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معمارپور غیاثی, علی, عباسی, مرتضی, قیدر خلجانی, جعفر. (1404). ارزیابی تامین‌کنندگان در مگاپروژه‌های ماژولار با استفاده از رویکرد LOPCOW-ARTASI تحت عدم قطعیت. سامانه مدیریت نشریات علمی, 23(77), 85-132. doi: 10.22054/jims.2025.85695.2968
علی معمارپور غیاثی; مرتضی عباسی; جعفر قیدر خلجانی. "ارزیابی تامین‌کنندگان در مگاپروژه‌های ماژولار با استفاده از رویکرد LOPCOW-ARTASI تحت عدم قطعیت". سامانه مدیریت نشریات علمی, 23, 77, 1404, 85-132. doi: 10.22054/jims.2025.85695.2968
معمارپور غیاثی, علی, عباسی, مرتضی, قیدر خلجانی, جعفر. (1404). 'ارزیابی تامین‌کنندگان در مگاپروژه‌های ماژولار با استفاده از رویکرد LOPCOW-ARTASI تحت عدم قطعیت', سامانه مدیریت نشریات علمی, 23(77), pp. 85-132. doi: 10.22054/jims.2025.85695.2968
معمارپور غیاثی, علی, عباسی, مرتضی, قیدر خلجانی, جعفر. ارزیابی تامین‌کنندگان در مگاپروژه‌های ماژولار با استفاده از رویکرد LOPCOW-ARTASI تحت عدم قطعیت. سامانه مدیریت نشریات علمی, 1404; 23(77): 85-132. doi: 10.22054/jims.2025.85695.2968

ارزیابی تامین‌کنندگان در مگاپروژه‌های ماژولار با استفاده از رویکرد LOPCOW-ARTASI تحت عدم قطعیت

مطالعات مدیریت صنعتی
مقاله 3، دوره 23، شماره 77، تیر 1404، صفحه 85-132    اصل مقاله (1.01 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22054/jims.2025.85695.2968
نویسندگان
علی معمارپور غیاثی1؛ مرتضی عباسی* 2؛ جعفر قیدر خلجانی3
1دانشجوی دکتری، گروه مهندسی صنایع، دانشکده مدیریت و مهندسی صنایع، دانشگاه صنعتی مالک اشتر، تهران، ایران
2استادیار، گروه مهندسی صنایع، دانشکده مدیریت و مهندسی صنایع، دانشگاه صنعتی مالک اشتر، تهران، ایران
3دانشیار، گروه مهندسی صنایع، دانشکده مدیریت و مهندسی صنایع، دانشگاه صنعتی مالک اشتر، تهران، ایران
چکیده
ارزیابی تأمین‌کنندگان در موفقیت مگاپروژه‌های ماژولار نقشی تعیین‌کننده دارد؛ زیرا این پروژه‌ها به‌واسطه‌ی نیاز به هماهنگی پیچیده‌ی زیرسیستم‌های گوناگون و یکپارچگی دقیق ماژول‌ها، مستلزم همکاری با تأمین‌کنندگانی توانمند هستند. هدف این تحقیق ارائه یک چارچوب یکپارچه جهت ارزیابی تامین‌کنندگان مگاپروژه‌های ماژولار است. در این پژوهش، برای اولین بار جهت ارزیابی تامین‌کنندگان از رویکرد ترکیبی مبتنی بر روش‌های LOPCOW و ARTASI توسعه‌یافته بر اساس مجموعه‌های فازی کروی (SF-LOPCOW و SF-ARTASI) استفاده شده است. این رویکرد قادر است هم‌زمان با عدم قطعیت و تصمیم‌گیری گروهی مقابله کند. بر اساس این رویکرد، ۳۱ معیار مبتنی بر ابعاد پایداری برای فرایند ارزیابی تامین‌کنندگان مگاپروژه‌های ماژولار شناسایی شده است. سپس، با استفاده از روش SF-LOPCOW وزن‌دهی به معیارها انجام می‌شود. بر اساس نتایج این مرحله، هزینه، استراتژی و سازمان‌دهی و میزان پسماند تولیدی به ترتیب با ۰.۰۸۷، ۰.۰۸۳ و ۰.۷۹ بیشترین وزن‌ها را به خود اختصاص دادند. در آخر، بر اساس یک مطالعه موردی ۱۲ شرکت تامین‌کننده تعیین شده برای مسئله ارزیابی تامین‌کنندگان مگاپروژه‌های ماژولار از طریق روش SF-ARTASI ارزیابی و اولویت‌بندی می‌گردند. مقایسه نتایج SF-ARTASI با سایر روش‌های تصمیم‌گیری چند معیاره موجود در ادبیات و همچنین تحلیل حساسیت، کارآمدی رویکرد پیشنهادی و پایداری رتبه‌بندی آن را در سناریوهای مختلف نشان می‌دهد.
کلیدواژه‌ها
مدیریت مگاپروژه؛ مگاپروژه‌های ماژولار؛ ارزیابی تامین‌کننده؛ تصمیم‌گیری چند‌معیاره؛ مجموعه‌های فازی کروی
مراجع
  1. کشاورز قرابائی، مهدی. (۱۴۰۳). یک مدل چندهدفه مبتنی بر تصمیم‌گیری گروهی و مجموعه‌های فازی فیثاغورثی بازه‌ای-مقدار برای مسئله انتخاب تأمین‌کننده و تخصیص سفارش. مطالعات مدیریت صنعتی، ۲۲ (۷۴)، ۱-۴۹. https://doi.org/10.22054‌/jims.2024.80903.2926
  2. معمارپور غیاثی، علی، عباسی، مرتضی و قیدرخلجانی، جعفر. (۱۴۰۴). ارزیابی علل افزایش زمان و هزینه مگاپروژه‌ها با استفاده از رویکرد یکپارچه مبتنی بر روش‌های بهترین-بدترین و مارکوس توسعه‌یافته بر اساس تئوری اعداد Z. چشم‌انداز مدیریت صنعتی، ۱۵ (۱)، ۷۳-۱۰۰. https://doi.org/10.48308/jimp.15.1.73
  3. معمارپور غیاثی، علی، عباسی، مرتضی، پیری، مرتضی و اخوان، پیمان. (۱۴۰۳). موانع پیاده‌سازی تکنولوژی بلاکچین در لجستیک بشردوستانه در شرایط عدم قطعیت. مطالعات مدیریت کسب‌وکار هوشمند، ۱۲ (۴۷)، ۱۵۳-۱۸۴. https://doi.org/10.22054‌/ims.2023.72916.2304
  4.  Aljohani, A., Ahiaga-Dagbui, D., & Moore, D. (2017). Construction projects cost overrun: What does the literature tell us? International Journal of Innovation,
  5. Amindoust, A., Ahmed, S., Saghafinia, A., & Bahreininejad, A. (2012). Sustainable supplier selection: A ranking model based on fuzzy inference system. Applied Soft Computing, 12(6), 1668-1677. https://doi.org/10.1016/j.asoc.2012.01.023
  6. Ashkanani, S., & Franzoi, R. (2023). Gaps in megaproject management system literature: a systematic overview. Engineering, Construction and Architectural Management, 30(3), 1300-1318. https://doi.org/10.1108/ECAM-12-2021-1113
  7. Atanassov, K. T., & Atanassov, K. T. (1999). Intuitionistic fuzzy sets. Springer. https://doi.org/10.1007/978-3-7908-1870-3_1
  8. Cheraghalipour, A., & Farsad, S. (2018). A bi-objective sustainable supplier selection and order allocation considering quantity discounts under disruption risks: A case study in plastic industry. Computers & Industrial Engineering, 118, 237-250. https://doi.org/10.1016/‌j.cie.2018.02.04
  9. Christanto, S., Runtuk, J. K., & Ng, P. K. (2025). Optimizing Supplier Selection: A Comparative Study of Fuzzy Vikor and Fuzzy Moora for Performance-Based Decision Making. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3525362
  10. Çobanoğulları, G., Daldıran, K., & Daldıran, B. (2026). Analysis of Innovation Performance of South-Eastern European Countries in Transition Economies: An Application of the Entropy-Based ARTASI Method. Spectrum of Operational Research, 193-214. https://doi.org/10.31181/sor31202642
  11. Dang, P., Gao, H., Niu, Z., Geng, L., Hui, F. K. P., & Sun, C. (2024). The Supplier Selection of Prefabricated Component Production Line: A Lean-Based AHP–Improved VIKOR Framework. Buildings, 14(12), 4018. https://doi.org/10.3390/buildings14124018
  12. Dhruva, S., Krishankumar, R., Ravichandran, K. S., Kaklauskas, A., Zavadskas, E. K., & Gupta, P. (2025). Selection of waste treatment methods for food sources: an integrated decision model using q-rung fuzzy data, LOPCOW, and COPRAS techniques. Clean Technologies and Environmental Policy, 1-25. https://doi.org/10.1007/s10098-025-03160-6
  13. Durdu, D. (2025). Evaluating Financial Performance with SPC-LOPCOW-AROMAN Hybrid Methodology: A Case Study for Firms Listed in BIST Sustainability Index. Knowledge and Decision Systems with Applications, 1, 92-111. https://doi.org/10.59543/‌kadsa.v1i.13879
  14. Dündar, S. (2024). Project performance analysis of Turkish universities by LOPCOW-CRADIS methods. Journal of Turkish Operations Management, 8(2), 409-425. https://doi.org/10.56554/jtom.1336202
  15. Ecer, F., & Pamucar, D. (2022). A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690
  16. Ecer, F., Tanrıverdi, G., Yaşar, M., & Görçün, Ö. F. (2025). Sustainable aviation fuel supplier evaluation for airlines through LOPCOW and MARCOS approaches with interval-valued fuzzy neutrosophic information. Journal of Air Transport Management, 123, 102705. https://doi.org/10.1016/j.jairtraman.2024.102705
  17. Elkington, J., & Rowlands, I. H. (1999). Cannibals with forks: The triple bottom line of 21st century business. Alternatives Journal, 25(4), 42.
  18. Fallahpour, A., Nayeri, S., Sheikhalishahi, M., Wong, K. Y., Tian, G., & Fathollahi-Fard, A. M. (2021). A hyper-hybrid fuzzy decision-making framework for the sustainable-resilient supplier selection problem: a case study of Malaysian Palm oil industry. Environmental Science and Pollution Research, 1-21. https://doi.org/10.1007/s11356-021-12491-y
  19. Famiyeh, S., Amoatey, C. T., Adaku, E., & Agbenohevi, C. S. (2017). Major causes of construction time and cost overruns: A case of selected educational sector projects in Ghana. Journal of Engineering, Design and Technology, 15(2), 181-198. https://doi.org/10.1108/JEDT-11-2015-0075
  20. Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project management journal, 45(2), 6-19. https://doi.org/10.1002/pmj.21409
  21. Flyvbjerg, B. (2021). Make megaprojects more modular. Harvard Business Review, 58-63
  22. Gao, Y., & Yu, A. (2025). A spherical fuzzy WASPAS approach to prioritize the factors enhancing the effectiveness of physical education classroom teaching. Scientific Reports, 15(1), 20875. https://doi.org/10.1038/s41598-025-05273-w
  23. Ghiaci, A. M., & Ghoushchi, S. J. (2023). Assessment of barriers to IoT-enabled circular economy using an extended decision-making-based FMEA model under uncertain environment. Internet of Things, 100719. https://doi.org/10.1016/j.iot.2023.100719
  24. Ghoushchi, S. J., Bonab, S. R., Ghiaci, A. M., Haseli, G., Tomaskova, H., & Hajiaghaei-Keshteli, M. (2021). Landfill site selection for medical waste using an integrated SWARA-WASPAS framework based on spherical fuzzy set. Sustainability, 13(24), 13950. https://doi.org/10.3390/su132413950
  25. Görçün, Ö. F., Tirkolaee, E. B., Küçükönder, H., & Garg, C. P. (2024). Assessing and selecting sustainable refrigerated road vehicles in food logistics using a novel multi-criteria group decision-making model. Information Sciences, 661, 120161. https://doi.org/10.1016/j.ins.2024.120161
  26. Hajiaghaei-Keshteli, M., Cenk, Z., Erdebilli, B., Özdemir, Y. S., & Gholian-Jouybari, F. (2023). Pythagorean fuzzy TOPSIS method for green supplier selection in the food industry. Expert Systems with applications, 224, 120036. https://doi.org/10.1016/j.eswa.‌2023.120036
  27. Hallak, J. (2024). Optimizing construction supplier selection in conflict-affected regions: a hybrid multi-criteria framework. Operations Management Research, 1-25. https://doi.org/10.1007/s12063-024-00505-0
  28. He, Q., Chen, X., Wang, G., Zhu, J., Yang, D., Liu, X., & Li, Y. (2019). Managing social responsibility for sustainability in megaprojects: An innovation transitions perspective on success. Journal of cleaner production, 241, 118395. https://doi.org/10.1016/j.jclepro.‌2019.118395
  29. Hendiani, S., Mahmoudi, A., & Liao, H. (2020). A multi-stage multi-criteria hierarchical decision-making approach for sustainable supplier selection. Applied Soft Computing, 94, 106456. https://doi.org/10.1016/j.asoc.2020.106456
  30. Hoseini, S. A., Fallahpour, A., Wong, K. Y., Mahdiyar, A., Saberi, M., & Durdyev, S. (2021). Sustainable supplier selection in construction industry through hybrid fuzzy-based approaches. Sustainability, 13(3), 1413. https://doi.org/10.3390/su13031413
  31. Hosseini, S. M., Paydar, M. M., & Hajiaghaei-Keshteli, M. (2021). Recovery solutions for ecotourism centers during the Covid-19 pandemic: Utilizing Fuzzy DEMATEL and Fuzzy VIKOR methods. Expert Systems with applications, 185, 115594. https://doi.org/10.1016/j.eswa.2021.115594
  32. Jafarzadeh Ghoushchi, S., Memarpour Ghiaci, A., Rahnamay Bonab, S., & Ranjbarzadeh, R. (2022). Barriers to circular economy implementation in designing of sustainable medical waste management systems using a new extended decision-making and FMEA models. Environmental science and pollution research, 29(53), 79735-79753. https://doi.org/10.1007/s11356-022-19018-z
  33. Jafarzadeh Ghoushchi, S., Shaffiee Haghshenas, S., Memarpour Ghiaci, A., Guido, G., & Vitale, A. (2022). Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment. Neural Computing and Applications, 1-19. https://doi.org/10.1007/s00521-022-07929-4
  34. Jauhar, S. K., & Pant, M. (2017). Integrating DEA with DE and MODE for sustainable supplier selection. Journal of computational science, 21, 299-306. https://doi.org/10.1016/j.jocs.2017.02.011
  35. Kara, K., Yalçın, G. C., Kaygısız, E. G., Simic, V., Örnek, A. Ş., & Pamucar, D. (2024). A picture fuzzy CIMAS-ARTASI model for website performance analysis in human resource management. Applied Soft Computing, 162, 111826. https://doi.org/10.1016/j.asoc.‌111826
  36. Karamoozian, A., & Wu, D. (2020). A hybrid risk prioritization approach in construction projects using failure mode and effective analysis. Engineering, Construction and Architectural Management, 27(9), 2661-2686. https://doi.org/10.1108/ECAM-10-2019-0535
  37. Keleş, N., & Kahveci, A. (2025). EVALUATING THE LOGISTICS PERFORMANCE OF THE EU CANDIDATE AND MEMBER COUNTRIES USING THE WENSLO AND ARTASI METHODS. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (68), 43-66. https://doi.org/10.30794/pausbed.1594714
  38. Khan, S. A., Kusi-Sarpong, S., Arhin, F. K., & Kusi-Sarpong, H. (2018). Supplier sustainability performance evaluation and selection: A framework and methodology. Journal of cleaner production, 205, 964-979. https://doi.org/10.1016/j.jclepro.2018.09.144
  39. Kou, G., Aydın, F. B., Eti, S., Yüksel, S., & Dinçer, H. (2025). A novel Spherical fuzzy MEREC-ARAS decision framework for optimizing innovation-driven investment strategies in energy systems. Energy Strategy Reviews, 59, 101771. https://doi.org/10.1016/j.esr.‌101771
  40. Kutlu Gündoğdu, F., & Kahraman, C. (2019). Spherical fuzzy sets and spherical fuzzy TOPSIS method. Journal of Intelligent & Fuzzy Systems, 36(1), 337-352. https://doi.org/10.3233/JIFS-181401
  41. Li, H., Cao, Y., & Su, L. (2022). Pythagorean fuzzy multi-criteria decision-making approach based on Spearman rank correlation coefficient. Soft Computing, 26(6), 3001-3012. https://doi.org/10.1007/s00500-021-06615-2
  42. Liang, R., Li, R., Yan, X., Xue, Z., & Wei, X. (2023). Evaluating and selecting the supplier in prefabricated megaprojects using extended fuzzy TOPSIS under hesitant environment: A case study from China. Engineering, Construction and Architectural Management, 30(5), 1902-1931. https://doi.org/10.1108/ECAM-09-2021-0793
  43. Lin, C., Chen, J., Feng, C., & Li, X. (2024). Optimizing supplier selection for prefabricated components: a comprehensive evaluation. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-09-2024-1230
  44. Liu, H.-C., Quan, M.-Y., Li, Z., & Wang, Z.-L. (2019). A new integrated MCDM model for sustainable supplier selection under interval-valued intuitionistic uncertain linguistic environment. Information sciences, 486, 254-270. https://doi.org/10.1016/j.ins.2019.02.056
  45. Lotfi, Z. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
  46. Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of cleaner production, 140, 1686-1698. https://doi.org/10.1016/j.jclepro.2016.09.078
  47. Mahmoudi, A., Deng, X., Javed, S. A., & Zhang, N. (2021). Sustainable supplier selection in megaprojects: grey ordinal priority approach. Business Strategy and the Environment, 30(1), 318-339. https://doi.org/10.1002/bse.2623
  48. Mani, V., Agrawal, R., & Sharma, V. (2014). Supplier selection using social sustainability: AHP based approach in India. International strategic management review, 2(2), 98-112. https://doi.org/10.1016/‌j.ism.2014.10.003
  49. Memari, A., Dargi, A., Jokar, M. R. A., Ahmad, R., & Rahim, A. R. A. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of manufacturing systems, 50, 9-24. https://doi.org/10.1016/j.jmsy.2018.11.002
  50. Memarpour Ghiaci, A., Garg, H., & Jafarzadeh Ghoushchi, S. (2022). Improving emergency departments during COVID-19 pandemic: a simulation and MCDM approach with MARCOS methodology in an uncertain environment. Computational and Applied Mathematics, 41(8), 1-23. https://doi.org/10.1007/s40314-022-02080-1
  51. Mignacca, B., & Locatelli, G. (2021). Modular circular economy in energy infrastructure projects: Enabling factors and barriers. Journal of Management in Engineering, 37(5), 04021053. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000949
  52. Murugan, R. B., & Wong, K. Y. (2025). Sustainable Supplier Selection for Labelling Materials Used in a Herbicide Manufacturing Company. In Green Finance and Energy Transition: Innovation, Legal Frameworks and Regulation (pp. 147-158). Springer. https://doi.org/10.1007/978-3-031-75960-4_15
  53. Nadeem, M., Gyapong, E., & Ahmed, A. (2020). Board gender diversity and environmental, social, and economic value creation: Does family ownership matter? Business Strategy and the Environment, 29(3), 1268-1284. https://doi.org/10.1002/bse.2432
  54. Nişel, R., & Nişel, S. (2024). Advancing Global Innovation Metrics: A Comprehensive Country Ranking Using the Novel LOPCOW-CoCoSo Model. In Ethics and Sustainability in Accounting and Finance, Volume IV (pp. 99-118). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-4351-3_7
  55. Pamucar, D., Özçalıcı, M., & Gurler, H. E. (2025). Evaluation of the efficiency of world airports using WENSLO-ARTASI and Monte-Carlo simulation. Journal of Air Transport Management, 124, 102749. https://doi.org/10.1016/j.jairtraman.2025.102749
  56. Pamucar, D., Simic, V., Görçün, Ö. F., & Küçükönder, H. (2024). Selection of the best Big Data platform using COBRAC-ARTASI methodology with adaptive standardized intervals. Expert Systems with applications, 239, 122312. https://doi.org/10.1016/j.eswa.2023.122312
  57. Radovanović, M., Jovčić, S., Petrovski, A., & Cirkin, E. (2025). Evaluation of university professors using the spherical fuzzy AHP and grey MARCOS multi-criteria decision-making model: A case study. Spectrum of decision making and applications, 2(1), 198-218. https://doi.org/10.31181/sdmap21202518
  58. Rashidi, K., & Cullinane, K. (2019). A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: Implications for sourcing strategy. Expert Systems with applications, 121, 266-281. https://doi.org/10.1016/j.eswa.2018.12.025
  59. Rong, Y., Yu, L., Liu, Y., Simic, V., & Garg, H. (2024). The FMEA model based on LOPCOW-ARAS methods with interval-valued Fermatean fuzzy information for risk assessment of R&D projects in industrial robot offline programming systems. Computational and Applied Mathematics, 43(1), 25. https://doi.org/10.1007/s40314-023-02532-2
  60. Rostami, A., & Oduoza, C. F. (2017). Key risks in construction projects in Italy: contractors’ perspective. Engineering, Construction and Architectural Management, 24(3), 451-462. https://doi.org/10.1108/‌ECAM-09-2015-0142
  61. Sahin, F., & Menekse, A. (2025). Internal control risk assessment using interval valued spherical fuzzy CRITIC EDAS. Scientific Reports, 15(1), 21505. https://doi.org/10.1038/s41598-025-07852-3
  62. Shang, Z., Yang, X., Barnes, D., & Wu, C. (2022). Supplier selection in sustainable supply chains: Using the integrated BWM, fuzzy Shannon entropy, and fuzzy MULTIMOORA methods. Expert Systems with applications, 195, 116567. https://doi.org/10.1016/j.eswa.2022.‌116567
  63. Sharma, P., Nila, B., Pamucar, D., & Roy, J. (2025). Integrating LOPCOW-DOBI method and possibilistic programming for two-stage decision making in resilient food supply chain network. Journal of Industrial Information Integration, 100847. https://doi.org/10.1016/j.jii.2025.100847
  64. Su, Y., Zhao, M., Wei, C., & Chen, X. (2022). PT-TODIM method for probabilistic linguistic MAGDM and application to industrial control system security supplier selection. International Journal of Fuzzy Systems, 1-14. https://doi.org/10.1007/s40815-021-01125-7
  65. Tatar, V., Ayvaz, B., & Pamucar, D. (2025). A quantitative ergonomic risk assessment model of maritime port operations: An integrated spherical fuzzy-FUCOM-ARTASI approach. Ocean & Coastal Management, 267, 107710. https://doi.org/10.1016/j.ocecoaman.‌107710
  66. Tirkolaee, E. B., Mardani, A., Dashtian, Z., Soltani, M., & Weber, G.-W. (2020). A novel hybrid method using fuzzy decision making and multi-objective programming for sustainable-reliable supplier selection in two-echelon supply chain design. Journal of cleaner production, 250, 119517. https://doi.org/10.1016/j.jclepro.‌2019.119517
  67. Tshidavhu, F., & Khatleli, N. (2020). An assessment of the causes of schedule and cost overruns in South African megaprojects: A case of the critical energy sector projects of Medupi and Kusile. Acta Structilia, 27(1), 119-143.
  68. Unal, Y., & Temur, G. T. (2021). Sustainable supplier selection by using spherical fuzzy AHP. Journal of Intelligent & Fuzzy Systems, 42(1), 593-603. https://doi.org/10.3233/JIFS-219214
  69. Wang, S., Chong, H.-Y., & Zhang, W. (2024). The impact of BIM-based integration management on megaproject performance in China. Alexandria Engineering Journal, 94, 34-43. https://doi.org/10.1016/j.aej.2024.03.036
  70. Xu, Z., Qin, J., Liu, J., & Martínez, L. (2019). Sustainable supplier selection based on AHPSort II in interval type-2 fuzzy environment. Information sciences, 483, 273-293. https://doi.org/10.1016/‌j.ins.2019.01.013
  71. Yadavalli, V. S., Darbari, J. D., Bhayana, N., Jha, P., & Agarwal, V. (2019). An integrated optimization model for selection of sustainable suppliers based on customers’ expectations. Operations Research Perspectives, 6, 100113. https://doi.org/10.1016/j.orp.2019.100113
  72. Yager, R. R. (2013). Pythagorean fuzzy subsets. 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS).https://doi.org/10.1109/IFSA-NAFIPS.2013.6608375
  73. Yalçın, G. C., Kara, K., & Senapati, T. (2024). A hybrid spherical fuzzy logarithmic decomposition of criteria importance and alternative ranking technique based on Adaptive Standardized Intervals model with application. Decision Analytics Journal, 11, 100441. https://doi.org/10.1016/j.dajour.2024.100441
  74. Yu, C., Shao, Y., Wang, K., & Zhang, L. (2019). A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment. Expert Systems with applications, 121, 1-17. https://doi.org/10.1016/j.eswa.2018.12.010
  75. Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information sciences, 8(3), 199-249. https://doi.org/10.1016/0020-0255(75)90017-1
  76. Zhao, L., Liu, Z., & Mbachu, J. (2019). Optimization of the supplier selection process in prefabrication using BIM. Buildings, 9(10), 222. https://doi.org/10.3390/buildings9100222
  77. Zhou, Z., & Mi, C. (2017). Social responsibility research within the context of megaproject management: Trends, gaps and opportunities. International journal of project management, 35(7), 1378-1390. https://doi.org/10.1016/j.ijproman.2017.02.017
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