Abstract

BackgroundIn the increasingly competitive market environment, the high complexity of innovation activities makes enterprises gradually combine with other institutions or groups to form a collaborative innovation network and jointly participate in the completion of innovation activities. Aiming at the vulnerability risk of collaborative innovation network caused by a series of psychological behaviors of each subject under the influence of internal and external environment, a vulnerability risk assessment method of collaborative innovation network based on cloud model is proposed. At the same time, the emotional behavior of multiple subjects is analyzed and studied.Subjects and MethodsFirstly, by systematically combing the existing research results, the influencing factors of collaborative innovation network vulnerability risk are analyzed and identified, and the collaborative innovation network vulnerability risk evaluation index is constructed. Secondly, in order to prevent the weight difference of individual indicators from being too large and reduce the correlation degree between indicators, the anti entropy weight method is used to determine the weight of evaluation indicators. Then, considering the fuzziness and uncertainty of qualitative and quantitative description of evaluation indicators, the comprehensive evaluation method based on cloud model is used to evaluate the vulnerability risk of collaborative innovation network. Finally, taking the vulnerability risk analysis of project product collaborative innovation network of enterprise a as an example, the risk assessment analysis is carried out. The modified Lin Shangping's “innovative network Emotion Scale” and “Minnesota Satisfaction Scale (MSQ)” were used in the study. Using the convenient sampling method, 200 questionnaires were distributed to the empirical objects, and 200 were recovered. The sample structure distribution is that men account for 49.7%, the proportion under the age of 25 (including) is the lowest, accounting for 2.5%, and the proportion over the age of 36 is the highest, accounting for 52.6%. As for the education level, universities (colleges and universities) the proportion is the highest, accounting for 64.0%. In terms of service years, the proportion of 1-3 years is the lowest, accounting for 4.4%, and the proportion of more than 7 years is the highest, accounting for 84.2%. The total correlation coefficient and total reliability of the modified items were analyzed to delete the items without internal consistency in the questionnaire, so as to improve the reliability of the questionnaire and the quality of measurement tools. Regression analysis was used to verify the three hypothesesResultsOur research results show that the collaborative innovation network vulnerability risk of the product is generally at a low level. In order to specifically understand the influencing factors of collaborative innovation network vulnerability risk, the cloud chart analysis of secondary indicators shows that the equity index of benefit distribution and the index of risk prevention mechanism are at medium risk.ConclusionUsing the comprehensive evaluation method of anti entropy weight method and cloud model to analyze the vulnerability risk of collaborative innovation network can help enterprise managers effectively understand the weak links of collaborative innovation network, formulate and implement feasible countermeasures, and provide decision support for the risk management and sustainable operation of collaborative innovation network. Of course, there are still some deficiencies in this study: in the composition of indicators, qualitative indicators are the main indicators; It mainly evaluates and analyzes the indicators, and then considers the correlation between risk indicators and network risk management. Multi-agent collaborative innovation is an important mode to promote enterprise innovation and development and obtain competitive advantage. As an important part of collaborative innovation network, risk management is an important guarantee to avoid risks and carry out collaborative innovation activities smoothly. Therefore, this paper analyzes the vulnerability risk of collaborative innovation network, which helps to enrich the collaborative innovation network and risk management system, improve the efficiency of enterprise product innovation, reduce the risk of collaborative innovation, and maintain the sustainable operation and development of collaborative innovation network.AcknowledgementsThe authors acknowledge the collective support granted by National Natural Science Youth Foundation of China (Grant No 71701027); Chongqing Municipal Education Commission Humanities and Social Sciences Research General Project (Grant No 20SKGH116); Chongqing Natural Science Foundation of the General Project (Grant No cstc2020jcyj-msxmX0562); China Postdoctoral Science Foundation Funded Project (2018M643456); Chongqing Natural Science Foundation Project (Grant No cstc2020jcyj-msxmX0864) and Chongqing Social Science Planning and Cultivation Project (Grant No 2020PY51).

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