新就业群体友好场景满意度评价研究——以杭州市为例

A Study on the Satisfaction Evaluation of Friendly Scenarios for New Employment Groups—Taking Hangzhou as an Example

摘要: 本文以杭州市新就业群体为研究对象，基于562份有效问卷，围绕新就业群体友好场景的满意度评价展开实证分析。首先，运用描述性统计方法对友好场景满意度现状进行初步分析；其次，采用验证性因子分析建立满意度评价结构，将14个影响因子划分为服务设施、现有工作支撑、未来职业支持和社会尊重四个维度；在此基础上，进一步运用层次分析法确定各级指标权重，并计算综合满意度得分。研究结果表明，杭州市新就业群体对友好场景整体处于较满意水平。其中，社会尊重维度评价较高，服务设施与现有工作支撑仍有提升空间；选址合理性和线上功能实用性是当前友好场景建设中的相对薄弱环节。基于此，本文提出优化场景空间布局、完善线上线下服务衔接、提升服务功能适配性等建议，为新就业群体友好场景建设和城市基层治理优化提供参考。

Abstract: Taking new employment groups in Hangzhou as the research object, this paper conducts an empirical study on the satisfaction evaluation of friendly service scenarios for new employment groups based on 562 valid questionnaires. Firstly, descriptive statistical analysis is used to preliminarily examine the satisfaction status of friendly service scenarios. Secondly, confirmatory factor analysis is employed to construct a satisfaction evaluation system, and 14 influencing factors are classified into four dimensions: service facilities, current work support, future career support, and social respect. On this basis, the analytic hierarchy process is further applied to determine the weights of indicators at different levels and calculate the comprehensive satisfaction score. The results show that new employment groups in Hangzhou are generally satisfied with friendly service scenarios. Among them, the dimension of social respect is evaluated relatively highly, while service facilities and current work support still require further improvement. In particular, the rationality of location selection and the practicality of online functions are relatively insufficient in the current construction of friendly service scenarios. Accordingly, this paper proposes suggestions such as optimizing the spatial layout of friendly service scenarios, improving the connection between online and offline services, and enhancing the adaptability of service functions, so as to provide a reference for the construction of friendly service scenarios for new employment groups and the optimization of urban grassroots governance.