatică, 25 (2), pp. 39- 48.
Suciu, C. R. (1997). Modelarea și simularea proceselor economice, ediția a II-a. București: Editura Didactică și
Weske, M., van der Aalst, W.M.P., Verbeek, H.M.W. (2004). Advances in business process management. Data
& Knowledge Engineering, 50, pp.1-8.
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