Preferences For Amenities Research Articles

Motivations in transition: destination choices of inter-provincial migration among Chinese older adults

Despite the growing interest in the migration of older adults in China, the intricacies linking migration motivations with destination choices remain insufficiently explored. Drawing from China’s unique context, we categorize inter-provincial older migrants into three types: employment-led, dependent, and lifestyle. Using microdata from the Sixth Population Census of 2010 and the 1% Population Sampling Survey of 2015, we examine their evolving motivations and corresponding shifts in destination preferences. The analysis shows an increase in lifestyle-oriented migration and a decrease in dependent migration, while employment-led migration has remained stable relative to the total. Older migrants seeking employment tend to favor destinations further south, prioritizing regional economic conditions. In contrast, those motivated by lifestyle factors exhibit a broader range of destination choices, largely due to their preference for amenities. Dependent older adult migrants consider both job-related and amenity-related factors and demonstrate a stronger tendency to relocate to the east. Amenity-related factors have increasingly influenced the destination choices across all three types of migration over time. Our findings provide deeper insights into the intricacies of migration in old adulthood and highlight the need for tailored policymaking.

체류형 관광자의 어메니티 인식과 만족 및 행동의도에 관한 연구 - 제주 체류 한달살기 경험자를 대상으로

The purpose of this study is to examine the impact of amenity perceptions of long-stay tourists on tourism satisfaction and behavioral intention. As long-stay tourists stay in a certain area for a certain period of time and engage in tourism behaviors, they are likely to strengthen their relationship with the area and develop into a settled population. Therefore, we set up amenities that represent local characteristics as spatial resources, and examined how long-stay tourists perceive the amenities in Jeju, and how their tourism satisfaction and behavioral intentions change according to their perceptions of the amenities. To achieve the objectives, a survey was conducted among long-stay tourists in Jeju during the month of April 2024, and 230 idle copies were obtained. The results of the empirical analysis showed that first, amenity factors have a significant effect on tourism satisfaction. Among the amenity factors of environment, convenience, and culture established in this study, environment has the most significant effect on satisfaction. Second, tourism satisfaction has a significant effect on behavioral intention. These results have academic implications for the development of a grounded theory of long-stay tourists. In addition, given that local amenities have a significant positive effect on tourism satisfaction and behavior, identifying the amenity preferences of long-stay tourists can be used as basic policy data for attracting a permanent population to a region.

Willingness to fight on: Environmental quality in dynamic contests

AbstractWe show that the prevalence of prolonged tennis contests drops sharply when the ambient environment deteriorates through heat or pollution. We develop a multi‐battle dynamic model to investigate how the disutility from a protracted competition shapes agents' willingness to fight on. Our theory predicts that a poor environment amplifies the momentum of a competitor's head start. We show how model primitives including preferences for environmental amenities can be inferred from battle‐to‐battle transition probabilities. We find that heat and pollution affect incentives to compete strategically. In a contest between equally able rivals at the median prize of $15,100, the value of a head start is $130‐370 higher in a degraded environment compared with a climate‐controlled one.

서울시 생활인구와 도시 씬의 영향 관계 연구

This study analyzes the relationship between the movement of the living population and cultural consumption in Seoul from the perspective of the urban scene. The movement of the living population in a city is an interaction created by individual choices and regional characteristics, and it can be said to be an essential element fora city to remain alive. This can be seen as playing the same role as blood circulation in the human body, and smooth movement leads to vitality and vitality in the city. This study examined how the movement of the living population in Seoul and the urban scene are connected by utilizing the concept of the urban scene, which is the main analytical framework for explaining urban culture. As a result of the study, it was possible to confirm the significant influence of the urban scene on the living population.In particular, significant effects of self-expression scene and deviance scene can be confirmed in the total living population, daytime and nighttime living population, and through this, people's preference for amenities that reveal personal taste and identity can be inferred. In addition, it was confirmed that the influence of the urban scene becomes clearer as the previous generations are passed on to the later generations. As a result of this study, policy implications for the influence of urban amenity composition and cultural characteristics on urban vitality are presented. The study can be expected to help explore the possibility of utilizing the urban scene in urban planning and long-term vision.

Analyzing Digital Features Of Accommodation Products Leading To Consumer Purchase

Accommodation industry experiences shifts in the customer preferences as digital era of e-commerce arrives. This shift forces business to focus more on integrated service delivery that leverages technology and applications. This further opens the opportunity to use customer narratives in providing valuable insights on what aspects these accommodation providers have to consider. This study explored the narratives from accommodation customers using qualitative analysis. Thirty-two (32) customers were purposively sampled to elicit information-rich narratives through one-on-one interviews. Findings indicated that reliable and fast internet access is particularly crucial for customers who have remote work responsibilities and those who heavily rely on the internet for communication purposes. Customers value the availability of digital resources such as laptops and computers, especially for situations where work or communication emergencies arise. Addressing customers' concerns about internet security and catering to their preferences for digital amenities can lead to increased customer satisfaction, positive reviews, and ultimately boost bookings and revenue for accommodations. It is essential for accommodation providers to stay technologically relevant and continuously adapt to meet customers' evolving digital needs to remain competitive in the ever-changing hospitality industry. By doing so, they can establish a stronger position in the market and create a positive impact on their overall business performance.

City parks and slow streets: A utility-based access and equity analysis

During the spring and summer of 2020, cities across the world responded to the global COVID-19 pandemic by converting roadway facilities into open pedestrian spaces. These conversions improved access to public open space, but measuring the variation in that improvement among different populations requires clear definitions of access and methods for measuring it. In this study, we evaluate the change in a utility-based park accessibility measure resulting from street conversions in Alameda County, California. Our utility-based accessibility measure is constructed from a park activity location choice model we estimate using mobile device data – supplied by StreetLight Data, Inc. – representing trips to parks in that county. The estimated model reveals heterogeneity in inferred affinity for park attributes among different sociodemographic groups. We find, for example, that neighborhoods with more lower-income residents and those with more residents of color show a greater preference for park proximty while neighborhods with higher incomes and those with more white residents show a greater preference for park size and amenities. We then apply this model to examine the accessibility benefits resulting from COVID-19 street conversions to create a set of small park-like open spaces; we find that this has been a pro-social policy in that Black, Hispanic, and low-income households receive a disproportionate share of the policy benefits, relative to the population distribution.

Do preferences for urban amenities differ by skill?

Abstract By investing in urban amenities, city-level policies often aim to attract highly skilled workers. However, studies relying on revealed preferences struggle to provide causal evidence that skilled workers value urban amenities more than less skilled workers. Therefore, we use a stated-preference experiment with hypothetical job choices between two cities that differ in wages, urban amenities and economic dynamism. We find that respondents are willing to forgo a significant fraction of their wages for better urban amenities. Most strikingly, preferences do not differ systematically by skill level. Hence, the higher fraction of highly skilled workers in amenity-rich places stems from the inability of low-skilled workers to move to and afford living in their preferred locations.

Does housing policy impact income sorting near urban amenities? Evidence from Vienna, Austria

Local amenities capitalize into housing values and form the foundation for income and preference-based sorting of residents into communities. Ellickson’s single-crossing property establishes how household sorting leads to correlation between income and preferences for amenities. For amenities including urban green, metro stations and centrality, income-based sorting describes the process by which higher-income residents choose to locate in close proximity to higher levels of amenities. Using Vienna as an example, we empirically investigate the role housing policies have on this expected pattern of sorting. We find that the provision of municipality housing and capped rents reduces income gradients between block groups adjacent to amenities and those further away while we do not find a significant effect associated with limited-profit housing. For policymakers, this suggests that policy design plays a critical role in ensuring availability of local amenities across income groups while simultaneously confirming the single-crossing result holds despite the existence of significant market regulations.

Location Based Recommendation System with machine learning.

Machine learning allows us to give vast volumes of data to computer algorithms and have them assess and make data-driven judgments and recommendations entirely based on the incoming data. This project will employ machine learning to analyze geolocation data and user preferences in order to provide the user with intelligent recommendations. In today's fast-paced and hectic world, it's common to be too exhausted to prepare a home-cooked supper. Even if you eat home-cooked meals every day, it's not uncommon to desire to treat yourself to a decent dinner now and then for social or recreational reasons. Consider the instance of someone who has recently relocated to a new location. They already have particular tastes and interests. . If a person lives near his favorite outlet, it will save him and his food providers a lot of time and effort. This project involves categorizing popular snack destinations for incoming students based on their mood and preferences for amenities, affordability, and proximity to the place using K-Means Clustering to find the easiest food location for students in Greater Noida (or any other city of your choice) by using K-Means Clustering to find the easiest food location for students in Greater Noida (or any other city of your choice) by using K-Means Clustering to find the easiest food location for students in Greater Noida.

A test–retest analysis of stated preferences in uncertain times

In environmental valuation, the issue of the temporal stability of stated preferences to changes in environmental (dis)amenities is important because their results can be employed to inform decision-making. This includes cost–benefit analysis for large infrastructure projects such as coastal protection. A couple of studies have investigated stability of stated preferences over varying time periods. However, less evidence is available for temporal stability of stated preferences for (dis)amenities in uncertain times, i.e., times that are characterized by larger degrees of uncertainty regarding the (near) future. Using a choice experiment on coastal adaptation to climate change, this paper examines the test–retest reliability of individual preferences and resulting welfare estimates over the course of the Covid-19 pandemic. We do so by surveying the same respondents at two points in time five months apart during the ongoing pandemic. Using a latent class model, we find similar preference heterogeneity patterns but different class sizes. While the welfare measure of an adaptation scenario that focuses on safety increases across survey waves, scenarios that centre on recreation or nature have decreasing welfare effects. This suggests that individuals set other priorities in uncertain times. • We study temporal stability of stated preferences during the COVID-19 pandemic. • We record preferences for coastal adaptation to climate change at the Baltic Sea. • We find similar preference heterogeneity patterns for both survey waves. • In the second wave, however, more respondents focus on the heightening of dykes. • Overall, results point to an increased valuation of safety during uncertain times.

Urban Transformations and Complex Values: Insights From Beirut

Through an urban renewal process driven by a well-resourced Lebanese diaspora and foreign investment, Beirut has undergone conspicuous morphological densification, characterised by parcel aggregation and exploitation of building height. Planning agencies have contributed to these transformations, deliberately involved in the production of illegality, and contributing to unplanned urban development. Although recent literature has substantially furthered our understanding of deregulated planning in Beirut, little is known of the preferences of residents with regards to the urban development process. This article sheds light on how morphological densification affects the complex values attached by residents to their urban environments using a novel data set and mixed-methods approach. It explores how dramatic urban restructuring affects resident values of architectural amenities and neighbourhood belonging. Findings show that although living in areas with different rates of building change does not affect preferences for architectural amenities, it affects resident socio-political activism towards the preservation of their built environment. Residents living in areas with high building-change rates had almost 50% lower odds of being willing to stop new construction near their location of residence because of their lack of confidence in the planning system. Neighbourhood belonging is not significantly affected by construction rates, but substantially increases both with the number of years lived in a neighbourhood and in locations with better building conditions, confirming a role for the built environment.

Heterogeneous Preferences for Neighborhood Amenities: Evidence from GPS data

Heterogeneous Preferences for Neighborhood Amenities: Evidence from GPS data

Simulation of pedestrian accessibility to assess the spatial distribution of urban amenities

A city can be perceived as a framework for the everyday activities of its residents, whose movements create complex network patterns as consequences of their individual decisions. Given that there are apparent differences in the use of urban amenities among residents of different ages, we examined the spatial distribution of urban amenities with regard to the preferences of various age groups and the pedestrian accessibility of amenities. In this paper, we propose an algorithm for detecting the most favorable combinations for the spatial distribution of urban amenities, in order to minimize the total walking distances and maximum frequencies of pedestrians of different age groups. The proposed method focuses on the parametric interpretation of various age groups, their preferences for urban amenities, the mutual proximity between residential and non-residential areas, and crowd intensity. Since residents act as agents whose individual decisions are not predictable, we used agent-based modeling to simulate pedestrian movement in order to optimize the spatial distribution of amenities. The digital environment, which allows the parameterization of different types of data, is used for simulation performance. The simulation outcome is quantitatively presented through two criteria of pedestrian accessibility, whose mutual relationship is used to detect the final, optimized combination for the spatial distribution of amenities. This approach can assist with a better understanding of pedestrian dynamics and support pedestrian-friendly choices in urban systems. Finally, the algorithm is applied to the case study of real space in a brownfield location.

Occupational Segregation in a Roy Model with Composition Preferences

We propose a model of labor market sector self-selection that combines comparative advantage, as in the Roy model, and sector composition preference. Two groups choose between two sectors based on heterogeneous potential incomes and group compositions in each sector. Potential incomes incorporate group specific human capital accumulation and wage discrimination. Composition preferences are interpreted as reflecting group specific amenity preferences as well as homophily and aversion to minority status. We show that occupational segregation is amplified by the composition preferences and we highlight a resulting tension between redistribution and diversity. The model also exhibits tipping from extreme compositions to more balanced ones. Tipping occurs when a small nudge, associated with affirmative action, pushes the system to a very different equilibrium, and when the set of equilibria changes abruptly when a parameter governing the relative importance of pecuniary and composition preferences crosses a threshold.

The value of climate amenities: A comparison of hedonic and discrete choice approaches

Amenities that vary across cities are typically valued using either a hedonic model, in which amenities are capitalized into wages and housing prices, or a discrete model of household location choice. In this paper, we use the 2000 Public Use Microdata Sample (PUMS) to value climate amenities using both methods. We compare estimates of marginal willingness to pay (MWTP), allowing preferences for climate amenities to vary by location. We find that mean MWTP for warmer winters is about twice as large using the discrete choice approach as with the hedonic approach; mean MWTP for cooler summers is approximately the same. The two approaches differ, however, in their estimates of MWTP by location. These disparities lead to significant differences in estimates of willingness to pay to avoid the A2 and B1 SRES scenarios in 2020–2050 using the two approaches.

The Role of Smart Growth in Residential Location Choice: Heterogeneity of Location Preferences in the Chicago Region

We investigate the role of smart growth in household location choice in the Chicago region, using a discrete choice analysis. In the midst of continued region-wide suburbanization, households tend to move to neighborhoods with rich consumption amenities and high transit access. However, this study does not find evidence that the neighborhood’s physical compactness is a significant location factor. Location preference for compact, mixed-use, and transit-oriented neighborhoods is significantly affected by the life cycle stage and income level, but less influenced by generation and age. Millennial households show strong preference for amenities and transit access only before they marry and have children.

The language of neighborhoods: A predictive-analytical framework based on property advertisement text and mortgage lending data

Real estate property listings use specific language to market properties to a target buyer – typically one that will garner the largest profit. As home-seekers have different preferences for house characteristics and neighborhood amenities, the words used to advertise homes are expected to vary according to the type of neighborhood and expected homebuyer. In this article, we develop a framework for extracting the key characteristics used to advertise properties according to the racial and income profile of home mortgage applicants in different types of neighborhoods. We perform an exploratory text analysis on words according to neighborhood types and use a binomial logistic regression model to determine the most discriminatory words for each type of neighborhood. Finally, we assess the ability of the property listing text to predict the type of neighborhood the property belongs to. Using a small, illustrative case study of listings from Charlotte, North Carolina, we find that the presence of specific neighborhood names holds more importance in neighborhoods with primarily White homebuyers. In gentrifying neighborhoods, unique property characteristics such as parquet flooring, and words associated with revitalization near the city center are common. Listings in neighborhoods with minority homebuyers are less likely to mention schools and feature traditionally suburban descriptors such as cars, garage, and roadways. We envision that this framework, using near real-time data sources, holds the potential to advance neighborhood prediction efforts, our understanding of amenity preferences and sorting patterns, and to illuminate less visible processes of change such as discrimination in the housing market.

What do residential lotteries show us about transportation choices?

Credibly identifying how the built environment shapes behaviour is empirically challenging, because people select residential locations based on differing constraints and preferences for site amenities. Our study overcomes these research barriers by leveraging San Francisco’s affordable housing lotteries, which randomly allow specific households to move to specific residences. Using administrative data, we demonstrate that lottery-winning households’ baseline preferences are uncorrelated with their allotted residential features such as public transportation accessibility, parking availability and bicycle infrastructure – meaning that neighbourhood attributes and a building’s parking supply are effectively assigned at random. Surveying the households, we find that these attributes significantly affect transportation mode choices. Most notably, we show that essentially random variation in on-site parking availability greatly changes households’ car ownership decisions and driving frequency, with substitution away from public transport. In contrast, we find that parking availability does not affect employment or job mobility. Overall, the evidence from our study robustly supports that local features of the built environment are important determinants of transportation behaviour.

Labor Market Frictions and Moving Costs of the Employed and Unemployed

This paper examines the role of labor market frictions and moving costs in explaining the migration behavior of US workers by employment status. Using data on low-skilled workers from the Survey of Income and Program Participation (SIPP), I estimate a dynamic model of individual labor supply and migration decisions. The model incorporates a reduced-form search model and allows for migration for non-market reasons. My estimates show that moving costs are substantial and that labor market frictions primarily inhibit migration of the employed. I use the model to study migration responses to local labor market shocks and to a moving subsidy. Workers' preferences for non-market amenities, coupled with substantial moving costs and employment frictions, grant market power to incumbent employers. Large moving costs also likely affect employers' recruiting behavior.

Measuring heterogeneous preferences for residential amenities

This study reports on estimates of heterogeneous preferences for residential amenities among households in the Mountain West region of the US. The estimates are derived from a choice experiment funded by the Utah Department of Transportation and Utah Transit Authority—an experiment based upon large samples of both homeowners and renters who participated in a larger, statewide transportation study. The choice experiment and transportation study allow us to control for a rich set of household-level demographic and lifestyle characteristics, which in turn permits identification of a host of factors contributing to heterogeneity in residential preferences. We leverage a percentage-change housing cost attribute included in the experiment to obtain measures of marginal willingness to pay (MWTP) for the various residential attributes and attribute levels in our study. Our method of converting the percentage-change cost attribute to dollar-denominated MWTP results in theoretically plausible estimates of a household's MWTP. We find that preferences for residential amenities differ across homeowners and renters with respect to intensity rather than direction—homeowners are generally willing to pay more for these amenities, in some cases up to seven times more. Our quantitative estimates of these preferences and the extent to which we control for heterogeneity across households provide urban and regional planners with precise monetary welfare measures for a sizable majority of the region's residents.