Savasdisara, Tongchai et alli. ‘Residential Mobility in Private Lower-Cost Housing in Bangkok’, in Housing Studies, Vol. 3, No. 4, pp. 250-258.
Summary:
This is essentially a research survey conducted of 13 districts, 20 settlements and 1100 households in Bangkok regarding residential mobility and satisfaction levels in regards to private housing estates in the city; the aim was to balance the existing research on government initiated development (mostly by Western organisations) which essentially analyse the government’s response as opposed to residents’ perspectives. The result of the research study culminated in the creation of a model for low-income countries to explain residential mobility in regards to home ownership and resident satisfaction, in terms of individual dwelling units, estate environment, and the age of the household head.
Notes from the text:
The most influential factors of residents’ satisfaction comprise:
- Physical and environmental aspects of the neighbourhood (public facilities and infrastructure i.e. playgrounds, parks, roads, sidewalk, streetlights at night, waste disposal and collection)
- Quality of dwelling units (number and size of rooms, kitchen and toilet, washing areas, natural light and ventilation)
- Environmental and location (accessibility to work, healthcare, school, shops and markets)
- Social relations (friends and neighbours) – the most powerful factor
The author refers to residential mobility in terms of moving out from the current housing estate.
- Background: socio-economic and attributes of residents & physical and environmental characteristics of neighbourhoods
- Dependent: planning-to-move
- Intervening: residents’ satisfaction
The primary requirements for moving to new estates are improvements and provision of essential services.
Previous studies on government housing assessed the roles of the Government and the NHA: “Early highly subsidised government housing projects have proved inefficient and expensive for government” (p 251).
The most important reasons for loving out of existing estates were either related to social ties or LAND OWNERSHIP.
Even though previous models for analysing residential mobility were conceptualised in the US, they can still be used as basic guidelines.
Theoretical causes for migration:
- Lee (1966) – based on the DECISION-MAKING PROCESS; area of origin, area of destination, personal characteristics, intervening obstacles
Conceptual causes for migration:
- Simon (1957) – based on HUMAN DECISION-MAKING; capacity for formulate and solve problems, acquire and retain information, simplify situation and make a rational decision
Types of stimuli for planning-to-move:
- Rossi (1955) – relationship between housing and mobility; housing complaints, overcrowding, landlord problems, neighbourhood conditions
- Leslie and Richardson (1961) – “physical limitations combined with frustrated aspirations” (ibid)
Behavioural theory:
- Wolpert (1965) – “rational response to a wide range of socio-economic conditions” (ibid); negative and positive evaluations of current and prospective areas affect the decision to move
- Golant (1971) – three variables identified in Wolpert’s theory: environment, individual and interactions between environment and individuals, “When the stress reaches threshold strength, the individual acts” (p 252)
- Speare (1974) – set of background variables: friends and relative index, crowding ratio, age of household heads, duration of residence, property ownership, represent desire to move/stay; intervening variable: RESIDENTIAL SATISFACTION
- Bach and Smith (1977) – elaborated Speare’s model
The districts of the Greater Bangkok area were combined to create the sample area for the survey based the US models. The survey was undertaken between 22 March and 4 May 1986, of household heads who make the most of the decision-making and are family representatives, which meant only weekends were available.
Five factors (also referred to as indices in statistical terms) of housing satisfaction comprise:
- Location (accessibility to workplace, shops, markets, schools, public transport, telephone services, electricity, water and street lights at night)
- Dwelling unit (size and number of rooms, kitchen and laundry, bathroom, ventilation and brightness)
- Environment (noise from neighbours and local area, smoke and odours, cleanliness, roads and walkways, privacy, drainage systems and water supply)
- Public facilities (security and maintenance of estate, public parking, children’s playgrounds, recreational spaces, fire protection and safety)
- Neighbours (attitudes in regards to education, economic status and friendliness)
There were a lot of statistical terminologies including various variables, Lambda, Gamma and Pearson’s product moment correlation coefficients. Tables are used to describe the outcomes of the surveys in respect to these ‘coefficients’.
- Lambda coefficients are nominal measurements of two variables
- Gamma coefficients are measured ordinally
- Pearson’s product correlation coefficient measures intervals
The results comprised a casual model represented background variables, residential satisfaction and planning-to-move. These were outlined in three phases:
- Phase 1 Planning-to-move constraints: exogenous variables; background variables with important links with residential satisfaction and/or planning to move variables
- Phase 2 Residential satisfaction: intervening variable; impact on personal, household and socio-environmental factors, general residential satisfaction
- Phase 3 Planning to move: endogenous variable; two-step questions
Path analysis used in the analysis of causality, “to find out whether the background variables have direct planning-to-move or whether they affect planning-to-move indirectly through residential satisfaction” (p 255).
The most likely reason for moving out was home/property/land ownership as opposed to assumptions of residential satisfaction being the most influential factor. “The strongest influences on plans to move house relates to property ownership, followed by residential satisfaction itself… Suwannodom (1982) found land ownership to be a strong determinant” (p 257).
Mobility becomes more difficult with older age; it is easier when people are younger.
Combining the various regions in Thailand would be equivalent to the size of US city analysis using Western models.
Economic necessity is also quite influential in decision-making as it is important to consider the job opportunities with the home-to-work travel times (ibid).
Ultimately, “good designs may reduce discomforts with these issues even though the price of individual houses remains the same” (ibid).
Tags: Bangkok, Economics, Finance, Housing, Low-cost Housing, Mobility, Residential, Surveys