Impact of Tenant Satisfaction on Commercial Property Vacancy Rates: An Empirical Study

Thesis Abstract

This study investigates how tenant satisfaction influences vacancy rates in urban commercial properties, addressing the persistent mismatch between tenant perceptions and observable occupancy dynamics that undermines asset performance. The problem stems from limited empirical evidence linking satisfaction determinants—maintenance responsiveness, amenity quality, lease flexibility, and communication effectiveness—to measurable vacancy outcomes in diversified property portfolios. The aim is to quantify the impact of tenant satisfaction on vacancy rates and to identify which satisfaction dimensions most strongly predict occupancy stability in commercial estates. Specific objectives are (1) to measure overall tenant satisfaction across a representative sample of office and retail properties; (2) to examine the relationship between satisfaction sub-dimensions (facility management, financial terms, communication, and building environment) and vacancy rates; (3) to assess moderating effects of property class, location, and lease type on the satisfaction–vacancy relationship; (4) to develop a predictive model of vacancy likelihood using satisfaction metrics; and (5) to offer managerial recommendations for improving occupancy performance. The methodology adopts a positivist, cross-sectional research design complemented by a longitudinal component to capture vacancy fluctuations over a two-year window. The population comprises commercial properties within the central business districts and secondary markets of three major metropolitan regions, totaling approximately 180 properties managed by 50 firms. A stratified random sampling approach will select 120 properties, with tenant surveys distributed to a minimum of 2,400 tenants (mean of 20 tenants per property) to ensure adequate power for multivariate analyses. Data collection will combine (i) tenant-level survey instruments validated for reliability (Cronbach’s alpha > 0.70) to measure satisfaction dimensions, perceived service quality, and intention to renew; and (ii) property-level records sourced from facility managers documenting vacancy rates, lease expiry calendars, and turnover costs. The survey instrument will incorporate Likert-scale items aligned with established scales in facility management and customer satisfaction literature, plus open-ended questions to capture nuanced experiences. Secondary data will include building age, size, class, location quality, and amenity provision. Validity and reliability will be ensured through pretesting, confirmatory factor analysis (CFA) for the satisfaction construct, and test-retest reliability for key scales. Data analysis will proceed in three stages descriptive statistics to profile satisfaction levels and vacancy distributions; multilevel (hierarchical) linear modeling (HLM) to account for tenant- and property-level variation and to estimate the impact of satisfaction dimensions on vacancy rates while controlling for confounders; and structural equation modeling (SEM) to test the hypothesized causal pathways among satisfaction constructs and occupancy outcomes. Additional regression analyses will explore interaction effects to identify moderating roles of property class (A, B, C) and lease type (gross, net). The theoretical framework will anchor on the Expectation-Confirmation Theory and Signaling Theory, augmented by the Asset-Performance perspective from real estate literature, to explain how satisfaction signals influence tenant renewal decisions and vacancy dynamics. Expected findings include a negative and statistically significant relationship between overall tenant satisfaction and vacancy rates, with maintenance responsiveness, and communication quality emerging as the strongest predictors. The study anticipates that the impact of satisfaction on vacancy will be stronger in premium class A properties and in markets with higher rent sensitivity, with lease type moderating effects evident—gross leases may attenuate the satisfaction–vacancy link due to bundled services. The contribution to knowledge lies in providing the first large-scale, multi-market empirical evidence linking tenant satisfaction to objective occupancy performance, integrating both tenant-reported perceptions and property-level outcomes, and offering a validated predictive model for vacancy risk anchored in satisfaction metrics. The main conclusion is that enhancing tenant satisfaction yields lower vacancy propensity and improved renewal rates, contributing to asset value and cash-flow stability. Practical recommendations include strengthening responsive maintenance protocols, optimizing communication channels between property managers and tenants, revising lease terms to balance transparency and flexibility, and prioritizing amenity investments aligned with tenant preferences identified in the study. Policymakers and practitioners are advised to adopt a data-driven dashboard integrating satisfaction indicators with vacancy metrics to monitor and mitigate occupancy risk across commercial property portfolios.