{"title":"在系统文献综述中识别研究的挑战:组织增长和衰退主题的分析","authors":"R. Dantas, D. Fleck","doi":"10.1108/gkmc-03-2023-0098","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to check the fragmentation of knowledge across multiple sources of evidence, identifying, scrutinizing and outlining suggestions concerning the challenges researchers face when using multiple sources of data to identify studies.\n\n\nDesign/methodology/approach\nThis study produced a comprehensive database of 15,848 items from Scopus, Web of Science and EBSCO on the organizational growth and decline topics. The analyses carried out to check the fragmentation of scientific knowledge and the challenges in identifying studies have made use of the basic data frame functions in R’s language and the Bibliometrix and Corpus R’s packages.\n\n\nFindings\nThis study confirms the fragmentation of scientific knowledge as well as it identifies the following challenges: missing information in key fields, nonexistence of standards in terminology, limitations on data extraction, duplicates and multiple formats of cited reference. Additionally, it suggests practical coping procedures and advances implications for stakeholders and an agenda for future research.\n\n\nOriginality/value\nThis study provides valuable and practical examples with empirical confirmation of scientific knowledge fragmentation and offers an integrated view of many challenges in the process of identifying studies. Moreover, by offering suggestions to address these challenges, this study not only offers a practical guide to scientific researchers but also initiates a wider discussion regarding knowledge organizing in social sciences.\n","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Challenges in identifying studies to include in a systematic literature review: an analysis of the organizational growth and decline topics\",\"authors\":\"R. Dantas, D. 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The analyses carried out to check the fragmentation of scientific knowledge and the challenges in identifying studies have made use of the basic data frame functions in R’s language and the Bibliometrix and Corpus R’s packages.\\n\\n\\nFindings\\nThis study confirms the fragmentation of scientific knowledge as well as it identifies the following challenges: missing information in key fields, nonexistence of standards in terminology, limitations on data extraction, duplicates and multiple formats of cited reference. Additionally, it suggests practical coping procedures and advances implications for stakeholders and an agenda for future research.\\n\\n\\nOriginality/value\\nThis study provides valuable and practical examples with empirical confirmation of scientific knowledge fragmentation and offers an integrated view of many challenges in the process of identifying studies. Moreover, by offering suggestions to address these challenges, this study not only offers a practical guide to scientific researchers but also initiates a wider discussion regarding knowledge organizing in social sciences.\\n\",\"PeriodicalId\":43718,\"journal\":{\"name\":\"Global Knowledge Memory and Communication\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Knowledge Memory and Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/gkmc-03-2023-0098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Knowledge Memory and Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/gkmc-03-2023-0098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
本文旨在检查跨多个证据来源的知识碎片化,识别、审查并概述有关研究人员在使用多个数据来源识别研究时面临的挑战的建议。设计/方法/方法本研究从Scopus、Web of Science和EBSCO中建立了一个关于组织成长和衰退主题的综合数据库,共15848个条目。为检查科学知识的碎片化和识别研究的挑战而进行的分析使用了R语言中的基本数据框架函数以及Bibliometrix和Corpus R的软件包。本研究证实了科学知识的碎片化,并指出了以下挑战:关键领域信息缺失,术语标准不存在,数据提取的局限性,引用文献的重复和多种格式。此外,它提出了实际的应对程序,并提出了对利益相关者的启示和未来研究的议程。原创性/价值本研究为科学知识碎片化的实证证实提供了有价值和实用的例子,并为识别研究过程中的许多挑战提供了一个综合的观点。此外,本研究提出了解决这些挑战的建议,不仅为科研人员提供了实践指导,而且引发了关于社会科学知识组织的更广泛的讨论。
Challenges in identifying studies to include in a systematic literature review: an analysis of the organizational growth and decline topics
Purpose
This paper aims to check the fragmentation of knowledge across multiple sources of evidence, identifying, scrutinizing and outlining suggestions concerning the challenges researchers face when using multiple sources of data to identify studies.
Design/methodology/approach
This study produced a comprehensive database of 15,848 items from Scopus, Web of Science and EBSCO on the organizational growth and decline topics. The analyses carried out to check the fragmentation of scientific knowledge and the challenges in identifying studies have made use of the basic data frame functions in R’s language and the Bibliometrix and Corpus R’s packages.
Findings
This study confirms the fragmentation of scientific knowledge as well as it identifies the following challenges: missing information in key fields, nonexistence of standards in terminology, limitations on data extraction, duplicates and multiple formats of cited reference. Additionally, it suggests practical coping procedures and advances implications for stakeholders and an agenda for future research.
Originality/value
This study provides valuable and practical examples with empirical confirmation of scientific knowledge fragmentation and offers an integrated view of many challenges in the process of identifying studies. Moreover, by offering suggestions to address these challenges, this study not only offers a practical guide to scientific researchers but also initiates a wider discussion regarding knowledge organizing in social sciences.