{"title":"绘制机构投资者行为研究的知识结构图：文献计量分析","authors":"Barkha Dhingra, Mahender Yadav","doi":"10.1108/jm2-12-2023-0288","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>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.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>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.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>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.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>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.</p><!--/ Abstract__block -->","PeriodicalId":16349,"journal":{"name":"Journal of Modelling in Management","volume":"64 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mapping the intellectual structure of research on institutional investors’ behavior: a bibliometric analysis\",\"authors\":\"Barkha Dhingra, Mahender Yadav\",\"doi\":\"10.1108/jm2-12-2023-0288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>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.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>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.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>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.</p><!--/ Abstract__block -->\\n<h3>Originality/value</h3>\\n<p>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.</p><!--/ Abstract__block -->\",\"PeriodicalId\":16349,\"journal\":{\"name\":\"Journal of Modelling in Management\",\"volume\":\"64 1\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Modelling in Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/jm2-12-2023-0288\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Modelling in Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jm2-12-2023-0288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
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.
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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