Skip to main content
  • 1837 Accesses

Abstract

New knowledge often arises at the intersection of different scientific schools when well-known laws of one science adapted to and interpreted by the other science enable to look at the studied phenomenon at the other angle. An example is application of the thermodynamical approach to the mathematical description and business system management focused on the decrease in their entropy and increase in productive efficiency. A theoretical approach proposed by the author becomes even more valuable as the national theory and practice do not contain any developments in the assessment of business system efficiency based on the energy-entropic method. The universality of the proposed method is based on the fact that all systems of the material world—wildlife and inanimate nature, technology and production are arenas of ever-present changes in the amounts of energy and entropy, studying of which can give new knowledge of laws governing functioning and development of such systems. This research shows scientifically-based application of the energy-entropic method to the assessment of economic efficiency of any production.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 179.00
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Energy Z transferred by mass can depend on the means of transition, whereas the amount of mass must remain the same.

  2. 2.

    Considering the material model of production, we do not analyze many non-material types of service, including so-called “services of financial intermediaries”.

  3. 3.

    Visually identical designation of the state of system S and entropy S in this context does not cause misinterpretation.

  4. 4.

    Actual specific power intensity can differ from the calculated values because of the usage of homogeneous but qualitatively different types of energy resources. In other words, it is possible to obtain different quantities of calories by burning the same type of fuel. To get a more precise estimation of the caloric content of power resources, for example, on the territory of Kazakhstan, it is necessary to correct the obtained coefficients for the discrepancy (in %) between calculated and actual power intensity in Kazakhstan based on the assumption that the entire territory has the same type of consumption and the same quality of power resources.

  5. 5.

    Gross domestic product (GDP) is used as a key economic indicator with which power indicators are compared. In conditions where the role of the non-productive sphere is a strong part of the increase of the total efficiency of usage of major production factors, the GDP is a more adequate indicator of economic development than the national income, covering as it does only the sphere of goods production.

  6. 6.

    It is necessary to note differences in the entropy values obtained from deviations of the production process parameters from the planned values and deviations from the statistical data for previous periods of time. The choice of the method of calculation depends on the research purpose and conditions.

  7. 7.

    The elements of the system and vectors-deviations have the same notations to avoid misinterpretations.

  8. 8.

    Checked by repeated computing experiments.

  9. 9.

    In order to check the difference in deviation values obtained in different ways.

  10. 10.

    An example of the estimation procedure is derivation of estimate (3.29) using Table 3.5.

References

  1. Mutanov, G.M., Useinov, B.M., Kutuzova, E.S.: New technologies in application of the laws of thermodynamics to studying of economic systems. In: Proceedings of International Scientific Conference Current Scientific Achievements and Fundamental Physical Training. Vestnik KazGU, p. 72 (1999)

    Google Scholar 

  2. Mutanov, G.M., Useinov, B.M., Kutuzova, E.S.: Application of the laws of thermodynamics to description and studying of economic systems. In: NKU Vestnik, Penropavlovsk, p. 80 (2000)

    Google Scholar 

  3. Ajibola, O.O., Aviara, N.A., Ajetumobi, O.E.: Sorption equilibrium and thermodynamic properties of cowpea (Vigna unguiculata). J. Food Eng. 58(4), 317–324 (2003)

    Article  Google Scholar 

  4. Da Silva, G., Kim, C.-H., Bozzelli, J.W.: Thermodynamic properties (enthalpy, bond energy, entropy, and heat capacity) and internal rotor potentials of vinyl alcohol, methyl vinyl ether, and their corresponding radicals. J. Phys. Chem. 110(25), 7925–7934 (2006)

    Article  Google Scholar 

  5. Tavakkoli, M., Masihi, M., Ghazanfari, M.H., Kharrat, R.: An improvement of thermodynamic micellization model for prediction of asphaltene precipitation during gas injection in heavy crude. Fluid Phase Equilib. 308(1–2), 153–163 (2011)

    Article  Google Scholar 

  6. Ferro, R., Cacciamani, G.: Remarks on crystallochemical aspects in thermodynamic modeling. Calphad 26(3), 439–458 (2002)

    Article  Google Scholar 

  7. Chen, W.-H.: Business process management: a thermodynamics perspective. J. Appl. Manag. Stud. 8, 241–257 (1999)

    Google Scholar 

  8. Bazarov, I.P., Thermodynamics. Vysshaya Shkola (1991), p. 376

    Google Scholar 

  9. Jaber, M.Y., Nuwayhid, R.Y., Rosen, M.A.: A thermodynamic approach to modelling the economic order quantity. Appl. Math. Model. 30, 867–883 (2006)

    Article  Google Scholar 

  10. Fisk, D.: Thermodynamics on main street: when entropy really counts in economics. Ecol. Econ. 70, 1931–1936 (2011)

    Article  Google Scholar 

  11. Cutrini, E.: Using entropy measures to disentangle regional from national localization patterns. Reg. Sci. Urban Econ. 39, 243–250 (2009)

    Article  Google Scholar 

  12. Yakovlev, V.B., et al.: Construction of Models of Continuous Technological Processes: Teaching Aid. KazPTI, Alma-Ata (1988), p. 31

    Google Scholar 

  13. Wehrl, A.: General properties of entropy. Rev. Mod. Phys. 50, 221 (1978)

    Article  Google Scholar 

  14. Glensdorf, P., Progozhin, I.: Thermodynamic Theory of Structure, Stability and Fluctuations. Mir, Moscow (1973), p. 280

    Google Scholar 

  15. Markvart, T.: Solar cell as a heat engine: energy-entropy analysis of photovoltaic conversion. Phys. Status Solidi (a) 205(12), 2752–2756 (2008)

    Article  Google Scholar 

  16. Peng, L., Sun, H., Sun, D., Yi, J.: The geometric structures and instability of entropic dynamical models. Adv. Math. 227, 459–471 (2011)

    Article  Google Scholar 

  17. Korn, G., Korn, T.: Reference Book on Mathematics for Scientists and Engineers. Nauka, Moscow (1973), p. 831

    Google Scholar 

  18. Kurosk, A.G.: Course of Higher Algebra. Nauka, Moscow (1975), p. 432

    Google Scholar 

  19. Odum, G., Odum, E.: Energy Basis of Man and Nature. Progress, Moscow (1978), p. 380

    Google Scholar 

  20. Cafaro, C., Giffin, A., Ali, S.A., Kim, D.-H.: Reexamination of an information geometric construction of entropic indicators of complexity. Appl. Math. Comput. 217(1), 2944–2951 (2010)

    Article  Google Scholar 

  21. Georgescu-Roegen, N.: Entropy Law and Economic Process. Cambridge, MA (1971)

    Google Scholar 

  22. Kapur, J.N., Kesavan, H.K.: Entropy Optimization Principles with Applications p. 408. Academic Press, San Diego (1992)

    Google Scholar 

  23. Caticha, A.: Entropic dynamics. In: Fry, R.L. (ed.) Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP Conf. Proc., vol. 617, p. 302 (2002)

    Google Scholar 

  24. Jost, L.: Entropy and diversity. Oikos 103(2), 363–375 (2006)

    Article  Google Scholar 

  25. Mutanov, G.M., Kutuzova, E.S.: Electro-Entropic Methods of Assessment and Control of Economic Systems. Galym, Almaty (2002), p. 142

    Google Scholar 

  26. de Marchi, N.B., Blaug, M.: Appraising Economic Theories: Studies in the Methodology of Research Programs. Edward Elgar, Brookfield (1991)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mutanov, G. (2015). Energy-Entropic Methods in Assessment and Control of Economic Systems. In: Mathematical Methods and Models in Economic Planning, Management and Budgeting. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45142-7_3

Download citation

Publish with us

Policies and ethics