Treffer: Sustainability in construction economics as a barrier to cloud computing adoption in small-scale Building projects.
Calautit, K. & Johnstone, C. State-of-the-art review of micro to small-scale wind energy harvesting technologies for building integration. Energy Conversion and Management: X, : p. 100457. (2023).
Hwang, J. M. et al. Identifying critical factors and trends leading to fatal accidents in small-scale construction sites in Korea. Buildings 13 (10), 2472 (2023). (PMID: 10.3390/buildings13102472)
Shang, G., Low, S. P. & Lim, X. Y. V. Prospects, drivers of and barriers to artificial intelligence adoption in project management. Built Environ. Project Asset Manage. 13 (5), 629–645 (2023). (PMID: 10.1108/BEPAM-12-2022-0195)
Bachar, R. et al. Optimal allocation of safety resources in small and medium construction enterprises. Saf. Sci. 181, 106680 (2025). (PMID: 10.1016/j.ssci.2024.106680)
Alshahrani, R. et al. Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial intelligence-enabled sustainable cloud system in an IT industry. Expert Syst. Appl. 238, 121732 (2024). (PMID: 10.1016/j.eswa.2023.121732)
Aziz, S., Kumar, P. & Khan, A. Assessing the impact of digital supply chain management on the sustainability of construction projects. Rev. Bus. Econ. Stud. 12 (3), 60–73 (2024). (PMID: 10.26794/2308-944X-2024-12-3-60-73)
Bamgbose, O. A., Ogunbayo, B. F. & Aigbavboa, C. O. Barriers to Building information modelling adoption in small and medium enterprises: Nigerian construction industry perspectives. Buildings 14 (2), 538 (2024). (PMID: 10.3390/buildings14020538)
Jayawardana, J. et al. Key Barriers and Mitigation Strategies Towards Sustainable Prefabricated construction–a Case of Developing Economies (Engineering, Construction and Architectural Management, 2024).
Kineber, A. F. et al. Modeling the impact of overcoming the green walls implementation barriers on sustainable Building projects: A novel mathematical partial least squares—SEM method. Mathematics 11 (3), 504 (2023). (PMID: 10.3390/math11030504)
Martin, H. et al. Validating the relative importance of technology diffusion barriers–exploring modular construction design-build practices in the UK. Int. J. Constr. Educ. Res., : pp. 1–21. (2024).
Cheng, Q. et al. Leveraging BIM for sustainable construction: benefits, barriers, and best practices. Sustainability 16 (17), 7654 (2024). (PMID: 10.3390/su16177654)
Byers, B. & De Wolf, C. QR code-based material passports for component reuse across life cycle stages in small-scale construction. Circular Econ., : pp. 1–16. (2023).
Al Naimat, A. & Liang, D. Substantial gains of renewable energy adoption and implementation in Maan, Jordan: A critical review. Results Eng., : p. 101367. (2023).
Datta, S. D. et al. Benefits and barriers of implementing Building information modeling techniques for sustainable practices in the construction industry—A comprehensive review. Sustainability 15 (16), 12466 (2023). (PMID: 10.3390/su151612466)
Nguyen, T. D. & Adhikari, S. The role of Bim in integrating digital twin in Building construction: A literature review. Sustainability 15 (13), 10462 (2023). (PMID: 10.3390/su151310462)
Ghansah, F. A. & Edwards, D. J. Digital technologies for quality assurance in the construction industry: current trend and future research directions towards industry 4.0. Buildings 14 (3), 844 (2024). (PMID: 10.3390/buildings14030844)
Omole, F. O., Olajiga, O. K. & Olatunde, T. M. Challenges and successes in rural electrification: a review of global policies and case studies. Eng. Sci. Technol. J. 5 (3), 1031–1046 (2024). (PMID: 10.51594/estj.v5i3.956)
Tran, H. V. V. & Nguyen, T. A. A review of challenges and opportunities in BIM adoption for construction project management. Eng. J. 28 (8), 79–98 (2024). (PMID: 10.4186/ej.2024.28.8.79)
Olanrewaju, O. I. et al. Modelling the relationship between Building information modelling (BIM) implementation barriers, usage and awareness on Building project lifecycle. Build. Environ. 207, 108556 (2022). (PMID: 10.1016/j.buildenv.2021.108556)
Bello, S. A. et al. Cloud computing in construction industry: use cases, benefits and challenges. Autom. Constr. 122, 103441 (2021). (PMID: 10.1016/j.autcon.2020.103441)
Ngcobo, K. et al. Enterprise Data Management: Types, Sources, and real-time Applications To Enhance Business performance-a Systematic Review (Systematic Review| September, 2024).
Atkinson, E. et al. Challenges in the adoption of mobile information communication technology (M-ICT) in the construction phase of infrastructure projects in the UK. Int. J. Building Pathol. Adaptation. 40 (3), 327–344 (2022). (PMID: 10.1108/IJBPA-04-2021-0048)
Lam, P. T. et al. Data centers as the backbone of smart cities: principal considerations for the study of facility costs and benefits. Facilities 39 (1/2), 80–95 (2021). (PMID: 10.1108/F-09-2019-0103)
Koralun-Bereźnicka, J. & Gostkowska-Drzewicka, M. Trade credit policies in the construction industry: A comparative study of Central-Eastern and Western EU countries. Int. J. Manage. Econ., 2024(online first).
Junejo, A. K. et al. Adaptive speed control of PMSM drive system based a new sliding-mode reaching law. IEEE Trans. Power Electron. 35 (11), 12110–12121 (2020). (PMID: 10.1109/TPEL.2020.2986893)
Zhang, S. et al. Practical adoption of cloud computing in power systems—Drivers, challenges, guidance, and real-world use cases. IEEE Trans. Smart Grid. 13 (3), 2390–2411 (2022). (PMID: 10.1109/TSG.2022.3148978)
Javaid, M. et al. Evolutionary trends in progressive cloud computing based healthcare: ideas, enablers, and barriers. Int. J. Cogn. Comput. Eng. 3, 124–135 (2022).
Adeusi, O. C. et al. IT standardization in cloud computing: security challenges, benefits, and future directions. World J. Adv. Res. Reviews. 22 (05), 2050–2057 (2024). (PMID: 10.30574/wjarr.2024.22.3.1982)
Toufaily, E., Zalan, T. & Dhaou, S. B. A framework of blockchain technology adoption: an investigation of challenges and expected value. Inf. Manag. 58 (3), 103444 (2021). (PMID: 10.1016/j.im.2021.103444)
Selesi-Aina, O. et al. The future of work: A Human-centric approach to AI, robotics, and cloud computing. J. Eng. Res. Rep. 26 (11), 62–87 (2024). (PMID: 10.9734/jerr/2024/v26i111315)
Shehu, Z., Endut, I. R. & Akintoye, A. Factors contributing to project time and hence cost overrun in the Malaysian construction industry. J. Financial Manage. Property Constr. 19 (1), 55–75 (2014). (PMID: 10.1108/JFMPC-04-2013-0009)
Shelden, D. R. et al. Data standards and data exchange for Construction 4.0, in Construction 4.0. Routledge. pp. 222–239. (2020).
Shin, Y. et al. A formwork method selection model based on boosted decision trees in tall Building construction. Autom. Constr. 23, 47–54 (2012). (PMID: 10.1016/j.autcon.2011.12.007)
Shvets, Y. & Hanák, T. Use of the internet of things in the construction industry and facility management: usage examples overview. Procedia Comput. Sci. 219, 1670–1677 (2023). (PMID: 10.1016/j.procs.2023.01.460)
Aati, K. et al. Analysis of road traffic accidents in dense cities: geotech transport and ArcGIS. Transp. Eng., : p. 100256. (2024).
Abuhussain, M. A. et al. Integrating Building Information Modeling (BIM) for optimal lifecycle management of complex structures. in Structures. Elsevier. (2024).
Alotaibi, B. S. et al. Building information modeling (BIM) adoption for enhanced legal and contractual management in construction projects. Ain Shams Eng. J. 15 (7), 102822 (2024). (PMID: 10.1016/j.asej.2024.102822)
Althoey, F. et al. Influence of IoT Implementation on Resource Management in Construction. Heliyon, (2024).
Elmousalami, H. H. Artificial intelligence and parametric construction cost estimate modeling: State-of-the-art review. J. Constr. Eng. Manag. 146 (1), 03119008 (2020). (PMID: 10.1061/(ASCE)CO.1943-7862.0001678)
Khan, A. M., Alaloul, W. S. & Musarat, M. A. The Carbon Footprint of Net Zero Buildings: A Critical Review. in 4th International Conference on Data Analytics for Business and Industry (ICDABI). 2023. IEEE. (2023).
Khan, A. M., Alaloul, W. S. & Musarat, M. A. A Critical Review of Digital Value Engineering in Building Design Towards Automated Constructionp. 1–46 (Environment, 2024).
Khan, A. M. et al. Python: An Automation Tool for Unlocking Innovation and Efficiency in the AEC Sector. in. 4th International Conference on Data Analytics for Business and Industry (ICDABI). 2023. IEEE. (2023).
Khan, A. M. et al. Internet of things (IoT) for safety and efficiency in construction Building site operations. Sci. Rep. 14 (1), 28914 (2024). (PMID: 395725811158282310.1038/s41598-024-78931-0)
Khan, A. M. et al. Optimizing energy efficiency through Building orientation and Building information modelling (BIM) in diverse terrains: A case study in Pakistan. Energy 133307, p (2024).
Khan, A. M. et al. BIM integration with XAI using LIME and MOO for automated green Building energy performance analysis. Energies 17 (13), 3295 (2024). (PMID: 10.3390/en17133295)
Maglad, A. M. et al. Bim-based energy analysis and optimization using insight 360 (case study). Case Stud. Constr. Mater. 18, pe01755 (2023).
Musarat, M. A. et al. A survey-based approach of framework development for improving the application of internet of things in the construction industry of Malaysia. Results Eng., : p. 101823. (2024).
Musarat, M. A. et al. Substitution of workforce with robotics in the construction industry: A wise or witless approach. J. Open. Innovation: Technol. Market Complex., : p. 100420. (2024).
Musarat, M. A. et al. Automated monitoring innovations for efficient and safe construction practices. Results Eng. 22, 102057 (2024). (PMID: 10.1016/j.rineng.2024.102057)
Noghabaei, M. et al. Trend analysis on adoption of virtual and augmented reality in the architecture, engineering, and construction industry. Data 5 (1), 26 (2020). (PMID: 10.3390/data5010026)
Pan, X. et al. BIM adoption in sustainability, energy modelling and implementing using ISO 19650: A review. Ain Shams Eng. J. 15 (1), 102252 (2024). (PMID: 10.1016/j.asej.2023.102252)
Sajjad, M. et al. BIM-driven energy simulation and optimization for net-zero tall buildings: sustainable construction management. Front. Built Environ. 10, 1296817 (2024). (PMID: 10.3389/fbuil.2024.1296817)
Sajjad, M. et al. BIM implementation in project management practices for sustainable development: partial least square approach. Ain Shams Eng. J., : p. 103048. (2024).
Waqar, A. et al. Challenges of blockchain implementation in construction. J. Eng. 2024 (1), 2442345 (2024). (PMID: 10.1155/2024/2442345)
Waqar, A. et al. Analyzing the impact of holistic Building design on the process of lifecycle management of Building structures. Sci. Rep. 14 (1), 29020 (2024). (PMID: 395786091158472410.1038/s41598-024-80547-3)
Waqar, A. et al. Limitations to the BIM-based safety management practices in residential construction project. Environ. Challenges. 14, 100848 (2024). (PMID: 10.1016/j.envc.2024.100848)
Waqar, A. et al. Sustainable leadership practices in construction: Building a resilient society. Environ. Challenges. 14, 100841 (2024). (PMID: 10.1016/j.envc.2024.100841)
Waqar, A., Khan, A. M. & Othman, I. Blockchain empowerment in construction supply chains: enhancing efficiency and sustainability for an infrastructure development. J. Infrastructure Intell. Resil. 3 (1), 100065 (2024).
Waqar, A. et al. BIM in green building: enhancing sustainability in the small construction project. Clean. Environ. Syst., : p. 100149. (2023).
Waqar, A. et al. Complexities for adopting 3D laser scanners in the AEC industry: structural equation modeling. Appl. Eng. Sci. 16, 100160 (2023).
Waqar, A. et al. Integration of passive RFID for small-scale construction project management. Data Inform. Manage. 7 (4), 100055 (2023). (PMID: 10.1016/j.dim.2023.100055)
Zhang, J. et al. BIM-based architectural analysis and optimization for construction 4.0 concept (a comparison). Ain Shams Eng. J. 14 (6), 102110 (2023). (PMID: 10.1016/j.asej.2022.102110)
Ibeh, C. V. et al. A review of agile methodologies in product lifecycle management: bridging theory and practice for enhanced digital technology integration. Eng. Sci. Technol. J. 5 (2), 448–459 (2024). (PMID: 10.51594/estj.v5i2.805)
Hodson, E. et al. Evaluating social impact of smart City technologies and services: methods, challenges, future directions. Multimodal Technol. Interact. 7 (3), 33 (2023). (PMID: 10.3390/mti7030033)
Nilashi, M. et al. Critical data challenges in measuring the performance of sustainable development goals: solutions and the role of big-data analytics. Harv. Data Sci. Rev. 5 (3), 1–36 (2023).
Aldoseri, A., Al-Khalifa, K. N. & Hamouda, A. M. Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges. Appl. Sci. 13 (12), 7082 (2023). (PMID: 10.3390/app13127082)
Zhu, S. et al. Intelligent computing: the latest advances, challenges, and future. Intell. Comput. 2, 0006 (2023). (PMID: 10.34133/icomputing.0006)
Akanfe, O., Lawong, D. & Rao, H. R. Blockchain technology and privacy regulation: reviewing frictions and synthesizing opportunities. Int. J. Inf. Manag. 76, 102753 (2024).
Niaz, M. & Nwagwu, U. Managing healthcare product demand effectively in the Post-Covid-19 environment: navigating demand variability and forecasting complexities. Am. J. Economic Manage. Bus. (AJEMB). 2 (8), 316–330 (2023). (PMID: 10.58631/ajemb.v2i8.55)
Aithal, P. Super-Intelligent Machines-analysis of developmental challenges and predicted negative consequences. Int. J. Appl. Eng. Manage. Lett. (IJAEML). 7 (3), 109–141 (2023). (PMID: 10.47992/IJAEML.2581.7000.0191)
Sompolgrunk, A. et al. An integrated model of BIM return on investment for Australian small-and medium-sized enterprises (SMEs). Eng. Constr. Architectural Manage. 30 (5), 2048–2074 (2023). (PMID: 10.1108/ECAM-09-2021-0839)
Albahri, A. S. et al. A systematic review of trustworthy and explainable artificial intelligence in healthcare: assessment of quality, bias risk, and data fusion. Inform. Fusion. 96, 156–191 (2023). (PMID: 10.1016/j.inffus.2023.03.008)
Bammidi, T. R. et al. The crucial role of data quality in automated Decision-Making systems. Int. J. Manage. Educ. Sustainable Dev. 7 (7), 1–22 (2024).
Tomar, M. & Periyasamy, V. The role of reference data in financial data analysis: challenges and opportunities. J. Knowl. Learn. Sci. Technol. ISSN. 1(1) (online), 2959–6386 (2023).
Liu, Z. et al. Advanced controls on energy reliability, flexibility, resilience, and occupant-centric control for smart and energy-efficient buildings—a state-of-the-art review. Energy Build., : p. 113436. (2023).
Šestak, M. & Copot, D. Towards trusted data sharing and exchange in agro-food supply chains: design principles for agricultural data spaces. Sustainability 15 (18), 13746 (2023). (PMID: 10.3390/su151813746)
Muhammad, D. & Bendechache, M. Unveiling the Black Box: A Systematic Review of Explainable Artificial Intelligence in Medical Image Analysis (Computational and structural biotechnology journal, 2024).
Bouchetara, M., Zerouti, M. & Zouambi, A. R. Leveraging artificial intelligence (AI) in public sector financial risk management: innovations, challenges, and future directions. EDPACS 69 (9), 124–144 (2024). (PMID: 10.1080/07366981.2024.2377351)
Polancos, R. V. & Seva, R. R. A risk minimization model for a multi-skilled, multi-mode resource-constrained project scheduling problem with discrete time-cost-quality-risk trade-off Engineering Management Journal, 2024. 36(3): pp. 272–288.
Rane, N. & Cost Integrating Building Information Modelling (BIM) and Artificial Intelligence (AI) for Smart Construction Schedule, Cost, Quality, and Safety Management: Challenges and Opportunities. Quality, and Safety Management: Challenges and OpportunitiesSeptember 16, 2023. (2023).
Bello, S. A. et al. Effect of age, impaction types and operative time on inflammatory tissue reactions following lower third molar surgery. Head Face Med. 7, 1–8 (2011). (PMID: 10.1186/1746-160X-7-8)
Hong, J. et al. Virtual reality-based analysis of the effect of construction noise exposure on masonry work productivity. Autom. Constr. 150, 104844 (2023). (PMID: 10.1016/j.autcon.2023.104844)
Weitere Informationen
The application of intelligent technology to enhance decision-making, optimize processes, and boost project economics and sustainability has the potential to significantly revolutionize the construction industry. However, there are several barriers to its use in small-scale construction projects in China. This study aims to identify these challenges and provide solutions. Using a mixed-methods approach that incorporates quantitative analysis, structural equation modeling, and a comprehensive literature review, the study highlights key problems. These include specialized challenges, difficulty with data integration, financial and cultural constraints, privacy and ethical issues, limited data accessibility, and problems with scalability and connection. The findings demonstrate how important it is to get rid of these barriers to fully utilize intelligent computing in the construction sector. There are recommendations and practical strategies provided to help industry participants get over these challenges. Although the study's geographical emphasis and cross-sectional approach are limitations, they also offer opportunities for further investigation. This study contributes significantly to the growing body of knowledge on intelligent computing in small-scale construction projects and offers practical guidance on how businesses might leverage their transformative potential.
(© 2025. The Author(s).)
Declarations. Competing interests: The authors declare no competing interests. Ethics approval: “This study involved participants for data collection using LIDAR technology in construction management. All methods were performed in accordance with relevant guidelines and regulations. The experimental protocols were reviewed and approved by the Ethics Committee of the Third Professional Design and Research Institute, China Architecture Design & Research Group, Beijing, 101100, China. Written informed consent was obtained from all participants prior to their inclusion in the study, ensuring their voluntary participation and understanding of the research objectives.”