The Study On Management Mechanism Of Collaborative Innovation Alliance For Complex Major Science&Technology Project

With the rapid development of national strength, Chinese government currentlyhas launched a series of complex major scientific&technological (S&T) projectssuch as manned spaceflight project, lunar exploration project and so on. It is able toenhance productivity through the development of the S&T, which, in turn, supportseconomic growth, and the progress of society. Complex major (S&T) project is amultidisciplinary giant system, which requires the integration of technical resources.More importantly, it is indispensable that the collaboration between all kinds ofparticipants. The traditional development mode, planned economy mode, has madesome remarkable achievements, but it can no longer survive in the modern worldbecause high cost, lack of communication, low innovation efficiency are not beingchanged. So it seems that constructing a collaborative innovation alliance by differenttypes of organizations is becoming a reasonable and appropriate way to allocateinnovative resources for the activities of innovation. However, the concept ofcollaborative innovation alliance is still a new thing for Chinese society.Well-documented examples of successful cases and experiences are rare, and there isa lack of related theories also. What is more, there are also not many systematicachievements discussing alliances for the complex major S&T project. In this sense,this thesis provides a new challenge to scholars regarding the design and formation ofthe collaborative mechanism for the goal of complex major S&T project, while alsoenriching the research in this area.The goal of this paper is to talk about how to design the management mechanismof alliance to improve the level of cooperation within different participants, andeventually achieve the mission of project. After the literature review, this studypresents the research framework in terms of the four stages of the organizational lifecycle, which is “forming the alliance system——allocating the innovationresources——controlling the innovative process——sharing the cooperative fruits”.Both qualitative and quantitative methods are applied in this paper, taking intoconsideration both theoretical and experimental perspectives. The main contents aredisplayed as follows: Firstly, this study proposes that the process of forming alliance includes threestages, which are organizing the alliance, selecting member and constructingrelationship network. A dynamic “N+X” organization mode is proposed due to thecharacteristics of the task of collaborative innovation alliance. This mode emphasizesthe key role of leadership in the alliance, which can know the overall situation of thealliance. Furthermore, the goal of partner selection is to evaluate the capability ofthose candidates with loose relationship, which supposes the different motivations ofconstructing alliance as influential factors in the weight setting due to the intensitiesof motivations affecting the weighting process. The intuitionistic triangular fuzzynumbers with TOPSIS are applied to evaluate the capability of each candidate. A casestudy is also given to demonstrate the validity and feasibility of the proposedapproach, which provides the methodology for how to select the appropriate partnerfor collaborative innovation.Secondly, evolutionary game theory and integration theory are used to analyzethe cooperative game behavior of partners during the process of resources integration,and the cooperative game model with supervision mechanism is given to avoid thepotential opportunistic behaviors in order to effectively allocate innovative resourceswithin alliance. In addition, cloud computing is applied to design the resourceintegration platform for the collaborative innovation alliance. This is an effective andefficient manner to allocate hardware and software resources within alliance, whilealso being conducive to the resource allocation and comprehensive integration. Itoffers the technical support for the activities of collaborative innovation.Thirdly, the overall situation of alliance is considered as the target ofperformance measure in chapter5. The study improves the classical Balanced ScoreCard through adding the dimension of social effect, as the complex major S&Tproject has a tremendous influence on society. Based on this, a combined methodconstituted of Rough Sets and BP artificial neural network is provided. Rough Sets isapplied to reduce the evaluation criteria in order to effectively measure theperformance of alliance, and particle swarm optimization is used to replace thetraditional method in BP neural network algorithm, the defect of which can be erasedthrough this work. The result demonstrates that this combined method can effectively reduce data processing, focus data range, and optimize the evaluationprocess. This study is to explore the method of performance evaluation ofcollaborative innovation alliance, which is necessary supplement for the method ofcurrent research as well.Fourthly, this paper builds an improved Shapley model to identify eachparticipant’s returns, which divides total economic returns into basic returns andbonus two parts. The commitment of stock capital and risk-taking are considered astwo modified index for distribution of basic returns, and bonus is distributed by theindex of the final contribution of collaborative innovation. This method ensures thatevery participant would like to engage in the activities of collaborative innovation inorder to acquire corresponding benefits. The study in this part not only solves theproblem of how to share the benefits during the collaboration of innovation, but alsoprovides a vision for how to deal with the issue of benefits distribution after collaborativeinnovation.Finally, a collaborative innovation alliance for “The manned space flight project”is chosen as a case study, which is used to demonstrate the conclusions of this paper.