SavedAdd your journal

Journals / Gazi University Journal of Science / 2025 / Volume: 38 Issue: 4

A Study on the Importance of Factors Effecting the Occupational Safety Performance

Cihangir Gümüştaş(BAHÇEŞEHİR ÜNİVERSİTESİ)0000-0002-0487-2282
Elif Haktanır Aktaş(BAHÇEŞEHİR ÜNİVERSİTESİ)0000-0002-3341-4360
Gül Tekin Temur(BAHÇEŞEHİR ÜNİVERSİTESİ)0000-0003-3853-0974
Ahmet Beşkese(BAHÇEŞEHİR ÜNİVERSİTESİ)0000-0003-4427-3986
Pages
—
Publication Date
2025-12-01
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings underscore the prominence of factors such as Workload Pressure, Management and Supervisor Commitment to Safety, Sanctions and Auditing, Number of Subcontractors, and Equipment Conditions in enhancing safety performance.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In contemporary workplaces, organizational safety is not just a regulatory obligation but a critical determinant of sustainable success.
📊
Key Findings & Data:Utilizing the Interval-Valued Picture Fuzzy Analytic Hierarchy Process (IVPF-AHP) method, this research aims to prioritize the most crucial factors influencing safety performance.
💡
Conclusion & Impact:The findings underscore the prominence of factors such as Workload Pressure, Management and Supervisor Commitment to Safety, Sanctions and Auditing, Number of Subcontractors, and Equipment Conditions in enhancing safety performance.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Interval-valued picture fuzzy sets · AHP · Occupational safety performance

Abstract

In contemporary workplaces, organizational safety is not just a regulatory obligation but a critical determinant of sustainable success. With the evolving technological advancements in industries, understanding the factors that influence occupational safety becomes paramount. This study examines the multifaceted structure of occupational safety criteria, recognizing its importance in ensuring not only the physical well-being of workers but also the organizational resilience. Utilizing the Interval-Valued Picture Fuzzy Analytic Hierarchy Process (IVPF-AHP) method, this research aims to prioritize the most crucial factors influencing safety performance. Through a comprehensive analysis of 20 sub-criteria under five main categories — Organization, Safety Climate, Regulatory Characteristics, Workplace Environment, and Individual Characteristics — the study reveals insights into the nuanced interplay of organizational, managerial, and individual factors that shape safety outcomes. The findings underscore the prominence of factors such as Workload Pressure, Management and Supervisor Commitment to Safety, Sanctions and Auditing, Number of Subcontractors, and Equipment Conditions in enhancing safety performance.

🔖

Cite This Article

Gümüştaş, C., Aktaş, E. H., Temur, G. T., Beşkese, A. (2025). A Study on the Importance of Factors Effecting the Occupational Safety Performance. Gazi University Journal of Science, Volume: 38 Issue: 4. https://doi.org/10.35378/gujs.1501298

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (132)

  1. Gao, Y., González, V.A. and Yiu, T.W., “Exploring the Relationship between Construction Workers’ Personality Traits and Safety Behavior”, J. Constr. Eng. Manag, 146: 04019111, (2020). DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001763
  2. Lee, W., Migliaccio, G.C., Lin, K.-Y. and Seto, E.Y.W., “Workforce development: understanding task-level job demands-resources, burnout, and performance in unskilled construction workers”, Saf. Sci, 123: 104577, (2020). DOI: https://doi.org/10.1016/j.ssci.2019.104577
  3. Karuppiah, K., Sankaranarayanan, B. and Ali, S.M., “A fuzzy ANP–DEMATEL model on faulty behavior risks: implications for improving safety in the workplace”, Int. J. Occup. Saf. Ergon, 28: 923–940, (2022). DOI: https://doi.org/10.1080/10803548.2020.1847486
  4. Altunkaynak, B., “A statistical study of occupational accidents in the manufacturing industry in Turkey”, Int. J. Ind. Ergon, 66: 101–109, (2018). DOI: https://doi.org/10.1016/j.ergon.2018.02.012
  5. European Agency for Safety and Health at Work, “Occupational safety and health in Europe - state and trends 2023”, (2023). COI: 20.500.12592/qhkb73
  6. Mutlu, N.G. and Altuntas, S., “Analyzing factors influencing the severity of occupational accidents in textile industry using decision tree algorithms”, Clust. Comput, 27: 787–825, (2024). DOI: https://doi.org/10.1007/s10586-022-03958-9
  7. T.C. Çalışma Ve Sosyal Güvenlik Bakanlığı Rehberlik ve Teftiş Başkanlığı, Y.Y., “2022 Yılı Yapı İşyerlerinde İş sağlığı ve Güvenliği Programlı Teftişi”, (2022).
  8. Fernández-Muñiz, B., Montes-Peón, J.M. and Vázquez-Ordás, C.J., “Safety leadership, risk management and safety performance in Spanish firms”, Saf. Sci, 70: 295–307, (2014). https://doi.org/10.1016/j.ssci.2014.07.010
  9. Hanvold, T.N., Kines, P., Nykänen, M., Thomée, S., Holte, K.A., Vuori, J., Wærsted, M. and Veiersted, K.B., “Occupational Safety and Health Among Young Workers in the Nordic Countries: A Systematic Literature Review”, Saf. Health Work, 10: 3–20, (2019). DOI: https://doi.org/10.1016/j.shaw.2018.12.003
  10. Chan, A.P.C. and Chan, A.P.L., “Key performance indicators for measuring construction success”, Benchmarking Int. J, 11: 203–221, (2004). DOI: https://doi.org/10.1108/14635770410532624
  11. Eskandari, D., Gharabagh, M.J., Barkhordari, A., Gharari, N., Panahi, D., Gholami, A. and Teimori-Boghsani, G., “Development of a scale for assessing the organization’s safety performance based fuzzy ANP”, J. Loss Prev. Process Ind, 69: 104342, (2021). DOI: https://doi.org/10.1016/j.jlp.2020.104342
  12. Sheehan, C., Donohue, R., Shea, T., Cooper, B. and Cieri, H.D., “Leading and lagging indicators of occupational health and safety: The moderating role of safety leadership”, Accid. Anal. Prev, 92: 130–138, (2016). DOI: https://doi.org/10.1016/j.aap.2016.03.018
  13. Ale, B., “More thinking about process safety indicators”, Saf. Sci, 47: 470–471, (2009). https://doi.org/10.1016/j.ssci.2008.07.012
  14. Beriha, G.S., Patnaik, B., Mahapatra, S.S. and Padhee, S., “Assessment of safety performance in Indian industries using fuzzy approach”, Expert Syst. Appl, 39: 3311–3323, (2012). DOI: https://doi.org/10.1016/j.eswa.2011.09.018
  15. Abu-Khader, M.M., “Impact of Human Behaviour on Process Safety Management in Developing Countries”, Process Saf. Environ. Prot, 82: 431–437, (2004). DOI: https://doi.org/10.1205/psep.82.6.431.53206
  16. Anderson, M., “Behavioural Safety and Major Accident Hazards”, Process Saf. Environ. Prot, 83: 109–116, (2005). DOI: https://doi.org/10.1205/psep.04230
  17. Chen, Y., Yu, X. and Yang, Z., “A fuzzy decision support system for risk prioritization in fine kinney-based occupational risk analysis”, J. Soft Comput. Decis. Anal, 3: 1–17, (2025). DOI: https://doi.org/10.31181/jscda31202545
  18. Aksüt, G., Eren, T. and Alakaş, H.M., “Using wearable technological devices to improve workplace health and safety: An assessment on a sector base with multi-criteria decision-making methods”, Ain Shams Eng. J, 15: 102423, (2024). DOI: https://doi.org/10.1016/j.asej.2023.102423
  19. Ayvaz, B., Tatar, V., Sağır, Z. and Pamucar, D., “An Integrated fine-kinney risk assessment model utilizing fermatean fuzzy AHP-WASPAS for occupational hazards in the aquaculture sector”, Process Saf. Environ. Prot, 186: 232–251, (2024). DOI: https://doi.org/10.1016/j.psep.2024.04.025
  20. Ayyildiz, E., Erdogan, M. and Gul, M., “A comprehensive risk assessment framework for occupational health and safety in pharmaceutical warehouses using pythagorean fuzzy bayesian networks”, Eng. Appl. Artif. Intell, 135: 108763, (2024). DOI: https://doi.org/10.1016/j.engappai.2024.108763
  21. Kursunoglu, N., “Fuzzy multi-criteria decision-making framework for controlling methane explosions in coal mines”, Environ. Sci. Pollut. Res, 31: 9045–9061, (2024). DOI: https://doi.org/10.1007/s11356-023-31782-0
  22. Serrato, R.B., “A novel global probabilistic fuzzy system for occupational risk assessment (GPFSORA)”, Ing. Investig, 42: e104181, (2024). DOI: https://doi.org/10.15446/ing.investig.104181
  23. Sherin, S. and Raza, S., “risk analysis and prioritization with AHP and fuzzy TOPSIS techniques in surface mines of Pakistan”, J. Min. Environ, 15: 463–479, (2024). DOI: https://doi.org/10.22044/jme.2023.13687.2533
  24. Ahmed, T., Hoque, A.S.M., Karmaker, C.L. and Ahmed, S., “Integrated approach for occupational health and safety (OHS) risk Assessment: An Empirical (Case) study in Small enterprises”, Saf. Sci, 164: 106143, (2023). DOI: https://doi.org/10.1016/j.ssci.2023.106143
  25. Badida, P., Janakiraman, S. and Jayaprakash, J., “Occupational health and safety risk assessment using a fuzzy multi-criteria approach in a hospital in Chennai, India”, Int. J. Occup. Saf. Ergon, 29: 1047–1056, (2023). DOI: https://doi.org/10.1080/10803548.2022.2109323
  26. Koulinas, G.K., Demesouka, O.E., Marhavilas, P.K., Orfanos, N.I. and Koulouriotis, D.E., “Multicriteria Health and Safety Risk Assessments in Highway Construction Projects”, Sustainability, 15: 9241, (2023). DOI: https://doi.org/10.3390/su15129241
  27. Küçükarslan, A.B., Köksal, M. and Ekmekci, I., “A Model Proposal for Measuring Performance in Occupational Health and Safety in Forest Fires”, Sustainability, 15: 14729, (2023). DOI: https://doi.org/10.3390/su152014729
  28. Chen, W., Yang, B. and Liu, Y., “An integrated QFD and FMEA approach to identify risky components of products”, Adv. Eng. Inform, 54: 101808, (2022). DOI: https://doi.org/10.1016/j.aei.2022.101808
  29. Ye, W., Gao, C., Liu, Z., Wang, Q. and Su, W., “A Fuzzy-AHP-based variable weight safety evaluation model for expansive soil slope”, Nat. Hazards, 119: 559–581, (2023). DOI: https://doi.org/10.1007/s11069-023-06130-7
  30. Marhavilas, P.K., Filippidis, M., Koulinas, G.K. and Koulouriotis, D.E., “Safety-assessment by hybridizing the MCDM/AHP & HAZOP-DMRA techniques through safety’s level colored maps: Implementation in a petrochemical industry”, Alex. Eng. J, 61: 6959–6977, (2022). DOI: https://doi.org/10.1016/j.aej.2021.12.040
  31. Omidi, L., Salehi, V., Zakerian, S.A. and Nasl Saraji, J., “Assessing the influence of safety climate-related factors on safety performance using an Integrated Entropy-TOPSIS Approach”, J. Ind. Prod. Eng, 39: 73–82, (2022). DOI: https://doi.org/10.1080/21681015.2021.1958937
  32. Unver, S. and Ergenc, I., “Safety risk identification and prioritize of forest logging activities using analytic hierarchy process (AHP)”, Alex. Eng. J, 60: 1591–1599, (2021). DOI: https://doi.org/10.1016/j.aej.2020.11.012
  33. 33] Ferrari, G.N., Leal, G.C.L., Galdamez, E.V.C. and Souza, R.C.T.D., “Prioritization of occupational health and safety indicators using the Fuzzy-AHP method”, Production, 30: e20200054, (2020). DOI: https://doi.org/10.1590/0103-6513.20200054
  34. Zytoon, M.A., “A Decision Support Model for Prioritization of Regulated Safety Inspections Using Integrated Delphi, AHP and Double-Hierarchical TOPSIS Approach”, IEEE Access, 8: 83444–83464, (2020). DOI: https://doi.org/10.1109/ACCESS.2020.2991179
  35. Akbar, S. and Ahsan, K., “Workplace safety compliance implementation challenges in apparel supplier firms”, J. Clean. Prod, 232: 462–473, (2019). DOI: https://doi.org/10.1016/j.jclepro.2019.05.368
  36. Gul, M., Ak, M.F. and Guneri, A.F., “Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry”, J. Safety Res, 69: 135–153, (2019). DOI: https://doi.org/10.1016/j.jsr.2019.03.005
  37. Dağdeviren, M. and Yüksel, İ., “Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management”, Inf. Sci, 178: 1717–1733, (2008). DOI: https://doi.org/10.1016/j.ins.2007.10.016
  38. Ilbahar, E., Karaşan, A., Cebi, S. and Kahraman, C., “A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system”, Saf. Sci, 103: 124–136, (2018). DOI: https://doi.org/10.1016/j.ssci.2017.10.025
  39. Raviv, G., Fishbain, B. and Shapira, A., “Analyzing risk factors in crane-related near-miss and accident reports”, Saf. Sci, 91: 192–205, (2017a). DOI: https://doi.org/10.1016/j.ssci.2016.08.022
  40. Raviv, G., Shapira, A. and Fishbain, B., “AHP-based analysis of the risk potential of safety incidents: Case study of cranes in the construction industry”, Saf. Sci, 91: 298–309, (2017b). DOI: https://doi.org/10.1016/j.ssci.2016.08.027
  41. Basahel, A. and Taylan, O., “Using fuzzy ahp and fuzzy topsis approaches for assessing safety conditions at worksites in construction industry”, Int. J. Saf. Secur. Eng, 6: 728–745, (2016). DOI: https://doi.org/10.2495/SAFE-V6-N4-728-745
  42. Gnoni, M.G., Duraccio, V. and Iavagnilio, R., “A fuzzy AHP-based approach for assessing the faulty behaviour risk at workplace”, Int. J. Bus. Syst. Res, 10: 291, (2016). DOI: https://doi.org/10.1504/IJBSR.2016.075759
  43. Enchill, E. and Nyamah, E.Y., “AHP Application In Occupational Safety Analysis In An Industrial Gas Manufacturing Company (Ghana)”, Int. J. Manag. Econ. 1, (2015). DOI: https://doi.org/10.1016/j.ssci.2014.11.018
  44. Podgórski, D., “Measuring operational performance of OSH management system – A demonstration of AHP-based selection of leading key performance indicators”, Saf. Sci, 73: 146–166, (2015). DOI: https://doi.org/10.1016/j.ssci.2014.11.018
  45. Aminbakhsh, S., Gunduz, M. and Sonmez, R., “Safety risk assessment using analytic hierarchy process (AHP) during planning and budgeting of construction projects”, J. Safety Res, 46: 99–105, (2013). DOI: https://doi.org/10.1016/j.jsr.2013.05.003
  46. Zheng, G., Zhu, N., Tian, Z., Chen, Y. and Sun, B., “Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments”, Saf. Sci, 50: 228–239, (2012). DOI: https://doi.org/10.1016/j.ssci.2011.08.042
  47. Gürcanli, G.E. and Müngen, U., “An occupational safety risk analysis method at construction sites using fuzzy sets”, Int. J. Ind. Ergon, 39: 371–387, (2009). DOI: https://doi.org/10.1016/j.ergon.2008.10.006
  48. Dağdeviren, M., Yüksel, İ. and Kurt, M., “A fuzzy analytic network process (ANP) model to identify faulty behavior risk (FBR) in work system”, Saf. Sci, 46: 771–783, (2008). DOI: https://doi.org/10.1016/j.ssci.2007.02.002
  49. Zohar, D., “Safety climate: Conceptual and measurement issues”, in: Quick, J. C., Tetrick, L. E. (Eds.), Handbook of Occupational Health Psychology. American Psychological Association, Washington, pp. 123–142, (2003). DOI: https://doi.org/10.1037/10474-006
  50. Clarke, S., “The relationship between safety climate and safety performance: A meta-analytic review”, J. Occup. Health Psychol, 11: 315–327, (2006). DOI:. https://doi.org/10.1037/1076-8998.11.4.315
  51. Oah, S., Na, R. and Moon, K., “The Influence of Safety Climate, Safety Leadership, Workload, and Accident Experiences on Risk Perception: A Study of Korean Manufacturing Workers”, Saf. Health Work, 9: 427–433, (2018). DOI: https://doi.org/10.1016/j.shaw.2018.01.008
  52. Kouabenan, D.R., Ngueutsa, R. and Mbaye, S., “Safety climate, perceived risk, and involvement in safety management”, Saf. Sci, 77: 72–79, (2015). DOI: https://doi.org/10.1016/j.ssci.2015.03.009
  53. Zohar, D. and Luria, G., “A Multilevel Model of Safety Climate: Cross-Level Relationships Between Organization and Group-Level Climates”, J. Appl. Psychol, 90: 616–628, (2005). DOI: https://doi.org/10.1037/0021-9010.90.4.616
  54. Feng, Y., “Effect of safety investments on safety performance of building projects”, Saf. Sci, 59: 28–45, (2013). DOI: https://doi.org/10.1016/j.ssci.2013.04.004
  55. Fang, D., Jiang, Z., Zhang, M. and Wang, H., “An experimental method to study the effect of fatigue on construction workers’ safety performance”, Saf. Sci, 73: 80–91, (2015). DOI: https://doi.org/10.1016/j.ssci.2014.11.019
  56. Pinto, A., Nunes, I.L. and Ribeiro, R.A., “Occupational risk assessment in construction industry – Overview and reflection”, Saf. Sci, 49: 616–624, (2011). DOI: https://doi.org/10.1016/j.ssci.2011.01.003
  57. Huang, Y.-H., Ho, M., Smith, G.S. and Chen, P.Y., “Safety climate and self-reported injury: Assessing the mediating role of employee safety control”, Accid. Anal. Prev, 38: 425–433, (2006). DOI: https://doi.org/10.1016/j.aap.2005.07.002
  58. Fleming, “Effective Supervisory Safety Leadership Behaviors in the Offshore Oil and Gas Industry”, HSE Books, (2001).
  59. Xia, N., Xie, Q., Griffin, M.A., Ye, G. and Yuan, J., “Antecedents of safety behavior in construction: A literature review and an integrated conceptual framework”, Accid. Anal. Prev, 148: 105834, (2020). DOI: https://doi.org/10.1016/j.aap.2020.105834
  60. Mohammadi, A., Tavakolan, M. and Khosravi, Y., “Factors influencing safety performance on construction projects: A review”, Saf. Sci, 109: 382–397, (2018). DOI: https://doi.org/10.1016/j.ssci.2018.06.017
  61. Niskanen, T., “Safety climate in the road administration”, Saf. Sci, 17: 237–255, (1994). DOI: https://doi.org/10.1016/0925-7535(94)90026-4
  62. Meliá, J.L., Mearns, K., Silva, S.A. and Lima, M.L., “Safety climate responses and the perceived risk of accidents in the construction industry”, Saf. Sci, 46: 949–958, (2008). DOI: https://doi.org/10.1016/j.ssci.2007.11.004
  63. Hayes, B.E., Perander, J., Smecko, T. and Trask, J., “Measuring Perceptions of Workplace Safety: Development and Validation of the Work Safety Scale”, J. Safety Res. 29, (1998). DOI: https://doi.org/10.1016/S0022-4375(98)00011-5
  64. Kalteh, H.O., Mortazavi, S.B., Mohammadi, E. and Salesi, M., “The relationship between safety culture and safety climate and safety performance: a systematic review”, Int. J. Occup. Saf. Ergon, 27: 206–216, (2021). DOI: https://doi.org/10.1080/10803548.2018.1556976
  65. Seo, H.C., Lee, Y.S., Kim, J.J. and Jee, N.Y., “Analyzing safety behaviors of temporary construction workers using structural equation modeling”, Saf. Sci, 77: 160–168, (2015). DOI: https://doi.org/10.1016/j.ssci.2015.03.010
  66. Kao, K.Y., Spitzmueller, C., Cigularov, K. and Wu, H., “Linking insomnia to workplace injuries: A moderated mediation model of supervisor safety priority and safety behavior”, J. Occup. Health Psychol, 21: 91–104, (2016). DOI: https://doi.org/10.1037/a0039144
  67. Xiang, Q., Ye, G., Liu, Y., Miang Goh, Y., Wang, D. and He, T., “Cognitive mechanism of construction workers’ unsafe behavior: A systematic review”, Saf. Sci, 159: 106037, (2023). DOI: https://doi.org/10.1016/j.ssci.2022.106037
  68. Johnson, R.C., Eatough, E.M., Chang, C.-H. (Daisy)., Hammer, L.B. and Truxilllo, D., “Home is where the mind is: Family interference with work and safety performance in two high risk industries”, J. Vocat. Behav, 110: 117–130, (2019). DOI: https://doi.org/10.1016/j.jvb.2018.10.012
  69. Liao, P.-C., Liu, B., Wang, Y., Wang, X. and Ganbat, T., “Work paradigm as a moderator between cognitive factors and behaviors – A comparison of mechanical and rebar workers”, KSCE J. Civ. Eng, 21: 2514–2525, (2017). DOI: https://doi.org/10.1007/s12205-017-0091-2
  70. Barr, G.C., Kane, K.E., Barraco, R.D., Rayburg, T., Demers, L., Kraus, C.K., Greenberg, M.R., Rupp, V.A., Hamilton, K.M. and Kane, B.G., “Gender Differences in Perceptions and Self-reported Driving Behaviors Among Teenagers”, J. Emerg. Med. 48, 366-370. e3, (2015). DOI: https://doi.org/10.1016/j.jemermed.2014.09.055
  71. Han, S., Saba, F., Lee, S., Mohamed, Y. and Peña-Mora, F., “Toward an understanding of the impact of production pressure on safety performance in construction operations”, Accid. Anal. Prev, 68: 106–116, (2014). DOI: https://doi.org/10.1016/j.aap.2013.10.007
  72. Cox, S.J. and Cheyne, A.J.T., “Assessing safety culture in offshore environments”, Saf. Sci, (2000). DOI: https://doi.org/10.1016/S0925-7535(00)00009-6
  73. Minchin, R.E., Glagola, C.R., Guo, K. and Languell, J.L., “Case for drug testing of construction workers 22”, (2006). DOI: https://doi.org/10.1061/(ASCE)0742-597X(2006)22:1(43)
  74. Swuste, P., Frijters, A. and Guldenmund, F., “Is it possible to influence safety in the building sector? Saf”, Sci, 50: 1333–1343, (2012). DOI: https://doi.org/10.1016/j.ssci.2011.12.036
  75. Zutshi, A. and Sohal, A.S., “A framework for environmental management system adoption and maintenance: an Australian perspective”, Manag. Environ. Qual. Int. J, 16: 464–475, (2005). DOI: https://doi.org/10.1108/14777830510614330
  76. Da Silva, S.L.C. and Amaral, F.G., “Critical factors of success and barriers to the implementation of occupational health and safety management systems: A systematic review of literature”, Saf. Sci, 117: 123–132, (2019). DOI: https://doi.org/10.1016/j.ssci.2019.03.026
  77. Abad, J., Lafuente, E. and Vilajosana, J., “An assessment of the OHSAS 18001 certification process: Objective drivers and consequences on safety performance and labour productivity”, Saf. Sci, 60: 47–56, (2013). DOI: https://doi.org/10.1016/j.ssci.2013.06.011
  78. Kahya, E., “The effects of job characteristics and working conditions on job performance”, Int. J. Ind. Ergon, 37: 515–523, (2007). DOI: https://doi.org/10.1016/j.ergon.2007.02.006
  79. Nahrgang, J.D., Morgeson, F.P. and Hofmann, D.A., “Safety at work: A meta-analytic investigation of the link between job demands, job resources, burnout, engagement, and safety outcomes”, J. Appl. Psychol, 96: 71–94, (2011). DOI: https://doi.org/10.1037/a0021484
  80. Frazier, C.B., Ludwig, T.D., Whitaker, B. and Roberts, D.S., “A hierarchical factor analysis of a safety culture survey”, J. Safety Res, 45: 15–28, (2013). DOI: https://doi.org/10.1016/j.jsr.2012.10.015
  81. Chen, Z.-S., Liu, X.-L., Rodríguez, R.M., Wang, X.-J., Chin, K.-S., Tsui, K.-L. and Martínez, L., “Identifying and prioritizing factors affecting in-cabin passenger comfort on high-speed rail in China: A fuzzy-based linguistic approach”, Appl. Soft Comput, 95: 106558, (2020). DOI: https://doi.org/10.1016/j.asoc.2020.106558
  82. Mitropoulos, P., Cupido, G. and Namboodiri, M., “Cognitive approach to construction safety: Task demand-capability model”, J. Manag. Eng. 22, (2006). DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000060
  83. Park, M. and Peña‐Mora, F., “Dynamic change management for construction: introducing the change cycle into model‐based project management”, Syst. Dyn. Rev, 19: 213–242, (2003). DOI: https://doi.org/10.1002/sdr.273
  84. Khosravi, Y., Asilian-Mahabadi, H., Hajizadeh, E., Hassanzadeh-Rangi, N., Bastani, H. and Behzadan, A.H., “Factors Influencing Unsafe Behaviors and Accidents on Construction Sites: A Review”, Int. J. Occup. Saf. Ergon, 20: 111–125, (2014). DOI: https://doi.org/10.1080/10803548.2014.11077023
  85. Mohseni, P.H., Farshad, A.A., Mirkazemi, R. and Orak, R.J., “Assessment of the living and workplace health and safety conditions of site-resident construction workers in Tehran, Iran”, Int. J. Occup. Saf. Ergon, 21: 568–573, (2015). DOI: https://doi.org/10.1080/10803548.2015.1096061
  86. Goh, Y.M., Love, P.E.D., Stagbouer, G. and Annesley, C., “Dynamics of safety performance and culture: A group model building approach”, Accid. Anal. Prev, 48: 118–125, (2012). DOI: https://doi.org/10.1016/j.aap.2011.05.010
  87. Votano, S. and Sunindijo, R.Y., “Client Safety Roles in Small and Medium Construction Projects in Australia”, J. Constr. Eng. Manag, 140: 04014045, (2014). DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000899
  88. Guo, B.H.W., Yiu, T.W. and González, V.A., “Predicting safety behavior in the construction industry: Development and test of an integrative model”, Saf. Sci, 84: 1–11, (2016). DOI: https://doi.org/10.1016/j.ssci.2015.11.020
  89. Büyüközkan, G. and Ruan, D., “Evaluation of software development projects using a fuzzy multi-criteria decision approach”, Math. Comput. Simul, 77: 464–475, (2008). DOI: https://doi.org/10.1016/j.matcom.2007.11.015
  90. Beskese, A., Corum, A. and Anolay, M., “A model proposal for ERP system selection in. automotive industry”, Inf. Syst. Technol, 26: 317–342, (2019).
  91. Beskese, A., Demir, H.H., Ozcan, H.K. and Okten, H.E., “Landfill site selection using fuzzy ahp and fuzzy TOPSIS: A Case Study for Istanbul”, Environ. Earth Sci, 73: 3513–3521, (2015). DOI: https://doi.org/10.1007/s12665-014-3635-5
  92. Torfi, F., Farahani, R.Z. and Rezapour, S., “Fuzzy AHP to determine the relative weights of evaluation criteria and fuzzy TOPSIS to rank the alternatives”, Appl. Soft Comput, 10: 520–528, (2010). DOI: http://dx.doi.org/10.1016/j.asoc.2009.08.021
  93. Saaty, T.L. and Özdemir, M.S., “How many judges should there be in a group? Ann”, Data Sci, 1: 359–368, (2014). DOI: https://doi.org/10.1007/s40745-014-0026-4
  94. Ziemba, P., Piwowarski, M. and Nermend, K., “Remote work in post-pandemic reality: multi-criteria evaluation of teleconferencing software”, Sustainability, 15: 9919, (2023). DOI: https://doi.org/10.3390/su15139919
  95. Shi, X., Kosari, S. and Khan, W.A., “Some novel concepts of interval-valued picture fuzzy graphs with applications toward the transmission control protocol and social networks”, Front. Phys, 11: 1260785, (2023). DOI: https://doi.org/10.3389/fphy.2023.1260785
  96. Azeem, M., Ali, J. and Ali, J., “Interval-valued picture fuzzy decision-making framework with partitioned maclaurin symmetric mean aggregation operators”, Sci. Rep, 14: 23155, (2024). DOI: https://doi.org/10.1038/s41598-024-72726-z
  97. Cuong, B.C., “Picture fuzzy sets”, J. Comput. Sci. Cybern, 30: 409-420, (2014). DOI: https://doi.org/10.15625/1813-9663/30/4/5032
  98. Khalil, A.M., Li, S.-G., Garg, H., Li, H. and Ma, S., “New Operations on Interval-Valued Picture Fuzzy Set, Interval-Valued Picture Fuzzy Soft Set and Their Applications”, IEEE Access, 7: 51236–51253, (2019). https://doi.org/10.1109/ACCESS.2019.2910844
  99. Saaty, T.L., “How to make a decision: the analytic hierarchy process”, Eur. J. Oper. Res, 48: 9–26, (1990). DOI: https://doi.org/10.1016/0377-2217(90)90057-I
  100. Saaty, T.L., Fundamentals of the Analytic Hierarchy Process, in: Schmoldt, D, L., Kangas, J., Mendoza, G. A., Pesonen, M. (Eds.), The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making, Managing Forest Ecosystems. Springer Netherlands, Dordrecht, pp. 15–35, (2001). DOI: https://doi.org/10.1007/978-94-015-9799-9_2
  101. Acar, C., Beskese, A. and Temur, G.T., “Comparative fuel cell sustainability assessment with a novel approach”, Int. J. Hydrog. Energy, 47: 575–594, (2022). DOI: https://doi.org/10.1016/j.ijhydene.2021.10.034
  102. Erdoğan, M. and Kaya, İ., “A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey”, Appl. Soft Comput, 39: 84–93, (2016). DOI: https://doi.org/10.1016/j.asoc.2015.11.013
  103. Yildiz, D., Temur, G.T., Beskese, A. and Bozbura, F.T., “Evaluation of positive employee experien ce using hesitant fuzzy analytic hierarchy process”, J. Intell. Fuzzy Syst, 38: 1043–1058, (2020). DOI: https://doi.org/10.3233/JIFS-179467
  104. Abdullah, L. and Goh, P., “Decision making method based on Pythagorean fuzzy sets and its application to solid waste management”, Complex & intelligent systems, 5(2): 185-198, (2019). DOI: https://doi.org/10.1007/s40747-019-0100-9
  105. Gündoğdu, F. K., Duleba, S., Moslem, S. and Aydın, S., “Evaluating public transport service quality using picture fuzzy analytic hierarchy process and linear assignment model”, Applied Soft Computing, 100: 106920, (2021). DOI: https://doi.org/10.1016/J.ASOC.2020.106920
  106. Wan Mohd, W.R., Abdullah, L., Yusoff, B., Taib, C.M.I.C.1, and Merigo, J.M., “An integrated MCDM model based on Pythagorean fuzzy sets for green supplier development program”, Malaysian Journal of Mathematical Sciences, 13(S): 23–37, (2019).
  107. Saaty, T.L., “The analytic hierarchy process-what it is and how it is used”, Math. Model. 9, (1987). DOI: http://dx.doi.org/10.1016/0270-0255(87)90473-8
  108. Masmali, I., Hassan, R., Shuaib, U., Razaq, A., Razzaque, A. and Alhamzi, G., “Stock Reordering Decision Making under Interval Valued Picture Fuzzy Knowledge”, Symmetry, 15: 898, (2023). DOI: https://doi.org/10.3390/sym15040898
  109. Naeem, M., Qiyas, M. and Abdullah, S., “An Approach of Interval-Valued Picture Fuzzy Uncertain Linguistic Aggregation Operator and Their Application on Supplier Selection Decision-Making in Logistics Service Value Concretion”, Math. Probl. Eng, 2021: 1–19, (2021). DOI: https://doi.org/10.1155/2021/8873230
  110. Lingard, H., Cooke, T. and Blismas, N., “Do Perceptions of Supervisors’ Safety Responses Mediate the Relationship between Perceptions of the Organizational Safety Climate and Incident Rates in the Construction Supply Chain? J”, Constr. Eng. Manag, 138: 234–241, (2012). DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000372
  111. Molenaar, K.R., Park, J.I. and Washington, S., “Framework for Measuring Corporate Safety Culture and Its Impact on Construction Safety Performance”, J. Constr. Eng. Manag, 135: 488–496, (2009). DOI: https://doi.org/10.1061/(ASCE)0733-9364(2009)135:6(488)
  112. Gümüştaş, C. and Küskü, F., “Dynamics of Organizational Distrust: An Exploratory Study in Workplace Safety”, Saf. Sci, 134: 105032, (2021). DOI: https://doi.org/10.1016/j.ssci.2020.105032
  113. Leung, M.Y., Liang, Q. and Olomolaiye, P., “Impact of job stressors and stress on the safety behavior and accidents of construction workers”, J. Manag. Eng. 32, (2016). DOI: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000373
  114. Mohamed, S., Ali, T.H. and Tam, W.Y.V., “National culture and safe work behaviour of construction workers in Pakistan”, Saf. Sci, 47: 29–35, (2009). DOI: https://doi.org/10.1016/j.ssci.2008.01.003
  115. Sun, X., Chong, H.-Y., Liao, P.-C., Fang, D. and Wang, Y., “A System Dynamics Model of Prevention through Design towards Eliminating Human Error”, KSCE J. Civ. Eng, 23: 1923–1938, (2019). DOI: https://doi.org/10.1007/s12205-019-0845-0
  116. Pybus, R., Safety Management: Strategy and Practice, Butterworth-Heinemann, (1996).
  117. Arcury, T.A., Summers, P., Carrillo, L., Grzywacz, J.G., Quandt, S.A. and Mills, T.H., “Occupational safety beliefs among Latino residential roofing workers”, Am. J. Ind. Med, 57: 718–725, (2014). DOI: https://doi.org/10.1002/ajim.222
  118. Stege, T.A.M., Bolte, J.F.B., Claassen, L. and Timmermans, D.R.M., “Particulate matter exposure in roadwork companies: A mental models study on work safety”, Saf. Sci, 120: 137–145, (2019). DOI: https://doi.org/10.1016/j.ssci.2019.06.043
  119. Ju, D., Qin, X., Xu, M. and DiRenzo, M.S., “Boundary conditions of the emotional exhaustion-unsafe behavior link: The dark side of group norms and personal control”, Asia Pac. J. Manag, 33: 113–140, (2016). DOI: https://doi.org/10.1007/s10490-015-9455-7
  120. Patel, D.A. and Jha, K.N., “Neural Network Approach for Safety Climate Prediction”, J. Manag. Eng, 31: 05014027, (2015). DOI: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000348
  121. Choudhry, R.M. and Fang, D., “Why operatives engage in unsafe work behavior: Investigating factors on construction sites”, Saf. Sci, 46: 566–584, (2008). DOI: https://doi.org/10.1016/j.ssci.2007.06.027
  122. Hon, C.K.H., Chan, A.P.C. and Wong, F.K.W., “An analysis for the causes of accidents of repair, maintenance, alteration and addition works in Hong Kong”, Saf. Sci, 48: 894–901, (2010). DOI: https://doi.org/10.1016/j.ssci.2010.03.013
  123. Jitwasinkul, B. and Hadikusumo, B.H.W., “Identification of Important Organisational Factors Influencing Safety Work Behaviours in Construction Projects”, J. Civ. Eng. Manag, 17: 520–528, (2011). DOI: https://doi.org/10.3846/13923730.2011.604538
  124. Manzey, D. and Marold, J., “Occupational accidents and safety: The challenge of globalization 47, 723–726”, (2009). DOI: https://doi.org/10.1016/j.ssci.2008.01.013
  125. Hallowell, M.R., Hinze, J.W., Baud, K.C. and Wehle, A., “Proactive Construction Safety Control: Measuring, Monitoring, and Responding to Safety Leading Indicators”, J. Constr. Eng. Manag, 139: 04013010, (2013). DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000730
  126. Stoilkovska, B.B., Žileska Pančovska, V. and Mijoski, G., “Relationship of safety climate perceptions and job satisfaction among employees in the construction industry: the moderating role of age”, Int. J. Occup. Saf. Ergon, 21: 440–447, (2015). DOI: https://doi.org/10.1080/10803548.2015.1096059
  127. Feng, Y., Teo, E.A.L., Ling, F.Y.Y. and Low, S.P., “Exploring the interactive effects of safety investments, safety culture and project hazard on safety performance: An empirical analysis”, Int. J. Proj. Manag, 32: 932–943, (2014). DOI: https://doi.org/10.1016/j.ijproman.2013.10.016
  128. Cheng, C.W., Leu, S.S., Lin, C.C. and Fan, C., “Characteristic analysis of occupational accidents at small construction enterprises”, Saf. Sci, 48: 698–707, (2010). DOI: https://doi.org/10.1016/j.ssci.2010.02.001
  129. Kang, K. and Ryu, H., “Predicting types of occupational accidents at construction sites in Korea using random forest model”, Saf. Sci, 120: 226–236, (2019). DOI: https://doi.org/10.1016/j.ssci.2019.06.034
  130. Zohar, D., “Safety climate: Conceptual and measurement issues”, in: Quick, J. C., Tetrick, L. E. (Eds.), Handbook of Occupational Health Psychology. American Psychological Association, Washington, pp. 123–142, (2003). DOI: https://doi.org/10.1037/10474-006
  131. Clarke, S., “The relationship between safety climate and safety performance: A meta-analytic review”, J. Occup. Health Psychol, 11: 315–327, (2006). DOI:. https://doi.org/10.1037/1076-8998.11.4.315
  132. Beskese, A., Corum, A. and Anolay, M., “A model proposal for ERP system selection in. automotive industry”, Inf. Syst. Technol, 26: 317–342, (2019).