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| Quantitative Evaluation of Science and Technology Service Industry Policies Based on PMC Index Model:A Comparison of Liaoning and Related Provinces and Cities |
| Du Baogui,Chen Lei |
| （School of Humanities and Law of Northeastern University,Shenyang 110169,China） |
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Abstract The policy of science and technology service industry is one of the important factors affecting the development of science and technology service industry.The development effect of science and technology service industry is closely related to the formulation of its policies and measures.Therefore, it is beneficial to understand the rationality of existing policies and measures of science and technology service industry by evaluating the policies of science and technology service industry, which provides reference significance for optimizing and improving future policies of science and technology service industry.From the existing research literature, it can be seen that the research literature of science and technology service industry policy at home and abroad mostly focuses on policy formulation, policy implementation, policy environment and other aspects, and there is a lack of the related research of policy evaluation, which is the weak link of policy analysis of science and technology service industry at present.
PMC index model is an "exotic product" of foreign policy evaluation methods.Domestic scholars have evaluated some policies in China by using the revised and adjusted policy model, and achieved good results, expanding the applicable scope of the index model in China's policies, and providing method reference and empirical experience for the study on the policy evaluation of science and technology service industry.This study takes PMC index model as the core research method to quantitatively evaluate and analyze the relevant policy texts of science and technology service industry.Firstly, based on the existing index system of PMC index model, text mining method was employed to describe and summarize the contents of 68 policy texts of science and technology service industry in China from 2012 to 2020, the evaluation index system of PMC index model was adjusted and supplemented, so as to build an evaluation index system applicable to science and technology service industry policy and improve the effectiveness of policy evaluation of science and technology service industry.Secondly, in the process of using PMC index model to evaluate the policies of science and technology service industry, it was necessary to assign digital values to the corresponding policy contents and realize the quantitative processing of policy contents, so as to facilitate the calculation and comparison of PMC index of various policy texts.
In order to make full use of the advantages of PMC index model, this study evaluates two policies of science and technology service industry in Liaoning Province, and also adopts comparative analysis method.In addition, 10 representative policies of science and technology service industry from different regions and levels are selected as the control samples of science and technology service industry policies in Liaoning Province.By comparing PMC index scores of different policies, it is easier to find the defects and deficiencies of policies, and at the same time it can provide reference for further optimization of policies.
Generally speaking, first of all, among the 12 policy samples of science and technology service industry in this study, 5 policies were rated as good, and the remaining 7 policies acceptable, which shows that the overall quality of China's science and technology service industry policies needs to be improved.Secondly, from the PMC index ranking of policy samples, P12>P3>P9>P7>P11>P6>P4>P8>P2>P5>P10>P1, it can be seen that the quality of China's science and technology service industry policy shows a trend of "lower is better than upper", that is, the lower the government level, the higher the quality of science and technology service industry policy issued by the corresponding level of government.Furthermore, according to the average scores of the first-level variables of various policies, the six first-level variables cover areas, policy tools, policy audiences, policy implementation basis, industrial process and document citation have higher average scores and relatively excellent variable performance, while the four first-level variables policy nature, policy timeliness, policy operability and publishing institutions have lower average scores and relatively poor variable performance.
According to the PMC surface diagram of each policy and PMC model multi-input-output table, combined with the specific content of each policy, we can carry out horizontal or vertical comparative analysis between policy samples from different variable levels, discuss and find out the advantages and disadvantages of each policy, and then put forward countermeasures and suggestions for policy optimization, which is also the core part of this study.The results show that there are some problems in Liaoning's science and technology service industry policy, such as unclear cognition of policy objects, incomplete use of policy tools, imperfect construction of policy mechanism, etc.Therefore, it is necessary to enhance decision makers' understanding of the current situation and laws of industrial development, complete the shortcomings of policy tools and improve the policy mechanism.
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Received: 27 August 2020
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