Analysis of Residential Satisfaction Changes by the Land Bank Program Using Text Mining

Many American manufacturing cities have experienced depopulation and economic downturns over the past five decades, and various revitalization strategies have been suggested to overcome the decline issue—ranging from redevelopment to smart decline. However, while most land bank-related studies have focused on socioeconomic dynamics (income levels, unemployment rate, etc.) through the program, there is a lack of direct research on residential satisfaction changes. Additionally, surveys were frequently used in previous studies to evaluate residential satisfaction; however, this method has disadvantages, including constraints on time and cost, and the inability to take into account external factors that may affect residential satisfaction. Furthermore, most studies on urban decline have focused primarily on declining factors, and there have been few investigations into how cities change as urban regeneration strategies advance. Therefore, the primary purpose of this study is to identify the influence of the land bank program on residential satisfaction by using Twitter data. Approximately 300,000 Twitter posts containing location information generated within the city of Detroit were collected to determine the degree of sensitivity to each tweet and categorized into positive and negative emotions to determine the relationship between residential satisfaction and the land bank program. As a result, the increase in homeownership, built year, house value, and the number of land banking sold properties were found to have a negative effect on neighborhood satisfaction in Detroit. Although the research results indicated that while the land bank program did not significantly improve residential satisfaction in Detroit, it has made a partial contribution to improving living standards. These findings emphasize the importance of enhancing residential satisfaction and suggest the need for policy change. In response to the problem of urban contraction, it seems that indiscriminately distributing houses is not the only solution to prevent urban shrinkage. Furthermore, this study shows meaningful results on text mining and provides the possibility of developing research using social network services

The Effects of Auricular Acupressure on Low Back Pain, Neuropathy and Sleep in Patients with Persistent Spinal Pain Syndrome (PSPS): A Single-Blind, Randomized Placebo-Controlled Trial

(1) Background: Various procedures were performed on patients with persistent spinal pain syndrome (PSPS), but the clinical effect and safety were insufficient. The study was to examine the effects of auricular acupressure (AA) on low back pain, neuropathy, and sleep in patients on PSPS. (2) Methods: This was a randomized, single-blind, placebo-controlled study conducted from 1 March 2022 to 31 July 2022. The participants who had at least one lumbar surgery were randomly assigned to either the experimental group (n = 26) or the placebo control group (n = 25). All participants received 6 weeks of AA intervention. To validate the effects of the intervention, pressure pain thresholds (PPT), the Visual Analogue Scale (VAS), douleur neuropathique 4 (DN4) questions, the Pittsburgh Sleep Quality Index (PSQI), and actigraphy with a Fitbit Alta were conducted. The data were analyzed with SPSS/WIN ver. 27.0, using a t-test and repeated-measures ANOVA. (3) Results: The findings showed that there were significant differences in pain (back VAS p = 0.003, leg VAS p = 0.002, PPT p = 0.008), neuropathy (DN4 p = 0.034), and sleep actigraphy (sleep efficiency p = 0.038, number of awake p = 0.001, deep sleep stage p = 0.017). (4) Conclusions: We conclude that AA is an effective, safe, cost-effective, non-invasive nursing intervention that can improve pain, neuropathy, and sleep in patients on PSPS

Analysis of Residential Satisfaction Changes by the Land Bank Program Using Text Mining

Many American manufacturing cities have experienced depopulation and economic downturns over the past five decades, and various revitalization strategies have been suggested to overcome the decline issue—ranging from redevelopment to smart decline. However, while most land bank-related studies have focused on socioeconomic dynamics (income levels, unemployment rate, etc.) through the program, there is a lack of direct research on residential satisfaction changes. Additionally, surveys were frequently used in previous studies to evaluate residential satisfaction; however, this method has disadvantages, including constraints on time and cost, and the inability to take into account external factors that may affect residential satisfaction. Furthermore, most studies on urban decline have focused primarily on declining factors, and there have been few investigations into how cities change as urban regeneration strategies advance. Therefore, the primary purpose of this study is to identify the influence of the land bank program on residential satisfaction by using Twitter data. Approximately 300,000 Twitter posts containing location information generated within the city of Detroit were collected to determine the degree of sensitivity to each tweet and categorized into positive and negative emotions to determine the relationship between residential satisfaction and the land bank program. As a result, the increase in homeownership, built year, house value, and the number of land banking sold properties were found to have a negative effect on neighborhood satisfaction in Detroit. Although the research results indicated that while the land bank program did not significantly improve residential satisfaction in Detroit, it has made a partial contribution to improving living standards. These findings emphasize the importance of enhancing residential satisfaction and suggest the need for policy change. In response to the problem of urban contraction, it seems that indiscriminately distributing houses is not the only solution to prevent urban shrinkage. Furthermore, this study shows meaningful results on text mining and provides the possibility of developing research using social network services

Rapid Development, Build-Out Ratio and Subsequent Neighborhood Turnover

Neighborhood development is primarily comprised of structural elements that include design elements, nearby amenities and ecological attributes. This paper assumes that the process of development itself also influences the character of the neighborhood—specifically, that the rate of development and build-out ratio influences neighborhood turnover. While the structural components clearly set a framework for development, the process of development expresses the character of the neighborhood in subtle messages conveyed through the market. Neighborhoods in the rapidly growing university town of College Station, Texas are analyzed in terms of neighborhood design, nearby amenities and landscape ecology components. Residential property records are used to characterize each neighborhood in terms of the rate of development and current build-out ratio. The multivariate analysis indicates that the development rate increases subsequent neighborhood turnover rates while the build-out ratio decreases it

Predictable Surprise: The Spatial and Social Morphology of Aging Suburbs in the U.S. Metropolitan Areas

Elderburbs, defined as old suburban neighborhoods in terms of their ‘built environments’ and ‘demographic structures’, have emerged prominently in academic discussion due to the social vulnerability and outdated built environments of senior dominant neighborhoods that barely meet the needs of their aging populations. Even though previous literature has revealed concerns about suburban decline and the growing number of seniors, these two points of interest have largely been examined in isolation from one another. Thus, this paper attempts to unveil the spatial and social morphology of Elderburbs in 20 U.S. metropolitan areas from 1990 to 2010. Elderburbs were identified by two major criteria; built year (first-generation suburbs built between 1950 and 1970) and demographic aging (based on elderly, elderly-child, and elderly dependency ratios). The findings of this study indicate that Elderburbs have increased and expanded out to suburban areas, especially in the Northeast and Midwest. On the contrary, Elderburbs in the South have decreased and moved closer to core cities. Differing from our assumptions, both Elderburbs and Elderurbans were found to be less socially vulnerable than ordinary suburban and urban neighborhoods

A Comparison of Vacancy Dynamics between Growing and Shrinking Cities Using the Land Transformation Model

Every city seeks opportunities to spur economic developments and, depending on its type, vacant land can be seen as a potential threat or an opportunity to achieve these developments. Although vacant land exists in all cities, the causes and effects of changes in vacant land can differ. Growing cities may have more vacant land than shrinking cities because of large scale annexation. Meanwhile, depopulation and economic downturn may increase the total amount of vacant and abandoned properties. Despite various causes of increase and decrease of vacant land, the ability to predict future vacancy patterns—where future vacant parcels may occur—could be a critical test to set up appropriate development strategies and land use policies, especially in shrinking cities, to manage urban decline and regeneration efforts more wisely. This study compares current and future vacancy patterns of a growing city (Fort Worth, TX, USA) and a shrinking city (Chicago, IL, USA), by employing the Land Transformation Model (LTM) to predict for future vacant lands. This research predicts and produces possible vacancy pattern scenarios by 2020 and deciphers the ranking of determinants of vacant land in each city type. The outcomes of this study indicate that the LTM can be useful for simulating vacancy patterns and the causes of vacancy vary in both growing and shrinking cities. Socio-economic factors such as unemployment rate and household income are powerful determinants of vacancy in a growing city, while physical and transportation-related conditions such as proximity to highways, vehicle accessibility, or building conditions show a stronger influence on increasing vacant land in a shrinking city

Can Hotel Companies’ Water Conservation Management and Waste Reduction Measures Influence Hotel Customers’ Willingness to Pay More and Intention to Revisit?

This study investigated the effect of hotel water conservation management and waste reduction measures on customers’ social and personal norms, willingness to pay more, and revisit intention, with cost consciousness as a moderating variable. A total of 311 valid samples were obtained by conducting a survey on customers who have used hotels for the past year. To perform the empirical analysis, SPSS 22.0 (IBM, New York, NY, USA) and AMOS 22.0 (IBM, New York, NY, USA) were used. As a result of the analysis, seven of the eight hypotheses were accepted, and the ninth hypothesis that tested the moderating effect was partially accepted. The results of the study revealed that a hotel’s eco-friendly activities had a positive effect on its overall performance. The results also provide insight that can lay the foundation for the sustainable management of hotels

Spatial Association of Urban Form and Particulate Matter

Increasingly detrimental effects of fine particulate matter (PM) have been observed in Northeast Asia owing to its rapid economic development. Previous studies have found that dust, combustion, and chemical reactions are the major sources of PM; nevertheless, the spatial configuration of land use and land cover, which is of most interest to planners and landscape architects, also influences the PM levels. Here, we attempted to unveil the relationship between PM and different types of land use cover (i.e., developed, agricultural, woody, grass, and barren lands) in 122 municipalities of Korea. Landscape ecology metrics were applied to measure the spatial configuration of land use pattern and spatial lag models by taking into account the transboundary nature of air pollution, allowing us to conclude the following regarding PM levels: (1) the size of land cover type matters, but their spatial configuration also determines the variations in PM levels; (2) the contiguity and proximity of landcover patches are important; (3) the patterns of grasslands (e.g., simple, compact, and cluster (with large patches) patterns) and woodlands (e.g., complex, contiguous, and cluster (with large patches) patterns) considered desirable for minimizing PM are dissimilar in terms of contiguity

Seasonal Pattern of Decomposition and N, P, and C Dynamics in Leaf litter in a Mongolian Oak Forest and a Korean Pine Plantation

Distinct seasons and diverse tree species characterize temperate deciduous forests in NE Asia, but large areas of deciduous forests have been converted to conifer plantations. This study was conducted to understand the effects of seasons and tree species on leaf litter decomposition in a temperate forest. Using the litterbag method, the decomposition rate and nitrogen, phosphorous, and carbon dynamics of Mongolian oak (Quercus mongolica), Korean pine (Pinus koraiensis), and their mixed leaf litter were compared for 24 months in a Mongolian oak stand, an adjacent Korean pine plantation, and a Mongolian oak—Korean pine mixed stand. The decomposition rates of all the leaf litter types followed a pattern of distinct seasonal changes: most leaf litter decomposition occurred during the summer. Tree species was less influential on the leaf litter decomposition. The decomposition rates among different leaf litter types within the same stand were not significantly different, indicating no mixed litter effect. The immobilization of leaf litter N and P lasted for 14 months. Mongolian oak leaf litter and Korean pine leaf litter showed different N and P contents and dynamics during the decomposition, and soil P2O5 was highest in the Korean pine plantation, suggesting effects of plantation on soil nutrient budget