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SYSTEM OF PREVENTIVE АCTION OF CONSTRUCTION ENTERPRISES ON THE BASIS OF IDENTIFICATION OF ANTICRISIS POTENTIAL | Bielienkova | Scientific Journal of Astana IT University

SYSTEM OF PREVENTIVE АCTION OF CONSTRUCTION ENTERPRISES ON THE BASIS OF IDENTIFICATION OF ANTICRISIS POTENTIAL

O. Bielienkova, S. Stetsenko, L. Sorokina, O. Molodid, N. Bolila

Аннотация


Peculiarities of formation of anti-crisis potential of construction enterprises are considered. Construction companies are rapidly adapting to the requirements of the digital economy, transforming the management structure, business processes. To improve the system of preventive protection and protection of enterprises from loss of viability and subsequent self-liquidation or bankruptcy, a system of indicators is proposed, which allows to identify existing risks and threats at an early stage. In order to improve the mechanism of control of the stability of the system of anti-crisis potential of construction enterprises in the medium term, a cluster analysis was performed. The study was based on 53 enterprises of the type of activity «construction». This study allowed us to identify the most important, priority, leading indicators of the loss of economic security and to clarify the threshold values of these indicators and the degree of their «blurring» in the unstable conditions of the external economic environment. Indicators of crisis state of construction enterprises are determined by means of fuzzy sets, among which it is possible to allocate: level of capital consumption by owners, level of operating sales on retained earnings, return on working capital on retained earnings, cost of operating expenses on personnel costs, term of accounts payable. The main direct and indirect signs of deterioration of the anti-crisis potential of the enterprise are revealed. The model of information interaction of divisions of the enterprise is offered. All processes of information exchange with the help of IMS (Information Management System) have the ultimate goal of the maximum possible exclusion from the business practice of paper documents and the transition to direct paperless data exchange (in the practice of construction is an example of creating a BIM-model of objects).

Ключевые слова


economic security, anti-crisis potential, digitalization, financial indicators, construction enterprise.

Полный текст:

PDF (English)

Литература


Zeltser, R., Bielienkova, O., Novak, Ye. and Dubinin, D. (2019). Digital Transformation of Resource

Logistics and Organizational and Structural Support of Construction. Nauka i innovatsii, vol. 15(5),

-51

Tugay, O.A., Zeltser, R.Ya., Kolot, M.A., Panasiuk, I.O. (2019). Organization of Supervision over

Construction Works Using Uavs and Special Software. Nauka i innovatsii, vol. 15(4), 23-32

Tugay, O.A., Shebek, M.O., Dubynka, O.V. 2019). Identifying New and Structuring Existing

Organizational and Technological Approaches to Managing the Cycle of Engineering Preparation

for a Construction and Investment Project. Nauka innov. 15(2), 105-114

Abidali, A.F., & Harris, F. (1995). A methodology for predicting company failure in the

construction industry. Construction Management and Economics, vol. 13(3), 189-196. doi:

1080/01446199500000023

Chan, J. K. W., Tam, C. M., & Cheung, R. K. C. (2005). Construction firms at the crossroads in hong kong:

Going insolvency or seeking opportunity. Engineering, Construction and Architectural Management,

vol. 12(2), 111-124. doi: 10.1108/09699980510584476

Edum-Fotwe, F., Price, A., & Thorpe, A. (1996). A review of financial ratio tools for predicting

contractor insolvency. Construction Management and Economics, vol. 14(3), 189-198. doi:

1080/014461996373458

Kangari, R., Farid, F., & Elgharib, H.M. (1992). Financial performance analysis for construction

industry. Journal of Construction Engineering and Management, vol. 118(2), 349-361. doi: 10.1061/

(ASCE)0733-9364(1992)118:2(349)

Mason, R. J., & Harris, F. C. (1979). Predicting company failure in the construction industry. Proceedings

Institution of Civil Engineers, vol. 66(2), 301-307.

Tserng, H., Lin, G., Tsai, L., & Chen, P. (2011). An enforced support vector machine model for

construction contractor default prediction. Automation in Construction, 20(8), 1242-1249. doi:

1016/j.autcon.2011.05.007

Deakin, E. B. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting

Research, vol. 10(1), 167-179.

Edison, H.J. (2003). Do indicators of financial crises work? an evaluation of an early warning system.

International Journal of Finance and Economics, vol. 8(1), 11-53. doi: 10.1002/ijfe.197

Karas, M., & Režňáková, M. (2017). The stability of bankruptcy predictors in the construction and

manufacturing industries at various times before bankruptcy. E a M: Ekonomie a Management, 20(2),

-133. doi: 10.15240/tul/001/2017-2-009

Lin, F., Liang, D., & Chen, E. (2011). Financial ratio selection for business crisis prediction. Expert

Systems with Applications, 38(12), 15094-15102. doi: 10.1016/j.eswa.2011.05.035

Spicka, J. (2013). The financial condition of the construction companies before bankruptcy. European

Journal of Business and Management, vol. 5(23), 160-169.

Thomas Ng, S., Wong, J. M. W., & Zhang, J. (2011). Applying Z-score model to distinguish insolvent

construction companies in China. Habitat International, vol. 35(4), 599-607. doi: 10.1016/j.

habitatint.2011.03.008

Tian, S., Yu, Y., & Guo, H. (2015). Variable selection and corporate bankruptcy forecasts. Journal of

Banking and Finance, vol. 52, pp. 89-100.

Tseng, F., & Hu, Y. (2010). Comparing four bankruptcy prediction models: Logit, quadratic interval

logit, neural and fuzzy neural networks. Expert Systems with Applications, vol. 37(3), 1846-1853. doi:

1016/j.eswa.2009.07.081

Wang, Y., & Lee, H. (2008). A clustering method to identify representative financial ratios. Information

Sciences, vol. 178(4), 1087-1097. doi: 10.1016/j.ins.2007.09.016

Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress

prediction models. Journal of Accounting Research, vol. 22(SUPPL.), 59-82. Retrieved from www.

scopus.com

Stetsenko, S.P., Tytok, V.V., Emelianova, O.M., Bielienkova, O. Yu and Tsyfra T.Yu. (2020). Management

of Adaptation of Organizational and Economic Mechanisms of Construction to Increasing Impact

of Digital Technologies on the National Economy. Journal of Reviews on Global Economic. no. 9, 149-

Zvarikova, K., Spuchlakova, E., & Sopkova, G. (2017). International comparison of the relevant

variables in the chosen bankruptcy models used in the risk management. Oeconomia Copernicana,

vol. 8(1), 145-157. doi: 10.24136/oc.v8i1.10

Rutkovskaya, D., Pilins’kij, & M.,Rutkovskij, L. (2007). Nejronnye seti, geneticheskie algoritmy i

nechetkie sistemy. M.: Goryachaya liniya – Telekom.

Tugai O.A., Hryhorovskyi P.Ye., Khyzhniak V.O., Stetsenko S.P., Bielienkova O.Yu., Molodid О.S.,

Chernyshev D.O (2019). Organizational and technological, economic quality control aspects in the

construction industry: collective monograph – Lviv-Toruń: Liha-Pres.

Baležentis, T., & Zeng, S. (2013). Group multi-criteria decision making based upon interval-valued

fuzzy numbers: An extension of the MULTIMOORA method. Expert Systems with Applications, vol.

(2), 543-550. doi: 10.1016/j.eswa.2012.07.066




DOI: http://dx.doi.org/10.37943/AITU.2020.53.13.002

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