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Method for capturing demands for housing customisation: balancing value for customers and operations costs

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Abstract

Mass customisation is a business strategy for house building companies to improve value generation and obtain a competitive advantage by offering the product variety that meets customers’ needs and, at the same time, maintaining costs and delivery time within market expectations. Companies aiming to define product variety should be able to assess the value of customisable attributes, as well as, estimate additional costs for both customer and themselves. This paper proposes a method for capturing customers’ demands to support the definition of the solution space in mass customised housing projects, based on preference models and the willingness-to-pay approaches that regard customer´s value, and its trade-offs with operations costs. The method was applied in an exploratory study with potential customers of the main social housing program from Brazil for initially testing its utility. The method was useful for identifying the most relevant housing customisable attributes and for estimating customers’ willingness-to-pay for different housing alternatives based on the preference model. The findings were summarised to support the definition of the solution space by indicating customers’ propensity to buy according to operations costs and profitability for each product alternative.

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Notes

  1. The minimum cost of construction work was established based unitary costs estimated by on SINAPI (a Building Cost Index System run by the Brazilian Government) and an average amount of construction work in housing units of MHML Program.

References

  • Baldauf, J. P., Formoso, C. T., Tzortzopoulos, P., Miron, L. I. G., & Soliman, J. (2020). Using building information modelling to manage client requirements in social housing projects. Sustainability (Switzerland), 12(7), 1–21. https://doi.org/10.3390/su12072804.

    Article  Google Scholar 

  • Barlow, J., & Ozaki, R. (2003). Achieving ‘customer focus’ in private housebuilding: Current practice and lessons from other industries. Housing Studies, 18(1), 87–101. https://doi.org/10.1080/0267303032000076858.

    Article  Google Scholar 

  • Battesini, M., & Caten, C. S. (2005). Análise conjunta com estimulação em duas etapas. Produto e Produção, 8, 31–51.

    Google Scholar 

  • Brandli, L. L., & Heineck, L. F. M. (2005). As abordagens dos modelos de preferência declarada e revelada no processo de escolha habitacional. Ambiente Construído, 5(48), 61–75.

    Google Scholar 

  • BRASIL. (2019) Boletim Mensal dos Subsídios da União avalia resultados do Minha Casa Minha Vida, [ published in Portuguese] https://www.gov.br/economia/pt-br/assuntos/noticias/2019/08/boletim-mensal-dos-subsidios-da-uniao-avalia-resultados-do-minha-casa-minha-vida . Accessed 21 Dec 2019.

  • Breidert, C., Hahsler, M., & Reutterer, T. (2006). A review of methods for measuring willingness-to-pay. Innovative Marketing. https://doi.org/10.3111/13696998.2011.644408.

    Article  Google Scholar 

  • CAIXA. (2015). Caderno de Orientação técnica.

  • CAIXA (2018). “Minha Casa Minha Vida”. http://www.ademi.org.br/docs/CartilhaCaixa.pdf

  • Cambridge Dictionary. (2020). Security. https://dictionary.cambridge.org/us/dictionary/english/security. Accessed 30 Oct 2020.

  • Da Rocha, C. G. (2011). A conceptual framework for defining customisation strategies in the house-building sector. Ph.D. Thesis, Universidade Federal of Rio Grande do Sul, Porto Alegre, Brazil.

  • De Medeiros, J. F., Ribeiro, J. L. D., & Cortimiglia, M. N. (2016). Influence of perceived value on purchasing decisions of green products in Brazil. Journal of Cleaner Production, 110, 158–169. https://doi.org/10.1016/j.jclepro.2015.07.100.

    Article  Google Scholar 

  • Earnhart, D. (2002). Combining revealed and stated data to examine housing decisions using discrete choice analysis. Journal of Urban Economics, 51(1), 143–169. https://doi.org/10.1006/juec.2001.2241.

    Article  Google Scholar 

  • Echeveste, M. E., & Mossé, D. (2017). A method for measuring customer value: a case study. In IIE annual conference. Proceedings, institute of industrial and systems engineers (pp. 1235–1240).

  • Ferguson, S. M., Olewnik, A. T., & Cormier, P. (2014). A review of mass customization across marketing, engineering and distribution domains toward development of a process framework. Research in Engineering Design, 25(1), 11–30. https://doi.org/10.1007/s00163-013-0162-4.

    Article  Google Scholar 

  • Fettermann, D. D. C., Tortorella, G. L., & Taboada, C. M. (2019). Mass customization process in companies from the housing sector in Brazil. In G. Cortés-Robles, J. L. García-Alcaraz, & G. Alor-Hernández (Eds.), Managing innovation in highly restrictive environments lessons from Latin America and emerging markets (pp. 99–118). http://www.springer.com/series/11690

  • Fogliatto, F. S., & da Silveira, G. J. C. (2008). Mass customization: A method for market segmentation and choice menu design. International Journal of Production Economics, 111(2), 606–622. https://doi.org/10.1016/j.ijpe.2007.02.034.

    Article  Google Scholar 

  • Fogliatto, F. S., da Silveira, G. J. C., & Borenstein, D. (2012). The mass customization decade: An updated review of the literature. International Journal of Production Economics, 138(1), 14–25. https://doi.org/10.1016/j.ijpe.2012.03.002.

    Article  Google Scholar 

  • Formoso, C., Leite, F., & Miron, L. (2011). Client requirements management in social housing: A case study on the residential leasing program in brazil. Journal of Construction in Developing Countries, 16(2), 47–67.

    Google Scholar 

  • Franke, N., & Hader, C. (2014). Mass or only ‘niche customization’? Why we should interpret configuration toolkits as learning instruments. Journal of Product Innovation Management. https://doi.org/10.1111/jpim.12137.

    Article  Google Scholar 

  • Frutos, J. D., & Borenstein, D. (2004). A framework to support customer–company interaction in mass customization environments. Computers in Industry, 54(2), 115–135. https://doi.org/10.1016/j.compind.2003.09.004.

    Article  Google Scholar 

  • Granja, A. D., Catharine, D., Knatz, C., Affonso, L., Barros, F., Paoli, D. D., & Jacomit, A. M. (2009). A natureza do valor desejado na habitação social. Ambiente Construído, 9(2), 87–103.

    Google Scholar 

  • Green, P. E., Krieger, A. M., & Wind, Y. (2001). Thirty years of conjoint analysis : Reflections and prospects. Interfaces, 31(3), 56–73.

    Article  Google Scholar 

  • Green, P. E., & Wind, Y. (1975). A new way to measure consumer judgments. Harvard Business Review, 75404, 107–117.

    Google Scholar 

  • Greene, M., & Ortúzar, J. D. D. (2002). Willingness to pay for social housing attributes: A case study from Chile. International Planning Studies, 7(1), 55–87.

    Article  Google Scholar 

  • Hentschke, C. dos S. (2014). Método para identificar atributos customizáveis na habitação baseado no modelo conceitual Cadeia Meios-Fim. Universidade Federal do Rio Grande do Sul.

  • Hankammer, S., Wang, N., & Guo, J. (2016). Consumption trends in china and germany in comparison: An empiricial cross-cultural study on the role of sustainability and customizability. Proceedings of the 7th international conference on mass customization and personalization in central Europe (MCP-CE 2016), 110–117.

  • Hart, C. W. L. (1995). Mass customization: Conceptual underpinnings, opportunities andlimits. International Journal of Service Industry Management, 6(2), 36–45. https://doi.org/10.1108/09564239510084932.

    Article  Google Scholar 

  • Hentschke, C. S., Formoso, C. T., & Echeveste, M. E. (2020a). A customer integration framework for the development of mass customised housing projects. Sustainability (Switzerland), 12(Special issue: ZEMCH International research 2020), 1–26.

    Google Scholar 

  • Hentschke, C. S., Formoso, C. T., Rocha, C. G., & Echeveste, M. E. S. (2014). A method for proposing valued-adding attributes in customized housing. Sustainability (Switzerland), 6(12), 9244–9267. https://doi.org/10.3390/su6129244.

    Article  Google Scholar 

  • Hentschke, C. S., Tillmann, P. A., Formoso, C. T., Martins, V. L. M., & Echeveste, M. E. S. (2020b). Using conjoint analysis to understand customer preferences in customized low-income housebuilding projects. Ambiente Construído, 20(1), 247–262.

    Article  Google Scholar 

  • Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression (2nd ed.). New York: Wiley. https://doi.org/10.1002/0471722146.

    Book  Google Scholar 

  • Jansen, S. J. T. (2014). Different values, different housing? Can underlying value orientations predict residential preference and choice? Housing, Theory and Society, 31(3), 254–276. https://doi.org/10.1080/14036096.2013.867279.

    Article  Google Scholar 

  • Jansen, S. J. T., Coolen, H. C. C. H., & Goetgeluk, R. W. (Eds). (2011). The measurement and analysis of housing preference and choice. Springer, 272 pp. https://doi.org/10.1007/978-90-481-8894-9.

  • Jun, H. J., Kim, J. H., Rhee, D. Y., & Chang, S. W. (2020). “ SeoulHouse2Vec ”: An embedding - based collaborative filtering housing recommender system for analyzing housing preference. Sustainability, 12(6964), 1–24. https://doi.org/10.3390/su12176964.

    Article  Google Scholar 

  • Kalantari, H. D., & Johnson, L. (2017). Australian customer willingness to pay and wait for mass-customised products. Asia Pacific Journal of Marketing and Logistics, 30(1), 106–120. https://doi.org/10.1108/APJML-01-2017-0006.

    Article  Google Scholar 

  • Kam, K. J., Lim, A. S. H., Al-Obaidi, K. M., & Lim, T. S. (2018). Evaluating housing needs and preferences of generation y in Malaysia. Planning Practice and Research, 33(2), 172–185. https://doi.org/10.1080/02697459.2018.1427413.

    Article  Google Scholar 

  • Kaur Sahi, G., Sehgal, S., & Sharma, R. (2017). Predicting customers recommendation from co-creation of value customization and relational value. Vikalpa, 42(1), 19–35. https://doi.org/10.1177/0256090916686680.

    Article  Google Scholar 

  • Klink, J., & Denaldi, R. (2014). On financialization and state spatial fixes in Brazil. A geographical and historical interpretation of the housing program my house my life. Habitat International, 44, 220–226. https://doi.org/10.1016/j.habitatint.2014.06.001.

    Article  Google Scholar 

  • Kotha, S. (1995). Mass customization : Implementing the emerging paradigm for competitive advantage. Strategic Management Journal. https://doi.org/10.1002/smj.4250160916.

    Article  Google Scholar 

  • Kowaltowski, D. C. C. K., Atália, E., Muianga, D., Denis, A., Moreira, D. D. C., Bernardini, S. P., et al. (2018). A critical analysis of research of a mass-housing programme. Building Research & Information, 3218, 1–18. https://doi.org/10.1080/09613218.2018.1458551.

    Article  Google Scholar 

  • Kowaltowski, D. C. C. K., & Granja, A. D. (2011). The concept of desired value as a stimulus for change in social housing in Brazil. Habitat International, 35(3), 435–446. https://doi.org/10.1016/j.habitatint.2010.12.002.

    Article  Google Scholar 

  • Larsen, M. S. S., Lindhard, S. M., Brunoe, T. D., Nielsen, K., & Larsen, J. K. (2019). Mass customization in the house building industry: Literature review and research directions. Frontiers in Built Environment, 5(October), 1–12. https://doi.org/10.3389/fbuil.2019.00115.

    Article  Google Scholar 

  • Lee, X. S., Khamidi, M. F., Kuppusamy, S., & Heng, C. T. (2018). Client-oriented building mass customization (CoBMC). IOP Conference Series: Materials Science and Engineering. https://doi.org/10.1088/1757-899X/291/1/012011.

    Article  Google Scholar 

  • Lermen, F. H., Ribeiro, J. L. D., Echeveste, M. E., Milani Martins, V. L., & Tinoco, M. A. C. (2020). Sustainable offers for drying and storage of grains: Identifying perceived value for Brazilian farmers. Journal of Stored Products Research. https://doi.org/10.1016/j.jspr.2020.101579.

    Article  Google Scholar 

  • Linner, T., & Bock, T. (2012). Evolution of large-scale industrialisation and service innovation in Japanese prefabrication industry. Construction Innovation, 12(2), 156–178. https://doi.org/10.1108/14714171211215921.

    Article  Google Scholar 

  • Lis, L., & Amaral, L. (2017). Governo amplia Minha Casa, Minha Vida para famílias com renda de até R$ 9 mil. [published in Portuguese]. https://g1.globo.com/economia/noticia/governo-amplia-minha-casa-minha-vida-para-familias-com-renda-de-ate-r-9-mil.ghtml. Accessed Jan 2018.

  • Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated choice methods: Analysis and applications. Port Chester: Cambridge University Press.

    Book  Google Scholar 

  • Luce, D., & Tukey, J. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement. Journal of Mathematical Psychology, 1, 1–27.

    Article  Google Scholar 

  • Lukka, K. (2003). The constructive research aproach. In Ojala, L. & Himola, O-P.(eds) Case study research in logistics (pp. 83–101). Turku School of Economics and Business Administration, Series B1.

  • March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems, 15, 251–266.

    Article  Google Scholar 

  • Martinez, E., Tommelein, I. D., & Alvear, A. (2017). Integration of lean and information technology to enable a customization strategy in affordable housing. In Proceedings of the 25th annual conference of the international group for lean construction (IGLC), Heraklion, Greece, 9–12 July 2017 (pp. 95–102). https://doi.org/10.24928/2017/0136.

  • Ministerio das Cidades. (2017). PORTARIA No 269, DE 22 DE MARÇO DE 2017.

  • Molin, E. J. E. (2011). Chapter 6 : Conjoint Analysis. In The Measurment and analysis of housing preference and choice (pp. 127–156).

  • Molin, E. J. E., Oppewal, H., & Timmermans, H. J. P. (2001). Analyzing heterogeneity in conjoint estimates of residential preferences. Journal of Housing and the Built Environment, 16, 267–284.

    Article  Google Scholar 

  • Moreira, V. de S., Silveira, S. de F. R., & Euclydes, F. M. (2017). Minha Casa, Minha Vida em números: quais conclusões podemos extrair? IV Encontro Brasileiro de Administração Pública, 594–613. http://www.ufpb.br/ebap/contents/documentos/0594-613-minha-casa.pdf

  • Nahmens, I., & Bindroo, V. (2011). Is customization fruitful in industrialized homebuilding industry? Journal of Construction Engineering and Management, 137(12), 1027–1035. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000396.

    Article  Google Scholar 

  • Nijënstein, S., Haans, A., Kemperman, A. D. A. M., & Borgers, A. W. J. (2015). Beyond demographics: human value orientation as a predictor of heterogeneity in student housing preferences. Journal of Housing and the Built Environment, 30(2), 199–217. https://doi.org/10.1007/s10901-014-9402-9.

    Article  Google Scholar 

  • Noguchi, M., & Hernández-Velasco, C. R. (2005). A ‘mass custom design’ approach to upgrading conventional housing development in Mexico. Habitat International, 29(2), 325–336. https://doi.org/10.1016/j.habitatint.2003.11.005.

    Article  Google Scholar 

  • Olanrewaju, A. L., Wong, Hw., & C. . (2019). Evaluation of the requirements of first time buyers in the purchase of affordable housing in Malaysia. Journal of Housing and the Built Environment. https://doi.org/10.1007/s10901-019-09681-z.

    Article  Google Scholar 

  • Ortúzar, J. de D., & Willumsen, L. G. (2011). Modelling Transport (fourth edi.). Chichester: Wiley.

  • Orzechowski, M. A., Arentze, T. A., & Borgers, A. W. J. (2005). Alternate methods of conjoint analysis for estimating housing preference functions : Effects of presentation style. Journal of Housing and the Built Environment. https://doi.org/10.1007/s10901-005-9019-0.

    Article  Google Scholar 

  • Piller, F. T. (2004). Mass customization: Reflections on the state of the concept. The International Journal of Flexible Manufacturing Systems, 16, 313–334.

    Article  Google Scholar 

  • Piller, F. T., Moeslein, K., & Stotko, C. M. (2004). Does mass customization pay? An economic approach to evaluate customer integration. Production Planning & Control, 15(4), 435–444. https://doi.org/10.1080/0953728042000238773.

    Article  Google Scholar 

  • Pine, B. J., II. (1994). Personalizando produtos e serviços : Customização maciça. . Makon Books do Brasil.

    Google Scholar 

  • Rietveld, J. (2018). Creating and capturing value from freemium business models: A demand-side perspective. Strategic Entrepreneurship Journal, 12(2), 171–193. https://doi.org/10.1002/sej.1279.

    Article  Google Scholar 

  • Rose, J. M., Bliemer, Mi., & C. J. . (2009). Constructing efficient stated choice experimental designs. Transport Reviews, 29(5), 587–617. https://doi.org/10.1080/01441640902827623.

    Article  Google Scholar 

  • Salvador, F., De Holan, P. M., & Piller, F. (2009). Cracking the code of mass customization. MIT Sloan Management Review, 50(50315), 70–78.

    Google Scholar 

  • Schoenwitz, M., Naim, M., & Potter, A. (2012). The nature of choice in mass customized house building. Construction Management and Economics, 30(April), 203–219.

    Article  Google Scholar 

  • Schoenwitz, M., Potter, A., Gosling, J., & Naim, M. (2017). Product, process and customer preference alignment in prefabricated house building. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2016.10.015.

    Article  Google Scholar 

  • Sillano, M., de Ortúzar, J., & D. . (2005). Willingness-to-pay estimation with mixed logit models: Some new evidence. Environment and Planning A, 37(3), 525–550. https://doi.org/10.1068/a36137.

    Article  Google Scholar 

  • Silveira, G. D., Borenstein, D., & Fogliatto, H. S. (2001). Mass customization : Literature review and research directions. International Journal Production Economics, 72(49), 1–13.

    Article  Google Scholar 

  • Squire, B., Readman, J., Brown, S., & Bessant, J. (2004). Mass customization: The key to customer value? Production Planning & Control, 15(4), 459–471. https://doi.org/10.1080/0953728042000238755.

    Article  Google Scholar 

  • Tillmann, P. A., & Formoso, C. T. (2008). Opportunities to adopt mass customisation – a case study in the Brazilian house building sector. Proceedings for the 16 Annual Conference of the International Group for Lean Construction, 447–458.

  • Train, K. (2016). Mixed logit with a flexible mixing distribution. Journal of Choice Modelling, 19, 40–53. https://doi.org/10.1016/j.jocm.2016.07.004.

    Article  Google Scholar 

  • Train, K., & Weeks, M. (2005). Discrete choice models in preference space and willingness-to-pay space. In: A. Alberini & R. Scarpa (Eds.), Applications of simulation methods in environmental and resource economicsa (pp. 1–17). Dordrecht: Springer.

    Google Scholar 

  • Valença, M. M., & Bonates, M. F. (2010). The trajectory of social housing policy in Brazil : From the National Housing Bank to the Ministry of the Cities. Habitat international, 34, 165–173. https://doi.org/10.1016/j.habitatint.2009.08.006.

    Article  Google Scholar 

  • Vasanen, A. (2012). Beyond stated and revealed preferences: The relationship between residential preferences and housing choices in the urban region of Turku, Finland. Journal of Housing and the Built Environment, 27(3), 301–315. https://doi.org/10.1007/s10901-012-9267-8.

    Article  Google Scholar 

  • Woodruff, R. B. (1997). Customer value: The next source for competitive advantage. Journal of the Academy of Marketing Science, 25(2), 139–153.

    Article  Google Scholar 

  • Zogaj, S., & Bretschneider, U. (2012). Customer integration in new product development: A literature review concerning the appropriateness of different customer integration methods to attain customer knowledge. ECIS 2012 - Proceedings of the 20th European Conference on Information Systems. doi:https://doi.org/10.2139/ssrn.2485240.

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Acknowledgements

The authors would like to thank CAPES for partially funding this research. The authors would also like to thank João Soliman Junior, Luciana Gheller, Cristiane Schvarstzhaupt, Angélica Segala, Angela Silva and Mariana Nolde, for their collaboration in the initial steps of this research.

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  1. Civil Engineering Post Graduate Program: Construction and Infrastructure (PPGCI), Universidade Federal do Rio Grande Do Sul (UFRGS), Av. Osvaldo Aranha, 99, 7o Andar, sala 706, Porto Alegre, 90035-190, Brazil

    Cynthia dos S. Hentschke, Márcia Elisa S. Echeveste & Carlos T. Formoso

  2. Industrial Engineering Department, Universidade Federal do Rio Grande Do Sul (UFRGS), Av. Osvaldo Aranha, 99, 5° Andar, Porto Alegre, 90035-190, Brazil

    José Luis D. Ribeiro

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  1. Cynthia dos S. Hentschke
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dos S. Hentschke, C., S. Echeveste, M.E., T. Formoso, C. et al. Method for capturing demands for housing customisation: balancing value for customers and operations costs. J Hous and the Built Environ 37, 311–337 (2022). https://doi.org/10.1007/s10901-021-09838-9

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