绘制机构投资者行为研究的知识结构图:文献计量分析

IF 1.8 Q3 MANAGEMENT
Barkha Dhingra, Mahender Yadav
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引用次数: 0

摘要

目的本研究旨在分析集中研究机构投资者行为的现有知识体系。本研究使用 Scopus 数据库收录的高度认可的期刊中的 446 篇文章,运用文献计量分析法研究了所选研究领域的趋势。研究结果作者发现,由于学术界对该主题的兴趣,有关机构投资者行为的研究在过去 40 年中显著增加。本研究观察到了这一领域研究的五个统一主题:机构投资者与公司行为;机构投资者交易模式与绩效的决定因素;交易活动及其结果;羊群效应、原因与后果;以及机构投资与公司绩效。此外,作者还阐述了未来的研究方向,如机构投资者的控制权如何影响治理信息披露。作者为进一步的研究奠定了坚实的基础,为知识库做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping the intellectual structure of research on institutional investors’ behavior: a bibliometric analysis

Purpose

This study aims to analyze the existing body of knowledge concentrating on institutional investors’ behavior. It seeks to track how this domain has evolved through collaborative networks, as well as significant contributors, themes and research opportunities for future work.

Design/methodology/approach

The present study applies bibliometric analysis to examine the trends in the selected research field, using 446 articles from highly recognized journals indexed in the Scopus database.

Findings

The authors discovered that research on institutional investors’ behavior has significantly increased over the past four decades due to academic interest in the topic. This study observed five themes that unite the research in this field: institutional investors and corporate behavior; determinants of institutional investors’ trading patterns and performance; trading activity and its outcomes; herding, causes and consequences; and institutional investment and corporate performance. Moreover, future directions are penned down, such as how institutional investors’ control influences governance disclosures.

Originality/value

This study serves as a guide by mapping and analyzing the intellectual development of the research literature on institutional investors’ behavior. The authors contribute to the knowledge base by providing a solid foundation for further studies.

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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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