The Residential Images Method

  • Jeroen P. J. Singelenberg
  • Roland W. Goetgeluk
  • Sylvia J. T. Jansen


In this chapter we concentrate on the “residential images” method, which is often used in applied research and marketing. Residential images include information in pictures, facts, and figures. The main ingredients include: a frontal view of the house in its direct surroundings, simplified floor plan, number of rooms and square meters, price or rent, availability, and special services or requirements. Residential images resemble real-world situations in which people search in newspapers and more often nowadays on the Internet for new offers. This chapter discusses the pros and cons.


Attribute Level Conjoint Analysis Choice Rule Photo Collage Residential Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bettman, J. R. (1979). An information processing theory of consumer choice. Reading: Addison-Wesley.Google Scholar
  2. Boogaard, R. P. J., & Sievers, A. (2009). Doelgroepen- en woonwensenonderzoek Riverstone, Richten op Individuality & Stability. Woudenberg: INBO.Google Scholar
  3. Boumeester, H. J. F. M., Coolen, H. C. C. H., Dol, C. P., Goetgeluk, R. W., Jansen, S. J. T., Mariën, A. A. A., & Molin, E. (2008). Module Consumentengedrag WoON 2006 (Hoofdrapport). Delft: Onderzoeksinstituut OTBGoogle Scholar
  4. Brouwer, R., Hess, S., & Linderhof, V. (2007). De baten van wonen aan water: een internet keuze excperiment. Amsterdam: IVM/VU-Amsterdam.Google Scholar
  5. Buys, A., & Singelenberg, J. (1989). Woonbeeldenonderzoek: ontstaan en ontwikkelingen. In S. Musterd (Ed.), Methoden voor woning en woonmilieubehoefteonderzoek (Vol. 340, pp. 10–19). Amsterdam: SISWO publikatie.Google Scholar
  6. de Graaff, D., Mulder S., & Bemer E. (2007). Haalbaarheid van woonconcepten voor senioren. Amsterdam: TNS Nipo consult, rapport in opdracht van Ministerie van VROMGoogle Scholar
  7. Dijkstra, J., & Timmermans, H. J. P. (1997). Exploring the possibilities of conjoint measurement as a decision-making tool for virtual wayfinding environments. In Y. T. Liu (Ed.) Proceedings of the second conference on computer aided architectural design research in Asia (pp. 61–72), Taipeh: Hu’s Publishers.Google Scholar
  8. Gaber, J., & Gaber, S. L. (2004). If you could see what I know: Moving planners’ use of photographic images from illustrations to empirical data. Journal of Architectural and Planning Research, 21, 222–238.Google Scholar
  9. Hooimeijer, P. (1994). Hoe meet je woonwensen? Methodologische haken en ogen. In I. Smid & H. Priemus (Eds.), Bewonerspreferenties: Richtsnoer voor investeringen in nieuwbouw en de woningvoorraad (pp. 3–12). Delft: Delftse Universitaire Pers.Google Scholar
  10. Hooimeijer, P. (2007). Dynamiek in de derde leeftijd, de consequenties voor het woonbeleid. Den Haag: Ministerie van VROM.Google Scholar
  11. Jaeger, S. R., Hedderley, D., & MacFie, H. J. H. (2005). Methodological issues in conjoint analysis: A case study. European Journal of Marketing, 11(12), 1217–1239.Google Scholar
  12. Jansen, S., Boumeester, H., Coolen, H., Goetgeluk, R., & Molin, E. (2009). The impact of including images in a conjoint measurement task: Results of two small-scale studies. Journal of Housing and the Built Environment, 24(3), 271–297.CrossRefGoogle Scholar
  13. Jansen, S., Boumeester, H., Coolen, H., Goetgeluk, R., & Molin, E. (in press). The effect of presentation: What you see is what you value. Journal of Architectural and Planning Research.Google Scholar
  14. Kauko, T., Goetgeluk, R., & Priemus, H. (2009). Water in residential environments. Built Environment, 35(4), 577–592.CrossRefGoogle Scholar
  15. Louviere, J. J., Schroeder, H., Louviere, C. H., & Woodworth, G. G. (1987). Do the parameters of choice models depend on differences in stimulus presentation: Visual versus verbal presentation? Advances in Consumer Research, 14, 79–82.Google Scholar
  16. Orzechowski, M. A., Arentze, T. A., Borgers, A. W. J., & Timmermans, H. J. P. (2005). Alternate methods of conjoint analysis for estimating housing preference functions: Effects of presentation style. Journal of Housing and the Built Environment, 20(4), 349–362.CrossRefGoogle Scholar
  17. Schkade, D. A., & Kleinmuntz, D. N. (1994). Information displays and choice processes: Differential effects of organization, form, and sequence. Organizational Behavior and Human Decision Processes, 57, 319–337.CrossRefGoogle Scholar
  18. Singelenberg, J. (1980). Woonbeeldenonderzoek toont grote behoefte van Dameenheden aan. Bouw, 18, 33–37.Google Scholar
  19. Singelenberg, J. (2008). SEV-advies inzake waterwonen. Rotterdam: SEV.Google Scholar
  20. Smardon, R. C., Palmer, J. F., & Felleman, J. P. (1986). Foundations for visual project analysis. New York: Wiley.Google Scholar
  21. Tversky, A. (1972a). Elimination by aspects: A theory of choice. Psychological Review, 79, 281–299.CrossRefGoogle Scholar
  22. Tversky, A. (1972b). Choice by elimination. Journal of Mathematical Psychology, 9, 341–367.CrossRefGoogle Scholar
  23. Vriens, M., Loosschilder, G. H., Rosbergen, E., & Wittink, D. R. (1998). Verbal versus realistic pictorial representations in conjoint analysis with design attributes. Journal of Product Innovation Management, 15, 455–467.CrossRefGoogle Scholar
  24. Wittink, D. R., Vriens, M., & Burhenne, W. (1994). Commercial use of conjoint analysis in Europe: Results and critical reflections. International Journal of Research in Marketing, 11, 41–52.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Jeroen P. J. Singelenberg
    • 1
  • Roland W. Goetgeluk
    • 2
  • Sylvia J. T. Jansen
    • 3
  1. 1.SEVRotterdamThe Netherlands
  2. 2.Demography & HousingABF ResearchDelftThe Netherlands
  3. 3.OTB Research Institute for the Built EnvironmentDelft University of TechnologyDelftThe Netherlands

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