The decline of the downtown has been observed in many cities across the world. In response, many small cities in Japan, for example, have been making regeneration efforts including development controls on large-scale shopping centers. It is extremely useful to analyze the potential effects of relevant planning policies before implementation. We developed an urban planning support tool, a multiagent simulation (MAS) model called Shopsim-MAS, to investigate the impacts of some downtown revitalization policies through consequent spatial dynamics of shop market shares. We discuss methods to model household behavior and to understand the market area dynamics of shops. The Shopsim-MAS model developed in this project has proven to be a useful means to analyze the impact of downtown revitalization policies in Japan. It is also expected to be further expanded for impact analysis of similar or more sophisticated urban policies in other parts of the world.
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References
1.
AndoYYokotaKYoshikawaY, 2005, “Urban simulation by a multi agent system considering emergence and agglomeration of vacant buildings in urban decline process and effect of empty space on commerce”Journal of the City Planning Institute of Japan40(1) 52–59 (in Japanese)
2.
ArentzeT ATimmermansH J P, 2004, “A micro-simulator of urban land use dynamics integrating a multi-agent model of land development and an activity-based model of transport demand”, in Proceedings of the 83rd Annual Meeting of the Transportation Research Board 11–15 January, Washington, DC
3.
ArentzeT AOpewalHTimmermansH J P, 2005, “A multipurpose shopping trip model to assess retail agglomeration effects”Journal of Marketing Research42109–115
4.
BaltasGDoyleP, 2001, “Random utility models in marketing research: a survey”Journal of Business Research51115–125
5.
BenatiSHanseP, 2002, “The maximum capture problem with random utilities: problem formulation and algorithms”European Journal of Operational Research143518–530
6.
BenensonI, 1998, “Multi-agent simulations of residential dynamics in the city”Computer, Environment and Urban Systems22(1) 25–42
7.
BoxallP CAdamowiczW L, 2002, “Understanding heterogeneous preferences in random utility models: a latent class approach”Environmental and Resource Economics23421–446
8.
BruecknerJ KThisseJ FZenouY, 1999, “Why is central Paris rich and downtown Detroit poor? An amenity-based theory”European Economic Review4391–107
9.
CascettaEPapolaA, 2001, “Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand”Transportation Research Part C: Emerging Technologies9249–263
10.
CascettaERussoFViolaF AVitettaA, 2002, “A model of route perception in urban road networks”Transportation Research Part B: Methodological36577–592
11.
ChabrolMSarramiaDTchernevN, 2006, “Urban traffic systems modelling methodology”International Journal of Production Economics99 (1–2) 156–176
12.
DomencichTMcFaddenD L, 1975Urban Travel Demand: A Behavioral Analysis (North-Holland, Amsterdam)
13.
FotheringhamA SBrunsdonCCharltonM, 2000Quantitative Geography: Perspectives on Spatial Data Analysis (Sage, London)
14.
FrewJ R, 1990, “The effects of zoning on population and employment density”Journal of Real Estate Finance and Economics3155–163
15.
HanaokaKKondoAHiroseYHagiokaJ, 2000, “Gaps between consumers and store managers in evaluation of shopping complexes”Journal of the City Planning Institute of Japan35157–162 (in Japanese)
16.
KidaniHKawakamiM, 1996, “Actual condition and planning theme of building activity in urbanization control area”Journal of the City Planning Institute of Japan31583–588
17.
KiiMDoiK, 2005, “Multi-agent land-use and transport model for the policy evaluation of a compact city”Environment and Planning B: Planning and Design32485–504
18.
LiXLiuX, 2008, “Embedding sustainable development strategies in agent-based models for use as a planning tool”International Journal of Geographical Information Science22(1) 21–45
19.
LijesenM G, 2006, “A mixed logit based valuation of frequency in civil aviation from SP-data”Transportation Research Part E: Logistics and Transportation Review4282–94
20.
LoiblWToetzerT, 2003, “Modelling growth and densification process in suburb regions: simulations of landscape transition with spatial agents”Environmental Modelling and Software18553–563
21.
MarleyA A J, 2002, “Random utility models and their applications: recent developments”Mathematical Social Sciences43289–302
22.
MuromachiYHarataNOhtaK, 1990, “An impact analysis of a large-scale shopping center development in the metropolitan suburbs”Journal of the City Planning Institute of Japan25487–492 (in Japanese)
23.
NamatameA, 1998Multi-agents and Complex Theory (Morikita, Tokyo) (in Japanese)
24.
OrtúzarJ DWillumsenL G, 2001Modelling Transport3rd edition (John Wiley, New York)
25.
OutramV EThompsonE, 1978, “Driver route choice-behavioural and motivational studies”, in Proceedings 5th PTRC Summer Annual Meeting (PTRC, London) pp 114–121
26.
ProvencherBBishopR C, 2004, “Does accounting for preference heterogeneity improve the forecasting of a random utility model? A case study”Journal of Environmental Economics and Management48793–810
27.
SuárezAdel BosqueI RRodríguez-PooJ MMoralI, 2004, “Accounting for heterogeneity in shopping centre choice models”Journal of Retailing and Consumer Services11119–129
28.
SemboloniFAssfalgJArmeniSGianassiRMarsoniF, 2004, “CityDev, an interactive multi-agents urban model on the web”Computers, Environment and Urban Systems2845–64
29.
VeldhuisenK JTimmermansH J PKapoenL L, 2000, “Microsimulation model of activity — travel patterns and traffic flows: specification, validation tests, and Monte Carlo error”Transportation Research Recordnumber 1706, 126–135
30.
WilsonA G, 1967, “A statistical theory of spatial distribution models”Transportation Research1253–269
31.
WilsonA G, 1971, “A family of spatial interaction models and associated developments”Environment and Planning A31–32
