Assessing and Representing Livability through the Analysis of Residential Preference
2. Challenges of Defining and Assessing Livability
3. The Conceptual Livability Framework
3.1. Theoretical Foundations
3.2. Key Elements and Their Relationships in the Conceptual Livability Framework
4.1. The Design of the Survey
- Represent different levels of economic development: Livability rankings tend to focus only on large cities located in countries with a mature development status; these rankings therefore predominantly represent a Western culture. To get a broader overview, we included cities from Africa and Latin America to study whether the level of economic development and cultural differences may influence the perception of relevant livability factors.
- Different population sizes: We selected the study areas to represent cities with different sizes and political roles, such as regional centers and capitals with a few million people.
- Age and sex of the respondents: We asked that residents were at least 18 years old, but we also tried to represent the older population, as their needs and expectations may be specific. In terms of sex, we tried to represent both sexes in around the same proportion.
- Local expertise: Although we did not aim for city-specific results, it was relevant to select cities where the authors or their colleagues were familiar with the local circumstances.
- Around 50 participants per study area: This sample size was not enough to support city-scale analysis, however, a minimum of 50 responses rendered it possible to represent the various age groups and areas within a city, while keeping the effort required to find respondents reasonable.
4.1.1. Thematic Categories of the Questionnaire
- General information: As the introductory part of the questionnaire, this section contained questions about demography (sex, age, marital status, education, household members, etc.) and monthly income.
- Sense of community and belonging: In the first main part of the questionnaire, participants were asked about the neighborhood and community they lived in and their general satisfaction with it. The community meant their home and the group of people living in its closest surroundings (few buildings/building blocks). The neighborhood is the part of the city where this community lives.
- Urban form: Participants were asked about their perceptions of the built environment in their neighborhoods. Built environment consists of the buildings, public spaces, and other elements of the street such as trees and street furniture.
- Mobility: This part of the questionnaire investigated transportation mode preferences according to different activity types, motivations for dominant car usage, importance and availability of different mobility-related factors, perceived transportation safety, and self-reported overall quality of walking, cycling, and transportation.
- Urban functions: In the fifth part of the questionnaire, people were asked about specific urban functions and their accessibility, also considering further mobility parameters. We also asked respondents to evaluate the general fulfilment of their needs by urban functions.
- Housing: This part of the questionnaire addressed housing conditions and related infrastructure.
- General satisfaction: As a final topic, we asked the participants about their general satisfaction in terms of city quality.
4.1.2. Street Network Density Categories
- A denser street network might provide better accessibility, and this could induce the perception of higher livability. However, too high density might have the opposite effect (higher building/population density may imply an overcrowded environment with more motorized traffic, which means more pollution and less traffic safety)
- The density of the street network might be a better predictor of the level of perceived livability/mobility conditions than the city-specific characteristics, or the level of economic development, mainly because people from areas with similar street network densities might have more similar perceived livability values than people from the same city but with different street network densities, due to the varying accessibility of functions.
4.2. Evaluation of the Survey Results
4.3. Relational-Statistical Learning
4.4. Validation—GIS Analysis
5.1. Respondents of the Questionnaire
5.2. Logistic Regression
5.3. Relational-Statistical Learning
5.4. GIS Analysis
- Detailed investigation using all factors: This approach provided a thorough analysis, where individual perceptions and expectations were given a high relevance. The limitation of the method is clearly how time- and resource-consuming it is to interview enough people. Therefore, this approach might be optimal for smaller areas, and for investigating the expectations of different socioeconomic groups. However, by adding spatial aspects based on the approximate addresses of the people, the GIS analysis can reveal further issues and differences at finer spatial scales as well. If the investigation has a more specific purpose than a “general diagnosis”, some thematic factor groups may be omitted. For example, in a transportation-related project, community aspects might have a lower relevance.
- Using the key livability parameters: By using the identified subset of livability parameters, researchers and planners can still investigate the quality of an area thoroughly, but in a slightly less resource-consuming way. This type of assessment can still provide details about the different aspects of livability, along with the calculated probability values that can be utilized as weights in the end. Again, the responses of the people can be localized at finer scales within the city; it is therefore possible to locate areas with given problems based on the responses. For example, if in one area people are less likely to commute by bike, or have a lower level of perceived safety, such information may provide relevant input and starting points for further planning steps.
- Using probability values as weights: Researchers and planners might decide to only use the calculated probability values as weights for some or all the listed parameters to evaluate the overall performance of an area in terms of livability. In this case, spatial aspects might have a lower relevance, depending on the purpose of the analysis.
- Modeling: As our validation example illustrated, if a comprehensive analysis is not required, using only three parameters can also represent livability in an area very well. In our case, out of these three parameters, only one had personal relevance, which can again limit the direct involvement of residents in the analysis process. When asking a large enough number of people only about their overall perceptions of the built environment, combined with the spatial analysis of the other two parameters, it was still possible in our study to get a good approximation of the level of livability.
Conflicts of Interest
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|Country||City||Population||Number of Responses *|
|Nicaragua||León||168,000 ||32 *||131 responses from developing countries|
|Kenya||Nairobi||5,970,000 ||46 *|
|Austria||Vienna||1,900,000 ||91||309 responses from developed countries|
|United States||Portland, OR||653,000 ||43|
|Modifying factors (MO)||Level of development (developing/developed)||1.71583||<0.001 ***|
|Salary compared to basic needs||0.65158||0.02730 *|
|Overall housing conditions 1||2.20714||<0.001 ***|
|Community (CO)||Being a member of this community makes me feel good. 2||1.2085||<0.001 ***|
|I trust people in this community. 2||0.9752||0.001618 **|
|Most community members know me by face. 2||0.9979||0.008569 **|
|Members of this community care about each other. 2||1.1183||0.008702 **|
|Urban form (FO)||Buildings in a street with similar style (architectural design). 3||−0.84488||0.089097 ·|
|Street furniture (benches or chairs to sit. dustbins. shade. drinking fountains. etc.) 4||0.70985||0.089852 ·|
|Trees along the streets. 4||1.16364||0.005797 **|
|Overall quality of the built environment. 1||1.47969||<0.001 ***|
|Transportation mode (TM) 7||Going to work by bicycle. 5||1.80005||0.01753 *|
|Going to shop by public transport. 5||−0.81267||0.03276 *|
|Going to shop by bicycle. 5||−2.13342||0.00474 **|
|Perceived mobility (PM) 8||Perceived cycling and walking safety. 6||0.5308||0.06222.|
|Perceived cycling and walking quality. 1||0.9728||0.00109 **|
|Perceived overall transportation quality. 1||1.2||<0.001 ***|
|Car (CA) 9||Car is the only way to reach the person’s destination. 2||−0.81582||0.068534.|
|Car is used because the person’s destinations are too far. 2||0.98735||0.021055 *|
|Mobility infrastructure (M) 10||Special transportation services. 3||−3.227676||0.0118 *|
|Easy to read traffic signs. 4||2.116724||0.0448 *|
|Enforced speed limits. 4||1.194553||0.0372 *|
|Function & needs (FU, N)||I would let my children to walk/cycle alone. 2||0.8991||0.00227 **|
|There is a lot of crime in the neighborhood. 2||−0.8912||0.01426 *|
|Needs are fulfilled by the available urban functions. 2||0.4674||0.040538 *|
|Modifying factors (MO)||Level of development.||0.47727||0.88142|
|Salary compared to basic needs.||0.125|
|Overall housing conditions.||0.2|
|Community (CO)||Being a member of this community makes me feel good.||0.69767||0.88571|
|I trust people in this community.||0.67857|
|Most community members know me by face.||0.53125|
|Members of this community care about each other.||0.75|
|Urban form (FO)||Buildings in a street with similar style (architectural design).||0.79412||0.91935|
|Street furniture (benches or chairs to sit, dustbins, shade, drinking fountains, etc.)||0.7037|
|Trees along the streets.||0.52|
|Overall quality of the built environment.||0.75|
|Transportation mode (TM)||Going to work by bicycle.||0.9999||0.63636|
|Going to shop by public transport.||0.66667|
|Going to shop by bicycle.||0.33333|
|Perceived mobility (PM)||Perceived cycling and walking safety.||0.47727||0.88608|
|Perceived cycling and walking quality.||0.63636|
|Perceived overall transportation quality.||0.71429|
|Car (CA)||Car is the only way to reach the person’s destination.||0.33333||0.75439|
|Car is used because the person’s destinations are too far.||0.78261|
|Mobility infrastructure (M)||Special transportation services.||0.45946||0.91827|
|Easy to read traffic signs.||0.625|
|Enforced speed limits.||0.69231|
|Function & needs (FU, N)||I would let my children to walk/cycle alone.||0.6666||0.89326|
|There is a lot of crime in the neighborhood. *||0.64734|
|Needs are fulfilled by the available urban functions.||0.76144|
|Road network density (RC)||Higher density of road network supporting human-scaled mobility||0.77559|
|Predicted Higher Satisfaction||Predicted Lower Satisfaction|
|Actual Higher Satisfaction||53||11|
|Actual Lower Satisfaction||4||7|
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Kovacs-Györi, A.; Cabrera-Barona, P.; Resch, B.; Mehaffy, M.; Blaschke, T. Assessing and Representing Livability through the Analysis of Residential Preference. Sustainability 2019, 11, 4934. https://doi.org/10.3390/su11184934
Kovacs-Györi A, Cabrera-Barona P, Resch B, Mehaffy M, Blaschke T. Assessing and Representing Livability through the Analysis of Residential Preference. Sustainability. 2019; 11(18):4934. https://doi.org/10.3390/su11184934Chicago/Turabian Style
Kovacs-Györi, Anna, Pablo Cabrera-Barona, Bernd Resch, Michael Mehaffy, and Thomas Blaschke. 2019. "Assessing and Representing Livability through the Analysis of Residential Preference" Sustainability 11, no. 18: 4934. https://doi.org/10.3390/su11184934