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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.

Behind the source of environmental problems lie many factors. If we do not wish to ruin the world for future generations after making our own world uninhabitable by abusing the resources, we need to think and question many issues starting from our philosophy of science to our ways of consumption and from alternative technologies to the madness of the consumer society. The economic model applied today is the linear economy model which was developed after the industrial revolution. This model is based on the production and consumption process, which is entirely based on the take–make–dispose understanding in industry, agriculture and trade. The first priority in this cycle is the industry rather than the environment. However, the population is expected to increase gradually in half a century that will cause lack of food and shelter problems in every sense. As an alternative to linear economy, circular economy is defined as an economic approach that the value of products, materials and resources are kept as long as possible in the economy whereas the amount of waste is the lowest. The concept of circular economy is based on a transition to restorative industrial economy, renewable energy, reducing the use of toxic chemicals meanwhile avoiding waste. In this context, the consumer movement consisted of individuals who have high awareness and consciousness of the environment, reshapes consumption decisions and correspondingly initiatives are created. Adopting an understanding called lifestyle of health and sustainability, the consumers prioritize by making their consumptions sustainable, protecting green marketing practices and the ecological system for future generations.

This study aims to determine the number of segments of green consumer behavior on toiletries products, and the tendency of transition between clusters is estimated. This study also provides recommendations based on the results.

This study used primary data collected through an online and offline questionnaire. The questionnaire was intended to identify the socio-demographic characteristics, green consumer behavior state according to the environment as well as the willingness of the respondents to purchase various toiletries products (current, less green, and greener). Prior to segmenting green consumer behavior, scale purification using confirmatory factor analysis was performed to ensure the indicators used were valid. The k-means clustering algorithm was used for the segmentation, while discriminant analysis was used to validate the segmentation result. The Markov chain approach was performed to estimate the tendency of the transition between constructed segments, where the logistic regression model was applied to predict the individual transition probability.

The clustering algorithm resulted in three segments: light green, green and dark green. The light green segment has the lowest attitude toward the environmental criteria while the members of the dark green segment have the highest attitude among the other segments. The logistic regression indicated that the tendency of individuals to stay in the current segment or move to the adjacent segment was influenced by socio-demographic factors. The one-step transition probability matrix revealed that the tendency of a particular segment to move to the greener segment was greater than to stay or even move to the less green segment. The Markov chain approach then showed that the steady-state condition will emerge after 18 steps.

This study was limited geographically and by the criteria used for segmenting the green consumer behavior; therefore, it is recommended that this study be replicated on a greater scale with more criteria. A wider geographic area could be considered, including a national study, and more criteria, such as social influences, could be considered. This study does not focus on specific toiletries products. Selecting more specific toiletries products could be considered to provide a more reliable response from the respondents. Moreover, factors around the willingness to pay for green products were not investigated in greater detail although these factors might become indicators that can distinguish between two or more segments.

This study empirically supports the theory that consumer environmentally friendly behavior can be used to appropriately categorize consumers into several segments, and thereby guide the development of a more differentiated policy approach for business and government.

Green consumer behavior may help save the environment and it will be beneficial in reducing environmental damage.

The study extends the existing literature related to green consumer behavior by segmenting the green consumer behavior based on the environmental criteria and applying the Markov chain approach to estimate the tendency of transition between segments.