The Relation Between Residential Self-Selection and Urban Mobility in Middle Eastern Cities: the Case of Alexandria, Egypt

Abstract

The present paper attempts to fill a part of the gap in the studies on residential location choices and their relations to urban mobility, socio-economics, and the built environment by presenting the results of a study on Alexandria, Egypt, by analysing the results of a survey in eight neighbourhoods undertaken in 2015. Four questions were answered in this study: (i) “How are the main drivers behind residential location choices in Alexandria connected to various socio-demographic groups or people with different availability to urban and built environments?”, (ii) “How are the main residential self-selections in Alexandria associated with one another and which are the most important?”, (iii) “How are the housing location-related decisions of Egyptians similar to or different from international decisions?”, and (iv) “How can planners and decision-makers use the knowledge produced by this study for urban planning and housing in Egypt?”. Library work and the results of a Χ2 test of independence show that availability of transportation modes, nice neighbourhoods, and affordability are the strongest motives behind decisions. However, socio-economic factors are generally stronger than urban mobility and spatial issues. These findings are partly different from those of high-income countries.

Relationship of Residential Location Choice with Commute Travels and Socioeconomics in the Small Towns of South Asia: The Case of Hafizabad, Pakistan

“…In the absence of sufficient social safety nets for the masses, owning a house is generally an asset accumulation strategy of the people, which gives them a feeling of security and protection in times of need. Another study also found owner-occupation of housing units in the shape of family assets as determinants of residential location choices in Alexandria, Egypt [29]. However, this finding has not surfaced as such for the cases of developed countries where the ratio of owner-occupied housing units was found less than many developing countries.…”

“…This reflects the dominantly patriarchal character of Pakistani society, where male heads of the households make the key decisions [53]. A study found gender to be a significant factor of residential location choices in Alexandria, Egypt [29]. In Nigeria, a study found low involvement of women in deciding residential locations [31].…”

“…Masoumi (2013) also found a significant role of socioeconomics in determining the residential location choices in Tehran, Iran [28]. In another study conducted in Alexandria, Masoumi et al (2021) identified neighborhood characteristics, availability of transportation modes, and affordability as the strongest determinants of the residential location choices [29]. Ibrahim (2017) also found the availability of transportation modes as the leading determinant of the residential location choices in Alexandria [30].…”

Residential Location Choice in Istanbul, Tehran, and Cairo: The Importance of Commuting to Work

“…There are very limited studies on this region; e.g., we already know that in Iran socioeconomic factors might play a stronger role in defining residential location choices compared to mobility needs [15]. In Alexandria, Egypt, availability of transportation modes, "nice neighborhoods", and affordability are the strongest motives behind location decisions [16]. Similar to Iran, in Alexandria, socio-economic factors are generally stronger than urban mobility and spatial issues.…”

“…From a methodological point of view, the studies on the MENA region have rarely applied Geographical Information Systems (GIS) to quantify land use in the disaggregate data. Most of the studies on the region have utilized statistical analysis methods determining either aggregate or disaggregate data, but they are limited by the data derived from questionnaires e.g., [15][16][17]. An exception is, e.g., the work of Mehriar et al (2020), who quantified the street network configuration and connectivity and brought the related variables into their models [18].…”