The Principle of Relatedness

Hidalgo, César A.; Balland, Pascale; Boschma, Ron; Delgado, Mercedes; Feldman, Maryann P.; Frenken, Koen; Glaeser, Edward L.; He, Canfei; Kogler, Dieter F.; Morrison, Andrea; Neffke, Frank; Rigby, David L.; Stern, Scott; Zheng, Siqi; Zhu, Shengjun

doi:10.1007/978-3-319-96661-8_46

Cited by 182 publications

(142 citation statements)

References 30 publications

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“…The purpose of the present contribution was to provide an initial critical review of the relatedness literature, and subsequently to evaluate its insights for regional diversification. Now well established, it is argued that relatedness is a tier one concept and when paired with the regional diversification literature can show promise not least in terms of, economic geography, regional studies, innovation studies, organizational management and economic sociology (Hidaldo et al, ). Against this backdrop, our arguments have been organized around three main pillars.…”

Section: Resultsmentioning

confidence: 99%

Related to what? Reviewing the literature on technological relatedness: Where we are now and where can we go?

Whittle

Kogler

2020

Papers in Regional Science

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The objective of this paper is to critically review contemporary insights derived from studies that focus on relatedness. A well-established body of literature has identified three approaches for measuring relatedness, those based on co-occurrence matrices, industrial hierarchy and resource similarity. From these measures, several authors have begun developing relational networks to capture the branching capabilities of products, industries, technologies and skills. Thereafter the present contribution then shifts from analysing 'what is' and begins considering what 'could be'? It argues that the concept of relatedness lies at the heart of deconstructing issues of unrelated diversification and smart specialisation.

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Section: Resultsmentioning

confidence: 99%

Related to what? Reviewing the literature on technological relatedness: Where we are now and where can we go?

Whittle

Kogler

2020

Papers in Regional Science

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“…PACS codes) into a research space in which scientifically similar topics are placed close to each other. The motivation behind this methodology lies in the principle of relatedness [57,58]: i.e. it is easier to specialize and work in related research areas requiring a set of common skills/knowledge.…”

Section: Resultsmentioning

confidence: 99%

“…The RCA in the context of the research space has been introduced by Guevara et al [47] to explore the principle of relatedness [57,58,76] in the process of scientific production: i.e. it is easier to specialize and work in related research areas requiring a set of common skills/knowledge.…”

Section: Knowledge Density and The Prediction Of Scientific Specializmentioning

confidence: 99%

Mapping the physics research space: a machine learning approach

et al. 2019

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Scientific discoveries do not occur in vacuum but rather by connecting existing pieces of knowledge in new and creative ways. Mapping the relation and structure of scientific knowledge is therefore central to our understanding of the dynamics of scientific production. Here we introduce a new approach to generate scientific knowledge maps based on a machine learning approach that, starting from the observed publication patterns of authors, generates an N-dimensional space where it is possible to measure the similarity or distance between different research topics and knowledge domains. We provide an implementation of the proposed approach that considers the American Physical Society publications database and generates a map of the research space in Physics that characterizes the relation among research topics over time. We use this map to measure two indicators, the research capacity fingerprint and the knowledge density, to profile the research activity in physical sciences of more than 400 urban areas across the world. We show that these indicators can be used to analyze and predict the evolution over time of the research capacity and specialization of specific geographical areas. Furthermore we provide an extensive analysis of the relation between socio-economic development indicators and the ability to produce new knowledge for 67 countries, as measured by our approach, highlighting some key correlates of scientific production capacity. The proposed approach is scalable to very large datasets and can be extended to study other disciplines and research areas without having to rely on ad-hoc science classification schemes.

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“…The economic complexity theory was formulated and developed by Hausmann & Hidalgo (Hidalgo et al 2009;Hidalgo et al 2007;Hausmann et al 2013;Hidalgo et al 2016;Hidalgo 2018;Hidalgo et al 2018). Economic complexity is a measure of the knowledge in a society that gets translated into the products it makes (Hidalgo et al 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The authors examine the longterm relationship between economic complexity, energy consumption structure, and greenhouse gas emission. Recent economic complexity studies concentrate on the principle of relatedness in the economic diversification, the dominance of technological innovation and optimization of knowledge diffusion (Boschma 2017;Hidalgo 2018;Hidalgo et al 2018;Alshamsi, Pinheiro et al 2018;Utkovski et al 2018;Hartmann et al 2019;Roos 2019). At the same time, it is necessary to recognize the technical issues in measuring the economic complexity level.…”

Section: Literature Reviewmentioning

confidence: 99%

European countries’ typology by the intensity of transboundary cooperation and its impact on the economic complexity level

Roos

Voloshenko

Drok

et al. 2020

GES

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Over recent years, it has become increasingly obvious that the countries, regions and individual systems are now developing within the framework of the emerging technological paradigm. The key elements for their development are knowledge and capabilities, being transformed into the products exported by a given country, these constitute the core of the economic complexity theory. In this article, the authors attempt to assess the long-term correlations between economic complexity and transboundary intensity drawing on the example of European countries. The authors developed a European Countries’ Typology according to their transboundary cooperation intensity. The paper establishes that the influence of the transboundary factor weakens as the economic complexity increases, and under certain conditions, it has a negative impact. It substantiates that the revealed relationships are due to the increasing role of global processes rather than transboundary ones as the economy becomes more complex and oriented towards the global market.

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The Principle of Relatedness

Cited by 182 publications

References 30 publications

Related to what? Reviewing the literature on technological relatedness: Where we are now and where can we go?

Related to what? Reviewing the literature on technological relatedness: Where we are now and where can we go?

Mapping the physics research space: a machine learning approach

European countries’ typology by the intensity of transboundary cooperation and its impact on the economic complexity level

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