Perceived thermal comfort and workplace well-being: a seasonal analysis integrating environmental sensor data

Thermal comfort plays a critical role in workplace satisfaction and well-being. However, few studies combine objective sensor data and subjective perceptions across real-world office settings and seasonal variability. This study investigates whether objective and perceived indicators of thermal comfort predict job satisfaction. We examined whether discomfort is driven more by physical conditions or by a mismatch between current and preferred thermal states. Data were collected across four seasons in three public office buildings in Bolzano, Italy. Participants (n ≈ 56 per season) completed a survey on perceived thermal comfort, desired thermal state, causes of discomfort (e.g., air drafts, surfaces), job satisfaction, perceived performance, and well-being. Indoor temperature was continuously monitored via environmental sensors. A hierarchical linear regression was conducted with job satisfaction as the dependent variable. Predictors were added in four steps: (1) objective variables (temperature, season, building), (2) perceived causes of discomfort, (3) desired thermal state and (4) a mismatch index based on absolute deviation from thermal preference. Only the third model was statistically significant (p = .009), with both causes of discomfort (β = –0.51, p = .018) and desired thermal state (β = 0.61, p = .001) predicting job satisfaction. Temperature, season, and building were not significant. The final model showed a small additional improvement (adj. R² = .11), but no significant effect for mismatch. Subjective perceptions, especially unmet thermal preferences, appear more critical than objective temperature in shaping workplace satisfaction. Findings support user- centered approaches to indoor climate regulation.