In the post-pandemic era, the street vendor economy has emerged as a vital means of alleviating employment pressure and stimulating market vitality, necessitating a scientific evaluation and optimization of its public governance policies. This study employs the PMC (Policy Modeling Consistency) Index Model to conduct a quantitative analysis of nine street vendor-related policies issued by national and local governments between 2020 and 2022. By integrating text mining and social network mapping methods, the paper constructs an evaluation system comprising ten primary variables and forty-two secondary variables. Based on the distribution of high-frequency terms, socio-semantic network diagrams, PMC index scores, and PMC surface plots, the study finds that the overall design of the street vendor policies is generally sound (with an average PMC index score of 7.28, and six policies rated as excellent). However, structural shortcomings persist, including short policy durations (78% are short-term), insufficient cross-departmental coordination (78% were issued by a single department), and incomplete coverage of target beneficiaries (some policies fail to focus on core groups). Local policies outperform national ones in areas such as incentive mechanisms and content innovation, reflecting greater governance flexibility. Accordingly, the study recommends policy optimization from three perspectives: top-level design (formulating medium- to long-term plans and optimizing policy tool portfolios), implementation mechanisms (providing categorized support and dynamic monitoring), and collaborative governance (enhancing interdepartmental coordination and promoting social participation), with the aim of promoting the normalization and sustainable development of the street vendor economy.
Research Article
Open Access