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Convolutional Gravitational Models for Economic Exchanges: Mathematical Extensions for Dynamic Processes and Knowledge Flows

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Advances in Human Factors, Business Management and Society (AHFE 2018)

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Abstract

The Gravity Model of trade is a regression model for exchanges between countries. The model comprises a measure of exchange as its dependent variable, a measure of mass for each of the two exchanging parties, and a distance. Typically, the dependent variable represents exports, the measures of mass are the GDPs of two countries, and the distance is geographical distance. The analysis in this paper yields a number of simplifying assumptions, which if relaxed may yield a stronger model. The paper focuses on knowledge flows as measured through citations as a use case of a new convolutional gravitational model, which includes an element of delay in between the production of a good and its acquisition. The convolutional model further extends the concept of a distance between two entities to include a measure of affinity. These extensions clarify some limits of the basic model and conditions when it is appropriate.

M. H. Teodorescu—Also an affiliate of Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge MA 02139, USA.

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Correspondence to Mike Horia Teodorescu .

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Teodorescu, M.H. (2019). Convolutional Gravitational Models for Economic Exchanges: Mathematical Extensions for Dynamic Processes and Knowledge Flows. In: Kantola, J.I., Nazir, S., Barath, T. (eds) Advances in Human Factors, Business Management and Society. AHFE 2018. Advances in Intelligent Systems and Computing, vol 783. Springer, Cham. https://doi.org/10.1007/978-3-319-94709-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-94709-9_22

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