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The aim of this research is to investigate the impact of thermal, acoustic and HVAC upgrades on the perception of the quality of life among residential building occupants.

The present study used a quantitative research approach, utilizing a questionnaire as the research instrument. A survey was conducted with 1,119 residential apartment building occupants in Prishtina, Kosovo, using a stratified random sampling method for selection of participants.

The present study used quantitative research with a questionnaire as the research instrument. The survey was conducted with 1,119 residential apartment building occupants in Prishtina, Kosovo, using stratified random sampling. The study found that thermal retrofits, acoustic retrofits and HVAC upgrades as a whole model affect the perception of the quality of life of residential building occupants in Prishtina, Kosovo. However, the study found that not all dimensions of the constructed research model (thermal, acoustic and HVAC) affect the perception of the quality of life of residential building occupants. Specifically, thermal retrofitting seems to strongly influence the perception of quality of life, while HVAC upgrades do not seem to have an impact on the quality of life of occupants. Finally, acoustic retrofits also influence the perception of the quality of life, although not to the same degree as thermal retrofitting.

The present study contributes to understanding the role that thermal retrofits, acoustic retrofits and HVAC upgrades play in the perception of quality of life by building occupants in an understudied region with a booming real estate sector such as Kosovo. The study also highlights the need for further analysis to understand why HVAC upgrades do not seem to influence the perception of quality of life by residential building occupants in Kosovo.

The present study is the first to quantify the impact of thermal, acoustic and HVAC upgrades on the perception of the quality of life of residential building occupants in Prishtina, Kosovo.

The present study aims to investigate the relationship between building regulations, urban planning, and perceptions of housing affordability and prices in Prishtina, Kosovo.

A self-report survey with 1,000 respondents, selected through stratified probability sampling, provided the necessary data. Principal component analysis was applied to the questionnaire's internal structure, while regression analysis helped uncover housing affordability and housing prices perception predictors.

The study found that building regulation standards and zoning/land-use regulations reveal positive relationships with housing prices and housing affordability perception. Among these components, building regulations and standards show a stronger connection with housing affordability and price perception in comparison to urban planning and development.

By investigating the relationship between building regulations, urban planning, and housing affordability and price perception in Prishtina, the present research makes a valuable contribution to the existing literature. The findings of this research hold significant implications for policymakers, urban planners, and developers, highlighting the relevance of adopting a well-balanced approach to building regulations and urban planning in order to uphold and maintain housing affordability and understand housing price dynamics.

The novelty of this research originates from the investigation of these relationships within a rapidly urbanizing city context, contributing to a deeper understanding of the complex dynamics between regulatory policies and outcomes in the housing market. Further research should examine additional dimensions and employ longitudinal designs to gain a deeper understanding of the components predicting housing affordability and price perception in Prishtina and similar urban contexts.

This study aims to investigate the strategic priorities of green building projects and analyze energy consumption alternatives in green residence projects using two innovative methods.

This study uses two methods, decision-making trial and evaluation laboratory (DEMATEL) to measure strategic priorities and golden-cut quantum spherical fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) to analyze energy consumption alternatives.

The study reveals that sustainability and atmosphere are the most significant factors in determining the priorities of green residence projects, whereas innovation has a limited impact on addressing environmental challenges in the building sector. The ranking of energy use alternatives shows that sustainability issues and atmosphere quality of space heating and cooking are the top priorities, whereas other factors like white goods, water heating, lighting and space cooling are ranked lower.

This paper offers a significant contribution to the understanding of green buildings by introducing innovative methodological approaches. Theoretically, it uses the DEMATEL to enhance traditional analytical frameworks, marking a novel effort in understanding green residence projects. In addition, the golden-cut quantum spherical fuzzy TOPSIS method is introduced, offering a comprehensive decision-making framework for green projects, considering factors like energy consumption and economic feasibility. This combination of methodologies provides a holistic evaluation, emphasizing sustainability in green building construction. This study reveals untapped potential for environmental sustainability and energy efficiency, enriching the existing knowledge base.

The purpose of this study is to carry out a comparative analysis of four machine learning models such as linear regression, decision trees, k-nearest neighbors and support vector regression in predicting housing prices in Prishtina.

Using Python, the models were assessed on a data set of 1,512 property transactions with mean squared error, coefficient of determination, mean absolute error and root mean squared error as metrics. The study also conducts variable importance test.

Upon preprocessing and standardization of the data, the models were trained and tested, with the decision tree model producing the best performance. The variable importance test found the distance from central business district and distance to the road leading to central business district as the most relevant drivers of housing prices across all models, with the exception of support vector machine model, which showed minimal importance for all variables.

To the best of the author’s knowledge, the originality of this research rests in its methodological approach and emphasis on Prishtina's real estate market, which has never been studied in this context, and its findings may be generalizable to comparable transitional economies with booming real estate sector like Kosovo.