Sage Journals: Discover world-class research

Abstract

While high-tech enterprises have achieved high returns through technological innovation, they also face high risks. This study builds a technology innovation risk evaluation system for high-tech enterprises from eight dimensions: technology risk, capital risk, patent risk, talent risk, management risk, policy risk, industrial risk, and market risk. Based on the subjective and fuzzy characteristics of the evaluation indicators, a risk evaluation model for technological innovation based on fuzzy evaluation was established, and an empirical study was conducted with a technological innovation project of a petrochemical company in Shanghai. The research results show that the high-tech enterprises’ technology innovation risk evaluation model constructed in this study has high accuracy for the quantification of technological innovation risk, and the technology innovation risk evaluation model is highly practical, which provides a reasonable basis for risk management decisions in the process of a high-tech company technology innovation.

Keywords

Fuzzy evaluation technology innovation risk evaluation high-tech enterprises

Get full access to this article

View all access options for this article.

References

Bergek

, Hekkert

, Jacobsson

, Markard

, Sanden

and Truffer

, Technological innovation systems in contexts: Conceptualizing contextual structures and interaction dynamics, Environmental Innovation and Societal Transitions16 (2015), 51–64.

Kim

, Kim

and Park

, Factors affecting product innovation performance according to dynamics of environment: evidence from Korean high–tech enterprises in manufacturing sector, International Journal of Technology Management67(2) (2015), 269–288.

Claudio

, Malerba

, Mancusi

M.L.

, Perani

and Vezzulli

, Innovation, profitability and growth in medium and high-tech manufacturing industries: Evidence from Italy, Applied Economics44(15) (2012), 1963–1976.

J.S.

, Lu

J.T.

and Guo

, Relationship between technological diversification of social network and technological innovation performance: Empirical evidence from China, Science, Technology and Society20(1) (2015), 60–88.

Cheng

, Sun

, Su

and Yang

, Venture capital, innovation, and growth: Evidence from Chinese metropolitan data, Applied Economics Letters26 (2019), 1–5.

Dangelico

R.M.

, Pujari

and Pontrandolfo

, Green product innovation in manufacturing firms: A sustainability-oriented dynamic capability perspective, Business Strategy and the Environment26(4) (2017), 490–506.

Jaroslav

, Eva

, Zoltan

and Jaroslav

, Innovations in sme segment: important factors and differences in the approach by size and age of the company, Transformations in Business & Economics17(3) (2018), 55–71.

Lee

and D.A. F.M., Veloso, Hounshell, Linking induced technological change, and environmental regulation: Evidence from patenting in the US auto industry, Research Policy40(9) (2011), 1240–1252.

, Huang

and Ye

, Risk identification, evaluation and response of low-carbon technological innovation under the global value chain: A case of the Chinesemanufacturing industry, Technological Forecasting and Social Change100 (2015), 238–248.

10.

Berglund

, Risk conception and risk management in corporate innovation: Lessons from two Swedish cases, Interntional Journal of Innovation Management11(04) (2007), 497–513.

11.

Luo

J.L.

and Hu

Z.H.

, Risk paradigm and risk evaluation of farmers cooperatives’ technology innovation, Economic Modelling44 (2015), 80–85.

12.

D.D.

, Kefan

and Hua

, Modeling technological innovation risks of an entrepreneurial team using system dynamics: An agent-based perspective, Technological Forecasting and Social Change77(6) (2010), 857–869.

13.

Polk

, Plank

R.E.

and Reid

D.A.

, Technical risk and new product success: An empirical test in high technology business markets, Industrial Marketing Management25(6) (1996), 531–543.

14.

Choi

H.G.

and Ahn

, Risk analysis models and risk degree determination in new product development: A case study, Journal of Engineering and Technology Management27(1-2) (2010), 110–124.

15.

Nieto-Morote

and Ruz-Vila

, A fuzzy approach to construction project risk assessment, International Journal of Project Management29(2) (2011), 220–231.

16.

Reza

, Ahmad

, Shahriyari

N. A.

, Jonas

and Keshavarz

G. M.

, A fuzzy aras method for supply chain management performance measurement in smes under uncertainty, Transformations in Business & Economics16(2A) (2017), 319–348.

17.

García

V.G.

, Gil-Lafuente

A.M.

and Calderon

, A fuzzy logic approach towards innovation measurement, Global Journal of Business Research9(3) (2015), 53–71.

18.

Janekova

, Fabianova

and Fabian

, Assessment of economic efficiency and risk of the project using simulation, International Journal of Simulation Modelling18(2) (2019), 242–253.

19.

Hellstrom

, Systemic innovation and risk: Technology assessment and the challenge of responsible innovation, Technology in Society25(3) (2003), 369–384.

20.

Kumar

and Yadav

, A fuzzy logic system to detect and classify faults for laboratory prototype model of TCSC compensated transmission line, Journal of Power Technologies99(1) (2019), 49–57.

21.

Tomasz

, Jakubowska

and Andrzejczyk

, The impact of environmentally friendly refrigerants on heat pump efficiency, Journal of Power Technologies99(1) (2019), 40–48.

Research on technology innovation risk evaluation of high-tech enterprises based on fuzzy evaluation

Abstract

Keywords

Get full access to this article

References