Modelling of management activity of the organization considering the impact of implicit factors in business processes
DOI:
https://doi.org/10.15587/1729-4061.2018.121647Keywords:
implicit factors, fuzzy set theory, business processes, management activity, investment potentialAbstract
The article presents a further development of theoretical investigation of management activity of the organization considering implicit factors of influence of the economic system and questions of effective usage of intangible resources. The authors substantiate the objective need for improvement of the mechanism of assessment of implicit factors from the position of maximizing the efficiency of business processes of the enterprise and formation of its potential. Creation of such mechanism, in the term, allows developing the economic and mathematical hierarchical model of the assessment of the influence of implicit factors on further successful activity of the organization, which is aimed at improvement of the process of business process management in conditions of informational economy.
The essence of the proposed method is to use expert assessments, which quantitatively characterize the object of the research, for the description of the economic problem. In the future, reasonable management decisions are made on their basis. At the same time, the traditional mathematical apparatus does not include tools that can help to reflect the fuzziness of the assessments of the group of experts. During the modelling of complex business processes, it is also necessary to consider a significant number of subjective and implicit factors. Therefore, the traditional quantitative analysis will not be practical under the condition of its acceptable accuracy.
The methodology of expert assessment was proposed in this paper. It is based on the main provisions of the fuzzy set theory and the construction of the membership function by means of analytical procedures. For this purpose, two interconnected tasks were consistently solved. Firstly, we made a quantitative assessment of the degree of expert consistency based on the calculation of fuzzy indexes. Secondly, we made aggregation of the results obtained by means of construction of the membership function, which is adequate to the investigated system. Practical realization of these tasks was accomplished by means of the well-known algorithms of the apparatus of the fuzzy set theory.
The effectiveness of the proposed model was tested on the example of the assessment of the investment potential of the sustainable development of the mining exporting company “Limited Liability Company “Hlukhiv quartzite quarry” ” (Ukraine) with the usage of the expert method. The article includes the comparison and economic substantiation of the results of the assessment of the influence of implicit factors on the specified company before and after application of the proposed methodology.
The proposed mechanism of taking into account implicit factors on the basis of the hierarchical economic and mathematical model allows optimizing management decisions in business processes and provides the possibility of developing the adaptive management system of the modern manufacturing organization.
Thus, the proposed methodology allows quantifying the influence of implicit factors on the investment potential of the sustainable development of the enterprise in the form of aggregated assessment. The last one is determined by means of the expert method. This will give the possibility to make economically sound management and technological decisions on major business processes. In particular, regarding the expediency of increasing the volume of quartz production at the enterprise under review in the short run.
References
- Pakseresht, M., Seyyedi, M. A., Zade, M. M., Gardesh, H. (2009). Business process measurement model based on the fuzzy multi agent systems. AIKED Proceedings of WSEAS, 501–506.
- Huang, S. Y., Lee, C.-H., Chiu, A.-A., Yen, D. C. (2014). How business process reengineering affects information technology investment and employee performance under different performance measurement. Information Systems Frontiers, 17 (5), 1133–1144. doi: 10.1007/s10796-014-9487-4
- Van Looy, A., Shafagatova, A. (2016). Business process performance measurement: a structured literature review of indicators, measures and metrics. SpringerPlus, 5 (1). doi: 10.1186/s40064-016-3498-1
- Batocchio, A., Ghezzi, A., Rangone, A. (2016). A method for evaluating business models implementation process. Business Process Management Journal, 22 (4), 712–735. doi: 10.1108/bpmj-08-2015-0117
- Pádua, S. I. D., Jabbour, C. J. C. (2015). Promotion and evolution of sustainability performance measurement systems from a perspective of business process management. Business Process Management Journal, 21 (2), 403–418. doi: 10.1108/bpmj-10-2013-0139
- Camara, M. S., Ducq, Y., Dupas, R. (2013). A methodology for the evaluation of interoperability improvements in inter-enterprises collaboration based on causal performance measurement models. International Journal of Computer Integrated Manufacturing, 27 (2), 103–119. doi: 10.1080/0951192x.2013.800235
- Shumpeter, Y. (2007). Teoriya ekonomicheskogo razvitiya. Kapitalizm, sotsializm i demokratiya. Moscow: Eksmo, 864.
- Mainzer, K. (2011). Interdisciplinarity and innovation dynamics. On convergence of research, technology, economy, and society. Poiesis & Praxis, 7 (4), 275–289. doi: 10.1007/s10202-011-0088-8
- Kouz, R. (2007). Firma, rynok i pravo. Moscow: Novoe izd-vo, 224.
- del-Río-Ortega, A., Resinas Arias de Reyna, M., Durán Toro, A., Ruiz-Cortés, A. (2012). Defining process performance indicators by using templates and patterns. Business process management, 7481, 223–228. doi: 10.1007/978-3-642-32885-5_18
- Kravchenko, V. M. (2012). Hibrydnyi metod pidtrymky ta pryiniattia upravlinskykh rishen na osnovi obrobky ekspertnykh sudzhen i nechitkoi lohiky. Formuvannia rynkovoi ekonomiky v Ukraini, 27, 165–168.
- Vasylkovskyi, D. M. (2013). Metodolohiya modeliuvannia protsesu ukhvalennia upravlinskykh rishen pry rozrobtsi i realizatsiyi stratehichnykh napriamiv pidvyshchennia ekonomichnoho potentsialu pidpryiemstva. Ekonomichnyi analiz, 12, 71–75.
- Vasylkovskyi, D. M. (2015). Rozrobka stratehiyi rozvytku ekonomichnoho potentsialu pidpryiemstva na osnovi metodu nechitkoho modeliuvannia. Visnyk Khmelnytskoho natsionalnoho universytetu. Ekonomichni nauky, 2 (4), 36–42.
- Tsiutsiura, S. V., Kryvoruchko, O. V., Tsiutsiura, M. I. (2012). Teoretychni osnovy ta sutnist upravlinskykh rishen. Modeli pryiniattia upravlinskykh rishen. Upravlinnia rozvytkom skladnykh system, 9, 50–58.
- Lipych, L. H. (2010). Biznes-protsesy ta yikh informatsiyne zabezpechennia. Aktualni problemy ekonomiky, 10, 202–206.
- Sobolevskyi, R., Vaschuk, A., Tolkach, O., Korobiichuk, V., Levytskyi, V. (2017). A procedure for modeling the deposits of kaolin raw materials based on the comprehensive analysis of quality indicators. Eastern-European Journal of Enterprise Technologies, 3 (3 (87)), 54–66. doi: 10.15587/1729-4061.2017.103289
- Wetzstein, B., Leitner, P., Rosenberg, F., Dustdar, S., Leymann, F. (2011). Identifying influential factors of business process performance using dependency analysis. Enterprise Information Systems, 5 (1), 79–98. doi: 10.1080/17517575.2010.493956
- Koetter, F., Kochanowski, M. (2014). A model-driven approach for event-based business process monitoring. Information Systems and e-Business Management, 13 (1), 5–36. doi: 10.1007/s10257-014-0233-8
- Novakivskyi, I. I., Prokopyshyn-Rashkevych, L. M. (2011). Ekonomiko-matematychni modeli optymalnoho rozvytku struktury upravlinskoho potentsialu pidpryiemstva. Investytsiyi: praktyka ta dosvid, 6, 33–37.
- Zadeh, L. A. (2006). Generalized theory of uncertainty (GTU) – principal concepts and ideas. Computational Statistics & Data Analysis, 51 (1), 15–46. doi: 10.1016/j.csda.2006.04.029
- Jantzen, J. (2007). Foundations of Fuzzy Control. John Wiley & Sons, Ltd, 209. doi: 10.1002/9780470061176
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Copyright (c) 2018 Serhii Hushko, Oleksandr Temchenko, Iryna Kryshtopa, Hanna Temchenko, Iryna Maksymova, Oleksandr Huk
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