Науковий вісник НГУ

Research on the impact of cognitive biases of workers on the subjective assessment of occupational risk

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №1 2023

Last Updated on 25 February 2023

Published on 30 November -0001

Hits: 3100

Authors:

Z.G.Zhanbirov, orcid.org/0000-0002-6444-0836, Academy of Logistics and Transport, Almaty, the Republic of Kazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

O.V.Deryugin*, orcid.org/0000-0002-2456-7664, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.B.Toktamyssova, orcid.org/0000-0002-9434-7413, Kostanay Engineering and Economic University named after M.Dulatov, Kostanay, the Republic of Kazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

D.A.Agabekova, orcid.org/0000-0003-2604-0126, Eurasian Technological University, Almaty, the Republic of Kazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

M.M.Arkhirei, orcid.org/0000-0002-6803-0703, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (1): 136 - 141

https://doi.org/10.33271/nvngu/2023-1/136

Abstract:

Purpose. When assessing occupational risks (OR) of professional activities of employees of the motor transport company (MTC), there is often a problem to determine the probability of a hazardous event and the severity of its consequences under the influence of various cognitive biases. Therefore, there arises an urgent issue of taking into account the cognitive biases and their influence on the assessment of PR. This is achieved by studying the impact of awareness and worldview of employees on the assessment of PR and developing recommendations for reducing cognitive bias in determining the likelihood of a hazardous event.

Methodology. The study involved 87 employees of the motor transport company of different ages, experience and level of education, who were interviewed on a specially designed checklist which provides for the ranking of harmful factors that affect the employee when performaning production tasks, taking into account the impact of five cognitive biases on the value the probability of a hazardous event.

Findings. According to the results of the study, it can be concluded that motor transport company workers with significant professional experience were most concerned about the intensity and pace of work, as well as the number of repetitive movements, which significantly affected the level of safety when performaning production tasks. Less experienced workers highlighted the intensity of work, the pace of work and the monotony of work and from the point of view of males, the greatest concern was the intensity and monotony of work, in contrast to females who are concerned about the pace of work and uncomfortable posture. It is determined that employees perceive occupational risk more optimistically if they understand that it is controlled. There has also been a deteriorating trend due to a lack of time to conduct a proper analysis of the impact of harmful factors on workers’ health.

Originality. Relationship is established between cognitive biases that occur in employees during the assessment of OR with the determination of the probability of a hazardous situation, which increases the probability of errors from 10 to 20 % during professional activities.

Practical value. Recommendations are developed to reduce the impact of subjective assessment on the magnitude of PR, which is based on increasing the number of participants with different worldviews, experience, education.

Keywords: cognitive bias, occupational risk, occupational safety, management decisions

References.

1. World Health Organization. Road traffic injuries 2021 (2021). Retrieved from https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries#.

2. Official website of the European Union. Road safety: 4 000 fewer people lost their lives on EU roads in 2020 as death rate falls to all time low (2021). Retrieved from https://ec.europa.eu/transport/modes/road/news/2021-04-20-road-safety_en.

3. Tsopa, V., Cheberiachko, S., Yavorska, O., Deryugin, O., & Bas, I. (2022). Increasing the safety of the transport process by minimizing the professional risk of a dump truck driver. Mining of mineral deposits, 16(3), 101-108. https://doi.org/10.33271/mining16.03.101.

4. Patrol police of Ukraine (n.d.). Statistics of road accidents in Ukraine for the period from 01.01.2020 to 31.12.2020. Retrieved from http://patrol.police.gov.ua/statystyka/.

5. Bazaluk, O., Koriashkina, L., Cheberyachko, S., Deryugin, O., Odnovol, M., Lozynskyi, V., & Nesterova, O. (2022). Functional Resonance Analysis Method for Incident Risk Assessment During Passenger Road Transportation. Heliyon, 8(11), e11814. https://doi.org/10.1016/j.heliyon.2022.e11814.

6. Medina-Aman, G., Escobar-Segovia, K., & Arias-Ulloa, C. (2021). Risk factors and their relationship in drivers of an interprovincial transport cooperative in Ecuador. Revista San Gregorio, 1(46), 30-46. https://doi.org/10.36097/rsan.v1i46.1477.

7. Ríos-Domínguez, N., Abella-Corredor, L., Ríos-Domínguez, I., Lugo-Calderón, E., & Severiche-Sierra, C. (2022). Cardiovascular risk in urban collective public service transport drivers: application of the Framingham scale. IPSA Scientia, 7(3), 59-66. https://doi.org/10.25214/27114406.1521.

8. Taran, I., & Litvin, V. (2018). Determination of rational parameters for urban bus routes with combined operating mode. Transport Problems, 13(4), 157-171. https://doi.org/10.20858/tp.2018.13.4.14.

9. Ellis, A. P. J., Porter Christopher, O. L. H., & Mai, K. M. (2022). The impact of supervisor-employee self-protective implicit voice theory alignment. Journal of Occupational and Organizational Psychology, 95(1), 155-183. https://doi.org/10.1111/joop.12374.

10. Naumov, V., Zhamanbayev, B., Agabekova, D., Zhanbirov, Z., & Taran, I. (2021). Fuzzy-logic approach to estimate the passengers preference when choosing a bus line within the public transport system. Communications – Scientific Letters of the University of Žilina, 23(3), A150-A157. https://doi.org/10.26552/com.C.2021.3.A150-A157.

11. Lu, C.-C., & Liang, J.-K. (2022). Exploring factors that influence the cardiovascular health of bus drivers for the improvement of transit safety. International Journal of Occupational Safety and Ergonomics. https://doi.org/10.1080/10803548.2022.2120259.

12. Busetto, L., Wick, W., & Gumbinger, C. (2020). How to use and assess qualitative research methods. Neurological Research and Practice, 2, 14. https://doi.org/10.1186/s42466-020-00059-z.

13. Siebenkäs, A., & Stelzer, D. (2019). Assessing Theories for Research on Personal Data Transparency. In Kosta, E., Pierson, J., Slamanig, D., Fischer-Hübner, S., & Krenn, S. (Eds.) Privacy and Identity Management. Fairness, Accountability, and Transparency in the Age of Big Data. Privacy and Identity 2018. IFIP Advances in Information and Communication Technology, 547. Cham: Springer. https://doi.org/10.1007/978-3-030-16744-8_16/.

14. Olabode, S. O., Adesanya, A. R., & Bakare, A. A. (2017). Ergonomics Awareness and Employee Performance: An Exploratory Study. Economic and Environmental Studies, 17(4), 813-829. https://doi.org/10.25167/ees.2017.44.11.

15. Latip, S. N. N. A., Latip, M. S. A., Tamrin, M., & Nawi, M. Z. M. (2022). The Perspective of Work Ergonomics on Employee Task Performance in Hotel and Tourism Industry Malaysia. Proceedings, 82, 7. https://doi.org/10.3390/proceedings2022082007.

16. Teng, K., Thekdi, S. A., & Lambert, J. H. (2012). Identification and evaluation of priorities in the business process of a risk or safety organization. Reliability Engineering and System Safety, 99, 74-86. https://doi.org/10.1016/j.ress.2011.10.006.

17. Sahebjamnia, N., Torabi, S. A., & Mansouri, A. (2015). Integrated business continuity and disaster recovery planning: Towards organizational resilience. European Journal of Operational Research, 242(1), 261-273. https://doi.org/10.1016/j.ejor.2014.09.055.

18. Rinaldi, M., Murino, Te., Gebennini, E., Morea, D., & Bottan, E. (2022). A literature review on quantitative models for supply chain risk management: Can they be applied to pandemic disruptions? Computers & Industrial Engineering, 170, 108329. https://doi.org/10.1016/j.cie.2022.108329.

19. Dehaene, H., De Neve, J., & Rosseel, Y. (2021). A Wilcoxon-Mann-Whitney Test for Latent Variables. Frontiers in Psychology, Section Quantitative Psychology and Measurement, 12, 754898. https://doi.org/10.3389/fpsyg.2021.754898.

20. Vander Weele, T. J., & Mathur, M. B. (2019). Some desirable properties of the bonferroni correction: is the bonferroni correction really so bad? American Journal of Epidemiology, 188(3), 617-618. https://doi.org/10.1093/aje/kwy250.

• < Prev
• Next >