Safety Science 59 (2013) 78–85

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Safety Science

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Professional subcultures in nuclear power plants

0925-7535/$ - see front matter � 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.ssci.2013.05.004

⇑ Corresponding author. Tel.: +46 (0)70 5397260.E-mail addresses: Carl.rollenhagen@vattenfall.com (C. Rollenhagen), jwd@psy-

chology.su.se (J. Westerlund), katharina.naswall@canterbury.ac.nz (K. Näswall).1 Tel.: +46 (0)8 16 38 56.2 The concepts of safety culture and safety climate are used interchangeably in this

article. The concept of safety culture is often assumed to represent a deeper (valueoriented) layer of organizational culture than climate.

Carl Rollenhagen a,⇑, Joakim Westerlund b,1, Katharina Näswall c

a Royal Institute of Technology, Academy for Nuclear Safety, SE-100 44 Stockholm, Swedenb Department of Psychology, Stockholm University, S-10691 Stockholm, Swedenc Department of Psychology, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand

a r t i c l e i n f o a b s t r a c t

Article history:Received 4 October 2012Received in revised form 23 April 2013Accepted 5 May 2013Available online 30 May 2013

Keywords:Safety cultureSafety climateSubculturesNuclear power plantsOrganizational factors

Using a safety climate survey as the point of departure, the present study explores some aspects of plantcultures vs. professional subcultures in three Swedish nuclear power plants (named A, B and C). The rat-ings on the safety climate survey by workers on power plant A were subjected to an exploratory factoranalysis. A six-factor solution explained a total of 56.0% of the variance in the items included. The six fac-tors were considered to measure Safety management, Change management and experience feedback,Immediate working group, Knowledge and participation, Occupational safety, and Resources. The six fac-tor model was tested by running a confirmatory factor analysis on the ratings by workers on power plantB and C, respectively. The model fit for both plants was acceptable and supported the six factor structure.For each of the six factors, a 3 � 3 ANOVA was conducted on the ratings, with the three largest depart-ments (Operation, Maintenance, Engineering support) and power plants (A, B, C) as the between-subjectsfactors. Differences between power plants as well as differences between departments were found forseveral factors. Overall, the differences between departments were larger than those between powerplants. The results are discussed in terms of challenges for creating safety climate in organizations thatharbor several professional subcultures.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

It is commonly believed that the concepts of safety culture andsafety climate offer interesting perspectives on safety-related diag-noses and change in organizations. Although both of these conceptshave been accused of being vague and sometimes misused (Anton-sen, 2009; Hale, 2000; Guldenmund, 2000, 2007; Pidgeon, 1998;Rollenhagen, 2010) there is still a large amount of attention in bothresearch and practice paid to these subjects.

Even though the concept of safety culture and that of safety cli-mate represents partly different traditions and research orienta-tions2 (Cox and Flin, 1998), both concepts are neverthelessassociated with a human-centered approach to safety (as a comple-ment to more traditional engineering approaches). At the core of suchhuman-centered perspectives we find concepts such as beliefs, values,attitudes, perceptions, norms and behavior (Fazio, 1986; Kleinke,1984). Moreover, safety culture and climate research rests on the

assumption that organizations and their members share (at leastsome) safety related beliefs, perceptions, values, behaviors, etc.(Guldenmund, 2000). A large amount of research has been devotedto finding exactly what beliefs, attitudes, etc. people share with re-spect to safety. For example, in the safety climate tradition, studieshave tried to extract generic safety climate dimensions (Guldenmund,2007; Yule, 2003). Many questions are still unanswered in the contextof safety culture and climate research, and several of these issues aregenuinely difficult ones, in a conceptual, ontological and epistemolog-ical sense. This article attempts to explore some aspects of those diffi-culties, namely the role of subcultures (i.e., professional cultures).

Richter and Koch (2004) argue that safety cultures may beunderstood by utilizing at least three broadly defined perspectives:integration, differentiation and ambiguity. If integration is the fo-cus, an organization is often assumed to exhibit a grand unifyingculture with characteristics that may be different from other orga-nizations. However, organizational cultures may also be under-stood from a perspective of differentiation and ambiguity wheredifferent subcultures emerge.

The existence of subcultures in organizations has been high-lighted by several researchers (Cooper, 2000; Mearns et al.,1998). For example, Jones and James (1979) found, in a study of na-val ships, that functional groups (e.g., navigation, missiles,maintenance) exhibited more similarity in their perceptions of

C. Rollenhagen et al. / Safety Science 59 (2013) 78–85 79

the work environment than did individuals in the same structuralgroups (e.g., ships). Parker (2000) has argued that several factorsmight influence the emergence of subcultures in organizations.One of these concern what people do in different functions (profes-sional groups). Richter and Koch (2004) discuss previous researchwith the underlying assumption that subcultures in organizationsmay transcend organizational boundaries (such as professionalcultures that are unified by what people do rather than by belong-ing to a specific organization).

Schein (1996) also discusses differences between professionalgroups in terms of cultural attributes. The idea that subgroupsmay exhibit different cultures/climates may perhaps, at first sight,seem to be a platitude. However, how people at various analyticallevels (e.g., branch, company, functional groups, professions, etc.)develop shared perceptions, attitudes, norms, etc. is still not verywell understood, although there are several theoretical contribu-tions addressing this issue (see Beyer et al., 2000). Zohar (2010)summarizes: ‘‘One key theoretical question relates to the processthrough which these perceptions become shared and, therefore,climate emerges. How do individual perceptions become shared?Why do groups engage in activities resulting in this emergence?These questions – focused on the attendance of climate – havenot received much attention in the literature yet. . .’’ (p. 1519).

Many factors may be assumed to contribute to shared percep-tions/attitudes, including leadership, common tasks, common lan-guage, social interaction, group pressures, common enemies, etc.One step towards a deeper understanding about characteristicsof safety climates, which is the focus of the present research, isto explore how different professional groups assess aspects ofimportance for safety. This question is important, not least for at-tempts to change organizations towards better safety cultures.For example, if professional subcultures become very strong, thenmuch management attention have to be focused around attemptsto integrate subcultures, particularly so if the safety of an organiza-tion is in strong need of cooperation and integration between func-tional/professional groups. By the term ‘‘professional groups’’ wehere mean people who share approximately the same tasks in anorganization.

The focus in this study was to provide answers to the followingquestion: How similar are three dominant professional groups (i.e.operators, maintenance, and engineering staff) working in the dif-ferent nuclear power plants in their assessment of various factorsof importance for safety?

The study was conducted in two steps. In the first step it wasexplored if the same ‘‘safety climate’’ factors in one Swedish nucle-ar power plant would also be obtained for two other plants. Theoutcome of this step showed that a similar factor structure was ob-tained using data from the three different plants. This is an inter-esting finding in itself but one that will not be explored tofurther depth in the present study. The second step was to usethe factor structure obtained for shedding light on the main ques-tion about possible differences in professional subcultures. Finallywe present the findings in a broader theoretical context.

2. Method

2.1. Safety climate survey

The safety climate questionnaire used in the present research isa result of research collaboration between three nuclear powerplants in Sweden. A former version of the questionnaire had beenin use for more than 10 years among the plants and was updated in2007 in view of experiences gained over the years. The 2007version (see Rollenhagen and Westerlund, 2007) extended the pre-vious version in the following respects:

� A differentiation was made between items focusing on nuclearsafety and items focusing on occupational safety. An example ofa question that was added to the new version is: ‘‘Compliancewith rules for occupational safety is. . .’’� Some general organizational items common to both occupa-

tional and nuclear safety were included, exemplified by: ‘‘Thecooperation among persons in my immediate working groupis. . .’’� Specific items which are unique for nuclear power productions

(e.g., outage management) were included, for example: ‘‘Duringoutage operations, the time resources I have for performing jobswith desired quality is. . .’’

Items in the updated questionnaire were selected to includefactors found to be relevant factors/dimensions by the researchgroup, and were obtained from selected research on safety cultureand safety climate published prior to 2007. Among the selecteditems were those focusing on management attention to safety,safety management systems, resources, knowledge about safety,communication and change management? The questionnaire in-cluded 45 items.

For all questions, verbally anchored scales (1–7) were used asresponse scales, as in the following examples:

� Openness to discuss nuclear safety issues in the plant is. . .

� Very bad 1 2 3 4 5 6 7 Very good� The status of the safety department in the plant is. . .

� Very low 1 2 3 4 5 6 7 Very high

The questionnaire was administered through the internal webwith full anonymity. Respondents had the opportunity to refrainfrom answering to items they might perceive as non-relevant bymarking a specific box. The response rates were above 85% for allthree plants. The internal attrition on the 45 items among the2547 completed questionnaires ranged from 0.7% for ‘‘Cooperationin my working group’’ as well as for ‘‘Order at my workplace’’ to19.4% for ‘‘Descriptions of roles/responsibilities’’ with a meaninternal attrition rate of 8.1%.

3. Results

3.1. Dimensionality

The ratings on the safety climate survey by workers on powerplant A were subjected to an exploratory factor analysis with Prin-cipal Axis Factoring as the extraction method using PASW Version18. This revealed eight underlying factors with eigenvalues exceed-ing 1. An inspection of the screeplot showed, however, that therewas a clear elbow after the sixth factor. Using Cattell’s (1966) testas criteria for factor extraction, six factors were therefore retainedfor further investigation. This was also supported by the results ofParallel Analysis (Horn, 1965), which showed only six factors witheigenvalues exceeding the corresponding criterion values for a ran-domly generated data matrix of the same size (45 items � 1229participants and with 1000 replications).

The six-factor solution explained a total of 56.0% of the variancein all items included, with factor 1–6 explaining 36.5%, 4.8%, 4.3%,4.0%, 3.3%, and 3.0% of the variation respectively before rotation. Toaid in the interpretation of these six factors, oblique rotation wasperformed (Direct Oblimin). The factor loadings in the pattern ma-trix are presented in Table 1.

Factor 1 comprised 10 items concerning safety issues and waslabeled F1–Safety management (Cronbach’s alpha = .93). Typicalitems explored ‘‘safety management commitment’’; ‘‘systems forcorrecting nuclear safety deficiencies’’; ‘‘nuclear safety rule com-

Table 1Factor loadings in the pattern matrix from the exploratory factor analysis on the safety climate survey ratings by workers on Power plant A (n = 1229, numberof factors according to Parallel Analysis and Cattell’s scree test, Principal Axis Factoring as extraction method, pairwise deletion of missing data and DirectOblimin as rotation method. Factor loadings <.35 have been hidden).

Factor

1 2 3 4 5 6 *

Upper managements safety commitment .78 1Overall the safety culture is. . . .71 1Correction of nuclear safety deficiencies .69 1Nuclear safety rule compliance .67 1Roles/responsibilities are clear .67 1Managing resolutions of conflicts safety-economy .60 1Identification of nuclear safety problems .57 1Openness to discuss safety issues .39 .36 1Tendency to Stop-Act-Think-Review (STAR) .39 1Descriptions of roles/responsibilities .39 1Safety department statusReporting of human factor issuesManagers explanations of reasons for change �.57 2My groups opinions are considered in change �.53 2Experience feedback at the company �.47 2Upper managers ability to go from decision to action �.45 2Feedback from auditing �.44 2Experience feedback from outage �.41 2Cooperation in my working group .76 3Cooperation with other groups .52 3Availability of group manager when needed .50 3Strategies in my group to find causes to failures .49 3Opportunities to discuss safety issuesOrder at my workplaceQuality of my instructionsMy knowledge of safety policies .75 4My knowledge of nuclear safety issues .68 4My knowledge of the quality system .53 4My participation in developing nuclear safety .50 4My tasks are safety related .46 4My training so I can work safely .35 4Occupational safety at my work .83 5Time resources for occupational safety .73 5Rule compliance for occupational safety .58 5Risk identification for occupational safety .49 5My time resources in outage periods .45 �.35 5Tendency to blame individualsSecurity arrangementsManning enough to reach high quality �.72 6Strategies for long term manning issues �.59 6My time recourses non-outage operations �.53 6Conditions for planning in my work �.50 6Management is realistic about what the org. can handle �.43 �.48 6Access to competent contractors �.41 6Updating of technical documents

* Suggested factor belonging.

80 C. Rollenhagen et al. / Safety Science 59 (2013) 78–85

pliance’’ and how the respondents perceived the ‘‘nuclear safetyculture’’ of the plant. Factor 1 was given the label ‘‘safety manage-ment’’ but as can be seen from the items defining this factor it in-volves both structural and behavioral facets. Factor 1 essentiallygroups items that often have been perceived as central to safetyclimate, that is, management commitment and resolutions of con-flicts between production and safety, structural factors (roles andresponsibilities, system for problem identification and resolution),openness for discussions of safety issues, and compliance withsafety rules. The high loading on the question exploring ‘‘Manage-ments safety commitment’’ as an important aspect of safety cli-mate has been confirmed by many previous studies (e.g., Cheyneet al., 1998; Cohen, 1977; Dedobbeleer and Beland, 1991; DeJoyet al., 2004; Donald and Canter, 1994; Hofmann and Stetzer,1996; Ostrom et al., 1993; O’Toole, 2002; Rundmo, 1996; Rundmoand Hale, 2003; Seo et al., 2004; Simonds and Shafari-Sahrai, 1977;Smith et al., 1978; Zohar, 1980; Zohar and Luria, 2005). How man-agement copes with potential conflicts between safety and produc-tion, as reflected in Factor 1, is also one aspect of safety climate

that has been attributed high importance for safety climate (Zoharand Luria, 2004).

Factor 2 comprised 6 items concerning change management andexperience feedback and was labeled F2–Change management andexperience feedback (Cronbach’s alpha = .84). Typical items definingthis factor were whether management were able to explain rea-sons for change, if the opinions of staff were considered in changemanagement and various items exploring feedback of experiencesgained in different situations. Managing change and experiencefeedback is one of the cornerstones for safety management. A gen-eral discussion of experience feedback can be obtained in, forexample, Kjellén (2002) and a discussion of different aspects ofchange management can, for example, be found in Grote (2008).

Factor 3 comprised 4 items concerning the immediate workinggroup and was labeled F3–Immediate working group (Cronbach’s al-pha = .74). Typical items defining this factor explored facets associ-ated with the respondent’s immediate working group in terms ofinternal cooperation, cooperation with other groups and availabil-ity of group manager. That the nearest working group has influence

Table 2Fit statistics for the ratings on the safety climate survey by workers on power plant Band workers on power plant C respectively, using the six factor model.

Power plant df v2 RMSEA SRMR CFI AIC

Power plant Ba 614 5688.65* 0.093 0.070 0.95 4573.23Power plant Cb 614 4332.72* 0.10 0.074 0.96 4510.72

* p < .05;a n = 732.b n = 586.

Table 3Cronbach’s alpha.

Factor Number ofitems

Power plant

A B C

F1–Safety 10 .93 .93 .95F2–Change management and experience

feedback6 .84 .86 .89

F3–Immediate working group 4 .74 .76 .82F4–Knowledge and participation 6 .78 .78 .80F5–Occupational safety 5 .86 .86 .86F6–Resources 6 .84 .82 .87

Table 4Number of respondents.

Department

Operation Maintenance Engineering support

Power plantA 442 248 144B 194 206 139C 164 137 120

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on safety climate has been discussed and observed in several stud-ies (Melía et al., 2008; Tucker et al., 2008; Jiang et al., 2010; Youngand Parker, 1999).

Factor 4 comprised 6 items concerning knowledge and partici-pation and was labeled F4–Knowledge and participation (Cronbach’salpha = .78). Typical items defining this factor were the respon-dents’ self-assessment of their knowledge of nuclear issues suchas safety policies, the quality system and general principles regard-ing nuclear safety. Both knowledge and participation has previ-ously been found as defining important aspects of safety climate(Seo et al., 2004; Flin et al., 2000).

Factor 5 comprised 5 items concerning occupational safety andwas labeled F5–Occupational safety (Cronbach’s alpha = .86). Typi-cal items explored the general perceptions of the occupationalsafety domain as well as time dedicated to occupational safety pro-cedures. Safety climate studies have typically not made a distinc-tion among different types of safeties and some researchers havequestioned if it is reasonable to assume the existence of genericsafety climates that hold between different branches and types ofsafeties (Grote, 2012; Coyle et al., 1995; McDonald and Ryan,1992). One of the reasons for updating the 2007 questionnairewas the finding that the respondent’s whished to make distinctionsbetween occupational and nuclear safety – a distinction thattended to be confused in the original questionnaire.

Factor 6 comprised 6 items concerning resources and was la-beled F6–Resources (Cronbach’s alpha = .84). Typical items ex-plored time and staffing resources. Perhaps somewhat surprising,items measuring time and manning resources have not been socommon in safety climate questionnaires. Based on commonobservations of work in organization, lack of manning and time re-sources appears to be important factors that influence behaviorassociated with risk. Also, in studies of human reliability (HRA)constraints imposed by manning and time resources often appearas explanations for more or less safe behavior (De Felice et al.,2012).

In conclusion, the factor structure obtained includes several fac-tors previously identified in safety climate research. For example,in a review study by Flin et al. (2000), the most common factorsidentified were ‘‘management/supervision’’, ‘‘safety systems’’ and‘‘risk’’, but ‘‘work pressure’’ and ‘‘competence’’ also appeared. Seoet al. (2004), in a review of previously identified factors, found acore of generic safety climate concepts: management commitmentto safety, supervisor safety support, coworkers safety support, em-ployee participation in safety, and competence.

This six factor model was tested using Lisrel 8.80 (Jöreskog andSörbom, 2001), by subjecting the ratings by workers on powerplant B and the ratings by workers on power plant C to separateconfirmatory factor analyses.

In order to determine goodness of fit as well as comparative fitfor the overall model, a number of fit statistics were used in addi-tion to the chi-square measure. A Root Mean Square Error ofApproximation (RMSEA) below .05 was considered as very goodfit, and a value below .08 as good fit (Steiger, 1990). As a measureof comparative fit, CFI was used, where levels above .90 were con-sidered indicative of good fit (Bentler, 1990). As a measure of par-simonious fit, Akaike Information Criterion (AIC), where lowerlevels indicate a more parsimonious model. The Standard RootMean Residual (SRMR) was used as an indication of the residualof the models, and lower levels indicate better fit. Local fit in termsof factor loadings was also considered.

The results of the confirmatory factor analyses of the safety cli-mate survey are presented in Table 2. The model fit for both plantswas acceptable, indicating a reasonable fit to data in both organi-zations. This provides preliminary support for the six factor modelderived from the exploratory factor analysis. Closer inspection ofthe factor loadings showed that all items loaded significantly on

the proposed factors, indicating a good local fit for the proposedmodel in both samples tested.

The reliability levels (Cronbach’s alpha) for the dimensions in-cluded in the six factor model on data from power plant B and C,were satisfactory to very good for all six factors (Table 3).

3.2. Group differences

For each of the six factors, a 3 � 3 ANOVA was conducted on theratings, with Department (Operation, Maintenance, Engineeringsupport) and Power plant (A, B, C) as between subjects factors.Numbers of respondents in each department and in each Powerplant are presented in Table 4. The three departments examinedwere the three largest departments. Please note that in the factoranalyses respondents from smaller department were also included.

For F1–Safety management, a small but significant effect ofDepartment was found (F2,1773 = 22.36, p < .001, g2

partial = .025).Workers in the Operations department gave somewhat higher rat-ings on F1–Safety management than workers in the two otherdepartments, see Fig. 1. Neither the effect of Power plant nor thePower plant � Department interaction effect was howeversignificant.

For F2–Change management and experience feedback a very smallbut significant effect of Power Plant was found (F2,1764 = 6.56,p = .001, g2

partial = .007). Workers in Power plant B rated F2–ChangeManagement and experience feedback marginally lower than work-ers in the two other Power plants, see Fig. 2. Neither the effect ofDepartment nor the Power plant � Department interaction effectwas significant.

Fig. 1. Estimated marginal mean ratings on F1–Safety management as a function ofDepartment (Operation, Maintenance or Engineering support) and Power plant (A, Bor C).

Fig. 2. Mean ratings on F2–Change Management and experience feedback as afunction of Department (Operation, Maintenance or Engineering support) andPower plant (A, B or C).

Fig. 3. Mean ratings on F3–Immediate working group as a function of Department(Operation, Maintenance or Engineering support) and Power plant (A, B or C).

Fig. 4. Mean ratings on F4–Knowledge and participation as a function of Department(Operation, Maintenance or Engineering support) and Power plant (A, B or C).

82 C. Rollenhagen et al. / Safety Science 59 (2013) 78–85

For F3–Immediate working group there was also a very small butsignificant effect of Power plant (F2,1777 = 5.63, p = .004, g2

partial =.006). However, the differences between the three departmentswas larger (F2,1777 = 51.25, p < .001, g2

partial = .055). Workers in theOperations department gave higher ratings on F3–Immediate work-ing group than did workers in the two other departments, see Fig. 3.The Power plant � Department interaction effect was notsignificant.

Also for F4–Knowledge and participation there was significantdifferences between the three departments (F2,1779 = 46.18, p <.001, g2

partial = .049) with especially high ratings from workers inthe Operation department, see Fig. 4. There were however no sig-nificant differences between the three Power Plants and therewas no significant Power plant � Department interaction effect.

For F5–Occupational safety we obtained a main effect of Powerplant (F2,1735 = 5.24, p = .009, g2

partial = .005), a main effect ofDepartment (F2,1735 = 7.48, p = .001, g2

partial = .009), and aninteraction effect between Power plant � Department (F2,1735 =3.59, p = .006, g2

partial = .008). All effects were small however. Theresult is illustrated in Fig. 5.

For F6–Resources we obtained a main effect of Power plant(F2,1774 = 30.44, p < .001, g2

partial = .033). Workers in Power plant B

gave especially low ratings on F6–Resources. We also obtained amain effect of Department (F2,1774 = 34.79, p < .001, g2

partial =.038).Workers in the Operations department gave especially highratings on F6–Resources. We also obtained a very small but signif-icant interaction effect Power plant � Department (F2,1774 = 2.85,p = .023, g2

partial = .006). The result is illustrated in Fig. 6.The results from the ANOVAs are summarized in Table 5.

4. General discussion

Nuclear power plant operations are, just as in many otherindustries, in need of strong integration between different sub pro-cesses to be safe and effective. This integration is complicated bythe fact that nuclear power plants include several professionalgroups, each with partly different traditions, tasks and subcultures.The possibility of creating a safety culture in the sense of being a‘‘grand plant safety culture’’ may thus face serious difficulties inview of the existence of several professional subcultures. Suchsubcultures may transcend individual organizations, for exampleby the existence of professional networks, professional journals,use of language, jargons, etc. The present research providestentative evidence that the differences between professional

Fig. 5. Mean ratings on F5–Occupational safety as a function of Department(Operation, Maintenance or Engineering support) and Power plant (A, B or C).

Fig. 6. Mean ratings on F6–Resources as a function of Department (Operation,Maintenance or Engineering support) and Power plant (A, B or C).

Table 5Eta-squared partial for the main effect of Power plant, the main effect of Departmentand the Power plant � Department interaction effect.

Factor Powerplant

Department Powerplant � Department

F1–Safety Management .003 .025*** .004F2–Change management and

experience feedback.007** .003 .002

F3–Immediate working group .006** .055*** .003F4–Knowledge and

participation.000 .049*** .002

F5–Occupational safety .005** .009*** .008**

F6–Resources .033*** .038*** .006*

* p < .05,** p < .01,*** p < .001.

C. Rollenhagen et al. / Safety Science 59 (2013) 78–85 83

subcultures, on at least some dimensions of safety climate, arelarger than the differences found between plants, indicating thatbelonging to a particular professional subcultures is more impor-tant for safety climate perceptions than what plant one works in.As mentioned in the introduction a similar observation was doneby Jones and James (1979) in a study of naval ships.

How can the differences between plants and professionalgroups observed in the present study be explained and what arethe consequences for practices and research? These two broadquestions will be addressed in this final section.

The first factor, named ‘‘Safety management’’, explained 36% ofthe variance and contains individual items that can be viewed asthe ‘‘core’’ of safety culture/climate (management commitment onsafety, correction of safety deficiencies, clear roles and responsibili-ties, etc.). A small but significant difference between departmentswas obtained were Operations departments scored somewhat high-er than the other two departments. One potential explanation forthis result is that Operations departments, by the nature of their‘‘sharp end’’ activities, have developed a more rule oriented culturewith a clearly perceived production line type of organization. Oper-ations departments are directly responsible for nuclear safety whichcreates a strong demand for being informed about the dynamicoperating state of the plant. However, it is also possible that Opera-tions departments exhibit a somewhat more defensive stance aboutquestionnaire items exploring rules, responsibilities, managementcommitment, etc. In comparison, Technical support organizationsand Maintenance are usually more project oriented.

The small but significant differences between plants in Factor 2– Change management and experience feedback – can presumablybe explained in the context of the volume of ongoing retrofits andchange management projects that was present at the time for thisstudy. The different plants have varied schedules for when largeretrofit programs should be implemented. These programs put alot of burden on the technical support departments and to someextent also on the maintenance departments.

Judging from the factor labeled – ‘‘Immediate working group’’ –a factor strongly defined by items exploring internal and externalcooperation, there appears to be a relatively homogenous ‘‘operat-ing culture’’ existing at all the nuclear power plants. A very smallbut significant effect of Power plant was observed. However, thedifferences between the three departments were larger. It istempting to understand this finding as being a result of standard-ization with respect to operating procedures, simulator training,etc. which increases the possibility to create a shared collective‘‘operator identity.’’ Maintenance work, by comparison, is dividedinto several relatively independent subgroups (mechanical, electri-cal, instrumental, etc.) and the same holds for engineering, whichmay result in relatively more coordinating difficulties in compari-son with the operation subculture.

The factor labeled ‘‘Knowledge and participation’’ (Factor 4)indicates the existence of strong professional subcultures regard-less of plants. Again, this observation can presumably be explainedby differences in the characteristics of work among the differentprofessional groups. Maintenance departments and technical sup-port are less homogeneous that operation departments.

On Factor 5 – Occupational safety – there were small but signif-icant differences both between power plants and professionalgroups. We refrain from speculating about the reasons for thesedifferences. It is still worth noting, however, that much of safetyclimate research have been performed in the context of occupa-tional safety rather than system safety. The fact that occupationalsafety is discerned as a separate factor in the analysis suggests thatwork trying to diagnose safety culture/climate should be sensitiveto what kind on safety that is in focus.

Concerning Factor 6 – Resources – there were also differencesamong the power plants. By comparing Fig. 2 (change manage-ment) and Fig. 5 (resources) we can see that it is people at plant Bwho scored the lowest in both of these factors. This aspect of safetyculture/climate is thus best perceived as contextual, rather than onereflecting basic differences in more stable professional cultures.

Some general discussion themes of relevance for the present re-port will be discussed below including a discussion of some more

84 C. Rollenhagen et al. / Safety Science 59 (2013) 78–85

concrete implications for safety management and safety culture/climate research.

The professional subcultures in this study were operations,maintenance and engineering. Each of these subcultures is distin-guished by differences in educational backgrounds, career develop-ments, training opportunities and the type of core task in focus forthe respective group. Organizational cultures have been under-stood as reflecting different ideologies (Beyer, 1981; Zammutoet al., 2000). An ideology represents a relatively coherent set of be-liefs about how to work to attain desired outcomes and how tounderstand the world; the concept of ideology is thus very closelyrelated to the concept of culture, and particularly those culturaltheories that focus on the deeper assumptions as being a core con-stituent of a culture (Schein, 2004). A possible way to furtherunderstand the differences found in the present study could beto discern various ideologies and connected value systems for thethree professional groups. The competing values framework repre-sents a conceptual framework that might be suitable for such adeeper inquiry.

Using the competing values framework (Quinn and Rohrbaugh,1983) as a point of departure, the following ideologies/modelshave been suggested: the Human Relational Model (focus on devel-opment of human resources); the Internal Process Model (focus onstability and control); the Open system model (focus on growthand resource acquisition) and the Rational Goal Model (focused onproductivity and efficiency). Research departing from the compet-ing value framework in relation to safety is represented by, forexample Colley et al. (2013).

Prima facie, all these above mentioned ideologies are present atnuclear power plants. From an overall safety perspective, theInternal Process Model is perhaps the dominant one with its focuson control and stability of operations. At the same time, manage-ment also has to take into account a Rational Goal Model, wherefocusing on productivity and efficiency and the balance betweenfocusing on safety and productivity has been perceived as a coredimension of safety culture/climate (Zohar, 2010). Different pro-fessional groups might develop different profiles in terms of thoseideologies mentioned above, and this could provide importantinformation for change management efforts regarding safetyculture.

Another line of research that further could explore how differ-ent professional groups manifest different climates can be foundin sociological and critical traditions focusing on human powerrelations (Antonsen, 2009). At nuclear plants, different professionalgroups have access to various levels of power (for example, opera-tion departments are usually very strong centers of power). Thestatus might thus differ between professional groups. For example,maintenance has sometimes been characterized as manual laborwith lower status than other professional groups in some respects(Perin, 2005; Reiman and Odewald, 2006). Future research should,we believe, focus more strongly on how professional groups maydiffer in organizations and what this implies for safety culture/cli-mate assessment and change.

What are the more concrete implications of the present re-search in terms of practices for safety culture/safety climate diag-nostics and change management? Firstly, the present researchindicates that a unit of analysis which is based on the idea thatprofessional cultures are important in diagnosing safety culture/climate. General assessment tools for safety climate should, we be-lieve, have a more focused approach that is tailored to the charac-teristics of different professional groups, their context and tasks.Secondly, different kinds of safety should, if relevant, be addressedas present in the same organization (occupational safety, systemsafety, etc.), rather than as an undifferentiated view of the conceptof safety. Thirdly, it should be recognized that some facets of anorganizations culture/climate are more stable than others, for

example, contextual factors such as reorganizations and majortechnological retrofits may influence some professional groupsmuch more than others. This entails that global generalizationsof the type that an organization has ‘‘a good/bad safety culture’’ al-ways should be taken with caution and be related to the dynamicsof the underlying factors used in the assessment. Fourthly, safetyculture/climate is perhaps best diagnosed in the context of alsousing items that explore more general organizational characteris-tics other than those that are believed to be safety related. Manydifferent cultures are present in organizations (professional cul-tures, innovation cultures, production cultures, different types ofsafety, etc.) and to understand the position of ‘‘safety’’ in these,the diagnostic tools used should be sufficiently broad and exploreseveral interacting subcultures.

The present research could be criticized on several grounds.Firstly, the questionnaire used could be biased towards itemswhich perhaps are more familiar to some groups than others, thuscreating various response biases. For example, a high score in someitems might indicate that a person perceives that some state of af-fairs are reasonably good ‘‘in general’’ (as a deductive statement)but another person may draw on experiences from particular sali-ent cases in a more inductive cognitive style. Questionnaires aboutsafety climate, including the present one, are not always sensitiveto such potential differences, and cognitive styles could perhapsvary between professional groups. For example, depending on jobcharacteristics, some groups could exhibit a more nuanced cogni-tive map with respect to safety issues than another group. A secondproblem with a questionnaire of the present kind concerns thegeneral criticism that can be directed to these means of collectinginformation about safety climates (Guldenmund, 2007). Variousfactors including social desirability, motives to ‘‘punish’’ manage-ment, etc. could of course influence the results. A third criticismcould be directed to the strategy used here by which the same fac-tor structure was used as a benchmark for the comparison. Analternative approach could have been to analyze the data by adeparture in individual factor structures obtained for each profes-sional group. It is possible that different professional groups wouldobtain slightly different factor structures. This could be the subjectfor further research.

5. Summary and general conclusions

� An exploratory factor analysis on ratings on a safety climatesurvey by workers on power plant A resulted in a six-factorsolution explaining a total of 56.0% of the variance in the itemsincluded. The six factors were considered to measure Safetymanagement, Change management and experience feedback,Immediate working group, Knowledge and participation, Occu-pational safety, and Resources.� The six factor model was tested by running a confirmatory fac-

tor analysis on the ratings by workers on power plant B and C,respectively. The model fit for both plants was acceptable andsupported the six factor structure.� For each of the six factors, a 3 � 3 ANOVA was conducted on

the ratings, with the three largest departments (Operation,Maintenance, Engineering support) and power plants (A, B,C) as the between-subjects factors. Differences between powerplants as well as differences between departments were foundfor several factors. Overall, the differences between depart-ments were larger than those between power plants.� Further research should aim for a closer analysis of the ideolo-

gies that characterize different professional groups at nuclearpower plants – for instance in terms of the competing valuesframework. Also more attention should be devoted to under-standing how power relations might affect safety cultures.

C. Rollenhagen et al. / Safety Science 59 (2013) 78–85 85

� Since nuclear power plants are in need of strong coordinationbetween professional groups, management attention to thisissue seems particularly important to support strong safety cul-tures – attention to differences in professional culture might bean important aspect in this work.� There are several types of safety in many organizations (occupa-

tional, system, etc.) and tools to diagnose safety culture/climateshould take that into consideration.� Research of safety culture/climate should have a broad point of

departure that allows for locating values of safety in the realmof other types of values present in organizations.

References

Antonsen, S., 2009. Safety culture and the issue of power. Safety Science 47, 183–191.

Bentler, P.M., 1990. Comparative fit indexes in structural models. PsychologicalBulletin 107, 238–246.

Beyer, J.M., 1981. Ideologies, values, and decision making in organizations. In:Nystrom, P.C., Starbuck, W.H. (Eds.), Handbook of Organizational Design, vol. 2.Oxford University Press, New York, pp. 166–202.

Beyer, J.M., Hannah, D.R., Milton, L.P., 2000. Ties that bind – culture andattachments in organization. In: Ashkanasy, Neal M., Wilderom, Celeste P.M.,Peterson, Mark F. (Eds.), Handbook of Organisational Culture and Climate. SagePublications, Inc., pp. 323–338.

Cattell, R.B., 1966. The scree test for number of factors. Multivariate BehavioralResearch 1, 245–276.

Cheyne, A., Cox, S., Oliver, A., Tomás, J.M., 1998. Modelling employee attitudes tosafety. Work and Stress 12, 255–271.

Cohen, A., 1977. Factors in successful occupational safety programs. Journal ofSafety Research 9, 168–178.

Colley, S.K., Lincolne, J., Neal, A., 2013. An examination of the relationship amongstprofiles of perceived organizational values, safety climate and safety outcomes.Safety Science 51, 69–76.

Cooper, M.D., 2000. Towards a model of safety culture. Safety Science 36 (2), 111–136.

Cox, S.J., Flin, R., 1998. Safety culture: philosophers stone or a man of straw? Workand Stress 12 (3), 202–216.

Coyle, I.R., Sleeman, S.D., Adams, N., 1995. Safety climate. Journal of Safety Research26, 247–254.

De Felice, F., Petrillo, A., Carlomusto, A., Ramondo, A., 2012. Human ReliabilityAnalysis: a review of the state of the art. IRACST– International Journal ofResearch in Management & Technology (IJRMT) 2(1). ISSN 2249-9563

Dedobbeleer, N., Beland, F., 1991. A safety climate measure for construction sites.Journal of Safety Research 22, 97–103.

DeJoy, D.M., Schaffer, B.S., Wilson, M.G., Vandenberg, R.J., Butts, M.M., 2004.Creating safer workplaces: assessing the determinants and role of safetyclimate. Journal of Safety Research 35, 81–90.

Donald, I., Canter, D., 1994. Employee attitudes and safety in the chemical industry.Journal of Loss Prevention in the Process Industries 7, 203–208.

Fazio, R.H., 1986. How attitudes guide behaviour? In: Sorrentino, R.M., Higgins, E.T.(Eds.), The Handbook of Motivation and Cognition; Foundations of SocialBehaviour. Guilford Press, New York, pp. 204–243.

Flin, R., Mearns, K., OConnor, P., Bryden, R., 2000. Measuring safety climate:identifying the common features. Safety Science 34 (1–3), 177–192.

Grote, G., 2008. Diagnosis of safety culture: a replication and extensiontowards assessing ‘‘safe’’ organizational change processes. Safety Science46, 450–460.

Grote, G., 2012. Safety management in different high-risk domains – all the same?Safety Science 50, 1983–1992.

Guldenmund, F.W., 2000. The nature of safety culture: a review of theory andresearch. Safety Science 34 (1–3), 215–257.

Guldenmund, F.W., 2007. The use of questionnaires in safety culture research – anevaluation. Safety Science 45, 723–743.

Hale, A.R., 2000. Editorial. Cultures confusion. Safety Science 34 (1–3), 1–4.Hofmann, D.A., Stetzer, A., 1996. A cross-level investigation of factors influencing

unsafe behaviours and accidents personnel. Psychology 49, 307–339.Horn, J.L., 1965. A rationale and test for the number of factors in factor analysis.

Psychometrica 30, 179–185.Jiang, L., Yu, G., Li, Y., Li, F., 2010. Perceived collegues’ safety knowledge/behaviour

and safety performance: safety climate as a moderator in a multilevel study.Accident Analysis and prevention 42 (5), 1468–1476.

Jones, A.P., James, L.R., 1979. Psychological climate: dimensions and relationships ofindividual and aggregated work environment perceptions. OrganizationalBehaviour and Human Performance 23, 201–250.

Jöreskog, K., Sörbom, D., 2001. LISREL 8: User’s Reference Guide, second ed. SSI,Lincolnwood, IL.

Kjellén, U., 2002. Prevention of Accidents through Experience Feedback. Taylor andFrancis.

Kleinke, C.L., 1984. Two models for conceptualising the attitude–behaviourrelationship. Human Relations 37 (4), 333–350.

McDonald, N., Ryan, F., 1992. Constraints in the development of safety culture: apreliminary analysis. The Irish Journal of Psychology 13, 273–281.

Mearns, K., Flin, R., Gordon, R., Fleming, M., 1998. Measuring safety climate onoffshore installations. Work and Stress 12 (3), 238–254.

Melía, J.L., Mearns, K., Silva, S.A., Lima, M.L., 2008. Safety climate responses and theperceived risk of accidents in the construction industry. Safety Science 46, 949–958.

Ostrom, L., Wilhelmsen, C., Daplan, B., 1993. Assessing safety culture. Nuclear Safety34, 163–172.

O’Toole, M., 2002. The relationship between employees’ perceptions of safety andorganizational culture. Journal of Safety Research 33 (2), 231–243.

Parker, M., 2000. Organizational Culture and Identity. Sage, London.Perin, C., 2005. Shouldering Risks: The Culture of Control in the Nuclear Power

Industry. Princeton University Press, New Jersey.Pidgeon, N., 1998. Safety culture: key theoretical issues. Work and Stress 12, 202–

216.Quinn, R.E., Rohrbaugh, J., 1983. A spatial model of effectiveness criteria: toward

competing values approach to organizational analysis. Management Science 29,363–377.

Reiman, T., Odewald, P., 2006. Assessing the maintenance unit of a nuclear powerplant – identifying the cultural conceptions concerning the maintenance workand the maintenance organization. Safety Science 44 (9), 821–850.

Richter, A., Koch, C., 2004. Integration, differentiation and ambiguity in safetycultures. Safety Science 42, 703–722.

Rollenhagen, C., 2010. Can focus on safety culture become an excuse for notrethinking design of technology? Safety Science 48, 268–278.

Rollenhagen, C., Westerlund, J., 2007. Development of a safety climatequestionnaire for nuclear power plants. In: Human Factors and Power Plants.Joint 8th IEEE HFPP/13TH HPRCT, 26–31 August, 2007, Monterey, USA.

Rundmo, T., 1996. Associations between risk perception and safety. Safety Science24, 197–209.

Rundmo, T., Hale, A., 2003. Managers’ attitudes towards safety and accidentprevention. Safety Science 41, 557–574.

Schein, E.H., 1996. Three cultures of management: the key to organizationallearning. Sloan Management Review 38 (1), 9–20.

Schein, E.H., 2004. Organizational Culture and Leadership. Jossey-Bass, San Francisco.Seo, D.C., Torabi, M.R., Blair, E.H., Ellis, N.T., 2004. A cross-validation of safety

climate scale using confirmatory factor analytic approach. Journal of SafetyResearch 35, 427–445.

Simonds, R.H., Shafari-Sahrai, Y., 1977. Factors apparently affecting injuryfrequency in eleven matched pairs of companies. Journal of Safety Research 9,120–127.

Smith, M.J., Cohen, A., Cohen, H.H., Cleveland, R.S., 1978. Characteristics ofsuccessful safety programs. Journal of Safety Research 10, 5–15.

Steiger, J.H., 1990. Structural model evaluation and modification: an intervalestimation approach. Multivariate Behavioral Research 25, 173–180.

Tucker, S., Chmiel, N., Turner, N., Hershcovis, M.S., Stride, C.B., 2008. Perceivedorganizational support for safety and employee safety voice: the mediating roleof coworker support for safety. Journal of Occupational Health Psychology 13(4), 319–330.

Young, S.A., Parker, C.P., 1999. Predicting collective climates: assessing the role ofshared work values, needs, employee interaction and work group membership.Journal of Organizational Behavior 20, 1199–1218.

Yule, S., 2003. Senior Management Influence on Safety Performance in UK and USEnergy Sectors. Doctoral Thesis. University of Aberdeen, Scotland.

Zammuto, R.F., Blair, G., Goodman, E.A., 2000. Managerial ideologies, organizationculture, and the outcome of innovation: a competing values perspective. In:Ashkanasy, Neal M., Wilderom, Celeste P.M., Peterson, Mark F. (Eds.), Handbookof Organisational Culture and Climate. Sage Publications, Inc., pp. 261–278.

Zohar, D., 1980. Safety climate in industrial organizations: theoretical and appliedimplications. Journal of Applied Psychology 65 (1), 96–102.

Zohar, D., 2010. Thirty years of safety climate research: reflections and futuredirections. Accident Analysis and Prevention 42, 1517–1522.

Zohar, D., Luria, G., 2004. Climate as social-cognitive construction of supervisorypractices: scripts as proxy of behaviour patterns. Journal of Applied Psychology89, 322–333.

Zohar, D., Luria, G., 2005. A multilevel model of safety climate: cross levelrelationships between organization and group-level climates. Journal of AppliedPsychology 90 (4), 616–628.