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The purpose of this paper is to investigate how to measure the effect of unobservable factors on residential choice behaviour in an attempt to advance the understanding of how to perform advanced market analysis. This research is important to residential developers, as the diversity of preferences is increasingly driven by lifestyle-based households and affluent households.

Information about the pros and cons of renting an apartment in an ongoing residential development project in Stockholm came from interviews using the laddering technique. Qualitative data were subsequently analysed using exploratory and confirmatory factor analysis to confirm which factors had the highest effect on an overall assessment of living in the development and a value-for-money conclusion.

Among the potentially important factors identified, respondents who became residents perceived the development to be more noise-free than those who did not when stating the overall value of living in the development and making a value-for-money conclusion. The perception of noise differed between the two groups, meaning that those who did not become residents believed the development to be more exposed to noise. The standard of the apartment was the second most influential factor when stating the overall value of living in the development and making a value-for-money conclusion. The belief of being able to relax in the home environment had no significant effect on overall value for either group.

The results show that confirmatory factor analysis can be used in measuring the effect of unobservable factors in residential choice behaviour. The methodology presented may advise developers, architects or planners in evaluating those attributes that create value-for-money to improve, for example, overall design solutions in urban development projects.

The purpose of the present study is to explore the factors that influence the residential location choice of households in the Indian context.

Two sub-urban towns of Kolkata, i.e. Biddhanagar Municipal Corporation and Rajarhat Newtown, are taken as case studies. In total, 34 variables are considered related to the household's socioeconomic background (10), dwelling (3), travel (2) and level of importance of neighborhood characteristics (19). A revealed preference household survey is conducted, which resulted in the collection of 390 samples. Firstly, 19 level of importance variables are deduced to 3 latent factors using exploratory and confirmatory factor analysis. After that, a utility function is estimated using a multinomial logit regression to identify significant factors.

The results indicate the significance of car ownership, work travel time, work mode, monthly income, proximity to work, proximity to family/relative/friends, proximity to quality schools, quality of physical infrastructure such as water availability, power availability and housing typology among others in the residential location choice of households.

Kolkata, a major metropolitan area in eastern India, has been experiencing space constraints to cater to the housing demand of the ever-increasing population. Although satellite towns are being developed, the infrastructure landscape in such towns is uneven, resulting in more housing demand in one area than another. The study furnishes significant findings to develop more informed policies to attract households in low-demand areas and manage high-demand areas to achieve sustainable planning.

Considering the importance of geographical context, it is the first study on residential location choice, providing a perspective of household behavior from eastern India. It also shows the importance of physical infrastructure attributes in residential location choice for developing countries, which is seldom employed in the current practice. Moreover, previous studies (although few) done in India consider the objective value of location characteristics. The present study focuses on subjective value or the level of importance perceived by respondents.

This study aims to clarify the following research questions: to what extent do people consider natural disaster risks as important for residential selection? what personal demographics and attitudes toward natural disaster risks are associated with the relative importance of natural disasters for residential selection? and to what extent do the associated personal attributes influence the relative importance of natural disasters for residential selection?

An internet-based survey was performed to collect 2,000 responses from residents of Osaka Prefecture, Japan, to gauge people’s relative importance of safety against natural disasters regarding residential preference. The obtained results were analysed using two types of statistical analysis, specifically chi-square test and multivariable logistic regression analyses.

It was found that 37.3% of the respondents in Osaka Prefecture, Japan, considered the “safety against natural disasters” relatively important when selecting a residential location. The statistical analysis also demonstrated that those having a relatively higher level of disaster awareness and preparedness were 1.41 times more likely to prefer to live in a place that is safer from natural disasters. Thus, it was suggested that disaster education aimed at raising the level of people’s disaster awareness could be effective to increase the number of people who choose to live in a safer place from natural disasters.

Living in an area that is safer from natural disasters can effectively minimize human and property damage. Recently, several measures have been taken in Japan to guide people to live in a safer place. The clarification of the extent to which people consider natural disaster risks as important for residential selection and the understanding of the categories of the people who are likely to do so is important to develop more effective natural disaster measures; however, there has been less attention on such investigation. Therefore, this study conducted an internet-based survey and examined it.

This paper aims to report on homebuyers’ preferences and willingness to pay for installed home photovoltaic systems. Their influence on the market position of a dwelling is relatively unknown. Considering that expected lifespan of photovoltaic systems is at least 25 years, it is likely that many dwellings with a photovoltaic system will enter the housing market.

Few houses with installed photovoltaic systems have been sold in the market to date. Lack of real market data imposes a method based on the stated preference data. Therefore, the general preferences toward photovoltaic systems are determined by a discrete choice model based on responses of 227 homebuyers in the Eindhoven region, The Netherlands. Further, the model estimates were used to assess the indirect willingness to pay for home photovoltaic systems. This initial willingness to pay is further reassessed with the direct willingness to pay collected in an open-ended questionnaire format.

Results of the model show that the homebuyers’ preferences for home photovoltaic systems are large and significant. In addition to general preferences, this article reports on the taste heterogeneity carried out by separating observations based on the respondents’ characteristics. For example, photovoltaic systems are more appealing to homebuyers in more urban or central neighbourhoods. Further, the results of the direct survey lead to the conclusion that people are probably willing to pay close to the replacement value of the system and only 22 per cent of all respondents did not want to pay anything for the installed photovoltaic system.

These findings are exploratory and they raise a number of questions for further investigations, such as those regarding the real estate value of the installed photovoltaic systems. The reported findings must be regarded as local, thus further research is necessary to understand the impact on European housing markets.

Preferences and willingness to pay for home photovoltaic systems can provide a variety of economic, social and political recommendations to different interested parties such as homeowners, buyers, realtors, retailers, energy companies and governments. For instance, a homeowner would like to know what would be the effect of a photovoltaic system on the housing market.

As per the knowledge of authors, this is the first paper to estimate the impact of an installed photovoltaic system on housing choice, measured by stated choice data in the local housing market. It expands the existing body of knowledge for increasingly important issues of valuing and measuring preferences for photovoltaic systems installed on dwellings.

This paper aims to discuss the link between socio-economic characteristics of house buyers and their housing location choices. The major objective of the study is an examination of the role of household socio-economic characteristics. The research addresses the importance of previous residence location and latent housing motives for intra-urban housing mobility.

The research examines housing preferences structure and analyzes housing location choices in the city of Krakow (Poland) using discrete choice model (conditional logit model). The research is based on stated preference data from Krakow.

The results of this study suggest that demand for housing alternatives is negatively linked to the distance from current residence. Other factors stay equal, the further the distance, the less likely a household is willing to choose a location within the metropolitan area. The study indicates that housing motives can help explain housing location decisions.

The paper provides an empirical assessment of housing decisions in Krakow, one of the major metropolitan areas in Poland.

The paper contributes to a better understanding of the nature of housing decision and housing preferences in emerging markets in Central and Eastern Europe. As a result, presented research helps to fill the gap in housing market and urban economics literature.

The purpose of this study is to theorize and measure a consumption criterion of housing affordability and then to compare its predictions with those of a normative criterion over time. The new consumption criterion of housing affordability is quantified with predicted compensatory expenditures that a resident would pay to upgrade to their most preferred home. Its predictions are compared with those of the most popular normative criterion that predicts unaffordability if a resident spends more than a proportion such as 30% of their income on housing.

This study uses census and experimental data for owner-occupiers in two mid-sized Canadian cities between 1987 or 2001 and 2020 or 2021. These data are mapped and statistically analysed for comparing the predictions of the two criteria.

The study’s primary finding is that both criteria predict improved affordability of owned homes over time. Secondarily, however, the consumption criterion predicts worse unaffordability for the minority experiencing this. It furthermore clarifies their budgets for housing as more constraining than their social utilities that they may have already revised toward affordable home attributes. Indisputable unaffordability after the end of the study period may have nullified the originally recommended sacrifices for residents upgrading to their most preferred owned home.

The study is original because it demonstrates that a new consumption criterion of housing affordability subsumes the popular normative criterion if plausible assumptions are made about a homeowner’s choices. It then proceeds to speculate how this new criterion might refine the normative criterion with predicted compensatory expenditures for a resident’s affordable preferred homes.

Mixed logit models can represent heterogeneity across individuals, in both observed and unobserved preferences, but require computationally expensive calculations to compute probabilities. A few methods for including error covariance heterogeneity in a closed form models have been proposed, and this paper adds to that collection, introducing a new form of a Network GEV model that sub-parameterizes the allocation values for the assignment of alternatives (and sub-nests) to nests. This change allows the incorporation of systematic (nonrandom) error covariance heterogeneity across individuals, while maintaining a closed form for the calculation of choice probabilities. Also explored is a latent class model of nested models, which can similarly express heterogeneity. The heterogeneous models are compared to a similar model with homogeneous covariance in a realistic scenario, and are shown to significantly outperform the homogeneous model, and the level of improvement is especially large in certain market segments. The results also suggest that the two heterogeneous models introduced herein may be functionally equivalent.

In metropolitan areas experiencing rapid urbanization and housing production, the size of housing units emerges as a crucial factor to consider in housing policy formulation. This study aims to focus on Turkey, a developing country undergoing rapid urbanization and a construction boom in recent years, to examine households’ housing size preferences. Through a detailed analysis, this research delves into the causal relationships between income, education and housing size preferences.

This study uses the Family Structure Survey in Turkey 2016 data set collected nationwide by the Turkish Statistical Institute (TurkStat). To address potential endogeneity issues related to income and education levels in households’ choice of house size, an extended regression model is used. In addition, survey weights are applied to the statistical model to generalize the results of the study.

The study demonstrates that household income correlates with an increase in house size, while household education is associated with a decrease in house size. Variables such as household age, composition and vehicle ownership are found to impact the choice of house size. Particularly, one-person and couple-only households tend to prefer smaller dwellings compared to others. Lastly, the results reveal that the influence of household composition on dwelling size varies according to household age.

This study presents a comprehensive analysis of the determinants influencing households’ housing size preferences within the framework of a developing country context, focusing on Turkey. It specifically offers insights into the causal impact of education and income levels on housing size preferences, as well as the intricate interplay between household characteristics in shaping these preferences.

A method is proposed for handling multi-attribute judgment problems with a large number of attributes such as mobile phone features. To minimize the complication of multi-attributes and reduce the consumers’ choice task burden, this paper aims to suggest an integrated hierarchical survey design (IHSD) with the Kano model. The author compared the utility of mobile phone’s attributes for each market and for customer segment by analyzing empirical data on wear obtained from six Middle East and African countries, five Asia-Pacific countries and three European countries. Based on an IHSD of 10,200 respondents, brand, camera, memory and LTE (4G) play vital roles in all regions. In contrast, Wi-Fi, file-editor, MMS, LCD size and phone type are displayed as the least important attributes. The results of this study were successfully implemented for product planning, product development and marketing strategy in terms of price setting, features prioritizing and optimal designing for new products in the mobile phone company.

The first step was to list all possible features with the product planning team, product development team and market research specialists. The second step divided the selected features for designing a mobile phone into subgroups based on their functional characteristics by using the Kano model. The method for classifying features was determined using Kano questionnaire. The third step incorporated a fractional factorial design for the “must-be” choice-based conjoint (CBC) (Oppewal et al., 1994) which includes two factors: whether customers required the “one-dimensional” feature or the “attractive” feature, along with the “must-be” attributes. The consumers who selected the “must-be” features could choose both the “one-dimensional” feature and the “attractive” feature groups or one of the two feature groups in no particular order. Fractional factorial design was applied to both the “one-dimensional” features and the “attractive” features for individual CBCs. Random sequences of the combinations of attribute levels were generated for each of the three types of CBC analyses (“must-be”, “one-dimensional” and “attractive”). At the same time, the fourth step conducted a survey of the individual groups for the conjoint analysis on the functional characteristics of a mobile phone. The analysis of the accumulated data obtained from all the feature groups was completed using conditional logit models as part of the fifth step. In addition, the “must-be” CBC design was linked with the “one-dimensional” and “attractive” CBC designs. The sixth step was to analyze the accumulated results obtained from all the feature groups and estimate the usefulness of each feature’s level in the context of the CBC. Based on the results of the sixth step, the importance and willingness-to-pay of each attribute were estimated in the seventh step.

Use of the conjoint important score is aimed to expand the market by finding the different consumers’ needs across the regions. In detail, attributes such as “FM Transmitter”, “Touch screen” and “Health (heart rate)” are considered consumers’ new crucial needs in Europe, which would enable the product to superiorly differentiate itself from others to dominate the current market. On the other hand, it is shown that attributes such as “brand”, “mobile TV”, “external memory”, “mobile tracker” and “4G” are more important in Asia-Pacific. Therefore, if mobile manufacturers develop this sector more, it will grant mobile manufacturers the opportunity to lead the market. The only difference of the Middle East and African consumers is that “NFC” has a higher importance while the rest of the needs are very similar to those of Asia-Pacific. Regarding willingness-to-pay (WTP) among countries, the highest scoring utility, besides brand, appeared to be associated with the camera function in all countries. Especially, relatively low utility value was given in Wi-Fi and File-editer, MMS, LCD size and Phone type. In a value-based approach, the price of a product is based on the perceived valuation by the target customers. The research in the field of pricing is of ample importance. This is because price is the only element of the marketing mix that generates income. All other elements, such as advertising and promotion, product development, selling effort, distribution and packaging, involve expenditures (Monroe, 2003). Regarding among regions, the needs for 3G and the internet-related feature (WAP, Wi-Fi, etc.) in the emerging market are low compared to those for 4G and internet-related feature in the mature market. Also, the needs for productivity and advanced features, such as camera and e-mail, are lower in Asia-Pacific than in Europe. It is therefore recommended that manufactures and marketers of mobile phones should consider producing and selling phones with modern technology features that are more durable and of highly quality.

The integrated hierarchical survey by function with the Kano model proves to be a highly useful, efficient and accurate methodology for understanding a consumer mobile phone behavior. Although the proposed method was applied to designs of mobile phones in the emerging and mature markets, its accuracy was not compared with the traditionally used methods such as CBC, adaptive conjoint analysis and hybrid method. This is left for further areas of research.

The results of this research study correspond with previous studies conducted (Pakola et al., 2010; Das, 2012; Malaasi, 2012, 2008; Dziwornu, 2013), which consider the features of mobile phone as a crucial factor in consumer buying decision in all countries. It is significant that this study made huge impact on mobile phone manufacturers in several ways. It has been converted into product development with consumer-oriented approach. The pricing policy has been changed from cost-based pricing into value-based pricing; and marketing strategy has been changed from an unsystematic function into a systematic and consistent one.

The proposed method with the Kano model proved to be a practical and efficient tool for decision-making, as it helped mobile manufacturers to better understand how customers evaluate and perceive quality attributes. The Kano model was used to explain how the quality attributes can be classified into mainly three categories of perceived quality: “must-be”, “one-dimensional” and “attractive”. It has lots of benefits in terms of cost and time reduction and is expected to bring a great effect into the industrial field.

This paper aims to identify and to compare workplace location attributes that appealed to Generation Y and Z talent.

Semi-structured interviews were conducted with 12 participants to identify workplace location attributes. Choice-based conjoint surveys were collected from 750 Generation Y and Z individuals in the talent pool of Bangkok, Thailand to compare the importance of attributes.

The most important workplace location attribute was the availability and diversity of restaurants followed by place appearance, traffic density, availability of public workspaces, public transport and after-work activities. Transport-related attributes were more important for older generations, whereas public workspaces and place appearance were more important for younger talent.

To attract talent, the Bangkok Metropolitan Administration (BMA) should address the weaknesses of potential workplace locations through efficient, low-cost and rapid development plans. Although Bangkok is known for street food, BMA policies that promote restaurants as the most important attribute are limited. The BMA should initiate plans to promote the availability and diversity of restaurants. Innovation districts in Bangkok should connect to restaurants and food networks in their vicinity.

The existing literature explored factors that attract talent at the city level, but no study has investigated attractiveness at the workplace location level. Despite some similarities, workplace location attributes identified in this study were more specific than city-level attributes.