Integrating Digital Twins in Real Estate: Revolutionising Property Management

Abstract

The use of digital twin technology in property management is examined in this study, with a focus on the Malaysian real estate market. Thus, the goal is to use digital twins with real-time monitoring, predictive maintenance, and building system optimisation to overcome the inefficiencies of traditional property management. The study has various significances, first as it fulfils the research goals of not only pinpointing the inefficiencies and problems that the traditional property management process in Malaysia is currently facing but also structuring a path towards having the advanced digital twin technology introduced to the given field. In general, the study examined both residential and commercial properties, including office buildings and high-rise apartments. A mixed methodology is used in the study, which includes quantitative data from 100 tenants and qualitative interviews with 50 property managers regarding the cost reduction, tenant satisfaction, and operational efficiency of digital twins. While quantitative data was subjected to descriptive and inferential statistical methods using SPSS as the preferred statistical package, qualitative data was subjected to thematic analysis. The results are maintenance expenses have decreased by 30%, tenant complaints have decreased by 25%, and operating expenses have decreased by 20%. These findings also highlight issues with key data integration, including scalability of digital twin applications, data security issues, and interoperability between legacy systems and digital twins. Despite the fact that the technology has many advantages, the study makes it evident that more research is required to fully examine cost-benefit analysis over an extended period of time and to determine whether the technology can scale across various property types. The results offer valuable perspectives for policymakers, property managers, and individuals seeking to incorporate these technologies into real estate management.