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Presenter: Andy Newing

These online resources introduce you to Spatial Interaction Models (SIMs). SIMs are statistical models used to predict origin-destination flows. They are widely applied within geography, planning, transportation and the social sciences to predict interactions or flows related to commuting, migration, access to services etc. They are also widely applied across the commercial sector for example to model flows of consumers between home and retail centres with broad applications in commercial decision making and policy evaluation.

Spatial Interaction ModellingSpatial Interaction Modelling

This short video introduces you to Spatial Interaction Models (SIMs) within the context of social sciences research. No prior knowledge of SIMs are required as we use a straightforward and intuitive example based on modelling flows of consumers between their homes and retail stores. We use this example to outline the nature of spatial interaction and some of the theoretical considerations underpinning these models. We make use of accompanying online resources, including a PDF document (introduced fully within the video) which you can use to consider some of the underlying concepts.

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Introduction to spacial interaction modelling

Here are the slides in Microsoft Powerpoint format. You may want to explore the slides or download the entire presentation by clicking the link below

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These video resources were recorded on 2018-08-08 by the National Centre for Research Methods (NCRM) at the University of Southampton.

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Powerpoint presentations (PDF)

Video Transcripts (PDF)

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Recommended readings

  • Birkin, M and Clarke. G.P. 1991. Spatial interaction in geography. Geography Review, 4(5), pp.16-21.
  • Birkin, M., Clarke, G.P. and Clarke. M. 2010. Refining and operationalising entropy-maximising models for business applications Geographical Analysis, 42(4), pp.422-445.
  • Clarke, G.P. and Clarke, M. 2001. From theory to practice - making spatial interaction models work in different contexts, in G.P. Clarke & M. Madden (eds) Regional science in business, Springer-Verlag, Berlin, 137-158
  • Dennett, A. 2012. Working Paper Series Paper 181 Estimating flows between geographical locations: ?get me started in? spatial interaction modelling. London: Centre for Advanced Spatial Analysis, University College London
  • Newing, A, Clarke, G. P. Clarke, M. 2014. Developing and applying a disaggregated retail location model with extended retail demand estimations. Geographical Analysis. 47(3) pp219-239.
  • Roy, J. R. 2004. Spatial Interaction Modelling - A regional science context. Berlin: Springer-Verlag.
  • Roy, J. R. and Thill, J.-C. 2004. Spatial interaction modelling. Papers in Regional Science, 83(1), pp.339-361.
  • Wilson, A. G. 1971. A family of spatial interaction models, and associated developments. Environment and Planning 3, pp.1-32.
  • Wilson, A. G. 2010. Entropy in urban and regional modelling: retrospect and prospect. Geographical Analysis, 42(4), pp.364-394.


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Introduction to spacial interaction modelling

Bio paragraph of Andy Newing

Andy is a Lecturer in Retail Geography based in the Centre for Spatial Analysis and Policy (CSAP)at the University of Leeds. Andy carries out applied high impact research in collaboration with commercial and public sector organisations. Research interests include spatial and quantitative analysis for retail location planning and analytics, consumer data analysis, health service delivery, census/neighbourhood analysis, geodemographics, household energy, transport and urban planning. Andy is part of the Consumer Data Research Centre and also the Leeds Institute for Data Analytics. Andy delivers NCRM face to face training in Geographical Information Systems, Spatial Interaction Modelling and Population

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