| China is speeding up the building of a digital China,with data becoming a new factor of production and accelerating global production,circulation,distribution and consumption activities.With the surge in data volume in all walks of life,enterprises start digital transformation one after another,and management activities such as data collection,storage,processing and sharing are faced with challenges.How to improve the organization’s data management ability and consolidate the foundation of data management has become an important task.For research institutes,experimental data is a basic and strategic resource,which has its own needs of quality assurance,security and confidentiality,property rights protection,sharing and interconnection.However,there are some problems in the digital transformation of research institutes,such as link breakdown,low digitization degree of system,and insufficient integration application.Therefore,it is in urgent need of a set of scientific and effective methods to guide institutions to carry out experimental data management.Based on the process perspective,the maturity model evaluates the status quo of management capabilities such as integration sharing,value application,security and confidentiality of test data,provides suggestions and roadmap for continuous improvement,and promotes organizations to establish systematic test capabilities.Thesis reviewed and summarized the existing data management capability maturity literature at home and abroad,combined with the requirements and characteristics of test data,selected the DCMM as the basis,embedded 77 three-level indicators,to construct the test data management capability maturity evaluation index of scientific research institutions.In the evaluation model,the best and worst method and variable weight theory are used to determine the optimal weight,and the maturity level of the organization and each index is judged by the combination of prospect theory and three decisions.Specifically,the best and worst method is used to calculate the constant weight of the evaluation index of the experimental data management of scientific research institutes.In order to help institutions establish the advantage index and improve the disadvantage index,the variable weight interval of rewards and punishments is divided,and the mixed state variable weight function is used to obtain the optimal weight to realize the development of strengths and avoid weaknesses.In the evaluation model of three-branch decision making based on prospect theory,the difference of reference points and decision-maker types will affect value perception.This thesis considers mean and positive and negative ideal points as reference points,conservative,neutral and risk-taking decision-makers,calculates the comprehensive prospect value of organizations and indicators,and analyzes the pros and cons of each indicator.The traditional maturity level is defined subjectively,in this thesis,the threshold between the second,third and fourth levels of maturity is calculated by using the three-way decision,and the grade of the evaluation object is judged based on the conditional probability.At the same time,the maturity level of the organization can be judged according to the decision rules of the maximum prospect value.On the basis of judging a certain level,the relative loss function matrix is used to realize the depth classification of maturity level of units.Finally,the test data management capability maturity of K institute was evaluated to verify the feasibility and scientificity of maturity model.After comparative analysis of the prospect value before and after the weight change,the change of reference point,it is concluded that the maturity level of K unit and its primary index is generally level 2.After depth grading,it is further divided into 2~+\2\2~-level combined with conditional probability,and corresponding improvement suggestions are put forward. |
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