The role of personality traits,work motivation and

organizational safety climate inrisky occupational performance

of professional driversLaura Seibokaite

Department of Theoretical Psychology, Vytautas Magnus University,Kaunas, Lithuania, and

Aukse EndriulaitieneDepartment of General Psychology, Vytautas Magnus University,

Kaunas, Lithuania

Abstract

Purpose – The purpose of this paper is to combine individual (personality traits and profiles) andorganizational (perceived safety climate and work motivation) factors and look for a model thatexplains safety performance in a sample of professional drivers. The authors hypothesize that theeffect of personality on risky driving is moderated by perceived organizational safety climate andwork motivation.

Design/methodology/approach – The sample consisted of 166 professional drivers (males). Thesubjects completed the self-reported questionnaire that consisted of the Big Five Inventory, DriverBehaviour Questionnaire, Work motivation and Safety Climate Questionnaires. Cross-sectionalmethodology, analysis of variance, cluster analysis and structural equation modeling were used topredict the relationships between personality traits, organizational factors, and risky driving.

Findings – The results revealed that personality profile is very important in occupational setting,predicting work motivation, perceived safety climate in organization as well as risky or safe driving.Results encourage making a conclusion that “socially oriented” drivers drive less riskily if they havehigher levels of work motivation and the perception of organizational climate being safe. “Emotionallyunstable” professional drivers are probably driven by neuroticism and are non-responsive toorganizational factors.

Research limitations/implications – The design does not allow making causal statements.In addition, the sample is quite small and may not be representative. Self-report data may bias theresults due to social desirability or lack of experience in self-reflection.

Practical implications – The results of the present investigation have expanded understanding ofthe role of personality and organizational interaction in predicting occupational safety of professionaldrivers. The main implication for practitioners is to develop such selection procedures that couldidentify drivers with safe driving personalities.

Originality/value – The research contributes to the field of occupational safety by integratingindividual attributes with organizational factors by providing empirical findings and theoreticalinterpretations.

Keywords Lithuania, Occupational safety, Industrial trucks, Buses, Employees attitudes, Personality,Professional drivers, Personality traits, Organizational safety climate, Work motivation, Risky driving,Safe driving

Paper type Research paper

The current issue and full text archive of this journal is available at

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Received 4 January 2010Accepted 12 July 2010

Baltic Journal of ManagementVol. 7 No. 1, 2012

pp. 103-118q Emerald Group Publishing Limited

1746-5265DOI 10.1108/17465261211195892

Newnam et al. (2005) state that road crashes are now the most common cause ofwork-related injury, death, and work absence in a number of countries. Some authorsargue that traffic accident is the most significant cause of accidental deaths at work inFinland (Salminen, 2000), work-related road crashes caused at least from one-quarter toone-third of occupational deaths in the USA, Australia, and EU countries (EuropeanRoad Safety Observatory, 2007). Although mass media often presents the informationabout fatalities involving professional drivers on Lithuanian roads, there is no officialstatistical data on work-related traffic accidents rate in Lithuania (Sadauskas, 2008).But according to the number of general road traffic accidents and casualties of thoseaccidents Lithuania occupies the leading position in Europe. There occurapproximately 6,500 road accidents per year in Lithuania, which cause more than700 deaths and approximately 8,000 injuries (Statistical Department of Lithuania, 2007;Obelenis and Kaveckaite, 2004; Sadauskas, 2006). This shows that the problem needsattention from community, organizations, and researchers.

High rates in work-related crashes suggest that road safety should be an importantconcern for all organizations where employees are engaged in work-related driving.However, surprisingly little research has investigated driving behaviour in anorganizational setting. Although management of safety in organization should be one ofthe management responsibilities, scarce research results about work-related driving canbarely contribute to the development of management in this area (Newnam et al., 2005).

Avoiding work-related traffic accidents is the major concern of transport-usingorganizations and their managers, first of all because those accidents are much moreexpensive for organization than any other occupational injury; also as any work-relatedaccidents traffic crashes have negative impact upon organizational effectiveness andemployee morale (Salminen, 2008).

One group of professionals that might contribute to higher or lower safety on theroads is professional drivers (taxi drivers, bus drivers, truck drivers, etc.). Their riskydriving (i.e. work performance) might lead to car accidents with tremendous social,environmental, and economic consequences (Patil et al., 2006; Dekker, 2004; Eby, 2004).On the one hand, professional drivers should demonstrate lower levels of risky drivingbecause they have more driving experience; they have obligations to their organizationto work effectively (i.e. without accidents). On the other hand, they are more confidentin their driving abilities, so may not consider their action to be a risky one even thoughit increases his or her chances of being in a crash, also they might feel the pressure fromwork environment to work/drive fast, without rest, etc. Risky driving behaviours arethose actions that increase the objective likelihood of a crash or the severity of injuryshould a crash occur (for example, minor driving lapses like getting into the wronglane, serious errors like failing to notice the road signs and intentional violations, likeover speeding, running red lights, alcohol impaired driving, etc.) (Sumer et al., 2005).

Understanding organizational and individual factors that might predict professionaldriver’s risk-taking behaviour might be of crucial importance for managers andsupervisors who are responsible for monitoring safety in the organizations andemployee health (Wills et al., 2005).

Literature analysis reveals several individual factors that contribute to the riskydriving behaviour in the general population. Most authors agree that young (Bogg andRoberts, 2004; Eby, 2004; Lawton et al., 2007; Whissell and Bigelow, 2003) male(Eby, 2004; Endriulaitiene and Marksaityte, 2007) drivers with predisposition

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to sensation seeking, aggressiveness, anger, and anxiety, impulsiveness, lowconscientiousness, more frequent alcohol and drug use are more prone to riskydriving behaviour (Bogg and Roberts, 2004; Engstrom et al., 2003; Machin and Sankey,2006; Oltedal and Rundmo, 2006; Deffenbacher et al., 2003; Krahe, 2005; Skaar andWilliams, 2005; Whissell and Bigelow, 2003). Data about risky driving correlates ofprofessional drivers, which might include various organizational factors, are scarce.So, the main purpose of this study is to combine individual (personality traits andprofiles) and organizational (perceived safety climate and work motivation) factors andlook for a model that explains safety performance of professional drivers.

There is a body of empirical work exploring the links between personality traits andaccident involvement; still the empirical evidence is contradictory and confusing (Clarkeand Robertson, 2005). The most common correlates of risky driving, as well as ofoccupational performance and accidents, studied in previous research are personalitytraits, usually explored by using five-factor model. All five personality traits(extraversion, neuroticism, openness, agreeableness, and conscientiousness) might havepositive or negative effect to risky driving in general population, but this relationshipmight be significantly moderated by organizational context (Clarke and Robertson,2005; Lajunen, 2001).

Extraversion is described as a trait of sociability, preference of large groups andgatherings, assertiveness, activity, cheerfulness, and optimism. This trait is usuallyfound to be positively correlated with risk-taking behaviour (Arthur and Graziano,1996; Clarke and Robertson, 2005; Lajunen, 2001; Sumer et al., 2005; Schwebel et al.,2007). However, several studies fail to prove the correlation between extraversion andrisky behaviour on the road (Elander et al., 1993).

Some authors mention neuroticism as risky driving and accident involvementpredictor (Sumer et al., 2005), but much larger amount of research results shows nocorrelation between neuroticism and risky driving (Arthur and Graziano, 1996;Lajunen, 2001; Stephens and Groeger, 2009). Neuroticism is understood as the generaltendency to experience negative affects, such as fear, sadness, anger, anxiety, guilt, anddifficulties to cope with stress. Clarke and Robertson (2005) in a meta-analytic reviewreport mixed results concerning neuroticism in driving context.

Openness (refers to active imagination, aesthetic sensitivity, preference for variety,intellectual curiosity, and independence of judgment) is one of the traits, which is lessstudied in risky behaviour research. However, some evidence is found for significantpositive relationship (Arthur and Graziano, 1996; Sumer et al., 2005). Anyway scholarsinvite more extensive studies on the role of openness for driving behaviour and itsconsequences (Clarke and Robertson, 2005; Sumer et al., 2005).

People who are low in agreeableness are less able to cooperate with others, usuallyare less helpful and more selfish, so they demonstrate high levels of risk taking on theroad (Clarke and Robertson, 2005; Sumer et al., 2005). Still the research is not extensiveand unclear, e.g. Arthur and Graziano (1996) have not found significant correlationbetween agreeableness and driving behaviour.

Conscientiousness has the clearest and the strongest contribution to the explanationof risk-taking behaviour, as well as risky driving behaviour. Individuals who are low inconscientiousness show the lack of discipline, dutifulness, absence of logical andsystematic approach to decision making, lack of goal setting and failure to follow rules.Such personality trait leads to higher involvement in risky driving behaviours

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(Arthur and Graziano, 1996; Clarke and Robertson, 2005; Oltedal and Rundmo, 2006;Sumer et al., 2005).

Generalizing the results mentioned above the importance of personality traits forrisky driving is obvious; the directions of relationships are equivocal. Also, theattention must be paid that given research results are derived from general populationand it is difficult to conclude that the same relationship patterns will be repeated inprofessionals’ sample. Based on the previous studies, we propose that higherextraversion, agreeableness, conscientiousness, and lower neuroticism and opennesslead to less prominent risky driving of professional drivers.

Controversial results might be explained by some methodological limitations inprevious investigations – different assessment tools (Clarke and Robertson, 2005),simple correlations and regression analysis. Here, we hypothesize that compositepersonality profiles have higher predictive value for risky driving behaviour rather thansingle personality trait. As far as personality profiles are not derived in the previousstudies, we do not make any presumptions and propose only exploratory results.

If the risky driving is studied in professionals, organizational factors shouldnecessarily be taken into account. Scholars suggest that emphasis within safety issuehas been shifted away from individual factors, which influence involvement in crashesand accidents towards organizational factors (Neal et al., 2000). In this paper,organizational safety climate and work motivation are taken as a focus. Safety climaterefers to workforce perceptions of the value and importance associated with safety inorganization (Newnam et al., 2005). It might include several components like perceptionsabout how committed managers and supervisors are to employees’ safety, how wellsafety policies are communicated to employees, how work pressure is compliant withsafety procedures, are employees trained to follow safety rules, etc. (Wills et al., 2005).

Research show that at least some components of safety climate predict overallself-reported driver behaviour and accident involvement (Rowland et al., 2007;Wills et al., 2005, 2006; Newnam et al., 2005). In this study, we also expect that riskydriving of professionals is related to safety climate and its components – those driverswho report poor safety climate in their organizations tend to drive in risky manner.

As the sample of professional drivers is not frequent in investigations concerningrisky driving and safe behaviour (especially in Lithuania), there are no abundantresearch results about the importance of work motivation in this area. Some indirectresearch results (Sjoberg, 2007; Bjorklund, 2007) let us presume that willingness towork might be positively related to safe driving of professionals. Also, it is possiblethat safe organizational climate increases employees’ work motivation and interactionof work motivation and safety climate might contribute to risky driving. In thisinvestigation, work motivation was added as an expressed driver’s attitude towardswork (i.e. willingness to work).

Any single variable either individual or organizational does not providecomprehensive understanding of human behaviour and its implications. Theintegrative model of factors, related to risky driving of professionals might be ofgreater value. Therefore, based on the existing results, we hypothesize that integrativemodel might explain risky driving behaviour of professional drivers. We propose thatpersonality of the driver has both direct and indirect influence on risky driving. Someauthors argue that safety procedures and rules might be differently perceived due todifferent personal characteristics of employees (Newnam et al., 2005). The same goes

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for work motivation – individual differences of employees predict different levels andsources of work motivation (Liesiene and Endriulaitiene, 2008). Therefore, the effect ofpersonality on risky driving is moderated by perceived organizational safety climateand work motivation.

MethodSubjectsThe sample consisted of 166 professional drivers (males) who drive small bussesand heavy trucks from different Lithuanian organizations (mean age 41.71, SD ¼ 10.10years). Mean experience in driving was 20.67, SD ¼ 9.64 years. Only those organizationsand drivers who agreed to participate were included in the study. The overall responserate was close to 75 per cent.

InstrumentsThe Big Five Inventory (BFI) (Benet-Martinez and John, 1998) was employed to measurefive personality traits. BFI consists of 44 items, allowing researchers quickly andefficiently assess five personality dimensions – neuroticism (Cronbach’s a ¼ 0.57),extraversion (Cronbach’s a ¼ 0.60), openness (Cronbach’s a ¼ 0.80), agreeableness(Cronbach’s a ¼ 0.56), and conscientiousness (Cronbach’s a ¼ 0.60). BFI was adaptedto Lithuanian language following the standard translation and back translationprocedure for an international project.

Risky driving behaviour was assessed with the help of Lithuanian version of thedriver behaviour questionnaire (Lawton et al., 1997). It is a 24-item inventory thatyields three broad factors of self-reported driving behaviour: violations (Cronbach’sa ¼ 0.75), errors (Cronbach’s a ¼ 0.77), and lapses (Cronbach’s a ¼ 0.56). Cronbach’sa for the whole scale was 0.81. In this study, we used a two-factor solution, as factors oferrors and lapses were correlated (Pearson’s rho was 0.40, p , 0.001). The factor“errors” consisted of 17 items, Cronbach’s a ¼ 0.80, the factor “violations” consisted ofsix items, Cronbach’s a ¼ 0.74), they explained 30 per cent of data variance. One itemwas excluded from further analyses due to unsatisfactory factor loading (,0.30).

Work motivation was measured by ten-item scale that was constructed according tothe previous research (Sjoberg et al., 2005; Sjoberg, 2007; Storseth, 2006; Bagdoniene et al.,2005). The items were phrased as: “do you feel stimulated by your work tasks?”, “wouldyou like to spend more time at work?”, “is your work motivating?”, etc. (five-point scalesranging from 1 – “never” to 5 – “always“). The internal consistency (Cronbach’sa) of thescale was 0.76.

The safety climate questionnaire was 35-item survey with six underlying factors(communication and procedures, work pressure, management commitment,relationships, driver training, and safety rules). In the current study, we usedmodified for drivers version developed by Wills et al. (2005). The item examples are:“driver safety is seen as an important part of fleet management in this organization”and “management are committed to driver safety” (five-point scales ranging from 1 –“never” to 5 – “always”). Six factors explained 69 per cent of data variance, internalconsistency of six factors was as follows – factor 1 “communication and procedures”,13 items, Cronbach’s a ¼ 0.92; factor 2 “work pressure”, seven items, Cronbach’sa ¼ 0.86; factor 3 “management commitment”, four items, Cronbach’s a ¼ 0.84; factor

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4 “relationships”, five items, Cronbach’s a ¼ 0.82; factor 5 “driver training”, threeitems, Cronbach’s a ¼ 0.83; factor 6 “safety rules”, three items, Cronbach’s a ¼ 0.65.

Participants were also asked to indicate their age, frequency of driving, vehicle thatthey drive for occupational purposes, the number of accidents and offences during thelast year.

ResultsFirst of all the descriptives of driving behaviour, personality traits, work motivation,and components of safety climate are introduced (Table I). As it is seen, means ofdriving behaviour, work motivation scales are moved towards minimum, while meansof safety climate scales are slightly moved towards maximum.

Testing the hypotheses about the relationships between risky driving and othervariables analysed here, the correlation analysis was run (Table II). As it was expected,risky driving is related with personality traits of the driver (except openness). Thosedrivers, who scored lower on extraversion, agreeableness, conscientiousness, andhigher on neuroticism, tend to drive in more risky manner. Interestingly, this refersonly to general score of driving behaviour and errors while driving, but not toviolations. Driving violations has only small negative correlation with neuroticism.Personality traits have higher overall correlations then other variables, but still fromsmall (0.18) to moderate (0.38). Risky driving is correlated with work motivation ofprofessional drivers. Respondents with lower motivation to work tend to report morefrequent violent driving. The correlation between driving behaviour and general scoreof safety climate is not significant. Anyway, small negative correlations are observedin some subscales. Drivers, who report that safety rules are followed in theirorganization under any circumstances, tend to make less driving errors and violations.Those, who experience less work pressure and have good relationships in theirorganizations, report less frequent errors while driving. Work motivation did notcorrelate with perceived safety climate and its subscales (except training withcorrelation 20.174, p ¼ 0.023).

n Mean SD Minimum Maximum

dbq: general score 170 18.1 8.63 0 44dbq: violations 170 5.4 3.73 0 21dbq: errors 170 11.8 6.14 0 32scq: safety rules 168 11.9 2.42 6 15scq: communication procedures 168 49.1 10.12 24 65scq: work pressure 168 27.0 5.04 11 35scq: management commitment 169 15.0 3.94 4 20scq: relationships 168 19.5 3.45 10 25scq: training 169 11.5 2.99 3 15scq: general score 166 134.0 24.92 66 175Extraversion 170 25.2 3.48 16 35Agreeableness 169 28.9 3.98 17 40Conscientiousness 170 30.2 4.07 23 40Neuroticism 170 14.9 3.24 6 25Openess 170 23.3 4.66 12 35Work motivation 170 32.1 5.69 13 44

Table I.Descriptives of drivingbehaviour, personalitytraits, work motivation,and safety climate

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It was hypothesized that higher extraversion, agreeableness, conscientiousness, andlower neuroticism and openness is associated with risky driving of professional drivers.The results of the study confirmed this hypothesis except for openness. Univariateanalysis was used to explore the amount of variance of driving behaviour explained byeach personality trait separately and all traits together. The results are placed inTable III. Single personality traits explain very few (from 3 to 12 per cent) of drivingbehaviour variance in professionals, but all traits, except openness have statisticallysignificant contribution in explaining driving behaviour ( p , 0.05). As single variableconscientiousness has the highest explanatory value for driving behaviour (12 per cent),while other traits can explain only 3-6 per cent of driving behaviour. All personalitytraits together explain 13 per cent of driving behaviour, similar as conscientiousnessalone. When all traits are added to analysis, conscientiousness remains only onesignificant variable that explains studied occupational behaviour.

Literature and results of this study suggests that personality traits areinterconnected. So, here it was presumed that personality traits compose differentprofiles of personality. For that purpose, a cluster analysis was conducted, includingfive personality traits as grouping variables. In order to make comparable data acrossthe scales, values have been transformed to T scores. K-means cluster analysis wasapplied. Analysis was started with two-cluster solution, and number of clusterswas manually added until the solution became meaningless. Three-cluster solutionwas defined as the most appropriate (Figure 1), because four-cluster solution revealedtwo out of four clusters that were hardly differentiable. About 30.2 per cent of samplebelongs to the first cluster titled “socially oriented” (people belonging to this grouphave relatively high scores of all traits and low score on neuroticism). The largestgroup of drivers (almost half of the sample) could be referred to “defensive”respondents, whose scores of all personality traits is very close to overall mean ofsample (second cluster). Finally, the last group (third cluster) includes respondents,who have predominant neuroticism and openness to experience and rather low scoreson other personality traits (further this cluster is called “emotionally unstable”). About20 per cent of the sample belongs to this group.

dbq: general score dbq: violations dbq: errors

scq: safety rules 2 0.228** 2 0.191* 2 0.201**

scq: communication procedures 20.086 20.011 20.115scq: work pressure 2 0.205** 20.089 2 0.185*

scq: management commitment 20.019 20.026 20.033scq: relationships 2 0.161* 20.007 2 0.212**

scq: training 20.136 20.107 20.129scq: general score 20.132 20.049 20.148work motivation 2 0.175* 2 0.173* 20.108Extraversion 2 0.180* 20.001 2 0.226**

Agreeableness 2 0.187* 20.012 2 0.250***

Conscientiousness 2 0.353*** 20.133 2 0.378***

Neuroticism 0.309*** 0.191* 0.306***

Openess 0.110 0.012 0.118

Note: Significant at: *p , 0.05, **p , 0.01, and ***p , 0.001

Table II.Correlations between

driving behaviour andsafety climate,

personality traits, workmotivation

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Driving behaviour of drivers’, who belong to different clusters, was compared.One-way ANOVA with post hoc Scheffe test was used. Representatives of clusters didnot differ in violations while driving ( p . 0.05). “Socially oriented” drivers have thelowest scores (15.0) of general driving behaviour scale and driving errors scale (9.3),

Source Type III sum of squares df Mean square F Sig.

Corrected model 479.88 1 479.88 6.66 0.011Intercept 2,912.51 1 2,912.51 40.41 ,0.001Extraversion 479.88 1 479.88 6.66 0.011Error 12,109.77 168 72.08Total 68,392 170Corrected total 12,589.65 169R 2 ¼ 0.038 (adjusted R 2 ¼ 0.032)Corrected model 509.37 1 509.37 7.33 0.007Intercept 2,940.00 1 2,940.00 42.33 ,0.001Agreeableness 509.37 1 509.37 7.33 0.007Error 11,598.61 167 69.45Total 66,792 169Corrected total 12,107.98 168R 2 ¼ 0.042 (adjusted R 2 ¼ 0.036)Corrected model 1,587.32 1 1,587.32 24.24 ,0.001Intercept 5,032.67 1 5,032.67 76.85 ,0.001Conscientiousness 1,587.32 1 1,587.32 24.24 , 0.001Error 11,002.33 168 65.49Total 68,392 170Corrected total 12,589.65 169R 2 ¼ 0.126 (adjusted R 2 ¼ 0.121)Corrected model 792.39 1 792.39 11.28 0.001Intercept 514.64 1 514.64 7.33 0.007Neuroticism 792.39 1 792.39 11.28 0.001Error 11,797.26 168 70.22Total 68,392 170Corrected total 12,589.65 169R 2 ¼ 0.063 (adjusted R 2 ¼ 0.057)Corrected model 40.83 1 40.83 0.55 0.461Intercept 1,591.64 1 1,591.64 21.31 ,0.001Openness 40.83 1 40.83 0.55 0.461Error 12,548.82 168 74.70Total 68,392 170Corrected total 12,589.65 169R 2 ¼ 0.003 (adjusted R 2 ¼ 20.003)Corrected model 1,919.39 5 383.88 6.14 ,0.001Intercept 945.04 1 945.04 15.12 ,0.000

Extraversion 92.43 1 92.43 1.48 0.226Agreeableness 2.20 1 2.20 0.04 0.851Conscientiousness 692.54 1 692.54 11.08 0.001Neuroticism 101.52 1 101.52 1.62 0.204Openness 169.87 1 169.87 2.72 0.101

Error 10,188.59 163 62.51Total 66,792 169Corrected total 12,107.98 168R 2 ¼ 0.159 (adjusted R 2 ¼ 0.133)

Table III.Analyses of variancefor risky driving andpersonality traits

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when comparing with “defensives” (18.7 and 12.3) and “emotionally unstables” (20.7and 14.1) (F(2,166) ¼ 5.503, p ¼ 0.005 for driving behaviour; F(2,166) ¼ 7.592, p ¼ 0.001for driving errors). “Defensive” and “emotionally unstable” drivers did not differaccording to driving behaviour and driving errors.

Spearman correlations among driving behaviour, safety climate, and workmotivation in different clusters were calculated. For drivers, who were referred to“defensive” and “emotionally unstable”, only few significant correlations were found.Driving violations were negatively correlated with work motivation (0.31; p ¼ 0.004)and safety rules (20.22; p ¼ 0.043) for “defensive” respondents. Driving errors werepositively correlated with safety communications and procedures (0.34; p ¼ 0.048) for“emotionally unstable” participants. Almost all significant correlations amongvariables were revealed for “socially oriented” drivers. Driving errors as well as thegeneral score of driving behaviour were related with work motivation and componentsof perceived safety climate (except management commitment to safety). Whilecorrelations for driving errors are bigger than for general score of driving behaviour,correlations for driving errors are presented here. “Socially oriented” drivers, who havehigher work motivation (20.32; p ¼ 0.02), perceive safety rules as working well intheir organization (20.45; p ¼ 0.001), safety communications and procedures beingeffective (20.46; p ¼ 0.001), little pressure at work (20.45; p ¼ 0.001), relationships atwork as good (20.49; p , 0.001), receiving training towards safety (20.43; p ¼ 0.002),tend to make less errors during driving.

Finally, a structural equation model was produced for relationships betweenpersonality traits, work motivation, perceived safety climate at work, and drivingbehaviour. As model is saturated due to relations among all variables, data fit indexes losethe meaningfulness (x 2 ¼ 0.000 and df ¼ 1) and are not introduced here. Saturated modelshows no effect of work motivation and perceived safety climate on driving behaviour,which is explained only by conscientiousness. Conscientiousness, agreeableness,

Figure 1.Profiles of personalitytraits in three-cluster

solution

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and extraversion account for work motivation, and conscientiousness, agreeableness, andneuroticism explain perception of safety climate in organization. Personality traits havesignificant covariance, but no covariance have been found between work motivation andsafety climate. In order to have the model, which is not saturated, all non-significant effectswere removed, until effects all included in the model became significant. Model shown inFigure 2 met all goodness of fit criteria: x 2 ¼ 22.384; df ¼ 13; p ¼ 0.05; comparative fitindex ¼ 0.957; root mean square error of approximation ¼ 0.066 (the method ofmaximum likelihood was used). It is seen from the analysis that work motivation andgeneral score of safety climate have no impact on driving behaviour. The only factor,which contributes to explanation of risky driving, is conscientiousness. Conscientiousnesshas impact to work motivation and perceived safety climate. Lower agreeableness andhigher extraversion are related with higher work motivation. Also, it has to be noted thatpersonality traits have significant covariance, indicating neuroticism as the most differentpersonality trait in comparison with others (all traits have negative covariance withneuroticism and positive covariance with each other).

Separate models were created for prognosis of driving violations and driving errors.While these models revealed very similar results like in prognosis of general scale ofdriving behaviour, separate models are not introduced here.

Figure 2.The model of risky drivingbehaviour

0.941

0.933–0.359

0.390

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dbq: generalscore

Workmotivation

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Note: Standardized regression weights are displayed on the arrows

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DiscussionThis study explored the relationships between professional driver’s personality profile,work motivation, perceptions of organizational safety climate and occupationalperformance – risky or non-risky driving. Therefore, the study contributes to the fieldof occupational safety by integrating individual attributes with organizational factors.In general, we found that personality is very important in occupational settings,predicting work motivation, perceived safety climate in organization as well asoccupational performance (risky or safe driving).

Consistent with other research investigating personality traits in driving context(Arthur and Graziano, 1996; Sumer et al., 2005), we have found that conscientiousnesshad stronger correlations with risky driving behaviour than other personality traits inprofessional drivers’ sample. This trait was also related with higher levels of workmotivation and higher levels of perceived safety climate. The results supported ourhypotheses that drivers with higher levels of extraversion, agreeableness,conscientiousness and lower levels of neuroticism are less prone to risky driving.We supported the ideas that responsiveness of conscientious individuals to socialresponsibility and performance norms, low aggressiveness, sociability and competentcommunication of agreeable and extravert individuals make them engage in less riskydriving (Arthur and Graziano, 1996; Clarke and Robertson, 2005; Lajunen, 2001;Sumer et al., 2005; Schwebel et al., 2007). Contrary to Sumer et al. (2005) we foundmoderate correlation between neuroticism and risky driving. Maybe high associationbetween neuroticism and stress, emphasized by Clarke and Robertson (2005), mightexplain this result in Lithuanian sample. Also, it must be taken into account thatneuroticism was important trait, differentiating personality profiles of professionaldrivers, so it is possible that in Lithuania this personality trait acts as an importantpredictor. Lajunen (2001) paid attention that culture and nationality might beimportant in traffic safety results. On the other hand, taken into general model andcontext of all personality traits together, neuroticism was not important predictor ofrisky driving. So, the result is contradictory and requiring future investigations.Contrary to expectations we did not fount the significant relation between opennessand risky driving. Sumer et al. (2005) stated that openness is associated with trainingproficiency so that it might be desirable for organizational productivity. It mightdepend upon organization (that was not controlled in our study) that someorganizations relate productivity with safety and quality, others with quantity nomatter of safety. So, this might eliminate the effect of openness in occupational drivingcontext.

Based on current data, we conclude that separate personality traits quite poorly addto the explanation of risky driving of professionals (they accounted only for 13 per centof variance) possibly due to inter-correlations among them. Therefore, we suggest thatcomposite personality profiles may be more reasonable way to analyse the impact ofpersonality to behaviour. Our sample was clustered into three personality profiles. Asmore favourable profile in the context of risky driving (low risk), we treat the group of“socially oriented” drivers – those, who have low neuroticism and high scores of othertraits. As it was expected and in line with previous research for these drivers thecorrelations between work motivation, safety climate, and occupational performancewere significant (Neal et al., 2000; Newnam et al., 2005). Generally stated, higher levelsof work motivation and having perception of organizational climate being safe resulted

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in less risky driving. Two other profiles of drivers are referred to risk takers –“emotionally unstable” (predominant neuroticism and openness to experience and lowother scores) and “defensives” (mean scores of all traits). Interestingly, rare andinconsistent correlations among investigated variables emerged in these groups.Results encourage making a conclusion, that “socially oriented” drivers are susceptibleto organizational factors and management safety efforts, while “emotionally unstable”ones are probably driven by neuroticism and non-responsive to external influences(like, motivating efforts or strengthening safety politics). Following the results ofcorrelation analysis and driving behaviour comparisons we guess, that “defensive”drivers are quite similar to “emotionally unstable”, but due to social desirability theydo not reveal actual personality predispositions (Owsley et al., 2003). This presumptionis still very speculative and calls for future investigations.

It has to be noted that in this investigation driving errors mostly account for riskydriving behaviour rather than intentional violations. Contrary to previous results(Reason et al., 1990; Sevelyte and Endriulaitiene, 2009) personality traits and profileswere more related to driving errors than to violations in the sample of professionaldrivers. Reason et al. (1990) suggested that violations have more social andmotivational nature and should be related to personality, while errors have moreinformation processing background. We presume that our contradictory results weredue to special sample and occupational pressure. Professional drivers denied violationsthey commit, because they try to protect their work position. Errors are perceived asless intentional and less socially threatening by drivers and management, so moreacceptable, safe, and overt.

Contrary to our expectations the effect of personality on risky driving was notmoderated by perceived organizational safety climate and work motivation in the finalmodel when all variables were employed. As it was mentioned above personality traits(conscientiousness especially) produced the largest number of paths as predictors ofwork motivation, safety climate, and driving behaviour. Work motivation andperceived safety climate were independent factors and unrelated to risky driving. Thepossible explanation of unexpected results is that our sample is overrepresented by“emotionally unstable” and “defensive” drivers (about 70 per cent of subjects) whoserisky occupational performance pattern was not related to organizational factorsinvestigated here. So, the final model is more suitable to describe the behaviour ofdrivers who are prone to risky driving, report higher level of neuroticism and arereluctant to disclose themselves. Of course this explanation requires furtherexplorations and confirmation.

There were several limitations in the current study, therefore, the results should beinterpreted and generalized with caution. The first issue is measurement based onself-report. Self-report data are the major concern in most psychological studies due topossible reporting biases in answers. Respondents might be not enough experienced inself-reflection when they describe their personality traits. Also, professional driversmight be fearful of their supervisors and not to disclose behaviours that might betreated as irresponsible driving style (Wallace et al., 2006).

The second limitation is relatively small and not random sample size. We encourageother scientists to replicate the similar procedure in larger and more differentiatedsamples (e.g. taxi drivers, bus drivers, etc.). Third, cross-sectional methodology doesnot allow drawing causal statements about relations investigated in this study.

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Although structural linear modelling gave the opportunity to assume causal paths inrelations, longitudinal design would be more preferable for more confident andsophisticated data.

Not withstanding limitations the results of the present investigation have expandedunderstanding the role of personality and organizational interaction in predictingoccupational safety of professional drivers. The main implications for practitioners aretwo-fold. First of all, it is important to develop such recruitment and selection proceduresthat help to identify drivers with safe driving personality profile, as drivers’ personalitycontribute to their own and organizational safety. Also, drivers’ personality playssignificant role in organizational factors, such as work motivation, safety climateperceptions that are related to organizational effectiveness (Liesiene and Endriulaitiene,2008). On the other hand, investments into social and organizational enhancementsmight be sometimes doomed to failure in advance. Data of our study revealed that onlypart of drivers are sensitive to safety politics and organizational efforts to enhance safedriving behaviour. Organizations that hire drivers with not safe personality profileshould look for different preventive organizational factors, while traditionalinterventions like promotion of safety climate in organization or motivating to workfail to be effective.

Conclusions. Personality is very important in occupational settings, predicting work

motivation, perceived safety climate in organization as well as occupationalperformance (risky or safe driving). The effect of personality on risky drivingwas not moderated by perceived organizational safety climate and workmotivation. Work motivation and perceived safety climate were independentfactors related to personality taits, but unrelated to risky driving.

. Drivers with higher levels of extraversion, agreeableness, conscientiousness andlower levels of neuroticism were less prone to risky driving. Conscientiousnesshad stronger correlations with risky driving behaviour, higher levels of workmotivation and higher levels of perceived safety climate than other personalitytraits in professional drivers’ sample.

. Composite personality profiles rather than single traits may be more reasonableway to analyse the impact of personality to occupational behaviour. “Sociallyoriented” drivers – those, who had low neuroticism and high scores of othertraits, were less prone to risky driving; for these drivers the correlations amongwork motivation, safety climate, and occupational performance were significant.Rare and inconsistent correlations among work motivation, safety climate, andrisky driving emerged in “emotionally unstable” (predominant neuroticism andopenness to experience and low other scores) and “defensive” (mean scores of alltraits) groups of drivers who were referred as risk takers.

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About the authorsLaura Seibokaite, received her PhD from the Vytautas Magnus University, Faculty of SocialSciences, where she works as a Lecturer. Her research interests are: issues and difficulties ofadolescence, problem behaviour in adolescence, risk-taking behaviour in applied fieldsof psychology (emigration, driving, etc.). She has published several articles mainly in the field ofrisky and problem behaviour. Laura Seibokaite is the corresponding author and can be contactedat: l.seibokaite@smf.vdu.lt

Aukse Endriulaitiene received her PhD from the Vytautas Magnus University, Faculty ofSocial Sciences, where she works as an Associated Professor and Chair of General PsychologyDepartment. Her research interests are human recourse management and psychology,transformational leadership, risk-taking behaviour and decisions. She has published more than20 articles and has experience in academic journal co-editing.

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