Operationalizing the concept of neighborhood: Application to residential location choice analysis

Abstract

In this paper, we explore different conceptualizations to represent neighborhoods in residential location choice models, and describe three alternative ways for constructing operational units to represent neighborhoods. In particular, we examine the possibility of using the census units to represent the hierarchical ‘fixed neighborhood’ definition, and the circular units and network bands to represent the hierarchical ‘sliding neighborhood’ definition. Overall, the network band definition is conceptually appealing. It also is marginally superior to the other two operational representations from a model fit standpoint.

Introduction

In the literature relating to urban planning and travel behavior modeling, ‘neighborhood’ is a widely used and important term. Studies of the housing market investigate what kind of people live in what kind of neighborhoods (Hunt et al., 1994). Research work on the land-use/transportation interaction frequently use neighborhood as a synonym for built environment or land-use. In particular, advocates and skeptics of the ‘New Urbanism’ concept talk about whether neighborhood design and other characteristics can affect various aspects of travel behavior (Ewing and Cervero, 2001).

Obviously, any study about neighborhoods is a spatial investigation. Yet, the spatial definition of neighborhood has received very little attention in the literature. Theoretical studies of neighborhood effects often use the term neighborhood rather loosely. For instance, New Urbanism designs tend to focus on the microscale of 400 m (one-quarter mile) or less. Yet it is not clear on an a priori basis whether residential and travel choice behavior is influenced by the urban form within small neighborhoods, or over larger areas, or both. On the other hand, empirical studies of neighborhood effects across many disciplines typically use census tracts, zip code areas, or transport analysis zones (TAZ) as operational surrogates for neighborhoods (Sampson et al., 2002, Dietz, 2002). This use of administrative boundaries as operational units typically has little theoretical foundation and subjects the analysis to the modifiable areal unit problem (MAUP) (Openshaw, 1984), leading to potentially inaccurate analytic outcomes and erroneous recommendations for urban policy (see, for example, Fotheringham and Wong, 1991, Guo and Bhat, 2004, for more detailed discussions of the MAUP).

So how do we define neighborhoods? Or, how do we measure neighborhood characteristics and the associated effects? Our simple answer is that we should measure what matters to people over the area that really matters to people. For example, in the study of residential location choice, a common hypothesis is that good access to stores is an attractive neighborhood feature. When examining such a hypothesis, if we define a neighborhood over too large an area, any spatially concentrated commercial activities would likely be averaged out with surrounding low-density patterns. Consequently, it would be difficult to associate the commercial intensity with the choice behavior being studied. Alternatively, if we arbitrarily define a neighborhood to exclude a commercial center that is in fact easily accessible for a given household, it would again be difficult to account for the presence of the commercial center in explaining the residential location choice of that household. Therefore, only when the chosen definition reflects the decision makers’ perceived neighborhoods can we accurately study the effect of neighborhoods.

The objective of this paper is to clarify what we, as decision makers and as analysts, mean by neighborhood and to develop ways of operationalizing the concept of neighborhood. With residential location choice as the application context, we expand on an earlier work (Guo and Bhat, 2004) that proposed a hierarchical spatial representation of neighborhoods to examine neighborhood effects. Our previous study showed the superiority of the hierarchical, multi-scale, approach over the conventional, single-scale, approach to accommodate the effect of built form, land-use, and other neighborhood attributes. However, the challenge remains regarding how to exploit the flexibility of using analyst-defined spatial units to appropriately identify the impacts of neighborhood factors. In this paper, we specifically examine three alternative sets of operational units for neighborhood definition and embed these spatial representations to study the effects of neighborhood factors on households’ residential location choices. Our results demonstrate the feasibility of using these operational units of neighborhood, the sensitivity of modeling outcomes to the choice of spatial units, and the strengths and limitations of the alternative units.

The remainder of this paper is structured as follows. The next section discusses the concept of neighborhood, as used in earlier studies. Section 3 provides a background for residential location choice analysis and discusses the methodological shortcomings in the conventional approach with regard to the definition of neighborhood. Section 4 briefly reviews the hierarchical approach proposed in Guo and Bhat (2004) for representing neighborhoods in residential location choice analysis. Section 5 discusses three different ways to operationalize the concept of hierarchical neighborhoods. An empirical application of the three ways of representing neighborhoods is described in Section 6. Finally, Section 7 concludes with a summary of the contribution of the study.