Investigating the Socioeconomic Factors Influencing Households’ Residential Location Choice Using Multinomial Logit Analysis

Abstract

: Increasing amounts of literature have been published recently on the factors that influence household residential location decisions. These factors include transportation accessibility, physical and environmental aspects of neighborhoods, household socioeconomic characteristics, and others. However, few research has looked at how the attributes of a housing location influence households’ choices. As a result, the primary goal of this study is to examine the influencing factors for households’ residential location choices. This has been achieved by developing a discrete choice analysis that utilizes a multinomial logit model, using state-wide data from the National Household Travel Survey (NHTS). The key findings of this study reveal that the most influential factors include; household income, race, household size, number of vehicles in the household, type of housing, and the household structure. The critical factors linked with high-income groups include access to school, proximity to work, and closeness to friends and family. Similarly, when it comes to race, there is a significant disparity between different races. White people, for instance, are more likely to choose their residential locations based on the size and quality of the property. On the other hand, the number of adults in the household correlates with the convenience to work. When the size of the household grows, it is more likely that they will choose their home location depending on whether or not they have friends and family in the new area. In terms of housing types, people who live in a house are more likely to choose their home location based on the size and quality of the property. Apartment dwellers, on the other hand, tend to be more related to different criteria, such as housing cost and neighborhood quality. These findings have several meaningful implications for housing professionals and urban planners to predict how the growth and development of a city will occur. Moreover, it will help to fully understand the significant factors affecting people’s behavior when choosing their residential locations.