A recent study of property valuation literature indicated that the vast majority of researchers and academics in the field of real estate are focusing on Mass Appraisals rather than on the further development of the existing valuation methods. Researchers are using a variety of mathematical models used within the field of Machine Learning, which are applied to real estate valuations with high accuracy. On the other hand, it appears that professional valuers do not use these sophisticated models during daily practice, rather they operate using the traditional five methods. The Department of Lands and Surveys in Cyprus recently published the property values (General Valuation) for taxation purposes which were calculated by applying a hybrid model based on the Cost approach with the use of regression analysis in order to quantify the specific parameters of each property. In this paper, the authors propose a number of algorithms based on Artificial Intelligence and Machine Learning approaches that improve the accuracy of these results significantly. The aim of this work is to investigate the capabilities of such models and how they can be used for the mass appraisal of properties, to highlight the importance of sensitivity analysis in such models and also to increase the transparency so that automated valuation models (AVM) can be used for the day-to-day work of the valuer.

This study presents a comparative assessment of emerging sustainability trends in tourist facilities, focusing on multiple hotels and resorts. By analyzing various aspects, such as energy efficiency, waste management, water conservation, and community engagement, this study evaluates the sustainability initiatives undertaken by these establishments. Through a systematic review of sustainability reports, practices, challenges, and innovations, it identifies key trends shaping the future of sustainable tourism in the hospitality industry. Initially, two case studies of hospitality developments that are awarded with sustainability prizes have been reviewed. These real estate developments are located in the Maldives and Greece, and following their detailed review, a comparison is drawn with a sample of multiple hotels in Pafos City, Cyprus. This study aims to ascertain the presence of a reciprocal relationship between sustainable tourism destinations and their immediate environs, encompassing the local community. This investigation hinges on an analysis of the sustainable practices implemented by hotels situated within these destinations. Moreover, this study explores the distance of hotels from achieving sustainable development by analyzing their environmental, social, and economic practices. This investigation encompasses a range of hotels in Cyprus and internationally. Recommendations toward a more sustainable approach for touristic real estate units has been made, and it is concluded that the development of sustainable tourist destinations requires active involvement from the local and the government authorities, supported by programs facilitating sustainable tourism. Encouraging synergies among businesses and supporting destination management partnerships are crucial. Sustainable hospitality should adhere to environmental excellence, social responsibility, and economic viability. The findings provide valuable insights for policymakers, hotel managers, and stakeholders seeking to enhance environmental performance and social responsibility within tourist accommodations.

The purpose of this article is to examine the prediction accuracy of the Random Forests, a machine learning method, when it is applied for residential mass appraisals in the city of Nicosia, Cyprus. The analysis is performed using transaction sales data from the Cyprus Department of Lands and Surveys, the Consumer Price Index of Cyprus from the Cyprus Statistical Service and the Central Bank of Cyprus' Residential Index (Price index for apartments). The Consumer Price Index and the price index for apartments record quarterly price changes, while the dependent variables for the computational models were the Declared and the Accepted Prices that were conditional on observed values of a variety of independent variables. The Random Forests method exhibited enhanced prediction accuracy, especially for the models that comprised of a sufficient number of independent variables, indicating the method as prominent, although it has not yet been utilized adequately for mass appraisals.

Property tax in Greece is levied since 1985 not on Market Values but on the “objective value” of the properties as it is defined by the Ministry of Economics. It forms a non-flexible system, with market-irrelevant and unrealistic values, inducing land-policy practices and potential political cost to each periodical update. Furthermore, instead of adjusting taxation levels to the current economic reality, the real estate market is experiencing further burdening through approximately 40 different property taxes and levies, leading to further shrinking and depreciation. The authors believe that a fairer taxation system could significantly assist the property sector in Greece. Thus, through this paper and by studying and analyzing best practices from other countries, they propose models that can be applied with the use of existing data in Greece. This work aims to identify the critical parameters that affecting property values in Thessaloniki to create a Market Value forecasting tool for a fairer taxation system, to highlight the importance of a GIS system for this purpose and to compare the results of MRA with the use of SPSS with those of GWR in ArcGIS environment. For the purposes of this study, the Municipality of Thessaloniki was chosen due to its very well organized portal with significant and well organized geographical data and because authors manage to access some data from the Central Bank of Greece, regarding property valuations.

In recent years, the desire and requirement for green buildings have increased. The aim of this research is to determine and confirm the increased request for green properties and to investigate whether this is related to a new need or simply a desire of buyers. Moreover, the paper examines people’s knowledge of greenness and sustainability and their wish to live and work in sustainable buildings. The methodology used for this research is based on quantitative research methods with the use of questionnaires to better understand the residents’ awareness, needs, and desires related to sustainability. The research was based on the hypothesis that increased knowledge and awareness of sustainable design can affect the real estate market. Secondly, this research examined whether the increased desire and need for sustainable buildings may increase the market value of sustainable buildings and if people with higher incomes desire green buildings more. Finally, the last hypothesis examined regarded the differences between residential and commercial buildings in terms of sustainable design. The study explored whether buyers will pay extra to purchase a sustainable property and how sustainability can affect the market value and the construction industry. The participants who took part in the research study were living and working in Cyprus. One of the significant outcomes was the fact that people who have knowledge and awareness related to sustainability are willing to pay extra to purchase green properties. Another interesting outcome was that most people have knowledge of sustainable building design. This awareness is crucial as people’s desire is the strongest driver, which can influence them to invest more in green real estate.

The energy efficiency of existing buildings is a crucial factor in addressing energy consumption challenges in European countries, accounting for nearly 40% of the total energy usage. One such country is Cyprus, which faces significant challenges in transforming its existing building stock into energy-efficient and sustainable structures. To face this situation, extensive focus has been made by the government on the energy-efficient retrofit of non-residential public buildings erected before 2010, which lack any energy efficiency measures. This study examines the case of the Pano Polemidia Cultural Hall (PPCH), which represents the building stock of that period. Through the simulation of two scenarios, before and after the adoption of retrofit measures, the existing energy performance is initially evaluated and then the adoption of sustainable solutions, which improve substantially the energy efficiency and can be easily adopted from the relevant authorities, is explored. These retrofit measures include installation of HVAC system, covering of the shell of the building with external thermal insulation, lighting replacement with LED devices, installation of PV system and solar panels, and replacement of the external openings with aluminum windows. The results derived show that the energy consumption of the building was reduced from 468 to 218 kWh/m²·yr, with renewable energy sources (RESs) contributing 177 kWh/m²·yr, the CO₂ emissions were reduced from 136.73 to 11.5 kg/m²·yr, while the reduction in energy consumption per sector ranged from 25% in lighting to 83% in hot water. Therefore, it is evident that a comprehensive retrofitting plan can transform the PPCH into a near-zero energy consumption building that also provides value to the local community and can act as a successful example for any other non-residential buildings with similar characteristics.