Analysis of building maintenance process solutions in the management of commercial real estate
DOI: https://doi.org/10.3846/mla.2026.27390Abstract
Building maintenance is one of the key areas of real estate management, ensuring the technical reliability of buildings, user safety, and the preservation of long-term asset value. As business clients’ expectations increase and digital technologies continue to evolve, the efficiency of building maintenance processes has become an essential factor in ensuring operational continuity and competitiveness. The aim of this study is to analyse building maintenance process solutions applied in the management of commercial real estate and to identify the main directions for process improvement. The research was based on a qualitative methodology, including a literature review, semi-structured expert interviews, cause-and-effect analysis, and SWOT analysis. Five experienced professionals representing the fields of real estate management and building maintenance participated in the expert survey. The findings indicate that the effectiveness of maintenance processes is primarily influenced by standardized procedures, employee competence, preventive maintenance practices, and the integration of digital technologies. The study also demonstrates that Building Information Modelling (BIM), Computerized Maintenance Management Systems (CMMS), and Internet of Things (IoT) technologies provide significant opportunities for improving maintenance planning, data management, and decision-making. Based on the research findings, practical recommendations and a building maintenance process improvement model are proposed for the management of commercial real estate.
Article in Lithuanian.
Pastatų priežiūros proceso sprendinių analizė valdant verslo klientų nekilnojamąjį turtą
Santrauka
Pastatų priežiūra yra viena svarbiausių nekilnojamojo turto valdymo sričių, užtikrinanti statinių techninį patikimumą, naudotojų saugumą ir ilgalaikės turto vertės išsaugojimą. Didėjant verslo klientų reikalavimams bei sparčiai vystantis technologijoms, pastatų priežiūros procesų efektyvumas tampa svarbiu konkurencingumo ir veiklos tęstinumo veiksniu. Straipsnio tikslas – išanalizuoti pastatų priežiūros proceso sprendinius valdant verslo klientų nekilnojamąjį turtą bei nustatyti pagrindines proceso tobulinimo kryptis. Tyrime taikyta mokslinės literatūros analizė, ekspertų apklausa, priežasčių bei pasekmių analizė ir SSGG analizė. Tyrime dalyvavo penki nekilnojamojo turto valdymo ir pastatų priežiūros specialistai, turintys ilgametę profesinę patirtį. Tyrimo rezultatai parodė, kad didžiausią įtaką priežiūros procesų efektyvumui daro standartizuotų procedūrų naudojimas, darbuotojų kompetencija, prevencinės priežiūros taikymas ir skaitmeninių technologijų integracija. Nustatyta, kad kompiuterizuotos priežiūros valdymo sistemos, statinio informacinis modeliavimas ir daiktų interneto technologijos sudaro prielaidas efektyvesniam sprendimų priėmimui bei eksploatacinių rizikų mažinimui. Remiantis tyrimo rezultatais pateikiamos rekomendacijos pastatų priežiūros procesams tobulinti verslo klientų nekilnojamojo turto valdymo srityje.
Reikšminiai žodžiai: pastatų priežiūra, nekilnojamojo turto valdymas, verslo klientai, BIM, CMMS, IoT, rizikų valdymas, procesų tobulinimas.
Keywords:
building maintenance, real estate management, commercial real estate, Building Information Modelling (BIM), Computerized Maintenance Management Systems (CMMS), Internet of Things (IoT), process improvement, preventive maintenanceHow to Cite
Share
License
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Adamonytė, E. (2021). Analysis of the causes of building defects and administrative problems. Mokslas – Lietuvos ateitis / Science – Future of Lithuania, 13. https://doi.org/10.3846/mla.2021.13718
Al-Refaie, A., Al-Hawadi, A., & Lepkova, N. (2022). Blockchain design with optimal maintenance planning. Buildings, 12(11), Article 1902. https://doi.org/10.3390/buildings12111902
Al-Refaie, A., Abu Hamdieh, B., & Lepkova, N. (2023). Prediction of maintenance activities using generalized sequential pattern and association rules in data mining. Buildings, 13(4), Article 946. https://doi.org/10.3390/buildings13040946
Bongini, A., Sparacino, M., Marzi, L., & Biagini, C. (2025). Enhancing facility management with emerging technologies: A study on the application of blockchain and NFTs. Buildings, 15(11), Article 1911. https://doi.org/10.3390/buildings15111911
Halmetoja, E., & Lepkova, N. (2022). Utilising building information models in facility maintenance and operations. Teknik Dergi, 33(5), 12351–12377. https://doi.org/10.18400/tekderg.748397
Ishikawa, K. (1986). Guide to quality control. Asian Productivity Organization.
Ma, S., Flanigan, K. A., & Bergés, M. (2024). State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies. arXiv. https://doi.org/10.1016/j.aei.2024.102800
Malienė, V., Alexander, K., & Lepkova, N. (2008). Facilities management development in Europe. International Journal of Environment and Pollution, 35(2–4), 171–184. https://doi.org/10.1504/IJEP.2008.021354
Mannino, A., Dejaco, M. C., & Re Cecconi, F. (2021). Building information modelling and internet of things integration for facility management: Literature review and future needs. Applied Sciences, 11(7), Article 3062. https://doi.org/10.3390/app11073062
Okoro, C. S. (2023). Sustainable facilities management in the built environment: A mixed-method review. Sustainability, 15(4), Article 3174. https://doi.org/10.3390/su15043174
Viduto, K. (2021). Smart technologies in the field of facility management. Mokslas – Lietuvos ateitis / Science – Future of Lithuania, 13. https://doi.org/10.3846/mla.2021.14052
View article in other formats
CrossMark check
Published
Issue
Section
Copyright
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.