دانشگاه مازندران

 آمار

تعداد نشریات32
تعداد شماره‌ها591
تعداد مقالات5,779
تعداد مشاهده مقاله8,660,782
تعداد دریافت فایل اصل مقاله6,342,639
Lale Arefi, Shahin, Bitarafan, Mahdi. (1405). A Technology-Maturity-Based Foresight Portfolio Framework for Smart Seismic Structures: Integrating CRITIC, SWARA-Based Weighting, Fuzzy VIKOR, Borda Analysis, and Monte Carlo Uncertainty Assessment. پژوهشنامه مدیریت اجرایی, (), 21-45. doi: 10.22080/ceas.2026.32049.1110
Shahin Lale Arefi; Mahdi Bitarafan. "A Technology-Maturity-Based Foresight Portfolio Framework for Smart Seismic Structures: Integrating CRITIC, SWARA-Based Weighting, Fuzzy VIKOR, Borda Analysis, and Monte Carlo Uncertainty Assessment". پژوهشنامه مدیریت اجرایی, , , 1405, 21-45. doi: 10.22080/ceas.2026.32049.1110
Lale Arefi, Shahin, Bitarafan, Mahdi. (1405). 'A Technology-Maturity-Based Foresight Portfolio Framework for Smart Seismic Structures: Integrating CRITIC, SWARA-Based Weighting, Fuzzy VIKOR, Borda Analysis, and Monte Carlo Uncertainty Assessment', پژوهشنامه مدیریت اجرایی, (), pp. 21-45. doi: 10.22080/ceas.2026.32049.1110
Lale Arefi, Shahin, Bitarafan, Mahdi. A Technology-Maturity-Based Foresight Portfolio Framework for Smart Seismic Structures: Integrating CRITIC, SWARA-Based Weighting, Fuzzy VIKOR, Borda Analysis, and Monte Carlo Uncertainty Assessment. پژوهشنامه مدیریت اجرایی, 1405; (): 21-45. doi: 10.22080/ceas.2026.32049.1110

A Technology-Maturity-Based Foresight Portfolio Framework for Smart Seismic Structures: Integrating CRITIC, SWARA-Based Weighting, Fuzzy VIKOR, Borda Analysis, and Monte Carlo Uncertainty Assessment

Civil Engineering and Applied Solutions
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 13 شهریور 1405
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/ceas.2026.32049.1110
نویسندگان
Shahin Lale Arefi* 1؛ Mahdi Bitarafan2
1Department of Civil Engineering, Esfarayen University of Technology, Esfarayen, Iran
2International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran
تاریخ دریافت: 17 خرداد 1405،  تاریخ بازنگری: 01 مرداد 1405،  تاریخ پذیرش: 13 شهریور 1405 
چکیده
The rapid development of smart seismic technologies requires structured approaches for selecting foresight methods according to technology maturity. Existing studies mainly address the technical development or performance assessment of individual technologies, while limited attention has been given to maturity-sensitive foresight portfolio design. This study proposes a technology-maturity-based foresight portfolio framework for smart seismic structures. First, scientific and patent-based evidence is screened and coded. The CRITIC method is used to weight evidence indicators and construct weighted maturity profiles, after which technologies are assigned to four planning-oriented maturity/application stages using predefined profile-based classification rules: emerging/research-oriented, developing/technology-readiness, implementation-oriented, and recovery/resilience-oriented. Second, twelve valid expert questionnaires are used to evaluate decision criteria and foresight methods. The criteria are weighted through a SWARA-based procedure, and eight foresight methods are ranked using Fuzzy VIKOR. Third, the overall VIKOR ranking is complemented by a separate tied-rank Borda analysis based on experts’ stage-specific portfolio assessments to extract maturity-sensitive foresight portfolios. Robustness is examined using expert agreement and reliability checks, Monte Carlo uncertainty analysis, VIKOR sensitivity analysis, and comparative validation with TOPSIS and PROMETHEE II. The results show that seismic resilience support is the most important criterion. Delphi and technology roadmapping form the most stable overall foresight core, while stage-specific portfolios vary across maturity contexts. The proposed framework supports maturity-sensitive foresight planning for resilient smart seismic infrastructure.
کلیدواژه‌ها
Smart seismic structures؛ Technology foresight؛ Foresight portfolio؛ SWARA-based weighting؛ Fuzzy VIKOR؛ Seismic resilience
مراجع
  1. Terzic, V., Villanueva, P. K., Saldana, D., Yoo, D. Y. Framework for modelling post-earthquake functional recovery of buildings. Engineering Structures, 2021; 246: 113074. doi:10.1016/j.engstruct.2021.113074.
  2. Bhatta, S., Dang, J. Use of IoT for structural health monitoring of civil engineering structures: a state-of-the-art review. Urban Lifeline, 2024; 2: 17. doi:10.1007/s44285-024-00031-2.
  3. Sun, Z., Jayasinghe, S., Sidiq, A., Shahrivar, F., Mahmoodian, M., Setunge, S. Approach towards the development of digital twin for structural health monitoring of civil infrastructure: A comprehensive review. Sensors, 2025; 25: 59. doi:10.3390/s25010059.
  4. Lale Arefi, S., Gholizad, A. Damage detection of truss structures by reduction of degrees of freedom using the Serep method. The Baltic Journal of Road and Bridge Engineering, 2020; 15: 1–25. doi:10.7250/bjrbe.2020-15.459.
  5. Lale Arefi, S., Gholizad, A., Seyedpoor, S. M. Damage detection of structures using modal strain energy with Guyan reduction method. Journal of Rehabilitation in Civil Engineering, 2020; 8: 47–60. doi:10.22075/jrce.2020.19803.1384.
  6. Dannemand Andersen, P., Bevolo, M., Ilevbare, I., Malliaraki, E., Popper, R., Spaniol, M. J. Technology foresight for public funding of innovation: Methods and best practices. Luxemburg (LU): Publications Office of the European Union; 2023. Report No.: JRC134544.
  7. Kishita, Y. Foresight and roadmapping methodology: Trends and outlook. Foresight and STI Governance, 2021; 15: 5–11. doi:10.17323/2500-2597.2021.2.5.11.
  8. Bitarafan, M., Hosseini, K. A., Hashemkhani Zolfani, S., Ziari, K. Evaluating earthquake resilience in urban areas: A novel fuzzy RANCOM approach. Environment, Development and Sustainability, 2026; 28: 2483–2520. doi:10.1007/s10668-025-06393-z.
  9. Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O'Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A., von Winterfeldt, D. A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 2003; 19: 733–752. doi:10.1193/1.1623497.
  10. Cimellaro, G. P., Reinhorn, A. M., Bruneau, M. Framework for analytical quantification of disaster resilience. Engineering Structures, 2010; 32: 3639–3649. doi:10.1016/j.engstruct.2010.08.008.
  11. Sattar, S., Ryan, K., Arendt, L., Bonowitz, D., Comerio, M., Davis, C., Deierlein, G., Johnson, K. Recommended options for improving the built environment for post-earthquake reoccupancy and functional recovery time. Gaithersburg (MD): National Institute of Standards and Technology; 2021. Report No.: 1254.
  12. Bitarafan, M., Arefi, S. L., Zolfani, S. H., Mahmoudzadeh, A. Selecting the best design scenario of the smart structure of bridges for probably future earthquakes. Procedia Engineering, 2013; 57: 193–199. doi:10.1016/j.proeng.2013.04.027.
  13. Qiu, S., Malik, M., Ehsan, H., Wang, W., Wang, J., Cheng, R., Wei, W., Zaheer, Q. Trends and perspectives in structural health monitoring through edge computing: A review with zero-shot natural language processing categorization. Journal of Railway Science and Technology, 2025; 1: 59–74. doi:10.1016/j.jrst.2025.08.003.
  14. Avci, O., Abdeljaber, O., Kiranyaz, S., Hussein, M., Gabbouj, M., Inman, D. J. A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications. Mechanical Systems and Signal Processing, 2021; 147: 107077. doi:10.1016/j.ymssp.2020.107077.
  15. Boje, C., Guerriero, A., Kubicki, S., Rezgui, Y. Towards a semantic Construction Digital Twin: Directions for future research. Automation in Construction, 2020; 114: 103179. doi:10.1016/j.autcon.2020.103179.
  16. Jirawattanasomkul, T., Hang, L., Srivaranun, S., Likitlersuang, S., Jongvivatsakul, P., Yodsudjai, W., Thammarak, P. Digital twin-based structural health monitoring and measurements of dynamic characteristics in balanced cantilever bridge. Resilient Cities and Structures, 2025; 4: 48–66. doi:10.1016/j.rcns.2025.08.001.
  17. Spencer, B. F., Nagarajaiah, S. State of the art of structural control. Journal of Structural Engineering, 2003; 129: 845–856. doi:10.1061/(ASCE)0733-9445(2003)129:7(845).
  18. Zhong, C., Christopoulos, C. Self-centering seismic-resistant structures: Historical overview and state-of-the-art. Earthquake Spectra, 2022; 38: 1321–1356. doi:10.1177/87552930211057581.
  19. Pratap, M., Vesmawala, G. R. The state-of-the-art review on development of replaceable fuse components in resilient moment resisting frame. Structures, 2023; 56: 104888. doi:10.1016/j.istruc.2023.104888.
  20. Molina Hutt, C., Vahanvaty, T., Kourehpaz, P. An analytical framework to assess earthquake-induced downtime and model recovery of buildings. Earthquake Spectra, 2022; 38: 1283–1320. doi:10.1177/87552930211060856.
  21. Cook, D. T., Liel, A. B., Haselton, C. B., Koliou, M. A framework for operationalizing the assessment of post-earthquake functional recovery of buildings. Earthquake Spectra, 2022; 38: 1972–2007. doi:10.1177/87552930221081538.
  22. Kourehpaz, P., Molina Hutt, C., Zsarnóczay, A. Impact of parameter selection on seismic loss and recovery time estimates: A variance-based sensitivity analysis. Earthquake Spectra, 2025; 41: 1713–1737. doi:10.1177/87552930241307624.
  23. Mucedero, G., Yukselen, B., Couto, R., Calvi, G. M., Monteiro, R. Beyond structural safety: Downtime-based performance criteria as future design objectives for Italian buildings. Journal of Earthquake Engineering, 2026; 30: 1632–1657. doi:10.1080/13632469.2025.2605583.
  24. Forcellini, D., Ranjbar, F., Asgari, A., Bagheri, M., Yazdani, H. Seismic resilience assessment of pile groups against liquefaction-induced lateral spreading: Influence of ground inclination and pile spacing. Engineering Structures, 2026; 360: 122786. doi:10.1016/j.engstruct.2026.122786.
  25. Asadoullahtabar, S. R., Asgari, A., Mohammad Rezapour Tabari, M. Assessment, identifying, and presenting a plan for the stabilization of loessic soils exposed to scouring in the path of gas pipelines, case study: Maraveh-Tappeh city. Engineering Geology, 2024; 342: 107747. doi:10.1016/j.enggeo.2024.107747.
  26. Olechowski, A. L., Eppinger, S. D., Joglekar, N., Tomaschek, K. Technology readiness levels: Shortcomings and improvement opportunities. Systems Engineering, 2020; 23: 395–408. doi:10.1002/sys.21533.
  27. Daim, T. U., Rueda, G., Martin, H., Gerdsri, P. Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change, 2006; 73: 981–1012. doi:10.1016/j.techfore.2006.04.004.
  28. Popper, R. How are foresight methods selected? Foresight, 2008; 10: 62–89. doi:10.1108/14636680810918586.
  29. Coppoletta, F. N., Acuto, A., Corvello, V., Filice, L. Technology foresight: A taxonomy. Advances in Business and Management Research, 2026; 1: 100004. doi:10.1016/j.abmr.2026.100004.
  30. Rowe, G., Wright, G. The Delphi technique as a forecasting tool: Issues and analysis. International Journal of Forecasting, 1999; 15: 353–375. doi:10.1016/S0169-2070(99)00018-7.
  31. OECD Science, Technology and Industry Working Papers. Building capacity in technology horizon scanning: A guide for policymakers. Paris (FR): OECD; 2026. Report No.: 2026/06.
  32. Amer, M., Daim, T. U., Jetter, A. A review of scenario planning. Futures, 2013; 46: 23–40. doi:10.1016/j.futures.2012.10.003.
  33. Phaal, R., Farrukh, C. J. P., Probert, D. R. Technology roadmapping—A planning framework for evolution and revolution. Technological Forecasting and Social Change, 2004; 71: 5–26. doi:10.1016/S0040-1625(03)00072-6.
  34. Zadeh, L. A. Fuzzy sets. Information and Control, 1965; 8: 338–353. doi:10.1016/S0019-9958(65)90241-X.
  35. Keršuliene, V., Zavadskas, E. K., Turskis, Z. Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (Swara). Journal of Business Economics and Management, 2010; 11: 243–258. doi:10.3846/jbem.2010.12.
  36. Hwang, C.-L., Yoon, K. Multiple Attribute Decision Making. 1st ed. Heidelberg (DE): Springer Berlin; 1981. doi:10.1007/978-3-642-48318-9.
  37. Opricovic, S., Tzeng, G.-H. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 2004; 156: 445–455. doi:10.1016/S0377-2217(03)00020-1.
  38. Behzadian, M., Kazemzadeh, R. B., Albadvi, A., Aghdasi, M. PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 2010; 200: 198–215. doi:10.1016/j.ejor.2009.01.021.
  39. UN Trade and Development. Technology Foresight and Technology Assessment for Sustainable Development. 1st ed. New York (NY): United Nations Publications; 2025. doi:10.18356/9789211593297.
  40. Nkrumah, S. A. M., Filippova, O., Levy, D., Ying, F. Bridging the gap: A literature Review of post-earthquake building functional recovery through a user-informed lens. Journal of Real Estate Literature, 2026; 34: 1–30. doi:10.1080/09277544.2025.2529104.
  41. Bitarafan, M., Zolfani, S. H., Arefi, S. L., Zavadskas, E. K., Mahmoudzadeh, A. Evaluation of real-time intelligent sensors for structural health monitoring of bridges based on SWARA-WASPAS; a case in Iran. The Baltic Journal of Road and Bridge Engineering, 2014; 9: 333–340. doi:10.3846/bjrbe.2014.40.
  42. Ijadi Maghsoodi, A., Ijadi Maghsoodi, A., Poursoltan, P., Antucheviciene, J., Turskis, Z. Dam construction material selection by implementing the integrated SWARA—CODAS approach with target-based attributes. Archives of Civil and Mechanical Engineering, 2019; 19: 1194–1210. doi:10.1016/j.acme.2019.06.010.
  43. Khalesi, H., Balali, A., Valipour, A., Antucheviciene, J., Migilinskas, D., Zigmund, V. Application of hybrid SWARA–BIM in reducing reworks of building construction projects from the perspective of time. Sustainability, 2020; 12: 8927. doi:10.3390/su12218927.
  44. Alrasheedi, A. F., Mishra, A. R., Rani, P., Zavadskas, E. K., Cavallaro, F. Multicriteria group decision making approach based on an improved distance measure, the SWARA method and the WASPAS method. Granular Computing, 2023; 8: 1867–1885. doi:10.1007/s41066-023-00413-x.
آمار
تعداد مشاهده مقاله: 23


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب