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Purpose This study identifies key challenges to adopting smart real estate (SRE) technologies and offers insights and recommendations to enhance decision-making for stakeholders, including buyers and property investors. Design/methodology/approach To achieve the aim of the study, a rigorous research approach was employed, conducting an in-depth analysis of 41 academic papers utilising PRISMA guidelines and checklists. The chosen methodology also applies a PEST (Political, Economic, Social and Technological) framework to identify factors influencing technology adoption in the real estate sector. Findings The study uncovers critical challenges to adopting smart real estate technologies, such as regulatory ambiguity, high implementation costs, and societal resistance. PEST analysis reveals that unclear standards and guidelines, coupled with the high financial burden of technology implementation, are significant obstacles. Socially, resistance to change and difficulties in integrating new technologies are prevalent. The study also underscores the potential of artificial intelligence (AI) for predictive analytics and blockchain for secure transactions and records, though their adoption is currently hindered by inadequate infrastructure and regulatory challenges. These findings underscore the need for strategic interventions to address these challenges and facilitate the effective integration of advanced technologies in the real estate sector, thereby enhancing industry innovation and competitiveness. Practical implications The study offers insights for real estate stakeholders to embrace technology effectively, with a conceptual framework contributing to industry advancements. Originality/value The study’s key contribution is offering real estate stakeholders execution tactics and recommendations to navigate challenges and utilise technology, thereby driving industry innovation and enhancing competitiveness.
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Stored only when both papers are in the corpus — 11 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.