Behavioural Comparison of Driverswhen Driving a Motorcycle or a Car: A Structural Equation Modelling Study
Abstract
The goal of the study was to investigate if the drivers behave in the same way when they are driving a motorcycle or a car. For this purpose, the Motorcycle Rider Behaviour Questionnaire and Driver Behaviour Questionnaire were conducted among the same drivers population. Items of questionnaires were used to develop a structural equation model with two factors, one for the motorcyclist’s behaviour, and the other for the car driver’s behaviour. Exploratory and confirmatory factor analyses were also applied in this study. Results revealed a certain difference in driving behaviour. The principal reason lies probably in mental consciousness that the risk-taking driving of a motorbike can result in much more catastrophic consequences than when driving a car. The drivers also pointed out this kind of thinking and the developed model has statistically confirmed the behavioural differences. The implications of these findings are also argued in relation to the validation of the appropriateness of the existing traffic regulations.
References
Knez M, Jereb B, Obrecht M. Factors influencing the purchasing decisions of low emission cars: a study of Slovenia. Transportation research. Part D: Transport and Environment. 2014;30:53-61.
OECD. Road Safety Annual Report; 2014 [cited 22 Dec 14]. Available from: http://www.internationaltransportforum.org/pub/pdf/14IrtadReport.pdf
Houston DJ. Motorcyclists. In: Porter BE, editor. Handbook of Traffic Psychology. London: Academic Press Elsevier, 2011; p. 375-387.
Hurt HH, Ouellet JV, Tho DR. Motorcycle accident cause factors and identification of countermeasures: Technical report; 1981 [cited 18 Dec 14]. Available from: http://isddc.dot.gov/OLPFiles/NHTSA/013695.pdf
Diamantopoulou K, Brumen I, Dyte D, Cameron M. Analysis of trends in motorcycle crashes in Victoria. Research Report; 1995 [cited 10 Dec 14]. Available from: http://www.monash.edu.au/miri/research/reports/muarc084.html
European commission: Statistics – accidents data; 2014 [cited 11 Dec 14]. Available from: http://ec.europa.eu/transport/road_safety/specialist/statistics/index_en.htm
DEKRA Automotive GmbH Motorcycle Road Safety Report 2010 – Strategies for Preventing Accidents on the Roads of Europe, Stuttgart; 2010.
Kalyoncuoğlu FS, Tiğdemir M. The effects of daily driven distance and age f actor on the traffic accidents. Promet – Traffic & Transportation. 2014;26(3):201-207.
Reason J. Human Error. Cambridge: Cambridge University Press; 1990.
Lindberg G. Accidents. Research in Transportation Economics. 2005;14:155-183.
Rumar K. The role of perceptual and cognitive filters in observed behaviour. In: Evans L, Schwing RC, editors. Human behaviour and Traffic Safety. New York/London: Plenum Press; 1985.
Wåhlberg AE, Dorn L, Kline T. The Manchester Driver Behaviour Questionnaire as a Predictor of Road Traffic Accidents. Theoretical Issues in Ergonomics Science. 2011;12(1):66-86.
Elliott MA, Baughan CJ, Sexton BF. Errors and violations in relation to motorcyclists’ crash risk. Accident Analysis and Prevention. 2007;39(3):491-499.
Reason J, Manstead A, Stradling S, Baxter J, Campbell K. Errors and violations on the roads: a real distinction? Ergonomics. 1990;33:1315-1332.
Özkan T, Lajunen T, Doğruyol B, Yıldırım Z, Coymak A. Motorcycle accidents, rider behaviour, and psychological models. Accident Analysis and Prevention. 2012;49:124- 132.
Mattsson M. Investigating the factorial invariance of the 28-item DBQ across genders and age groups: an Exploratory Structural Equation Modeling study. Accident Analysis and Prevention. 2012;48:379-396.
Lajunen T, Parker D, Summala S. The Manchester Driver Behaviour Questionnaire: a cross-cultural study. Accident Analysis and Prevention. 2004;36:231-238.
Lawton R, Parker D, Stradling SG, Manstead ASR. Predicting road traffic accidents: the role of social deviance and violations. British Journal of Psychology. 1997;88(2):249-262.
Parker D, Reason JT, Manstead ASR, Stradling SG. Driving errors, driving violations and accident involvement. Ergonomics. 1995;38(5):1036-1048.
Banet A, Bellet T. Risk awareness analysis: a comparison between car drivers and motorcyclists. Proceedings of European Conference on Human Centred Design for Intelligent Transport Systems; 2008, p. 287-297.
Horswill MS, Helman S. A behavioral comparison between motorcyclists and a matched group of non-motorcycling car drivers: factors influencing accident risk. Accident Analysis and Prevention. 2003;35:589-597.
Kline RB. Principles and Practice of Structural Equation Modeling (2th ed.). New York: The Guilford Press; 2005.
Hoyle RH. Handbook of Structural Equation Modeling. New York: The Guilford Press; 2012.
Hair JF. Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. New Jersey: Prentice Hall; 2010.
Byrne BM. Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming. New York: Routledge; 2009.
Curran PJ, West SG, Finch JF. The Robustness of Test Statistics to Nonnormality and Specification Error in Confirmatory Factor Analysis. Psychological Methods. 1996;1:16-29.
Ullman JB. Structural equation modeling: Reviewing the basics and moving forward. Journal of Personality Assessment. 2006;87(1):35-50.
Weston R, Gore PA. A Brief Guide to Structural Equation Modeling. The Counseling Psychologist. 2006;34(5):719-751.
Zhai X, Liu AMM, Fellows R. Human Resource Practices in Chinese Construction Organizations: Development of a Measurement Scale. International Journal of Architecture, Engineering and Construction. 2013;2(3):170-183.
Chou CP, Bentler PM. Estimates and tests in structural equation modelling. In: Hoyle RH, editor. Structural Equation Modeling: Concepts, Issues, and Applications. Thousand Oaks: Sage, 1995; p. 37-56.
Lei M, Lomax RG. The effect of varying degrees of nonnormality in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal. 2005;12(1):1-27.
Hoyle RH. Structural Equation Modeling: Concepts, Issues, and Applications. Thousand Oaks: Sage, CA; 1995.
El-Basyouny K, El-Bassiouni MY. Modeling and analyzing traffic safety perceptions: An application to the speed limit reduction pilot project in Edmonton, Alberta. Accident Analysis & Prevention. 2013;51:156-167.
Müller J, Bühner M, Ellgring H. Is there a reliable factorial structure in the 20-item Toronto Alexithymia Scale?: A comparison of factor models in clinical and normal adult samples. Journal of Psychosomatic Research. 2003;55(6):561-568.
Frohlich MT, Westbrook R. Arcs of integration: an international study of supply chain strategies. Journal of Operations Management. 2001;19(2):185-200.
Sahin M, Todiras A, Nijkamp P, Neuts B, Behrens C. A Structural Equations Model for Assessing the Economic Performance of High-Tech Entrepreneurs. In: Capello R, Dentinho TP, editors. Globalization Trends and Regional Development, 2013; p. 211-259.
Li J, Zhou L, Zhu D, Hu C, Zhang X, Xu Y. Chinese version of the nursing students’ perception of instructor caring (C-NSPIC): Assessment of reliability and validity. Nurse Education Today. 2013;33(12):1482-1489.
Hooper D, Coughlan J, Mullen MR. Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods. 2008;6(1):53-60.
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