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Application of Agent-Based Modelling to the Dynamics of Creative Industries’ Interactions with Urban Land Use: An Introduction

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Creative Industries and Urban Spatial Structure

Abstract

As has been proposed, the dynamics of creative industries’ interactions with urban land use is complex and can be examined by the approach of agent-based modelling. In agent-based modelling, one central issue is to clearly define the rules that the agents follow. However, the locational behaviours of the creative firms and the creative workers are not easy to describe as the factors are multidimensional. This chapter focuses on explaining how the concept of locational utility function is introduced to describe the locational behaviours of the firms and the workers and what the requisite data are for this purpose.

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References

  • Amblard F, Phan D (2007) Introduction. In: Phan D, Amblard F (eds) Agent-based modelling and simulation in the social and human sciences. Bardwell Press, Oxford, pp 1–33

    Google Scholar 

  • Batty M, Crooks AT, See LM, Heppenstall AJ (2012) Perspectives on agent-based models and geographical systems. In: Heppenstall AJ, Crooks AT, Batty LMM (eds) Agent-based models of geographical systems. Springer, Dordrecht, pp 1–15

    Chapter  Google Scholar 

  • Charypar D, Nagel K (2005) Generating complete all-day plans with genetic algorithms. Transp 32(4):369–397

    Article  Google Scholar 

  • Crooks AT, Castle CJE (2012) The integration of agent-based modelling and geographical information for geospatial simulation. In: Heppenstall AJ, Crooks AT, Batty LMM (eds) Agent-based models of geographical systems. Springer, Dordrecht, pp 219–251

    Chapter  Google Scholar 

  • Crooks AT, Heppenstall AJ (2012) Introduction to agent-based modelling. In: Heppenstall AJ, Crooks AT, Batty LMM (eds) Agent-based models of geographical systems. Springer, Dordrecht, pp 85–105

    Chapter  Google Scholar 

  • Eiselt HA, Marianov V (2011) Foundations of location analysis. Springer, NewYork/London

    Book  Google Scholar 

  • Ferber A (2007) Multi-agent concepts and methodologies. In: Phan D, Amblard F (eds) Agent-based modelling and simulation in the social and human sciences. Bardwell Press, Oxford, pp 1–33

    Google Scholar 

  • Foot DHS (1981) Operational urban models : an introduction. Methuen, London

    Google Scholar 

  • Handy S, Niemeier D (1997) Measuring accessibility: an exploration of issues and alternatives. Environ Plan A 29(7):1175–1194

    Article  Google Scholar 

  • Harrington JW, Warf B (2002) Industrial location: principles, practice, and policy. Routledge, London/New York

    Google Scholar 

  • Heppenstall AJ, Evans AJ, Birkin MH (2007) Genetic algorithm optimisation of an agent-based model for simulating a retail market. Environ Plan B: Plan Des 34(6):1051–1070

    Article  Google Scholar 

  • Horni A, Scott DM, Balmer M, Axhausen KW (2009) Location choice modeling for shopping and leisure activities with MATSim: utility function extension and validation results. Working paper 5xx. Institute for transport planning and systems, ETH Zürich

    Google Scholar 

  • Levy S, Martens K, Heijden RVD, Filatova T (2013) Negotiated heights: an agent-based model of density in residential patterns. Paper presented at the 13th international conference on Computers in Urban Planning and Urban Management (CUPUM), Utrecht

    Google Scholar 

  • McCann P (2002) Industrial location economics. E. Elgar, Cheltenham

    Book  Google Scholar 

  • Railsback SF, Grimm V (2012) Agent-based and individual-based modeling : a practical introduction. Princeton University Press, Princeton

    Google Scholar 

  • Silva EA (2011) Cellular automata and agent base models for urban studies: from pixels to cells to hexa-dpi’s. In: Yang X (ed) Urban remote sensing: monitoring, synthesis and modeling in the urban environment. Wiley, Hoboken, pp 323–334

    Chapter  Google Scholar 

  • Silva EA, Wu N (2012) Surveying models in urban land studies. J Plan Lit 27(2):139–152

    Article  Google Scholar 

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Liu, H., Silva, E.A., Wang, Q. (2015). Application of Agent-Based Modelling to the Dynamics of Creative Industries’ Interactions with Urban Land Use: An Introduction. In: Creative Industries and Urban Spatial Structure. Advances in Asian Human-Environmental Research. Springer, Cham. https://doi.org/10.1007/978-3-319-16610-0_3

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