Search Results (237)

This study empirically delves into whether residential heating methods significantly affect apartment prices in Uiwang City, a suburban city near the Seoul Metropolitan area, South Korea. Using data from 1256 apartment sales, where both district heating systems (DHSs) and individual heating systems (IHSs) coexist, a hedonic price equation was estimated to analyze the impact of the heating method choices on housing values. Various housing attributes, including physical, locational, and environmental factors, were controlled, and multiple regression models were compared to identify the best-performing specification. The results show that apartments equipped with a DHS are priced, on average, KRW 92 million (USD 72 thousand) higher than those with an IHS. The price difference corresponds to KRW 849 thousand (USD 665) per m² and possesses the statistical significance at the 5% level. Moreover, it is quite meaningful, representing roughly 11.2% of the price of an average apartment. These findings suggest that the use of DHS has a positive effect on apartment prices that reflect consumers’ preferences, beyond its advantages in stable heat supply and energy cost savings. This article provides empirical evidence that DHS can serve as an important urban infrastructure contributing to asset value enhancement. Although this study is based on a specific geographic area and caution must be exercised in generalizing its findings, it reports the interesting finding that residential heating method significantly affects housing prices. Full article

In this study, we extend the UTAUT2 model to explore the determinants of green purchase intention in Taiwan. By incorporating environmental concern, government support, and green trust, the model highlights how contextual and trust-based factors shape sustainable consumption. Based on 590 valid survey responses, analysis using covariance-based structural equation modeling reveals that performance expectancy, effort expectancy, social influence, price value, environmental concern, government support, and green trust all positively influence green purchase intention. Notably, green trust also mediates the relationship between the core UTAUT2 constructs and green purchase intention. In contrast, hedonic motivation and habit show no significant effects, suggesting that sustainable consumption has not become habitual or emotionally driven behavior in Taiwan. These findings emphasize the importance of rational evaluation, social context, and policy support in driving green behavior and offer practical implications for promoting sustainable consumption. Full article

This study investigated the intangible value transferred from urban megaprojects to surrounding residential property markets, focusing on Brisbane’s transformative urban regeneration projects currently in the development pipeline. The research objectives were twofold: first, to empirically investigate the dynamics of property markets influenced by urban megaprojects and second, to assess the impact of a specific case study on these markets through a longitudinal analysis of residential sales data. Drawing from environmental economics, the concept of willingness to pay (WTP) is used to quantify externalities associated with urban megaprojects. The research constructs a comprehensive dataset integrating geospatial and property-specific data. Through revealed preference methods, the intangible value transferred from mixed-use developments is identified and quantified via residential transaction prices. Utilising hedonic price modelling, this study systematically analysed residential transaction data to estimate implicit prices associated with spatial proximity to megaprojects. A comprehensive dataset integrating property-specific attributes, geospatial proximity measures, and temporal dynamics of project development phases underpins this analysis. This research and its findings advance the existing literature in several important dimensions. That is, this research represents the first microeconomic assessment of the property market’s impacts resulting from mixed-use megaprojects in Brisbane, offering novel empirical insights for both academic and practical applications, how urban megaprojects shape residential property values, and informing stakeholders involved in urban planning, policymaking, and real estate investment decisions. Practitioners and policymakers can leverage these insights to inform policy frameworks and strategic decisions. At the governmental level, the results offer applicable insights for urban revitalisation strategies, particularly relevant to central business districts undergoing similar developments. Private sector stakeholders can utilise these outcomes to anticipate market adjustments, managing supply and demand fluctuations more effectively. Full article

With the rapid development of digital technology, the use of digital learning resources has become increasingly widespread and is now an integral part of higher education. However, there is a lack of research on engineering students’ behavioral intention to use digital resources and their digital literacy. This study, which is based on two waves of longitudinal survey data from 422 Chinese engineering students, employs the unified theory of acceptance and use of technology 2 (UTAUT2) model to systematically analyze the factors influencing engineering students’ behavioral intention to use digital learning resources and explore the longitudinal relationship between this intention and digital literacy. The results show that engineering students’ behavioral intention to use digital learning resources positively predicts their digital literacy. Effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit are positively related to engineering students’ behavioral intention, whereas performance expectancy and price value do not have significant effects. The findings extend the application of the UTAUT2 model in the context of digital education and reveal a longitudinal link between the use of digital learning resources and digital literacy. This provides theoretical support and practical guidance for optimizing digital learning environments, enhancing digital literacy in engineering students, and improving the design of teaching resources in higher education, contributing to the development of engineering education in China in the digital age. Full article

Climate change and extreme rainfall events pose great pressures on a city’s resilience to flooding and waterlogging. Designed as a kind of green infrastructure to manage stormwater, urban sponge parks (USPs) in China have been demonstrated to have ecological and societal benefits, while their landscape economic values lack evaluation. Taking the real-estate choices surrounding six USPs in China as an example, an evaluation framework integrating text mining with housing introduction documents and hedonic price model (HPM) regression with housing prices was constructed to combine the stated preferences and revealed preferences of citizens when purchasing properties. The main findings include the following: (1) USPs do contribute to property appreciation, especially in newer urban areas, although they are not as strong as location and property characteristic factors; (2) the extent of the influence of USPs on houses decreases as the distance increases, with a maximum radius of 3 km; (3) a USP’s effects vary according to the urban and environmental context, as HPM with GWR (R² ranges from 0.203 to 0.679) outperforms the OLS method (R² ranges from 0.149 to 0.491), which evokes the need for more affluent and detailed analyses in the future. This study demonstrates the economic benefits of USPs and provides an evaluation approach based on citizen science data, which could contribute to the policy-making of USPs in China and promote the implementation of Nature-based Solutions. Full article

Using ArcGIS software to conduct spatial autocorrelation analysis, it was found that the price distribution of rural homestays in Suzhou is not random but shows apparent spatial clustering. Among the 81 rural homestays were 9 high-high clusters, 25 low-low clusters, 1 high-low outlier, and 5 low-high outliers. The hedonic price model is an economic model that breaks down goods or services into multiple attributes to estimate their prices. Based on this model, this paper further investigates the differentiated impacts and interactions between internal accommodation characteristics and external environmental attributes in the pricing mechanism of rural homestays in Suzhou. The results show that (1) the high-priced rural homestays in Suzhou are concentrated in the lake island resort with good natural environment and perfect infrastructure; (2) the location, facility quality, and network score of rural homestays have a positive impact on housing prices; (3) the parking lot of rural homestays hurts housing prices; (4) the quality of rural residential buildings and facilities has the most significant positive impact on housing prices. By comparing the hedonic price model of rural homestay and the heterogeneous preferences of consumers, this study provides rural homestay operators with effective room pricing strategies and marketing implications, provides policymakers with reference factors to promote the development of rural homestay industry, and has specific guiding significance for the sustainable development of the homestay industry. Full article

Urban sprawl and excessive reliance on motorization have led to many urban problems. The balance of supply and demand in the real estate market, as well as price fluctuations, also face many challenges. Urban rail transit not only alleviates traffic congestion and air pollution, but also significantly reduces residents’ commuting time, broadens urban accessibility, and reshapes the decision-making basis for residents when choosing residential locations. This study takes the 1st, 2nd, 3rd, 4th, 8th, 11th, and 13th metro lines that have been opened in Qingdao City as examples. It selects 12,924 residential samples within a 2 km radius along the rail transit lines. By using GIS spatial analysis tools and the multi-scale geographically weighted regression (MGWR) model, it analyzes the spatial differentiation characteristics of housing prices along the rail transit lines and the reasons and mechanisms behind them. The empirical results show that housing prices decrease to varying degrees with the increase in the distance from the rail transit. For every additional 1 km from the rail transit station, the housing price increases by 0.246%. Through model comparison, it was found that MGWR has a better fitting degree than the traditional ordinary least squares method (OLS) and the previous geographically weighted regression model (GWR), and reveals the spatial heterogeneity of the influence of urban rail transit on housing prices. Different indicator elements have different effects on housing prices along these lines. The urban rail transit factor in the location characteristics has a positive impact on housing prices, and has a significant negative correlation in some areas. The significant influence range of the distance to the nearest metro station on housing prices is concentrated within a radius of 373 m, and the effect decays beyond this range. The total floors, building area, green coverage rate, property management fee, and the distance to hospitals and parks in the neighborhood and structural characteristics have spatial heterogeneity. Analyzing the areas affected by the urban rail transit factor, it was found that the double location superposition effect, the networked transportation system, and the agglomeration of urban functional axes are important reasons for the significant phenomena in some local areas. This research provides a scientific basis for optimizing the sustainable development of rail transit in Qingdao and formulating differentiated housing policies. Meanwhile, it expands the application of the MGWR model in sustainable urban spatial governance and has practical significance for other cities to achieve sustainable urban development. Full article

This study quantifies the market values, or implicit prices, of honey quality features (e.g., organic and origin information, package-related features) and floral varieties for supporting beekeepers in differentiating their products to escape from price competition characterizing the Italian honey market. The research employed a sample of sales data, 660 observations collected from the Italian market, and a hedonic price model, estimated via Ordinary Least Squares, to assess the implicit prices of honey characteristics. A high premium price was recorded for honey with added royal jelly and propolis, as well as for “100% Italian” honey. In contrast, moderate price premiums were recorded for Protected Designation of Origin and organic honey. Furthermore, the floral varieties used largely affected the product price: the highest premium prices were estimated for the Manuka, Kanuka, and Tawari floral varieties. Price premiums above +50% were estimated for floral varieties such as Strawberry tree, Pine, Cistus, Tree of Heaven, Sainfoin, Marruca, and Solidago. Results suggest that honey quality features and some floral varieties can effectively differentiate products, supporting beekeepers to achieve higher revenues. This study offers empirical evidence of the extent to which floral varieties and other product characteristics affect the market price of honey using a dataset of secondary data, with the aim to support producers to improve their competitive position in the market. Full article

At the crossroads of technological innovation and established practice, property valuation is experiencing a significant shift with the introduction of artificial intelligence (AI) and machine learning (ML). While these technologies offer new efficiencies and predictive capabilities, their integration raises important legal, ethical, and professional questions. This paper addresses these challenges by proposing a structured framework for incorporating Explainable Artificial Intelligence (XAI) techniques into valuation practices. The primary aim is to improve their consistency, objectivity, and transparency to ensure the internal accountability of AI-driven methodologies. Drawing from the international valuation standards, the discussion centres on the essential balance between automated precision and the professional duty of care—a balance that is crucial for maintaining trust in and upholding the integrity of property valuations. By examining the role of AI within the property market and the consequent legal debates about and requirements of transparency, this article underscores the importance of developing AI-enabled valuation models that professionals and consumers alike can trust and understand. The proposed framework calls for a concerted cross-disciplinary effort to establish industry standards that support the responsible and effective integration of AI into property valuation, ensuring that these new tools meet the same high standards of reliability and clarity expected by the industry and its clients. Full article

This study aims to determine the effects of the variables within the UTAUT 2 model on the intention to use a Fully Electric Car. In this context, data were collected through survey forms from 401 white-collar workers who are considered to have a higher economic status. Initially, validity and reliability analyses were conducted on the scales used in the Smart PLS program, and subsequently, the hypotheses were interpreted using the results obtained from structural equation modeling. In this study, it was found that effort expectancy, social influence, perceived ease of use, hedonic motivation, and habit had a positive and significant impact on the intention to use electric vehicles. Performance expectancy has a negative and significant effect on the intention to use electric cars, while price has no significant effect. It was determined that the intention to use electric vehicles was found to mediate the relationship between perceived ease of use and actual usage behavior. This research can offer significant contributions to literature, particularly by examining the influence of habit on behavioral intention and the effect of hedonic motivation on electric vehicle usage intention. By testing the UTAUT 2 model in the context of electric vehicle acceptance, this study supports the universality and applicability of the model to various technologies. Emphasizing the role of variables such as hedonic motivation and habit in electric vehicle acceptance adds a new dimension to the UTAUT 2 model. Thus, it makes an important contribution to technology acceptance research. Full article

This study investigates how the simultaneous development of multiple urban megaprojects creates synergistic effects in residential property markets, with significant implications for urban planning and policy. Through an enhanced hedonic pricing model incorporating inter-project interaction terms, the research quantifies both individual and collective impacts of concurrent developments on property values. Analysis of comprehensive transaction data (2016–2022) reveals complex patterns of complementary and competing effects between proximate megaprojects, demonstrating that their combined impact differs substantially from the sum of their individual effects. The findings highlight the critical importance of coordinated planning approaches that consider inter-project dynamics when designing urban regeneration strategies. This research provides the first empirical measurement of megaproject synergy effects, offering valuable insights for policymakers and investors in optimizing the economic outcomes of transformational flagship buildings. Full article

The transition of global agriculture from yield-driven production to quality-driven systems has gained urgency, where premium pricing strategies offer pathways to enhance farmer incomes and promote sustainable practices. As a critical staple crop, rice exemplifies the challenges of aligning producer standards with consumer preferences to realize market premiums. This study systematically evaluates determinants of consumers’ willingness to pay (WTP) for premium rice, integrating analyses of attribute preferences, cognition perception, and purchasing experience. Utilizing survey data from 1714 consumers across four Chinese cities, we employ principal component analysis to identify key quality dimensions and ordered logit models to quantify their impacts. Hedonic pricing theory informs the estimation of implicit prices for specific attributes. The results reveal that intrinsic characteristics (like nutrition) and extrinsic cues (like the brand), along with consumers’ nutritional awareness, knowledge, and perceptions of quality-price correlation, jointly drive premium WTP. The mean acceptable premium reaches 4.52 yuan/500 g, with nutritional attention enhancements commanding the highest valuation (0.171 yuan/500 g). The findings underscore the necessity of standardized quality grading systems aligned with consumer preferences and targeted interventions to bridge information asymmetries. Policymakers are recommended to improve supply-side quality signaling through enhanced packaging and certification systems while strengthening demand-side nutrition education to facilitate value chain coordination and sustainable, high-quality development in agriculture. Full article

This study explores the public acceptance of autonomous vehicles (AVs) using the Unified Theory of Acceptance and Use of Technology 2 framework. Drawing on survey data from 1000 commuters in Seoul, South Korea, this study examines the influence of performance expectations, effort expectations, social influence, hedonic motivation, and facilitating conditions on the behavioral intention to adopt AVs. Structural equation modeling reveals that hedonic motivation (β = 0.56, p < 0.001), price value (β = 0.47, p < 0.001), and performance expectancy (β = 0.64, p < 0.001) are critical determinants of AV acceptance. Additionally, risk perception negatively impacts behavioral intention (β = −0.25, p < 0.001), while policy support (β = 0.51, p < 0.001) and facilitating conditions (β = 0.46, p < 0.001) demonstrate substantial positive influences. Demographic analysis highlights age and gender as significant moderators, with younger users prioritizing performance expectancy and being more sensitive to risk, while older users exhibit a shift from hedonic to utility-driven motivations as they age. Women exhibit greater sensitivity to policy support and economic factors, while men respond more strongly to environmental considerations. In addition, prior experience with advanced driver assistance systems amplifies the influence of enjoyment on facilitating conditions, whereas inexperienced users are more affected by perceived risks. These findings underscore the importance of tailored interventions that address demographic variations, enhance user satisfaction, and balance cost-effectiveness with safety assurances. This study provides insights into actionable strategies for policymakers and industry leaders to promote AV adoption and support the evolution of sustainable urban mobility systems. Full article

This study investigates the determinants of bottled water prices in Saudi Arabia using a hedonic price model, analyzing data collected from nine retail stores in Al-Ahsa Governorate. The analysis of 499 observations reveals that physical attributes, such as bottle size, packaging material (glass and aluminum), non-standard caps, and packaging type (multipack and box), significantly influence the price. Specifically, larger bottles, multipacks, and boxes are associated with lower per-liter prices, while glass and aluminum packaging and non-standard caps command higher prices. Chemical characteristics of bottled water, including total dissolved solids (TDS), sodium, and pH, have a minimal impact, and in some cases, they exhibit a negative influence on prices. Crucially, market dynamics, including the source of origin (imported vs. domestic) and the type of retail store, impact prices significantly. Imported bottled water is priced higher than domestically produced varieties, while products sold in hypermarkets are cheaper than those in other retail stores. Moreover, when analyzing domestic and imported bottled water separately, physical characteristics lose their statistical significance for imported products, and chemical characteristics become irrelevant for domestically produced bottled water. The study highlights the complex interplay of product characteristics and market factors shaping bottled water prices, providing insights for both the bottled water industry and policymakers. Full article

Urban greenspaces, such as parks and other public vegetated spaces, provide respite from the built environment for residents and visitors. Lesser-known urban greenspaces are community-managed open spaces (CMOSs), such as play lots, community gardens, and memorial gardens. This study investigated the effect of the distance to and size of parks and CMOSs on residential house prices in Baltimore, MD, in 2016–2017 using a hedonic price model. This is the first study of an urban city comparing parks and CMOSs. The study included 21,116 houses sold and revealed that park proximate price premiums ranged from 7.73% to 11.01% for distances of up to a 1/2 mile, and the CMOS proximate price premiums were 8.69% and 8.96% for distances of up to 1/8 and 1/4 miles, respectively. Moreover, both parks and CMOSs revealed a buyer preference of a 1/8 to 1/2 mile distance from these urban greenspaces. Small- to medium-sized parks, less than 9.65 acres, increased house prices by approximately 2.36%, and small CMOSs, less than 0.24 acres, increased house prices by 5.93%. These results confirm that parks and CMOSs provide economic benefits in addition to their social, health, and well-being benefits and suggest that CMOSs are a viable economic development strategy for communities. Full article