Dataset for Structural Equation Modelling in Environmental Psychology: nZEB Retrofitting in Cluj-Napoca,

Description:

This data repository contains survey responses collected by the Romanian Institute for Social Research (IRES) using Computer-Assisted Telephone Interviewing (CATI) in January 2024. The dataset was designed to investigate the mediational pathways between environmental values, beliefs, norms, and energy efficiency behaviours in the context of nearly Zero Energy Building (nZEB) retrofitting. Specifically, we examine how values influence pro-environmental action purposes, mediated by climate beliefs, social norms, and trust, while considering socio-demographic attributes as confounders.

The study contributes to understanding how psychological constructs and demographic factors shape pro-environmental behaviour in urban sustainability transitions. It applies the Value-Belief-Norm (VBN) theory, extending it to an urban context characterized by rapid development and demographic shifts.

Data Collection & Methodology

Survey Implementation

Two waves of interviews were conducted to ensure validity and reliability:

• Wave 1: 100 pilot interviews (average duration: 28 minutes) tested the internal consistency of scales, assessed using Cronbach's alpha and McDonald's omega.
• Wave 2: 1,226 interviews (average duration: 19 minutes) were conducted, from which 1,002 valid responses were retained (no data imputation was performed).

Sampling & Representativity

• The Cluj Metropolitan Area was oversampled, ensuring meaningful comparisons between urban and suburban areas.
• Initial underrepresentation of young respondents (under 29 years old) and men was corrected through post-stratification weighting based on official INS Tempo (2022) demographic data.
• After weighting, the final sample is statistically representative of the Cluj Metropolitan Area, with a maximum margin of error of ±3.6%.
• Occupational & educational distributions closely match regional labour market trends:
• • Education levels: 4.1% primary/secondary, 46% secondary, 49% tertiary.
  • Socio-economic Index (SEI): Constructed following Ganzeboom et al. (1992) and Treiman (2019) to measure income, education, and occupational prestige.

Questionnaire Structure & Constructs

The survey integrates validated psychometric scales from the literature, translated into Romanian, and structured into the following sections:

A. Home Information

• Dwelling type, material, surface area, heating system, thermal insulation, and window types.

B. Energy & Gas Consumption

• Appliance age, energy-saving devices, electricity/gas-saving efforts, and lighting types.

C. Climate Change Beliefs, Values, Norms, and Behaviour

• Values (Hedonic, Egoistic, Altruistic, Biospheric) – Based on De Groot & Steg (2008).
• Beliefs (Climate Beliefs, Climate Urgency) – Based on van Valkengoed et al. (2021).
• Norms (Problem Awareness, Efficiency Commitment) – Based on van der Werff & Steg (2015).
• Action Purposes (Personal, Block-Level, Neighbourhood-Level) – Based on Hurst, Loo, & Walker (2023).
• Trust (Stakeholder trust in climate action & governance) – Based on Uslaner (2003).

D. Socio-Economic & Demographic Variables

• Socio-Economic Index (SEI): Composite of income, education, and occupational status.
• Demographics: Gender, age (55+), ethnic minority status.

nZEB Retrofitting & Policy Relevance

The dataset investigates the role of psychological and social factors in nZEB retrofitting adoption. Romania's 2023 nZEB legislation, aligned with Directive 2010/31/EU, mandates that at least 30% of a building’s energy consumption come from renewable sources (on-site or nearby). Key elements of nZEB retrofitting include:

• Improved insulation
• High-performance windows
• Optimized heating/cooling systems
• Enhanced ventilation & lighting
• Renewable energy integration

Understanding barriers and drivers of nZEB adoption is critical for designing effective policy interventions targeting sustainability in urban housing.

Dataset Contents

• data.csv: Primary dataset with all survey responses (fully anonymized).
• transform variables.R: R script for Categorical Principal Component Analysis (C-CPA) using GiFi.
• lavaan.R: R script for Structural Equation Modelling (SEM) analysis using lavaan.
• Constructs Diagram.txt: mxGraph JScript for visual representation of the psychological constructs used in the study.
• VBN-A Diagram.txt: mxGraph JScript for conceptual diagram mapping VBN Theory onto nZEB retrofitting actions-purposes
• Questionnaire in English.txt: Survey questionnaire (English translation).
• Questionnaire in Romanian.txt: Survey questionnaire (original Romanian version).

Statistical Analysis

• Categorical Principal Component Analysis (C-PCA):
• • Weighting & Demographic Adjustments
  • Factor loadings, KMO, Cronbach’s α, McDonald’s ω, eigenvalues provided for construct validity.
  • Ensuring population representativity using INS Tempo (2022) benchmarks.
• Structural Equation Modelling (SEM):
• • Lavaan package in R
  • Regression coefficients reported with estimates, standard errors, and z-values.
  • Confidence intervals included for transparency.
  • Fit indices: R², CFI, RMSEA, and SRMR.

Ethical Considerations

• Approval & Consent: The study protocol was approved by our institution.
• Anonymity: Data collection adhered to strict confidentiality procedures.
• Informed Consent: Verbal consent was obtained before participation.