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An NK-like model for complexity

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  • Marco Valente

Abstract

The level and nature of complexity is widely regarded as an important determinant of a number of economic, technological and organizational phenomena. A popular modeling tool for the representation of complexity in economics and organizational sciences is the NK model that represents the complexity stemming from the interactions among the elements of a system. This paper proposes an enhanced model for complexity that, though maintaining the core design (and properties) of the NK model, provides a more intuitive and richer representation of complexity, extending its applications and deepening the understanding of its effects on economic systems. The proposed pseudo-NK (pNK) model is defined on real-valued variables, as opposed to the binary variables required by NK, so as to allow for richer and more intuitive definitions of distance and search strategies. It also admits as a source of complexity not only the number of interactions, as in NK, but also their intensity, opening a novel way to express and measure the level of complexity. Finally, instead of relying on statistical properties of a large dataset of random values, pNK is defined as a deterministic function, far simpler to implement, to interpret and to calibrate for specific requirements. The paper replicates known results and presents original ones; in both cases, the proposed model proves a powerful tool for the investigation of the role of complexity, particularly in agent-based models. Copyright Springer-Verlag Berlin Heidelberg 2014

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  • Marco Valente, 2014. "An NK-like model for complexity," Journal of Evolutionary Economics, Springer, vol. 24(1), pages 107-134, January.
    • Handle: RePEc:spr:joevec:v:24:y:2014:i:1:p:107-134
    DOI: 10.1007/s00191-013-0334-4
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    Cited by:

    1. Giovanni Dosi & Luigi Marengo & Evita Paraskevopoulou & Marco Valente, 2017. "A model of cognitive and operational memory of organizations in changing worlds," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 41(3), pages 775-806.
    2. Eric Kemp-Benedict, 2022. "A classical-evolutionary model of technological change," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1303-1343, September.
    3. Tommaso Ciarli & Karolina Safarzynska, 2020. "Sustainability and Industrial Challenge: The Hindering Role of Complexity," SPRU Working Paper Series 2020-18, SPRU - Science Policy Research Unit, University of Sussex Business School.
    4. Thiago Caliari & Ricardo Machado Ruiz & Marco Valente, 2016. "Heterogeneidade Da Demanda E Inovação De Produtos," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 135, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. Peili Yu & Junguo Shi & Bert M. Sadowski & Önder Nomaler, 2020. "Catching Up in the Face of Technological Discontinuity: Exploring the Role of Demand Structure and Technological Regimes in the Transition from 2G to 3G in China," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 815-841, July.

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    More about this item

    Keywords

    NK model; Complexity; Simulation models; C63; D83; O32; O33;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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