Search Results (12)

Due to the increase in recreational demands, the significance of protected areas and forests with recreational potential in forests increased with the demands of nature tourism, which in turn provided new income sources to the forestry industry. In the current study, the economic values of the Uzungöl Nature Park’s lake view, an international tourist destination, were estimated using the hedonic pricing method. In the study, 188 questionnaires were conducted with 89 businesses, and the hedonic price function (HPF) was determined based on the study data collected from the businesses in Uzungöl Nature Park. It was estimated that the mean lake view in-room accommodation price for the hotels in Uzungöl Nature Park was USD 207.38 and the lake causes an increase of $2.8 per square meter and $144.67 in total on the room price of the hotels. The study findings demonstrated that the lake view was a desirable quality for hotel rooms, which is reflected in the prices in Uzungöl. The significant contribution of the lake view to room prices would support the planning and management of protected areas that are usually rich in natural resources. Determining the economic value of the lake view will enable business owners operating in the region or those planning to establish new businesses to make more informed pricing strategies. It will also strengthen hotel owners’ marketing campaigns and enable them to think more rationally about new investments (such as adding rooms or services). Business owners will be able to optimize their rooms based on lake views in order to offer more lake-view rooms to customers. Determining the economic value of the lake view will raise awareness about the protection of natural areas. By investing in eco-friendly and sustainable practices, hotel owners will contribute to the conservation of natural resources. The value estimates determined in the present study would also contribute to the employment of total forest value calculations and resource accounting systems. Full article

Urban park green spaces have the functions of improving the urban ecological environment and providing recreational services, and at the same time, they have a certain effect on the value of the surrounding residential property. To quantitatively assess the value of the landscape premium function of park green space, many scholars have carried out research exploration and adopted a variety of methods (such as the contingent valuation method (CVM), travel cost method (TCM) and hedonic price method (HPM)), which have developed from simple theoretical models with single factors to complex empirical models with multiple factors. Among them, the hedonic price method has become the mainstream research method, and in recent years, it has been widely adopted in combination with GIS technology. In terms of research objects, single park green space or multiple park green spaces in large cities are the main focus, while there are fewer studies on park green spaces in built-up areas of small and medium-sized cities. In terms of research content, there are more studies on the value-added coefficient of landscape premium and influence distance, and there are fewer studies on the total value of landscape premium. This article aims to calculate the total landscape premium value of all park green spaces in the built-up areas of small and medium-sized cities, proposing a complete and operable accounting system for the functional value of park green space landscape premiums by combining GIS with a hedonic pricing model and remote sensing image interpretation methods. For the first time, a method for interpreting the height of residential buildings within the benefit range of landscape premium through remote sensing images is proposed, and then the floor area ratio of residential plots is estimated, so as to estimate the total area of actual beneficial buildings. Therefore, this paper takes Chifeng City, a small and medium-sized city, as a case study, and empirically demonstrates the assessment of the landscape premium function of parks and green spaces in the built-up area of Chifeng City by using this accounting system. Research shows that this method has certain feasibility, not only calculating the total value of landscape premium but also addressing the issue in existing studies where all areas within the potential range of landscape premium function are counted as appreciated areas, leading to an overestimation of the premium. It further advances the accuracy of accounting for the value of landscape premium function of urban park green space and provides theoretical reference for the planning and construction of urban park green space. Full article

The global offer of legume-based snacks has sharply increased in recent years. However, to date, few studies have focused on the relationship between product supply and demand concerning the importance of attributes of such innovative foods. In this research, we identified the key internal and external determinants that affect legumes snack (LS) price and choice by Italian industries and consumers, respectively. In parallel, we investigated their preferences and perceptions towards these foods. We used the hedonic price model (HPM) and the discrete choice experiment (DCE) approach for these purposes, respectively. HPM revealed that the monetary value of LS was determined to greater significance by the: (i) size of the package; (ii) presence of rice, presence of lentils; (iii) presence of the nutritional information; and (iv) the discount shops as site of purchase. DCE revealed that the: (i) origin certification, (ii) recyclability of the package, and (iii) use of extra virgin olive oil of LS provided Italian consumers a high utility, for which they were willing to pay an average price premium of EUR 3.85, 3.64, and 1.87, respectively. On the contrary, the sunflower oil induced a decrease in their function utility. As such, this paper contributes to define potent market-segmentation strategies and to deliver effective private and public nutrition interventions for healthy eating. Full article

An investigation into the pricing mechanism of Airbnb is crucial for achieving the sustainable development of sharing economy accommodations and has great academic and practical significance. The existing pricing studies on sharing economy accommodation have identified a set of important factors impacting prices based on the hedonic price model. However, the spatial scale of the impact of various hedonic attributes on Airbnb listing prices is not yet clear. This study takes Beijing, China, as a case study; develops a conceptual framework that incorporates four categories of hedonic attributes; and uses a spatial heterogeneity perspective to investigate the multiscale spatial effects of various attributes on the prices of Airbnb listings. Our findings revealed the following: (1) The explanatory power of different categories of attributes towards listing prices varies from high to low, as follows: functional attributes, locational attributes, reputational attributes, and host status attributes, among which the functional attributes are the most important determinants of Airbnb listing prices. (2) There are multiscale, spatially heterogeneous relationships between Airbnb listing attributes and prices. Specifically, the functional attribute variables have local influencing scales, the reputation attribute variables have regional scales, and the variables of host status and locational attributes have global scales. (3) Compared with ordinary least squares (OLS) regression and geographically weighted regression (GWR), multiscale geographic weighted regression (MGWR) improves overall modelling ability by introducing multiple scales and is better suited to illuminating the hedonic pricing of sharing economy accommodations. This study provides new insights into the spatially varied relationships between listing attributes and Airbnb listing prices, which can deepen our understanding of sharing economy accommodation and help hosts formulate location-based pricing strategies. Full article

Electric vehicles can be a solution to certain social problems in Indonesia, such as pollution and an increase in consumption of energy from fossil fuels, which cannot be met by domestic production. The discussion of the TPB theoretical model, UTAUT2, and risk perception, using the structural equation modeling (SEM) method, in this study aims to provide an overview of the factors that drive interest in adopting electric vehicles in Indonesia. Data were collected from 526 respondents in various cities located in Indonesia. The results showed that the model can estimate the study variables adequately. The constructs of TPB such as attitude toward use (ATU), subjective norm (SBN), and perceived behavior control (PBC) positively affect interest in using electric vehicles. Meanwhile, ATU is influenced by performance and effort expectancies, hedonic motivation, price value, as well as functional, financial, and social risks. Another factor, known as PBC, is influenced by certain facilitating conditions. The ATU factor is the most influential on the use of electric vehicles, therefore factors such as performance expectancy, effort expectancy, hedonic motivation, price value, functional risk, financial risk, and social risk need to be properly analyzed. Full article

It is generally accepted that the perception of homeowners towards certain potential risks or amenities fades as distance from the risk or amenity increases. This study aims to illustrate the distance–decay pattern with an appropriate mathematical function. Distance–decay functions and parameters that yield the minimum residual sum of squares (RSS) for a given regression model are considered to be the optimal approximation for the pattern of decay. The effect of flood risk and mass rapid transit (MRT) accessibility on residential housing prices in Taipei, Taiwan, are used as examples to test the optimization process. The results indicate that the type of distance function affects both the significance and the magnitude of the regression coefficients. In the case of Taipei, concave functions provide better fits for both the flood risk and MRT accessibility. RSS reduction is up to 10% compared to the blank. Surprisingly, the impact range for the flood risk is found to be larger than that for MRT accessibility, which suggested that the impact range of perception for uncertain risks is larger than expected. Full article

Coastal erosion and inundation represent the main impacts of climate change and the consequential sea level rise (SLR) on beaches. The resultant deterioration of coastal habitats and decline in beach tourism revenue has been a primary concern for coastal managers and researchers. Nevertheless, the extent of SLR on beach tourism in Egypt remains relatively unknown. Therefore, this study investigates the relationship between beach width shrinkage due to SLR and the loss in tourist resort revenue. We use the hedonic pricing approach, which combines economic and environmental variables, to determine the environmental impact on beach tourism along 14 km of the coast of Sahl Hasheesh and Makadi Bay, Hurghada, Egypt. The resort revenue depends on the cumulative benefits from the market price of the resort rooms, which is a function of morphological variables and tourism variables. Three regression models (semi-log, double-log, and custom-log) were used to select the most appropriate functional hedonic model. Three coastal slopes were considered (0.03, 0.06, and 0.12) to address the uncertainty in beach width. When 0.06 coastal slope is used, the expected losses in revenue are 84,000, 220,000, and 546,000 USD/day period (representing 3%, 7%, and 18%) for 2030, 2050, and 2100, respectively, considering the lowest scenario representative concentration pathway (RCP2.6); for the worst case (RCP8.5 SLR), the expected losses are 142,000, 369,000, and 897,000 USD/day period (representing 5%, 12%, and 30%) for 2030, 2050, and 2100, respectively. Full article

This study aims to offer a new estimate of the hedonic price function of residential areas in Japanese metropolitan areas, focusing on the reasons for residential preferences. More specifically, it introduces two new explanatory variables—‘regional vulnerability’ and ‘accessibility to destination stations’—and determines their usefulness. Based on the evaluation done in this study, the hedonic price function mentioned above showed 60% interpretability (as compared to 52% interpretability by hedonic price function using only conventional explanatory variables.) In addition, the significance level of both the explanatory variables was low, and the land price changed by 9% as the regional vulnerability changed by 1 grade. Furthermore, residents placed great emphasis on both variables. This made it evident that the introduction of the two explanatory variables that reflect the reasons for residential preferences specific to Japanese metropolitan areas was reasonable. Full article

Street greenery is a component of urban green infrastructure. By forming foundational green corridors in urban ecological systems, street greenery provides vital ecological, social, and cultural functions, and benefits the wellbeing of citizens. However, because of the difficulty of quantifying people’s visual perceptions, the impact of street-visible greenery on housing prices has not been fully studied. Using Beijing, which has a mature real estate market, as an example, this study evaluated 22,331 transactions in 2014 in 2370 private housing estates. We selected 25 variables that were classified into three categories—location, housing, and neighbourhood characteristics—and introduced an index called the horizontal green view index (HGVI) into a hedonic pricing model to measure the value of the visual perception of street greenery in neighbouring residential developments. The results show that (1) Beijing’s homebuyers would like to reside in residential units with a higher HGVI; (2) Beijing’s homebuyers favour larger lakes; and (3) Beijing’s housing prices were impacted by the spatial development patterns of the city centre and multiple business centres. We used computer vision to quantify the street-visible greenery and estimated the economic benefits that the neighbouring visible greenery would have on residential developments in Beijing. This study provides a scientific basis and reference for policy makers and city planners in road greening, and a tool for formulating street greening policy, studying housing price characteristics, and evaluating real estate values. Full article

Innovative solutions have been implemented to promote sustainable mobility in urban areas. In the Nantes area (northwestern part of France), alternatives to single-occupant car use have increased in the past few years. In the urban area, there is an efficient public transport supply, including tramways and a “busway” (Bus Rapid Transit), as well as bike-sharing services. In periurban and rural areas, there are carpool areas, regional buses and the new “tram-train” lines. In this article, we focus on the impact on house prices of these “sustainable” transportation infrastructures and policies, in order to evaluate their values. The implicit price of these sustainable transport offers was estimated through hedonic price functions describing the Nantes urban and periurban/rural housing markets. Spatial regression models (SAR, SEM, SDM and GWR) were carried out to capture the effect of both spatial autocorrelation and spatial heterogeneity. The results show patterns of spatial heterogeneity of transportation offer implicit prices at two scales: (i) between urban and periurban/rural areas, as well as (ii) within each territory. In the urban area, the distance to such offers was significantly associated with house prices. These associations varied by type of transportation system (positive for tramway and railway stations and negative for bike-sharing stations). In periurban and rural areas, having a carpool area in a 1500-m buffer around the home was negatively associated with house prices, while having a regional bus station in a 500-m buffer was non-significant. Distance to the nearest railway station was negatively associated with house prices. These findings provide research avenues to help public policy-makers promote sustainable mobility and pave the way for more locally targeted interventions. Full article

The Hedonic Pricing Method is one of the principal assessment methods for evaluating services and resources not normally exchanged on the market. However, the method is often unable to account for the great variety of qualities in an urban context and faces scarce and heterogeneous market data. This paper presents a model for the valuation of benefits generated by environmental and urban improvement investments adopting a mixed hedonic-multi-attribute procedure for modeling a value function of urban real estate values. The peculiarity of the model is that the independent variables are aggregated indicators, which synthetize more detailed characteristics. Using the expertise of real estate agents, all relevant variables influencing real estate values were weighted and synthetized in a set of cardinal indicators. Next, market prices were used to calibrate a hedonic function that transforms the cardinal indicators into real estate values. The valuation model was integrated into a GIS for mapping the housing value, and its variation induced by urban investment. The proposed model pointed out plausible and robust results, in particular, the possibility to use any available information, such as location, position, technical and economic characteristics of buildings, and organize it in a flexible and transparent way, and to keep evident the role of each characteristic through the hierarchical structure of the model. The model was applied to the real estate market of Venice to test the effects of the MOSE project (Electromechanical Experimental Module) for the protection of Venice from high tides. The results of the application showed a relevant increase in real estate values in the center of Venice, especially related to property in ground floor units, of about 1.4 billion €. Full article

In the formulation of hedonic models, in addition to locational factors and building structures which affect the house prices, the generation of the omitted variable bias is thought to occur in cases when local environmental variables and the individual characteristics of house buyers are not taken into consideration. However, since it is difficult to obtain local environmental information in a small neighborhood unit and to observe individual characteristics of house buyers, these variables have not been sufficiently considered in previous studies. We demonstrated that non-negligible levels of omitted variable bias are generated if these variables are not considered. Full article