Exploring spatial variations in the relationships between residents' recreation demand and associated factors: A case study in Texas

Lee, Kyung Hee; Schuett, Michael A.

doi:10.1016/j.apgeog.2014.06.018

Cited by 45 publications

(30 citation statements)

References 28 publications

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“…It is inferred that because they live closer to the park, reaching the recreation area is easier, so visitors were more willing to participate in recreational activities in this place. These results are consistent with those of previous studies [37]. There is a positive correlation with "time of stay at the Calligraphy Greenway" (β = 1.313 ***), so the more frequently visitors make visits, the longer are their stays, because a greater frequency of visits indicates that a visitor already relies heavily on recreation at the Calligraphy Greenway, so he or she prioritizes this area when considering recreational options.…”

Section: A Multilinear Regression Analysis Of the Resultssupporting

confidence: 82%

“…There is a positive correlation between "time of stay at the Calligraphy Greenway" and "educational level" (β = 0.183 *), so the higher a visitor's level of education, the longer the stay at the Calligraphy Greenway, which is consistent with the results of previous studies [4,37]. The time of stay has a positive correlation (β = 0.015 ***) with "number of visits to the Calligraphy Greenway over the past year," so the more regularly a person visited the Calligraphy Greenway, the more likely they were to linger at the Calligraphy Greenway.…”

Section: A Multilinear Regression Analysis Of the Resultssupporting

confidence: 82%

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Preferences of Tourists for the Service Quality of Taichung Calligraphy Greenway in Taiwan

Liu

Chuang

2018

Forests

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This study explores preferences for a set of attributes that characterize the recreational value of Calligraphy Greenway, the most notable greenbelt in Taichung City, Taiwan. As an urban green space, the Calligraphy Greenway has its own recreational attributes and visitors' preferences. This study uses the choice experiment method to determine visitors' preference levels for five major attributes to improve the recreational quality. On average, each visitor visited there 9.15 times in the past year and spent 2.37 h per visit. Of the five recreational attributes, satisfaction with recreational activity opportunities had the highest score and satisfaction with cultural landscape resources had the lowest score. The importance is ranked in the order of recreational service quality, total recreational cost, environmental landscape resources, cultural landscape resources and recreational activity opportunities. Considering difference of groups, female visitors were more concerned with cost and activities but male visitors were more concerned with service quality and natural/cultural landscape resources. Local visitors were more concerned with cost and activities but non-local visitors were more concerned with environmental/cultural landscape resources. Both were concerned with service quality. Based on the results, this study makes the following recommendations: cultural landscape resources and quality of recreational services and facilities should be improved and more complete interpretative educational guidance should be provided to increase visitors' willingness to visit. Additionally, it is suggested to set up various districts to cater for preferences of different visitor groups.

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Section: A Multilinear Regression Analysis Of the Resultssupporting

confidence: 82%

Section: A Multilinear Regression Analysis Of the Resultssupporting

confidence: 82%

Preferences of Tourists for the Service Quality of Taichung Calligraphy Greenway in Taiwan

Liu

Chuang

2018

Forests

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“…GWR is a local spatial statistical method for evaluating how the relationships between a dependent variable and one or more explanatory variables change spatially. As one of the useful tools to explore the spatial local heterogeneity, GWR has been widely used in many fields in recent years, For example, the geographic variation and impact factors of urban public green space availability [46], peri-urban agriculture [47], noise pollution [48], population [49] and resident recreation demand [50] have been investigated with GWR. The GWR method was usually compared with global spatial statistical methods, such as the ordinary least squares (OLS) regression, regression kriging, or co-kriging and the comparisons showed the advantages of GWR in improving mapping quality and exploring spatially varying local relationships [47][48][49][50][51].…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal Effects of Main Impact Factors on Residential Land Price in Major Cities of China

Yang

et al. 2017

Sustainability

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Abstract:With the rapid development of land marketization in China, the spatial patterns of residential land prices in different regions have become increasingly complicated. The very high and continuously rising residential land prices in many cities are causing significant challenges to economic development and social stability. Yet, there has only been a limited amount of attempts made to model and analyze the regional dynamic changes of residential land price systematically, especially in term of the spatially varying effects of key demographic and economic factors. In this study we provided a perspective analysis of the changes of residential land prices in 2008, 2011 and 2014 based on the land price monitoring records of 105 cities and then conducted a geographically weighted regression (GWR) analysis on the relationships between residential land price and three major impact factors (i.e., immigrant population, gross domestic product (GDP) and investment in residential buildings). Results show that the areas in which GDP had relatively strong positive impacts on residential land price expanded with time. The negative effects of immigrant population on residential land price were mainly concentrated in the cities around the Bohai Rim and the area with negative effects gradually shrank in the three studied years. Conversely, the areas with negative correlation between investment in residential buildings and residential land price gradually expanded in size over time. A geographical detector was used to examine the relative importance of factors to residential land price. It was found that the GDP had more significant influence on residential land price than other factors and the influence of the three factors to overall variation in residential land price increased over the three studied years. These results underscore the importance of taking spatially varying effects of major driving factors into account in policy-making on regional land market.

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“…Because of this advantage, the GWR is widely used in the area of urban planning (Lu et al 2013;Huang et al 2010;Kaligari and Ziberna 2014), ecological and environmental applications (Clement et al 2009) and sometimes even in climate research (Brown et al 2012). Although, GWR is not a problem-free statistical method, with major concerns focused on issues such as kernel and bandwidth selection, some researchers have applied this method even in diverse disciplines (e.g., Bagheri et al 2009;Bitter et al 2007;Du et al 2014;Haitao et al 2014;Lee and Schuett 2014;Megler et al 2014). GWR is applied specifically to the urban expansion by Du et al (2014) and ShafizadehMoghadam and Helbich (2015).…”

Section: Introductionmentioning

confidence: 99%

Modeling spatial variation of explanatory factors of urban expansion of Kolkata: a geographically weighted regression approach

Mondal

Das

Dolui

2015

Model. Earth Syst. Environ.

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Modern cities face a large number of issues related to boundary, land alteration and environmental degradation. Extensive urban expansion is an especially serious problem faced by most of the cities in developing countries. Urban management has extensive engagement with rapid urban expansion and their factors to achieve a sustainable form of development. A more inclusive understanding of the urban driver variables and their cross comparison greatly helps to investigate this rapid urban expansion. The major theme of this study will be to inquire into this factors of urban expansion. Both global and local regressions are performed to determine the spatial variability of the driving forces of urban expansion. The results indicate that geographically weighted regression model outperformed global regression. Urban expansion in the city of Kolkata can be observed mainly in two directions; northeast and south-east. The possible reasons include that of economic appraising, lack of environmental distress and good spatial settings along with investor interest, which together determine the biased bidirectional axial expansion. This study comes to the conclusion that local variables are significant in driving the bi-directional urban expansion in the context of a biased urban management.

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Exploring spatial variations in the relationships between residents' recreation demand and associated factors: A case study in Texas

Cited by 45 publications

References 28 publications

Preferences of Tourists for the Service Quality of Taichung Calligraphy Greenway in Taiwan

Preferences of Tourists for the Service Quality of Taichung Calligraphy Greenway in Taiwan

Spatiotemporal Effects of Main Impact Factors on Residential Land Price in Major Cities of China

Modeling spatial variation of explanatory factors of urban expansion of Kolkata: a geographically weighted regression approach

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