Quantitative Assessment and Optimization Paths of Data Factor Policies Based on the PMC Index Model
China's data factor market is still in its early stage of development,making scientifically-based policy formulation crucial for its stable growth.This paper employs content analysis to examine 28 national-level data factor policies as of the end of 2023 and utilizes the PMC index model for quantitative evaluation.The results indicate that 5 policies achieved a perfect level,16 were rated excellent,and 3 were acceptable.There remains room for improvement in the diversity,comprehensiveness,balance,and sustainability of these policies.This paper proposes the following recommendations:First,to address the insufficient coverage of certain stakeholders in previ-ous policies,a more inclusive cooperation mechanism should be established to ensure active participation from all parties in developing the data factor market.Second,to enhance the support for technological tools and service scenarios,which were rated lower in previous policies,future policies should further strengthen these areas.Third,given the high scores in risk management and lower scores in value creation,future policies should focus on improving efficiency and value creation while ensuring security and control.Fourth,to address the lower scores in long-term planning within policy timeliness,the sustainability of future policies should be enhanced.
data factorquantitative evaluationPMC index modeldata factor market
NETL
NSTL
万方数据
