Managing Technological and Market Risks in Engineering-Based Business Model Innovation: Integrating digital decision support system

¹ Korkyt Ata Kyzylorda University, the city of Kyzylorda, Aiteke bi 29A 0000-0001-8376-1275, This email address is being protected from spambots. You need JavaScript enabled to view it.
² Abai Kazakh National Pedagogikal Universiti, Dostyk Avenue 13, Almaty 050010, Kazakhstan, 0000-0003-2392-0136, This email address is being protected from spambots. You need JavaScript enabled to view it.
³ Al-Farabi Kazakh National university, 71 Al-Farabi avenue, Almaty 050040, Kazakhstan, 0000-0003-0817-5756
⁴ Department of Investments and Capital Markets at the Banking and Finance Academy of the Republic of Uzbekistan, Uzbekistan, This email address is being protected from spambots. You need JavaScript enabled to view it. , 0000-0003-4813-035X
⁵ Tashkent State University of Economics, Tashkent, Uzbekistan, This email address is being protected from spambots. You need JavaScript enabled to view it. , 0009-0004-9536-0953
⁶ Tashkent State University of Economics, Tashkent, Uzbekistan, This email address is being protected from spambots. You need JavaScript enabled to view it. , 0009-0005-2637-6860

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

The extant literature regarding the effects of technological and market risks on business model innovation shows inconsistent findings, either positive or negative effects have been reported. The objective of this study is the integration of a digital decision support system for the management of technological and market risks in engineering-based business models in order to improve strategic decision quality and innovation outcomes. The objectives of the research are to identify the necessary decision criteria for correcting the assessment errors based on the priorities derived from the decision hierarchy. The two methods are applied to evaluate the relative importance of risk factors of engineering-based business model innovation over the period considered and analyze the structural relationships of the risk constructs in the technological and in the market domains. The method used is analytic hierarchy process, structural equation modeling, and regression analysis of the data taken from the observations of the engineering-based firms included in the empirical sample, collected for a period of five years (2019–2023). The results show that there is a strong relationship in the technological and market risk dimensions in the context of engineering-based business model innovation, and at the same time, digital decision support creates a more significant increase in long run business performance stability. Furthermore, the results suggest the complementarity of the two methodologies in the context of a digital decision support system for the analysis of the risk structure in engineering-based business models.