Calibrating Resident Surveys with Operational Data in Community Planning

TL;DR

This paper presents a method to calibrate resident survey perceptions with actual operational data, revealing that dissatisfaction correlates with effective capacity constraints rather than nominal limits, aiding better community planning decisions.

Contribution

It introduces a framework that maps perceived problem rates to utilization data, integrating behavioral metrics into community performance assessments for improved decision-making.

Findings

Dissatisfaction occurs near effective capacity, not nominal capacity.

Perceived difficulty is higher among active users due to operational frictions.

Calibrating perceptions with data improves diagnosis of system conditions.

Abstract

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.