Odbor znalectví ve stavebnictví a oceňování nemovitostí


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    Public recreation is an environmental aspect affecting not only the environment
    (Mendel University in Brno, 2022-05-09) Brandejs, David; Vařechová, Martina; Klika, Pavel; Hlavinková, Vítězslava
    Optimal recreation should lead to the regeneration of the organism, which is conditioned by a retreat from everyday worries and work responsibilities. The most efficient and reliable way is to travel to places that are almost the opposite of everyday life. The diversity of requirements of individuals who are tired of physical or mental work logically implies the diversity of recreational areas. There are a large number of cultural and natural monuments, mountain resorts, spas and water areas. However, the increased concentration of tourists in these localities may be ambivalent. A positive economic effect can be the reduction of unemployment and the development of local business in tourist attractions. These aspects lead to longer-term regional stability. The negative impact is mainly environmental pollution by carbon dioxide emissions. In some cases, there is also unwanted noise pollution, light smog and changes in local hydrogeology associated with unplanned development. With the growing popularity of travel, the demands on the quality and quantity of not only holiday accommodation are growing, which has led to a sharp rise in property prices in this segment. The study maps how the environmental aspect of the attractiveness of a holiday or tourist destination affects the value of residential real estate.
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    Review of clustering methods used in data-driven housing market segmentation
    (Polish Real Estate Scientific Society, 2023-09-08) Skovajsa, Štěpán
    There was already a huge effort spent to prove the existence of housing market segments, how to utilize them to improve valuation accuracy, and gain knowledge about the inner structure of the whole superior housing market. Accordingly, many different methods on the topic were explored, but there is still no universal framework known. The aim of this article is to review some previous studies on data-driven housing market segmentation methods with a focus on clustering methods and their ability to capture market segments with respect to the shape of clusters, fuzziness, and hierarchical structure.