Professional subcultures in nuclear power plants

Safety Science 59 (2013) 78–85

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Professional subcultures in nuclear power plants Carl Rollenhagen a,⇑, Joakim Westerlund b,1, Katharina Näswall c a

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

a r t i c l e

i n f o

Article history: Received 4 October 2012 Received in revised form 23 April 2013 Accepted 5 May 2013 Available online 30 May 2013 Keywords: Safety culture Safety climate Subcultures Nuclear power plants Organizational factors

a b s t r a c t Using a safety climate survey as the point of departure, the present study explores some aspects of plant cultures vs. professional subcultures in three Swedish nuclear power plants (named A, B and C). The ratings on the safety climate survey by workers on power plant A were subjected to an exploratory factor analysis. A six-factor solution explained a total of 56.0% of the variance in the items included. The six factors were considered to measure Safety management, Change management and experience feedback, Immediate working group, Knowledge and participation, Occupational safety, and Resources. The six factor model was tested by running a confirmatory factor analysis on the ratings by workers on power plant B 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 departments (Operation, Maintenance, Engineering support) and power plants (A, B, C) as the between-subjects factors. Differences between power plants as well as differences between departments were found for several factors. Overall, the differences between departments were larger than those between power plants. The results are discussed in terms of challenges for creating safety climate in organizations that harbor several professional subcultures. Ó 2013 Elsevier Ltd. All rights reserved.

1. Introduction It is commonly believed that the concepts of safety culture and safety climate offer interesting perspectives on safety-related diagnoses and change in organizations. Although both of these concepts have been accused of being vague and sometimes misused (Antonsen, 2009; Hale, 2000; Guldenmund, 2000, 2007; Pidgeon, 1998; Rollenhagen, 2010) there is still a large amount of attention in both research and practice paid to these subjects. Even though the concept of safety culture and that of safety climate represents partly different traditions and research orientations2 (Cox and Flin, 1998), both concepts are nevertheless associated with a human-centered approach to safety (as a complement to more traditional engineering approaches). At the core of such human-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 ⇑ Corresponding author. Tel.: +46 (0)70 5397260. E-mail addresses: [email protected] (C. Rollenhagen), [email protected] (J. Westerlund), [email protected] (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 (value oriented) layer of organizational culture than climate. 0925-7535/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ssci.2013.05.004

assumption that organizations and their members share (at least some) safety related beliefs, perceptions, values, behaviors, etc. (Guldenmund, 2000). A large amount of research has been devoted to finding exactly what beliefs, attitudes, etc. people share with respect to safety. For example, in the safety climate tradition, studies have tried to extract generic safety climate dimensions (Guldenmund, 2007; Yule, 2003). Many questions are still unanswered in the context of safety culture and climate research, and several of these issues are genuinely difficult ones, in a conceptual, ontological and epistemological sense. This article attempts to explore some aspects of those difficulties, namely the role of subcultures (i.e., professional cultures). Richter and Koch (2004) argue that safety cultures may be understood by utilizing at least three broadly defined perspectives: integration, differentiation and ambiguity. If integration is the focus, an organization is often assumed to exhibit a grand unifying culture with characteristics that may be different from other organizations. However, organizational cultures may also be understood from a perspective of differentiation and ambiguity where different subcultures emerge. The existence of subcultures in organizations has been highlighted by several researchers (Cooper, 2000; Mearns et al., 1998). For example, Jones and James (1979) found, in a study of naval 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

the work environment than did individuals in the same structural groups (e.g., ships). Parker (2000) has argued that several factors might influence the emergence of subcultures in organizations. One of these concern what people do in different functions (professional groups). Richter and Koch (2004) discuss previous research with the underlying assumption that subcultures in organizations may transcend organizational boundaries (such as professional cultures that are unified by what people do rather than by belonging to a specific organization). Schein (1996) also discusses differences between professional groups in terms of cultural attributes. The idea that subgroups may exhibit different cultures/climates may perhaps, at first sight, seem to be a platitude. However, how people at various analytical levels (e.g., branch, company, functional groups, professions, etc.) develop shared perceptions, attitudes, norms, etc. is still not very well understood, although there are several theoretical contributions addressing this issue (see Beyer et al., 2000). Zohar (2010) summarizes: ‘‘One key theoretical question relates to the process through 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 – have not received much attention in the literature yet. . .’’ (p. 1519). Many factors may be assumed to contribute to shared perceptions/attitudes, including leadership, common tasks, common language, social interaction, group pressures, common enemies, etc. One step towards a deeper understanding about characteristics of safety climates, which is the focus of the present research, is to explore how different professional groups assess aspects of importance for safety. This question is important, not least for attempts to change organizations towards better safety cultures. For example, if professional subcultures become very strong, then much management attention have to be focused around attempts to integrate subcultures, particularly so if the safety of an organization is in strong need of cooperation and integration between functional/professional groups. By the term ‘‘professional groups’’ we here mean people who share approximately the same tasks in an organization. The focus in this study was to provide answers to the following question: How similar are three dominant professional groups (i.e. operators, maintenance, and engineering staff) working in the different nuclear power plants in their assessment of various factors of importance for safety? The study was conducted in two steps. In the first step it was explored if the same ‘‘safety climate’’ factors in one Swedish nuclear power plant would also be obtained for two other plants. The outcome of this step showed that a similar factor structure was obtained using data from the three different plants. This is an interesting finding in itself but one that will not be explored to further depth in the present study. The second step was to use the factor structure obtained for shedding light on the main question about possible differences in professional subcultures. Finally we present the findings in a broader theoretical context.

2. Method 2.1. Safety climate survey The safety climate questionnaire used in the present research is a result of research collaboration between three nuclear power plants in Sweden. A former version of the questionnaire had been in use for more than 10 years among the plants and was updated in 2007 in view of experiences gained over the years. The 2007 version (see Rollenhagen and Westerlund, 2007) extended the previous version in the following respects:

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 A differentiation was made between items focusing on nuclear safety and items focusing on occupational safety. An example of a question that was added to the new version is: ‘‘Compliance with rules for occupational safety is. . .’’  Some general organizational items common to both occupational and nuclear safety were included, exemplified by: ‘‘The cooperation among persons in my immediate working group is. . .’’  Specific items which are unique for nuclear power productions (e.g., outage management) were included, for example: ‘‘During outage operations, the time resources I have for performing jobs with desired quality is. . .’’ Items in the updated questionnaire were selected to include factors found to be relevant factors/dimensions by the research group, and were obtained from selected research on safety culture and safety climate published prior to 2007. Among the selected items were those focusing on management attention to safety, safety management systems, resources, knowledge about safety, communication and change management? The questionnaire included 45 items. For all questions, verbally anchored scales (1–7) were used as response 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 web with full anonymity. Respondents had the opportunity to refrain from answering to items they might perceive as non-relevant by marking a specific box. The response rates were above 85% for all three plants. The internal attrition on the 45 items among the 2547 completed questionnaires ranged from 0.7% for ‘‘Cooperation in my working group’’ as well as for ‘‘Order at my workplace’’ to 19.4% for ‘‘Descriptions of roles/responsibilities’’ with a mean internal attrition rate of 8.1%.

3. Results 3.1. Dimensionality The ratings on the safety climate survey by workers on power plant A were subjected to an exploratory factor analysis with Principal Axis Factoring as the extraction method using PASW Version 18. This revealed eight underlying factors with eigenvalues exceeding 1. An inspection of the screeplot showed, however, that there was a clear elbow after the sixth factor. Using Cattell’s (1966) test as criteria for factor extraction, six factors were therefore retained for further investigation. This was also supported by the results of Parallel Analysis (Horn, 1965), which showed only six factors with eigenvalues exceeding the corresponding criterion values for a randomly generated data matrix of the same size (45 items  1229 participants and with 1000 replications). The six-factor solution explained a total of 56.0% of the variance in 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. To aid in the interpretation of these six factors, oblique rotation was performed (Direct Oblimin). The factor loadings in the pattern matrix are presented in Table 1. Factor 1 comprised 10 items concerning safety issues and was labeled F1–Safety management (Cronbach’s alpha = .93). Typical items explored ‘‘safety management commitment’’; ‘‘systems for correcting nuclear safety deficiencies’’; ‘‘nuclear safety rule com-

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C. Rollenhagen et al. / Safety Science 59 (2013) 78–85 Table 1 Factor loadings in the pattern matrix from the exploratory factor analysis on the safety climate survey ratings by workers on Power plant A (n = 1229, number of factors according to Parallel Analysis and Cattell’s scree test, Principal Axis Factoring as extraction method, pairwise deletion of missing data and Direct Oblimin as rotation method. Factor loadings <.35 have been hidden). Factor 1 Upper managements safety commitment Overall the safety culture is. . . Correction of nuclear safety deficiencies Nuclear safety rule compliance Roles/responsibilities are clear Managing resolutions of conflicts safety-economy Identification of nuclear safety problems Openness to discuss safety issues Tendency to Stop-Act-Think-Review (STAR) Descriptions of roles/responsibilities Safety department status Reporting of human factor issues Managers explanations of reasons for change My groups opinions are considered in change Experience feedback at the company Upper managers ability to go from decision to action Feedback from auditing Experience feedback from outage Cooperation in my working group Cooperation with other groups Availability of group manager when needed Strategies in my group to find causes to failures Opportunities to discuss safety issues Order at my workplace Quality of my instructions My knowledge of safety policies My knowledge of nuclear safety issues My knowledge of the quality system My participation in developing nuclear safety My tasks are safety related My training so I can work safely Occupational safety at my work Time resources for occupational safety Rule compliance for occupational safety Risk identification for occupational safety My time resources in outage periods Tendency to blame individuals Security arrangements Manning enough to reach high quality Strategies for long term manning issues My time recourses non-outage operations Conditions for planning in my work Management is realistic about what the org. can handle Access to competent contractors Updating of technical documents *

2

3

.78 .71 .69 .67 .67 .60 .57 .39 .39 .39

4

5

*

6

1 1 1 1 1 1 1 1 1 1

.36

.57 .53 .47 .45 .44 .41

2 2 2 2 2 2 3 3 3 3

.76 .52 .50 .49

.75 .68 .53 .50 .46 .35 .83 .73 .58 .49 .45

.43

.35

4 4 4 4 4 4 5 5 5 5 5

.72 .59 .53 .50 .48 .41

6 6 6 6 6 6

Suggested factor belonging.

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

that has been attributed high importance for safety climate (Zohar and Luria, 2004). Factor 2 comprised 6 items concerning change management and experience feedback and was labeled F2–Change management and experience feedback (Cronbach’s alpha = .84). Typical items defining this factor were whether management were able to explain reasons for change, if the opinions of staff were considered in change management and various items exploring feedback of experiences gained in different situations. Managing change and experience feedback is one of the cornerstones for safety management. A general discussion of experience feedback can be obtained in, for example, Kjellén (2002) and a discussion of different aspects of change management can, for example, be found in Grote (2008). Factor 3 comprised 4 items concerning the immediate working group and was labeled F3–Immediate working group (Cronbach’s alpha = .74). Typical items defining this factor explored facets associated with the respondent’s immediate working group in terms of internal cooperation, cooperation with other groups and availability of group manager. That the nearest working group has influence

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on safety climate has been discussed and observed in several studies (Melía et al., 2008; Tucker et al., 2008; Jiang et al., 2010; Young and Parker, 1999). Factor 4 comprised 6 items concerning knowledge and participation and was labeled F4–Knowledge and participation (Cronbach’s alpha = .78). Typical items defining this factor were the respondents’ self-assessment of their knowledge of nuclear issues such as safety policies, the quality system and general principles regarding nuclear safety. Both knowledge and participation has previously 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 and was labeled F5–Occupational safety (Cronbach’s alpha = .86). Typical items explored the general perceptions of the occupational safety domain as well as time dedicated to occupational safety procedures. Safety climate studies have typically not made a distinction among different types of safeties and some researchers have questioned if it is reasonable to assume the existence of generic safety climates that hold between different branches and types of safeties (Grote, 2012; Coyle et al., 1995; McDonald and Ryan, 1992). One of the reasons for updating the 2007 questionnaire was the finding that the respondent’s whished to make distinctions between occupational and nuclear safety – a distinction that tended to be confused in the original questionnaire. Factor 6 comprised 6 items concerning resources and was labeled F6–Resources (Cronbach’s alpha = .84). Typical items explored time and staffing resources. Perhaps somewhat surprising, items measuring time and manning resources have not been so common in safety climate questionnaires. Based on common observations of work in organization, lack of manning and time resources appears to be important factors that influence behavior associated with risk. Also, in studies of human reliability (HRA) constraints imposed by manning and time resources often appear as explanations for more or less safe behavior (De Felice et al., 2012). In conclusion, the factor structure obtained includes several factors previously identified in safety climate research. For example, in a review study by Flin et al. (2000), the most common factors identified were ‘‘management/supervision’’, ‘‘safety systems’’ and ‘‘risk’’, but ‘‘work pressure’’ and ‘‘competence’’ also appeared. Seo et al. (2004), in a review of previously identified factors, found a core of generic safety climate concepts: management commitment to safety, supervisor safety support, coworkers safety support, employee participation in safety, and competence. This six factor model was tested using Lisrel 8.80 (Jöreskog and Sörbom, 2001), by subjecting the ratings by workers on power plant B and the ratings by workers on power plant C to separate confirmatory factor analyses. In order to determine goodness of fit as well as comparative fit for the overall model, a number of fit statistics were used in addition to the chi-square measure. A Root Mean Square Error of Approximation (RMSEA) below .05 was considered as very good fit, and a value below .08 as good fit (Steiger, 1990). As a measure of comparative fit, CFI was used, where levels above .90 were considered indicative of good fit (Bentler, 1990). As a measure of parsimonious fit, Akaike Information Criterion (AIC), where lower levels indicate a more parsimonious model. The Standard Root Mean Residual (SRMR) was used as an indication of the residual of the models, and lower levels indicate better fit. Local fit in terms of factor loadings was also considered. The results of the confirmatory factor analyses of the safety climate survey are presented in Table 2. The model fit for both plants was acceptable, indicating a reasonable fit to data in both organizations. This provides preliminary support for the six factor model derived from the exploratory factor analysis. Closer inspection of the factor loadings showed that all items loaded significantly on

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

Power plant B Power plant Cb *

df

v2

RMSEA

SRMR

CFI

AIC

614 614

5688.65* 4332.72*

0.093 0.10

0.070 0.074

0.95 0.96

4573.23 4510.72

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

Table 3 Cronbach’s alpha. Factor

Number of items

F1–Safety F2–Change management and experience feedback F3–Immediate working group F4–Knowledge and participation F5–Occupational safety F6–Resources

Power plant A

B

C

10 6

.93 .84

.93 .86

.95 .89

4 6 5 6

.74 .78 .86 .84

.76 .78 .86 .82

.82 .80 .86 .87

Table 4 Number of respondents. Department

Power plant A B C

Operation

Maintenance

Engineering support

442 194 164

248 206 137

144 139 120

the proposed factors, indicating a good local fit for the proposed model in both samples tested. The reliability levels (Cronbach’s alpha) for the dimensions included 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 the ratings, with Department (Operation, Maintenance, Engineering support) and Power plant (A, B, C) as between subjects factors. Numbers of respondents in each department and in each Power plant are presented in Table 4. The three departments examined were the three largest departments. Please note that in the factor analyses respondents from smaller department were also included. For F1–Safety management, a small but significant effect of Department was found (F2,1773 = 22.36, p < .001, g2partial = .025). Workers in the Operations department gave somewhat higher ratings on F1–Safety management than workers in the two other departments, see Fig. 1. Neither the effect of Power plant nor the Power plant  Department interaction effect was however significant. For F2–Change management and experience feedback a very small but significant effect of Power Plant was found (F2,1764 = 6.56, p = .001, g2partial = .007). Workers in Power plant B rated F2–Change Management and experience feedback marginally lower than workers in the two other Power plants, see Fig. 2. Neither the effect of Department nor the Power plant  Department interaction effect was significant.

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Fig. 1. Estimated marginal mean ratings on F1–Safety management as a function of Department (Operation, Maintenance or Engineering support) and Power 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. 2. Mean ratings on F2–Change Management and experience feedback 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).

For F3–Immediate working group there was also a very small but significant effect of Power plant (F2,1777 = 5.63, p = .004, g2partial = .006). However, the differences between the three departments was larger (F2,1777 = 51.25, p < .001, g2partial = .055). Workers in the Operations department gave higher ratings on F3–Immediate working group than did workers in the two other departments, see Fig. 3. The Power plant  Department interaction effect was not significant. Also for F4–Knowledge and participation there was significant differences between the three departments (F2,1779 = 46.18, p < .001, g2partial = .049) with especially high ratings from workers in the Operation department, see Fig. 4. There were however no significant differences between the three Power Plants and there was no significant Power plant  Department interaction effect. For F5–Occupational safety we obtained a main effect of Power plant (F2,1735 = 5.24, p = .009, g2partial = .005), a main effect of Department (F2,1735 = 7.48, p = .001, g2partial = .009), and an interaction effect between Power plant  Department (F2,1735 = 3.59, p = .006, g2partial = .008). All effects were small however. The result is illustrated in Fig. 5. For F6–Resources we obtained a main effect of Power plant (F2,1774 = 30.44, p < .001, g2partial = .033). Workers in Power plant B

gave especially low ratings on F6–Resources. We also obtained a main effect of Department (F2,1774 = 34.79, p < .001, g2partial = .038).Workers in the Operations department gave especially high ratings on F6–Resources. We also obtained a very small but significant interaction effect Power plant  Department (F2,1774 = 2.85, p = .023, g2partial = .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 other industries, in need of strong integration between different sub processes to be safe and effective. This integration is complicated by the fact that nuclear power plants include several professional groups, 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 in view of the existence of several professional subcultures. Such subcultures may transcend individual organizations, for example by the existence of professional networks, professional journals, use of language, jargons, etc. The present research provides tentative evidence that the differences between professional

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

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 5 Eta-squared partial for the main effect of Power plant, the main effect of Department and the Power plant  Department interaction effect. Factor

Power plant

Department

Power plant  Department

F1–Safety Management F2–Change management and experience feedback F3–Immediate working group F4–Knowledge and participation F5–Occupational safety F6–Resources

.003 .007**

.025*** .003

.004 .002

.006** .000

.055*** .049***

.003 .002

.005** .033***

.009*** .038***

.008** .006*

*

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

subcultures, on at least some dimensions of safety climate, are larger than the differences found between plants, indicating that belonging to a particular professional subcultures is more important for safety climate perceptions than what plant one works in. As mentioned in the introduction a similar observation was done by Jones and James (1979) in a study of naval ships.

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How can the differences between plants and professional groups observed in the present study be explained and what are the consequences for practices and research? These two broad questions will be addressed in this final section. The first factor, named ‘‘Safety management’’, explained 36% of the variance and contains individual items that can be viewed as the ‘‘core’’ of safety culture/climate (management commitment on safety, correction of safety deficiencies, clear roles and responsibilities, etc.). A small but significant difference between departments was obtained were Operations departments scored somewhat higher than the other two departments. One potential explanation for this result is that Operations departments, by the nature of their ‘‘sharp end’’ activities, have developed a more rule oriented culture with a clearly perceived production line type of organization. Operations departments are directly responsible for nuclear safety which creates a strong demand for being informed about the dynamic operating state of the plant. However, it is also possible that Operations departments exhibit a somewhat more defensive stance about questionnaire items exploring rules, responsibilities, management commitment, etc. In comparison, Technical support organizations and Maintenance are usually more project oriented. The small but significant differences between plants in Factor 2 – Change management and experience feedback – can presumably be explained in the context of the volume of ongoing retrofits and change management projects that was present at the time for this study. The different plants have varied schedules for when large retrofit programs should be implemented. These programs put a lot of burden on the technical support departments and to some extent also on the maintenance departments. Judging from the factor labeled – ‘‘Immediate working group’’ – a factor strongly defined by items exploring internal and external cooperation, there appears to be a relatively homogenous ‘‘operating culture’’ existing at all the nuclear power plants. A very small but significant effect of Power plant was observed. However, the differences between the three departments were larger. It is tempting to understand this finding as being a result of standardization with respect to operating procedures, simulator training, etc. which increases the possibility to create a shared collective ‘‘operator identity.’’ Maintenance work, by comparison, is divided into several relatively independent subgroups (mechanical, electrical, instrumental, etc.) and the same holds for engineering, which may result in relatively more coordinating difficulties in comparison with the operation subculture. The factor labeled ‘‘Knowledge and participation’’ (Factor 4) indicates the existence of strong professional subcultures regardless of plants. Again, this observation can presumably be explained by differences in the characteristics of work among the different professional groups. Maintenance departments and technical support are less homogeneous that operation departments. On Factor 5 – Occupational safety – there were small but significant differences both between power plants and professional groups. We refrain from speculating about the reasons for these differences. It is still worth noting, however, that much of safety climate research have been performed in the context of occupational safety rather than system safety. The fact that occupational safety is discerned as a separate factor in the analysis suggests that work trying to diagnose safety culture/climate should be sensitive to what kind on safety that is in focus. Concerning Factor 6 – Resources – there were also differences among the power plants. By comparing Fig. 2 (change management) and Fig. 5 (resources) we can see that it is people at plant B who scored the lowest in both of these factors. This aspect of safety culture/climate is thus best perceived as contextual, rather than one reflecting basic differences in more stable professional cultures. Some general discussion themes of relevance for the present report will be discussed below including a discussion of some more

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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 distinguished by differences in educational backgrounds, career developments, training opportunities and the type of core task in focus for the respective group. Organizational cultures have been understood as reflecting different ideologies (Beyer, 1981; Zammuto et al., 2000). An ideology represents a relatively coherent set of beliefs about how to work to attain desired outcomes and how to understand the world; the concept of ideology is thus very closely related to the concept of culture, and particularly those cultural theories that focus on the deeper assumptions as being a core constituent of a culture (Schein, 2004). A possible way to further understand the differences found in the present study could be to discern various ideologies and connected value systems for the three professional groups. The competing values framework represents a conceptual framework that might be suitable for such a deeper inquiry. Using the competing values framework (Quinn and Rohrbaugh, 1983) as a point of departure, the following ideologies/models have been suggested: the Human Relational Model (focus on development of human resources); the Internal Process Model (focus on stability and control); the Open system model (focus on growth and resource acquisition) and the Rational Goal Model (focused on productivity and efficiency). Research departing from the competing value framework in relation to safety is represented by, for example Colley et al. (2013). Prima facie, all these above mentioned ideologies are present at nuclear power plants. From an overall safety perspective, the Internal Process Model is perhaps the dominant one with its focus on control and stability of operations. At the same time, management also has to take into account a Rational Goal Model, where focusing on productivity and efficiency and the balance between focusing on safety and productivity has been perceived as a core dimension of safety culture/climate (Zohar, 2010). Different professional groups might develop different profiles in terms of those ideologies mentioned above, and this could provide important information for change management efforts regarding safety culture. Another line of research that further could explore how different professional groups manifest different climates can be found in sociological and critical traditions focusing on human power relations (Antonsen, 2009). At nuclear plants, different professional groups have access to various levels of power (for example, operation departments are usually very strong centers of power). The status might thus differ between professional groups. For example, maintenance has sometimes been characterized as manual labor with 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 may differ in organizations and what this implies for safety culture/climate assessment and change. What are the more concrete implications of the present research in terms of practices for safety culture/safety climate diagnostics and change management? Firstly, the present research indicates that a unit of analysis which is based on the idea that professional cultures are important in diagnosing safety culture/ climate. General assessment tools for safety climate should, we believe, have a more focused approach that is tailored to the characteristics of different professional groups, their context and tasks. Secondly, different kinds of safety should, if relevant, be addressed as present in the same organization (occupational safety, system safety, etc.), rather than as an undifferentiated view of the concept of safety. Thirdly, it should be recognized that some facets of an organizations culture/climate are more stable than others, for

example, contextual factors such as reorganizations and major technological retrofits may influence some professional groups much more than others. This entails that global generalizations of the type that an organization has ‘‘a good/bad safety culture’’ always should be taken with caution and be related to the dynamics of the underlying factors used in the assessment. Fourthly, safety culture/climate is perhaps best diagnosed in the context of also using items that explore more general organizational characteristics other than those that are believed to be safety related. Many different cultures are present in organizations (professional cultures, innovation cultures, production cultures, different types of safety, etc.) and to understand the position of ‘‘safety’’ in these, the diagnostic tools used should be sufficiently broad and explore several interacting subcultures. The present research could be criticized on several grounds. Firstly, the questionnaire used could be biased towards items which perhaps are more familiar to some groups than others, thus creating various response biases. For example, a high score in some items might indicate that a person perceives that some state of affairs are reasonably good ‘‘in general’’ (as a deductive statement) but another person may draw on experiences from particular salient cases in a more inductive cognitive style. Questionnaires about safety climate, including the present one, are not always sensitive to such potential differences, and cognitive styles could perhaps vary between professional groups. For example, depending on job characteristics, some groups could exhibit a more nuanced cognitive map with respect to safety issues than another group. A second problem with a questionnaire of the present kind concerns the general criticism that can be directed to these means of collecting information about safety climates (Guldenmund, 2007). Various factors including social desirability, motives to ‘‘punish’’ management, etc. could of course influence the results. A third criticism could be directed to the strategy used here by which the same factor structure was used as a benchmark for the comparison. An alternative approach could have been to analyze the data by a departure in individual factor structures obtained for each professional group. It is possible that different professional groups would obtain slightly different factor structures. This could be the subject for further research.

5. Summary and general conclusions  An exploratory factor analysis on ratings on a safety climate survey by workers on power plant A resulted in a six-factor solution explaining a total of 56.0% of the variance in the items included. The six factors were considered to measure Safety management, Change management and experience feedback, Immediate working group, Knowledge and participation, Occupational safety, and Resources.  The six factor model was tested by running a confirmatory factor analysis on the ratings by workers on power plant B 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 departments (Operation, Maintenance, Engineering support) and power plants (A, B, C) as the between-subjects factors. Differences between power plants as well as differences between departments were found for several factors. Overall, the differences between departments were larger than those between power plants.  Further research should aim for a closer analysis of the ideologies that characterize different professional groups at nuclear power plants – for instance in terms of the competing values framework. Also more attention should be devoted to understanding how power relations might affect safety cultures.

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 Since nuclear power plants are in need of strong coordination between professional groups, management attention to this issue seems particularly important to support strong safety cultures – attention to differences in professional culture might be an important aspect in this work.  There are several types of safety in many organizations (occupational, system, etc.) and tools to diagnose safety culture/climate should 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 realm of other types of values present in organizations.

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