Quantitative methods for executive public managers

Author:

Kamolov Sergey,Tarazevich Mariia

Abstract

Digitalization is becoming a priority in the development of the public governance system, and the question arises about the effectiveness and efficiency of management with the introduction of quantitative methods. This article presents a meta-analysis of relevant studies of quantitative methods that are used in the global practice of public administration. The purpose of the study: to determine a set of quantitative methods that will be necessary and sufficient in the decision-making arsenal of a public executive. A selection of two dozen articles was obtained during systematized research and grouped according to the criteria of compliance with a certain quantitative method and compared with the general potential of quantitative methods in relation to public administration. As a result, a classification of quantitative methods is proposed divided into three global classes of mathematical tools, namely, empirical, logical, and special methods. Methods from the classification are correlated with their potential areas of application in public administration. The authors concluded that it is necessary to increase the research, differentiate effective quantitative methods and introduce the necessary special training of managers for the rational application of quantitative methods in the public sphere.

Publisher

EDP Sciences

Subject

General Medicine

Reference24 articles.

1. Ministry of Digital Development, Communications and Mass Media of the Russian Federation (2022). Digital Public Administration. Retrieved from https://digital.gov.ru/ru/activity/directions/882/?utm_referrer=https%3a%2f%2fwww.google.com%2f (in Russ.)

2. Contracting in Brazilian public administration: A machine learning approach

3. Application of Regression-Based Machine Learning Algorithms in Sewer Condition Assessment for Ålesund City, Norway

4. Simulation and Managerial Decision Making:A Double-Loop Learning Framework

5. Tao L., Liang H., Wen B., & Huang T. Between Nature and Nurture: The Genetic Overlap between Psychological Attributes and Selection into Public Service Employment. Public Administration Review.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3