对数字化转型中知识转让伙伴关系的科学计量分析

Q1 Economics, Econometrics and Finance
Lihong Zhang , Saeed Banihashemi , Liting Zhu , Homa Molavi , Eyyub Odacioglu , Miyuan Shan
{"title":"对数字化转型中知识转让伙伴关系的科学计量分析","authors":"Lihong Zhang ,&nbsp;Saeed Banihashemi ,&nbsp;Liting Zhu ,&nbsp;Homa Molavi ,&nbsp;Eyyub Odacioglu ,&nbsp;Miyuan Shan","doi":"10.1016/j.joitmc.2024.100325","DOIUrl":null,"url":null,"abstract":"<div><p>In an era where digital transformation (DT) reshapes industries, the role of Knowledge Transfer Partnerships (KTP) in bridging academic insights with industrial innovation becomes crucial. This study conducts a comprehensive scientometric analysis of 360 academic papers spanning from 2013 to 2023 to map the evolving landscape of KTP in the context of DT. By employing advanced visualization tools including generative visual networks and keyword co-occurrence analysis through CiteSpace, critical research gaps and trends, particularly addressing how KTP can mitigate technological obsolescence and enhance innovation management within enterprises are identified. The findings reveal a significant escalation in research output related to KTP, with a pronounced focus on integrating cutting-edge technologies of Artificial Intelligence, machine learning and virtual reality and fostering market adaptability. This study charts the exponential growth of literature and highlights strategic areas of research entities, global geographical coverage, and advanced digital trends where KTPs are pivotal in enhancing organizational resilience and competitive advantage in a rapidly digitizing world. This paper contributes to the existing knowledge of KTP by identifying the patterns and trends of on-going research and offering an evolutionary model to guide theoretical development and practical business operations and policy making.</p></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2199853124001197/pdfft?md5=df4b3358ec6efd73df9f4a1bff19f40d&pid=1-s2.0-S2199853124001197-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A scientometric analysis of knowledge transfer partnerships in digital transformation\",\"authors\":\"Lihong Zhang ,&nbsp;Saeed Banihashemi ,&nbsp;Liting Zhu ,&nbsp;Homa Molavi ,&nbsp;Eyyub Odacioglu ,&nbsp;Miyuan Shan\",\"doi\":\"10.1016/j.joitmc.2024.100325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In an era where digital transformation (DT) reshapes industries, the role of Knowledge Transfer Partnerships (KTP) in bridging academic insights with industrial innovation becomes crucial. This study conducts a comprehensive scientometric analysis of 360 academic papers spanning from 2013 to 2023 to map the evolving landscape of KTP in the context of DT. By employing advanced visualization tools including generative visual networks and keyword co-occurrence analysis through CiteSpace, critical research gaps and trends, particularly addressing how KTP can mitigate technological obsolescence and enhance innovation management within enterprises are identified. The findings reveal a significant escalation in research output related to KTP, with a pronounced focus on integrating cutting-edge technologies of Artificial Intelligence, machine learning and virtual reality and fostering market adaptability. This study charts the exponential growth of literature and highlights strategic areas of research entities, global geographical coverage, and advanced digital trends where KTPs are pivotal in enhancing organizational resilience and competitive advantage in a rapidly digitizing world. This paper contributes to the existing knowledge of KTP by identifying the patterns and trends of on-going research and offering an evolutionary model to guide theoretical development and practical business operations and policy making.</p></div>\",\"PeriodicalId\":16678,\"journal\":{\"name\":\"Journal of Open Innovation: Technology, Market, and Complexity\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2199853124001197/pdfft?md5=df4b3358ec6efd73df9f4a1bff19f40d&pid=1-s2.0-S2199853124001197-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Open Innovation: Technology, Market, and Complexity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2199853124001197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Innovation: Technology, Market, and Complexity","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2199853124001197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0

摘要

在数字化转型(DT)重塑产业的时代,知识转移合作伙伴关系(KTP)在连接学术见解与产业创新方面的作用变得至关重要。本研究对 2013 年至 2023 年期间的 360 篇学术论文进行了全面的科学计量分析,以绘制 DT 背景下 KTP 的演变图景。通过采用先进的可视化工具,包括生成式可视化网络和 CiteSpace 的关键词共现分析,确定了关键的研究差距和趋势,特别是 KTP 如何缓解技术过时问题和加强企业内部的创新管理。研究结果表明,与 KTP 相关的研究成果大幅增加,重点明显集中在整合人工智能、机器学习和虚拟现实等尖端技术以及促进市场适应性方面。本研究描绘了文献的指数级增长,并强调了研究实体的战略领域、全球地理覆盖范围以及先进的数字化趋势,在这些领域中,KTP 在快速数字化的世界中对于增强组织复原力和竞争优势至关重要。本文通过识别正在进行的研究的模式和趋势,为现有的 KTP 知识做出了贡献,并提供了一个进化模型来指导理论发展和实际业务操作及政策制定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A scientometric analysis of knowledge transfer partnerships in digital transformation

In an era where digital transformation (DT) reshapes industries, the role of Knowledge Transfer Partnerships (KTP) in bridging academic insights with industrial innovation becomes crucial. This study conducts a comprehensive scientometric analysis of 360 academic papers spanning from 2013 to 2023 to map the evolving landscape of KTP in the context of DT. By employing advanced visualization tools including generative visual networks and keyword co-occurrence analysis through CiteSpace, critical research gaps and trends, particularly addressing how KTP can mitigate technological obsolescence and enhance innovation management within enterprises are identified. The findings reveal a significant escalation in research output related to KTP, with a pronounced focus on integrating cutting-edge technologies of Artificial Intelligence, machine learning and virtual reality and fostering market adaptability. This study charts the exponential growth of literature and highlights strategic areas of research entities, global geographical coverage, and advanced digital trends where KTPs are pivotal in enhancing organizational resilience and competitive advantage in a rapidly digitizing world. This paper contributes to the existing knowledge of KTP by identifying the patterns and trends of on-going research and offering an evolutionary model to guide theoretical development and practical business operations and policy making.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Open Innovation: Technology, Market, and Complexity
Journal of Open Innovation: Technology, Market, and Complexity Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
11.00
自引率
0.00%
发文量
196
审稿时长
1 day
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信