| The high-tech industry,as the type of industry with the most active technological innovation in current economic activities,plays an important role in promoting the transformation and upgrading of industrial structure,the transformation of industrial development mode and the improvement of international competitiveness of industry.Evaluating the operating results of the industry in a scientific and reasonable manner not only helps properly guide the operating behavior of the industry,but also assists the industry in finding the operating gaps and the intrinsic reasons for them,thus promoting the industry to improve its operating efficiency and economic benefits.With the maturation of networked development of production and operating systems in China’s high-tech industry,the complexity of uncertain information and behavioral preferences in the decisionmaking process has increased.By constructing the data envelopment analysis(DEA)theory and method for the uncertain information and behavior preferences,it is of great theoretical significance and application value to expand and enrich the existing theory and method of the high-tech industrial system.Considering the problem of insufficient theoretical research on efficiency assessment in the production processes of the high-tech industry,this thesis conducts theoretical research under individual fuzzy information and complex behavioral preferences among internal processes.Moreover,the constructed theories and methods are employed to innovation efficiency evaluation.The particular research contents of this thesis are expressed as follows:(1)To address the efficiency assessment of socio-economic systems containing imprecise information preferences,this thesis characterizes highly uncertain information by fuzzy preferences and constructs evaluation theories for uncertain systems based on DEA models.First,the semantic information with individual preference is characterized by using type-2 fuzzy theory.Moreover,the information with individual preferences is quantitatively transformed and combined with the DEA model to construct an efficiency model.Second,according to the membership function and monotonicity feature,the type-2 fuzzy DEA model is decomposed into four DEA sub-models,which can be solved separately.In addition,the ultimate efficiency is performed by using the α-cuts and the risk factor method.Finally,the validity and rationality of the proposed model are verified by numerical analysis.(2)For the existence of general behavioral preferences among socio-economic systems,an efficiency evaluation model considering the decision preference behavior is established based on the prospect theory and DEA model.Firstly,the prospect theory is used to characterize the decision reference dependence and loss aversion behaviors in the assessment process,and prospect crossefficiency DEA model is constructed by combining prospect theory with DEA cross-efficiency model.Secondly,a new distance entropy function is constructed to perform the set of prospect cross-efficiency for the inconsistency degree of the other-assessed and self-assessed prospect efficiencies to obtain the unique optimal efficiency.Finally,the actual application of the proposed method with general behavioral preferences is introduced through numerical analysis,and the validity and rationality of the method are verified by comparative analysis.(3)To solve the efficiency problem with the specific fairness concerns in the socio-economic system,an evaluation model with a balanced development perspective of fairness and efficiency is constructed based on fairness theory and network DEA model.Firstly,the fairness preferences in the operating system are defined by Neumann-Morgenstern utility,and the developmental utilities of each sub-stage and the overall system are constructed when different stages are prominent.Secondly,the deviation variables and Charnes-Cooper method are introduced to transform the constructed network DEA models with behavioral preferences into the corresponding ones.Finally,by applying the constructed model to the actual production system,the development level of the industry is measured from the perspective of fair and efficient balanced development,and the rationality and validity of the proposed model are verified by comparative analysis.(4)For the existence of specific cooperative preferences in the socio-economic system,an efficiency evaluation model is constructed based on the cooperative game and the network DEA model by considering the cooperative behavior in the decision-making system.Firstly,the network DEA model based on shared inputs is constructed by considering existence of sharing and reasonable allocation of some initial input resources in each sub-stage.Secondly,the network DEA model based on cooperative game and shared inputs is constructed by considering the cooperative behavior among the various sub-stages in the system.Finally,the proposed efficiency method with cooperative preferences is introduced through empirical analysis to verify the rationality of the proposed method.(5)To validate the effectiveness of the proposed DEA models based on individual fuzzy preferences or specific behavioral preferences in the system,empirical research of the application the DEA model with fuzzy preferences is carried out by using the high-tech industry as the research background.Firstly,based on the current development situation of China’s high-tech industry,the proposed interval type-2 fuzzy theory is applied to enrich the existing index system.Secondly,the cooperative game or fairness theory is combined with the network DEA model to construct efficiency models based on specific preferences,and the application is analyzed from different levels of the high-tech industrial system.Finally,the results of the analysis with individual preferences and system preferences are presented with corresponding constructive suggestions.In this thesis,the proposed DEA methods,with the fuzzy information preferences and the existence of specific behavioral preferences in the system,are applied and validated in the process of the high-tech industry.Theoretically,the DEA models with fuzzy information and behavioral preferences constructed in this thesis cannot only expand and enrich the existing DEA methods and industry index systems,but also enhance the effectiveness and rationality of the existing fuzzy DEA models and network DEA methods.Practically,the proposed DEA models with fuzzy information and behavioral preferences provide new research methods and research perspectives for the analysis of the development level of the systems in the high-tech industry,thereby providing targeted suggestions on the high quality of the high-tech industry. |
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