Self-organizing maps: a novel approach to identify and map business clusters

IF 3.6 2区管理学 Q2 BUSINESS

Journal of Management Analytics Pub Date : 2024-02-08 DOI:10.1080/23270012.2024.2306628

Francis Bowen, Janaína Siegler

引用次数: 0

Abstract

Business cluster identification is an essential topic for helping understand regional and global supply chains and establishing economic policies and logistics. This work aims to leverage the benef...

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自组织地图：识别和绘制企业集群的新方法

企业集群识别是帮助了解地区和全球供应链以及制定经济政策和物流的重要课题。这项工作旨在利用...

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来源期刊

Journal of Management Analytics SOCIAL SCIENCES, MATHEMATICAL METHODS-

CiteScore

13.30

自引率

3.40%

发文量

期刊介绍： The Journal of Management Analytics (JMA) is dedicated to advancing the theory and application of data analytics in traditional business fields. It focuses on the intersection of data analytics with key disciplines such as accounting, finance, management, marketing, production/operations management, and supply chain management. JMA is particularly interested in research that explores the interface between data analytics and these business areas. The journal welcomes studies employing a range of research methods, including empirical research, big data analytics, data science, operations research, management science, decision science, and simulation modeling.