Influence Factor And Risk Prevention And Control Of Knowledge Fusion In Growing Alliances

In the case of limited resources and insufficient innovative technology and ability,joining an industrial technology innovation alliance is the best way for enterprises to realize innovation and obtain benefits from it.In the growth period,the cooperative innovation of alliance enterprises has gradually started,and its smooth development has laid the foundation for the sustainable development and success of the alliance.The process of knowledge fusion can collect the knowledge scattered in the alliance,convert it into a unified expression,and then combine it with the internal knowledge of the enterprise to create new knowledge.It can be seen that knowledge fusion is an important way of alliance innovation.The knowledge integration of growing industrial technological innovation alliance plays an extremely important role in the healthy development of the alliance,the improvement of technological innovation ability and core competitiveness of alliance enterprises.Therefore,it is great significance to study the influencing factors and risk prevention and control of knowledge integration of growing industrial technological innovation alliance.This paper attempts to reveal which factors have an important impact on the knowledge integration of growing industrial technological innovation alliance,and which risks will lead to the failure of knowledge integration.Therefore,this paper focuses on the following issues: what are the influencing factors of knowledge fusion of industrial technological innovation alliance in the growth period? What are the effects of various factors on the knowledge fusion of industrial technological innovation alliance in the growth period? What are the effects of various influencing factors on the decision-making behavior of knowledge fusion of growing industrial technology innovation alliance enterprises? What risks will the knowledge fusion of industrial technological innovation alliance encounter in the growth period? What are the measures to overcome risks?Therefore,taking a growing alliance as the starting point,this paper systematically studies the impact factor of knowledge fusion and risk prevention and control by comprehensively using support vector machine(SVM),grounded theory,empirical research,game analysis and a particle swarm optimization(PSO)-improved back-propagation(BP)neural network,combined with life cycle theory,social network theory,resource bricolage theory and organizational learning theory.This paper reveals the effect of the various influencing factors on knowledge fusion,discusses the impact of various factors on enterprises' participation in the decision-making behavior of knowledge fusion in growing alliances,and puts forward the risks and countermeasures associated with knowledge fusion in growing alliances.This paper mainly carries out the following work.(1)Based on the grounded theory method,this paper reveals the influencing factors of knowledge fusion of industrial technological innovation alliance in the growth period.First,the growing alliances and their enterprises are selected.The stage division model of the alliance life cycle based on an SVM is constructed.Through comparative analysis with the BP neural network,the accuracy of the SVM model is verified.Based on the SVM and alliance development stage measurement scale,the alliance life cycle is divided,and the growing alliance and its enterprises are selected.A total of 296 growing alliance enterprises are selected.Second,based on grounded theory,the influencing factors of knowledge fusion in growing alliances are mined.The basic materials are obtained through interviews are sorted and coded.Finally,50 initial concepts,30 initial categories,9 main categories and 5core categories are extracted,including alliance networks,resource bricolage,organizational learning,legitimacy and procedural fairness within the alliance.(2)Based on the research on the influencing factors and their relationship,this paper constructs the action relationship model of these influencing factors on the knowledge fusion of growing industrial technological innovation alliance,empirically tests the correctness of the model and the role of different dimensions of various factors in the model,fills the gap in the research on the influence factors of knowledge fusion,and enriches the relevant research literature.At present,the research on knowledge fusion has mainly focused on the knowledge fusion algorithm and its application in the field of big data,while the research on the influencing factors of knowledge fusion in an alliance environment is scarce.This paper introduces factors such as alliance networks,resource bricolage,organizational learning,procedural fairness and the internal legitimacy of alliances.First,these factors are defined and divided into dimensions,and then,the influence mechanism model of knowledge fusion in the growing alliance is constructed.Then,the data are collected by questionnaire,and the model is analyzed and verified by SPSS 22.0.The results show that reveals the characteristics of industrial technological innovation alliance network in the growth period;Resource allocation network has the greatest impact on knowledge fusion;Technological innovation network,resource allocation network and social relationship network have a positive impact on knowledge bricolage,relationship bricolage,exploratory learning and utilization learning.Among them,social relationship network has the greatest impact on knowledge bricolage,and resource allocation network has the greatest impact on relationship bricolage,exploratory learning and utilization learning;Knowledge bricolage,relationship bricolage,exploratory learning and utilization learning play an intermediary role in the impact of technological innovation network,resource allocation network and social relationship network on knowledge fusion.Among them,relationship bricolage plays a complete intermediary role in the relationship between social relationship network and knowledge fusion,and knowledge bricolage,exploratory learning and utilization learning play a complete intermediary role in the relationship between resource allocation network and knowledge fusion;Knowledge bricolage,relationship bricolage,exploratory learning and utilization learning have a positive impact on knowledge fusion.Among them,the influence of relationship bricolage on knowledge fusion is better than knowledge bricolage,and the effect of utilization learning on knowledge fusion is greater than exploratory learning;and procedural fairness and intra-alliance legitimacy positively regulate the impact of resource allocation networks,technological innovation networks and social relationship networks on organizational learning(exploratory learning and exploitative learning)and resource bricolage(knowledge bricolage and relationship bricolage).(3)Using static game and dynamic game analysis methods,this paper analyzes the impact of alliance network,organizational learning,resource bricolage,procedural fairness and internal legitimacy of the alliance on the decision-making behavior of knowledge fusion.The game model fully considers the influence of alliance networks(resource allocation network,technological innovation network and social relationship network),organizational learning(exploratory learning and exploitative learning),resource bricolage(knowledge bricolage and relationship bricolage),procedural fairness and legitimacy within the alliance on participation in knowledge fusion decision making and brings these factors into the game model.On the premise of complete rationality,this paper constructs a static game model to analyze the selection strategy of one party's enterprise when the decision of the other party's enterprise is established.Moreover,on the premise of bounded rationality,this paper constructs a dynamic evolutionary game model,analyzes the equilibrium point and evolutionary stability strategy,then simulates the dynamic game model,and analyzes,in detail,the alliance networks(resource allocation network,technological innovation network and social relationship network),organizational learning(exploratory learning and exploitative learning),resource bricolage(knowledge bricolage and relationship bricolage).Furthermore,the influence of procedural fairness and intra-alliance legitimacy on enterprises' participation in knowledge fusion decision making is also considered.(4)Based on the research results of grounded theory,this paper proposes the risk factors for growing alliance knowledge fusion and constructs a risk evaluation index system,which includes the subject risk factors,relationship risk factors and internal environmental risks of the alliance.Among them,subject risks include learning ability risk,resource bricolaging ability risk,knowledge reconstruction ability risk,and limited knowledge search ability.Relationship risk factors include resource exchange relationships risk,technical cooperative R&D relationships risk and interpersonal interaction relationships risk.The internal environmental risks of the alliance include the equity risk and the legitimacy risk within the alliance.Second,a risk evaluation model based on a PSO-improved BP neural network is constructed.By comparing the evaluation results with the BP neural network,the accuracy and feasibility of the risk evaluation model based on the PSO-improved BP neural network are verified.Third,the knowledge fusion risk control system of the growing alliance is established to realize the implementation of the monitoring of knowledge fusion risk.The risk control system includes risk monitoring,risk assessment,risk early warning and risk control.Finally,this work puts forward effective and executable risk prevention and control measures to address the above risk factors.