THE EFFECT OF DRIVER SAFETY PRIORITY ON SLEEPY DRIVING BEHAVIOR: LINEAR AND NON-LINEAR REGRESSION ANALYSIS

Abstract

Driver safety priority is among the factors that affect the sleepy driving behavior of truck drivers. The aim of this paper is to determine the effect of truck drivers' driver safety priority on sleepy driving behavior with linear and non-linear models. Two hypotheses have been developed within the scope of the research. The sample area consists of 399 Turkish truck drivers. Surveys were collected face to face and online between January 2022 and April 2022. The sample area has been determined by simple random method. "Driver safety priority" and "Sleepy driving behavior" scales is used, which is tested for reliability and validity. Simple regression analysis has been performed for the linear model. In the selection of non-linear models, curve estimation models have been tested. The “Power” estimation model has been determined as the best model. According to the research findings, driver safety priority has a negative and significant effect on sleepy driving behavior in both linear and non-linear models. In addition, it has been determined that there is no significant difference between the percentages of explanation of linear and non-linear models. It has also been determined that the coefficient of the driver safety priority of the linear model on sleepy driving behavior is higher than the non-linear model. Based on the empirical findings, implications for both managers and drivers have been presented.

Keywords

• Driver Safety Priority
• Sleepy driving Behavior
• Linear Model
• Non-Linear Model
• Curve Estimation Models

Sürücü Emniyet Önceliğinin Uykulu Sürüş Davranışı Üzerindeki Etkisi: Doğrusal ve Doğrusal Olmayan Regresyon Analizi

Abstract

Tır sürücülerinin uykulu sürücü davranışı oluşumuna etki eden faktörler arasında sürücü emniyet önceliği gelmektedir. Bu ampirik araştırmanın amacı Türkiye’de tır sürücülerinin sürücü emniyet önceliğinin uykulu sürücü davranışı üzerindeki etkisinin doğrusal ve doğrusal olmayan modellerle tespit edilmesidir. Araştırma kapsamında iki hipotez geliştirilmiştir. Araştırmanın örneklem alanını 399 adet Türk tır sürücüsü oluşturmaktadır. Anketler yüz yüze ve çevrimiçi olarak Ocak 2022-Nisan 2022 tarihleri arasında toplanmıştır. Örneklem alan basit rastgele yöntemle belirlenmiştir. Araştırmada güvenilirliği ve geçerliliği test edilmiş “sürücü emniyet önceliği” ve “uykulu sürüş davranışı” ölçekleri kullanılmıştır. Doğrusal model için basit regresyon analizi yapılmıştır. Doğrusal olmayan model seçiminde eğri tahmin modelleri test edilmiştir. “Power” eğri tahmin modeli en iyi model olarak tespit edilmiştir. Araştırma bulgularına göre hem doğrusal hem de doğrusal olmayan modellerde sürücü emniyet önceliği uykulu sürücü davranışı üzerinde negatif yönde anlamlı bir etkiye sahiptir. Ayrıca doğrusal ve doğrusal olmayan modellere ait açıklama yüzdeleri arasında dikkate değer bir fark olmadığı tespit edilmiştir. Bunun yanı sıra doğrusal modele ait sürücü emniyet önceliğinin uykulu sürücü davranışı üzerindeki etki katsayısının doğrusal olmayan modele göre yüksek olduğu tespit edilmiştir. Araştırma bulgularına dayalı hem yöneticilere hem de sürücülere yönelik çıkarımlar sunulmuştur.

Keywords

• Sürücü Emniyet Önceliği
• Uykulu Sürüş Davranışı
• Doğrusal Model
• Doğrusal olmayan Model
• Eğri Tahmin Modelleri

References

1. Anderson, N. J., Smith, C. K. & Byrd, J. L. (2017). “Work‐related injury factors and safety climate perception in truck drivers”. American Journal of Industrial Medicine, 60 (8), 711-723. https://doi.org/10.1002/ajim.22737.
2. Bosak, J., Coetsee, W. J. & Cullinane, S. J. (2013). “Safety climate dimensions as predictors for risk behavior”. Accident Analysis & Prevention, 55, 256-264. https://doi.org/10.1016/j.aap.2013.02.022.
3. Bunn, T. L., Slavova, S., Struttmann, T. W. & Browning, S. R. (2005). “Sleepiness/fatigue and distraction/inattention as factors for fatal versus nonfatal commercial motor vehicle driver injuries”. Accident Analysis & Prevention, 37(5), 862-869.
4. Buyukozturk, S. Cakmak, E. K., Akgun, O. E, Karadeniz, S. & Demirel, F. (2016). Bilimsel arastirma yontemleri. Ankara, Turkey: Pegem Akademi.
5. Byrne, B. M. (2011). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge. https://doi.org/10.4324/9780203807644.
6. Chen, G. X., Sieber, W. K., Lincoln, J. E., Birdsey, J., Hitchcock, E. M., Nakata, A. & Sweeney, M. H., (2015). “NIOSH national survey of long-haul truck drivers: injury and safety”. Accident Analysis & Prevention, 85, 66-72. https://doi.org/10.1016/j.aap.2015.09.001.
7. Cooper, M. D. & Phillips, R. A. (2004). “Exploratory analysis of the safety climate and safety behavior relationship”. Journal of safety research, 35 (5), 497-512. https://doi.org/10.1016/j.jsr.2004.08.004.
8. Crum, M. R. & Morrow, P. C. (2002). “The influence of carrier scheduling practices on truck driver fatigue”. Transportation Journal, 42(1), 20.

9. Eymen, E. (2007). SPSS Veri Analizi Yöntemleri (1st ed.), İstatistik Merkezi, Ankara.
10. Fornell, C. & Larcker, D. F. (1981). “Evaluating structural equation models with unobservable variables and measurement error”. Journal of Marketing Research, 18(1), 39-50.
11. Gharibi, V., Mokarami, H., Cousins, R., Jahangiri, M. & Eskandari, D. (2020). “Excessive daytime sleepiness and safety performance: comparing proactive and reactive approaches”. The International Journal of Occupational and Environmental Medicine, 11 (2), 95. https://doi.org/10.34172/ijoem.2020.1872.
12. Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). “PLS-SEM: Indeed a silver bullet”. Journal of Marketing Theory and Practice, 19 (2), 139-152. https://doi.org/10.2753/MTP1069-6679190202.
13. Huang, Y. H., Zohar, D., Robertson, M. M., Garabet, A., Lee, J. & Murphy, L. A. (2013). “Development and validation of safety climate scales for lone workers using truck drivers as exemplar”. Transportation Research Part F: Traffic Psychology And Behaviour, 17, 5-19. http://dx.doi.org/10.1016/j.trf.2012.08.011.
14. Kline, R. B. (2011). Principles and practice of structural equation modelling (3rd ed.). New York, Guilford press. Lee, J., Huang, Y. H., Sinclair, R. R. & Cheung, J. H. (2019). “Outcomes of safety climate in trucking: A longitudinal framework”. Journal of Business and Psychology, 34 (6), 865-878. https://doi.org/10.1007/s10869-018-9610-5.
15. Lemke, M. K., Apostolopoulos, Y., Hege, A., Sönmez, S. & Wideman, L. (2016). “Understanding the role of sleep quality and sleep duration in commercial driving safety”. Accident Analysis & Prevention, 97, 79-86. https://doi.org/10.1016/j.aap.2016.08.024.
16. Lemke, M. K., Hege, A., Apostolopoulos, Y. & Sönmez, S. (2021). “Hours-of-service compliance and safety outcomes among long-haul truck drivers”. Transportation Research Part F: Traffic Psychology And Behaviour, 76, 297-308. https://doi.org/10.1016/j.trf.2020.11.017.
17. Mahajan, K., Velaga, N. R., Kumar, A. & Choudhary, P. (2019). “Effects of driver sleepiness and fatigue on violations among truck drivers in India”. International Journal of İnjury Control and Safety Promotion, 26 (4), 412-422. https://doi.org/10.1080/17457300.2019.1660375.
18. Meng, F., Li, S., Cao, L., Li, M., Peng, Q., Wang, C. & Zhang, W. (2015). “Driving fatigue in professional drivers: a survey of truck and taxi drivers”. Traffic Injury Prevention, 16(5), 474-483. https://doi.org/10.1080/15389588.2014.973945.
19. Misa, R., Conduit, R. & Coleman, G. (2011). “Sleepy driving in truck drivers: Insights from a self-report survey”. In Proceedings of the 47th Annual Conference Human Factors and Ergonomics Society of Australia (HFESA 2011) (pp. 1-8). RMIT University.
20. Moradi, A., Nazari, S. S. H. & Rahmani, K. (2019). “Sleepiness and the risk of road traffic accidents: A systematic review and meta-analysis of previous studies”. Transportation Research Part F: Traffic Psychology And Behaviour, 65, 620-629. https://doi.org/10.1016/j.trf.2018.09.013.
21. Myers, D. J., Nyce, J. M. & Dekker, S. W. (2014). “Setting culture apart: Distinguishing culture from behavior and social structure in safety and injury research”. Accident Analysis & Prevention, 68, 25-29. https://doi.org/10.1016/j.aap.2013.12.010.
22. Phillips, R. O. & Sagberg, F. (2013). “Road accidents caused by sleepy drivers: Update of a Norwegian survey”. Accident Analysis & Prevention, 50, 138-146. http://dx.doi.org/10.1016/j.aap.2012.04.003.
23. Radun, I., Ohisalo, J., Radun, J., Wahde, M. & Kecklund, G. (2013). “Driver fatigue and the law from the perspective of police officers and prosecutors”. Transportation Research Part F: Traffic Psychology And Behaviour, 18, 159-167. https://doi.org/10.1016/j.trf.2013.01.001.
24. Schwarz, C., Gaspar, J., Miller, T. & Yousefian, R. (2019). “The detection of drowsiness using a driver monitoring system”. Traffic Injury Prevention, 20(sup1), S157-S161. https://doi.org/10.1080/15389588.2019.1622005.
25. Shi, B., He, Y., Lee, J., Huang, Y. H. & Li, Y. (2022). “Safety climate profiles in remote workers: Association with key predictors and outcomes at the team level”. Safety Science, 145, 105477. https://doi.org/10.1016/j.ssci.2021.105477.
26. Sinaiko, H. W. & Brislin, R. W. (1973). “Evaluating language translations: Experiments on three assessment methods”. Journal of Applied Psychology, 57(3), 328.
27. Spielholz, P., Cullen, J., Smith, C., Howard, N., Silverstein, B. & Bonauto, D. (2008). “Assessment of perceived injury risks and priorities among truck drivers and trucking companies in Washington State”. Journal of Safety Research, 39(6), 569-576.
28. Tabachnick, B. G., Fidell, L. S. & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson.
29. Wang, Y., Li, L. & Prato, C. G., (2019). “The relation between working conditions, aberrant driving behaviour and crash propensity among taxi drivers in China”. Accident Analysis & Prevention, 126, 17-24. https://doi.org/10.1016/j.aap.2018.03.028.
30. Watling, C. N. (2018). “Drivers' perceived legitimacy of enforcement practices for sleep-related crashes: What are the associated factors?”. Journal of Forensic and Legal Medicine, 54, 34-38. https://doi.org/10.1016/j.jflm.2017.12.005.
31. Zhang, G., Yau, K. K., Zhang, X. & Li, Y. (2016). “Traffic accidents involving fatigue driving and their extent of casualties”. Accident Analysis & Prevention, 87, 34-42.
32. Zohar, D., Huang, Y. H., Lee, J. & Robertson, M. (2014). A mediation model linking dispatcher leadership and work ownership with safety climate as predictors of truck driver safety performance. Accident Analysis & Prevention, 62, 17-25. https://doi.org/10.1016/j.aap.2013.09.005.