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Expert vs. Lay Evaluation of Environmental Quality - I

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Expert vs. Lay Evaluation of Environmental Quality - I

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  1. SCALES ON PERCEIVED URBAN RESIDENTIAL QUALITY INDICATORS AND NEIGHBOURHOOD ATTACHMENT: A CONFIRMATORY ANALYSIS OF FACTORIAL STRUCTURESMarino Bonaiuto, Ferdinando Fornara, Mirilia BonnesUniversity of Rome “La Sapienza”Dipartimento di Psicologia dei Processi di Sviluppo e Socializzazione18th IAPS Conference. Wien, 5-10 July 2004

  2. Expert vs. Lay Evaluation of Environmental Quality - I • Expert Evaluation: also defined as “objective” or “technical” (Gifford, 2002) It involves tools and “hard” measures such as mechanical monitoring or objective indexes and estimates (e.g.: building density) to quantify EQ Evaluation as by-product of processes of analytic measure elicited from coded systems in the realm of technical-scientific knowledge

  3. Expert vs. Lay Evaluation of Environmental Quality - II • Layperson Evaluation: also defined as “subjective” or “observer-based” (Gifford, 2002) It relies on self-report tools through which people express their judgment on EQ (i.e.: the quality of an environmental object as it is experienced) Evaluation as by-product of daily psycho-social processes of knowledge, interpretation and use of the environment by the persons who experience it.

  4. Expert vs. Lay Evaluation of Environmental Quality - III • Both kinds of environmental evaluation aspire to objectivity by getting reproducible measures which are valid, reliable, sensible and useful • As well, both share subjectivity, since also expert evaluation relies on choice about which environmental dimensions and elements to assess, which sample of place and time to select (Uzzell, 1989)

  5. Expert vs. Lay Evaluation of Environmental Quality - IV • Different values, ideas and goals about the environment underlie expert and lay evaluation: this can produce discordance between the two kinds (e.g., the evaluation of urban green areas: wilderness vs. usability; see Bonnes & Bonaiuto, 1995) • For that, it is important to compare and integrate expert and lay evaluation data for improving environmental design and management

  6. Perceived Environmental Quality Indicators (PEQIs) - I • What are PEQIs? …a standard set of (perceived) indicators for a specific environmental object or place (e.g.: residential PEQIs), which can also be used for policy and monitoring functions (Bonaiuto, in press) • Initial goal (Craik & Zube, 1976): to set valid and general standards of perceived environmental quality for environmental elements such as air, water and light

  7. Perceived Environmental Quality Indicators (PEQIs) - II • Limits of the earliest approach: - no focus on contextual specificity of person-environment relationship - ignoring social construction processes which influence lay evaluation - molecolar units of analysis

  8. Residential Satisfaction (RS) - I • What is RS? …an evaluative response which regards the experience of pleasure or gratification deriving from living in a specific place (Amerigo, 2002) • RS is a construct of multidimensional nature which include cognitive, affective and behavioural aspects (Francescato, 2002)

  9. Residential Satisfaction (RS) - II • Focus on cognitive aspects - PEQIs of urban neighbourhoods: residents’ evaluation of the degree of quality possessed by salient attributes of residential environment • Focus on affective aspects - Neighbourhood Attachment (refers to the broader construct of Place Attachment , see Giuliani, 2003): feelings and emotions that people develop over time and come to experience with reference to home and their neighbourhood

  10. PEQIs of urban neighbourhoods Canter (1983), Guest e Lee (1984), Bonnes et al. (1991): Spatial features (architectural and town-planning) Human-social features (kind of neighbours and neighbourhood life) Functional features (services and facilities) In addition (Bonnes et al., 1997; Bonaiuto et al., 1999): Contextual features(pace of life; pollution; environmental maintenance)

  11. PREQ and NA indicators for urban places Setting up scales measuring indicators of Perceived Residential Environment Quality (PREQ) and Neighbourhood Attachment (NA) A long period of a step-by-step research process, including the consequential phases of: - scales’ creation - empirical verification - scales’ refinement - new empirical verification Data have been gathered mainly in neighbourhoods of a great city (i.e., Rome).

  12. Final path analysis model including the best predictors (>0.15) from each one of the four content areas and neighbourhood attachment as criterion. Χ2 = 25,91 (20), p=0.17, GFI =0.99, AGFI=0.97, CFI =0.99. Source: Bonaiuto et al., 1999 Lack of opportunities r²=0.02 Length of residence inRome 0.15 -0.15 -0.25 Length of residence in the neighborhood 0.20 0.12 Quiet r²=0.01 Neighbourhood Attachment r²=30 0.20 Estimated socio- economic level -0.12 0.15 Buildings’s aesthetic Pleasantness r²=0.02 0.17 -0.23 Presence of social relationship r²=0.02 0.15 -0.08 Number of persons living together -0.13 -0.08 -0.08 Lack of green areas r²=0.05 Inadequacy of cultural activities and meeting places r²=0.01 0.08

  13. Research objective Research hypothesis Validation of the factorial structure of themost recent version of PREQ and NA scales in middle- and low- extension urban environments • A Confirmatory Factor Analysis will confirm the scales’ factorial structure and the reliability of PREQ and NA indicators emerged in a previous Exploratory Factor Analysis on the same data (see Bonaiuto et al., in press)

  14. Architectural/town-planning features (3 scales): - Architectural and town-planning space (22 items) - Organization of accessibility and roads (14 items) - Green spaces (10 items) Social relations features (1 scale): People and social relations (24 items) Context features (3 scales): - Pace of life (16 items) - Environmental health (8 items) - Maintenance and care (12 items) Punctual and in-network services (4 scales): - Welfare services (12 items) - Cultural-recreational services (16 items) - Commercial services (8 items) Transportation services (8 items) Place Attachment (1 scale): Neighbourhood Attachment (8 items) ToolsThe 4 Generative Criteria and the 11 PREQ Scales (items = 150) and 1 NA Scale (items = 8)

  15. Sample Data analysis • Exploratory FA: Principal Component Analysis • Confirmatory Factor Analysis on each PREQ and NA scale: • - 3 (multi-factorial scales) or 4 (mono-factorial scales) item aggregates were created for running CFA - Sample split (males vs. females) in order to get a cross- sectional validation of structures - Comparison of nested models in order to choose the best fitting solution (Test Χ2 , a=.05) 1488 residents in different neighbourhoods of 11 Italian medium- and low-estension urban contexts (i.e. Palermo, Latina, Cesena, Pescara, L’Aquila, Grosseto, Agrigento, Firenze, Bologna, Matera, Salerno)

  16. Results of Principal Component Analysis on PREQ and NA indexes:number of items and Cronach’s Alfa (Source: Bonaiuto et al., in press)

  17. BD1 BD2 BD3 BA1 BA2 BA3 BV1 BV2 BV3 δ1 .86 Building Density NESTED MODELS Baseline Χ2 = 202.18 (48), S l invariant ΔΧ2 = 3.47 (9), NS l, F invariant ΔΧ2 = 2.02 (3), NSAccepted .81 δ2 .87 Architectural/town planning featuresArchitectural/town planning spaces – PREQ Scale 1 δ3 .45 δ4 .88 Building Aesthetics .90 .66 δ5 .82 δ6 .43 δ7 .84 Building Volume .90 δ8 FIT INDICES NNFI = 0.98 CFI = 0.98 RMSEA = 0.058 .89 δ9 N males = 744, N females = 741

  18. IP1 δ1 Internal Practicability IP2 δ2 IP3 δ3 EC1 δ4 External Connections EC2 δ5 EC3 δ6 .86 .82 NESTED MODELS Baseline Χ2 = 48.14 (16), S l invariant ΔΧ2 = 6.77 (6), NS l, F invariant ΔΧ2 = 1.93 (1), NSAccepted .70 Architectural/town planning featuresOrganization ofaccessibility and roads – PREQ Scale 2 .31 .82 .80 .73 FIT INDICES NNFI = 0.99 CFI = 0.99 RMSEA = 0.045 N males = 744, N females = 741

  19. GA1 δ1 GA2 δ2 Green Areas GA3 δ3 GA4 δ4 NESTED MODELS Baseline Χ2 = 30.02 (4), S l invariant ΔΧ2 = 3.74 (4), NS l, Өδ invariant ΔΧ2 = 3.29 (4), NS Accepted Architectural/town planning featuresGreen areas – PREQ Scale 3 .86 .88 .89 .79 FIT INDICES NNFI = 0.99 CFI = 0.99 RMSEA = 0.053 N males = 744, N females = 741

  20. NESTED MODELS Baseline Χ2 = 214.18 (48), S l invariant ΔΧ2 = 17.25 (9), S l, Өδ invariant ΔΧ2 = 10.68 (9), NS l, Өδ,F invariant ΔΧ2 = 5.97 (3), NSAccepted ST1 δ1 .82 Security and Tolerance .82 ST2 δ2 .84 Social relations featuresPeople and social relations – PREQ Scale 4 ST3 δ3 .41 DC1 δ4 .76 Discretion and Civility .83 DC2 δ5 .44 .86 DC3 δ6 .18 SC1 δ7 .81 Sociability and Cordiality .80 SC2 FIT INDICES NNFI = 0.97 CFI = 0.97 RMSEA = 0.059 δ8 .70 SC3 δ9 N males = 744, N females = 741

  21. SS1 δ1 School Services SS2 δ2 SS3 δ3 SC1 δ4 Social-Care services SC2 δ5 SC3 δ6 NESTED MODELS Baseline Χ2 = 41.49 (16), S l invariant ΔΧ2 = 8.79 (6), NS l, Өδ invariant ΔΧ2 = 2.52 (6), NS l, Өδ,F invariant ΔΧ2 = 0.69 (1), NSAccepted .75 .95 .72 Functional featuresWelfare services – PREQ Scale 5 .46 .75 .59 .56 FIT INDICES NNFI = 0.99 CFI = 0.99 RMSEA = 0.054 N males = 744, N females = 741

  22. SS1 δ1 Sport Services SS2 δ2 SS3 δ3 SA1 δ4 Socio-cultural Activities SA2 δ5 SA3 δ6 NESTED MODELS Baseline Χ2 = 60.11 (16), S l invariant ΔΧ2 = 1.86 (6), NS l, Өδ invariant ΔΧ2 = 10.63 (6), NS l, Өδ,F invariant ΔΧ2 = 0 (1), NSAccepted .85 .88 .86 Functional featuresRicreational services – PREQ Scale 6 .41 .90 .71 .75 FIT INDICES NNFI = 0.99 CFI = 0.99 RMSEA = 0.045 N males = 744, N females = 741

  23. CS1 δ1 CS2 δ2 Commercial Services CS3 δ3 CS4 δ4 NESTED MODELS Baseline Χ2 = 100.14 (4), S l invariant ΔΧ2 = 1.26 (4), NS l, Өδinvariant ΔΧ2 = 3.29 (4), NSAccepted Functional featuresCommercial services – PREQ Scale 7 .84 .89 .83 .74 FIT INDICES NNFI = 0.97 CFI = 0.97 RMSEA = 0.102 N males = 744, N females = 741

  24. TS1 δ1 TS2 δ2 Transport Services TS3 δ3 TS4 δ4 NESTED MODELS Baseline Χ2 = 9.60 (4), S l invariant ΔΧ2 = 4.07 (4), NS Accepted Functional featuresTransport services – PREQ Scale 8 .79 .83 .84 .86 FIT INDICES NNFI = 1.00 CFI = 1.00 RMSEA = 0.035 N males = 744, N females = 741

  25. RD1 δ1 Relaxing vs. Distressing RD2 δ2 RD3 δ3 SB1 δ4 Stimulating vs. Boring SB2 δ5 SB3 δ6 NESTED MODELS Baseline Χ2 = 38.01 (16), S l invariant ΔΧ2 = 2.96 (6), NS l, Өδ invariant ΔΧ2 = 3.97 (6), NS l, Өδ,F invariant ΔΧ2 = 1.74 (1), NSAccepted .87 .88 .77 Context featuresPace of life – PREQ Scale 9 -.10 .83 .83 .78 FIT INDICES NNFI = 1.00 CFI = 1.00 RMSEA = 0.029 N males = 744, N females = 741

  26. EH1 δ1 EH2 δ2 Evironment. Health EH3 δ3 EH4 δ4 NESTED MODELS Baseline Χ2 = 14.32 (4), S l invariant ΔΧ2 = 2.02 (4), NS Accepted Context featuresEnvironmental health – PREQ Scale 10 .80 .90 .88 .90 FIT INDICES NNFI = 1.00 CFI = 1.00 RMSEA = 0.037 N males = 744, N females = 741

  27. UC1 δ1 UC2 δ2 Upkeep and Care UC3 δ3 UC4 δ4 NESTED MODELS Baseline Χ2 = 26.41 (4), S l invariant ΔΧ2 = 3.70 (4), NS l, Өδ invariant ΔΧ2 = 2.59 (4), NS Accepted Context featuresUpkeep and care – PREQ Scale 11 .80 .79 .80 .76 FIT INDICES NNFI = 0.99 CFI = 0.99 RMSEA = 0.048 N males = 744, N females = 741

  28. NA1 δ1 NA2 δ2 Neighbourh. Attachment NA3 δ3 NA4 δ4 NESTED MODELS Baseline Χ2 = 43.54 (4), S l invariant ΔΧ2 = 0.17 (4), NS l, Өδ invariant ΔΧ2 = 5.94 (4), NS Accepted Neighbourhood AttachmentNeighbourhood attachment – NA Scale .80 .88 .86 .86 FIT INDICES NNFI = 0.99 CFI = 0.99 RMSEA = 0.065 N males = 744, N females = 741

  29. Conclusions CFA confirmed - 19 Perceived Residential Environment Quality (PREQ) - 1 Neighbourhood Attachment (NA) Next validity developments - Comparison between PREQIs and expert assessments - Test PREQIs’ discriminant validity (different neighbourhoods) - Test PREQIs in different countries - Test relationship between PREQIs, neighbourhood attachment and Satisfaction

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