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Residential Satisfaction as an Intervening Variable in Residential Mobility
Abstract
The stress-threshold model (Wolpert, 1965; Brown and Moore, 1970) assumes that people do not consider moving unless they experience residential stress. This paper develops a similar model of residential mobility in which residential satisfaction acts as an intervening variable between individual and residence variables and mobility. The model is tested with data from a panel study of Rhode Island residents. The results indicate that residential satisfaction at the first interview is related to the wish to move and to mobility in the year following the interview. Individual and residence characteristics such as age of head duration of residence, home ownership, and room crowding are shown to affect mobility through their effect on residential satisfaction.
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Cites
Lee, E. S. (1966) · Demography · doi:10.2307/2060063 · Cited by 4,535
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Environmental dimensions of migration
Hunter, L. M., Luna, J. K., & Norton, R. M. (2015) · Annual Review of Sociology · doi:10.1146/annurev-soc-073014-112223 · Cited by 449
Conflict‐Induced Displacement, Understanding the Causes of Flight
Adhikari, P. (2013) · American Journal of Political Science · doi:10.1111/j.1540-5907.2012.00598.x · Cited by 221
Rosenblatt, P., & DeLuca, S. (2012) · City & Community · doi:10.1111/j.1540-6040.2012.01413.x · Cited by 153
Koubi, V., Spilker, G., Schaffer, L., & Böhmelt, T. (2016) · Population and Environment · doi:10.1007/s11111-016-0258-7 · Cited by 125
Metadata
- Authors
- Speare, A.
- Venue
- Demography
- Publisher
- Duke University Press
- Published
- 1974-05-01
- Volume
- 11
- Issue
- 2
- Pages
- 173-188
- ISSN
- 0070-3370 (ISSN-L)
- 1533-7790
- OpenAlex
- W2086662293
- Cited by
- 736
- References
- 1
- FWCI
- 29.02
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
