The theory of technological response and progress in chaos

IF 2.3 Q3 REGIONAL & URBAN PLANNING Foresight Pub Date : 2023-04-21 DOI:10.1108/fs-11-2022-0138
Sercan Ozcan, Ozcan Saritas
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Design/methodology/approach This study used the grounded theory as a methodology with a mixed-method approach that included quantitative and qualitative methods. The authors used the quantitative method to assist with the qualitative step to build the TRPC theory. Accordingly, this study integrated machine learning and text mining approaches to the qualitative data analysis following the steps of the grounded theory approach. Findings As a result of the TRPC theory development process, the authors identified three types of technologies (survival, essential and enhancement technologies) and five types of periods (stable, initial, survival-dominant, essential-dominant and enhancement-dominant periods) that are specific to chaos-technology interactions. The policy implications of this study demonstrate that a required technological base and know-how must be established before a chaotic event emerges. Research limitations/implications Concerning the limitations of this study, social media data has advantages over other data sources, such as the examination of dynamic areas and analyses of immediate responses to chaos. However, other researchers can examine publications and patent sources to augment the findings concerning scientific approaches and new inventions in relation to COVID-19 and other chaos-specific developments. The authors developed the TRPC theory by studying the COVID-19 pandemic, however, other researchers can utilise it to study other chaos-related conditions, such as chaotic events that are caused by natural disasters. Other scholars can investigate the technological response and progress pattern in other rapidly emerging chaotic events of an uncertain and complex nature to augment these findings. Practical implications Following the indications of the OECD (2021a) and considering the study conducted by the European Parliamentary Research Service (Kritikos, 2020), the authors identified the key technologies that are significant for chaos and COVID-19 response using machine learning and text intelligence approach. Accordingly, the authors mapped all technological developments using clustering approaches, and examined the technological progress within the immediate chaos period using social media data. Social implications The key policy implication of this study concerns the need for policymakers to develop policies that will help to establish the required technological base and know-how before chaos emerges. As a result, a rapid response can be implemented to mitigate the chaos and transform it into a competitive advantage. The authors also revealed that this recommendation overlaps with the model of dynamic capabilities in the literature (Teece and Pisano, 2003). 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Abstract

Purpose This study aims to develop the first Theory of Technological Response and Progress in Chaos (TRPC) and examine the case of technological development during the COVID-19 pandemic. The research objectives of this study were to: identify the key technologies that act as a response mechanism during the chaos event, specifically in the case of COVID-19; examine how technologies evolve, develop and diffuse in an immediate crisis and a chaotic environment; theorise various types and periods of technological response and progress during the emergence of chaos and the stages that unfold; and develop policy-oriented recommendations and establish technological foundations to address subsequent chaos events. Design/methodology/approach This study used the grounded theory as a methodology with a mixed-method approach that included quantitative and qualitative methods. The authors used the quantitative method to assist with the qualitative step to build the TRPC theory. Accordingly, this study integrated machine learning and text mining approaches to the qualitative data analysis following the steps of the grounded theory approach. Findings As a result of the TRPC theory development process, the authors identified three types of technologies (survival, essential and enhancement technologies) and five types of periods (stable, initial, survival-dominant, essential-dominant and enhancement-dominant periods) that are specific to chaos-technology interactions. The policy implications of this study demonstrate that a required technological base and know-how must be established before a chaotic event emerges. Research limitations/implications Concerning the limitations of this study, social media data has advantages over other data sources, such as the examination of dynamic areas and analyses of immediate responses to chaos. However, other researchers can examine publications and patent sources to augment the findings concerning scientific approaches and new inventions in relation to COVID-19 and other chaos-specific developments. The authors developed the TRPC theory by studying the COVID-19 pandemic, however, other researchers can utilise it to study other chaos-related conditions, such as chaotic events that are caused by natural disasters. Other scholars can investigate the technological response and progress pattern in other rapidly emerging chaotic events of an uncertain and complex nature to augment these findings. Practical implications Following the indications of the OECD (2021a) and considering the study conducted by the European Parliamentary Research Service (Kritikos, 2020), the authors identified the key technologies that are significant for chaos and COVID-19 response using machine learning and text intelligence approach. Accordingly, the authors mapped all technological developments using clustering approaches, and examined the technological progress within the immediate chaos period using social media data. Social implications The key policy implication of this study concerns the need for policymakers to develop policies that will help to establish the required technological base and know-how before chaos emerges. As a result, a rapid response can be implemented to mitigate the chaos and transform it into a competitive advantage. The authors also revealed that this recommendation overlaps with the model of dynamic capabilities in the literature (Teece and Pisano, 2003). Furthermore, this study recommends that nations and organisations establish a technological base that specifically includes technologies that bear 3A characteristics. These are the most crucial technologies for the survival- and essential-dominant stages. Moreover, the results of this study demonstrate that chaos accelerates technological progress through the rapid adoption and diffusion of technologies into different fields. Hence, nations and organisations should regard this rapid progress as an opportunity and establish the prior knowledge base and technologies before chaos emerges. Originality/value The authors have contributed to the chaos studies and the relationship between chaos and technological development by establishing the first theoretical foundation using the grounded theory approach, hereafter referred to as the TRPC theory. As part of the TRPC theory, the authors present three periods of technological response in the following sequence: survival technology, essential technology and enhancement technology. Moreover, this study illustrates the evolving technological importance and priorities as the periods of technological progress proceed under rapidly developing chaos.
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混沌中的技术反应与进步理论
本研究旨在建立首个混沌中的技术响应与进步理论(TRPC),并考察新冠肺炎大流行期间的技术发展案例。本研究的研究目标是:确定在混乱事件中,特别是在COVID-19的情况下,作为响应机制的关键技术;检查技术如何演变,发展和扩散在一个直接的危机和混乱的环境;理论化各种类型和时期的技术反应和进步在混乱的出现和发展阶段;制定政策导向的建议并建立技术基础,以应对随后的混乱事件。设计/方法/方法本研究使用扎根理论作为一种方法,采用混合方法方法,包括定量和定性方法。作者采用定量方法辅助定性步骤建立了TRPC理论。因此,本研究遵循扎根理论方法的步骤,将机器学习和文本挖掘方法集成到定性数据分析中。在TRPC理论的发展过程中,作者确定了三种类型的技术(生存、基本和增强技术)和五种类型的时期(稳定、初始、生存-主导、基本-主导和增强-主导时期),这些时期是混沌-技术相互作用所特有的。本研究的政策含义表明,在混乱事件出现之前,必须建立必要的技术基础和专门知识。关于本研究的局限性,社交媒体数据比其他数据源有优势,例如对动态区域的检查和对混乱的即时反应的分析。然而,其他研究人员可以检查出版物和专利来源,以补充与COVID-19和其他特定混乱发展有关的科学方法和新发明的发现。作者通过研究COVID-19大流行开发了TRPC理论,然而,其他研究人员可以利用它来研究其他与混乱相关的情况,例如由自然灾害引起的混乱事件。其他学者可以研究其他不确定和复杂性质的快速出现的混乱事件中的技术响应和进步模式,以补充这些发现。根据经合组织(2021a)的指示,并考虑到欧洲议会研究服务处(Kritikos, 2020)进行的研究,作者确定了使用机器学习和文本智能方法对混乱和COVID-19应对具有重要意义的关键技术。因此,作者使用聚类方法绘制了所有技术发展,并使用社交媒体数据检查了直接混乱时期的技术进步。本研究的主要政策含义涉及决策者需要制定政策,帮助在混乱出现之前建立所需的技术基础和专门知识。因此,可以实施快速反应以减轻混乱并将其转化为竞争优势。作者还发现,这一建议与文献中的动态能力模型重叠(Teece和Pisano, 2003)。此外,本研究建议国家和组织建立一个专门包括具有3A特征的技术的技术基础。这些都是生存和基本主导阶段最关键的技术。此外,本研究的结果表明,混沌通过技术在不同领域的快速采用和扩散来加速技术进步。因此,国家和组织应将这种快速发展视为机遇,并在混乱出现之前建立先验知识基础和技术。作者运用扎根理论方法(以下简称TRPC理论)建立了第一个理论基础,为混沌研究以及混沌与技术发展的关系做出了贡献。作为TRPC理论的一部分,作者按照以下顺序提出了三个技术响应时期:生存技术、必要技术和增强技术。此外,本研究还说明了在快速发展的混乱中,随着技术进步时期的进行,技术重要性和优先级的变化。
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来源期刊
Foresight
Foresight REGIONAL & URBAN PLANNING-
CiteScore
5.10
自引率
5.00%
发文量
45
期刊介绍: ■Social, political and economic science ■Sustainable development ■Horizon scanning ■Scientific and Technological Change and its implications for society and policy ■Management of Uncertainty, Complexity and Risk ■Foresight methodology, tools and techniques
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