Transport mode preferences, risk perception and worry in a Norwegian urban population

Transport mode preferences, risk perception and worry in a Norwegian urban population

Accident Analysis and Prevention 50 (2013) 698–704 Contents lists available at SciVerse ScienceDirect Accident Analysis and Prevention journal homep...

238KB Sizes 0 Downloads 22 Views

Accident Analysis and Prevention 50 (2013) 698–704

Contents lists available at SciVerse ScienceDirect

Accident Analysis and Prevention journal homepage: www.elsevier.com/locate/aap

Transport mode preferences, risk perception and worry in a Norwegian urban population Isabelle Roche-Cerasi a,∗ , Torbjørn Rundmo b , Johannes Foss Sigurdson b , Dagfinn Moe a a b

SINTEF, Transport Research, Trondheim, Norway Norwegian University of Science and Technology, Department of Psychology, Trondheim, Norway

a r t i c l e

i n f o

Article history: Received 18 May 2011 Received in revised form 10 May 2012 Accepted 19 June 2012 Keywords: Risk perception Worry Transportation mode preferences Urban transport user

a b s t r a c t The main aim of the present study was to compare risk perception among Norwegians (n = 512) living in the region of Oslo. This study was part of an ERANET 13 project entitled PETRIS, Perception of transport risk in France and Norway. The data collection was carried out in January 2011. The response rate was 51 percent. The results showed that respondents, divided in two groups according to their transport mode preferences, assessed differently risk perception in public and private transportation. Respondents who preferred collective transportation assessed the probability of experiencing criminality in collective transport modes as higher than those who preferred private modes. They were also more worried of experiencing accidents, criminality, and terror attacks in collective transportation. The relationship between transport mode preferences and use, risk perception and worry are discussed. © 2012 Published by Elsevier Ltd.

Risk perception related to accidents and incidents due to criminal acts and terrorism may be associated to transport mode use and preferences. These transport related events may have serious consequences and can be important for transport users when using and preferring means of transport. This study aims at examining relations between the perceived risk of experiencing such events and transport mode use and preferences. Other risk judgments such as technological and environmental risk judgments were not investigated in this research. Risk perception is an important factor in transport safety and concerns all types of transport related risks, including accidental risks and other, non-accidental, such as risks related to criminality and terrorism. The higher rate of accidents involving young male drivers could be explained by the fact that male drivers misjudge risks to be lower than women do and that less experienced drivers carry more risk than older ones. Previous studies show that the perceived probability and the judgment of the consequences are important in risk perception (Sjöberg et al., 2004). In this study it is assumed that the risk perception of experiencing an accident is represented by the subjective probability assessment times the judgment of the severity of consequences (Rundmo, 2002; Sjöberg et al., 2004). The majority of studies were carried out on risks in collective transportation where the severity of consequences is considered as catastrophic; an accident leading generally to a large number of

∗ Corresponding author. Tel.: +47 99330858; fax: +47 73593000. E-mail address: [email protected] (I. Roche-Cerasi). 0001-4575/$ – see front matter © 2012 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.aap.2012.06.020

injuries and killed. The generalisation of these results to evaluate risk perception in types of transportation where the severity of consequences is more chronic than catastrophic must be taken with precaution (Rundmo et al., 2011). When the probability of experiencing an accident is low, transport users may not lay weight on consequences and therefore these variables may not have any influence on transport mode use or preferences. This is the case for airplane accidents where it is hypothesised that the severity of consequences has generally no influence on decisions about travelling by airplane. However in private transportation, the probability of experiencing an accident may be large enough to be associated with the use of transport modes. Rundmo et al. (2011) argued that if the probability is perceived as high enough, its assessment will be associated with decisions to use transport modes and a shift from a transport mode to another may occur, even if the severity of consequences is considered as minor. In that case, the judgment of consequences has no influence on decisions to use transport modes. In addition to perceived risk, worry may also be related to transportation mode use and choices. Worry is defined as ‘mental distress or agitation resulting from concern usually for something impending or anticipated’ in the Merriam Webster dictionary. Rundmo (2002) implied that when concerned about a hazard, thinking about it may evoke worry, and hence thinking about a risk source was found to be an important variable. Specific affective reactions (anticipated worry) when thinking about probability and consequences related to specific risk sources may be caused by the cognitive evaluation, i.e. probability judgements as well as evaluations of consequences. This is consistent with studies carried out by Rundmo and Sjöberg (1996),

I. Roche-Cerasi et al. / Accident Analysis and Prevention 50 (2013) 698–704

Rundmo et al. (2011), and Baron et al. (2000) showing that worry may be affected by probability assessments and associated with decisions related to transport mode use (Rundmo and Moen, 2007). Males and females perceive risk differently and generally females evaluate risks to be higher than men (Rundmo and Jørgensen, 2009). Worry was found to be important for females whereas probability is more important for males (Rundmo et al., 2011). Women rely more on affective evaluations and they feel more vulnerable when facing criminality. They had a tendency to be more worried about experiencing accidents in both collective and private transportation (Rundmo et al., 2011). Other demographic variables, such as age and education, have also been found to influence risk assessment. Previous studies showed that young drivers had a tendency to underestimate their risk compared to older drivers (Moe, 1986). The risk is also evaluated as lower when subjects have higher education. Gender, age and education are therefore expected to have an influence on worry of expected negative events in transport. In conclusion, the affective response should be taken into consideration in studies about risk perception in transport. Studying perceived risk and worry across the different types of transport modes is complex. Rundmo and Moen (2007) and Gröndahl-Backer et al. (2009) found that risk perception in transport may be divided into collective and private transport modes. In the present study, differences in perceived risk and worry for Norwegians living in the region of Oslo, who use and/or prefer either motorised (car and motorcycle) and non-motorised (bicycle and walking) private transport modes or public rail and road transport modes, were taken into consideration. The project was focused on the perception of risks associated with urban transportation modes (e.g. mode preferred to travel to work); therefore air transportation was not part of the study. Three variables are presented in this article and were entered in this analysis: probability assessment, severity of consequences and worry. The specific aims of the present study were to examine the following: • To study differences in transport mode use and preferences in a Norwegian urban population. • To study the perceived risk and worry of accident, violence and terrorism in transport. • To study the relationship between transport mode preferences, risk perception and worry. 1. Methods 1.1. Procedure The results are based on a telephone survey questionnaire carried out among a sample of the Norwegian population aged from 18 to 79 years (n = 512). The representative sample, living in the region of Oslo was provided by the national registration office. The respondents received an informative letter about the project and an interviewer called the respondents in January 2011. The response rate was 51 percent. 1.2. Sample A list of 3000 persons was provided by the national registration office, representing a minimum of 200 persons per age group for each gender. Of these 3000 respondents, 2047 were chosen after excluding professional drivers, persons who could not be reached, or not living anymore in the region of Oslo. The interviewers contacted 1007 persons and 512 responded positively. The response rate was in total 51 percent; the lowest score of 39 percent was

699

for women over 66 years old and the highest rate of 70 percent for women between 26 and 35 years old. The data collection was carried out during the period 4–18 January 2011. Of the 512 respondents 255 (49.8%) were males and 257 (50.2%) were females and all the respondents were above 18 years old. The sample is formed of around 43 persons per age group and gender. The age of the respondents ranged from 18 to over 79 years (mean = 45.38, standard deviation = 17.56). A total of 4.9 percent (n = 170) of the sample has primary or secondary school education as their highest completed education level. About 14 percent have a vocational or a general high school education as their highest completed education level. A high proportion of the sample (66.8%, n = 342) has a higher education level from college or university. There are no significant differences regarding age, gender and education between the sample and the Norwegian population living in the capital of Norway, as the education level is higher in the Oslo region than overall in the country. 1.3. Questionnaire The questionnaire was divided into seven parts related to accessibility of transport, transportation mode use, risk perception, worry, own experiences of accident and violence, perceived control and trust in the authorities. The first part concerned the transport modes available where the respondents live and work. The respondents were then asked how often they used public (bus, train, subway, tramway and ferry) and private transport modes (car, motorcycle, bicycle and as a pedestrian) on a five-point evaluation scale ranging from “never” to “very often”. They were also asked which transport mode they would have preferred to travel to work. “If you could choose freely between all the transport modes, which one would you rather choose to travel to your workplace/school?”, and “How often do you use the following transport modes to travel to your workplace/school?” to find the groups using private or public transport modes to travel to work. Ferry and motorcycle/scooter were excluded of the analysis due to a small number of users. The third part of the questionnaire included the evaluation of risk perception related to each of nine transport modes. The respondents were asked to assess the probability that they could experience an accident or a physical assault when using transport modes. A five-point evaluation scale ranging from “very unlikely” to “very likely” was used for all the measurements. The respondents were asked to assess the severity of consequences if an accident happened for each of the nine transport modes on a five-point evaluation scale ranging from “not serious at all” to “very serious”. In addition the respondents were also asked to assess the probability of experiencing a terror attack when using public transport modes. In the fourth part of the questionnaire, worry was measured by asking how worried the respondents are, when thinking about the probability of an accident, a physical assault or a terror attack when using public and private transport modes. A five-point evaluation scale ranging from “not at all worried” to “very worried” was used. In addition in the fifth part of the questionnaire, the respondents were asked about their own experience and the experience of their family members related to accident and violence in transport. The likelihood, severity of consequences and worry about accident, criminality and terror were assessed separately in this study to avoid respondent confusion. 1.4. Statistical analysis Cronbach’s ˛, as well as average corrected item – total correlations, were used to examine the reliability and internal consistency of measurement instruments and according to Nunnally criterion, an ˛ value over .70 should indicate a reliable scale (Nunnaly, 1978;

700

I. Roche-Cerasi et al. / Accident Analysis and Prevention 50 (2013) 698–704

Table 1 Reliability of indices. Measures Risk perception

Accident

Violence Worry

Accident Violence

Dimensions

Number of indicators

Cronbach’s ˛

Average corrected item – total correlation

Probability – public transport Probability – private transport Severity of consequences – public transport Severity of consequences – private transport Probability – public transport Probability – private transport

4 3 4 3 4 3

.911 .736 .910 .759 .948 .709

.80 .56 .80 .59 .88 .55

Worry – public transport Worry – private transport Worry –public transport Worry – private transport

4 3 4 3

.927 .845 .961 .809

.83 .71 .91 .69

Nordfjærn and Rundmo, 2010). These values were assessed for the likelihood, severity of consequences and worry about accident and criminality. A cluster analysis was used to determine groups of transportation mode users. To find the number of clusters, a hierarchical solution was used. To test the ideal cluster solution a k-mean procedure was applied, based on raw-scores. The respondents were also asked to answer questions about transportation mode preferences. Pearson’s correlation coefficients were used to study the relationship between transport mode preferences and use, and the variables such as gender, age, education level and driving licence possession. The mean values of the raw scores for each variable related to risk perception and worry of public and private transport modes were calculated for each respondent. To analyse differences in risk perception and worry related to transportation mode use and preferences, multivariate analyses of variance (MANOVA) were used to evaluate whether or not there were significant differences in risk perception and worry depending on which transport mode use the respondents prefer to use. Table 1 shows that the internal consistencies of the indices measuring risk perception and worry were found to be satisfactory. The Cronbach’s ˛ varied from .961 to .709 and the average corrected item – total correlation coefficients from .91 to .55. Probability assessment and worry related to terror attack in public transportation were measured by only one indicator.

Table 2 Transport mode preferences to travel to work. If you could choose freely between all the transport modes, which one would you rather choose to travel to your workplace/school?

N

Collective transport modes Bus Train Subway Tramway Private transport modes Car Bicycle Pedestrian

218 63 26 83 46 169 71 52 46

Total

387

2. Results 2.1. Transport mode preferences To examine transport mode use and preferences, the respondents were split in two groups, made of respondents who would rather choose either a public or a private transport mode to travel to work (if they could choose freely one of the seven proposed transport modes). Table 2 shows that of the 512 respondents, 218 would rather choose one of the collective transport modes while

Table 3 Cluster membership and transport mode preferences (n = 387). Transport mode preferences

Cluster 1: collective transport modes

Cluster 2: private transport modes

Chi-square Pearson value

121 97

74 95

5.23****

49 50 41 36 33 9

27 32 37 39 28 6

5.54 NS

Basic Vocational High school University/college

5 28 37 148

4 22 18 125

3.18 NS

Driving licence

No Yes

57 161

27 142

5.80****

Car at disposal

No Yes

84 134

44 125

6.72****

218

169

Gender

Women Men

Age groups

18–25 years 26–34 years 36–44 years 46–54 years 56–64 years 66+ years

Education

Total NS = non-significant. **** p < .05.

I. Roche-Cerasi et al. / Accident Analysis and Prevention 50 (2013) 698–704

701

Table 4 Cluster membership and transport mode use (n = 389). Transport mode use

Cluster 1: collective transport modes

Cluster 2: private transport modes

Chi-square Pearson value

Gender

Women Men

81 84

113 111

.07 NS

Age groups

18–25 years 26–34 years 36–44 years 46–54 years 56–64 years 66+ years

49 32 25 37 17 5

28 48 56 38 44 10

26.07*

Education

Basic Vocational High school University/college

5 18 34 108

4 20 21 169

10.92****

Driving licence

No Yes

60 105

26 198

33.82*

Car at disposal

No Yes

85 80

45 179

42.17*

165

224

Total NS = non-significant. * p < .001. **** p < .05.

169 prefer a private mode. Of the 512 respondents, 125 preferred either ferry, motorcycle/scooter or did not answer the question about their preferred mode to travel to work; these are mostly nonworking respondents. 10 respondents were found to use equally private and public modes to travel to work. Respondents who preferred ferry (1 respondent) and motorcycle/scooter (6 respondents) were taken out of the analysis due to a low number of respondents in these two groups. Table 3 shows cluster memberships of respondents who preferred either collective or private transport modes. The Chi-square Pearson values exceed 5 for three variables, gender, age groups, and driving licence. Two of these variables have a significance value smaller than .05, gender and driving licence, indicating that respondents’ gender and whether the respondent has or not a driving licence or a car at disposal had a significant effect on transport preferences. For the education level of the respondents, the Chisquare Pearson value reflects the high proportion of respondents with higher education. Cluster 1 of respondents preferring collective modes is constituted of 56 percent of women and 44 percent of men. 44 percent of women and 56 percent of men belonged to cluster 2. 62 percent of female respondents (n = 121) preferred collective modes, while for the male respondents, there is no preference. 68 percent of women under 45 years old (n = 140) and 59 percent of

men under 35 years old (n = 69) preferred public modes while 67 percent of men between 36 and 45 years old (n = 37) preferred private modes. In cluster 1, 38 percent (n = 83) preferred the subway to travel to work, while 29 percent (n = 63) would rather choose the bus. In cluster 2, 42 percent (n = 71) preferred the car whereas 31 percent (n = 52) would choose to cycle to work and 27 percent (n = 46) to walk. 2.2. Type of transport mode use Concerning the use of transport modes to travel to work, 165 of 389 respondents use collective modes while 224 respondents use private modes. 10 respondents were found using collective modes as well as private modes to travel to work. Table 4 shows cluster memberships of respondents who use either a collective or a private transport mode to travel to work. The Chi-square Pearson values exceed 5 for three variables, age groups, driving licence and education level. All these variables have a significance value smaller than .05, indicating that respondents’ age, education level and whether the respondent has or not a driving licence or a car at disposal has a significant effect on transport mode use. There is no significant association between the transport mode use and the gender of the respondents.

Table 5 Transport mode use and preferences to travel to work. How often do you use the following transport modes to travel to your workplace/school?

Collective transport modes Bus, train, subway, tramway If you could choose freely between all the transport modes, which one would you rather choose to travel to your workplace/school? Total *

p < .001.

Collective transport modes Bus, train, subway, tramway Private transport modes Car, bicycle, pedestrian

Total

Chi-square Pearson value

61.75*

Private transport modes Car, bicycle, pedestrian

128

85

213

33

133

166

161

218

379

702

I. Roche-Cerasi et al. / Accident Analysis and Prevention 50 (2013) 698–704

Table 6 The role of risk perception and worry in transport mode preferences. If you could choose freely between all the transport modes, which one would you rather choose to travel to your workplace/school? (Question 11)

Cluster 1: collective transport modes (N = 206)

Cluster 2: private transport modes (N = 159)

Mean

SD

Mean

SD

Probability accident – collective transport Probability accident – private transport Consequences accident – collective transport Consequences accident – private transport Probability violence – collective transport Probability violence – private transport Worry accident – collective transport Worry accident – private transport Worry violence – collective transport Worry violence – private transport Probability terror attack – collective transport Worry terror attack – collective transport

1.79 2.79 3.06 3.99 2.34 1.94 1.64 2.29 1.82 1.59 1.82 1.66

0.71 0.93 1.04 0.88 1.01 0.74 0.70 1.04 0.88 0.66 0.91 0.94

1.67 2.72 2.87 3.89 2.06 1.91 1.45 2.06 1.61 1.61 1.63 1.48

0.70 0.93 1.10 0.80 1.00 0.81 0.58 0.94 0.78 0.70 0.84 0.79

F-factors

1.37 NS .40 NS 2.54 NS 1.08 NS 4.77*** .00 NS 7.21*** 6.59**** 5.66**** .10 NS 3.44 NS 4.02****

Ratings of probabilities given on a 5-point scale from (1) very unlikely to (5) very likely, consequences from (1) not serious at all to (5) very serious and worry from (1) not worried at all to (5) very worried. NS = non-significant. *** p < .01. **** p < .05.

2.3. Association between transport mode use and preferences Table 5 shows transport mode use and preferences for 379 of the 512 respondents who work or are students. The value of the chisquare statistic, 61.75 is highly significant (p < .001), indicating that there were significant associations between mode use and which travel mode the respondents would rather use if they could choose freely. Mode use is related to past choices and reflects also which mode will be chosen in the future. It is important to note that in the region of Oslo, the respondents may use several modes to travel to work. The analysis showed significant differences between the two groups that preferred and used the same type of transportation, either collective or private modes. Differences were found in age group (2 = 15.10, p < .05), education level (2 = 8.79, p < .05) and whether the respondent has a car at disposal (2 = 27.59, p < .001). In the group of 128 respondents who prefer collective modes, 53 percent are women (n = 68), 61 percent (n = 78) are under 45 years old, 52 percent (n = 67) do not have a car at their disposal and 62 percent (n = 80) have a higher education level. In the group of 133 respondents who prefer private modes, 57 percent are men (n = 76), 57 percent (n = 76) are under 45 years old, 79 percent (n = 105) have a car at their disposal and 75 percent (n = 100) have a higher education level. The results showed that over 60 percent of respondents use often or very often the type of transportation they would anyhow have preferred to use to travel to work. People have a tendency to rationalise their decisions. 2.4. Differences in risk perception and worry due to transport mode preferences Multivariate analysis of variance was used to examine differences in risk perception and worry depending on which transport mode is preferred by 365 respondents, to travel to their workplace. The mean values of the raw scores for each variable were calculated in order to provide two new variables corresponding to collective and private transport. The MANOVA analysis showed that there is a significant overall difference in the judgments depending on transportation mode preferences, Wilks’  = 0.94, p < .05. Gender and age group, and whether the respondent has a car at disposal were entered as covariates in the analysis. Table 6 shows the mean values of the raw scores for each variable related to risk perception and worry, for the two clusters. The lower the mean values are in Table 6 for the clusters, the lower the probability assessment, the severity of consequences and the worry were perceived to be.

The differences were significant for worry of experiencing an accident with injuries when using both collective and private transport, (F = 7.21, p < .01, F = 6.59, p < .05). Those who preferred collective modes were more worried of experiencing accidents with both collective and private modes. Not surprisingly, the results showed low mean scores of worry for all respondents and private modes caused generally more worry about experiencing an accident than public ones. The lower the mean values are in Table 6 for the clusters, the lower the respondents were worried. Table 7 shows that the respondents who prefer collective modes are very little worried or little worried of experiencing an accident with collective transport modes (90.0 percent) and with private modes (63.1 percent). Around 20 percent are worried or very worried of experiencing an accident with car and bicycle. The respondents who prefer private transport modes are also very little worried or little worried of experiencing an accident with collective transport modes (93.8 percent) and with private modes (72.6 percent). Around 13 percent are worried or very worried of experiencing an accident with car and bicycle. Female respondents belonged more frequently to cluster 1 by statistical interference while the opposite in cluster 2 is noticed for men. Women with no driving licence belonged also more to cluster 1. The results are in accordance with the fact that in previous studies, women were generally found to be more worried than men concerning risks in transport modes (Moen, 2008). Concerning the probability assessment of being victim of an aggression in collective transportation (F = 4.77, p < .05), the worry of violence in collective transportation (F = 5.66, p < .05) and the Table 7 Percent of rated probability and worry for the two clusters. Percent (%)

Scalea

1

2

3

4

5

Probability violence – collective transport

Cluster 1 Cluster 2

24.2 34.1

40.9 39.5

15.1 14.8

17.4 8.7

2.4 2.8

Worry accident – collective transport

Cluster 1 Cluster 2

51.1 63.8

38.9 30.0

6.7 4.6

2.6 1.7

0.7 0

Worry accident – private transport

Cluster 1 Cluster 2

30.2 36.6

32.9 36.0

18.8 16.2

15.8 9.3

2.4 1.9

Worry violence – collective transport

Cluster 1 Cluster 2

45.2 57.4

38.1 29.2

9.4 9.9

6.7 3.4

0.7 0.0

Worry terror attack – collective transport

Cluster 1 Cluster 2

58.8 65.1

25.5 26.6

7.9 4.7

7.9 3.0

0.0 0.6

a Ratings of probabilities given on a 5-point scale from (1) very unlikely to (5) very likely and worry from (1) not worried at all to (5) very worried.

I. Roche-Cerasi et al. / Accident Analysis and Prevention 50 (2013) 698–704

worry of terror attack in collective modes (F = 4.02, p < .05), the differences between the two groups were smaller but statistically significant. The lower the mean values are in Table 6 for the clusters, the lower the probability assessment was. There was a tendency for those who preferred collective transportation, to perceive the probability of being victim of an aggression as higher than the group who preferred private modes. The respondents, who prefer collective modes, perceive the probability of being victim of an aggression as very unlikely or unlikely in collective transport modes (65.1 percent). 19.8 percent perceive the probability of being victim of an aggression as very likely or likely (Table 7). The respondents who prefer private transport modes also perceive the probability of being victim of an aggression as very unlikely or unlikely in collective transport modes (73.6 percent). 11.5 percent perceive the probability of being victim of an aggression as very likely or likely (Table 7). The results showed that the members of cluster 1 have indeed experienced more criminal acts than the members of cluster 2 (2 = 6.01, p < .05). They have also more often been victims of aggressions in collective transportation than those who preferred private transportation (2 = 8.78, p < .05). No significant differences were found concerning reported experiences of criminality in private transportation. The respondents were more worried of criminality and terrorism than accidents in collective transportation and the opposite was true for private transportation where respondents are more worried of experiencing an accident. The results showed that respondents of cluster 1 were also more worried of criminality and terror attacks in collective transportation than those who preferred one of the private modes. 83.3 percent of the respondents who prefer collective modes are very little worried or little worried of experiencing criminality in collective transport modes and 10.2 percent are worried or very worried of experiencing an accident with subway. 86.6 percent of the respondents who prefer private transport modes are also very little worried or little worried of experiencing an accident with collective transport modes (Table 7). 84.3 percent of the respondents who prefer collective modes and 91.7 percent of those who prefer private transportation are very little worried or little worried of experiencing terror in collective transport modes (Table 7). Although it was significant between the two clusters, an additional analysis was carried out to investigate which specific transport modes have contributed to these differences. The analysis (Wilks’  = 0.76, p < .05) showed that in cluster 1, those who preferred the bus to travel to work, are the most worried transport users of experiencing accidents (mean = 1.81, SD = 0.66) and criminality (mean = 1.99, SD = 0.95) in collective transportation; and between the respondents of cluster 2, it was the respondents who preferred the bicycle, who were more worried of accidents (mean = 1.56, SD = 0.68) and criminality (mean = 1.77, SD = 0.85) than the two other group members, preferring cars or walking. Female respondents belonged more frequently to cluster 1 who preferred the bus to travel to work while men were overrepresented by statistical interference in the group who preferred the car (2 = 20.25, p < .01). Between respondents who preferred rail transport modes, those who preferred the tramway were the most worried transport users, regarding experiencing accidents (mean = 1.62, SD = 0.72) and criminality (mean = 1.97, SD = 1.00) in collective transportation. 3. Discussion The main aim of the present study was to compare transport risk perception across individuals who lived in the region of Oslo.

703

This study was part of an ERANET 13 project between France and Norway and the survey was carried out in the two urban areas of Oslo and Paris. The weather conditions were considered as a minor problem in these urban areas and therefore not included in the survey. The cluster analysis divided the respondents in two groups according to their preferences in collective or private transport modes. The results showed that transport preferences are related to some aspects of risk perception and worry. Not surprisingly, all the results showed very low scores of probability assessment and worry for all the respondents. Previous studies showed that individuals assessed negative events as less likely to happen to them compared to others (Rundmo et al., 2011). Members of cluster 1 who preferred collective transport modes (bus, train, subway and tramway) rated probability and worry of experiencing unpleasant events in collective transport modes higher than cluster 2 who preferred private transport modes (car, bicycle, and walking). Nordfjærn and Rundmo (2010) found in a study carried out in 2008 among Norwegians that the probability of experiencing an accident and the severity of consequences in public transportation are judged to be lower than in private transportation. The probability assessment was congruent with statistics confirming that the private modes are the most risky transport modes in Norway. In the present study, differences in the probability assessment of experiencing an accident and the judgment of severity of consequences failed to reach significance between the clusters. But as expected, the mean scores are higher for private than for collective transportation, which means that the two groups judged the probability and the severity of consequences for the private transports to be higher than for collective transports (2 = 610.46, p < .001). In previous studies, consequences of airplane accidents were judged to be higher than any other transport mode. There was no significant difference in the judgment of consequences as a function of which type of urban transportation is preferred; this is as previously found by Rundmo et al. (2011). The two groups differed significantly for five predictors of risk perception: the probability of experiencing an aggression, worry about accidents, criminality and terror attacks in collective transportation and the worry about accidents when using private modes. Risk perception of experiencing incidents caused by nontransport sources was found related to transport mode use in previous studies as risk sensitivity is associated with risk perception. Rundmo et al. (2011) found that the probability assessment of experiencing criminality was related to transport mode use. The results showed that the respondents who use more often collective modes, judged the probability of experiencing criminality and terrorism to be greater than those who use preferentially private transport modes. In the present study, the mean scores in Table 6 showed that the respondents who preferred collective transportation, judged also the probability of experiencing criminality in collective transportation as higher than the respondents of the opposite group. But the probability of experiencing such events in public transportation may not be perceived as large enough to have a direct influence on transport mode choice. Transport users lay weight on consequences if the probability of such events is over a certain self-acceptance threshold. Then, they may choose to use another mode, if the severity of consequences is perceived as large enough. No significant differences were found between the clusters concerning change in travel habits after experiencing such events. 6.4 percent of the overall respondents confessed to have changed their travel habits or knew a family member who did so. Worry was found in previous studies to be an important predictor of risk evaluation (Rundmo and Moen, 2007). Rundmo et al. (2011) found significant differences in worry in a study among Norwegians where those who used private transportation

704

I. Roche-Cerasi et al. / Accident Analysis and Prevention 50 (2013) 698–704

most frequently were less worried than those who used public transportation. The present study came to an identical result. Respondents who preferred collective transportation are the most worried of experiencing an accident when they use both collective and private transport modes. Some people may be worried about driving into large cities such as Oslo (e.g. young drivers and elderly people). It could have been interesting to look at the urban size; however the samples’ size could be too small to be split into further subsamples. Cluster 1 is mostly constituted of women, which is in accordance with the finding that women are in general more worried than men (Moen, 2008). Respondents who preferred public transportation are also the most worried transport users regarding experiencing criminality and terror attack in the type of transportation they actually preferred. Significant differences were found between men and women (2 = 26.00, p < .05). Men estimate their own control over the risk of being involved in an accident when they use private or public transport modes as higher than women. 19.3 percent of men and 8.1 percent of women estimate that they have fairly good or full control over the risk in collective transportation and, 77.1 percent of men and 64.2 percent of women for private transportation. Previous studies show that people tend to estimate lower risks for them than compared to others (Nordfjærn and Rundmo, 2010). The separate analyses of worry of drivers and passengers were not part of the study but travellers may be more worried for family members, as a parent or spouse. The associations between transport mode preferences and dimensions of risk perception were mostly insignificant. A small significant difference between the clusters concerning collective transportation was only found in the probability assessment of experiencing criminality. The results indicate that transport mode use and preferences are not related to risk perception and worry. The present study has not measured behavioural intentions, only transport preferences and mode use based on self reported past mode use. Future studies should examine preferences and intentions as well as the relation between past behaviour and future use. Further investigation should also examine differences between

perceived risk and objective estimated risk in collective and private transportation. Acknowledgements The present research was given financial grants from the Norwegian Research Council of Norway in the framework of the ERANET 13 project, PETRIS (Perception of transport risk in France and Norway).

References Baron, J., Hershey, J.-C., Kunreuther, H., 2000. Determinants of priority for risk reduction: the role of worry. Retrieved 10.03.05, from http://www.sas.upenn.edu/∼baron/prot.htm. Gröndahl-Backer, A., Fyrhi, A., Ulleberg, P., Amundsen, A.H., 2009. Accidents and unpleasant incidents: worry in transport and prediction of travel behaviour. Risk Analysis 29, 1217–1226. Moe, D., 1986. Young Drivers. Relation Between Perceived and Real Ability, Behaviour Studies. TFB Report 1986. Swedish Transport and Communication Research Board, Stockholm (in Norwegian). Moen, B.E., 2008. Risk perception, priority of safety, and demand for risk mitigation in transport. Doctoral Thesis, Norwegian University of Science of Technology, Department of psychology, Trondheim, Norway. Nordfjærn, T., Rundmo, T., 2010. Differences in risk perception, priorities, worry and demand for risk mitigation in transport among Norwegians in 2004 and 2008. Safety Science 48, 357–364. Nunnaly, J.C., 1978. Psychometric Theory. McGraw Hill, NY, USA. Rundmo, T., 2002. Associations between affect and risk perception. Journal of Risk Research 5, 119–135. Rundmo, T., Sjöberg, 1996. Risk perception by offshore personnel related to platform movements. Safety Science 24 (3), 211–227. Rundmo, T., Moen, B.E., 2007. Risk sensitivity and priority of safety. In: Aven, T., Vinnem, J.E. (Eds.), Risk, Reliability and Societal Safety, vol. 2. Taylor & Francis, London, ISBN 0415447860, pp. 1623–1629. Rundmo, T., Jørgensen, S.H., 2009. Studies of risk perception and transport safety. Rotunde publication No. 90, Trondheim, ISBN:978-82-7892-030-5. Rundmo, T., Nordfjærn, T., Iversen, H.H., Oltedal, S., Jørgensen, S.H., 2011. The role of risk perception and other risk-related judgments in transportation mode use. Safety Science 49, 226–235. Sjöberg, L., Moen, B.E., Rundmo, T., 2004. Explaining Risk Perception: An Evaluation of the Psychometric Paradigm. Rotunde Publications, Norwegian University of Science and Technology, Department of Psychology, Trondheim, Norway.