Comparing Subjective and Objective Quality of Life Criteria: A Case Study of Green Space and Public Transport in Vienna, Austria

Haslauer, Eva; Delmelle, Elizabeth C.; Keul, Alexander; Blaschke, Thomas; Prinz, Thomas

doi:10.1007/s11205-014-0810-8

Cited by 44 publications

(23 citation statements)

References 23 publications

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“…Murawska [58] paid attention to the fact that the lack of one widely recognised definition results in using the term "quality of life" interchangeably with "living conditions", even though living conditions should refer to fulfilling material needs, and quality of life should also incorporate immaterial aspects. The life quality can be assessed based on the subjective opinion of the respondents, or objectively, with the use of secondary data [59][60][61][62].…”

Section: General Information About the Qol Conceptmentioning

confidence: 99%

Between the Social and Economic Dimensions of Sustainability in Rural Areas—In Search of Farmers’ Quality of Life

Wojewódzka-Wiewiórska

Kłoczko-Gajewska

Sulewski

2019

Sustainability

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Life quality is an important indicator of sustainable development. Farmers’ quality of life strongly affects the farm’s viability. The main goal of this study was to identify the relationships between three main components of farmers’ quality of life: economic situation, living conditions, and mental comfort. In the first phase of the study, the theoretical model representing potential relationships between quality of life components was constructed, and in the second phase the relationships were verified with the use of the structural equation modelling method. The sample consisted of 600 farmers participating in the Polish Farm Accountancy Data Framework (FADN). In the analyses, data from the FADN database and data obtained during supplementary interviews with farmers were used. The analyses revealed that living conditions are significantly and positively correlated with the economic situation and mental comfort, while mental comfort turned out to be negatively correlated with the economic situation. It was concluded that future agricultural and rural development policies should be more focused on the social dimension of sustainable development than before, particularly considering the fact that a farmer’s higher engagement in the improvement of their family’s economic condition might result in lowering their mental comfort due to the stress and work overload.

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Section: General Information About the Qol Conceptmentioning

confidence: 99%

Between the Social and Economic Dimensions of Sustainability in Rural Areas—In Search of Farmers’ Quality of Life

Wojewódzka-Wiewiórska

Kłoczko-Gajewska

Sulewski

2019

Sustainability

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“…All independent variables loaded high (over 68% explained variance by the factor) on at least one factor (with most only loading high on one factor) ( Table 4). Based on the raw variables that loaded strongly on the different components, the components were labeled as Urbanization and Population (1), Education and Income (2), Household and Community (3), and Public Green Spaces (4). The relationships between these four components and the dependent variables of "Excellent QoUL" and "Poor QoUL" were subsequently analyzed in a multiple regression analysis.…”

Section: Resultsmentioning

confidence: 99%

“…Numerous QoUL studies measuring cause and effect between objective and subjective indicators have been conducted [4][5][6][7][8][9][10][11][12], and various models representing the relationship between objective reality and subjective experience have been proposed, for example [2,13,14]. These models generally include several variables that are considered to play a role in the overall QoUL perspective at different geographic scales [15].…”

Section: Introductionmentioning

confidence: 99%

Modeling Quality of Urban Life Using a Geospatial Approach

2020

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The rapid global urbanization of the past century poses several challenges for planners and policy makers. In particular, the conflation of social and urban issues must be understood to create sustainable and livable urban places. In this regard, it was our aim to model and understand the relationship between urban characteristics and peoples’ perceived quality of urban life (QoUL) using statistical analysis and geospatial modeling. We selected objective variables representing urban characteristics based on literature and used principal components analysis to develop uncorrelated components. These components served as the independent variables in a multiple linear regression analysis. The subjective, dependent variables were extracted from a QoUL survey. Results indicated that only the Education/Income component is related to QoUL (R2 of 0.46). Using only single independent variables in a linear model explained 46% of the total variance—over 10% higher than any previously determined relationship between objective variables and subjective QoUL. Furthermore, we found that subjective high QoUL and subjective low QoUL were not strongly correlated, indicating that they are affected by different objective variables, respectively. This suggests that future efforts of increasing QoUL need to define their goals more precisely, as measures for increasing perceptions of high QoUL are likely different from measures for decreasing perceptions of low QoUL.

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“…The benefit of GIS is their demonstrated value in collecting, storing, and analyzing data systematically, usually with spatial (and temporal) relations, and also according to thematic groups representing various elements of the urban system (e.g., transportation, urban green, shopping facilities). Moreover, GIS combined with other methods, such as sensor measurements and questionnaires, can provide a powerful methodology for assessment and analysis, e.g., [35][36][37]. By visualizing the results of various GIS analyses in the form of maps, we can support planners and decision-makers or other stakeholders in urban quality improvement.…”

Section: Challenges Of Defining and Assessing Livabilitymentioning

confidence: 99%

Assessing and Representing Livability through the Analysis of Residential Preference

et al. 2019

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Livability reflects the quality of the person–environment relationship, namely how well the built environment or the available services in a city fulfill the residents’ needs and expectations. We argue that livability assessment can aid the implementation of certain New Urban Agenda (NUA) goals by providing a flexible way to assess urban environments and their quality. However, a reliable and transferable assessment framework requires the key elements of livability to be defined in such a way that measurable factors adequately represent the person–environment relationship. As an innovative approach, we determined key livability elements accordingly and asked over 400 residents worldwide to evaluate their urban environments using these parameters. Thereby, we could calibrate the livability assessment workflow by including personal aspects and identifying the most relevant livability factors through an ordinal regression analysis. Next, we performed relational-statistical learning in order to define the individual and combined contribution of these statistically significant factors to the overall livability of a place. We found that urban form and mobility-related factors tend to have the highest influence on residential satisfaction. Finally, we tested the robustness of the assessment by using geospatial analysis to model the livability for the city of Vienna, Austria. We concluded that the workflow allows for a reliable livability assessment and for further utilization in urban planning, improving urban quality by going beyond simple city rankings.

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Comparing Subjective and Objective Quality of Life Criteria: A Case Study of Green Space and Public Transport in Vienna, Austria

Cited by 44 publications

References 23 publications

Between the Social and Economic Dimensions of Sustainability in Rural Areas—In Search of Farmers’ Quality of Life

Between the Social and Economic Dimensions of Sustainability in Rural Areas—In Search of Farmers’ Quality of Life

Modeling Quality of Urban Life Using a Geospatial Approach

Assessing and Representing Livability through the Analysis of Residential Preference

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