A Cross-Level Exploratory Analysis of “Neighborhood Effects” on Urban Behavior: An Evolutionary Perspective
MetadataShow full metadata
It is now generally accepted that spatially-based neighborhood or contextual attributes influence individual behaviors. However, studies of contextual effects often operationalize “neighborhoods” as static, single-level administrative units that are chosen for data availability rather than theoretical reasons. This practice has led to new calls for sound conceptual models that guide data collection efforts and statistical analyses related to these phenomena. While many such models are in use or being proposed in the social sciences, this article argues that research in the field of evolutionary studies offers alternative and interesting ways of investigating neighborhood effects. Accordingly, the article pursues two objectives. First, it makes connections between neighborhood effects research in the social sciences and relevant literature in evolutionary game theory and evolutionary urban geography. Second, these interdisciplinary interactions guide the development of a cross-level conceptual model of neighborhood effects on urban social behavior. The conceptual model is then translated into an empirical model that tests whether and how property maintenance behavior in a selected U.S. study area changes as a function of neighborhood context. The findings reveal that neighborhood effects operate at multiple, interacting spatial levels in the study area, which suggests that conventional single-level administrative boundaries are not equipped to capture these effects. While they are proffered as exploratory, the results nonetheless imply that insights from evolutionary research can add depth and theoretical grounding to contextual effects studies in the social sciences.
CitationWeaver, R. (2015). A cross-level exploratory analysis of “neighborhood effects” on urban behavior: An evolutionary perspective. Social Sciences, 4(4), pp. 1046-1066.
Rights Holder© 2015 The Authors.
This work is licensed under a Creative Commons Attribution 4.0 International License.