Main Article Content
Balance of Labour Markets and Educational Services, Decision Support, Expert Assessments, Resources in The Construction Industry, Oriented Graph
Purpose: In this article, the procedure of the development of the forecast model is described. Within the model based on expert assessment factors that affect the imbalance between labour markets and educational services in the construction industry have been identified. Graphical visualization of models in the form of graphs is presented. On this basis, scenarios of social and economic development of the region in this area (optimistic, realistic and pessimistic scenarios) are defined.
Methodology: The developed method for constructing a predictive model includes the following steps. Stage 1 - a comprehensive consideration of the factors, Stage 2 - conducting the procedure for the selection of experts, Stage 3 - a preliminary assessment of the importance of groups of factors, Stage 4 - the construction of a system of interdependent equations describing LM and ESM, Stage 5 - development of a set of graph-analytical models that visualize the nature and direction of the influence of factors and groups of factors on LM and ESM
Result: While finding an imbalance between the labor and educational services markets, the most significant criteria from those considered in the study were identified. Oriented graphs visualizing the direct and indirect influence of significant criteria on the markets in question were constructed. The importance of the impact of potential measures, both on the labor market and on the educational services market, was calculated.
Applications: This research can be used for universities, teachers, and students.
Novelty/Originality: In this research, the model of Development of the Forecast Model for Management of the Disbalance between the Labor Markets and Educational Services in the Construction Industry is presented in a comprehensive and complete manner.
2. Ivashchuk, O. A., Konstantinov, I. S., & Udovenko, I. V. (2015). International Journal of Applied Engineering Research (IJAER), 10(12), 31371-31380.
3. Ivashchuk, O.A., Konstantinov, I.S., Udovenko, I.V., 2015. Potential of the Region of the Smart Control System. Smart Education and Smart e-Learning, 41:481-490. https://doi.org/10.1007/978-3-319-19875-0_43
4. Ivashchuk, O.A., Udovenko, I.V., 2015. Formation and development of personnel potential as a basis for creating new technologies at the junction of engineering and computer and computer sciences. Construction and Renovation, 6 (62): 75-80. (In Russian).
5. Lomakin, V. V., & Lifirenko, M. V. (2014). Supporting Tools for Decision-making in the Outdoor Lighting Control Systems. Research Journal of Applied Sciences, 9 (12), 1185-1190.
6. Lomakin, V. V., Putivtseva, N. P., Zaitseva, T. V., Liferenko, M. V., & Zaitsev, I. M. (2017). Multi-critera selection of a corporate system by using paired comparison analysis. J. Fundam. Appl. Sci., 9 (7S), 1472-1482.
7. Mamatov, A. V., Udovenko, I. V., & Putivtseva, N. P. (2018). Development of decision support models for managing the balance of labor markets and educational services in the construction industry. Information systems and technologies, 5(109), 57-65 (In Russian).
8. Putivtseva, N. P., Igrunova, S. V., Zaitseva, T. V., Nesterova, E. V., & Pusnaya, O. P. (2015). Decision support system in the implementation of projects. Scientific Reports of Belgorod State University. Series: History. Political science. Economy. Computer science, 7(204), 34(1), 170-174 (In Russian).
9. Putivtseva, N. P., Zaitseva, T. V., Pusnaya, O. P., Kuz`micheva, T. G., & Kaljuzhnaja, E. V. (2016). On the Use of Expert Evaluation Methods to Select the Electronic Document Management System. Journal of Engineering and Applied Sciences, 11(4), 733-737.
10. Zurn, P., Dal Poz, M. R., Stilwell, B., & Adams, O. (2004). Imbalance in the health workforce. Human resources for health, 2(1), 13. https://doi.org/10.1186/1478-4491-2-13
11. Bennett, J. (2003). Starting strong: The persistent division between care and education. Journal of early childhood research, 1(1), 21-48. https://doi.org/10.1177/1476718X030011006
12. Wieclaw, J., Agerbo, E., Mortensen, P. B., & Bonde, J. P. (2006). Risk of affective and stress related disorders among employees in human service professions. Occupational and Environmental Medicine, 63(5), 314-319. https://doi.org/10.1136/oem.2004.019398
13. Goos, M., Manning, A., & Salomons, A. (2009). Job polarization in Europe. American economic review, 99(2), 58-63. https://doi.org/10.1257/aer.99.2.58
14. Gorina, A. P. (2016). Issues and Prospectives of the Educational Service Market Modernization. European Research Studies, 19, 227.
15. Petras, E. M. (1981). 3: The Global Labor Market in the Modern World-Economy. International Migration Review, 15(1_suppl), 44-63. https://doi.org/10.1177/019791838101501s05
16. Gyourko, J., & Tracy, J. (1989). The importance of local fiscal conditions in analyzing local labor markets. Journal of Political economy, 97(5), 1208-1231. https://doi.org/10.1086/261650
17. Dabalen, A., Oni, B., & Adekola, O. A. (2001). Labor market prospects for university graduates in Nigeria. Higher Education Policy, 14(2), 141-159. https://doi.org/10.1016/S0952-8733(01)00010-1
18. Peri, G. (2016). Immigrants, productivity, and labor markets. Journal of Economic Perspectives, 30(4), 3-30. https://doi.org/10.1257/jep.30.4.3
19. Myles, J. (1990). States, Labor Markets, 1 r\and Life Cycles LA±. Beyond the marketplace: Rethinking economy and society, 271.
20. Zhang, L., Huang, J., & Rozelle, S. (2002). Employment, emerging labor markets, and the role of education in rural China. China Economic Review, 13(2-3), 313-328. https://doi.org/10.1016/S1043-951X(02)00075-5
21. Lewin-Epstein, N., & Semyonov, M. (1994). Sheltered labor markets, public sector employment, and socioeconomic returns to education of Arabs in Israel. American Journal of Sociology, 100(3), 622-651. https://doi.org/10.1086/230576