制造业中的创造性破坏和技术范式:技术组合评估的大规模回顾和框架

IF 5.2 3区 管理学 Q1 BUSINESS
Muntaser Mohamed Nuttah;Hatem Algabroun;Claudio Linhares;Lars Håkansson
{"title":"制造业中的创造性破坏和技术范式:技术组合评估的大规模回顾和框架","authors":"Muntaser Mohamed Nuttah;Hatem Algabroun;Claudio Linhares;Lars Håkansson","doi":"10.1109/TEM.2025.3592031","DOIUrl":null,"url":null,"abstract":"Manufacturing digitalization and automation research has expanded rapidly over the past decades. However, the current literature often presents fragmented views, lacking a comprehensive understanding of its evolution. Due to the vast number of publications, traditional literature reviews are impractical for broad fields like manufacturing digitalization and automation. This study leverages recent advancements in artificial intelligence (AI), large language models, and natural language processing to analyze 31 914 scientific papers from 1970 to 2023, providing a knowledge structure of the field. Moreover, we provide a roadmap of the field’s evolution using dynamic topic modeling. We note emerging trends in energy efficiency (since 2004), composite materials (2006), cybersecurity (2008), robotics (2014), and AI (2016), while simulation, scheduling, and process planning maintain steady and consistent research interests. In addition, we observe a decay in certain research areas such as manufacturing automation protocol, a once-prominent area in the 1980s introduced by general motors. We introduce a technology portfolio assessment framework categorizing technologies into emerging, established, experimental, and decaying quadrants. The proposed framework is based on the findings of this study, technology life cycle, creative destruction, and technological paradigms theories. The findings also offer insights into thematic shifts across the literature, consistent with creative destruction and technological paradigm theories. These findings hold implications for academia, industry, and policymakers, supporting more strategic innovation and resource allocation in the manufacturing sector.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"3397-3418"},"PeriodicalIF":5.2000,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Creative Destruction and Technological Paradigms in Manufacturing: A Large-Scale Review and Framework for Technology Portfolio Assessment\",\"authors\":\"Muntaser Mohamed Nuttah;Hatem Algabroun;Claudio Linhares;Lars Håkansson\",\"doi\":\"10.1109/TEM.2025.3592031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Manufacturing digitalization and automation research has expanded rapidly over the past decades. However, the current literature often presents fragmented views, lacking a comprehensive understanding of its evolution. Due to the vast number of publications, traditional literature reviews are impractical for broad fields like manufacturing digitalization and automation. This study leverages recent advancements in artificial intelligence (AI), large language models, and natural language processing to analyze 31 914 scientific papers from 1970 to 2023, providing a knowledge structure of the field. Moreover, we provide a roadmap of the field’s evolution using dynamic topic modeling. We note emerging trends in energy efficiency (since 2004), composite materials (2006), cybersecurity (2008), robotics (2014), and AI (2016), while simulation, scheduling, and process planning maintain steady and consistent research interests. In addition, we observe a decay in certain research areas such as manufacturing automation protocol, a once-prominent area in the 1980s introduced by general motors. We introduce a technology portfolio assessment framework categorizing technologies into emerging, established, experimental, and decaying quadrants. The proposed framework is based on the findings of this study, technology life cycle, creative destruction, and technological paradigms theories. The findings also offer insights into thematic shifts across the literature, consistent with creative destruction and technological paradigm theories. These findings hold implications for academia, industry, and policymakers, supporting more strategic innovation and resource allocation in the manufacturing sector.\",\"PeriodicalId\":55009,\"journal\":{\"name\":\"IEEE Transactions on Engineering Management\",\"volume\":\"72 \",\"pages\":\"3397-3418\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Engineering Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11105708/\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Engineering Management","FirstCategoryId":"91","ListUrlMain":"https://ieeexplore.ieee.org/document/11105708/","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0

摘要

在过去的几十年里,制造业数字化和自动化研究得到了迅速发展。然而,目前的文献往往呈现出碎片化的观点,缺乏对其演变的全面理解。由于出版物数量庞大,传统的文献综述对于制造业数字化和自动化等广泛领域来说是不切实际的。本研究利用人工智能(AI)、大型语言模型和自然语言处理的最新进展,分析了1970年至2023年的31914篇科学论文,提供了该领域的知识结构。此外,我们还使用动态主题建模提供了该领域发展的路线图。我们注意到能源效率(自2004年以来)、复合材料(2006年)、网络安全(2008年)、机器人(2014年)和人工智能(2016年)等领域的新兴趋势,而仿真、调度和工艺规划保持了稳定和一致的研究兴趣。此外,我们观察到某些研究领域出现衰退,例如制造自动化协议,这是通用汽车在20世纪80年代引入的一个曾经非常突出的领域。我们介绍了一个技术组合评估框架,将技术分类为新兴的、建立的、实验的和衰退的象限。该框架基于本研究成果、技术生命周期理论、创造性破坏理论和技术范式理论。研究结果还提供了对整个文学主题转变的见解,与创造性破坏和技术范式理论相一致。这些发现对学术界、工业界和政策制定者具有启示意义,支持制造业进行更多的战略创新和资源配置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Creative Destruction and Technological Paradigms in Manufacturing: A Large-Scale Review and Framework for Technology Portfolio Assessment
Manufacturing digitalization and automation research has expanded rapidly over the past decades. However, the current literature often presents fragmented views, lacking a comprehensive understanding of its evolution. Due to the vast number of publications, traditional literature reviews are impractical for broad fields like manufacturing digitalization and automation. This study leverages recent advancements in artificial intelligence (AI), large language models, and natural language processing to analyze 31 914 scientific papers from 1970 to 2023, providing a knowledge structure of the field. Moreover, we provide a roadmap of the field’s evolution using dynamic topic modeling. We note emerging trends in energy efficiency (since 2004), composite materials (2006), cybersecurity (2008), robotics (2014), and AI (2016), while simulation, scheduling, and process planning maintain steady and consistent research interests. In addition, we observe a decay in certain research areas such as manufacturing automation protocol, a once-prominent area in the 1980s introduced by general motors. We introduce a technology portfolio assessment framework categorizing technologies into emerging, established, experimental, and decaying quadrants. The proposed framework is based on the findings of this study, technology life cycle, creative destruction, and technological paradigms theories. The findings also offer insights into thematic shifts across the literature, consistent with creative destruction and technological paradigm theories. These findings hold implications for academia, industry, and policymakers, supporting more strategic innovation and resource allocation in the manufacturing sector.
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
IEEE Transactions on Engineering Management
IEEE Transactions on Engineering Management 管理科学-工程:工业
CiteScore
10.30
自引率
19.00%
发文量
604
审稿时长
5.3 months
期刊介绍: Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.
×
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:604180095
Book学术官方微信