Examining the relationship between safety culture maturity and safety performance of the mining industry

Safety Science 113 (2019) 345–355

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Examining the relationship between safety culture maturity and safety performance of the mining industry

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Eric Stemna,c, , Carmel Bofingera, David Cliffa, Maureen E. Hassallb a

Minerals Industry Safety and Health Centre, Sustainable Minerals Institute, The University of Queensland, Brisbane, QLD 4072, Australia The School of Chemical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia c Environmental and Safety Engineering Department, University of Mines and Technology, P.O. Box 237, Tarkwa, Ghana b

A R T I C LE I N FO

A B S T R A C T

Keywords: Safety culture Maturity model Ghanaian Mining Industry Incidence rate Maturity framework

A mature safety culture is regarded as an important means of ensuring good safety performance, particularly in reducing accidents. However, there is little empirical evidence in the literature that links safety culture maturity with actual safety performance metric. In this study, a safety culture maturity framework was used to examine the safety culture maturity level of mines in Ghana, and to explore the relationship of cultural maturity with accident rates. The safety culture maturity framework used consisted of 3 person and 10 system elements across five levels of culture maturity. A survey comprising the 13 elements was conducted among 828 employees of four large-scale gold mines in Ghana. Through principal component analysis, the structure of the framework was found valid and produced a good fit after testing the model through confirmatory factor analysis. One-way ANOVA showed that the mines had statistically significant differences in their mean incidence rate and pairwise comparison test revealed specific statistically significant mines. Similarly, Kruskal-Wallis H test also showed that the mines’ safety culture maturity scores differed significantly from each other and a pairwise test identified specific mines with significant differences. It was found that mines with lower incidence rates consistently had higher safety culture maturity scores for the elements than mines with higher incidence rate. Also, correlation analysis indicated a strong negative correlation between the incidence rate and most elements of the safety culture maturity framework. The model/framework used was found useful and practical to both employees and management, enabling the identification of weak areas that require improvements interventions.

1. Introduction Over the past three decades, safety culture has been deemed as a significant component of safety management systems (SMS) of many safety-critical industries including transportation (Czech et al., 2014; Payer, 1998), energy (Rosen, 1997) and oil and gas (May, 1998). The term safety culture was first used in the report of the International Nuclear Safety Advisory Group (INSAG) on the review of the 1986 Chernobyl disaster (Cooper, 2000; INSAG, 1986). Lee (1995) indicates that the violations and errors of the operating procedures that contributed to that disaster were evidence of a poor safety culture. Significant early works were done by Zohar (1980) and Cox and Cox (1991) and in 1991 Pidgeon (1991) described it as the most important theoretical development in health and safety. Reason (1998) also argues that safety culture is more important than other safety performance improvements strategies such as increased supervision and laborious procedures. According to Reason, the application of safety

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culture for accident reduction becomes even more important when an organisation’s accident statistics reach a plateau. At this plateau stage, introducing more hardware (technical controls) and software (administrative controls like procedures) become inappropriate (Cox and Cox, 1991). Rather, the hearts and minds of organisational members should be addressed (Parker et al., 2006). Reason (1997) proposes pragmatic ways of instituting such a culture – a culture that appeals to the hearts and minds of both frontline workers and management alike. Detailed reviews on the topic have been provided by Cooper (2000), HSE (2005) and Goncalves Filho and Waterson (2018). The term safety culture has been defined differently by different authors, and a collection of these definitions is provided by Cooper (2000). The commonality in the numerous definitions is that they can all be grouped into normative beliefs perspective, in so far as each is focused on different degrees on the way people think and/or behave in relation to safety (Cooper, 2000). Clarke (1999) defines it as the values and beliefs of an organisation that is specific to health and safety.

Corresponding author. E-mail addresses: [email protected], [email protected] (E. Stemn).

https://doi.org/10.1016/j.ssci.2018.12.008 Received 10 April 2018; Received in revised form 6 December 2018; Accepted 10 December 2018 0925-7535/ © 2018 Elsevier Ltd. All rights reserved.

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Zohar, 1980, 2000). These authors found a negative relationship between workers’ perceptions of a company’s safety climate and their accident experiences. Others equally found no association between safety climate and behavioural measures of safety performance (Glendon and Litherland, 2001). In a related work, Milczarek and Najmiec (2004) also justified the association between a worker’s safety culture and safety behaviour. Through a questionnaire study, they observed that workers who had accident experiences had lower safety culture than their counterpart who had no accident experience. Also, most of the studies reported so far focused on the abstract intangible component of safety climate which often provides a subjective measure rather than an objective evaluation (Fleming, 2007). In addition, all the studies have relied on self-reported accidents, not accident rates maintained by companies. This is largely because company provided accident rates have been criticised to be unreliable for such studies due to the likelihood of underreporting (McCurdy et al., 1991; Stout and Bell, 1991; Thompson et al., 1998; Witt et al., 1994). In this study, we developed a safety culture maturity framework, validated the usefulness of the framework in Ghanaian mines and assessed the relationship between safety culture maturity and actual accident reports. We do so with incident data supplied by Ghanaian mining companies. We argue that accident rates maintained by these companies might be a good data source if validity and reliability can be ascertained. It has been recognised that the accident rate of the mining industry remains alarming. The International Labour Organisation has stated that mining which employs 1% of the world’s workforce is responsible for 8% of the global workplace deaths (Duke, 2016; Lang, 2010). Therefore, the need to improve the safety performance of the industry, and reduce and eliminate workplace fatality is paramount. We also collected data using a safety culture maturity questionnaire comprising of person and system components and each can be analysed separately to determine which of them has more effect on the safety outcome.

According to Hopkins (2005), safety culture is about organisational collective practices. He emphasises that this view is more useful than the concept of culture as values because it provides a practical means of ensuring cultural changes. This understanding of safety culture supports the knowledge that culture is specific to a group because the practices of one group are unlikely to be relevant in their entirety to another (Filho et al., 2010). This study adopts this concept of safety culture. According to Fleming (2007), safety culture can be assessed either through a subjective or an objective approach. He explains that whereas objective assessments use only tangible concrete indicators (such as accident reports and reviews) visible to both insiders and outsiders of an organisation, subjective assessments use surveys requesting organisational members to indicate their opinion on mostly abstract intangibles indicators such as behaviours. Despite the differences in assessment approaches, safety culture is gaining widespread interest due to the changing characteristics of safety-critical industries (Kuhlmann, 2001; Milczarek and Najmiec, 2004). Some safety scholars have emphasised the effect of the safety culture concept in improving the safety performance of organisations by reducing accidents and disasters (Cooper, 2000). It has been stated elsewhere in the literature that organisations with good safety culture have lower accident rates than those with weak safety culture (Horbury and Bottomley, 1998). Clarke (1999) and Parker et al. (2006) stress that the application of safety culture for improving safety performance focuses on how social forces within an organisation act upon members with respect to safety. 2. The impact of safety culture/climate works Safety climate and safety culture evolved in the 1980s, originating from the overarching concept of organisational climate and organisational culture (Hecker and Goldenhar, 2013). More specifically, safety culture was first used in the INSAG report into the Chernobyl disaster (INSAG, 1986) Although the two concepts are often used interchangeably, some scholar argues that they are actually distinct but related (Mearns and Flin, 1999). The literature regards safety climate as the collective view of safety within an organisation, which exemplifies a snapshot of an organisation’s state of safety at any given time (Cooper, 2000; Zohar, 1980). Safety culture, on the other hand, reflects fundamental beliefs, values, norms and traditions about safety that resides within the larger framework of organisational systems (Mearns and Flin, 1999). Some scholars argue that safety climate is a manifestation of normative values, belief and behaviours at a discrete point in time, expressing safety culture as an underlying system that drives safety climate (Cooper, 2000; Guldenmund, 2000). Although there are divergent views on how safety culture and safety climate should be measured, there are overlaps in the assessment methodologies that have been used to assess the two concepts (Cox and Flin, 1998; Fleming, 2007; Mearns and Flin, 1999). For instance, Cox and Flin (1998) argues that some self-report surveys claiming to measure safety culture have components similar to those claiming to measure safety climate. Mearns and Flin (1999) further argues that the literature indicates that while perceptions/descriptive beliefs are the basis of climate, attitudes/normative beliefs are the foundations of culture. Safety climate is quite changeable as it is highly influenced by recent events, whereas safety culture is created from historical context based on repeated long-term patterns (Goulart, 2013). Thus, because of the relative stability of safety culture, improvement in safety culture maturity can be used as a more robust means of improving a company’s safety performance, which has long been emphasised in the literature (Clarke, 1999; Cooper, 2000; Parker et al., 2006; Reason, 2000). Although scholars stress the importance of safety culture maturity for improving safety performance, most of the works completed are conceptual. Most of the existing empirical works focus on workers’ risk behaviours and their perceptions on the safety climate of their organisations (Beus et al., 2010; Cheyne et al., 1998; Hayes et al., 1998; Neal et al., 2000; Østvik et al., 1997; Vinodkumar and Bhasi, 2009;

3. Concept of maturity models and safety culture Maturity models involve the use of several criteria on different maturity levels to evaluate the effectiveness of an analysed unit such as an organisation (Goncalves Filho and Waterson, 2018). The concept has been applied to determine how organisations deal with information, attitudes, values and beliefs (Hudson, 2001, 2003; Westrum, 2004, 2014). For example, Westrum (1993, 1996) proposed a 3-level maturity model concerning how organisations deal with information. Westrum’s 3-level model was later extended to 5 levels by Reason (1997), Hudson and Willekes (2000) and Fleming (2001), and adapted more specifically to safety culture maturity. The addition of the two extra levels was to add depth and allow for a more subtle classification (Parker et al., 2006). A detailed description of Hudson’s model is provided by Hudson (2003, 2007) and Parker et al. (2006). Fleming's (2001) model was based on the concept of capability maturity model used in software engineering and was developed to assist organisations to determine the maturity levels of their safety culture. His model is only applicable in (1) organisation with adequate safety management system, (2) where technical failures are not the dominant accident causal factor, (3) the organisation is compliant with health and safety law and (4) safety is not driven by avoidance of prosecution but by the desire to prevent accidents. Unlike Hudson’s model, Fleming’s model lacks empirical application largely due to these constraints. Though the concept of safety culture maturity model is recent, it has received wide acceptance and has been applied in industries including transportation (Gordon et al., 2007; Kyriakidis et al., 2012), offshore (Fleming, 2001; Hudson, 2007), petrochemical (Filho et al., 2010) and mining (Foster and Hoult, 2013).

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3.1. Safety culture maturity framework

4. Methods

The term safety culture framework as used here refers to a range of key aspects of safety culture across all levels of the maturity model that can be used by organisations to understand their safety culture. Whilst the maturity model refers to the level/stage of maturity, the framework refers to specific safety cultural elements such as management commitment and safety communications. Based on these elements, questionnaires and/or audits tools are developed with respect to the maturity model to study the safety culture maturity level of an organisation. Fleming’s (2001) model determines the safety culture maturity level across 10 elements. He emphasised that the overall safety culture maturity level of an organisation can be determined by finding the average of the level of maturity at each of the ten elements. By interviewing 26 top executives of oil companies, Parker et al. (2006) developed a theory-based framework consisting of 18 elements. Breaking down the qualitative descriptions provided by the executives into constituent statements, they develop a grid containing brief statements for each of the elements investigated across all five maturity levels. The 18 elements of the framework were then classified into tangible concrete elements (such as management systems) and intangible abstract elements (such as attitudes and behaviours). Through an empirical study, Lawrie et al. (2006) provided support for the framework. In a related work, Filho et al. (2010) developed a five-dimensional maturity framework and tested its applicability in the Brazilian petrochemical industry.

This research involved collecting safety culture and incident rate information from four large-scale mines in Ghana. The four mines together employ 9767 workers and were selected to enable a comparison of their incidence rates and self-reported safety culture maturity scores to determine if any association exist between their incidence rate and safety culture maturity level. All four sites are large-scale open-pit metalliferous gold mines, with Mines B and C having underground operations. However, the data used for this study excludes the underground operations. Mining currently takes place in 2, 4, 2, 1 open-pits at Mines A, B, C and D respectively. Mines B, C and D operate a conventional carbon-in-leach (CIL) milling operation, whereas Mine A operates a carbon-in-pulp processing plant. Accessibility to the production areas of all four mines is through ramps. The mines have been operating for different years and had different incidence rates. 4.1. Adapting a safety culture maturity model and framework for the Ghanaian Mining Industry The 5-level safety culture maturity model of Hudson’s was adapted for this research. This model was found to be more suitable for use in the Ghanaian mining industry (GMI) than Fleming’s (2001) model because the latter is only relevant to organisations satisfying a number of specific criteria. These criteria limited the general application of Fleming’s (2001) model in the GMI. For instance, preliminary analysis of accident data showed that technical failure is one of the major accident causal factors. Also, interviews with some mineworkers indicated that safety was driven by avoidance of punishment at some sites which further limits the use of Fleming’s (2001) model. The naming system of the model used is similar to the UK Coal Journey, MIRM and the Anglo American models because they were found to be simple and familiar to the GMI and would be easily understood by management and employees. The “Pathological” “Calculative” and “Generative” levels in Hudson’s model were renamed to “Basic” “Compliant” and “Resilient” respectively, similar to the MIRM, UK Coal Journey and the Anglo American models. However, the description of the various maturity levels in the model shown in Fig. 1 are similar to Hudson’s descriptions. Similar to the UK Safety Journey model, the maturity levels were seen as overlapping. This was to recognise the possibility of a mine site being at different maturity levels across the various safety culture elements. As shown in Fig. 1, the model is such that, at the lowest level the site has no culture and incidents are accepted, and as the site progress up, systems are put in place to improve the culture and prevent incidents. Based the model, a framework consisting of various elements and indicators was developed based on the literature (Anglo American Plc, 2010; Foster and Hoult, 2013; Mine Safety Operations Branch, 2011; Parker et al., 2006). The framework was divided into person and systems elements. The system elements are concrete tangible elements such as risks and hazards management while the person elements are abstract less tangible or intangibles such as workers commitments to safety and care for co-workers. This dichotomised classification of tangibles and intangibles, which formed the two dimensions of the framework named “Person” and “System” were based on the work of Parker et al. (2006). The person elements were based on the Anglo American safety risk management process and the system element were based on the UK Coal Journey model, the Anglo American safety risk management process and other existing literature. As shown in Table 1, the person dimension consisted of 3 elements with a total of 6 indicators, whereas the system dimension consisted of 10 elements with a total of 28 indicators.

3.2. Safety culture maturity models/frameworks in the mining and minerals industry Safety culture maturity model is a relatively new concept in the mining and minerals industry. There are disparities in safety culture within the industry and safety management varies across different operations, limiting the effectiveness of best practices that are introduced. As noted by Foster and Hoult (2013), mine sites at lower levels will require different strategies to those at the advanced levels, making the concept of maturity model appropriate for the industry. Early work was undertaken by a group of researchers at the Mineral Industry Safety and Health Centre of the University of Queensland who designed the Mineral Industry Risk Management Maturity (MIRM) Chart (Mine Safety Operations Branch, 2011). The chart which consists of five maturity levels arranged as a ladder was developed based on Hudson’s model and an approach used by Bayside Aluminium, a BHP Billiton site in Richards Bay, South Africa (Foster and Hoult, 2013; Mine Safety Operations Branch, 2011). Although the MIRM ladder adopts different names, the implied levels of maturity are similar to Hudson’s model. One significant aspect of the MIRM model is the emphasis on a strong relationship between the status of systems and the culture of the site. It, therefore, recognises that both culture and systems must progress together up the ladder and that one cannot progress without the other. Based on the MIRM Chart, Anglo American developed a safety journey workbook that has been divided into 6 people elements and 17 system elements (Anglo American Plc, 2010). Unlike the MIRM ladder, their model is arranged in a spiral staircase. In 2009 UK Coal Plc decided to address it declining safety performance and in 2010 a new safety management system (SMS) was adopted, drawing lessons from best practices of other mining companies (Foster and Hoult, 2013). The new SMS consisted of 12 standards. They recognised the need to evaluate compliance with the 12 standards, however, did not want to use a simple “yes” or “no”. Therefore, they decided to adopt a maturity model approach (Foster and Hoult, 2013). The UK Coal Journey model, which consisted of 5 overlapping steps did not separate person elements from system elements. Rather it incorporates the elements into each of the 12 standards of the SMS.

4.2. Safety culture maturity data collection The safety culture maturity of the mines was determined through 347

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Fig. 1. Safety culture maturity model.

that best reflects the current culture of the mine. The self-report questionnaires used for the study is shown Appendix A. To ensure equal representation, employees were stratified into different work groups such those involved in production and support service workers and randomly sampled. The fist author spent 6 months (October 2016–March 2017) in Ghana visiting the mines to distribute and collect completed questionnaires, moving from one section/department to the other at each of the mines. Since the mines practised a decentralised safety management, each department had at least a safety officer responsible for health and safety of the department. The safety officers were the main contact persons through whom questionnaires were distributed and collected. Bulk questionnaires were given to the safety officers who then randomly distributed them to employees in their department. The researcher also personally distributed some questionnaires during toolbox meetings, lunch breaks and personal visit to offices. This strategy was successful because the researcher spent at least a week at each of the mines. Some of the questionnaires were completed and returned on the same day whiles others were returned a few days later. Those who could not complete their questionnaires during the field visits were given extra days to complete and return them to their respective safety officers, who then delivered them to the researcher. The questionnaires were administered in English since that the official medium of instruction in all Ghanaian schools and the participants could read and write English. Of the 1040 distributed questionnaires, 850 were returned, however, 22 were incomplete and were removed. The average age and total mining experience of the respondents were 35.1 ( ± 15.5) years and 12.7 ( ± 9.6) years respectively. 83% were males and 17% were females. Concerning their hierarchical levels at the mines, 32% and 42% were frontline workers and frontline supervisors respectively, and 19% and 7% were middle and top managers respectively. Regarding the working groups the respondents belonged to, 44% were involved in mining operations, 17% in metallurgical and mineral processing, 18% in maintenance and engineering and 21% in support services. Table 2 shows characteristics of the mines All four mines are foreign owned, however, mines A, C and D belong to a multinational company, whereas mine B is a national company.

Table 1 Safety culture framework used for the study. Dimension

Elements

Indicators/Items

Person

Care and Respect (PE1)

Caring for myself Caring for others Leadership commitment Safety accountability Employee safety involvement Employee coaching and mentoring Work safety planning Rewards of good safety performance Safety management plan Status and size of safety department Safety and profitability/ production Contractor management Work-site job safety technique Informal risk assessment Formal risk assessment Hazard reporting Awareness of regulatory requirements Safety goals and target Safety goals and target monitoring Measurement of safety performance Safety communication HSE meetings Safety procedures Safety inspection Maintenance Safety behaviour monitoring Audit and review Safety training Assessments of safety training Acquiring information/ reporting Investigation and analysis Planning corrective actions Implementing and monitoring corrective actions Feedback and sharing of lessons

Safety Commitment and Accountability (PE2) Employee Involvement and Coaching (PE3) System

Safety Leadership (SE1)

Safety Policy and Commitment (SE2)

Risks and Hazards Management (SE3)

Regulatory Requirements (SE4) Objectives, Targets and Performance Measurement (SE5)

Safety Communication (SE6) Operational Control (SE7)

Monitoring, Audit and Review (SE8) Training and Competency (SE9) Learning from Incidents (SE10)

Table 2 Number of questionnaires distributed and analysed from each of the mines.

self-reported rating. A multiple-item questionnaire based on the safety culture maturity model and framework was administered during working hours to a random sample of 1040 employees across the four mines. The questionnaire consisted of 34 items; 6 and 28 items for the person and system elements respectively. Each item had 5 statements representing the five levels of culture maturity. For each of the 34 items, respondents were expected to choose one of the five statements 348

Mine

Number of employees

Distributed questionnaires

Analysed questionnaires

Response rate

A B C D Total

1872 4892 1603 1400 9767

259 330 230 221 1040

207 259 179 183 828

79.9% 78.5% 77.8% 82.8% 79.6%

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significant differences in their incidence rate also had statistically significant differences in their safety culture maturity scores. The results were further examined to determine whether, for the statistically significant sites, those that had lower incidence rates consistently had higher maturity scores and those that had higher incidence rates consistently had lower maturity scores. Finally, the five-year incidence rate for each of the sites was aggregated into a single score for the sites, likewise the safety culture maturity scores of the individual elements. Spearman’s correlation analysis was then conducted on the two aggregated variables to determine whether a statistically significant correlation existed between the incidence rate and the safety culture maturity scores and to identify where the relationship was weak and strong.

4.3. Incident data collection The data used comprised of a five-year monthly injury data containing the number of injuries recorded in a month, the total hours worked and the number of monthly employees each for the four mines. Injury data was also obtained during field visits to each of the mines. The injury data used in the study is the total recordable injury cases as defined by the ICMM (2014). To validate the reliability of the injury data, fatalities and serious injuries statistics were obtained from the Inspectorate Division of the Minerals Commission (responsible for regulating the health and safety of the GMI). 4.4. Data analysis 4.4.1. Incidence rate At all the mines, the frequency of less severe injuries such as medical treated injuries (MTI) and restricted work injuries (RWI) far exceeded fatalities and lost time injuries (LTI). For the five-year period, there were 2, 1, 2, 3 and 4, 8, 12, 5 fatalities and LTIs respectively at mines A, B, C and D. Thus, there were more LTIs than fatalities at all the mines, with the LTIs being more frequent at mine B and C than A and D. The monthly incidence (total reportable injury) rates of each of the sites for each one hundred workers employed were computed based on the Australian Standard (1990) for workplace injury and disease recording. To test whether any statistically significant differences existed between the means of the incidence rates of the four sites, a one-way ANOVA was carried out. The incidence rate was the dependent variable and the mine sites the independent variable. The data was first checked for normality and homogeneity of variances using Shapiro-Wilk and Levene tests respectively. The results indicated that the incidence rate was normally distributed, and the variance was statistically significantly equal. Since ANOVA is an omnibus test statistic that lacks the capability to determine which specific groups were statistically significantly different from each other, Tukey’s HSD post hoc test was conducted. This was to ascertain which specific site pairs’ incidence rate differ from each other. Since there were four sites, a total of 6 distinct combinations of groups were found, thus 6 tests were performed.

5. Results 5.1. Incidence rate of the mine sites There was a statistically significant difference between the incidence rates of the mines as determined by one-way ANOVA (F (3, 236) = 20.11, p < 0.01), indicating that the mean incidence rates are not the same for the four sites. A Tukey HSD post hoc test (see Table 3) revealed that the incidence rate of Mine A (0.12 ± 0.11) was statistically significantly lower than that of Mine B (0.22 ± 0.13), C (0.26 ± 0.05) and D (0.17 ± 0.11). Also, the incidence rate of Mine D was statistically significantly lower than that of C. However, there was no statistically significant difference between the incidence rates of mines A and B and B and D. 5.2. Safety culture maturity of the mine sites 5.2.1. Exploratory factor analysis Consistent with the literature (Vinodkumar and Bhasi, 2009), 70% of the completed questionnaires were randomly selected and subjected to principal component factor analysis (PCA) to determine the factor structure of the safety culture maturity scale. The remaining 30% were reserved for confirmatory factor analysis as described in the next paragraph. The data from 70% of the questionnaires was found suitable for factor analysis as the case-to-variable was above the minimum threshold of 5:1 (Hair et al., 1995), the measure of sampling adequacy, Kaiser-Mayer-Olkin (KMO) was 0.94, with Bartlett's Test of Sphericity value = 6781.69, df = 528, p < 0.01. To enhance factor interpretability, varimax rotation was performed, with a factor loading cut-off of 0.4 and items with a correlation coefficient below 0.3 were removed. The PCA resulted in the removal of 3 items and the extraction of 5 components with an eigenvalue above 1 which explained 66.35% of the cumulative variance. However, most of the items loaded onto the first two components. Thus, a scree plot and parallel analysis were carried out which resulted in the extraction of the first two components, indicating that those two components have the best and strongest interrelationships among the items and explain a lot more of the variance than the remaining components. The reliability of the instrument was checked and Cronbach Alpha was found to be above the minimum threshold of 0.6 (Hair et al., 1995). The two components, together with their respective number of items, factor loading and variance explained

4.4.2. Safety culture maturity score The focus of this analysis was first to determine the perceived safety culture maturity levels of the mines with respect to the elements of the framework and then determine whether any statistically significant differences exist between the maturity scores of the mines. Since some elements were assessed using multiple indicators, the average position of those elements was determined so that each element was represented with a single indicator. Then, the percentages of responses for each element across the five maturity levels were computed for each of the mine sites. To determine whether any statistically significant differences existed between the safety culture maturity levels of the mines, Kruskal-Wallis H test was conducted where the mines was the independent variable and the maturity levels (1-basic, 2-reactive, 3compliant, 4-proactive, 5-resilient) the dependent variable. The Kruskal-Wallis H test was chosen after results of Shapiro-Wilk normality test and Levene test for equality of variance showed that the maturity level scores were neither normally distributed nor had a homogeneous variance. Moreover, the safety culture data was viewed as categorical and not continuous. Dunn’s post hoc test using Bonferroni correction was carried out to determine the specific mines that were statistically significantly different from each other with respect to the safety culture maturity levels of the various elements.

Table 3 Tukey HSD post hoc test of incidence rate for the sites (significant at p < 0.05).

4.4.3. Association between incidence rate and safety culture maturity score To determine whether any association existed between a site’s incidence rate and its safety culture maturity level, results of the post hoc tests for the incidence rates and the maturity level scores were compared. This was to determine whether the sites that had statistically 349

Pair

Mean difference

Significance

AB AC AD BC BD CD

−0.10 −0.14 −0.05 −0.04 0.05 0.09

p = 0.000 p = 0.000 p = 0.041 p = 0.165 p = 0.051 p = 0.000

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Table 4 Results of PCA showing details of the extracted components. Component of safety culture maturity framework

Number of items

Factor loading

% variance explained

Cronbach Alpha

System elements of the safety culture maturity framework Person elements of the safety culture maturity framework

25 6

0.77–0.54 0.76–0.51

40.28 10.81

0.91 0.87

to compliant) and least characteristics of the higher levels (proactive and resilient). On the other hand, safety policy and commitment, risks and hazards management, operation controls and training and competency appears the best performing elements. The results show that risks and hazards management, safety communication, monitoring, audit and review and training and competency had no selection for the basic level at all four sites. Apart from these three elements, the remaining 6 elements present characteristics of the two extreme levels of maturity at most of the sites. Site A and D appear more mature than B and C since they had the highest frequency of the proactive and resilient levels across most of the elements. On the other hand, Site C appears least mature, having the lowest percentage of the higher maturity levels and the highest percentage of the lower maturity levels for all 10 system elements.

are shown in Table 4. 5.2.2. Confirmatory factor analysis The remaining 30% of the completed questionnaires were subjected to confirmatory factor analysis to determine whether the data will fit the structure of the safety culture maturity framework determined in the exploratory factor analysis. This process is similar to those reported in other studies (Cox and Cheyne, 2000; Neal et al., 2000; Vinodkumar and Bhasi, 2009). The structure of the framework was found suitable as the model fitted the data with the following results; comparative fit index (CFI) = 0.92, Tucker-Lewis index (LTI) = 0.89 and a root mean square error approximation (RMSEA) = 0.053. 5.2.3. Levels of safety culture maturity of the person elements Table 5 shows the percentage of answers from the respondents for the 3-safety culture person elements for each of the mines. They depict characteristics from the lowest level (1-Basic) to the highest level (5Resilient) of safety culture maturity. For the whole cohort, the modal choice was proactive for the elements care and respect and safety commitment and accountability whereas employee involvement and coaching element had a modal choice of compliant. Basic was most frequently chosen across all 3 elements at Site B and C than the other sites, whilst Site A appears the most matured, having the most frequency of the resilient level. The employee involvement and coaching element present characteristics of the two extreme levels of maturity across all the sites. Site C appears to have more characteristics of the lower maturity levels than the remaining sites, having the lowest percentage of the proactive and resilient levels across all the 3 elements.

5.2.5. Testing for statistically significant differences in the safety culture maturity levels The result of the Kruskal-Wallis test showed that there were statistically significant differences in the means of all elements of safety culture maturity between the four sites and the mines have different levels of safety culture maturity as shown in Table 7. Dunn’s pairwise test further showed strong evidence of differences between the safety culture maturity scores of some pairs of sites (Appendix B). For instance, for element PE1, care and respect, mine pairs AB, AC, BC and CD had statistically significant differences in their means score, whereas pairs AD and BD had no difference in their mean score. Again, for the overall safety culture maturity level, site pairs AC, BC and CD had significant differences in their mean scores, whereas, AB, AD and BD did not. The overall maturity score of mine C was lower than the remaining 3 mines. To test if the mean safety culture maturity scores of the mines were statistically different, the four mines were grouped into two; low injury mines (A and D) and high injury mines (C and B). Independent sample t-test was then run to determine the differences in the safety culture maturity scores between low and high injury mines. The result as shown in Table 8 indicates that the mean scores of all the safety culture elements were higher at the low injury mines than at the high injury mines, except for elements PE3 (employee involvement and coaching), SE4 (regulatory requirements) and SE7 (operational controls) were there was no statistically significant difference between the two groups.

5.2.4. Levels of safety culture maturity of the system elements The percentage of answers for the 10 system elements for the sites is depicted in Table 6. It shows characteristics from basic to resilient level of safety culture maturity. Overall, regulatory requirements and learning from incidents appears the worst performing elements across all the sites. They show more characteristics of the lowest levels (basic Table 5 Safety culture maturity level of the person elements across all sites. Person elements of safety culture maturity

% of responses from mine sites A

B

C

D

Overall

Care and respect Basic Reactive Compliant Proactive Resilient

0 7 44 38 11

11 14 21 46 8

9 28 38 22 3

0 10 47 36 6

5 16 35 38 7

Safety commitment and accountability Basic Reactive Compliant Proactive Resilient

0 5 29 48 18

6 14 16 46 18

13 2 53 32 1

0 6 13 75 6

4 6 24 53 13

Employee involvement and coaching Basic Reactive Compliant Proactive Resilient

3 3 27 48 18

5 15 20 42 18

8 13 48 29 2

5 6 65 23 2

5 8 38 36 13

5.3. Association between incidence rate and safety culture maturity level Comparing the results of the pairwise test of the incidence rate and that of the safety culture maturity elements indicated the existence of a relationship between the two variables for some mine pairs. For instance, as shown in Table 9, whereas the mean incidence rate of mine A was lower than that of mine C, its safety culture maturity level was consistently higher than that of mine C for all elements except element SE4, regulatory requirements, where there was no statistically significant difference between the two sites. Similarly, comparison of mine C and D also shows that while mine D had a lower mean incidence rate than mine C, its mean safety culture maturity score for most elements far exceeded that of mine C. These results indicate that mines with lower incidence rates consistently had higher safety culture maturity scores, whiles mines with higher incidence rates had lower safety culture maturity scores, suggesting that a relationship exists between a site’s incidence rate and its safety culture maturity level. 350

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Table 6 Safety culture maturity score the system elements across all sites. System elements of safety culture maturity

Table 7 Kruskal-Wallis H test of safety culture elements of the sites (significant at p < 0.05).

% of responses from site A

B

C

D

Element Name

χ2

df

Significance

PE1. Care and respect PE2. Safety Commitment and accountability PE3. Employee Involvement and Coaching SE1. Safety Leadership SE2. Safety Policy and Commitment SE3. Risks and Hazards Management SE4. Regulatory Requirements SE5. Performance Measurement SE6. Safety Communication SE7. Operational Control SE8. Monitoring, Audit and Review SE9. Training and Competency SE10. Learning from Incidents Overall safety culture maturity

42.782 42.900 54.301 74.985 84.852 60.771 24.372 64.515 43.085 23.573 50.685 20.720 47.067 61.608

3 3 3 3 3 3 3 3 3 3 3 3 3 3

p p p p p p p p p p p p p p

Overall

Safety Leadership Basic Reactive Compliant Proactive Resilient

0 3 33 30 33

0 9 28 43 20

4 13 63 18 0

0 6 41 47 6

1 7 37 38 17

Safety Policy and Commitment Basic Reactive Compliant Proactive Resilient

0 5 23 69 3

2 6 30 55 5

3 21 53 23 0

0 6 14 76 5

1 7 29 59 4

Risks and Hazards Management Basic Reactive Compliant Proactive Resilient

0 0 33 52 15

0 12 16 57 16

0 18 51 31 0

0 6 21 71 2

0 8 29 55 9

Regulatory Requirements Basic Reactive Compliant Proactive Resilient

15 25 36 17 6

8 23 39 21 8

19 22 38 10 11

8 15 53 16 8

11 21 41 18 8

Objectives, Targets and Performance Measurement Basic 0 Reactive 5 Compliant 28 Proactive 45 Resilient 21

5 14 30 43 7

1 21 60 16 2

0 6 36 56 2

2 11 37 42 7

Safety Communication Basic Reactive Compliant Proactive Resilient

0 3 36 61 0

0 22 22 54 2

0 10 68 22 0

0 6 32 53 9

0 9 37 50 3

Operational Control Basic Reactive Compliant Proactive Resilient

0 0 30 67 3

2 9 29 43 17

0 13 38 49 0

0 6 15 75 5

0 6 28 58 8

Monitoring, Audit and Review Basic Reactive Compliant Proactive Resilient

0 3 27 64 6

0 11 33 39 17

0 13 63 22 1

0 6 31 63 0

0 7 40 45 8

Training and Competency Basic Reactive Compliant Proactive Resilient

0 6 18 42 33

0 12 31 18 39

0 13 38 31 18

0 1 20 46 32

0 7 29 32 32

Learning from Incidents Basic Reactive Compliant Proactive Resilient

0 11 42 29 19

5 24 36 29 5

1 27 59 13 0

0 6 54 33 7

2 16 46 29 7

< < < < < < < < < < < < < <

0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001

χ2 – chi-square df – degrees of freedom.

incidence rate and the overall safety culture maturity as well as all elements of the safety culture maturity. The strongest relationship was for elements SE5 (performance measurement, −0.99), SE10 (learning from incidents, −0.98) and PE1 (care and respect, −0.95). On the other hand, there was no significant correlation for element PE 3 (employee involvement and coaching), SE3 (risk and hazards management), SE4 (regulatory requirements), SE6 (safety communication) and SE7 (operational control). A scatter plot (Fig. 2) of the incidence rate and the safety culture maturity scores further shows that mines with lower safety culture maturity score had higher incidence rate and those with higher safety culture maturity scores had lower incidence rates.

6. Discussion A number of limitations should be noted regarding the present study. The first is that the safety culture maturity of the mines was assessed through self-report and not through field observations and site audits. The main advantage of self-report is that it gives a direct perspective of the participants rather than deducing from observations. Self-report measures have however been found to be susceptible to social desirability bias and thus threaten the validity of the study (Fisher, 1993; Grimm, 2010). To overcome this challenge and improve the validity of the findings, several strategies were adopted to increase the number of participants and the study goes beyond the boundary of a single mine. Secondly, the study used company provided accident data which some critique as an unreliable data source for studies of this nature (McCurdy et al., 1991; Stout and Bell, 1991; Thompson et al., 1998; Witt et al., 1994). The data used here were obtained directly from the individual mines and validity with data from the regulator. Data from the two sources were found to be the same/similar, especially for fatalities and serious injuries. For the purposes of this study, it is our opinion that, the company provided data is more reflective of the existing safety performance of the mines. Another limitation is that the research is very specific to the GMI and focuses on only four gold mines. Although three of the mines are part of multinational companies, responses from different cultures and geographic area may produce different results. In addition, only 4 mines participated in the research, which further limits the generalisability of the findings. Given the influence of regulatory and company governance, the generalisation of the findings can only be determined with further testing. Although the framework was reviewed prior to fieldwork, further subject-matter experts review is needed to ensure that statements for each of the maturity level is distinct and that characteristics of the lower levels are not associated with the higher levels of maturity. Furthermore, testing the validity and reliability of the framework statistically will resolve

To determine if this relationship was statistically significant, the means of the five-year incidence rates of the sites together with the mean score of their safety culture maturity score for the 13 elements were correlated. Result of the correlation is presented in Table 10. The coefficient of correlation reveals a negative relationship between the 351

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Table 8 Mean scores of safety culture elements in mines with low incidence rate and in mines with high incidence rate (significant at p < 0.05). Safety culture elements

PE1. Care and respect PE2. Safety commitment and accountability PE3. Employee involvement and coaching SE1. Safety leadership SE2. Safety policy and commitment SE3. Risks and hazards management SE4. Regulatory requirements SE5. Performance measurement SE6. Safety communication SE7. Operational control SE8. Monitoring, audit and review SE9. Training and competency SE10. Learning from incidents Overall safety culture maturity

Mean of safety culture element at mines where the incidence rate was Low (A & D)

High (B & C)

3.56 3.82 3.47 3.76 3.75 3.76 3.23 3.70 3.62 3.58 3.66 4.06 3.50 3.42

3.14 3.31 3.35 3.45 3.34 3.53 3.18 3.19 3.39 3.46 3.43 3.71 2.98 3.19

Statistically significant mine pairs

Incidence rate

AB → (A < B); AC → (A < C) AD → (A < D); CD → (D < C) AB → (A > B); AC → (A > C) BC → (B > C); CD → (D > C) AB → (A > B); AC → (A > C) BD → (D > B); CD → (D > C) AC → (A > C); AD → (A > D) BC → (B > C); BD → (B > D) AC → (A > C); AD → (A > D) BC → (B > C); CD → (D > C) AC → (A > C); BC → (B > C) BD → (D > B); CD → (D > C) AC → (A > C); BC → (B > C) CD → (D > C) AB → (B > A); AD → (D > A) BD → (D > B); CD → (D > C) AB → (B > A); AC → (A > C) BC → (B > C); CD → (D > C) AC → (A > C); BC → (B > C) CD → (D > C) AC → (A > C); BC → (B > C) CD → (D > C) AC → (A > C); BC → (B > C) CD → (D > C) AC → (A > C); BC → (B > C) CD → (D > C) AB → (B > A); AC → (A > C) BD → (D > B); CD → (D > C) AC → (A > C); AD → (A > D) BC → (B > C); CD → (D > C)

PE1. Care and respect PE2. Safety commitment and accountability PE3. Employee involvement and coaching SE1. Safety leadership SE2. Safety policy and commitment SE3. Risks and hazards management SE4. Regulatory requirements SE5. Performance measurement SE6. Safety communication SE7. Operational control SE8. Monitoring, audit and review SE9. Training and competency SE10. Learning from incidents Overall safety culture maturity

5.04, 6.74, 1.42, 4.06, 6.59, 3.53, 0.41, 7.05, 3.63, 1.89, 3.57, 4.17, 7.03, 4.33,

p < 0.001 p < 0.001 p = 0.157 p < 0.001 p < 0.001 p < 0.001 p = 0.679 p < 0.001 p < 0.001 p < 0.058 p < 0.001 p < 0.001 p < 0.001 p < 0.001

the best performing site, followed by D, whereas C was the worst performing mine. Each of the participating mines is foreign owned, belonging to either a multinational or a national company with at least two sites in the country. Therefore, by effectively distinguishing low accident mines from high accident mines, the research findings shows that mines with similar hazards and risks can perform differently in terms of their safety output. These differences in safety performance could be attributed to a number of factors, one being the safety culture maturity of the mine, which was the focus of this research.

Table 9 Comparing the incidence rate and safety culture maturity of mines that had statistically significant differences in their mean score. Incidence rate and safety culture elements

t-test results

6.2. Structure of safety culture maturity framework The structure of the safety culture framework used for the study distinguished between person and system elements. Whereas the person dimension assessed the perceptions of norms, beliefs and tradition that are often intangible and difficult to document, the system dimension assessed the perceptions of well-document concrete elements, which are often reflected in a site’s safety management system. This structure of the framework was confirmed by results of the principal component analysis. The analysis extracted two components, explaining 51.09% of the variance. This separation of person and system component was useful in identifying specific problem areas to support the development of targeted solutions for improvement. Gordon et al. (2007) indicate that in an organisation where there is a safety management system but lacks good safety culture, the system will be ineffective, since decisions will not necessarily consider safety. Similarly, where there is good safety culture but no safety management system, the way safety is organised will be inconsistent, under-resourced and not seen as business driven (Foster and Hoult, 2013; Gordon et al., 2007). Foster and Hoult (2013) notes that this system-culture mismatch could possibly be the cause of system ineffectiveness experience at some mines. Thus, a safety culture maturity framework that considers both system and person elements is important. By applying a minimum of 0.4 factor loading and 0.3 correlation coefficient, all items were loaded, except three, namely, HSE meetings, assessment of safety training and informal risk assessment, which were removed. Many of the loaded items are similar to those reported in other studies (Cox and Cheyne, 2000; Glendon and Litherland, 2001; Varonen and Mattila, 2000; Vinodkumar and Bhasi, 2009; Zohar, 1980), indicating that several similarities exist among safety culture/climate items from different studies.

any contractions of the framework. However, despite these shortcomings, the study presents insightful findings that can help mines improve their safety culture maturity and reduce accidents, and provide useful direction for future research.

6.1. Incidence rate One-way ANOVA showed that the four mines had different incidence rate. Test result proved that these differences were significant at p < 0.05. Results of the pairwise comparison test further identified specific mine pairs that showed statistically significant differences in their mean incidence rate, distinguishing low accident mines from high accident mines. The incidence rate of mine A was consistently significantly lower than the remaining mines at p < 0.05. Also, mine D’s incidence rate was lower than that of C and B, indicating that mine A is

6.3. Levels of safety culture maturity Consistently throughout all the sites, the intangible person elements show more characteristics of the lower levels of maturity than the tangible system elements. This indicates that the study respondents perceived the more tangible and well-documented system elements to 352

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emphatically stated that, the site instituted a safety transformation with a focus on improving the culture of the mine. According to the interviewees, this has had a significant impact on the culture of the mine; moving from a culture where workers were blamed for accidents to a culture were accidents are analysed in detail to determine latent causes. This might have accounted for the higher maturity level at mine A. Thirdly, safety culture takes time to develop and development may be faster in some areas and companies than others. The studied mines have operated for different years and therefore might have attained different levels of safety performance.

Table 10 Spearman’s correlation (r) between incidence rate and safety culture maturity score (N = 4, significant at p < 0.05). Element of safety culture

Mean

SD

r

p-value

PE1. Care and respect PE2. Safety commitment and accountability PE3. Employee involvement and coaching SE1. Safety leadership SE2. Safety policy and commitment SE3. Risks and hazards management SE4. Regulatory requirements SE5. Performance measurement SE6. Safety communication SE7. Operational control SE8. Monitoring, audit and review SE9. Training and competency SE10. Learning from incidents Overall safety culture maturity

3.31 3.56 3.37 3.56 3.51 3.61 3.21 3.42 3.48 3.50 3.51 3.87 3.22 3.27

0.31 0.25 0.30 0.36 0.31 0.28 0.27 0.31 0.21 0.16 0.24 0.22 0.29 0.23

−0.95 −0.89 −0.66 −0.81 −0.83 −0.78 −0.13 −0.99 −0.77 −0.74 −0.83 −0.89 −0.98 −0.86

0.007 0.020 0.115 0.044 0.040 0.061 0.416 0.000 0.065 0.078 0.043 0.003 0.001 0.029

6.4. Relationship between incidence rate and safety culture maturity An important aspect of this study was to explore the relationship between safety culture maturity and safety performance using incidence rate. All the elements and the overall safety culture correlated negatively with the incidence rate, similar to the works of Vinodkumar and Bhasi (2009), Mearns et al. (2003) and Lee (1998). The elements showed significant correlation at p < 0.05, with the exception of elements PE3 (employee involvement and coaching), SE3 (risks and hazards management), SE4 (regulatory requirements), SE6 (safety communication) and SE7 (operational control), which had no significant correlation. The significantly correlated elements had a minimum correlation coefficient of −0.81, indicating a strong negative relationship. Results of the t-test and the pairwise comparison test of the incidence rate and the safety culture maturity of the various sites further support this observation. Mines with low incidence rates had higher safety culture maturity scores for most of the elements than mines with high incidence rates. In the correlation, 3 items, namely, care and respect, performance measurements and learning from accidents, stood out, having the strongest relationship with a correlation coefficient of almost −1. These elements provide useful insights for future research and for mines seeking to improve their safety performance. The element SE1, performance measure, which measures how safety goals and target are set and measured at the mines had the strongest correlation with incidence rate. This indicates that accident can be reduced when safety goals are correctly set and effectively measured. In order to achieve such improvement, the setting and measuring of safety goals and targets should move from lagging indicator that focuses on previous accident rates. Attention must shift to a proactive approach with a focus on leading indicators such as risk controls activities that will prevent accidents from happening. Also, SE10, learning from incident was the second highest correlated elements. This element measured the existing process followed to collect and analyse accident to extract and disseminate useful lessons. This element notes that to ensure continuous improvement in safety, all incidents regardless of how small they all must be seen as learning opportunities. Small deviations ought to be analysed carefully to identify insightful lessons not only for the prevention of future accidents, but also the lessons must be used to identify general weaknesses in the risk management system so that existing deficiencies can be corrected. Finally, PE1, which measures the views of individual organisational members concerning the presence of risks and hazards at the sites was the third highest correlated element. The element recognises that the perception of employees about risks and hazards is a key determinant of their thoughts and actions. For instance, if workers perceive risk-taking to be part of the job, it will reflect in their action and ultimately, there will be minimal chance of reducing and eliminating accidents. Also, PE1 assesses care and recognition of worker. When workers are regarded as just resources, it impacts their commitment towards risk control activities with ultimately affects the optimal performance of the company. The findings of this study present broad insights and direction for future research and industrial application, specifically the strongly correlated elements of the framework. Further investigation into how learning from incidents and performance measurement occur in the industry would be valuable.

Injury rate per 100 employee

0.30 Mine C

0.25

Mine B

0.20

Mine D

0.15

Mine A

0.10 0.05 0.00 1.00

1.50

2.00

2.50

3.00

3.50

4.00

Overall safety culture maturity score Fig. 2. Scatter plot of safety culture maturity score and incidence rate.

be performing better than the less tangible person elements. The mines should begin developing plans to ensure that person elements progress with the system elements to avoid the effects of a system-culture mismatch. The different levels of safety culture maturity found here is consistent with the concept of safety culture maturity. Safety culture develops at a different pace for different companies, dimensions and elements. There were significant differences in the maturity levels not only among the sites but also among the various elements of the framework. Filho et al. (2010) and Hudson and Willekes (2000) made similar observations in the Brazilian and the Omani oil industries respectively. Within a mine site, safety culture does not exert a consistent effect in all areas of the site’s safety system and efforts to improve safety culture might not exert the same effect in all areas. It may be stronger in some areas and weaker in others. Therefore, for a site seeking an improvement in safety culture maturity, these differences in the different areas ought to be considered. Through the application of the different levels of maturity, it was possible to reveal areas of weakness across the sites to support the development and implementation of specific targeted actions to improve the weak areas. The individual sites can begin to develop plans to improve their individual areas of weakness and possibly collaborate where there are overlaps. For instance, consistently throughout all the sites, the areas of regulatory requirements and learning from incidents were at the lowest level of safety culture maturity. There were differences among the mines regarding the maturity of safety culture, and several reasons could account for this. Some of the mines have been operating relatively longer than others have, and have been working on improving safety culture over time. Secondly, the mines have OHSAS 18001 as the minimum requirement for occupational health and safety management. For instance, mines A and B have been using OHSAS 18001 for over a decade and undertake yearly external review and audit to ensure compliance and continuous improvements. At Site A, during various interviews, participants 353

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7. Conclusions

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The research was carried out to explore the association between safety culture and safety performance using the safety culture maturity concept. Over 800 respondents, across 4 different mines completed a paper-based survey questionnaire, indicating that although higher maturity levels existed in their current safety culture, improvements opportunities also exist. The study further recognises that, a mine site may have different maturity levels for different safety culture elements, suggesting that safety culture does not exert a consistent effect in all areas of a site's safety management system. It is therefore important that improvement strategies must first target the weak areas. Though a heterogeneous group used the framework used in this study, the results were aggregated for the sites and not analysed for the separate groups. The framework used was found valid and reliable, supporting the need to have a safety culture maturity framework that contains both person intangible and system tangible components. The study provides some evidence of the existence of a negative correlation between accident rate and safety culture maturity. Consistently, low accident mines had higher safety culture maturity scores, while high accident mines had lower safety culture maturity scores. Also, the study showed that the various elements of the framework correlated differently with the incidence rate. The strongly correlated elements that could be the focus for further improvement in safety were performance measurement, learning from accident and care and respect. Declarations of interest None. Acknowledgement We acknowledge the assistance of the Inspectorate Division of the Minerals Commission of Ghana, the mine sites and survey respondents whose time, resources and information were vital to the research. Eric Stemn is a recipient of an Australian Government Research Training Program Scholarship and UQ Centennial Scholarship at The University of Queensland, Australia. We are grateful to Kenny Mensah Graham for his assistance in the statistical analysis. Finally, we thank the editor and two anonymous reviewers whose critical feedbacks and comments have greatly improved the paper. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ssci.2018.12.008. References Anglo American Plc., 2010. Safety Risk Management Process: SRMP Detailed Journey Workbook. Anglo American Services (UK) Ltd and University of Queensland. Australian Standard, 1990. Workplace Injury and Disease Recording Standard AS 1885.11990. Australian Standard, North Sydney, NSW, Australia, pp. 28. Beus, J.M., Payne, S.C., Bergman, M.E., Arthur Jr, W., 2010. Safety climate and injuries: an examination of theoretical and empirical relationships. J. Appl. Psychol. 95 (4), 713–727. https://doi.org/10.1037/a0019164. Cheyne, A., Cox, S., Oliver, A., Tomás, J.M., 1998. Modelling safety climate in the prediction of levels of safety activity. Work Stress 12 (3), 255–271. https://doi.org/10. 1080/02678379808256865. Clarke, S., 1999. Perceptions of organizational safety: implications for the development of safety culture. J. Org. Behav. 185–198. Cooper, M.D., 2000. Towards a model of safety culture. Saf. Sci. 36 (2), 111–136. https:// doi.org/10.1016/S0925-7535(00)00035-7. Cox, S., Cox, T., 1991. The structure of employee attitudes to safety: a European example. Work Stress 5 (2), 93–106. Cox, S., Flin, R., 1998. Safety culture: philosopher's stone or man of straw? Work Stress 12 (3), 189–201. Cox, S.J., Cheyne, A.J.T., 2000. Assessing safety culture in offshore environments. Saf. Sci. 34 (1), 111–129. https://doi.org/10.1016/S0925-7535(00)00009-6. Czech, B.A., Groff, L., Strauch, B., 2014. Safety cultures and accident investigation lessons learned. ISASI Forum 48, 25–29. Duke, P.L., 2016. Mining Safety. Available from < https://www.hsmemagazine.com/ article/mining-safety-1251 > (accessed: November 10 2017).

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