Prioritizing neighborhood attributes to enhance neighborhood satisfaction: An impact asymmetry analysis

Cao, Jason; Hao, Zhesong; Yang, Jun; Yin, Jiangbin; Huang, Xiaoyan

doi:10.1016/j.cities.2020.102854

Cited by 32 publications

(27 citation statements)

References 56 publications

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“…Although IAA generates a more granular classification, the factors are an extension of the 3FT since the first two are basic factors and the last two are excitement factors. Following this research line, several studies applied IAA and gradient boosting decision threes (GBDT) to examine a variety of user satisfaction topics, such as, elderly and public transport (Lan et al 2022), bus and BRT riders (Fang et al 2021;Wu et al, 2020) and neighborhood and urban planning (Cao et al 2020;Dong et al 2019). We, aware of the limitation of using the 3FT alone, mixed implicit and explicit importance with attribute performance to graphically identify attributes' relationship with satisfaction.…”

Section: Methods Complementaritymentioning

confidence: 99%

“…The axes intersection is defined by the average values of the implicit and explicit importance. A newer research line, based on the principles of the 3FT, applies the Impact-Asymmetry Analysis (IAA) for an accurate evaluation of non-linear effects (Cao et al 2020;Dong et al 2019;Fang et al 2021;Lan et al 2022;Wu et al, 2020). These papers identify the most influential factors on user satisfaction, accounting for the non-linear relationships.…”

Section: The Three-factor Theory Of Customer Satisfaction In Transpor...mentioning

confidence: 99%

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Identifying key elements for user satisfaction of bike-sharing systems: a combination of direct and indirect evaluations

2022

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Bike-sharing systems (BSS) are gaining popularity in cities worldwide, as a part of a generalized strategy to mitigate the problems derived from motorized transportation (congestion, pollution, noise, etc.). These systems have proved to have positive effects on cities, moreover, many of them have reached a performance peak and require improvements to attract/retain users and compete against emerging soft mobility alternatives. Whilst there are broad studies evaluating BSS demand and design, less attention has been paid to user satisfaction and the complexities underlying the relationships between the system attributes importance. This study proposes a novel combination of two methodologies for satisfaction assessment that allows decision-makers to identify the most influential system attributes on user satisfaction. The combined methods are the direct, explicit, Importance Performance Analysis (IPA), and the nonlinear, implicit Three-Factor Theory (3FT), which combined generate a three-dimensional scheme that facilitates the comprehension of the results. The combination was applied to a dataset of Madrid´s BSS to identify the attributes that perform poorly, and then assess their implicit influence on satisfaction to establish improvement priorities. The results suggest that station occupancy and bicycle availability and totem functioning are key service attributes to enhance satisfaction. Also, the combination of the two methodologies makes it possible to differentiate that maintenance is a priority for subscribers and network extension for occasional users. The pedelec system is a key attribute that might help overcome Madrid´s unfavorable cycling environment. This user-centric evaluation is a valuable tool that guides precise measure implementation, service operation, future design, and planning oriented to increase ridership.

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Section: Methods Complementaritymentioning

confidence: 99%

Section: The Three-factor Theory Of Customer Satisfaction In Transpor...mentioning

confidence: 99%

Identifying key elements for user satisfaction of bike-sharing systems: a combination of direct and indirect evaluations

2022

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“…Uncertain and confounding indicators may exist, such as the same questions applicable to different environmental conditions and inappropriate measurement methods. Moreover, discrete variables are typically used in questionnaires (20). Thus, the results need to be reclassified and scored to conform to a normal distribution and meet the requirements of statistical inference.…”

Section: Literature Review Research On the Quantitative Analysis Of...mentioning

confidence: 99%

“…Positive sentiments occur when advanced needs are met, but negative sentiments do not occur when they are not met. Negative sentiments occur when intermediate needs are not met and vice versa (20,66). Studies on residential environments found a non-linear relationship between negative sentiments and basic needs such as street lighting, residential safety, absence of noise, and nearby facilities (53,67).…”

Section: Studies On the Non-linear Correlation Between The Built Envi...mentioning

confidence: 99%

“…The sentiments of urban dwellers may have a multilevel relationship with the built environment. Some scholars have conducted hierarchical studies on the built environment at different administrative levels and under different development conditions to determine the impact of the built environment factors on residents' sentiments at multiple levels (20,84). Our sample data had a hierarchical structure, with low-level neighborhood data nested within high-level subdistrict data.…”

Section: Statistical Analysis Of the Correlation Between Residents' S...mentioning

confidence: 99%

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Does the built environment of settlements affect our sentiments? A multi-level and non-linear analysis of Xiamen, China, using social media data

Fan

Gai²,

Li³

et al. 2023

Front. Public Health

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IntroductionHumans spend most of their time in settlements, and the built environment of settlements may affect the residents' sentiments. Research in this field is interdisciplinary, integrating urban planning and public health. However, it has been limited by the difficulty of quantifying subjective sentiments and the small sample size.MethodsThis study uses 147,613 Weibo text check-ins in Xiamen from 2017 to quantify residents' sentiments in 1,096 neighborhoods in the city. A multilevel regression model and gradient boosting decision tree (GBDT) model are used to investigate the multilevel and nonlinear effects of the built environment of neighborhoods and subdistricts on residents' sentiments.ResultsThe results show the following: (1) The multilevel regression model indicates that at the neighborhood level, a high land value, low plot ratio, low population density, and neighborhoods close to water are more likely to improve the residents' sentiments. At the subdistrict level, more green space and commercial land, less industry, higher building density and road density, and a smaller migrant population are more likely to promote positive sentiments. Approximately 19% of the total variance in the sentiments occurred among subdistricts. (2) The proportion of green space and commercial land, and the density of buildings and roads are linearly correlated with residents' sentiments. The land value is a basic need and exhibits a nonlinear correlation with sentiments. The plot ratio, population density, and the proportions of industrial land and the migrant population are advanced needs and are nonlinearly correlated with sentiments.DiscussionThe quantitative analysis of sentiments enables setting a threshold of the influence of the built environment on residents' sentiments in neighborhoods and surrounding areas. Our results provide data support for urban planning and implementing targeted measures to improve the living environment of residents.

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Measuring the Potential for Meaningful Usability of Spaces: The Case Studies of Two Social Housing Districts in Cagliari, Italy

Annunziata

Garau

Lotfata

2023

Lecture Notes in Computer Science

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Prioritizing neighborhood attributes to enhance neighborhood satisfaction: An impact asymmetry analysis

Cited by 32 publications

References 56 publications

Identifying key elements for user satisfaction of bike-sharing systems: a combination of direct and indirect evaluations

Identifying key elements for user satisfaction of bike-sharing systems: a combination of direct and indirect evaluations

Does the built environment of settlements affect our sentiments? A multi-level and non-linear analysis of Xiamen, China, using social media data

Measuring the Potential for Meaningful Usability of Spaces: The Case Studies of Two Social Housing Districts in Cagliari, Italy

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