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Knowledge Complexity Reaction-Diffusion Equations With Application To Eastern Europe

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  • CIALFI Daniela

    (Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Studies G. d’Annunzio, Chieti-Pescara, Italy)

  • COLANTONIO Emiliano

    (Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Studies G. d’Annunzio, Chieti-Pescara, Italy)

Abstract

Nowadays, there is an increasing focus on knowledge input and output measurement rather than assessing the characteristics of the knowledge itself. This phenomenon happens since knowledge becomes central into capitalistic production processes: the competitive advantage of countries is the principal engine for the production of high-value, non-ubiquitous and complex knowledge (see Dicken, 2007). In this paper, we present the reaction-diffusion equations and their application to a particular economic phenomenon: in which way knowledge complexity diffusion might affect or not affect the labour productivity across the Eastern European countries. More profoundly, the aim followed by the present research work is to provide Eastern European countries with a substitute approach: a strategy. This strategy has the objective of enabling these countries to avoid acting as knowledge predators towards other countries (i.e. those such as Sweden, Finland and Denmark, referred to as prey countries, which invest their resources in knowledge and therefore in technology). We simulate the knowledge competition and the spill-over productivity effects across the Eastern and some European countries using specific reaction-diffusion equations types: the Lotka-Volterra equations which are able to describe a complex dynamic system of the prey-predator phenomenon. Our approach is based on the two steps of analysis. In essence, the first step, we compute the Knowledge Complexity Index of patents, for quantifying the European knowledge complexity; describing the possible spatial patterns and transformation of the European knowledge. Furthermore, we use the canonical Lotka-Volterra models of patents from the European Patent Office and the labour productivity data from the Eurostat database from 2000 and 2017 for Eastern European countries and some European countries, such as Finland, Sweden, Austria and Germany. More specifically, we have identified the presence of lagged knowledge between the Eastern European countries and some Northern European, such as Finland, Sweden and Denmark. In conclusion, the implementation of specific knowledge diffusion policy strategies could be helpful for future applications. It may avoid intra-guild cannibalism phenomenon from being engaged in some Eastern European countries.

Suggested Citation

  • CIALFI Daniela & COLANTONIO Emiliano, 2020. "Knowledge Complexity Reaction-Diffusion Equations With Application To Eastern Europe," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 23-31, July.
  • Handle: RePEc:ora:journl:v:1:y:2020:i:1:p:23-31
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    References listed on IDEAS

    as
    1. Pavitt, Keith, 1982. "R&D, patenting and innovative activities : A statistical exploration," Research Policy, Elsevier, vol. 11(1), pages 33-51, February.
    2. David J. Teece & Richard Rumelt & Giovanni Dosi & Sidney Winter, 2000. "Understanding Corporate Coherence: Theory and Evidence," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 9, pages 264-293, Edward Elgar Publishing.
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    More about this item

    Keywords

    Knowledge diffusion; complexity nonlinear systems; Eastern Europe; reaction-diffusion equations; Knowledge Complexity Index;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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