A method for capturing customers’ preferences for housing customisation

Abstract

The housebuilding sector has used mass production systems and reduced portfolios for many decades in different countries, countering the constant changes in society, resulting in neglecting the increasing diversity of customers’ requirements. Housebuilding companies should be able to meet this requirement’s diversity by offering a higher product variety and at the same time maintaining costs within market expectations. Mass customisation strategies have been presented as efficient alternatives to keep the balance between fulfilling clients’ specific needs and maintaining reasonable prices in housing by focusing on value generation. Moreover, there are limited ways of increasing value generation in housing considering its tradeoff with product cost, emphasising the need for the delimitation of a set of options (i.e.: solution space) adequate to customers’ preferences. Some research opportunities highlighted in the literature for adopting mass customisation in housing include solution space clear definition and the need for methods to explore the value perceived in product alternatives and reduce trade-offs between preferences and choice complexity. Accordingly, the main aim of this investigation is to propose a method for capturing customers’ preferencess and supporting customer integration in mass customisation strategies for housing. The design science approach was used as methodological underpinning for building the solution in this investigation. This thesis was structured in three academic papers. The first paper provides an overview of the available practices in house building and focuses on developing a framework of customer integration and core decision categories that support the definition of mass customisation strategies. In the second paper, a method for identifying customers’ preferences and support solution space definition was proposed, based on preference modelling and willingness-to-pay approaches regarding customer value and its balance with operations costs. In paper 3, another method is presented by adapting menu-based choice for housing and its implementation in an empirical study. The main contributions of this thesis include the method for capturing customers’ preferences, a framework of decision categories, and approaches for modelling customers willingness-to-pay for customised housing.