Keywords
spatial econometrics
space-time geography
space-economy
How to Cite
Abstract
This paper addresses new trends in quantitative geography research. Modern social science research - including economic and social geography - has in the past decades shown an increasing interest in micro-oriented behaviour of actors. This is inter alia clearly reflected in spatial interaction models (SIMs), where discrete choice approaches have assumed a powerful position. This paper aims to provide in particular a concise review of micro-based research, with the aim to review the potential - but also the caveats - of micro-models to map out human behaviour. In particular, attention will be devoted to interactive learning principles that shape individual decisions. Lessons from cognitive sciences will be put forward and illustrated, amongst others on the basis of computational neural networks or spatial econometric approaches. The methodology of deductive reasoning under conditions of large data bases in studying human mobility will be questioned as well. In this context more extensive attention is given to ceteris paribus conditions and evolutionary thinking.
References
Ahas R., Aasa A., Mark U., Pae T. & Kull T., 2006. Seasonal tourism spaces in Estonia: Case study with mobile positioning data. Tourism Management, 28(3): 898-910. DOI: https://www.doi.org/10.1016/j.tourman.2006.05.010
Ahas R., Aasa A., Silm S. & Tiru M., 2007. Mobile positioning data in tourism studies and monitoring: Case study in Tartu, Estonia. In: Sigala M., Mich L. & Murphy J. (eds), Springer computer science: Information and communication technologies in tourism. Springer, Berlin: 119-128. DOI: https://www.doi.org/10.1007/978-3-211-69566-1_12
Ahas R., Saluveer E., Tiru M. & Silm S., 2008. Mobile positioning based tourism monitoring system: Positium barometer. In: O'Connor P., Höpken W. & Gretzel U. (eds), Information and communication technologies in tourism 2008. Springer, Berlin: 475-485. DOI: https://www.doi.org/10.1007/978-3-211-77280-5_42
Andersson C., Frenken K. & Hellervik A., 2006. A complex networks approach to urban growth. Environment and Planning A, 38: 1941-1964. DOI: https://www.doi.org/10.1068/a37418
Anselin L. & Rey S.J. (eds), 2010. Perspectives on spatial data analysis. Springer Verlag, Berlin. DOI: https://www.doi.org/10.1007/978-3-642-01976-0
Arribas D., Nijkamp P. & Scholten H., 2010. Multidimensional urban sprawl in Europe: A self-organizing map approach. Technical report. Department of Spatial Economics, VU University, Amsterdam. Research Paper.
Bar-Gera H., 2007. Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: A case study from Israel. Transportation Research, Part C, 15(6): 380-391. DOI: https://www.doi.org/10.1016/j.trc.2007.06.003
Barabási A.L., 2009. We are at the threshold of understanding complexity. In: 12 Scientists on the 21st Century. World Science Forum, Budapest: 19-26.
Barabási A.L. & Albert R., 1999. Emergence of scaling in random networks. Science, 286: 509-512. DOI: https://www.doi.org/10.1126/science.286.5439.50910521342
Batty M., 2005. Cities and complexity. MIT Press, Cambridge, MA.
Bavaud F. & Mager C. (eds), 2009. Handbook of theoretical and quantitative geography. UNIL, Lausanne.
Bergh J.C.J.M. van den, 2004. Optimal climate policy is a utopia: From quantitative to qualitative cost-benefit analysis. Ecological Economics, 48: 385-393. DOI: https://www.doi.org/10.1016/j.ecolecon.2003.10.011
Bergh J.C.J.M. van den, 2007. Evolutionary thinking in environmental economics. Journal of Evolutionary Economics, 17: 521-549. DOI: https://www.doi.org/10.1007/s00191-006-0054-0
Bergh J.C.J.M. van den, Faber A., Idenburg A.M. & Oosterhuis F.H., 2007. Evolutionary economics and environmental policy: Survival of the greenest. Edward Elgar, Cheltenham. DOI: https://www.doi.org/10.4337/9781847205568
Bertuglia C.S. & Vaio F., 2009. The complexity approach to urban and regional systems and to the economy in general. Review of Economic Conditions in Italy, 2: 123-176.
Boccaletti S., Latora V., Moreno Y., Chavez M. & Hwang D.-U., 2006. Complex networks: Structures and dynamics. Physics Report, 424 (4-5): 175-308. DOI: https://www.doi.org/10.1016/j.physrep.2005.10.009
Boschma R.A., 2004. Competitiveness of regions from an evolutionary perspective. Regional Studies, 38(9): 1001-1014.10.1080/0034340042000292601
Boschma R.A. & Frenken K., 2006. Why is economic geography not an evolutionary science? Towards an evolutionary economic geography. Journal of Economic Geography, 6(3): 273-302. DOI: https://www.doi.org/10.1093/jeg/lbi022
Boschma R.A. & Lambooy J.G., 1999. Evolutionary economics and economic geography. Journal of Evolutionary Economics, 9: 411-429. DOI: https://www.doi.org/10.1007/s001910050089
Boulding K.E., 1981. Evolutionary economics. Sage Publications, Beverly Hills.
Boutilier C., Brafman R.I., Domshlak C., Hoos H.H. & Poole D., 2004. CP-Nets: A tool for representing and reasoning with conditional ceteris paribus preference statements. Journal of Artificial Intelligence Research, 21: 135-141. DOI: https://www.doi.org/10.1613/jair.1234
Brenner T., 2004. Local industrial clusters - existence, emergence and evolution. Routledge, London and New York.
Calabrese F., Ratti C. & Reades J., 2001. Eigenplaces: segmenting space through digital signatures. Pervasive Computing, 10: 1-6.
Casson M., 2009. The efficiency of the Victorian British railway network: A counterfactual analysis. Networks and Spatial Economics, 9(3): 339-378. DOI: https://www.doi.org/10.1007/s11067-008-9064-9
Codd E., 1968. Cellular automata. Academic Press, New York.
Couclelis H., 1997. From cellular automata to urban models. Environment and Planning B, 24: 165-174. DOI: https://www.doi.org/10.1068/b240165
Dobson J.E., Fisher P.F., 2003. Geoslavery. IEEE Technology and Society Magazine, Spring: 47-52. DOI: https://www.doi.org/10.1109/MTAS.2003.1188276
Eagle N., Pentland A. & Lazer D., 2009. Inferring friendship network structure by using mobile phone data. PNAS, 9(36): 15274-15278. DOI: https://www.doi.org/10.1073/pnas.0900282106274124119706491
Elhorst J.P., 2010. Applied spatial econometrics: Raising the bar. Spatial Economic Analysis, 5(1): 10-28. DOI: https://www.doi.org/10.1080/17421770903541772
Erdős P. & Rényi A., 1959. On random graphs. Publicationes Mathematicae, 6: 290-297.
ESRI, 2010. ESRI press release. Retrieved from http://www.esri.com/
Feynman R., 1960. There is plenty of room at the bottom. Engineering and Science, 23(5): 22-36.
Fischer M.M., Reismann M. & Scherngell T., 2010. Spatial interaction and spatial autocorrelation. In: Anselin L. & Rey S.J. (eds), Perspectives on spatial data analysis. Springer-Verlag, Berlin: 61-82. DOI: https://www.doi.org/10.1007/978-3-642-01976-0_5
Fotheringham A.S., Brunsdon C. & Charlton M., 2002. Geographically weighted regression. John Wiley, Chichester, UK.
Frenken K. (ed.), 2007. Applied evolutionary economics and economic geography. Edward Elgar, Cheltenham. DOI: https://www.doi.org/10.4337/9781847205391
Georgescu-Roegen N., 1971. The entropy law and the economic process. Harvard University Press, Cambridge, MA. DOI: https://www.doi.org/10.4159/harvard.9780674281653
Gibson J., 1979. The ecological approach to visual perception. Houghton Mifflin, Boston MA.
Gonzalez M.C., Hidalgo C.A. & Barabási A.L., 2008. Understanding individual human mobility patterns. Nature, 453: 779-782. DOI: https://www.doi.org/10.1038/nature0695818528393
Gorman S.P. & Kulkarni R., 2004. Spatial small worlds. Environment and Planning, B, 31(2): 273-296. DOI: https://www.doi.org/10.1068/b29118
Goss J., 1995. We know who you are and we know where you live. Economic Geography, 71(2): 171-198. DOI: https://www.doi.org/10.2307/144357
Gough I., Runciman G., Mace R., Hodgson G. & Rustin M., 2008. Darwinian evolutionary theory and the social sciences. 21st Century Society, 3(1): 65-86. DOI: https://www.doi.org/10.1080/17450140701780218
Hägerstrand T., 1970. What about people in regional science? Papers of the Regional Science Association, 24: 7-21. DOI: https://www.doi.org/10.1007/BF01936872
Haining R.P., Kerry R. & Oliver M.A., 2010. Geography, spatial data analysis and geostatistics: An overview. Geographical Analysis, 42(1): 7-31. DOI: https://www.doi.org/10.1111/j.1538-4632.2009.00780.x
Jiang B. & Yao X., 2006. Location-based services and GIS in perspective. Computers, Environment and Urban Systems, 30: 712-725. DOI: https://www.doi.org/10.1016/j.compenvurbsys.2006.02.003
Kaldor N., 1985. Economics without equilibrium. University College Cardiff Press, Cardiff.
Kohonen T., 2000. Self-organising maps. Springer-Verlag, New York. DOI: https://www.doi.org/10.1007/978-3-642-56927-2
Krugman P.R., 1991. Increasing returns and economic geography. Journal of Political Economy, 99(3): 483-499. DOI: https://www.doi.org/10.1086/261763
Kulkarni R., Schintler L.A., Stough R.R. & Button K., 2002. A Kohonen self-organizing map approach to modeling growth pole dynamics. Networks and Spatial Economics, 2: 175-189. DOI: https://www.doi.org/10.1023/A:1015317329803
Kumar K. & Lu Y., 2010. Cloud computing for mobile users: Can offloading computation save energy? Search, 43(4): 51-56. DOI: https://www.doi.org/10.1109/MC.2010.98
Lambooy J.G. & Boschma R.A., 2001. Evolutionary economics and regional policy. Annals of Regional Science, 35: 113-131. DOI: https://www.doi.org/10.1007/s001680000033
Lazer D., Pentland A., Adamic L., Aral S., Barabási A.L., Brewer D., Christakis N., Contractor N., Fowler J., Gutmann M., Jebara T., King G., Macy M., Roy D. & Alstyne M. van, 2009. Computational social science. Science, 323: 721-724. DOI: https://www.doi.org/10.1126/science.1167742274521719197046
LeSage J.P. & Pace R.K., 2009. Introduction to spatial econometrics. Taylor and Francis, Boca Raton. DOI: https://www.doi.org/10.1201/9781420064254
Maggioni M.A., 2002. Clustering dynamics and the location of high-tech firms. Springer, Heidelberg. DOI: https://www.doi.org/10.1007/978-3-642-57480-1
Marshall A., 1898. Principles of economics. MacMillan, London.
McGeachie M. & Doyle J., 2002. Efficient utility functions for ceteris paribus preferences. American Association for Artificial Intelligence: 279-284.
Medda F., Nijkamp P & Rietveld P., 2009. Dynamic effects of private costs on urban shape. In: Reggiani A. & Nijkamp P. (eds), Complexity and spatial networks. Springer-Verlag, Berlin: 51-60. DOI: https://www.doi.org/10.1007/978-3-642-01554-0_4
Nelson R. & Winter S., 1982. An evolutionary theory of economic change. Harvard University Press, Cambridge, MA.
Nijkamp P., 2007. Ceteris paribus, spatial complexity and spatial equilibrium - an interpretative perspective. Regional Science and Urban Economics, 37: 509-516. DOI: https://www.doi.org/10.1016/j.regsciurbeco.2007.04.006
Pagliara F. & Timmermans H.J.P., 2009. Choice set generations in spatial contexts. In: Bavaud F. & Mager C. (eds), Handbook of theoretical and quantitative geography. UNIL, Lausanne: 335-364.
Patuelli R., Griffith D.A., Tiefelsdorf M. & Nijkamp P., 2010. Spatial filtering methods for tracing space-time developments in an open regional system. In: Frenckel A., McCann Ph. & Nijkamp P. (eds), Societies in motion. Edward Elgar, Cheltenham (forthcoming).
Penn D.J., 2003. The evolutionary roots of our environmental problems: Towards a Darwinian ecology. The Quarterly Review of Biology, 78(3): 275-301. DOI: https://www.doi.org/10.1086/37705114528621
Persky J., 1990. Retrospectives: Ceteris paribus. Journal of Economic Perspectives, 4(2): 187-193. DOI: https://www.doi.org/10.1257/jep.4.2.187
Portugali J., 2000. Self-organization and the city. Springer-Verlag, Berlin. DOI: https://www.doi.org/10.1007/978-3-662-04099-7
Portugali J., 2004. Toward a cognitive approach to urban dynamics. Environment and Planning, B, 31: 598-613. DOI: https://www.doi.org/10.1068/b3033
Portugali J. (ed.), 2006. Complex artificial environments. Springer-Verlag, Berlin. DOI: https://www.doi.org/10.1007/3-540-29710-3
Portugali J., 2008. Learning from paradoxes about predictions in self-organizing cities. Planning Theory, 7: 248-262. DOI: https://www.doi.org/10.1177/1473095208094823
Pred A., 1977. The choreography of existence. Economic Geography, 53: 207-221. DOI: https://www.doi.org/10.2307/142726
Raubal M., Miller H. & Bridwell S., 2004. User centered time geography for location-based services. Geografiska Annaler, B, 86(4): 245-265. DOI: https://www.doi.org/10.1111/j.0435-3684.2004.00166.x
Reades J., Calabrese F. & Ratti C., 2009. Eigenplaces: Analyzing cities using the space-time structure of the mobile phone network. Environment and Planning, B, 36: 824-836. DOI: https://www.doi.org/10.1068/b34133t
Reades J., Calabrese F., Sevtsuk A. & Ratti C., 2007. Cellular census: Explorations in urban data collection. IEEE Pervasive Computing, 6(3): 30-38. DOI: https://www.doi.org/10.1109/MPRV.2007.53
Reggiani A. & Nijkamp P. (eds), 2009. Complexity and spatial networks. Springer-Verlag, Berlin. DOI: https://www.doi.org/10.1007/978-3-642-01554-0
Reggiani A. & Nijkamp P., 2010. Connectivity and concentration in airline networks. European Journal of Information Systems, March: 1-13.
Rozenblat C. & Melançon G., 2009. A small world perspective on urban systems. In: Bavaud F. & Mager C. (eds), Handbook of theoretical and quantitative geography. UNIL, Lausanne: 431-457.
Safarzynska K., 2010. Evolutionary modelling of transitions to sustainable development. PhD thesis, VU University, Amsterdam.
Shiode N., Li C., Batty M., Longley P. & Maguire D., 2002. Digital cities: Impacts and penetration of location- based services. University College, London. UCL Working Papers.
Simon H., 1962. The architecture of complexity. Proceedings of the American Philosophical Society, 106(6): 467-482.
Stam E., 2006. A process model of locational change: implications for an evolutionary economic geography. In: Pyka A. & Hanusch H. (eds), Applied evolutionary economics and the knowledge-based economy. Edward Elgar, Cheltenham: 143-165.
Steenbruggen J., Borzacchiello M.T., Nijkamp P. & Scholten H., 2010. Real-time data from mobile phone networks for traffic management. Research memorandum 2010-3. Dept. of Spatial Economics, VU University, Amsterdam.
Storper M., 1997. The regional world. Territorial development in a global economy. Guilford Press, London.
Sui D.Z., 2004. GIS, Cartography and the ‘Third Culture’: Geographic imaginations in the computer age. The Professional Geographer, 56(1): 62-72.
Tobler W., 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography, 46(2): 234-240. DOI: https://www.doi.org/10.2307/143141
Tobler W., 2004. On the first law of geography: A reply. Annals of the Association of American Geographers, 94(2): 304-310. DOI: https://www.doi.org/10.1111/j.1467-8306.2004.09402009.x
Tranos E., 2010. The geography of the Internet infrastructure in Europe. PhD thesis, Newcastle University, Newcastle.
Warf B. (ed.), 2006. Encyclopedia of human geography. Sage, Thousand Oaks, CA. DOI: https://www.doi.org/10.4135/9781412952422
Watts D.J. & Strogatz S.H., 1998. Collective dynamics of ‘small-world’ networks. Nature, 393: 440-442. DOI: https://www.doi.org/10.1038/309189623998
Wilson A.G., 2009. The thermodynamics of the city. In: Reggiani A. & Nijkamp P. (eds), Complexity and spatial networks. Springer-Verlag, Berlin: 11-31. DOI: https://www.doi.org/10.1007/978-3-642-01554-0_2
Yu H. & Shaw S., 2008. Exploring potential human activities in physical and virtual spaces: A spatio-temporal GIS approach. International Journal of Geographical Information Science, 22(4): 409-430. DOI: https://www.doi.org/10.1080/13658810701427569
License
This content is open access.