مهندسی سیستم و بهره‌وری

مهندسی سیستم و بهره‌وری

تحلیل موانع دستیابی به صنعت ساخت چهارم با رویکرد مدل‌سازی ساختاری-تفسیری

مقالات آماده انتشار

نوع مقاله : پژوهشی

نویسندگان
کسری رهبری پور 1
محمدرضا پاکدل فرد 2
حسن ستاری ساربانقلی 3
نیما ولی زاده 4
1 دانشجوی دکتری، گروه معماری، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
2 نویسنده مسئول: دانشیار، گروه معماری، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
3 دانشیار، گروه معماری و شهرسازی، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
4 استادیار، گروه معماری، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
10.22034/sep.2025.2068090.1374
چکیده
هدف این تحقیق تحلیل و سطح‌بندی موانع صنعت ساخت چهارم از موضع نوآورانه در توسعه مسکن ایران با رویکرد مدل‌سازی ساختاری-تفسیری است. در این روند برای تعیین میزان اثرگذاری و اثرپذیری موانع از نظرات 10 کارشناس که به روش نمونه‌گیری هدفمند از نوع گلوله برفی انتخاب‌شده بودند، استفاده شد. گردآوری اطلاعات با کمک پرسشنامه مقایسه زوجی و بیشترین توافق خبرگان در مورد هرکدام از مقایسه‌ها به‌عنوان معیار تصمیم‌گیری واقع شد. موانع دستیابی به صنعت چهارم در ساخت مسکن در 7 سطح دسته‌بندی شدند که سطوح پایین‌تر، بیانگر موانع مبنایی و سطوح بالاتر، موانع تأثیرگذار را نشان می‌دهند. شرایط بازار و منابع انرژی به‌عنوان موانع تأثیرگذار و موانع سنت و تجربیات گذشته به‌عنوان موانع مبنایی شناسایی شدند. بر اساس تحلیل قدرت وابستگی و محرک، موانع «تغییر و پذیرش» و «آگاهی و آموزش» تأثیر و وابستگی زیادی دارند، درحالی‌که موانع «نوآوری و بهره‌برداری» و «انرژی» تأثیر کمتری از خود نشان می‌دهند.

تازه های تحقیق

  • موانع دستیابی به صنعت ساخت چهارم در 7 سطح طبقه‌بندی شد.
  • «شرایط بازار و منابع انرژی» مهم‌ترین موانع تأثیرگذار و «سنت و تجربیات گذشته» اساسی‌ترین موانع مبنایی هستند.
  • موانع «تغییر و پذیرش» و «آگاهی و آموزش»، به دلیل وابستگی بالا و تأثیر گسترده‌شان بر سیستم، حیاتی تلقی می‌شود.

کلیدواژه‌ها
صنعت چهارم
صنعت ساخت چهارم
انقلاب صنعتی چهارم
مدل‌سازی ساختاری-تفسیری
ساخت مسکن
توسعه مسکن
موضوعات

عنوان مقاله English

Analysis of Barriers to Achieving Construction 4.0 Using the Interpretive Structural Modeling Approach

نویسندگان English

Kasra Rahbaripour 1
Mohammadreza Pakdelfard 2
Hassan Sattari Sarbangholi 3
Nima Valizadeh, 4
1 Ph.D. Student, Department of Architecture, Ta.C, Islamic Azad University, Tabriz, Iran
2 Corresponding author: Associate Professor, Department of Architecture, Ta.C, Islamic Azad University, Tabriz, Iran
3 Associate Professor, Department of Architecture and Urban Planning, Ta.C, Islamic Azad University, Tabriz, Iran
4 Assistant Professor, Department of Architecture, Ta.C, Islamic Azad University, Tabriz, Iran
چکیده English

This study aims to identify and hierarchize barriers to adopting Construction 4.0 in Iran's housing development sector from an innovation perspective, employing an Interpretive Structural Modeling (ISM) approach. To evaluate the influence and dependency of these barriers, insights from 10 experts, selected via purposive snowball sampling, were collected. Data were gathered through a pairwise comparison questionnaire, with the highest level of expert consensus determining the decision-making criterion. The barriers to implementing Construction 4.0 in housing development were classified into seven hierarchical levels, where lower levels represent foundational barriers and higher levels denote influential barriers. Market conditions and energy resources emerged as highly influential barriers, while tradition and past experiences were identified as foundational barriers. Analysis of dependency strength and driving power revealed that "change and acceptance" and "awareness and education" exhibited significant influence and dependency, whereas "innovation and utilization" and "energy" demonstrated comparatively lower impact.

کلیدواژه‌ها English

Industry 4.0
Construction 4.0
Fourth Industrial Revolution
Structural-Interpretive Modeling
Housing Construction
Housing Development

Copyright © Kasra Rahbaripour, Mohammadreza Pakdelfard, Hassan Sattari Sarbangholi, Nima Valizadeh

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

Abdul-Samad, Z., Xin, L. L., Alaloul, W. S., & Salleh, H. (2024). Towards Industrial Revolution (IR) 4.0 in the construction industry: Readiness of contractors. Results in Engineering, 22, 102321. https://doi.org/10.1016/j.rineng.2024.102321
Aigbavboa, C., & Kissi, E. (2025). Digital construction project cost management—an Industry 4.0 framework. Digital transformation in construction: Principles and applications, 147-158.
Alaboud, N., & Alshahrani, A. (2023). Adoption of building information modelling in the Saudi construction industry: An interpretive structural modelling. Sustainability, 15(7), 6130. https://doi.org/10.3390/su15076130
Alaloul, W. S., Liew, M. S., Zawawi, N. A. W. A., & Mohammed, B. S. (2018). Industry revolution IR 4.0: future opportunities and challenges in construction industry. In MATEC web of conferences (Vol. 203, p. 02010). EDP Sciences. https://doi.org/10.1051/matecconf/201820302010
Ali, S., Huang, J., Khan, S. U., & Li, H. (2020). A framework for modelling structural association amongst barriers to software outsourcing partnership formation: An interpretive structural modelling approach. Journal of Software: Evolution and Process, 32(6), e2243. https://doi.org/10.1002/smr.2243
Ansari, F. A., Haque, S. N., Khan, S., & Khan, W. (2024). Modeling the enablers of implementing green HRM practices: An ISM-MICMAC approach. Corporate Social Responsibility and Environmental Management, 31(6), 6260–6274. https://doi.org/10.1002/csr.2913
Asif, M., Sarim, M., Khan, W., & Khan, S. (2023). ISM- and MICMAC-based modelling of dairy supply chain: A study of enablers in Indian economy perspective. British Food Journal, 126(2), 578–594. https://doi.org/10.1108/BFJ-04-2023-0307
Baduge, S. K., Thilakarathna, S., Perera, J. S., Arashpour, M., Sharafi, P., Teodosio, B., Shringi, A., & Mendis, P. (2022). Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications. Automation in Construction, 141, 104440. https://doi.org/10.1016/j.autcon.2022.104440
Bahrami, M. R., Hashemzadeh, G. R., Shahmansoury, A., & Fathi Hafshejani, K. (2025). Analyzing effective components in industry 4.0 maturity for Iranian banking. System Engineering and Productivity, 5(1), 21-50. https://doi.org/10.22034/sep.2025.2047848.1246
Beck, C. (1993). Qualitative research: The evaluation of its credibility, fittingness, and auditability. Western Journal of Nursing Research, 15(2), 263–266. https://doi.org/10.1177/019394599301500212
Begić, H., & Galić, M. (2021). A Systematic Review of Construction 4.0 in the Context of the BIM 4.0 Premise. Buildings, 11(8), 337. https://doi.org/10.3390/buildings11080337
Biernacki, P., & Waldorf, D. (1981). Snowball sampling: Problems and techniques of chain referral sampling. Sociological Methods & Research, 10(2), 141–163. https://doi.org/10.1177/004912418101000205
Boton, C., Rivest, L., Ghnaya, O., & Chouchen, M. (2021). What is at the root of Construction 4.0: A systematic review of the recent research effort. Archives of Computational Methods in Engineering, 28(3), 2331–2350. https://doi.org/10.1007/s11831-020-09457-7
Charmaz, K. (2014). Constructing grounded theory.
Corbin, J. M., & Strauss, A. L. (2008). Basics of qualitative research. Basics of qualitative research.
Craveiro, F., Duarte, J. P., Bartolo, H., & Bartolo, P. J. (2019). Additive manufacturing as an enabling technology for digital construction: A perspective on Construction 4.0. Automation in Construction, 103, 251–267. https://doi.org/10.1016/j.autcon.2019.03.011
De Marco, C., Colabianchi, S., & Costantino, F. (2025). ISM2: Interpretive structural modelling methodology in the context of in-space manufacturing for a strategic space project guideline. Acta Astronautica. https://doi.org/10.1016/j.actaastro.2025.07.029
Di Nardo, M., Gallab, M., Murino, T., Wu, J., & Pandey, S. (2025). Integrating sustainability and industry 4.0: A framework for sustainable logistics 4.0. Circular Economy and Sustainability, 1-39. https://doi.org/10.1007/s43615-024-00492-1
Dworkin, S. L. (2012). Sample size policy for qualitative studies using in-depth interviews. Archives of Sexual Behavior, 41(6), 1319–1320. https://doi.org/10.1007/s10508-012-0016-6
Dos Santos Silva, J., Matos de Oliveira, A., Veríssimo de Oliveira, J., & Bouzon, M. (2025). Barriers to digital transformation in fruit and vegetable supply chains: a multicriteria analysis using ISM and MICMAC. OPSEARCH, 62(1), 460-482. https://doi.org/10.1007/s12597-024-00809-6
Eghbal, F., Ehsanifar, M., Mirhosseini, M., & Mazaheri, H. (2025). Identification and modeling of key factors significant to the financial performance of Iranian construction companies. System Engineering and Productivity, 4(4), 77-94. https://doi.org/10.22034/msb.2024.2034092.1218
El Jazzar, M., Schranz, C., Urban, H., & Nassereddine, H. (2021). Integrating construction 4.0 technologies: A four-layer implementation plan. Frontiers in Built Environment, 7, 671408. https://doi.org/10.3389/fbuil.2021.671408
Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115. https://doi.org/10.1111/j.1365-2648.2007.04569.x
Ershadi, M. J., Kianmehr, N., Nabatchian, M., Dinmohammadi, L. (2024). Designing a Productivity assessment model to identify and prioritize influential factors and examine obstacles facing Iranian research organizations.  System Engineering and Productivity. 4(2), 31-46. https://doi.org/10.22034/msb.2024.2019692.1171
Farinha, I. M., Ferreira, F. A., Ferreira, N. C., Garces, E., & Daim, T. (2025). Digital strategies and non-conventional sources of innovation: Analysis of causal relationships using interpretive structural modeling. Technology in Society, 82, 102940. https://doi.org/10.1016/j.techsoc.2025.102940
Forcael, E., Ferrari, I., Opazo-Vega, A., & Pulido-Arcas, J. A. (2020). Construction 4.0: A literature review. Sustainability, 12(22), 9755. https://doi.org/10.3390/su12229755
Graneheim, U. H., & Lundman, B. (2004). Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105–112. https://doi.org/10.1016/j.nedt.2003.10.001
Guba, E. G. (1981). Criteria for assessing the trustworthiness of naturalistic inquiries. Ectj, 29(2), 75-91. https://doi.org/10.1007/BF02766777
Harikannan, N., Vinodh, S., & Antony, J. (2025). Analysis of the relationship among Industry 4.0 technologies, sustainable manufacturing practices and organizational sustainable performance using structural equation modelling. The TQM Journal, 37(1), 42-72. https://doi.org/10.1108/TQM-02-2023-0044
Javaid, M. Z., Shoukat, M. Z., & Niazi, A. A. K. (2022). Total Interpretive Structural Modeling to Identify Enablers for Successful Implementation of Total Productive Management. Leadership, 1(2), 130-156.
Júnior, E. D. S., Silva, D. J. C. D., Carvalho, R. B. D., & Lopes, L. F. D. (2025). Barriers to implementing Industry 4.0: perceptions of professionals in the Brazilian cement industry. The International Journal of Advanced Manufacturing Technology, 137(9), 4989-5000. https://doi.org/10.1007/s00170-025-15443-9
Kazançoğlu, Y., Gozacan, N., Luthra, S., & Kumar, A. (2024). Are we really addressing the roadblocks to adoption of renewable and sustainable energy technologies? Total interpretive structural modeling approach. Environmental Science and Pollution Research, 31(11), 16846–16864. https://doi.org/10.1007/s11356-024-32096-5
Khalili, S., Saeedi, F., Yousefi, S., & Zandpourasl, M. (2025). Investigating the impact of the "attitude and mindset" component on the success of project managers in the Iranian construction industry. System Engineering and Productivity. 5(1), 1-19. https://doi.org/10.22034/sep.2025.2046688.1237
Khan, M. I., Yasmeen, T., Khan, M., Hadi, N. U., Asif, M., Farooq, M., & Al-Ghamdi, S. G. (2025). Integrating industry 4.0 for enhanced sustainability: Pathways and prospects. Sustainable Production and Consumption, 54, 149-189. https://doi.org/10.1016/j.spc.2024.12.012
Kloker, S., Straub, T., Morana, S., & Weinhardt, C. (2018). The effect of social reputation on retention: Designing a social real-time Delphi platform.
Kumar, R., & Goel, P. (2022). Exploring the domain of interpretive structural modelling (ISM) for sustainable future panorama: A bibliometric and content analysis. Archives of Computational Methods in Engineering, 29(5), 2781–2810. https://doi.org/10.1007/s11831-021-09675-7
Li, Y., Badulescu, A., & Badulescu, D. (2025). Modeling and Analyzing Critical Policies for Improving Energy Efficiency in Manufacturing Sector: An Interpretive Structural Modeling (ISM) Approach. Energies, 18(4), 893. https://doi.org/10.3390/en18040893
Lincoln, Y. S. (1995). Emerging criteria for quality in qualitative and interpretive research. Qualitative Inquiry, 1(3), 275–289. https://doi.org/10.1177/107780049500100301
Liu, W., & Feng, J. (2025). Identifying key factors and interrelationships affecting large-scale agricultural biomass production: Insights from interpretive structural modeling. Biomass and Bioenergy, 200, 108013. https://doi.org/10.1016/j.biombioe.2025.108013
Maskuriy, R., Selamat, A., Ali, K. N., Maresova, P., & Krejcar, O. (2019). Industry 4.0 for the construction industry—how ready is the industry?. Applied Sciences, 9(14), 2819. https://doi.org/10.3390/app9142819
Mason, M. (2010, September). Sample size and saturation in PhD studies using qualitative interviews. In Forum: Qualitative social research (Vol. 11, No. 3). Freie Universität Berlin. https://doi.org/10.17169/fqs-11.3.1428
Muñoz-La Rivera, F., Mora-Serrano, J., Valero, I., & Oñate, E. (2021). Methodological-technological framework for Construction 4.0. Archives of Computational Methods in Engineering, 28(2), 689–711. https://doi.org/10.1007/s11831-020-09455-9
Noy, C. (2008). Sampling knowledge: The hermeneutics of snowball sampling in qualitative research. International Journal of Social Research Methodology, 11(4), 327–344. https://doi.org/10.1080/13645570701401305
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533–544. https://doi.org/10.1007/s10488-013-0528-y
Rahbaripour, K., Pakdelfard, M., Sattari Sarbangholi, H., & Valizadeh, N. (2025). Construction 4.0 barriers in housing development in Iran. System Engineering and Productivity, 1-43. https://doi.org/10.22034/sep.2025.2060254.1320
Ranjan Debata, B., Sree, K., Patnaik, B., & Sankar Mahapatra, S. (2013). Evaluating medical tourism enablers with interpretive structural modeling. Benchmarking: An International Journal, 20(6), 716-743. https://doi.org/10.1108/BIJ-10-2011-0079
Ribeiro, A. M., Arantes, A., & Cruz, C. O. (2022). Barriers to the adoption of modular construction in Portugal: An interpretive structural modeling approach. Buildings, 12(10), 1509. https://doi.org/10.3390/buildings12101509
Royse, D. (2008). Program Evaluation: Its Role and Contribution to Evidence-Based Practice. SOCIAL WORK PRACTICE, 120.
Stake, R. E., Denzin, N. K., & Lincoln, Y. S. (1994). Handbook of qualitative research. NK Denzin & YS Lincoln (Eds.), 244.
Sarvari, R., Jabarzadeh, Y., Karami, A., & Jabarnejad, M. (2024). An interpretive structural modeling—analytic network process approach for analysing green entrepreneurship barriers. International Entrepreneurship and Management Journal, 20(1), 367–391. https://doi.org/10.1007/s11365-023-00881-2
Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018). Saturation in qualitative research: Exploring its conceptualization and operationalization. Quality & Quantity, 52(4), 1893–1907. https://doi.org/10.1007/s11135-017-0574-8
Sawhney, A., Riley, M., & Irizarry, J. (2020). Construction 4.0: Introduction and overview. In Construction 4.0 (pp. 3-22). Routledge.
Shafei, H., Rahman, R. A., & Lee, Y. S. (2025). Evaluating construction 4.0 technologies in enhancing safety and health: case study of a national strategic plan. Journal of Engineering, Design and Technology, 23(4), 1211-1242. https://doi.org/10.1108/JEDT-08-2023-0330
Shahzad, M. F., Liu, H., & Zahid, H. (2024). Industry 4.0 technologies and sustainable performance: Do green supply chain collaboration, circular economy practices, technological readiness and environmental dynamism matter? Journal of Manufacturing Technology Management, 36(1), 1–22. https://doi.org/10.1108/JMTM-05-2024-0236
Singh, A., Kumar, V., Verma, P., & Kandasamy, J. (2023). Identification and severity assessment of challenges in the adoption of Industry 4.0 in Indian construction industry. Asia Pacific Management Review, 28(3), 299–315. https://doi.org/10.1016/j.apmrv.2022.10.007
Siriwardhana, S., & Moehler, R. C. (2023). Enabling productivity goals through Construction 4.0 skills: Theories, debates, definitions. Journal of Cleaner Production, 425, 139011. https://doi.org/10.1016/j.jclepro.2023.139011
Sushil. (2017). Modified ISM/TISM process with simultaneous transitivity checks for reducing direct pair comparisons. Global Journal of Flexible Systems Management, 18(4), 331–351. https://doi.org/10.1007/s40171-017-0167-3
Talbi, A., & Souad, S. B. (2022). Industry 4.0 in construction organization of mega projects: A bibliometric analysis. Procedia Computer Science, 204, 524–531. https://doi.org/10.1016/j.procs.2022.08.064
Taqi, H. M. M., Nayeem, I., Bari, A. M., Anam, M. Z., & Ali, S. M. (2025). Addressing challenges to cloud manufacturing in industry 4.0 environment using an integrated approach: Implications for sustainability. Green Technologies and Sustainability, 100166. https://doi.org/10.1016/j.grets.2024.100166
Turner, C., Oyekan, J., Stergioulas, L., & Griffin, D. (2021). Utilizing Industry 4.0 on the construction site: Challenges and opportunities. IEEE Transactions on Industrial Informatics, 17(2), 746–756. https://doi.org/10.1109/TII.2020.3002197
Wang, Y., & Wang, X. (2025). Values, Application Scenarios and Challenges of Blockchain Technology: A Perspective from Construction 4.0. KSCE Journal of Civil Engineering, 100281. https://doi.org/10.1016/j.kscej.2025.100281
Warfield, J. N. (2007). Toward interpretation of complex structural models. IEEE transactions on systems, man, and cybernetics, (5), 405-417. https://doi.org/10.1109/TSMC.1974.4309336
W John, C. (2013). Qualitative Inquiry And Research Design Choosing Among Five Approaches. Library of Congress Cataloging-in-Publication Data.
You, Z., & Feng, L. (2020). Integration of industry 4.0 related technologies in construction industry: a framework of cyber-physical system. Ieee Access, 8, 122908-122922. https://doi.org/10.1109/ACCESS.2020.3007206
Zhang, C., Zhou, G., Li, J., Chang, F., Ding, K., & Ma, D. (2023). A multi-access edge computing enabled framework for the construction of a knowledge-sharing intelligent machine tool swarm in Industry 4.0. Journal of Manufacturing Systems, 66, 56-70. https://doi.org/10.1016/j.jmsy.2022.11.015
Zhang, J., Zhu, X., Khan, A. M., Houda, M., Rehman, S. K. U., Jameel, M., ... & Alrowais, R. (2023). BIM-based architectural analysis and optimization for construction 4.0 concept (a comparison). Ain Shams Engineering Journal, 14(6), 102110. https://doi.org/10.1016/j.asej.2022.102110
 
مهندسی سیستم و بهره‌وری

مقالات آماده انتشار، پذیرفته شده
انتشار آنلاین از 01 شهریور 1404

  • تاریخ دریافت 30 تیر 1404
  • تاریخ بازنگری 24 مرداد 1404
  • تاریخ پذیرش 01 شهریور 1404
  • تاریخ اولین انتشار 01 شهریور 1404
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