Methodological and Conceptual Framework of Means-End Chain Model for Housing Environment Research

Many theories, concepts and models have been evolved and developed over the years and used for housing research with some measuring only the objective characteristics of housing while others measure the subjective characteristics of the housing user. The Means-End Chain (MEC) model, although originally developed to link consumer products and products’ use research, is gaining acceptability within housing research over the past one decade. MEC model, unlike the other housing research theories and models, has been a potent and effective instrument in measuring both aspects of objective housing environment and the subjective characteristics or motivational factors of the housing user. MEC modeling approach is intuitively appealing and has won acceptance both in academic research and in practice. This conceptual and theoretical paper explores from literature the MEC model and attempts to propagate its use as a modeling research domain for housing environment research. It also presents the methodological framework employed by MEC model for data collection and data management. Data analysis in MEC is quite tasking and complex; there is therefore a need for a development of a simplified analysis format and an analytical tool that will be able to assist the researcher in managing the data generated by the laddering interviews.Keywords: Housing Preference and Choice, Laddering Technique, Means-End Chain, Stated Housing Preference and Choice Model

Computerized decision aid for first-time homebuyers

Technology-mediated assistance in house purchasing decision is evidenced in many developed countries, however, in Malaysia less study was found although the decision challenges faced by first-time homebuyers are undeniable. This study attempts to embed technology assistance in the prominent consumer decision-making process model for the purpose of assisting first time homebuyers to make a house purchasing decision. This study employs mixed method approaches with Klang Valley, Malaysia as case study. 19 housing attributes under Locational, Neighborhood, Structural and Social Cultural group, are surveyed to validate the distinctive nature of the attributes to be part of the decision-making criteria. Factor analysis is performed on 320 data from the potential first-time homebuyers in Klang Valley. Two key factors are confirmed from the analysis; which are needs (i.e. Locational and Structural) and preferences (i.e. Neighborhood and Social Cultural). Both factors are later embedded in the proposed design model of computerized decision aid for homebuyers. The model is then evaluated through expert reviews and data was analysed qualitatively using thematic analysis. Four themes emerged from the analysis, which are Suggestion, Concern, Strength, and Limitation. Meaningful discovery on how would the future applications may have an impact is made through analysing themes with negative connotation like Concern and Limitation. The focused themes also reflect actual insights from the industry’s key players, which are useful for improvement of the proposed design model and towards more effective computerized decisionaid for first-time homebuyers