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Main Author: Gabashvili, Irene S.
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.24899
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author Gabashvili, Irene S.
author_facet Gabashvili, Irene S.
contents Community associations rely heavily on resident surveys to guide decisions about amenities, infrastructure, and services. However, survey responses reflect perceptions that may not directly correspond to underlying operational conditions. This study bridges that gap by calibrating survey-based satisfaction measures against objective utilization data. Using parking and facility data from Tellico Village, we map perceived problem rates to utilization exceedance probabilities to estimate behavioral congestion thresholds. Results show that dissatisfaction emerges near effective capacity - once spatial, temporal, and informational constraints are considered - rather than at nominal capacity limits. Perceived difficulty is concentrated among active users and is shaped by operational frictions and incomplete system knowledge. These findings demonstrate that perceived congestion reflects constraints on access and reliability, not simply physical shortages. By distinguishing between effective and nominal capacity, the proposed framework enables more accurate diagnosis of system conditions. We propose incorporating behavioral metrics into community performance frameworks to support better decision-making, reduce unnecessary capital expansion, and target operational improvements more effectively.
format Preprint
id arxiv_https___arxiv_org_abs_2603_24899
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Calibrating Resident Surveys with Operational Data in Community Planning
Gabashvili, Irene S.
Econometrics
Applications
Community associations rely heavily on resident surveys to guide decisions about amenities, infrastructure, and services. However, survey responses reflect perceptions that may not directly correspond to underlying operational conditions. This study bridges that gap by calibrating survey-based satisfaction measures against objective utilization data. Using parking and facility data from Tellico Village, we map perceived problem rates to utilization exceedance probabilities to estimate behavioral congestion thresholds. Results show that dissatisfaction emerges near effective capacity - once spatial, temporal, and informational constraints are considered - rather than at nominal capacity limits. Perceived difficulty is concentrated among active users and is shaped by operational frictions and incomplete system knowledge. These findings demonstrate that perceived congestion reflects constraints on access and reliability, not simply physical shortages. By distinguishing between effective and nominal capacity, the proposed framework enables more accurate diagnosis of system conditions. We propose incorporating behavioral metrics into community performance frameworks to support better decision-making, reduce unnecessary capital expansion, and target operational improvements more effectively.
title Calibrating Resident Surveys with Operational Data in Community Planning
topic Econometrics
Applications
url https://arxiv.org/abs/2603.24899