Modeling Supply & Demand in the Self-Storage Market Using Data Envelopment Analysis (DEA)

This study investigates the drivers of structural demand for self-storage facilities and market attractiveness across New Jersey's diverse counties, using a refined dataset of 821 facilities from 2020 to 2023. By focusing exclusively on structural demand, this analysis intentionally excludes cyclical demand fluctuations caused by economic cycles, providing a clearer picture of long-term market dynamics. Key variables influencing Net Rentable Square Feet (NRSF) per capita and facilities per capita were identified through regression analysis and subsequently analyzed via Data Envelopment Analysis (DEA) to assess the overall efficiency of the self-storage industry in New Jersey’s 21 counties. This study innovatively fills a significant industry gap by utilizing NRSF per capita and facilities per capita as proxies in the DEA, where direct unit data availability is often scarce. Findings indicate a marked reliance on self-storage correlated with urban densification and demographic changes. Efficiency scores revealed varying levels of industry success in meeting these demands, offering urban planners and the self-storage industry valuable data-driven insights for strategic development in the evolving urban landscape.