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Çok Kriterli Karar Verme Yöntemleri Kullanılarak Üretim Sektörü Çalışanlarının İş Güvenliği Bilgi Düzeylerinin Konu Bazlı Değerlendirilmesi

Year 2026, Volume: 38 Issue: 1, 181 - 198, 20.03.2026
https://doi.org/10.7240/jeps.1811924
https://izlik.org/JA85ZK89BC

Abstract

İş güvenliği eğitimleri çalışanların kazalardan ve mesleki hastalıklardan korunmasında önemli bir yere sahiptir. eğitimlerin etkinliği ve içeriği de neticeleri etkilemektedir. Bu bakımdan çalışanların ihtiyaç duydukları eğitim konularının belirlenmesi önem arz etmektedir. Bu çalışmada iş güvenliği eğitimlerinde ihtiyaç duyulan konuların belirlenebilmesi için imalat sektörü çalışanlarının bilgi düzeyleri otuz sorudan oluşan bir test kullanılarak ölçülmüştür. Elde edilen veriler çok kriterli karar verme metodları ile analiz edilmiştir. Çalışmanın amacı imalat sektörü çalışanlarının iş güvenliği açısından bilgi eksikliği bulunan konuları saptamaktır. Sonuçlar imalat sektörü çalışanlarının; en çok kişisel koruyucu donanımlar konusunda bilgi eksikliği olduğunu göstermiştir. Ardından çalışma mevzuatı, güvenlik kültürü, yüksekte çalışma, kaldırma ekipmanları, acil durumlar ve isg uyarı işaretleri gelmektedir.

References

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  • Eyrenci, Ö., Taşkent, S., & Ulucan, D. (2019). Bireysel iş hukuku (9. Baskı). Beta.
  • Süzek, S. (1985). İş güvenliği hukuku. Ankara.
  • Çalışma ve Sosyal Güvenlik Bakanlığı. (2013, 15 Mayıs). Çalışanların iş sağlığı ve güvenliği eğitimlerinin usul ve esasları hakkında yönetmelik (Sayı: 28648). Resmî Gazete. https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=18371&MevzuatTur=7&MevzuatTertip=5 (October 2024)
  • Gül, M. (2018). A review of occupational health and safety risk assessment approaches based on multi-criteria decision-making methods and their fuzzy versions. Human and Ecological Risk Assessment: An International Journal, 24(1), 1–38.
  • Jasiulewicz-Kaczmarek, M., Antosz, K., Wyczółkowski, R., & Sławińska, M. (2022). Integrated approach for safety culture factor evaluation from a sustainability perspective. International Journal of Environmental Research and Public Health, 19(19), 11869.
  • Demir, G., Bouraima, M. B., Badi, I., Stević, Ž., & Das, D. K. (2025). Identification of industrial occupational safety risks and selection of optimum intervention strategies: Fuzzy MCDM approach. Mathematics, 13(2), 301.
  • Cerev, G., & Yıldırım, S. (2018). Çalışanların kişisel özelliklerinin iş kazası ve meslek hastalıklarına etkisi üzerine bir inceleme. Fırat Üniversitesi Uluslararası İktisadi ve İdari Bilimler Dergisi, 2(1), 53–72.
  • Robson, L. S., Stephenson, C. M., Schulte, P. A., Amick, B. C., Irvin, E. L., Eggerth, D. E., Chan, S., Bielecky, A. R., Wang, A. M., Heidotting, T. L., & Peters, R. H. (2012). A systematic review of the effectiveness of occupational health and safety training. Scandinavian Journal of Work, Environment & Health, 38(1), 193–208.
  • Burke, M. J., Sarpy, S. A., Smith-Crowe, K., Chan-Serafin, S., Salvador, R. O., & Islam, G. (2006). Relative effectiveness of worker safety and health training methods. American Journal of Public Health, 96(2), 204–207.
  • Türkiye İş Kurumu. (2024). İŞGÜCÜ PİYASASI ARAŞTIRMASI ANKARA İLİ 2023 YILI SONUÇ RAPORU. https://media.iskur.gov.tr/88084/ankara.pdf (October 2024)
  • Tekin, H. (2007). Eğitimde ölçme ve değerlendirme (19. baskı). Yargı Yayınevi.
  • Dimitrov, D. M. (2016). An approach to scoring and equating tests with binary items: Piloting with large-scale assessments. IEEE Transactions on Education, 59(3), 179–185.
  • Tavşancıl, E. (2020). Tutumların ölçülmesi ve SPSS ile veri analizi (6. baskı). Nobel Yayıncılık.
  • Özbek, H., & Keskin, S. (2007). Standart sapma mı yoksa standart hata mı? Van Tıp Dergisi, 14(2), 64–67.
  • Tekin, H. (2015). Eğitimde ölçme ve değerlendirme. Yargı Yayınevi.
  • Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2013). Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods. Engineering Economics, 24(1), 5–17.
  • Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • Turskis, Z., & Zavadskas, E. K. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy, 16(2), 159–172.
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag.
  • Işci, H., Baykara, Z., & Tülüce, B. (2023). Bulanık TOPSIS ve bulanık AHP yöntemleri ile risk analizi örneği. ALKÜ Fen Bilimleri Dergisi, 6(1).
  • Maniya, K., & Bhatt, D. (2010). A new preference selection index method for materials selection. Materials & Design, 31(4), 1785–1789.
  • Zambelli AE. A data-driven approach to estimating the number of clusters in hierarchical clustering. F1000Res. 2016 Dec 1;5:ISCB Comm J-2809.
  • Akogul, S., & Erisoglu, M. (2017). An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis. Entropy, 19(9), 452.
  • Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., & Ignatius, J. (2012). A state-of-the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051–13069.
  • Obeidat, M. S., Al Sliti, H., & Obeidat, A. (2025). The Preference Selection Index (PSI) in Multi-Criteria Decision-Making: A Systematic and Critical Review of Applications, Integrations, and Future Directions. Mathematical and Computational Applications, 30(6), 124.
  • Shbikat, N., & Bwaliez, O. M. (2025). Enhancing Kendall’s W using genetic algorithm: A computational approach to inter-rater reliability optimization. Expert Systems With Applications, 278, 127320.
  • M. Gul and A. F. Guneri, (2016). A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry. J. Loss Prev. Process Ind., vol. 40, pp. 89–100.
  • B. S. de Almeida Calixto and A. O. Michaloski. (2025). Assessment of occupational risk using multi-criteria fuzzy AHP methodology in a university laboratory. Sustainability, vol. 17, no. 6, Art. no. 2715.
  • Güner, M. D., & Ekmekci, P. E. (2019). Health Literacy Level of Casting Factory Workers and Its Relationship With Occupational Health and Safety Training. Workplace Health & Safety, 67(9), 452–460.
  • Barati Jozan, M. M., Ghorbani, B. D., Khalid, M. S., Lotfata, A., & Tabesh, H. (2023). Impact assessment of e-trainings in occupational safety and health: a literature review. BMC public health, 23(1), 1187.

Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods

Year 2026, Volume: 38 Issue: 1, 181 - 198, 20.03.2026
https://doi.org/10.7240/jeps.1811924
https://izlik.org/JA85ZK89BC

Abstract

Occupational safety training plays a significant role in protecting employees from accidents and occupational diseases. The effectiveness and content of training also influence the outcomes. In this regard, determining the training topics that employees need is important. In this study, the knowledge levels of manufacturing sector employees were measured using a 30-question test to determine the topics needed in occupational safety training. The data obtained were analyzed using multi-criteria decision-making methods. The aim of the study is to identify the topics in which manufacturing sector employees have knowledge gaps in terms of occupational safety. The results showed that manufacturing sector employees had the most knowledge gaps regarding personal protective equipment. This was followed by labor regulations, safety culture, working at heights, lifting equipment, emergencies, and occupational safety and health warning signs.

Ethical Statement

The author declare that they have carried out this completely original study by adhering to all ethical rules including authorship, citation and data reporting.

Supporting Institution

-

Thanks

I would like to thank Merve S. Arikan for her contributions to the data collection section.

References

  • Akpınar, T. (2018). İş sağlığı ve güvenliği hukuku. Seçkin Yayıncılık.
  • Eyrenci, Ö., Taşkent, S., & Ulucan, D. (2019). Bireysel iş hukuku (9. Baskı). Beta.
  • Süzek, S. (1985). İş güvenliği hukuku. Ankara.
  • Çalışma ve Sosyal Güvenlik Bakanlığı. (2013, 15 Mayıs). Çalışanların iş sağlığı ve güvenliği eğitimlerinin usul ve esasları hakkında yönetmelik (Sayı: 28648). Resmî Gazete. https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=18371&MevzuatTur=7&MevzuatTertip=5 (October 2024)
  • Gül, M. (2018). A review of occupational health and safety risk assessment approaches based on multi-criteria decision-making methods and their fuzzy versions. Human and Ecological Risk Assessment: An International Journal, 24(1), 1–38.
  • Jasiulewicz-Kaczmarek, M., Antosz, K., Wyczółkowski, R., & Sławińska, M. (2022). Integrated approach for safety culture factor evaluation from a sustainability perspective. International Journal of Environmental Research and Public Health, 19(19), 11869.
  • Demir, G., Bouraima, M. B., Badi, I., Stević, Ž., & Das, D. K. (2025). Identification of industrial occupational safety risks and selection of optimum intervention strategies: Fuzzy MCDM approach. Mathematics, 13(2), 301.
  • Cerev, G., & Yıldırım, S. (2018). Çalışanların kişisel özelliklerinin iş kazası ve meslek hastalıklarına etkisi üzerine bir inceleme. Fırat Üniversitesi Uluslararası İktisadi ve İdari Bilimler Dergisi, 2(1), 53–72.
  • Robson, L. S., Stephenson, C. M., Schulte, P. A., Amick, B. C., Irvin, E. L., Eggerth, D. E., Chan, S., Bielecky, A. R., Wang, A. M., Heidotting, T. L., & Peters, R. H. (2012). A systematic review of the effectiveness of occupational health and safety training. Scandinavian Journal of Work, Environment & Health, 38(1), 193–208.
  • Burke, M. J., Sarpy, S. A., Smith-Crowe, K., Chan-Serafin, S., Salvador, R. O., & Islam, G. (2006). Relative effectiveness of worker safety and health training methods. American Journal of Public Health, 96(2), 204–207.
  • Türkiye İş Kurumu. (2024). İŞGÜCÜ PİYASASI ARAŞTIRMASI ANKARA İLİ 2023 YILI SONUÇ RAPORU. https://media.iskur.gov.tr/88084/ankara.pdf (October 2024)
  • Tekin, H. (2007). Eğitimde ölçme ve değerlendirme (19. baskı). Yargı Yayınevi.
  • Dimitrov, D. M. (2016). An approach to scoring and equating tests with binary items: Piloting with large-scale assessments. IEEE Transactions on Education, 59(3), 179–185.
  • Tavşancıl, E. (2020). Tutumların ölçülmesi ve SPSS ile veri analizi (6. baskı). Nobel Yayıncılık.
  • Özbek, H., & Keskin, S. (2007). Standart sapma mı yoksa standart hata mı? Van Tıp Dergisi, 14(2), 64–67.
  • Tekin, H. (2015). Eğitimde ölçme ve değerlendirme. Yargı Yayınevi.
  • Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2013). Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods. Engineering Economics, 24(1), 5–17.
  • Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • Turskis, Z., & Zavadskas, E. K. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy, 16(2), 159–172.
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag.
  • Işci, H., Baykara, Z., & Tülüce, B. (2023). Bulanık TOPSIS ve bulanık AHP yöntemleri ile risk analizi örneği. ALKÜ Fen Bilimleri Dergisi, 6(1).
  • Maniya, K., & Bhatt, D. (2010). A new preference selection index method for materials selection. Materials & Design, 31(4), 1785–1789.
  • Zambelli AE. A data-driven approach to estimating the number of clusters in hierarchical clustering. F1000Res. 2016 Dec 1;5:ISCB Comm J-2809.
  • Akogul, S., & Erisoglu, M. (2017). An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis. Entropy, 19(9), 452.
  • Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., & Ignatius, J. (2012). A state-of-the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051–13069.
  • Obeidat, M. S., Al Sliti, H., & Obeidat, A. (2025). The Preference Selection Index (PSI) in Multi-Criteria Decision-Making: A Systematic and Critical Review of Applications, Integrations, and Future Directions. Mathematical and Computational Applications, 30(6), 124.
  • Shbikat, N., & Bwaliez, O. M. (2025). Enhancing Kendall’s W using genetic algorithm: A computational approach to inter-rater reliability optimization. Expert Systems With Applications, 278, 127320.
  • M. Gul and A. F. Guneri, (2016). A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry. J. Loss Prev. Process Ind., vol. 40, pp. 89–100.
  • B. S. de Almeida Calixto and A. O. Michaloski. (2025). Assessment of occupational risk using multi-criteria fuzzy AHP methodology in a university laboratory. Sustainability, vol. 17, no. 6, Art. no. 2715.
  • Güner, M. D., & Ekmekci, P. E. (2019). Health Literacy Level of Casting Factory Workers and Its Relationship With Occupational Health and Safety Training. Workplace Health & Safety, 67(9), 452–460.
  • Barati Jozan, M. M., Ghorbani, B. D., Khalid, M. S., Lotfata, A., & Tabesh, H. (2023). Impact assessment of e-trainings in occupational safety and health: a literature review. BMC public health, 23(1), 1187.
There are 31 citations in total.

Details

Primary Language English
Subjects Multiple Criteria Decision Making, Manufacturing Safety and Quality
Journal Section Research Article
Authors

Hasan İşci 0000-0002-8112-5504

Submission Date October 27, 2025
Acceptance Date February 6, 2026
Publication Date March 20, 2026
DOI https://doi.org/10.7240/jeps.1811924
IZ https://izlik.org/JA85ZK89BC
Published in Issue Year 2026 Volume: 38 Issue: 1

Cite

APA İşci, H. (2026). Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods. International Journal of Advances in Engineering and Pure Sciences, 38(1), 181-198. https://doi.org/10.7240/jeps.1811924
AMA 1.İşci H. Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods. JEPS. 2026;38(1):181-198. doi:10.7240/jeps.1811924
Chicago İşci, Hasan. 2026. “Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods”. International Journal of Advances in Engineering and Pure Sciences 38 (1): 181-98. https://doi.org/10.7240/jeps.1811924.
EndNote İşci H (March 1, 2026) Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods. International Journal of Advances in Engineering and Pure Sciences 38 1 181–198.
IEEE [1]H. İşci, “Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods”, JEPS, vol. 38, no. 1, pp. 181–198, Mar. 2026, doi: 10.7240/jeps.1811924.
ISNAD İşci, Hasan. “Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods”. International Journal of Advances in Engineering and Pure Sciences 38/1 (March 1, 2026): 181-198. https://doi.org/10.7240/jeps.1811924.
JAMA 1.İşci H. Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods. JEPS. 2026;38:181–198.
MLA İşci, Hasan. “Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods”. International Journal of Advances in Engineering and Pure Sciences, vol. 38, no. 1, Mar. 2026, pp. 181-98, doi:10.7240/jeps.1811924.
Vancouver 1.Hasan İşci. Topic-Based Evaluation of Occupational Safety Knowledge Levels of Manufacturing Sector Employees Using Multi-Criteria Decision-Making Methods. JEPS. 2026 Mar. 1;38(1):181-98. doi:10.7240/jeps.1811924