<p>Tenant satisfaction is a central indicator of effective Property Management Practices. In emerging real estate markets, however, these practices often lack coherent prioritization of core property management functions, namely planning, controlling, and responding, thus raising questions about their influence on tenant satisfaction. This study examines these relationships in six commercial and residential buildings across Dar es Salaam, Dodoma, and Arusha, Tanzania, with particular attention to technology adoption in property management. Employing a mixed-methods convergent parallel design, quantitative data were collected from 213 tenants through structured questionnaires, while qualitative insights were obtained from s emi-structured interviews with six property managers (PMs). Quantitative analysis involved descriptive statistics, factor analysis, and reliability testing (Cronbach’s <i>α</i> = 0.77), while qualitative data were thematically coded using QualCoder. Findings indicate that property managers who integrate planning, controlling, and responding functions in a balanced manner achieve the highest tenant satisfaction levels (above 80%). Controlling, particularly in lease enforcement, rental billing, energy management, and security monitoring, emerged as the strongest predictor of tenant satisfaction, while weak planning was the primary source of dissatisfaction. Technology adoption (e.g., AI-driven maintenance and digital communication) enhanced responsiveness but had limited effect where tenant trust in automation was low. Factor analysis identified three principal components, customer care, rental costs, and security and monitoring, explaining 78.9% of the variance in tenant satisfaction. The results suggest that in contexts with nascent regulatory frameworks, structured controlling functions can sustain high satisfaction even where planning is less developed, but balanced property management practice strategies remain optimal. Technology-first approaches may yield limited benefits unless paired with trust-building measures and adapted to local infrastructural realities. These findings contribute to the theoretical refinement of the planning and controlling framework in property management, support culturally adapted applications of the Technology Adoption Model and Expectancy-Disconfirmation Theory, and offer policy-relevant guidance for improving tenant satisfaction in low-resource property markets.</p>