INNOVATIVE MANAGEMENT MODELS IN THE WINDOW BUSINESS: OPTIMIZATION OF PRODUCTION, LOGISTICS, AND INSTALLATION UNDER MARKET GROWTH
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Abstract
The rapid growth of the construction industry and high demand for bespoke building solutions have made structural inefficiencies and failures in the context of window manufacturing companies more apparent, particularly the coordination between the production, logistics, and installation processes. To mitigate these challenges, this study devised the Integrated Window Operations Framework (IWOF), a process-oriented management model aimed at improving operational alignment and scalability. This study reinterprets existing research on digital supply chains, logistics optimization, and Industry 4.0 technologies through a lens of system-level integration based on a qualitative analytical methodology through a structured literature synthesis. Analysis indicates the window business is structurally inefficient due to stage fragmentation rather than technological limitations. Logistics is the primary coordinating mechanism, and real-time data visibility is demonstrated to be a required condition for successful integration. This analysis shows that digital technologies can improve performance only when integrated into a unified operating framework, and that scale lies in modular integration rather than enhanced volume generation. IWOF is a theoretical development for practice, broadening the concepts of supply chain integration to encompass process synchronization in construction-linked manufacturing systems. This research helps organizations move towards a faster, more resilient, and sustainable growth model in changing markets.
How to Cite
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window manufacturing, supply chain integration, Industry 4.0, logistics optimization, process synchronization, operational scalability
Alvarenga, M. Z., Oliveira, M. P. V. D., & Oliveira, T. A. G. F. D. (2023). The impact of using digital technologies on supply chain resilience and robustness: the role of memory under the covid-19 outbreak. Supply Chain Management: An International Journal, 28(5), 825–842. https://doi.org/10.54254/2754-1169/140/2024.GA18772
Anaba, D. C., Kess-Momoh, A. J., & Ayodeji, S. A. (2024). Optimizing supply chain and logistics management: A review of modern practices. Open Access Research Journal of Science and Technology, 11(2), 020–028. https://doi.org/10.53022/oarjst.2024.11.2.0083
Buhaievskyi, M., & Petrenko, Y. (2025). Planning and optimization models in ready-made concrete production and logistics. Radioelectronic and Computer Systems, 2025(2), 264–279. https://doi.org/10.32620/reks.2025.2.17
Cordon, Carlos (2023) : The surprising developments of digital supply chains to raise resilience in the face of disruptions, ADBI Working Paper, No. 1383, Asian Development Bank Institute (ADBI), Tokyo. https://doi.org/10.56506/KPJD9061
Ding, M. J., & Jie, F. (2025). Mitigating the supply chain uncertainties and risks in the construction projects: Case studies of Australian construction projects. Cleaner Logistics and Supply Chain, 16, 100237. https://doi.org/10.1016/j.clscn.2025.100237
Egwunatum, S., Anosike, N. M., & Ihekweme, M. N. (2026). Weighing on the Capabilities of Big Data Analytics for Sustainable Supply Chain Management in Construction Projects. Journal of Sustainability, 2(1). https://doi.org/10.55845/jos-2026-2183
Gu, X. (2024). The Role of Digital Techniques in Supply Chain Resilience: Exploration in the Logistics Sector. J. Bus. Res, 134, 103–115.
Ivanov, D., Dolgui, A., Das, A., & Sokolov, B. (2019). Digital supply chain twins: Managing the ripple effect, resilience, and disruption risks by data-driven optimization, simulation, and visibility. In Handbook of ripple effects in the supply chain (pp. 309–332). Cham: Springer International Publishing.
Khattab, S. A., Al Shaar, I. M., Alatyat, Z. A., & Abu Zaid, M. K. (2025). Big data analytics capability and green supply chain: Does supply chain visibility and agility matter? Journal of Information Systems Engineering and Management, 10(36s), e24684376.
Li, P., Chen, Y., & Guo, X. (2025). Digital transformation and supply chain resilience. International Review of Economics & Finance, 99, 104033. https://doi.org/10.1016/j.iref.2025.104033
Lu, J., Chuah, S. C., Xia, D. M., & Gary, J. (2025). The development of the modern logistics industry and its role in promoting regional economic growth in China’s underdeveloped northwest, driven by the digital economy. Economies, 13(9), 261. https://doi.org/10.3390/economies13090261
Mageto, J. (2021). Big data analytics in sustainable supply chain management: A focus on manufacturing supply chains. Sustainability, 13(13), 7101. https://doi.org/10.3390/su13137101
Masłowski, D., Deptuła, A., Ulbrich, W., Kocur, Ł., & Łapka, M. (2025). Identification and minimization of risks in the logistics processes of a window blinds manufacturing company using PHA and TPM.
Mohsen, B. M. (2023). Impact of artificial intelligence on supply chain management performance. Journal of Service Science and Management, 16(1), 44–58. https://doi.org/10.4236/jssm.2023.161004
Nesarnobari, S., Shahzad, W. M., Babaeian Jelodar, M., & Sutrisna, M. (2025). Offsite construction supply chain management: a scientometric analysis and systematic literature review. Architectural Engineering and Design Management, 21(3), 467–490. https://doi.org/10.1080/17452007.2024.2381497
Polusmiak, Yu., Pavliuk, T. & Kosach, I. (2024). Project management in the construction industry: identification of logistical problems and ways to optimise them. Management and Entrepreneurship: Trends of Development, 4(30), 69–78. https://doi.org/10.26661/2522-1566/2024-4/30-06
Rad, F. F., Oghazi, P., Palmié, M., Chirumalla, K., Pashkevich, N., Patel, P. C., & Sattari, S. (2022). Industry 4.0 and supply chain performance: A systematic literature review of the benefits, challenges, and critical success factors of 11 core technologies. Industrial Marketing Management, 105, 268–293. https://doi.org/10.1016/j.indmarman.2022.06.009
Rahman, M. A., Saha, P., Belal, H. M., Ratul, S. H., & Graham, G. (2024). Big data analytics capability and supply chain sustainability: Analyzing the moderating role of green supply chain management practices. Benchmarking: An International Journal. Advance online publication. https://doi.org/10.1108/BIJ-10-2024-0852
Spieske, A., & Birkel, H. (2021). Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic. Computers & industrial engineering, 158, 107452. https://doi.org/10.1016/j.cie.2021.107452
Tortorella, G. L., Giglio, R., & van Dun, D. H. (2019). Industry 4.0 adoption as a moderator of the impact of lean production practices on operational performance improvement. International Journal of Operations & Production Management, 39(6/7/8), 860–886. https://doi.org/10.1108/IJOPM-01-2019-0005
Zhang, C., Jiang, J., Xia, C., Fu, Y., Liu, J., & Duan, P. (2024). Dual-objective optimization of prefabricated component logistics based on JIT strategy. Scientific Reports, 14(1), 31267. https://doi.org/10.1038/s41598-024-82689-w
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