Market potential for smart growth neighbourhoods in the USA: A latent class analysis on heterogeneous preference and choice

With data from a 2011 National Association of Realtors community preference survey, we examined individuals’ preferences and the resulting market potential for smart growth neighbourhoods in the USA. Using a latent class choice model, we discovered four classes of individuals that reveal distinctive behaviours when choosing smart growth neighbourhoods, based on the interplay between aspects of community design, socioeconomic characteristics and personal attitudes. Based on these results we estimated the demand for smart growth neighbourhoods given the way they are planned and built. By linking the results of the latent class choice to a market diffusion model we were able to evaluate the effectiveness of a proposed smart growth neighbourhood design in inducing less sprawling development.

[1]  Jay Magidson,et al.  A nontechnical introduction to latent class models , 2005 .

[2]  J. Vermunt,et al.  Technical Guide for Latent GOLD Choice 4 . 0 : Basic and Advanced 1 , 2006 .

[3]  P. Doyle,et al.  Random utility models in marketing research: a survey , 2001 .

[4]  M. Batty,et al.  Simulating Emergent Urban Form Using Agent-Based Modeling: Desakota in the Suzhou-Wuxian Region in China , 2007 .

[5]  Daniel J. Phaneuf,et al.  Combining Revealed and Stated Preference Data to Estimate Preferences for Residential Amenities: A GMM Approach , 2012, Land Economics.

[6]  Zhongming Lu,et al.  Use of impact fees to incentivize low-impact development and promote compact growth. , 2013, Environmental science & technology.

[7]  D. McFadden The Choice Theory Approach to Market Research , 1986 .

[8]  Trine Kjær,et al.  A review of the discrete choice experiment - with emphasis on its application in health care , 2005 .

[9]  D. Olaru,et al.  Residential location and transit-oriented development in a new rail corridor , 2011 .

[10]  Steven Farber,et al.  Compact development and preference heterogeneity in residential location choice behaviour: A latent class analysis , 2015 .

[11]  Todd Litman Where We Want To Be: Home Location Preferences And Their Implications For Smart Growth , 2009 .

[12]  J. Levine,et al.  A Choice-Based Rationale for Land Use and Transportation Alternatives , 2005 .

[13]  Wolfgang Rid,et al.  Stated Preferences for Sustainable Housing Development in Germany—A Latent Class Analysis , 2011 .

[14]  Sigal Kaplan,et al.  Residential location choice of knowledge-workers: The role of amenities, workplace and lifestyle , 2013 .

[15]  Xiaoning Zhu,et al.  Cross-nested logit model for the joint choice of residential location, travel mode, and departure time , 2013 .

[16]  H. Martins,et al.  Urban compaction or dispersion? An air quality modelling study , 2012 .

[17]  Frank Southworth,et al.  Mitigating Climate Change through Green Buildings and Smart Growth , 2008 .

[18]  P. Boxall,et al.  Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach , 2002 .

[19]  Fuzhan Nasiri,et al.  A system dynamics approach for urban water reuse planning: a case study from the Great Lakes region , 2012, Stochastic Environmental Research and Risk Assessment.

[20]  Joan L. Walker,et al.  Latent lifestyle preferences and household location decisions , 2007, J. Geogr. Syst..

[21]  Phoebe Koundouri,et al.  Using a choice experiment to account for preference heterogeneity in wetland attributes: The case of Cheimaditida wetland in Greece , 2006 .

[22]  David Hoyos,et al.  The state of the art of environmental valuation with discrete choice experiments , 2010 .

[23]  R. Ewing Is Los Angeles-Style Sprawl Desirable? , 1997 .

[24]  Fiona Bull,et al.  The influence of urban design on neighbourhood walking following residential relocation: longitudinal results from the RESIDE study. , 2013, Social science & medicine.

[25]  M. Horner,et al.  Life Cycle and Environmental Factors in Selecting Residential and Job Locations , 2005 .

[26]  Paul Waddell,et al.  Residential mobility and location choice: a nested logit model with sampling of alternatives , 2010 .

[27]  H. Frumkin,et al.  Urban Form and Extreme Heat Events: Are Sprawling Cities More Vulnerable to Climate Change Than Compact Cities? , 2010, Environmental health perspectives.

[28]  Katherine A. Kiel,et al.  Location, Location, Location: The 3L Approach to House Price Determination , 2008 .

[29]  Reid Ewing,et al.  Travel and the Built Environment , 2010 .

[30]  Alan Borning,et al.  Microsimulation of Urban Development and Location Choices: Design and Implementation of UrbanSim , 2003 .

[31]  Michael P. Johnson Environmental Impacts of Urban Sprawl: A Survey of the Literature and Proposed Research Agenda , 2001 .

[32]  Jae Hong Kim Linking Land Use Planning and Regulation to Economic Development: A Literature Review , 2011 .

[33]  Shlomo Bekhor,et al.  GEV-based destination choice models that account for unobserved similarities among alternatives , 2008 .

[34]  J. Louviere,et al.  Tasmanian landowner preferences for conservation incentive programs: a latent class approach. , 2011, Journal of environmental management.

[35]  George A. Gonzalez Urban Sprawl, Global Warming and the Limits of Ecological Modernisation , 2005 .

[36]  David A. Hensher,et al.  A latent class model for discrete choice analysis: contrasts with mixed logit , 2003 .

[37]  D. Olaru,et al.  Lifecycle Stages and Residential Location Choice in the Presence of Latent Preference Heterogeneity , 2013 .

[38]  Anne van der Veen,et al.  Agent-Based Urban Land Markets: Agent's Pricing Behavior, Land Prices and Urban Land Use Change , 2009, J. Artif. Soc. Soc. Simul..

[39]  M. Baldassare,et al.  The Complexity of Public Attitudes Toward Compact Development , 2010 .