Elucidating the drivers of residential mobility and housing choice behaviour in a suburban township via push–pull–mooring framework

Abstract

This study applies the “push-pull-mooring” model of migration to explain home purchase intention in a suburban township. “Push” effects include dissatisfaction and high housing costs in one’s current neighbourhood (“the origin”). “Pull” effects were consumers’ perceived value of the suburban township (“the destination”), which encompassed price, functional, emotional, social, symbolic, and Feng Shui aspects. Relocation costs and alternative township’s attractiveness were hypothesized as “mooring” effects that negatively impact purchase intention as well as moderate the push and pull effects. 179 valid responses from prospective home buyers were analysed using partial least squares structural equation modelling (PLS-SEM). Pull effects were found to exert a positive influence while mooring and push effects exert a negative influence on purchase intention. Moderation effects of the mooring factors were found to be not significant in this context. This study offers several interesting implications for researchers and marketing practitioners in the real estate industry.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

References

  1. Adriaanse, C. C. M. (2007). Measuring residential satisfaction: A residential environmental satisfaction scale (RESS). Journal of Housing and the Built Environment,22(3), 287–304. https://doi.org/10.1007/s10901-007-9082-9.

    Article  Google Scholar 

  2. Alonso, W. (1964). Location and land use. Cambridge, MA: Harvard University Press.

    Google Scholar 

  3. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science,16(1), 74–94. https://doi.org/10.1007/BF02723327.

    Article  Google Scholar 

  4. Bansal, H. S. (2005). “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors. Journal of the Academy of Marketing Science,33(1), 96–115. https://doi.org/10.1177/0092070304267928.

    Article  Google Scholar 

  5. Bansal, H. S., Irving, P. G., & Taylor, S. F. (2004). A three-component model of customer commitment to service providers. Journal of the Academy of Marketing Science,32(3), 234–250. https://doi.org/10.1177/0092070304263332.

    Article  Google Scholar 

  6. Barreira, A. P., Nunes, L. C., Guimarães, M. H., & Panagopoulos, T. (2018). Satisfied but thinking about leaving: The reasons behind residential satisfaction and residential attractiveness in shrinking Portuguese cities. International Journal of Urban Sciences. https://doi.org/10.1080/12265934.2018.1447390.

    Article  Google Scholar 

  7. Bendapudi, N., & Berry, L. L. (1997). Customers’ motivations for maintaining relationship with service providers. Journal of Retailing,73(1), 15–37. https://doi.org/10.1016/S0022-4359(97)90013-0.

    Article  Google Scholar 

  8. Bryman, A., & Bell, E. (2011). Business Research methods (3rd ed.). New York: Oxford University Press.

    Google Scholar 

  9. Burgess, R., & Skeltys, N. (1992). Findings from the housing and location choice survey: An overview. (H. and U. D. D. & D. of H. H. and C. Services, Ed.). Australian Government Publishing Service.

  10. Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs: A typology, antecedents, and consequences. Journal of the Academy of Marketing Science,31(2), 109–126. https://doi.org/10.1177/0092070302250897.

    Article  Google Scholar 

  11. Chang, H. H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications,24(March), 50–67. https://doi.org/10.1016/j.elerap.2017.06.002.

    Article  Google Scholar 

  12. Cheah, S. L., Almeida, S., Shukri, M., & Lim, L. S. (2017). Imbalances in the property market. BNM Quarterly Bulletin (Third Quarter) (pp. 26–32).

  13. Cheah, J.-H., Memon, M. A., Chuah, F., Ting, H., & Ramayah, T. (2018). Asessing reflective models in marketing research: A comparison between PLS and PLSc. International Journal of Business and Society,19(1), 139–160.

    Google Scholar 

  14. Clark, W. A. V., & Onaka, J. (1983). Life cycle and housing adjustments as explanations of residential mobility. Urban Studies,20(1), 47–57.

    Article  Google Scholar 

  15. Costley, D. (2006). Master planned communities: Do they offer a solution to urban sprawl or a vehicle for seclusion of the more affluent consumers in Australia? Housing, Theory and Society,23(3), 157–175. https://doi.org/10.1080/14036090600862346.

    Article  Google Scholar 

  16. Duque-Calvache, R., Clark, W. A. V., & Palomares-Linares, I. (2017). How do neighbourhood perceptions interact with moving desires and intentions? Housing Studies,3037(November), 1–24. https://doi.org/10.1080/02673037.2017.1373748.

    Article  Google Scholar 

  17. Fang, Y. (2006). Residential satisfaction, moving intention and moving behaviours: A study of redeveloped neighbourhoods in inner-city Beijing. Housing Studies,21(5), 671–694. https://doi.org/10.1080/02673030600807217.

    Article  Google Scholar 

  18. Fischer, D. G., & Fick, C. (1993). Measuring social desirability: Short forms of the Marlowe-Crowne social desirability scale. Educational and Psychological Measurement,53(2), 417–424. https://doi.org/10.1177/0013164493053002011.

    Article  Google Scholar 

  19. Galster, G. (1987). Identifying the correlates of dwelling satisfaction: An empirical critique. Environment and Behavior, 19(5), 539–568. ISBN-10: 0803973233.

  20. Ghazali, E., Arnott, D., & Mutum, D. (2011). Conceptualising and measuring online switching costs. In Advances in Consumer Research—European Conference Proceedings (vol. 9, pp. 151–157). http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=77409956&site=ehost-live.

  21. Ghazali, E., Nguyen, B., Mutum, D. S., & Mohd-any, A. A. (2016). Constructing online switching barriers: Examining the effects of switching costs and alternative attractiveness on e-store loyalty in online pure-play retailers. Electronic Markets,26(2), 157–171. https://doi.org/10.1007/s12525-016-0218-1.

    Article  Google Scholar 

  22. Gram-Hanssen, K., & Bech-Danielsen, C. (2004). House, home and identity from a consumption perspective. Housing, Theory and Society,21(1), 17–26. https://doi.org/10.1080/14036090410025816.

    Article  Google Scholar 

  23. Hair, J. F. J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: SAGE Publications Inc.

    Google Scholar 

  24. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science,43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.

    Article  Google Scholar 

  25. Herrmann, A., Xia, L., Monroe, K. B., & Huber, F. (2007). The influence of price fairness on customer satisfaction: An empirical test in the context of automobile purchases. Journal of Product & Brand Management,16(1), 49–58. https://doi.org/10.1108/10610420710731151.

    Article  Google Scholar 

  26. Hou, A. C. Y., Chern, C. C., Chen, H. G., & Chen, Y. C. (2011). “Migrating to a new virtual world”: Exploring MMORPG switching through human migration theory. Computers in Human Behavior,27(5), 1892–1903. https://doi.org/10.1016/j.chb.2011.04.013.

    Article  Google Scholar 

  27. Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push-pull-mooring framework. Computers in Human Behavior,28(5), 1912–1920. https://doi.org/10.1016/j.chb.2012.05.010.

    Article  Google Scholar 

  28. Huang, X., Dijst, M., & van Weesep, J. (2018). Rural migrants’ residential mobility: Housing and locational outcomes of forced moves in China. Housing, Theory and Society,35(1), 113–136. https://doi.org/10.1080/14036096.2017.1329163.

    Article  Google Scholar 

  29. Ibem, E. O., Adeboye, A. B., Alagbe, O. A., & State, O. (2015). Similarities and differences in residents’ perception of housing. Journal of Building Performance,6(1), 1–14.

    Google Scholar 

  30. Jackson, J. (1986). Migration. New York: Longman.

    Google Scholar 

  31. Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research,30(2), 199–218. https://doi.org/10.1086/376806.

    Article  Google Scholar 

  32. Jim, C. Y., & Chen, W. Y. (2007). Consumption preferences and environmental externalities: A hedonic analysis of the housing market in Guangzhou. Geoforum,38(2), 414–431. https://doi.org/10.1016/j.geoforum.2006.10.002.

    Article  Google Scholar 

  33. Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of Retailing,76(2), 259–274. https://doi.org/10.1016/S0022-4359(00)00024-5.

    Article  Google Scholar 

  34. Jung, J., Han, H., & Oh, M. (2017a). Travelers’ switching behavior in the airline industry from the perspective of the push–pull–mooring framework. Tourism Management,59, 139–153. https://doi.org/10.1016/j.tourman.2016.07.018.

    Article  Google Scholar 

  35. Jung, J., Han, H., & Oh, M. (2017b). Travelers’ switching behavior in the airline industry from the perspective of the push–pull–mooring framework. Tourism Management,59, 139–153. https://doi.org/10.1016/j.tourman.2016.07.018.

    Article  Google Scholar 

  36. Karsten, L. (2007). Housing as a way of life : Towards an understanding of middle-class families’ preference for an urban residential location. Housing Studies,22(1), 83–98.

    Article  Google Scholar 

  37. Kauko, T. (2006). Expressions of housing consumer preferences: Proposition for a research agenda. Housing, Theory and Society,23(2), 92–108. https://doi.org/10.1080/14036090600773097.

    Article  Google Scholar 

  38. Keaveney, S. M. (1995). Customer switching behavior in service industries: An exploratory study. Journal of Marketing,59(2), 71. https://doi.org/10.2307/1252074.

    Article  Google Scholar 

  39. Lee, E. S. (1966). A theory of migration. Demography,3(1), 47. https://doi.org/10.2307/2060063.

    Article  Google Scholar 

  40. Lee, D. J., Yu, G. B., Merunka, D. R., Bosnjak, M., Sirgy, M. J., & Johar, J. S. (2015). Effect symmetry of benefit criteria in postpurchase evaluations. Psychology and Marketing,32(6), 651–669. https://doi.org/10.1002/mar.20807.

    Article  Google Scholar 

  41. Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology,86(1), 114–121. https://doi.org/10.1037//0021-9010.86.1.114.

    Article  Google Scholar 

  42. Longino, C. F. J. (1992). The forest and the trees: Micro-level considerations in the study of geographic mobility in old age. In A. Rogers (Ed.), Elderly migration and population redistribution (pp. 23–24). London: Bellhaven.

    Google Scholar 

  43. Marsh, A., & Gibb, K. (2011). Uncertainty, expectations and behavioural aspects of housing market choices. Housing, Theory and Society,28(3), 215–235. https://doi.org/10.1080/14036096.2011.599182.

    Article  Google Scholar 

  44. Mohit, M. A., Ibrahim, M., & Rashid, Y. R. (2010). Assessment of residential satisfaction in newly designed public low-cost housing in Kuala Lumpur, Malaysia. Habitat International,34(1), 18–27. https://doi.org/10.1016/j.habitatint.2009.04.002.

    Article  Google Scholar 

  45. Moon, B. (1995). Paradigms in migration research: Exploring ‘moorings’ as a schema. Progress in Human Geography,19(4), 504–524. https://doi.org/10.1177/030913259501900404.

    Article  Google Scholar 

  46. Mutum, D., Mohd Ghazali, E., Nguyen, B., & Arnott, D. (2014). Online loyalty and its interaction with switching barriers. Journal of Retailing and Consumer Services,21(6), 942–949. https://doi.org/10.1016/j.jretconser.2014.08.012.

    Article  Google Scholar 

  47. Olanrewaju, A., & Woon, T. C. (2017). An exploration of determinants of affardable housing choice. International Journal of Housing Markets and Analysis. https://doi.org/10.1108/IJHMA-11-2016-0074.

    Article  Google Scholar 

  48. Oliver, R. L., & Swan, J. E. (1989). Consumer perceptions of interpersonal equity and satisfaction in transactions: A field survey approach. Journal of Marketing,53(2), 21. https://doi.org/10.2307/1251411.

    Article  Google Scholar 

  49. Peng, X., Chris, Y., & Zhu, Q. (2016). Computers in human behavior investigating user switching intention for mobile instant messaging application : Taking WeChat as an example. Computers in Human Behavior,64, 206–216. https://doi.org/10.1016/j.chb.2016.06.054.

    Article  Google Scholar 

  50. Peng, Y.-S., Hsiung, H.-H., & Chen, K.-H. (2012). The level of concern about Feng Shui in house purchasing: The impacts of self-efficacy, superstition, and the big five personality traits. Psychology & Marketing,29(7), 519–530.

    Article  Google Scholar 

  51. Ravenstein, E. G. (1885). The laws of migration. Journal of the Royal Statistical Society of London,48(2), 167–235.

    Article  Google Scholar 

  52. Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2018). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management,5192(January), 1–27. https://doi.org/10.1080/09585192.2017.1416655.

    Article  Google Scholar 

  53. Ringle, C. M., Sarstedt, M., & Straub, D. (2012). A critical look at the use of PLS-SEM in MIS Quarterly. MIS Quarterly (MISQ),36(1), 3–14. https://doi.org/10.3200/JOEB.79.4.213-216.

    Article  Google Scholar 

  54. Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS. Boenningstedt, Germany: SmartPLS GmbH. Retrieved August 21, 2018 from http://www.smartpls.com.

  55. Sahari, Z. (2015). Limit urban sprawl. The Star Online. Retrieved January 3, 2019 from https://www.thestar.com.my/metro/views/2015/01/27/limit-urban-sprawl-time-to-start-greening-our-cities-for-the-future/.

  56. Sharma, N., & Patterson, P. G. (2000). Switching costs, alternative attractiveness and experience as moderators of relationship commitment in professional, consumer services. International Journal of Service Industry Management,11(5), 470–490. https://doi.org/10.1108/09564230010360182.

    Article  Google Scholar 

  57. Shen, J., & Wu, F. (2013). Moving to the suburbs: Demand-side driving forces of suburban growth in China. Environment and Planning A,45(8), 1823–1844. https://doi.org/10.1068/a45565.

    Article  Google Scholar 

  58. Sirgy, M. J., Grewal, D., Mangleburg, T. F., Park, J.-O., Chon, K.-S., Claiborne, C. B., et al. (1997). Assessing the predictive validity of two methods of measuring self-image congruence. Journal of the Academy of Marketing Science,25(3), 229–241. https://doi.org/10.1177/0092070397253004.

    Article  Google Scholar 

  59. Sirgy, M. Joseph, Grzeskowiak, S., & Su, C. (2005). Explaining housing preference and choice: The role of self-congruity and functional congruity. Journal of Housing and the Built Environment,20(4), 329–347. https://doi.org/10.1007/s10901-005-9020-7.

    Article  Google Scholar 

  60. Smetcoren, A. S., De Donder, L., Dury, S., De Witte, N., Kardol, T., & Verté, D. (2017). Refining the push and pull framework: Identifying inequalities in residential relocation among older adults. Ageing & Society,37(1), 90–112. https://doi.org/10.1017/S0144686X15001026.

    Article  Google Scholar 

  61. Soper, D. S. (2018). A priori sample size calculator for multiple regression [Software].

  62. Sun, S., & Manson, S. M. (2012). Intraurban migration, neighborhoods, and city structure. Urban Geography,33(7), 1008–1029. https://doi.org/10.2747/0272-3638.33.7.1008.

    Article  Google Scholar 

  63. Sweeney, J. C., & Soutar, G. N. (2001). Customer perceived value: The development of a multiple item scale. Pergamon,77(3), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0.

    Article  Google Scholar 

  64. Tehseen, S., Ramayah, T., & Sajilan, S. (2017). Testing and controlling for common method variance: A review of available methods. Journal of Management Sciences,4(2), 142–168. https://doi.org/10.20547/jms.2014.1704202.

    Article  Google Scholar 

  65. Vogt, C. A., & Marans, R. W. (2004). Natural resources and open space in the residential decision process: A study of recent movers to fringe counties in southeast Michigan. Landscape and Urban Planning,69(2–3), 255–269. https://doi.org/10.1016/j.landurbplan.2003.07.006.

    Article  Google Scholar 

  66. Voss, G. B., Parasuraman, A., & Grewal, D. (1998). The roles of price, performance, and expectations in determining satisfaction in service exchanges. Journal of Marketing,62(Oct), 46–61.

    Article  Google Scholar 

  67. Wong, E. (1996). Feng Shui: The ancient wisdom of harmonious living for modern times. Boston, MA: Shambhala Publications.

    Google Scholar 

  68. Wu, W. Y., Yau, O. H. M., & Lu, H.-Y. (2012). Feng Shui principles in residential housing selection. Psychology & Marketing,29(7), 502–518.

    Article  Google Scholar 

  69. Yang, Z., & Peterson, R. T. (2004). Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychology and Marketing,21(10), 799–822. https://doi.org/10.1002/mar.20030.

    Article  Google Scholar 

  70. Zeithaml, V. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing,52(3), 22. https://doi.org/10.2307/1251446.

    Article  Google Scholar 

Download references

Acknowledgements

This research was funded by the Research Management Unit, Faculty of Business and Accountancy, University of Malaya (Grant No. GPF017I-2018).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Ezlika M. Ghazali.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: Measurement instrument

Appendix: Measurement instrument

Constructs No. of items Items Measurement items Sources
Push effects: dissatisfaction with current housing situation
Housing attributes 8 HA1 Type of property Ibem et al. (2015)
Clark and Onaka (1983)
HA2 Built up area
HA3 Internal layout
HA4 External appearance/design
HA5 Number of bedrooms
HA6 Number of bathrooms
HA7 Natural lighting and ventilation
HA8 Level of privacy
HA9 Overall housing unit attributes
Neighbourhood attributes 5 NA1 Crime situation Mohit et al. (2010)
Duque-Calvache et al. (2017)
NA2 Security services
NA3 Noise level
NA4 Community relations
NA5 Cleanliness/general appearance
NA6 Overall neighbourhood environment
Price perception 6 PP1 The price of houses in my current neighbourhood is reasonable Chang et al. (2017)
Jung et al. (2017b)
Voss et al. (1998)
PP2 The price of houses in my current neighbourhood is expensive*
PP3 I would be pleased to pay the price for houses in my current neighbourhood
PP4 I am satisfied with the price of houses in my current neighbourhood
PP5 The houses in my current neighbourhood are fairly priced
PP6 The houses in my current neighbourhood are overpriced*
Pull effects: attractiveness of City of Elmina
Price value 7 PV1 The homes in the City of Elmina are reasonably priced Sweeney and Soutar (2001)
Herrmann et al. (2007)
Voss et al. (1998)
PV2 The homes in the City of Elmina offer value for money
PV3 The homes in the City of Elmina are good products for the price
PV4 The price of homes in the City of Elmina is appropriate relative to its value
PV5 The price of homes in the City of Elmina meets my expectations
PV6 The homes in the City of Elmina are expensive*
PV7 I would be pleased to pay the price for homes in the City of Elmina
Functional value 5 FV1 The homes in the City of Elmina have consistent quality Sweeney and Soutar (2001)
FV2 The homes in the City of Elmina are well designed
FV3 The homes in the City of Elmina have an acceptable standard of quality
FV4 The homes in the City of Elmina have good workmanship
FV5 The homes in the City of Elmina would last a long time
Emotional value 5 EV1 The neighbourhood environment in the City of Elmina is one that I would enjoy Sweeney and Soutar (2001)
EV2 The neighbourhood environment in the City of Elmina would make me want to stay here
EV3 The neighbourhood environment in the City of Elmina is one that I would feel relaxed to stay in
EV4 The neighbourhood environment in the City of Elmina makes me feel good
EV5 The neighbourhood environment in the City of Elmina would give me pleasure
Pull effects: attractiveness of City of Elmina
Social value 4 SV1 Buying a home in the City of Elmina would help me to feel acceptable Sweeney and Soutar (2001)
SV2 Buying a home in the City of Elmina would improve the way I am perceived socially
SV3 Buying a home in the City of Elmina would make a good impression on other people
SV4 Buying a home in the City of Elmina would give me social approval
Symbolic value 5 SCV1 Staying in the City of Elmina is consistent with how I see myself Sirgy et al. (1997)
SCV2 The City of Elmina reflects who I am
SCV3 People similar to me are staying in the City of Elmina
SCV4 The kind of person who typically stays in the City of Elmina are very much like me
SCV5 The City of Elmina mirrors my lifestyle
Feng Shui value 7 FSV1 Properties in the City of Elmina are backed by taller buildings or a mountain behind Wu et al. (2012)
FSV2 Properties in the City of Elmina have an open space in front
FSV3 Properties in the City of Elmina have a good view in front
FSV4 Properties in the City of Elmina have good sitting/facing directions
FSV5 Properties in the City of Elmina have appropriate internal layout
FSV6 Properties in the City of Elmina have been designed to avoid harmful objects e.g. does not directly face junctions, sharp edges of other buildings, or electric wires/viaduct
FSV7 Properties in the City of Elmina are associated with lucky numbers, e.g., address numbers and list price
FSV8 Overall, properties in the City of Elmina have good Feng Shui
Mooring effects     
Relocation costs 5 RC1 I would need to spend a lot of time and money to relocate from my current home/neighbourhood to the City of Elmina Bansal et al. (2004)
Sharma and Patterson (2000)
RC2 Overall, I would spend and lose a lot if I move from my current home/neighbourhood to the City of Elmina
RC3 Generally speaking, the costs in time, money and effort to move from my current home/neighbourhood to the City of Elmina would be high
RC4 I would feel frustrated to move out of my current home/neighbourhood to the City of Elmina
RC5 Considering everything, the costs to move out of my current home/neighbourhood and shift into the City of Elmina would be high
Alternative attractiveness 5 AA1 Purchasing a home in the above-mentioned development will be less costly than in the City of Elmina Bansal et al. (2004)
Sharma and Patterson (2000)
AA2 Overall, purchasing a home in the above-mentioned development would benefit me more than in the City of Elmina  
AA3 I would be much more satisfied with purchasing a home in the above-mentioned development compared to the City of Elmina
AA4 In general, I would be much more satisfied with the above-mentioned development than with the City of Elmina
AA5 Overall, the above-mentioned development would be a better purchase than the City of Elmina
Dependent variable No. of items items Measurement items Sources
Purchase Intention 4 PI1 The likelihood of me purchasing a home in the City of Elmina is…
Very Unlikely…..Very Likely
Oliver and Swan (1989)
PI2 The probability of me purchasing a home in the City of Elmina is…
Very Improbable…..Very Probable
PI3 Chances I would purchase a home in the City of Elmina are…
Not at all Certain…..Completely Certain
PI4 The possibility of me purchasing a home in the City of Elmina is…
Very Impossible…..Very Possible
Marker variable     
 Social desirability 7 SD1 I like to gossip at times Fischer and Fick (1993)
SD2 There have been occasions when I took advantage of someone
SD3 I sometimes try to get even rather than forgive and forget
SD4 I’m always willing to admit it when I make a mistake
SD5 At times I have really insisted on having things my own way
SD6 I have never been irked when people expressed ideas very different from my own
SD7 I have never deliberately said something that hurt someone’s feelings
  1. *These items are reversely coded

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ghazali, E.M., Ngiam, E.YL. & Mutum, D.S. Elucidating the drivers of residential mobility and housing choice behaviour in a suburban township via push–pull–mooring framework. J Hous and the Built Environ 35, 633–659 (2020). https://doi.org/10.1007/s10901-019-09705-8

Download citation

Keywords

  • Push–pull–mooring
  • Home purchase intention
  • Residential mobility
  • Housing choice behaviour
  • Attractiveness of alternatives
  • Feng-Shui
  • Switching barriers
  • PLS-SEM