Measuring Resilience Engineering: An Integrative Review and Framework for Bench-Marking Organisational Safety
Abstract
:1. Introduction
2. Research Paradigm and Theoretical Perspective
3. Method
3.1. Framing the Research Questions
- i.
- How has RE been conceptualized and defined in quantitative studies?
- ii.
- Which RE characteristics have been measured in these studies?
- iii.
- What psychometric properties were measured in these studies?
3.2. Searching and Selecting the Relevant Literature
3.3. Data Extraction
3.4. Critical Appraisal
- i.
- Aim(s): Is the aim(s)/purpose of research clearly stated?
- ii.
- Theory/model: Is an explicit theoretical framework/model used or discussed?
- iii.
- Research design: Is an overall research design mentioned or discussed?
- iv.
- Data collection: Does the data collection include procedures, settings and/or sampling?
- v.
- Data analysis: Is the data analysis sufficiently rigorous and includes quality aspects?
- vi.
- Bias: Were any biases or limitations of study considered and/or reported?
- vii.
- Results: Are the results clearly stated and discussed?
- viii.
- Value: Can this research be used to advance knowledge and/or practice?
3.5. Data Analysis and Synthesis
4. Results
4.1. General Characteristics of Reviewed Studies
4.2. Conceptualisation and Measurement of RE
4.3. Psychometric Properties
5. Discussion
5.1. A Predominant Dimensional Approach
5.2. Going Beyond the Predominant Dimensions
- The available margins of manoeuvre: Resilience, according to Hollnagel [19], assists organisations to adjust their functions before, during, or after any changes or disruptions in order to continue normal operations under both expected and unexpected conditions, so is very closely linked with adaptation. Indeed, resilience involves a return to its adaptive capacity in the face of new forms of variation and challenges [23]. For this reason, the available margins of manoeuvre are necessary for adaptation. In the current sector of French-language ergonomics [68,69,70,71], this notion of margins of manoeuvre was introduced in RE to in relation to resources set aside but which could be used to curtail unexpected demands and perturbations so that the system continued functioning instead of shutting down or reducing operations [72]. The lack or low rate of margins of manoeuvre reduces the adaptive capacity of organisations, making them vulnerable to variations induced by the occurrence of perturbations. The available margins of manoeuvre at the sharp-end level has been suggested to depend on two main factors within the organisation: (i) the degree of prescription/regulation; (ii) the degree of organisational control [73]. One of the instruments reviewed [53] investigated margins of manoeuvre by evaluating the closeness of its operating system in relation to its boundary of safe performance, and tolerance by gauging how well it worked at the borders when subjected to increased pressures and adaptive capacity. However, four instruments also measured tolerance [45,46,49,58]. Collectively, these capture the key facets that can be used to measure the available margins of manoeuvre.
- Strengthen dimensions in relation to trade-offs between production and safety: The social creation of safety in RE involves the effective management of trade-offs between production and safety (P/S) [24,26,74,75], which involve sacrificial decisions being made at all levels of the hierarchy and will impact on the overall safety level of the organisation. The ability of an organisation to achieve under conditions of high pressures through effective management of production/safety trade-offs is a fundamental in RE. Regarding the instruments analysed in this review, this is taken into account but mainly at the level of the “management commitment” dimension—i.e., at the blunt-end level. However, the number of specific questions aimed at evaluating this remained modest. It would therefore be appropriate to add more questions for evaluating trade-offs between P/S, considering a breakdown of these issues on several dimensions, and questioning the sharp-end level. It might also be relevant to add a specific dimension.
- Introduce a dimension dealing with managed safety vs. prescribed safety: At an operational level (i.e., sharp-end level), the degree of prescription within an organisation will more or less constrain front-line operators [76]. One of the indicators of RE (or lack of it) has been suggested to be the gap between work as prescribed and work as done [27,28], so monitoring and managing such gaps are important in driving safety achievements. According to Morel, Amalberti and Chauvin [26] and Dekker [28] the greater the degree of prescribing within an organisation, the less it will be possible for front-line operators to have sufficient autonomy and flexibility to adapt and deal with the occurrence of perturbations. On the other hand, the lower the level of prescribing, the greater the autonomy and margins of manoeuvre of front-line operators. From an RE perspective, this highlights two distinct forms of safety: one that is managed by the actors, on the one hand, and that prescribed by the organisation on the other [26,75,77,78]. Managed safety, which involves the adaptation of prescriptions to suit the context of local work situations, depends not only on the autonomy of the actors but also on their level of competence and expertise [26]. For this reason, any new instruments would need to incorporate questions that interrogate not only the level of prescription within organisations but also the autonomy of the actors, as well as their levels of competence and expertise. It should be noted that these three points are intrinsically linked to the issues raised above, which concern the trade-offs between performance and safety, on the one hand, and the margins of manoeuvre on the other.
5.3. Culture of Resilience vs. Climate of Resilience
5.4. A Unified Definition and Integrative Framework
“RE is a perspective for organisational safety management which enables organisational members to actively anticipate, respond, monitor and learn; by adapting to operate at the boundary of safe operations by narrowing the gap between work as imagined and work as performed; and manifested in an organisation’s culture, cognition and behaviours”
6. Strengths, Limitations and Implications
- i.
- A well-designed one can be used to collect huge quantities of data;
- ii.
- Respondents can be sourced from a wide range of contexts and levels of the organisation;
- iii.
- They are relatively inexpensive to administer;
- iv.
- They can be administered in different ways;
- v.
- Very little training is required to develop them;
- vi.
- Response rates for some types of instruments, such as group-administered questionnaires, can be higher;
- vii.
- i.
- It becomes difficult to avoid leading questions;
- ii.
- Questions can contain multiple sets of ideas so can become complicated;
- iii.
- Some questions, such as those on age, gender or the respondent’s specific role, can be irritating if no context is provided for their response;
- iv.
- v.
- The subjective use of scales can induce variations in perceptions among respondents [91];
- vi.
- Prior commitment from management and supervisors are required to enable operators complete these during their work hours [93];
- vii.
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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---|---|---|---|---|
1 | Pillay, Borys, Else and Tuck [30] | Introduced a theoretical framework for RE, proposed a toolkit for investigating RE through safety culture | Gold Mining, Australia | Structured safety climate survey |
2 | Heese, Kallus and Kolodej [29] | Developed and validated an Inventory for assessing behaviour and organisation resilience in Aviation (I-BORA) | Aviation, Austria | Structured questionnaire surveys |
3 | Shirali, et al. [45] | Examined the utility of using surveys for measuring RE | 11 Units of a large process industry, Iran | Structured questionnaire survey |
4 | Azadeh, et al. [46] | Assessed factors affecting the resilient levels using Fuzzy cognitive maps (FCM) | Petrochemical plants, Iran | Expert Views and Structured questionnaire survey |
5 | Azadeh, et al. [47] | Evaluated performance of Integrated RE through questionnaires and data envelopment analysis | Petrochemical departments, Iran | Structured questionnaire survey |
6 | Azadian, et al. [48] | Assessed crisis management using a questionnaire design which incorporated RE principles | Public hospitals, Iran | Structured questionnaire survey |
7 | Achard, et al. [49] | Assessed the potential for Resilience in Municipal Solid Waste Management Companies | MSWM Companies, Italy | Structured questionnaire survey |
8 | Azadeh and Zarrin [50] | Measured human resources productivity considering RE, motivational factors of work, environmental health and safety and ergonomics principles | Petrochemical plant, Iran | Structured questionnaire survey |
9 | Pęciłło [51] | Examined the utility of RE concepts in organisations with and without OSH across different sized enterprises. | Process industries, Poland | Structured questionnaire survey |
10 | Shirali, et al. [52] | Developed a new framework for evaluating crisis management through RE | Hospitals, Iran | Structured questionnaire survey |
11 | Shirali, et al. [53] | Assessed RE factors based on system properties | Process industry, Iran | Semi-structured interviews with MCQs, analysis of documents |
12 | Azadeh, et al. [54] | Used mathematical programming to develop and evaluate Integrated Resilience Engineering | Aluminium factory, Iran | Structured questionnaire survey |
13 | Chen, et al. [55] | Developed and validated a Safety Climate Resilience Model to predict construction safety performance. | Construction industry, Canada | Structured, self-administered questionnaire |
14 | Shirali, et al. [56] | Designed a validated instrument to Measure Resilience Safety Culture in Sociotechnical Systems. | Petrochemical Plants, Iran | Structured questionnaire survey |
15 | Garg, et al. [57] | Used a resilient safety culture (RSC) model to measure the impact of remoteness and mental health. | Oil and gas industry, Kuwait | Structured questionnaire survey |
16 | Shirali and Nematpour [58] | Quantified and ranked RE dimensions through analysis network process | Steel industry, Iran | Structured questionnaire survey |
17 | Zarrin and Azadeh [59] | Evaluated and analysed impacts of RE on integrated OHS management system | Petrochemical Plants, Iran | Structured questionnaire survey |
Study No. | I. Aims | II. Theory/Model | III. Research Design | IV. Data Collection | V. Data Analysis | VI. Bias/Limitations | VII. Results | VIII. Value |
---|---|---|---|---|---|---|---|---|
1 | Yes | Yes | No | Limited | No | No | No | Yes |
2 | No | No | No | Yes | Yes | No | Yes | Yes |
3 | Yes | No | Yes | Yes | Yes | No | Yes | Yes |
4 | No | No | No | Yes | Yes | No | Yes | Yes |
5 | No | Yes | No | Yes | Yes | No | Yes | Yes |
6 | Yes | No | Yes | Yes | Yes | No | Yes | Yes |
7 | No | No | No | Yes | Yes | No | Yes | Yes |
8 | No | No | Yes | Yes | Yes | No | Yes | Yes |
9 | No | No | No | Yes | Yes | No | Yes | Yes |
10 | Yes | No | Yes | Yes | Yes | No | Yes | Yes |
11 | Yes | No | Yes | Yes | Yes | No | Yes | Yes |
12 | Yes | No | Yes | Yes | Yes | No | Yes | Yes |
13 | Yes | No | Yes | Yes | Yes | Yes | Yes | Yes |
14 | Yes | No | No | Yes | Yes | No | Yes | Yes |
15 | No | Yes | Yes | Yes | Yes | No | Yes | No |
16 | No | No | Yes | Yes | Yes | No | Yes | Yes |
17 | Yes | No | No | Yes | Yes | No | Yes | No |
Authors | Definition |
---|---|
[30] | “developing an organisation’s behavioural and cognitive capability such that it can effectively adjust and continue performing optimally near an its safe operating envelop in the presence of everyday threats and environmental stressors at all levels of the organisation” (p. 134) |
[29] | “ability of a system or an organisation to react and recover from disturbances at an early stage with minimal effect on dynamic stability” (p. 2) |
[45] | “ability of a system to adapt its functioning before and during disturbances, so that it can continue operations after a major mishap or in the presence of continuous stresses” (p. 89) |
[46] | “a paradigm for safety management that concentrates on how to help people create foresight, anticipate the different forms of risk in order to cope with complexities under pressure and move towards success” (p. 100) |
[47] | “a paradigm for safety management that stresses how people, systems and organizations learn, adapt, and create safety in an environment with hazards, tradeoffs, and multiple goals” (pp. 231–232) |
[48] | “intrinsic ability of a system to adjust its operation before or following changes and disturbances, so it can maintain operations after an accident” (p. 247) |
[50] | “inherent ability of a system to adapt its function before and during the situations where normal functioning is disrupted, so that it can continue operations after a major disaster or in the presence of constant stresses” (p. 56) |
[53] | “intrinsic ability of a system to adapt its function before, during, or after major mishaps or changes, so that it can continue the operations required under both expected and unexpected conditions” (p. 20) |
[54] | “a paradigm for safety management that concentrates on how to help people deal with complexity under stress to achieve success” (p. 336) |
[56] | “an organizational culture that fosters safe practices for improved safety in an ultra-safe organization striving for cost-effective safety management” (p. 297) |
[58] | “capability to sustain or rapidly return to a steady state that allows the organization to continue operation during or after a major event or in the presence of continuous stresses” (p. 191) |
[59] | “ability of an organization to regulate its function before, during, and after perturbations and fluctuations, so that it can continue the operations required under both predicted and unpredicted situations” (p. 142) |
Author(s) | Sample and Size | Instrument | Theoretical Framework/Model | RE Characteristics/No. of Questions (Indicators) | Psychrometric Properties | Results |
---|---|---|---|---|---|---|
Pillay, Borys, Else and Tuck [30] | Not indicated | Toolkit for examining organisational safety culture and RE | Adapted four-boundary drift to failure model [60] | (27)
| None | None |
Heese, Kallus and Kolodej [29] | 282 | IBORA | Not indicated | (12)
| PCA – Kaiser’s and Varimax rotation Reliability-Cronbach’s alpha (⍺) | ⍺ GD-PS = 0.787 F = 0.633 I = 0.671 AR =0.708 |
Shirali, Mohammadfam and Ebrahimipour [45] | 88 Managers (3%) Supervisors (20%) Operators (77%) | Resilience engineering survey questionnaire | Not indicated | (57)
| PCA Reliability-Cronbach’s alpha (⍺) | ⍺ TMC= 0.806 JC = 0.806 LC = 0.777 A-O = 0.660 P = 0.700 F= 0.608 |
Azadeh, Salehi, Arvan and Dolatkhah [46] | 60 Experts (n = 30) Managers, engineers and experienced workers (n = 30) | Questionnaire developed for study | Not indicated | (Not disclosed)
| Final weights of resilience factors obtained by combination of Fuzzy Cognitive Maps (FCMs) results and data from questionnaire | Final weights TMC: 10.76 JC: 11.33 LC: 11.83 A: 12.28 P: 12.30 F: 12.20 T: 9.51 R: 7.83 FT: 11.95 |
Azadeh, Salehi, Ashjari and Saberi [47] | 115 Managers and supervisors (n = 37) Engineers, technicians and operators (n = 78) | Questionnaire developed for study | Integrated RE | (30)
| Data Envelopment Analysis (DEA) approach Reliability of collected data: Cronbach’s alpha (⍺) To verify the results of DEA approach: Spearman test of relationship (rs) | ⍺ whole tool: 0.9 rs = 0.904 |
Azadian, Shirali and Saki [48] | 113 Nurses from seven public hospitals | Questionnaire developed for study | Not indicated | (26)
| EFA Reliability-Cronbach’s alpha, Interclass correlation Coefficient (ICC). Validity–Content Validity Index/ratio: CVI and CVR | ⍺ /ICC TMC= 0.865/0.865 LR = 0.871/0.843 AW = 0.769/0.769 FL = 0.845/0.845 ⍺ whole tool: 0.951 ICC whole tool: 0.95 CVI whole tool: 0.85 CVR whole tool: 0.75 |
Achard, Agnello, Bragatto and Fabbricino [49] | 564 Employees of several operative units of the company | Resilience engineering survey questionnaire | Not indicated | (61)
| PCA Reliability-Cronbach’s alpha (⍺) | ⍺ TMC= 0.8 JC = 0.7 LC = 0.7 A-O = 0.7 P = 0.7 F= 0.8 |
Azadeh and Zarrin [50] | 165 Operators (n = 90) Supervisors (n = 53) Managers (n = 22) | Questionnaire developed for study, including RE (10), WMFs (4) and HSEE (4) factors | Not indicated | (30)
| EFA Reliability-Cronbach’s alpha (⍺) Validity–Content Validity Ratio (CVR) | ⍺ /CVR TLC= 0.919/0.921 LR = 0.868/0.813 FL = 0.812/0.898 RC = 0.853/0.980 AW = 0.884/0.929 PR= 0.750/0.960 SO = 0.756/0.866 TW = 0.924/0.959 RD = 0.722/0.813 FT = 0.853/0.839 |
Pęciłło [51] | Not indicated 100 Enterprises. | Questionnaire developed for study (Two parts; one deals with resilience) | Not indicated | (45)
| Correlation coefficients | Correlation coefficients L = 0.81 M = 0.79 R = 0.80 A = 0.82 Resilience Total = 0.84 |
Shirali, Azadian and Saki [52] | 310 Staff from eight hospitals Managers: 21.94% Nurses: 78.06% | Questionnaire developed for study | Not indicated | (44)
| EFA Reliability-Cronbach’s alpha (⍺), Intraclass Correlation Coefficient (ICC). Validity–Content Validity Index/ratio: CVI and CVR | ⍺ TLC = 0.83 JC = 0.85 LC = 0.77 AW = 0.88 P = 0.89 FL = 0.87 O = 0.63 ⍺ whole tool: 0.951 ICC whole tool: 0.95 CVI each item: > 0.80 CVR each item: > 0.75 |
Shirali, Motamedzade, Mohammadfam, Ebrahimipour and Moghimbeigi [53] | 32 Experienced operators (n = 24) Managers (n = 8) | Semi-structured interviews with multiple-choice questions | Not indicated | (105)
| PCA used to prioritize the 9 RE indicators Numerical Taxonomy (NT) used to validate the results of the PCA | PCA Ranking/Ranking BC = 1/2 F = 2/1 M = 8/8 T = 6/6 CSI = 9/9 L = 3/3 A= 5/5 R = 4/4 A = 7/7 |
Azadeh, Salmanzadeh-Meydani and Motevali-Haghighi [54] | 97 Senior managers (n = 2) Mid managers (n = 18) Administrators (n = 37) Staff (n = 40) | Questionnaire developed for study and based on IRE factors | Integrated RE | (30)
| Data Envelopment Analysis (DEA)PCA and Numerical Taxonomy (NT) used to validate and verify the resultsReliability of collected data: Cronbach’s alpha | ⍺ /Ranking MC= 0.839/5 RC = 0.604/2 L = 0.730/4 AW = 0.776/9 PR = 0.880/10 F= 0.614/3 SO = 0.678/1 TW= 0.833/7 FT = 0.749/8 R = 0.754/6 ⍺ whole tool: 0.913 |
Chen, McCabe and Hyatt [55] | 431 Questionnaires collected from 68 construction sites (403 analysed). | Questionnaire developed for study | Not indicated | (28)
| Cronbach’s alpha of the scales for each dimension. | ⍺ MC= 0.87 SSP = 0.86 CSP = 0.72 L = 0.83 R = 0.71 A = 0.68 AW = 0.80 |
Shirali, Shekari and Angali [56] | 312 Questionnaires collected from 12 units of plant. Managers = 61 Operators = 251 | Questionnaire developed for study | Not indicated | (57)
| EFA Reliability-Cronbach’s alpha (⍺)/test-retest r Validity–Content Validity Index/ratio: CVI and CVR/Kaiser–Meyer–Olkin (KMO) index | ⍺ JC = 0.84 MoC = 0.85 LC = 0.86 RAM = 0.89 P = 0.91 F = 0.83 RC = 0.88 MC = 0.77 AW = 0.89 SMS = 0.84 AI = 0.88 IoS = 0.83 C = 0.67 ⍺ whole tool: 0.943 CVI: 0.97 CVR: 0.83 KMO: 0.88 r = 0.85; p < 0.001 |
Garg, Alroomi, Tonmoy and Mohamed [57] | 139 Engineers, supervisors and managers. | Questionnaire developed for study | Resilient safety culture (RSC) model | (42)
| Relative importance index method (RII)—used to quantify the relative importance of all the 42 indicators of RSC for remote sites | RII/Ranking of constructs BC = 0.585/(1) PC = 0.576/(2) MC = 0.562/(3) |
Shirali and Nematpour [58] | 489 Workers | Resilience engineering survey questionnaire | Not indicated | (61)
| Analysis network process (ANP) used to quantify and determine the priorities of RE dimensions | Ranking MC= 1 JC = 2 LC = 3 A-O = 6 P = 5 F= 4 |
Zarrin and Azadeh [59] | 71 Employees | Questionnaire developed for study, including RE (7), HSEE (4) factors | Not indicated | (25)
| Reliability-Cronbach’s alpha (⍺) For the rest of the study: Z-numbers with Fuzzy Cognitive Map (FCP) approach | ⍺ TMC = 0.88 L = 0.72 F = 0.77 RC = 0.81 AW = 0.84 P = 0.80 R = 0.86 |
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Pillay, M.; Morel, G. Measuring Resilience Engineering: An Integrative Review and Framework for Bench-Marking Organisational Safety. Safety 2020, 6, 37. https://doi.org/10.3390/safety6030037
Pillay M, Morel G. Measuring Resilience Engineering: An Integrative Review and Framework for Bench-Marking Organisational Safety. Safety. 2020; 6(3):37. https://doi.org/10.3390/safety6030037
Chicago/Turabian StylePillay, Manikam, and Gaël Morel. 2020. "Measuring Resilience Engineering: An Integrative Review and Framework for Bench-Marking Organisational Safety" Safety 6, no. 3: 37. https://doi.org/10.3390/safety6030037
APA StylePillay, M., & Morel, G. (2020). Measuring Resilience Engineering: An Integrative Review and Framework for Bench-Marking Organisational Safety. Safety, 6(3), 37. https://doi.org/10.3390/safety6030037