arXiv subjects

Christopher K. Allsup

Publications and source records attributed to Christopher K. Allsup.

4 recordsLinked to original sources

arXiv2026

Stretching Rubber, Not Budgets: Accurate Parking Utilization on a Shoestring

Effective parking management is essential for ensuring safety and convenience in master-planned communities, particularly in active adult neighborhoods experiencing rapid growth. Accurately assessing parking utilization is a crucial first step in planning for future demand, but data collection methods can be costly and labor-intensive. This paper presents a low-cost yet highly accurate methodology for measuring parking utilization using pneumatic road tubes connected to portable traffic counters from JAMAR Technologies, Inc. By integrating results from JAMAR's analysis tool with custom Python scripting, the methodology enables precise parking lot counts through automated parameter optimization and error correction. The system's efficiency allows for scalable deployment without significant manual observation, reducing both costs and disruptions to daily operations. Using Tellico Village as a case study, this effort demonstrates that community planners can obtain actionable parking insights on a limited budget, empowering them to make informed decisions about capacity expansion and facility scheduling.

eess.SY↗

arXiv2025

Democratizing Strategic Planning in Master-Planned Communities

This paper introduces a strategic planning tool for master-planned communities designed specifically to quantify residents' subjective preferences about large investments in amenities and infrastructure projects. Drawing on data obtained from brief online surveys, the tool ranks alternative plans by considering the aggregate anticipated utilization of each proposed amenity and cost sensitivity to it (or risk sensitivity for infrastructure plans). In addition, the tool estimates the percentage of households that favor the preferred plan and predicts whether residents would actually be willing to fund the project. The mathematical underpinnings of the tool are borrowed from utility theory, incorporating exponential functions to model diminishing marginal returns on quality, cost, and risk mitigation.

econ.EM↗

arXiv2025

Resident Turnover and Community Satisfaction in Active Lifestyle Communities

An analysis of Tellico Village, a non-age-restricted active lifestyle community, reveals complex patterns in resident tenure and satisfaction. Longitudinal surveys (2018-2024) and property records show consistently high satisfaction levels (93%), yet a decline in median tenure from 13 years pre-COVID to 11 years post-COVID (p < 0.001), reflecting a broader nationwide trend in homeownership duration. Kaplan-Meier survival analysis identifies departure risk peaks at years 3, 5, 7, 11, 16, 22, and 26, corresponding to life transitions and market cycles. Satisfaction follows a U-shaped trajectory, lowest between years 6-9 (3-12). Key predictors include financial attitudes, recreational engagement, and openness to growth. While aggregate willingness to pay higher POA fees strongly correlates with satisfaction, explaining 94% of the variance, this relationship weakens at the neighborhood (44%) and household (5%) levels. Machine learning models - including Support Vector Machines, Random Forests, and XGBoost - and hedonic price analysis provided limited predictive power, suggesting the influence of unmeasured variables. The study advances understanding of housing tenure dynamics in lifestyle communities while highlighting the need for more sophisticated longitudinal tracking and instrumental variable approaches.

stat.AP↗

arXiv2024

Modeling the Dynamics of Growth in Master-Planned Communities

This paper describes how a time-varying Markov model was used to forecast housing development at a master-planned community during a transition from high to low growth. Our approach draws on detailed historical data to model the dynamics of the market participants, producing results that are entirely data-driven and free of bias. While traditional time series forecasting methods often struggle to account for nonlinear regime changes in growth, our approach successfully captures the onset of buildout as well as external economic shocks, such as the 1990 and 2008-2011 recessions and the 2021 post-pandemic boom. This research serves as a valuable tool for urban planners, homeowner associations, and property stakeholders aiming to navigate the complexities of growth at master-planned communities during periods of both system stability and instability.

econ.EM↗