Statistical methods & models for the evaluation systems for the public sector
• 大类 : 社会科学 - 3区
• 小类 : 运筹学与管理科学 - 4区
Socio-Economic Planning Scienceswill publish a special issue onStatistical methods & models for the evaluation systems for the public sector. This special issue takes a cue from the current debates and literature, which have shown that public service quality measurement is the basic prerequisite for quality improvements and planning or improving public policies that have a great impact in nowadays societies. This theme is also strongly connected with the measurement of the satisfaction level, which is one of the significant tools for public institutions to fully capture citizensâ€™ needs. The availability of big data also provides a complement to traditional data sources, such as survey data, to create a complete analysis of a service process.
This special issue welcomes submissions that work on new developments and thinking in statistics applied in the evaluation and quality of public services, with emphasis to modelling, theory development, empirical research, reviews and case studies Topics common within the scope of the special issue are numerical taxonomy, classification, multidimensional scaling and other ordination techniques, clustering, tree structures and other network models, as well as advanced statistical models such as Generalized Linear, Latent, and Mixed Models for the analysis of multivariate data of a different nature (e.g., ranking or ordinal categorical data), that play a crucial role together with related inferential methods that may depart from traditional approaches.
The special issue will include papers that offer methodological and policy insights. The authors of methodology-oriented papers must make an explicit attempt to justify the relevance of their work for public sector decision making. Contributions relying on abroad range of quantitative approaches are welcome, however, priority will be given to the submissions making original advances in modelling and/or optimization, as well as innovative applied contributions.