Purpose This research quantifies the economic viability and spatial efficiency of Internet of Things (IoT) -enabled adaptive furniture systems (IoT-hybrid adaptive and full robotic) in corporate real estate contexts. This study aims to address the persistent misalignment between static workplace configurations and dynamic occupancy patterns, which results in 62. 2% average vacancy rates despite substantial real estate investments. Design/methodology/approach This study used a sequential mixed-methods design comprising four integrated phases: (1) empirical analysis of 12. 4 billion occupancy data points collected from 130 organizations over a 36-month observation period; (2) development and testing of a functional prototype incorporating Arduino-based sensor networks with multiple control mechanisms governing three actuation systems; (3) computational spatial analysis using digital twin modeling; and (4) economic evaluation using net present value and internal rate of return calculations across diverse market contexts. Findings Adaptive systems achieved 60% space reduction in time-weighted analysis (65–70 square feet per person versus 92 square feet conventional), while fully robotic configurations achieved 46. 2 square feet per person with 77% improvement in spatial efficiency. The spatial case study demonstrated capacity improvements from 19 workstations (conventional) to 28 (adaptive) to 40 (fully robotic) within identical 2, 179-square-foot floor area. Economic analysis identified market-dependent viability thresholds: full robotic systems require annual rental rates exceeding 75 per square foot (5%–8% market coverage), hybrid adaptive systems prove viable above 48 per square foot (42% market coverage), while IoT-informed reallocation strategies achieve positive returns at just 21 per square foot (95% market coverage). Practical implications Corporate real estate executives could consider implementing tiered automation strategies based on local market conditions: IoT-based reallocation for markets below 48 per square foot, hybrid adaptive systems for 48–75 per square foot markets and full robotic automation only in premium markets exceeding 75 per square foot. The framework provides specific decision criteria and phased implementation guidance. Originality/value This study presents a novel integration of empirical validation, prototype testing, spatial case study analysis and market-specific economic modeling to establish adoption thresholds for adaptive workplace technologies adoption in corporate real estate.
Suleiman Alhadidi (Tue,) studied this question.