Innovative manufacturing planning based on integrated methodology of rational alternative selection
Abstract
Introduction. Innovation is one of the major factors of economic growth in modern economy on the macrolevel, and a prominent contributor to an enterprise's profit increase at microlevel. Nevertheless, innovation activity is accompanied by a high level of risk and may cause significant losses. Thus, the problem of limiting the risk by developing rational methods of decision making is relevant.
Aim and tasks. The article aims at development of integrated methodology for taking a decision as to selection of rational innovative production alternative based on the usage of a group of decision making methods in dependency on conditions under which the decision is being taken.
Results. The article analyses decision making process in the context of system approach and defines stages of decision making. Criteria of effective decision are described and classified. Methods of decision making are observed and classified according to the conditions of decision making. The necessary components of integrated methodology of selection of rational innovative production alternative are defined. The formation principles and general structure of the integrated methodology of selection of rational innovative production alternative are described.
Conclusions. The task of decision effectiveness assessment is complicated by simultaneous existence of number of performance goals with different suitability for formal evaluation, negative correlation between speed and accuracy of decision making, and temporal distance between decision making process and goal achievement, which requires employment of discounting methods. The above-mentioned factors determine the necessity for an integrated criterion, which includes economic efficiency indicators but is not reduced to them. Thus, integrated methodology of selection of rational innovative production alternative consists of multicriteria decision making solution, assessment of sufficient range of alternatives, allowance for uncertainty as to input information about criteria, inclusion of different types of criteria measurement, provision of possibility to use alternative information at all stages of decision making process.
Keywords:
innovative production, management decision making, manufacture organization, mathematical methods in management.References
2. Hrubyak, S. V. (2017). Modern aspects of development and making managerial decisions. Ekonomіka ta suspіl'stvo, 11, 201-204.
3. Gusarіna, N. V. (2017). Featurs of the system of support for adoption of decisions on management of innovative production sphere in the conditions of dynamic change of the external environment. Hlobalni ta natsionalni problemy ekonomiky, 20, 1052-1055.
4. Kabachenko, D. V. (2017). Management decision taking under uncertainty and risk. Ekonomіchnij vіsnik Nacіonal'nogo gіrnichogo unіversitetu, 2, 107-115.
5. Makarenko, M. V., Sapelnіkova N. L. and Onіshhenko V. V. (2017). Specifics of justification of a management decision based on the efficiency criterion. Bulletin of Donetsk State University of Management, 4, 86-95.
6. Yu, G. F., Fei, W., & Li, D. F. (2018). A compromise-typed variable weight decision method for hybrid multiattribute decision making. IEEE Transactions on Fuzzy Systems, 27,(5), 861-872.
7. Levykіn, V.M., & Chala O.V. (2018). Support decision-making in information control systems using the temporal knowledge base. Advanced Information Systems, 2(4), 101-107.
8. Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66- 83.
9. Shrestha, Y. R., Krishna, V., & von Krogh, G. (2021). Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges. Journal of Business Research, 123, 588-603.
10. Feng, F., Fujita, H., Ali, M. I., Yager, R. R., & Liu, X. (2018). Another view on generalized intuitionistic fuzzy soft sets and related multiattribute decision making methods. IEEE Transactions on Fuzzy Systems, 27(3), 474-488.
11. Dankeieva, O., Solomianiuk, N., Strashynska, L., Fiedotova, N., Soloviova, Y., & Koval, V. (2021). Application of Cognitive Modelling for Operation Improvement of Retail Chain Management System. TEM Journal, 10(1), 358-367.
12. Xu, H., & Deng, Y. (2019). Dependent evidence combination based on decision‐making trial and evaluation laboratory method. International Journal of Intelligent Systems, 34(7), 1555-1571.
13. Yankovyi, O., Koval, V., Trokhymets, O., Karpenko, M., & Matskevich, Y. (2020). Economic assessment of investment on the basis of production functions. Revista TURISMO: Estudos e Práticas, 2.
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