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Abstract

Research background: Mass appraisal is a process in which multiple properties are appraised simultaneously, with a uniform approach. One of the tools that can be used in this area are multiple regression models. In the valuation of real estate features are often described on an ordinal or nominal scale. Replacing them with dummy variables with an insufficient number of observations leads to multicollinearity. On the other hand, there is a risk of overfitting the model. One of the ways to eliminate or weaken these phenomena is to introduce regularization based on a model’s penalization for the high values of its weights.

Purpose: The aim of the study is to verify the hypothesis whether regularized regression reduces the errors of property valuation and which of the analyzed methods is the most effective in this context.

Research methodology: The article will present a study in which two ways of regularization will be applied – ridge and lasso regression, in the context of their impact on the errors of property valuation. The analyzed data set includes over 300 land properties valued by property appraisers. The key aspects of the study are the selection of optimal values of the regularization parameter and its influence on model’s errors with a different number of observations in the training sets.

Results: The study showed that regularization improves valuation results and, more specifically, allows for lower average absolute percentage errors. The improvement of model effectiveness was more pronounced in the case of ridge regression. An important result is also that regularization has provided a higher accuracy of valuation compared to multiple regression models for smaller training sets.

Novelty: The article confirms the effectiveness of regularization as a way to eliminate the problem of multicollinearity or overfitting of the model. The results showed that ridge regression can be an effective way of modelling the value of real estate. Especially in the case of a small amount of market data, which is an important conclusion in the context of the real estate market.

Abstract

Neighbouring local property markets are not separate realities. They influence one another and create an interrelated system of supply and demand. Some of these interrelations are convergent, while others result in contradictory trends on the markets. Convergence is a term denoting a process of some phenomena approaching its normative level. Tests for the presence of convergence help to assess if the objects under observation show resemblance in the context of the observed phenomenon, and to find out how long it takes for this resemblance to be complete. In this paper, I propose the application of methods normally used in tests for convergence for the purpose of the analysis of trends of the average residential property prices in some districts in Szczecin over the time range of 2006–2009, that is during the housing bubble on the residential property market. The study will provide information if such a market phase encourages price convergence.

Abstract

Research background: The article discusses the issue of the identification and measurement of market characteristics of real estate for valuation purposes. This problem is the most difficult stage of the whole valuation process in terms of both a substantive, methodological and analytical basis.

Goal: The aim of the research is to outline and explore on the basis of literature studies as well as developed problems to be solved in the process of mass valuation together with the presentation of an exemplary solution.

Methodology: In the theoretical part a hypothetical-deductive method which consists of developing a certain hypothesis and deducing its consequences was applied. The empirical section uses the method of scientific discussion among scientists and practicing valuers and, for the presentation of the results; some graphical methods were used for a statistical analysis.

Results: As a result of the conducted research, criteria to be used in identifying and classifying market characteristics for the purposes of valuation were identified and a set of market characteristics of properties was developed along with a method of identifying their states for the purposes of mass valuation.

Novelty: The article proves that the problem of the identification and classification of market characteristics of real estate for valuation purposes is extremely important from the point of view of the valuation process and the results obtained as a result of it as well. In addition, for some features, it is proposed to develop special measures such as the plot shape attractiveness ratio. This meets the problem of the objective measurement of market features of real estate. In relation to other features, the legitimacy of the expert approach was pointed out.

Abstract

Considering the significant growth of artificially built attractions in Thailand, the objective of this research is to study architectural design and perceived value toward revisit intention in artificially built attractions. The designs of these attractions are derived from foreign countries that would not be suitable for the Thai environment. Nevertheless, this could be considered through the perspective of marketing growth, which depicts artificially built attractions receiving good response from visitors. Therefore, it was essential to analyze customers’ attitude toward their travel and revisit intention to artificially built attractions. The research uses the quantitative method with 342 participants who visited the artificially built attractions. The result indicates that emotional, functional, and social values influence the revisit intention. Furthermore, the architectural design had a positive influence on emotional and social values. Though architectural design had no direct influence on revisit intention, it had indirect influence via emotional and social values. By analyzing the independent and dependent variables, it was indicated that, although all independent variables affect dependent variables, the scores of each of these factors were not high. Therefore, it can be concluded that artificially built attractions still have space for improvement in terms of perceived value in order to foster revisit intention.

Abstract

Sky-scrapers are rising in the panorama of big modern cities more and more often, becoming a symbol of dynamic growth and prestige. High-rise development appears to be an answer to the expanding demand for new residential and commercial space as urban land prices continue to go up and the availability of land decreases.

This article aims to identify factors affecting the choice of optimal building height in the context of economic effectiveness. It also presents factors that determine the implementation of high-rise development projects. Given the complexity of this subject matter, emphasis is placed on its economic dimension.

Abstract

Predicting demand on the residential real estate market and the behavior of the purchasers requires a wide knowledge of both the economic mechanisms and psychology of decision-making. Decisions on the real estate market are often made by people without professional skills, and using simplified strategies. However, the decision-making process, on top of its heuristic nature, is dynamic and changing. As a result, a discrepancy in the preferred characteristics of planned and actually bought real estate can be observed. Such a discrepancy can be explained with the occurrence of the compensation process. The aim of this article was to recognize and describe the compensation process on the example of the suburban residential real estate market. The aim was achieved by analyzing the preferences of potential buyers in terms of particular characteristics of the location of suburban plots destined for single-family housing (respondents divided into age groups: 25 and 26-40), analyzing the real settlement trend in the suburban zone (the result of actual transactions) and comparing the results, including compensation.

Abstract

This article analyzes the spread of market phenomena, market tensions and trends between real estate markets on the global scale. At the theoretical level, the main aim of the study was to determine the nature of the relationships between housing markets throughout the world. The main research goal was to identify and describe the strength of the correlations between the real estate markets of the world’s 10 largest economies (countries with the highest GDP). The analyses were conducted with the use of Pearson’s correlation tests, Granger causality tests and graphs. Our results revealed strong correlations between most of the markets; however, we did not find strong evidence for causality. In a globalizing world, national economies will become increasingly interconnected, which will indirectly influence the housing market.

Abstract

The aim of this analysis is to examine the characteristics of the Airbnb network, to verify the share of Airbnb offers that belong to the sharing economy and to identify the differences between the spatial distribution of the Airbnb network and the traditional hotel industry. The article is based on a unique dataset of web-scraped data on Airbnb listings in Warsaw (Poland), combined with district-level official statistics on the hotel industry. The analysis shows that only approximately 11% of offers belong to the sharing economy (“individuals granting each other temporary access to their under-utilised assets”), while at least one third of offers are provided by professional firms. The Airbnb network shows a strong centre-periphery pattern, with 75% of offers located within a range of 4.3 kilometres from the centre. The spatial concentration of Airbnb offers is strongly driven by their distance from metro lines, while it is weakly related to the amount of living space. On the district-level, the spatial distribution of Airbnb listings is correlated with that of the hotel industry, although Airbnb contributes to a more even spread of tourism in the city. The major contribution of this analysis is its presentation of the size and characteristics of the platform, which is essential for data-driven policy making.

Abstract

Research background: The development of business on a local level depends on a variety of factors, which as is often the case are shaped by the local authorities. An example of activities carried out by local governments in order to help develop businesses is the management of the spatial resources in a given municipality in such a way as to facilitate starting and developing companies.

Purpose: The principal objective of this study has been to identify how local authorities and businessmen perceive the role of conditions associated with the municipality’s spatial policy in terms of starting and conducting a business.

Research methodology: The research results rely on primary data acquired by conducting a survey based on a questionnaire designed by the authors.

Results: The results permitted to demonstrate differences and similarities among the opinions of our respondents concerning factors linked to the spatial policy of a municipality that have an impact on decisions to set up and develop companies. Among the location factors, the most important ones, according to both local governments and businessmen, were the state of the local infrastructure, such as IT, transportation, communication, waterworks and sewers, power supply.

Novelty: The confrontation of the replies provided by local authorities and by entrepreneurs concerns spatial policy, and the territorial scope of the research covering the whole of Poland, the different types of enterprises from various branches are the innovative element of the study.

Abstract

Construction companies are important economic actors in every country. Their activity translates into employment levels, tax revenues, and the provision of new spaces that require further expenditure on equipment, thus stimulating consumer spending. The activity of construction companies depends on the demand for space, the state of the economy and the financial market. Undoubtedly economic disturbances in the form of a recession have a significant impact on construction activity. The authors were interested in whether the boom and recession in the selected countries were similarly reflected in the activity of construction companies. In particular, they were interested in residential construction activity, although it was not possible to select companies that would only deal with residential construction. The authors selected four post-socialist countries and two countries which are called winners of the integration process due to their enormous economic growth. The authors outline the residential construction and construction sector results and activity in the Czech Republic, Poland, Slovakia, Hungary, Spain and Ireland, and draw a wider picture for analyses of construction companies’ financial results for the years 2003-2012. This period was chosen because it covered periods of both boom and bust. All enterprises were part of the sector denoted in the Amadeus database as primary code: Eurostat NACE Rev. 2 with codes: 41 - Construction of buildings: 4110 - Development of building projects, 4120 - Construction of residential and non-residential buildings. Due to the specificity of the construction sector the authors divided the surveyed enterprises into two groups – all companies; and only large and very large companies. It was not possible to separate data specifically with respect to residential construction companies.