2010-2020年斯洛文尼亚劳动力网络的社区分析

IF 2.8 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Viktor Andonovikj, P. Boškoski, Bojan Evkoski, Tjaša Redek, B. Mileva Boshkoska
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引用次数: 1

摘要

摘要:关于如何在劳动力市场中划分子网络,几乎没有证据表明正确的方法。本文的研究主题是2010年至2020年斯洛文尼亚劳动力网络中不同专业职业之间劳动力转移的计算影响识别。我们使用社区检测算法来识别职业群体,并对2010-2020年斯洛文尼亚劳动力网络进行影响分析。这直接支持决策者和就业服务部门为求职者确定工作机会。主要的分配是利用影响力分析来发现对斯洛文尼亚劳动力市场影响最大的职业和社区。据我们所知,这项研究是第一项在斯洛文尼亚劳动力网络中成功应用社区和影响力分析的工作。该论文具有几个重要意义,主要强调了利用现有数据来提高就业水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Community analysis in Slovenian labour network 2010-2020
ABSTRACT There is little evidence on the right approach on how to delineate the sub-networks in a labour market. The subject of research in this paper is computational influence identification of the labour force transitions between different professional occupations in the Slovenian labour network from 2010 to 2020. We use community detection algorithm to identify occupation groups and apply influence analysis on the Slovenian labour network from 2010 to 2020. This directly supports the decision-makers and employment services in identifying job opportunities for job-seekers based. The main conribution is using influence analysis to detect occupations and communities that had the most significant impact on the Slovenian labour market. The research is the first work to successfully apply community and influence analysis in the Slovenian labour network to the best of our knowledge. The paper carries several important implications, primarily highlighting the usage of existing data to increase employment levels.
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来源期刊
Journal of Decision Systems
Journal of Decision Systems OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
6.30
自引率
23.50%
发文量
55
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