The State of the Practice in Validation of Model-Based Safety Analysis in Socio-Technical Systems: An Empirical Study
Abstract
:1. Introduction
1.1. The Need to Understand the State of the Practice in Validation of Model-Based Safety Analysis
1.2. Scope of This Research
1.3. Research Questions
2. Materials and Methods
2.1. Identifying Relevant Literature and Sampling
- The below query is run on WoS:
- TS = ((“Safety” OR “Risk” OR “Reliability” OR “Resilience”) AND (“Model” OR “Method” OR “Approach” OR “Framework”))
- To limit the search to the Safety Science journal, its ISSN code is considered in a new query, which is IS = (0925–7535). Additionally, the 2010 to 2019 period is selected in WoS, further limiting the search.
- Finally, the result of the first query is combined with the second query, using the “AND” operator.
2.2. Data Retrieval Process and the Overall Trends in the Data
2.2.1. Country of Origin
2.2.2. Stages of a System Life Cycle
2.2.3. Industrial Application Domain
2.2.4. Model Type/Approach
2.2.5. Validation Approach
2.2.6. Terminology Used for Validation
2.3. Reliability Check of the Extracted Data
2.4. Data Analysis Method
3. Results
3.1. Percentage of the Papers in Which the Models Are Attempted to Be Validated
3.2. Approaches on Validation of Model-Based Safety Analysis
3.3. Relationship between Validation and Other Variables
3.3.1. Relationship between Validation and Safety Concept, Model Type/Approach, Country of Origin, Industrial Application Domain, and Stage of the System Life Cycle
- No relationship was found between how frequently validation was considered and models associated with particular safety-related concepts, including safety, risk, reliability, and resilience.
- No relationship was found between how frequently validation was considered and a specific model type/approach.
- No relationship was found between how frequently validation was considered and articles originating from a specific country.
- No relationship was found between how frequently validation was considered and a specific industry.
- No relationship was found between how frequently validation was considered and a specific stage of a system’s life cycle.
3.3.2. Relationship between Validation and the Year of Publication
3.4. Terminology of Validation
4. Discussion
4.1. The Choice of Sub-Questions
4.2. Adequacy of the Applied Validation Approaches in the Investigated Sample
- Establishing confidence in a model;
- Identifying more hazards; and
- Improving the agreement of a model’s output with empirical data.
4.3. Investigating the State of the Practice in Validation of Model-Based Safety Analysis among Practitioners
4.4. Conceptual-Terminological Focus on Validation as a Foundational Issue
4.5. Limitations of This Study and Further Future Research Directions
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Acknowledgments
Conflicts of Interest
Appendix A
Variables | Categories | |
---|---|---|
Title of the paper | - | |
Name of the Author/Authors | - | |
Digital Object Identifier (DOI) | - | |
Safety Concept |
|
|
Year of publication | This ranges from 2010 to 2019. | |
Country of origin |
|
|
Stage of the system life cycle |
| |
Industrial application domain |
|
|
Model type/approach |
|
|
Validation approach |
|
|
Word used for validation |
|
|
References
- Dekker, S. Foundations of Safety Science: A Century of Understanding Accidents and Disasters; CRC Press LLC: Milton, UK, 2019; ISBN 978-1-351-05978-7. Available online: http://ebookcentral.proquest.com/lib/dal/detail.action?docID=5746969 (accessed on 9 October 2021).
- Rae, A.; Nicholson, M.; Alexander, R. The State of Practice in System Safety Research Evaluation. In Proceedings of the 5th IET Internatioanl Conference on System Safety, Manchester, UK, 18–20 October 2010; Available online: https://www.researchgate.net/publication/224218867_The_state_of_practice_in_system_safety_research_evaluation (accessed on 9 October 2021).
- Reiman, T.; Viitanen, K. Towards Actionable Safety Science. In Safety Science Research; CRC Press: Boca Raton, FL, USA, 2019; ISBN 978-1-351-19023-7. [Google Scholar]
- Guillaume, O.; Herchin, N.; Neveu, C.; Noël, P. An Industrial View on Safety Culture and Safety Models. In Safety Cultures, Safety Models: Taking Stock and Moving Forward; Gilbert, C., Journé, B., Laroche, H., Bieder, C., Eds.; Springer Briefs in Applied Sciences and Technology; Springer International Publishing: Cham, Switzerland, 2018; pp. 1–13. ISBN 978-3-319-95129-4. [Google Scholar]
- Aven, T. Foundational Issues in Risk Assessment and Risk Management. Risk Anal. 2012, 32, 1647–1656. [Google Scholar] [CrossRef]
- Goerlandt, F.; Khakzad, N.; Reniers, G. Special Issue: Risk Analysis Validation and Trust in Risk management. Saf. Sci. 2017, 99, 123–126. [Google Scholar] [CrossRef]
- Hale, A. Foundations of safety science: A postscript. Saf. Sci. 2014, 67, 64–69. [Google Scholar] [CrossRef]
- Robson, L.S.; Clarke, J.A.; Cullen, K.; Bielecky, A.; Severin, C.; Bigelow, P.L.; Irvin, E.; Culyer, A.; Mahood, Q. The effectiveness of occupational health and safety management system interventions: A systematic review. Saf. Sci. 2007, 45, 329–353. [Google Scholar] [CrossRef]
- Goncalves Filho, A.P.; Waterson, P. Maturity models and safety culture: A critical review. Saf. Sci. 2018, 105, 192–211. [Google Scholar] [CrossRef] [Green Version]
- Sulaman, S.M.; Beer, A.; Felderer, M.; Höst, M. Comparison of the FMEA and STPA safety analysis methods—A case study. Softw. Qual. J. 2017, 27, 349–387. [Google Scholar] [CrossRef] [Green Version]
- Goerlandt, F.; Kujala, P. On the reliability and validity of ship–ship collision risk analysis in light of different perspectives on risk. Saf. Sci. 2014, 62, 348–365. [Google Scholar] [CrossRef]
- Suokas, J.; Kakko, R. On the problems and future of safety and risk analysis. J. Hazard. Mater. 1989, 21, 105–124. [Google Scholar] [CrossRef]
- Amendola, A.; Contini, S.; Ziomas, I. Uncertainties in chemical risk assessment: Results of a European benchmark exercise. J. Hazard. Mater. 1992, 29, 347–363. [Google Scholar] [CrossRef]
- Laheij, G.M.H.; Ale, B.; Post, J.G. Benchmark risk analysis models used in The Netherlands. Saf. Reliab. 2003, 993–999. [Google Scholar]
- Barlas, Y. Multiple tests for validation of system dynamics type of simulation models. Eur. J. Oper. Res. 1989, 42, 59–87. [Google Scholar] [CrossRef]
- Sargent, R.G. Verifying and validating simulation models. In Proceedings of the Winter Simulation Conference 2014, Savannah, GA, USA, 7–10 December 2014; pp. 118–131. [Google Scholar]
- Eker, S.; Rovenskaya, E.; Langan, S.; Obersteiner, M. Model validation: A bibliometric analysis of the literature. Environ. Model. Softw. 2019, 117, 43–54. [Google Scholar] [CrossRef] [Green Version]
- Le Coze, J.-C.; Pettersen, K.; Reiman, T. The foundations of safety science. Saf. Sci. 2014, 67, 1–5. [Google Scholar] [CrossRef]
- Casson Moreno, V.; Garbetti, A.L.; Leveneur, S.; Antonioni, G. A consequences-based approach for the selection of relevant accident scenarios in emerging technologies. Saf. Sci. 2019, 112, 142–151. [Google Scholar] [CrossRef]
- Li, Y.; Mosleh, A. Dynamic simulation of knowledge based reasoning of nuclear power plant operator in accident conditions: Modeling and simulation foundations. Saf. Sci. 2019, 119, 315–329. [Google Scholar] [CrossRef]
- Kulkarni, K.; Goerlandt, F.; Li, J.; Banda, O.V.; Kujala, P. Preventing shipping accidents: Past, present, and future of waterway risk management with Baltic Sea focus. Saf. Sci. 2020, 129, 104798. [Google Scholar] [CrossRef]
- Wybo, J.-L. Track circuit reliability assessment for preventing railway accidents. Saf. Sci. 2018, 110, 268–275. [Google Scholar] [CrossRef]
- Mikusova, M.; Zukowska, J.; Torok, A. Community Road Safety Strategies in the Context of Sustainable Mobility. In Management Perspective for Transport Telematics; Mikulski, J., Ed.; Springer International Publishing: Cham, Switzerland, 2018; pp. 115–128. [Google Scholar]
- Kirwan, B. Validation of human reliability assessment techniques: Part 1—Validation issues. Saf. Sci. 1997, 27, 25–41. [Google Scholar] [CrossRef]
- Hughes, B.P.; Newstead, S.; Anund, A.; Shu, C.C.; Falkmer, T. A review of models relevant to road safety. Accid. Anal. Prev. 2015, 74, 250–270. [Google Scholar] [CrossRef] [Green Version]
- Wolkenhauer, O. Why model? Front. Physiol. 2014, 5, 21. [Google Scholar] [CrossRef] [Green Version]
- Epstein, J.M. Why Model? J. Artif. Soc. Social Simul. 2008, 11. Available online: https://www.jasss.org/11/4/12.html (accessed on 9 October 2021).
- Edmonds, B.; Le Page, C.; Bithell, M.; Chattoe-Brown, E.; Grimm, V.; Meyer, R.; Montañola-Sales, C.; Ormerod, P.; Root, H.; Squazzoni, F. Different Modelling Purposes. J. Artif. Soc. Soc. Simul. 2019, 22, 6. [Google Scholar] [CrossRef] [Green Version]
- Kroes, P.; Franssen, M.; van de Poel, I.; Ottens, M. Treating socio-technical systems as engineering systems: Some conceptual problems. Syst. Res. Behav. Sci. 2006, 23, 803–814. [Google Scholar] [CrossRef] [Green Version]
- Li, J.; Hale, A. Output distributions and topic maps of safety related journals. Saf. Sci. 2016, 82, 236–244. [Google Scholar] [CrossRef]
- Reniers, G.; Anthone, Y. A ranking of safety journals using different measurement methods. Saf. Sci. 2012, 50, 1445–1451. [Google Scholar] [CrossRef]
- Amyotte, P.R.; Berger, S.; Edwards, D.W.; Gupta, J.P.; Hendershot, D.C.; Khan, F.I.; Mannan, M.S.; Willey, R.J. Why major accidents are still occurring. Curr. Opin. Chem. Eng. 2016, 14, 1–8. [Google Scholar] [CrossRef]
- Gullo, L.J.; Dixon, J. Design for Safety; John Wiley & Sons, Incorporated: Newark, UK, 2018; ISBN 978-1-118-97431-5. Available online: http://ebookcentral.proquest.com/lib/dal/detail.action?docID=5185085 (accessed on 9 October 2021).
- Leveson, N.G. Engineering a Safer World: Systems Thinking Applied to Safety; Engineering Systems; The MIT Press: Cambridge, UK, 2012; ISBN 978-0-262-01662-9. Available online: http://ezproxy.library.dal.ca/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=e000xna&AN=421818&site=ehost-live (accessed on 9 October 2021).
- Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ 2009, 339, b2535. [Google Scholar] [CrossRef] [Green Version]
- Wee, B.V.; Banister, D. How to Write a Literature Review Paper? Transp. Rev. 2015, 36, 278–288. [Google Scholar] [CrossRef] [Green Version]
- Li, J.; Goerlandt, F.; Reniers, G. An overview of scientometric mapping for the safety science community: Methods, tools, and framework. Saf. Sci. 2021, 134, 105093. [Google Scholar] [CrossRef]
- Greenham, D. Close Reading: The Basics; Routledge: London, UK; Taylor & Francis Group: New York, NY, USA, 2019; ISBN 978-0-203-70997-9. [Google Scholar]
- Bhattacherjee, A. Social Science Research: Principles, Methods, and Practices, 2nd ed.; Anol Bhattacherjee: Tampa, FL, USA, 2012; ISBN 978-1-4751-4612-7. [Google Scholar]
- Merigó, J.M.; Miranda, J.; Modak, N.M.; Boustras, G.; de la Sotta, C. Forty years of Safety Science: A bibliometric overview. Saf. Sci. 2019, 115, 66–88. [Google Scholar] [CrossRef]
- Brummett, B. Techniques of Close Reading; SAGE Publications, Inc.: Thousand Oaks, CA, USA, 2019; ISBN 978-1-5443-0525-7. [Google Scholar]
- Huang, Y.-F.; Gan, X.-J.; Chiueh, P.-T. Life cycle assessment and net energy analysis of offshore wind power systems. Renew. Energy 2017, 102, 98–106. [Google Scholar] [CrossRef]
- Dong, D.T.; Cai, W. A comparative study of life cycle assessment of a Panamax bulk carrier in consideration of lightship weight. Ocean Eng. 2019, 172, 583–598. [Google Scholar] [CrossRef]
- Kafka, P. Probabilistic safety assessment: Quantitative process to balance design, manufacturing and operation for safety of plant structures and systems. Nucl. Eng. Des. 1996, 165, 333–350. [Google Scholar] [CrossRef]
- Lu, Y.; Zhang, S.-G.; Tang, P.; Gong, L. STAMP-based safety control approach for flight testing of a low-cost unmanned subscale blended-wing-body demonstrator. Saf. Sci. 2015, 74, 102–113. [Google Scholar] [CrossRef]
- Ding, L.; Zhang, L.; Wu, X.; Skibniewski, M.J.; Qunzhou, Y. Safety management in tunnel construction: Case study of Wuhan metro construction in China. Saf. Sci. 2014, 62, 8–15. [Google Scholar] [CrossRef]
- Bağan, H.; Gerede, E. Use of a nominal group technique in the exploration of safety hazards arising from the outsourcing of aircraft maintenance. Saf. Sci. 2019, 118, 795–804. [Google Scholar] [CrossRef]
- Garmer, K.; Sjöström, H.; Hiremath, A.M.; Tilwankar, A.K.; Kinigalakis, G.; Asolekar, S.R. Development and validation of three-step risk assessment method for ship recycling sector. Saf. Sci. 2015, 76, 175–189. [Google Scholar] [CrossRef]
- Lim, G.J.; Cho, J.; Bora, S.; Biobaku, T.; Parsaei, H. Models and computational algorithms for maritime risk analysis: A review. Ann. Oper. Res. 2018, 271, 765–786. [Google Scholar] [CrossRef]
- Wienen, H.; Bukhsh, F.; Vriezekolk, E.; Wieringa, R. Accident Analysis Methods and Models—A Systematic Literature Review; Centre for Telematics and Information Technology (CTIT): Enschede, The Netherlands, 2017. [Google Scholar]
- Zahabi, M.; Kaber, D. A fuzzy system hazard analysis approach for human-in-the-loop systems. Saf. Sci. 2019, 120, 922–931. [Google Scholar] [CrossRef]
- Stringfellow, M.V. Accident Analysis and Hazard Analysis for Human and Organizational Factors. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 2010. Available online: https://dspace.mit.edu/handle/1721.1/63224 (accessed on 9 October 2021).
- Yazdi, M.; Nedjati, A.; Zarei, E.; Abbassi, R. A novel extension of DEMATEL approach for probabilistic safety analysis in process systems. Saf. Sci. 2020, 121, 119–136. [Google Scholar] [CrossRef]
- Goerlandt, F.; Khakzad, N.; Reniers, G. Validity and validation of safety-related quantitative risk analysis: A review. Saf. Sci. 2017, 99, 127–139. [Google Scholar] [CrossRef]
- Suokas, J. On the Reliability and Validity of Safety Analysis. Ph.D. Thesis, VTT Technical Research Centre of Finland, Espoo, Finland, 1985. [Google Scholar]
- Peterson, D.; Eberlein, R. Reality check: A bridge between systems thinking and system dynamics. Syst. Dyn. Rev. 1994, 10, 159–174. [Google Scholar] [CrossRef]
- Kirwan, B. Validation of human reliability assessment techniques: Part 2—Validation results. Saf. Sci. 1997, 27, 43–75. [Google Scholar] [CrossRef]
- Boring, R.L.; Hendrickson, S.M.L.; Forester, J.A.; Tran, T.Q.; Lois, E. Issues in benchmarking human reliability analysis methods: A literature review. Reliab. Eng. Syst. Saf. 2010, 95, 591–605. [Google Scholar] [CrossRef] [Green Version]
- Olphert, C.W.; Wilson, J.M. Validation of Decision-Aiding Spreadsheets: The Influence of Contingency Factors. J. Oper. Res. Soc. 2004, 55, 12–22. [Google Scholar] [CrossRef]
- Vergison, E. A Quality-Assurance guide for the evaluation of mathematical models used to calculate the consequences of Major Hazards. J. Hazard. Mater. 1996, 49, 281–297. [Google Scholar] [CrossRef]
- Mazaheri, A.; Montewka, J.; Kujala, P. Towards an evidence-based probabilistic risk model for ship-grounding accidents. Saf. Sci. 2016, 86, 195–210. [Google Scholar] [CrossRef]
- Landry, M.; Malouin, J.-L.; Oral, M. Model validation in operations research. Eur. J. Oper. Res. 1983, 14, 207–220. [Google Scholar] [CrossRef]
- Schwanitz, V.J. Evaluating integrated assessment models of global climate change. Environ. Model. Softw. 2013, 50, 120–131. [Google Scholar] [CrossRef]
- Gass, S.I. Decision-Aiding Models: Validation, Assessment, and Related Issues for Policy Analysis. Oper. Res. 1983, 31, 603–631. [Google Scholar] [CrossRef] [Green Version]
- Barlas, Y. Formal aspects of model validity and validation in system dynamics. Syst. Dyn. Rev. 1996, 12, 183–210. [Google Scholar] [CrossRef]
- Pitchforth, J.; Mengersen, K. A proposed validation framework for expert elicited Bayesian Networks. Expert Syst. Appl. 2013, 40, 162–167. [Google Scholar] [CrossRef] [Green Version]
- Hills, R.; Trucano, T. Statistical Validation of Engineering and Scientific Models: A Maximum Likelihood Based Metric; Sandia National Labs.: Livermore, CA, USA, 2002. [Google Scholar]
- Ayhan, B.U.; Tokdemir, O.B. Safety assessment in megaprojects using artificial intelligence. Saf. Sci. 2019, 118, 273–287. [Google Scholar] [CrossRef]
- Valdés, R.M.; Comendador, V.F.; Sanz, L.P.; Sanz, A.R. Prediction of aircraft safety incidents using Bayesian inference and hierarchical structures. Saf. Sci. 2018, 104, 216–230. [Google Scholar] [CrossRef]
- Phelan, S. Case study research: Design and methods. Eval. Res. Educ. 2011, 24, 221–222. [Google Scholar] [CrossRef]
- Lee, S.-W.; Rine, D. Case Study Methodology Designed Research in Software Engineering Methodology Validation. In Proceedings of the Sixteenth International Conference on Software Engineering & Knowledge Engineering (SEKE’2004), Banff, AB, Canada, 20–24 June 2004; p. 122. [Google Scholar]
- Hayes, R.; Kyer, B.; Weber, E. The Case Study Cookbook-Worcester Polytechnic Institute. Available online: https://zbook.org/read/9daf9_the-case-study-cookbook-worcester-polytechnic-institute.html (accessed on 9 October 2021).
- Eisenhardt, K.M. Building Theories from Case Study Research. Acad. Manag. Rev. 1989, 14, 532–550. [Google Scholar] [CrossRef]
- Yan, H.; Gao, C.; Elzarka, H.; Mostafa, K.; Tang, W. Risk assessment for construction of urban rail transit projects. Saf. Sci. 2019, 118, 583–594. [Google Scholar] [CrossRef]
- Alpeev, A.S. Safety Terminology: Deficiencies and Suggestions. At. Energy 2019, 126, 339–341. [Google Scholar] [CrossRef]
- Oberkampf, W.L.; Trucano, T.G. Verification and validation benchmarks. Nucl. Eng. Des. 2008, 238, 716–743. [Google Scholar] [CrossRef] [Green Version]
- Kaplan, S. The Words of Risk Analysis. Risk Anal. 1997, 17, 407–417. [Google Scholar] [CrossRef]
- Augusiak, J.; Van den Brink, P.J.; Grimm, V. Merging validation and evaluation of ecological models to ‘evaludation’: A review of terminology and a practical approach. Ecol. Model. 2014, 280, 117–128. [Google Scholar] [CrossRef]
- Gwet, K.L. Handbook of Inter-Rater Reliability: The Definitive Guide to Measuring the Extent of Agreement among Raters, 4th ed.; Advances Analytics, LLC: Gaithersburg, MD, USA, 2014; ISBN 978-0-9708062-8-4. [Google Scholar]
- Agresti, A. An Introduction to Categorical Data Analysis, 2nd ed.; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2007; ISBN 978-0-471-22618-5. [Google Scholar]
- Landis, J.R.; Koch, G.G. The Measurement of Observer Agreement for Categorical Data. Biometrics 1977, 33, 159–174. [Google Scholar] [CrossRef] [Green Version]
- McCrum-Gardner, E. Which is the correct statistical test to use? Br. J. Oral Maxillofac. Surg. 2008, 46, 38–41. [Google Scholar] [CrossRef]
- Hecke, T.V. Power study of anova versus Kruskal-Wallis test. J. Stat. Manag. Syst. 2012, 15, 241–247. [Google Scholar] [CrossRef]
- Chen, J.; Ma, L.; Wang, C.; Zhang, H.; Ha, M. Comprehensive evaluation model for coal mine safety based on uncertain random variables. Saf. Sci. 2014, 68, 146–152. [Google Scholar] [CrossRef]
- Zhao, H.; Qian, X.; Li, J. Simulation analysis on structure safety of coal mine mobile refuge chamber under explosion load. Saf. Sci. 2012, 50, 674–678. [Google Scholar] [CrossRef]
- Qingchun, M.; Laibin, Z. CFD simulation study on gas dispersion for risk assessment: A case study of sour gas well blowout. Saf. Sci. 2011, 49, 1289–1295. [Google Scholar] [CrossRef]
- Mohsen, O.; Fereshteh, N. An extended VIKOR method based on entropy measure for the failure modes risk assessment—A case study of the geothermal power plant (GPP). Saf. Sci. 2017, 92, 160–172. [Google Scholar] [CrossRef]
- Zhang, L.; Wu, S.; Zheng, W.; Fan, J. A dynamic and quantitative risk assessment method with uncertainties for offshore managed pressure drilling phases. Saf. Sci. 2018, 104, 39–54. [Google Scholar] [CrossRef]
- Bani-Mustafa, T.; Zeng, Z.; Zio, E.; Vasseur, D. A new framework for multi-hazards risk aggregation. Saf. Sci. 2020, 121, 283–302. [Google Scholar] [CrossRef]
- Zeng, Z.; Zio, E. A classification-based framework for trustworthiness assessment of quantitative risk analysis. Saf. Sci. 2017, 99, 215–226. [Google Scholar] [CrossRef] [Green Version]
- Razani, M.; Yazdani-Chamzini, A.; Yakhchali, S.H. A novel fuzzy inference system for predicting roof fall rate in underground coal mines. Saf. Sci. 2013, 55, 26–33. [Google Scholar] [CrossRef]
- Goerlandt, F.; Reniers, G. Prediction in a risk analysis context: Implications for selecting a risk perspective in practical applications. Saf. Sci. 2018, 101, 344–351. [Google Scholar] [CrossRef]
- Aven, T. What is safety science? Saf. Sci. 2014, 67, 15–20. [Google Scholar] [CrossRef]
- Rae, A.; Alexander, R.D. Probative blindness and false assurance about safety. Saf. Sci. 2017, 92, 190–204. [Google Scholar] [CrossRef] [Green Version]
- Groesser, S.; Schwaninger, M. Contributions to model validation: Hierarchy, process, and cessation. Syst. Dyn. Rev. 2012, 28, 157–181. [Google Scholar] [CrossRef]
- Oberkampf, W.L.; Trucano, T.G. Verification and validation in computational fluid dynamics. Prog. Aerosp. Sci. 2002, 38, 209–272. [Google Scholar] [CrossRef] [Green Version]
- Shirley, R.B.; Smidts, C.; Li, M.; Gupta, A. Validating THERP: Assessing the scope of a full-scale validation of the Technique for Human Error Rate Prediction. Ann. Nucl. Energy 2015, 77, 194–211. [Google Scholar] [CrossRef] [Green Version]
- Le Coze, J.-C. Safety Science Research: Evolution, Challenges and New Directions; Taylor & Francis Group: Milton, UK, 2019; ISBN 978-1-351-19022-0. Available online: http://ebookcentral.proquest.com/lib/dal/detail.action?docID=5850127 (accessed on 9 October 2021).
- Martins, L.E.G.; Gorschek, T. Requirements Engineering for Safety-Critical Systems: An Interview Study with Industry Practitioners. IEEE Trans. Softw. Eng. 2020, 46, 346–361. [Google Scholar] [CrossRef]
- Finlay, P.; Wilson, J.M. Validity of Decision Support Systems: Towards a Validation Methodology. Syst. Res. Behav. Sci. 1997, 14, 169–182. [Google Scholar] [CrossRef]
- Aven, T. The risk concept—historical and recent development trends. Reliab. Eng. Syst. Saf. 2012, 99, 33–44. [Google Scholar] [CrossRef]
- Goerlandt, F.; Montewka, J. Maritime transportation risk analysis: Review and analysis in light of some foundational issues. Reliab. Eng. Syst. Saf. 2015, 138, 115–134. [Google Scholar] [CrossRef]
- Goerlandt, F.; Li, J.; Reniers, G.; Boustras, G. Safety science: A bibliographic synopsis of publications in 2020. Saf. Sci. 2021, 139, 105242. [Google Scholar] [CrossRef]
- Li, J.; Goerlandt, F.; Reniers, G. Mapping process safety: A retrospective scientometric analysis of three process safety related journals (1999–2018). J. Loss Prev. Process Ind. 2020, 65, 104141. [Google Scholar] [CrossRef]
Year | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
Number of Articles | 8 | 7 | 12 | 10 | 11 | 16 | 13 | 16 | 28 | 30 |
Variables | Research Question | Null Hypothesis | p-Value |
---|---|---|---|
Validation and safety concept | RQ 4 | There is no correlation between validation and safety concept | 0.4974 |
Validation and model type/approach | RQ 5 | There is no correlation between validation and model type/approach | 0.5437 |
Validation and country of origin | RQ 6 | There is no correlation between validation and country of origin | 0.5982 |
Validation and industrial application domain | RQ 7 | There is no correlation between validation and industrial application domain | 0.5953 |
Validation and stage of the system life cycle | RQ 8 | There is no correlation between validation and stage of the system life cycle | 0.6027 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sadeghi, R.; Goerlandt, F. The State of the Practice in Validation of Model-Based Safety Analysis in Socio-Technical Systems: An Empirical Study. Safety 2021, 7, 72. https://doi.org/10.3390/safety7040072
Sadeghi R, Goerlandt F. The State of the Practice in Validation of Model-Based Safety Analysis in Socio-Technical Systems: An Empirical Study. Safety. 2021; 7(4):72. https://doi.org/10.3390/safety7040072
Chicago/Turabian StyleSadeghi, Reyhaneh, and Floris Goerlandt. 2021. "The State of the Practice in Validation of Model-Based Safety Analysis in Socio-Technical Systems: An Empirical Study" Safety 7, no. 4: 72. https://doi.org/10.3390/safety7040072