The quintuple innovation helix plus AI: A prospective retrospective approach and the use case of semiconductors

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-04-12 DOI:10.1016/j.techfore.2025.124122

Elias G. Carayannis , Steffen Preissler

{"title":"The quintuple innovation helix plus AI: A prospective retrospective approach and the use case of semiconductors","authors":"Elias G. Carayannis , Steffen Preissler","doi":"10.1016/j.techfore.2025.124122","DOIUrl":null,"url":null,"abstract":"<div><div>This article explores the intricate connections between economic, (geo)political, societal, scientific, and environmental factors aiming to foster dialogue on leveraging past developments for a desirable future (e.g. “Green ICT”, “Society 6.0”). Utilizing the Quintuple-Innovation-Helix-plus-AI Framework (QIH + AI), which integrates policy, economy, science, society, and environment (planet) as interrelated strands, the study emphasizes the significance of knowledge flows in shaping these domains.</div><div>The research identifies a gap in applying the QIH + AI model to the semiconductor industry and proposes a retrospective analysis of historical milestones to elucidate the evolution of this sector. By mapping these milestones onto QIH + AI, we demonstrate the dynamic interconnections among the strands and the influence of AI on the overall system development. Thus, we present a historical examination at a meta level (analogy: learning vs. learning-how-to-learn vs learning-to-learn-how-to-learn). This has not been a subject of research so far, constituting a notable gap.</div><div>The findings provide valuable insights for policymakers and industry leaders in navigating the complexities of technological advancements within the semiconductor landscape, ultimately contributing to a holistic understanding of the interplay between policy, economy, technology, society, and the environment.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"216 ","pages":"Article 124122"},"PeriodicalIF":12.9000,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040162525001532","RegionNum":1,"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

Abstract

This article explores the intricate connections between economic, (geo)political, societal, scientific, and environmental factors aiming to foster dialogue on leveraging past developments for a desirable future (e.g. “Green ICT”, “Society 6.0”). Utilizing the Quintuple-Innovation-Helix-plus-AI Framework (QIH + AI), which integrates policy, economy, science, society, and environment (planet) as interrelated strands, the study emphasizes the significance of knowledge flows in shaping these domains.

The research identifies a gap in applying the QIH + AI model to the semiconductor industry and proposes a retrospective analysis of historical milestones to elucidate the evolution of this sector. By mapping these milestones onto QIH + AI, we demonstrate the dynamic interconnections among the strands and the influence of AI on the overall system development. Thus, we present a historical examination at a meta level (analogy: learning vs. learning-how-to-learn vs learning-to-learn-how-to-learn). This has not been a subject of research so far, constituting a notable gap.

The findings provide valuable insights for policymakers and industry leaders in navigating the complexities of technological advancements within the semiconductor landscape, ultimately contributing to a holistic understanding of the interplay between policy, economy, technology, society, and the environment.

查看原文本刊更多论文

五重创新螺旋加上人工智能：半导体的前瞻性回顾方法和用例

本文探讨了经济、（地理）政治、社会、科学和环境因素之间的复杂联系，旨在促进利用过去的发展来实现理想的未来（例如“绿色ICT”、“社会6.0”）的对话。利用将政策、经济、科学、社会和环境（地球）作为相互关联的部分整合在一起的“五重创新-螺旋-人工智能框架”（QIH + AI），该研究强调了知识流动在塑造这些领域中的重要性。该研究发现了将QIH + AI模型应用于半导体行业的差距，并提出了对历史里程碑的回顾性分析，以阐明该行业的演变。通过将这些里程碑映射到QIH + AI上，我们展示了各个分支之间的动态相互联系以及AI对整个系统开发的影响。因此，我们在元层面上提出了一个历史检验（类比：学习vs.学习如何学习vs.学习如何学习）。到目前为止，这还不是一个研究课题，构成了一个显著的差距。这些发现为政策制定者和行业领导者提供了宝贵的见解，帮助他们驾驭半导体领域技术进步的复杂性，最终有助于全面了解政策、经济、技术、社会和环境之间的相互作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

期刊介绍： Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.