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Human and Ecological Risk Assessment: An International
Journal
ISSN: 1080-7039 (Print) 1549-7860 (Online) Journal homepage: http://www.tandfonline.com/loi/bher20
A review of occupational health and safety risk
assessment approaches based on multi-criteria
decision-making methods and their fuzzy versions
Muhammet Gul
To cite this article: Muhammet Gul (2018) A review of occupational health and safety risk
assessment approaches based on multi-criteria decision-making methods and their fuzzy versions,
Human and Ecological Risk Assessment: An International Journal, 24:7, 1723-1760, DOI:
10.1080/10807039.2018.1424531
To link to this article: https://doi.org/10.1080/10807039.2018.1424531
Published online: 02 Feb 2018.
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A review of occupational health and safety risk assessment
approaches based on multi-criteria decision-making methods
and their fuzzy versions
Muhammet Gul
Department of Industrial Engineering, Munzur University, Tunceli, Turkey
ARTICLE HISTORY
Received 17 December 2017
Revised manuscript
accepted 4 January 2018
ABSTRACT
Occupational health and safety (OHS) is a multidisciplinary activity
working under the tasks of protection of workers and worksites. Risk
assessment, as a compulsory process in implementation of OHS,
stands out as evaluating the risks arising from the hazards, taking into
account the required control measures, and deciding whether or not
the risks can be reduced to an acceptable level. The diversity in risk
assessment approaches is such that there are many methods for any
industry. Multicriteria decision-making (MCDM)-based approaches
contribute to risk assessment knowledge with their ability on solving
real-world problems with multiple, conflicting, and incommensurate
criteria. This article conducts a critical state-of-the-art review of OHS
risk assessment studies using MCDM-based approaches. Additionally, it
includes fuzzy versions of MCDM approaches applied to OHS risk
assessment. A total of 80 papers are classified in eight different
application areas. The papers are reviewed by the points of publication
trend, published journal, risk parameters/factors, and tools used. This
critical review provides an insight for researchers and practitioners on
MCDM-based OHS risk assessment approaches in terms of showing
current state and potential areas for attempts to be focused in the
future.
KEYWORDS
OHS; risk assessment; MCDM;
fuzzy sets; literature review
1. Introduction
Occupational health and safety (OHS) concerns the tasks of protection of workers and work-
sites, reducing number of occupational accidents, minimizing insufficient informing, and
improving awareness of employees, from a multi-disciplinary point of view (
_
Inan et al.
2017). As one of the most crucial processes of OHS management, risk assessment and man-
agement has gained great importance due to some regulatory and legal measures recently
(Sousa et al.2015). It identifies sources of risk and determines control measures before an
injury happened (Zanko and Dawson 2012). The following steps provide the risk assessment
process (Health and Safety Executive 2014; Verma and Chaudhri 2016): identifying the haz-
ards, deciding who might be harmed and how, evaluating the risks and deciding on
CONTACT Muhammet Gul muhammetgul@munzur.edu.tr Department of Industrial Engineering, Munzur
University, 62000,Tunceli, Turkey.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/bher.
© 2018 Taylor & Francis Group, LLC
HUMAN AND ECOLOGICAL RISK ASSESSMENT
2018, VOL. 24, NO. 7, 1723–1760
https://doi.org/10.1080/10807039.2018.1424531
precautions, recording significant findings, and reviewing the assessment and update if nec-
essary. The miscellany in risk assessment methods is such that there are many methods for
any industries classified into three groups as qualitative, quantitative, and hybrid (Marhavi-
las et al. 2011). The selection among these methods has become of vital importance as differ-
ent outputs, steps, and applications arise there from (Reniers et al.2005; Guneri et al.2015).
Risk assessment output varies dependent upon the type of method selected.
Multi-criteria decision-making (MCDM) is an advanced field of operations research
(OR), which explicitly considers multiple criteria in decision-making environments. It pro-
vides a broad range of methodologies to decision-makers and analysts, which are well suited
to the complexity of decision problems. MCDM-based approaches are considered in the
quantitative risk assessment category. MCDM methods heavily include human participation
and judgments (Kubler et al.2016). It deals with evaluating, assessing, and selecting alterna-
tives under conflicting criteria with respect to decision-maker(s) preferences (Gul et al.
2016). The main characteristics of a MCDM method include: alternatives, criteria against
evaluated alternatives, scores of alternatives on the criteria, and criteria weights reflecting rel-
ative importance of each criterion as compared with others (Gul et al.2016).
Numerous MCDM-based approaches have been proposed recently to help in selecting the
best alternative rather than taking decisions based only on personal opinions, assessments,
or experiences (Achillas et al.2013). Moreover, the decision-making process towards effi-
cient OHS risk assessment requires the consideration of a series of hazards or hazard types
with respect to different risk parameters. To that end, MCDM methods have been proposed
in recent years as a means to help decision-makers in prioritizing the risks, as well as provide
them a powerful tool towards eliminating risks to an acceptable level. Regarding the rapid
increase in applications of MCDM-based risk assessment approaches among traditional risk
analysis methods, this study basically aims to provide a systematic literature review on the
application of various MCDM methods to tackle OHS risk assessment problems. OHS risk
assessment and management involves many stakeholders who possess different objectives
and criteria (Klinke and Renn 2002). The subjectivity in the decision-making process often
leads to uncertainty due to the lack of information. At this time, decision-makers face a
number of challenges when evaluating risks. A risk assessment framework that ensures the
integration of stakeholder opinions through a wide spectrum of criteria is required. One of
the most important ways is to propose an approach using MCDM-based methods. MCDM
and fuzzy logic integrated MCDM readily provide capturing the judgment of the decision-
makers to weigh and rank the risk parameters and associated hazards when accurate and
complete risk data are unavailable (Ng et al.2017).
MCDM methods present significant advantages over other alternative decision-making
tools, as well as a number of drawbacks. In brief, the key characteristic of MCDM methods
is its flexibility on the judgment of the decision-maker(s). It explores the ideal decision by
assigning performance scores and weights (Bhagtani, 2008). Furthermore, MCDM methods
can be evaluated under a number of alternatives with respect to multiple criteria which are
measured quantitatively and qualitatively. These methods are used to identify either the sin-
gle most preferred alternative, short-list alternatives for subsequent detailed analysis, rank
different alternatives, or to differentiate acceptable from unacceptable possibilities (Achillas
et al.2013). On the other side, there are also some drawbacks. One of the major drawbacks
is its sensitivity to uncertainties. Critical inputs to the MCDM model such as weighting fac-
tors and thresholds are mostly based on the personal views and opinions of the experts
1724 M. GUL
participated. To that end, a sensitivity analysis for these inputs is usually performed as a last
step of the proposed approach. Additionally, for some of the MCDM methods addressed
within this literature review, preference and indifference thresholds are determined in order
to compare alternatives.
Different stakeholders involved in risk assessment and management operations (responsi-
ble OHS experts, employers, employees, engineers, researchers, etc.) can benefit from such a
review in many different ways. The use of MCDM is not yet widely preferred in all sectors
despite its advantages. Thus, by this study, stakeholders can be informed on the potentialities
of such MCDM and fuzzy MCDM-based approaches, their advantages and disadvantages in
comparison to classical risk assessment methods, in order to be supported in the prioritiza-
tion of the hazards and scoring the risks. From their point of view, researchers can benefit
by having access to a thorough list of case studies employing MCDM and fuzzy MCDM-
based approaches in risk assessment problems and which methods were used in each case.
Most importantly, the reader may have access to the risk parameters that were employed in
the recorded practical applications. Moreover, researchers can be also inspired in their work
by implementing different MCDM and fuzzy MCDM-based approaches in future challenges
dealing with risk assessment problems.
Prior to this study, several review studies on risk assessment were carried out under dif-
ferent outlooks. Due to the difference in the review scopes, these studies dealt with different
approaches. However, they all consider the main risk assessment processes and provide use-
ful insight. In Pinto et al. (2011), OHS risk assessment methods were dealt as a state-of-the-
art for construction industry by discussing the limitations and pointing advantages of fuzzy
sets based approaches. They generically referred to construction work sites and traditional
risk assessment methods. Marhavilas et al. (2011) aimed at determining, studying, analyzing,
elaborating, classifying, and categorizing the main risk assessment methods by a literature
review from 2000 to 2009. They focused on traditional risk assessment methods as in Pinto
et al. (2011) and did not pay enough attention to MCDM-based approaches. Verma and
Chaudhri (2016) carried out a comprehensive literature review on risk assessment techni-
ques adopted in the mining industry. Aven (2016) made a comprehensive review of recent
advances on risk assessment and management with a special focus on the fundamental ideas
and thinking. Unfortunately, no systematic and comprehensive review has been provided
for specifically MCDM-based OHS risk assessment approaches. Therefore, in this article, we
review the literature related to the approaches to OHS risk assessment based on MCDM
methods using academic databases of ScienceDirect, Springer, Taylor&Francis, Wiley, and
SagePub. A total of 80 papers were reviewed ranging from 2003 to 2018. Our contributions
to the knowledge are as follows: (1) to determine the MCDM-based OHS risk assessment
approaches, their pros and cons, and potential contributions; (2) to reveal application areas
(natural resources and environment, energy, manufacturing, transportation and supply
chain, construction, chemistry and biochemistry, health, safety and medicine, policy, social
and education) that have further used these approaches; (3) to show the sources in which
papers published related to these approaches; (4) to determine how the trend of these papers
will continue in the future; and (5) to show what risk parameters/factors used.
The proposed state-of the-art review is structured as follows: Section 2details the research
methodology considered to collect, classify, and analyze the papers. Section 3provides classi-
fication of papers in terms of applied MCDM based approaches. Section 4offers a compre-
hensive summary of the review outcomes, graphical representations, and an overall
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1725
assessment on current state, main challenges and open areas for improvement. Finally, Sec-
tion 5presents conclusion, limitations, and recommendations for future studies.
2. Research methodology
This review study was performed to put together articles in notable journals that provide
important insights to researchers and practitioners studying on OHS risk assessment. To
this end, we followed a research methodology as shown in Figure 1.
First, we collect relevant papers from significant databases with suitable search hints
(Occupational Health and Safety AND risk assessment AND multi criteria decision making;
Occupational Health and Safety AND risk assessment AND AHP; Occupational Health and
Safety AND risk assessment AND TOPSIS; Occupational Health and Safety AND risk assess-
ment AND VIKOR; Occupational Health and Safety AND risk assessment AND ELECTRE;
Occupational Health and Safety AND risk assessment AND PROMETHEE; Occupational
Health and Safety AND risk assessment AND fuzzy multi criteria decision making; fuzzy risk
assessment). By this way, we conducted an extensive search in the title, abstract, and key-
words of scholarly papers.
In the review process, the following main library databases cover most of the papers,
namely: Science Direct, Springer, Taylor & Francis, Wiley, Sage, and ASCE. Conference pro-
ceedings, book chapters, thesis, and unpublished working papers were excluded from the
review. The papers were analyzed, classified, and recorded on an Excel sheet using the fol-
lowing dimensions:
Year: Year of publication.
Journal: Title of journal which the paper published in.
Application area: Applied areas are natural resources and environment (NRE), energy
(E), manufacturing (M), transportation and supply chain (TSC), construction (C),
chemistry and biochemistry (CB), health, safety and medicine (HSM), Policy, social
and education (PSE).
Specific objective: Short purpose of the study in a few words including applied area or
methods used.
MCDM methods used: List of applied methods –as listed in Table 1 –used single or
hybrid.
Parameters/factors: Risk parameters/factors evaluated by the authors.
Second, a classification is carried out in terms of applied MCDM methods. Finally, we
analyse the papers in terms of statistical results for distribution of the papers and concluding
remarks for the future studies.
3. Applied MCDM-based risk assessment approaches
MCDM is one of the well-known branch of OR which deals with decision problems under the
presence of a number of decision criteria (Triantaphyllou et al. 1998). It includes the following
steps (Majumder, 2015): (1) identifying the goal of the decision-making process, (2) selection
of the criteria/parameters/factors, (3) selection of the alternatives, (4) selection of the weighing
methods to represent importance, (5) method of aggregation, and (6) decision-making based
on the aggregation results. In the literature, MCDM methods are classified by many ways. One
is to categorize them according to the type of the data used as deterministic, stochastic, or fuzzy
1726 M. GUL
MCDM methods (Triantaphyllou et al. 1998). Since crisp data are inadequate to model real-life
situations, MCDM methods are used in fuzzy environment (Gul and Guneri 2016). Second is
regarding the number of decision-makers involved in the decision process as single or group
MCDM methods. Third is regarding determination of criteria weights (such as AHP, ANP) or
alternative rankings. The ranking-based methods can be either compromise (such as TOPSIS
and VIKOR) or outranking (such as ELECTRE and PROMETHEE).
Figure 1. Research methodology flow chart.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1727
Fuzzy MCDM is used to model the uncertainty and vagueness since many real-world sys-
tems include incomplete and imprecise data. Moreover, in MCDM methods, it is often a dif-
ficult evaluation for analysts to give a precise rating to an alternative with respect to the
corresponding criterion. Assigning weights of criteria using fuzzy numbers instead of crisp
numbers is one of the advantages of fuzzy MCDM methods.
Prior to the classification to be followed, a general overview of the most widely used MCDM
methods is presented. Special focus is given on AHP/FAHP, ANP/FANP, TOPSIS/FTOPSIS,
and VIKOR/FVIKOR which are more commonly MCDM techniques used in risk assessment
problems. An in-depth knowledge and analysis is provided in Ho (2008)forAHP,Kubleret al.
(2016) for FAHP, Behzadian et al. (2012) for TOPSIS/FTOPSIS, Gul et al. (2016) for VIKOR/
FVIKOR. AHP proposed by Thomas L. Saaty is based on the hierarchical MCDM problem
consisting of a goal, criteria, and alternatives. In each hierarchical level, pairwise comparisons
are made with judgments using numerical values taken from the Saaty’sscaleof1–9 (Saaty
Table 1. Acronyms used in the review.
AHP Analytic hierarchy process
ANP Analytic network process
CFPR Consistent fuzzy preference relations
COPRAS Method of complex proportional assessment
DEA Data envelopment analysis
DEMATEL Decision-making trial and evaluation laboratory
ER Evidential reasoning
FAHP Fuzzy analytic hierarchy process
FANP Fuzzy analytic network process
FCE Fuzzy comprehensive evaluation
FDEMATEL Fuzzy decision-making trial and evaluation laboratory
FFMEA Fuzzy failure mode and effect analysis
FFMECA Fuzzy failure mode effects and criticality analysis
FIS Fuzzy inference system
FLINMAP Fuzzy linear programming technique for multidimensional analysis of preference
FMEA Failure mode and effect analysis
FMECA Failure mode effects and criticality analysis
FPROMETHEE Fuzzy preference ranking organization method for enrichment of evaluations
FRA Fuzzy reasoning approach
FTA Fault tree analysis
FTOPSIS Fuzzy technique for order preference by similarity to ideal solution
FVIKOR Fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje
HAZOP Hazard and operability analysis
HEART Human error assessment and reduction technique
HFACS Human factors analysis and classification system
HTA Hierarchical task analysis
LFPP Logarithmic fuzzy preference programming
MACBETH Measuring attractiveness by a categorical based evaluation technique
MOSAR Organized systematic method of risk analysis
MULTIMOORA Multi multi-objective optimization on the basis of ratio analysis
OWGA Ordered weighted geometric averaging operator
PROMETHEE Preference ranking organization method for enrichment of evaluations
QFD Quality function deployment
SCEBRA Scenario based risk assessment
SHARE SHip Accident Root cause Evaluation
SHERPA Systematic human error reduction and prediction approach
TODIM Tomada de Decis~
ao Iterativa Multicrit
erio (an acronym in Portuguese of interactive and
multi-criteria decision-making)
TOPSIS Technique for order preference by similarity to ideal solution
VIKOR VlseKriterijumska Optimizacija I Kompromisno Resenje (means multi-criteria optimization
and compromise solution)
WGA Weighted geometric averaging
1728 M. GUL
1990). The process of AHP enables one to obtain values that weight criteria, and define a rank-
ing of the alternatives while the evaluation is bottom-up. The decision-making process begins
with a comparison of the alternatives with respect to the criteria of the last level. The evaluation
continues up to the criteria of the first level, which are then compared to the goal. AHP has the
advantages of hierarchical structure definition, demonstration of the problem in a structural
manner, and integration of all the judgments with structured links. Another MCDM method
widely used in the field of risk assessment is ANP. The ANP was developed by Saaty in 1996,
as a generalization of the previously developed AHP methodology (Saaty, 1996). In contrast to
AHP, ANP contains a feedback loop for the different criteria and allows interrelations between
them. The TOPSIS method was first proposed by Hwang and Yoon (1981). It uses a given deci-
sion matrix to determine the ideal and negative ideal alternatives. The ranking of the alterna-
tives is then computed based on their separation from those values. VIKOR which was
developed by Opricovic (1998) is a compromise solution for ranking and selecting considering
conflicting criteria. The compromise solution is a feasible solution which is the closest to the
ideal solution like TOPSIS. Apart from these most widely used MCDM methods, there are
other methods that are rarely employed in risk assessment (e.g., DEMATEL, PROMETHEE,
MACBETH, MULTIMOORA, COPRAS, TODIM, and their fuzzy versions). These methods
will be referred to as appropriate in the following sections. The critical importance here in the
decision-making process is the selection of the appropriate method to be used in each particu-
larriskassessmentcasestudy.ThereisnogenericruleforthechoiceofaspecificMCDM
method for a risk assessment problem. The only criterion considered seems to be the question
whether the decision-maker necessitates a ranking of the alternatives, in which case TOPSIS or
VIKOR are mostly selected, or to be hybridized with one another, when AHP/FAHP or ANP/
FANP is usually preferred. Undoubtedly, the decision on the MCDM method to be employed
is made by the authors’previous experience and the flexibility of the method.
The classification we follow in this review study depends on MCDM or fuzzy MCDM
based approaches as applied single or two or more in combination. We do not prefer an
application area based or case-based classification since the focal point of the work may shift.
However, there is no methodological contribution in all reviewed studies. Some of the stud-
ies present a risk analysis in their application area as a novel and first attempt. That’s why
we prefer a method-based classification in this way. We specify the approaches as in the fol-
lowing subsections.
3.1. AHP- and FAHP-based approaches
Two of the most important MCDM methods widely used in the field of OHS risk assessment
are AHP and its fuzzy version FAHP. In risk assessment literature, researchers apply AHP in
order to prioritize the precautions or improvement actions of risky operations (Arslan 2009;
Fera and Macchiaroli 2010; Badri et al.2012), rank safety risks or failures caused by control-
lable hazards (Aminbakhsh et al.2013; Dong and Cooper 2016; Kokang€
ul et al.2017; Kang
et al.2014), and determine safety/risk scores/weights in a hierarchical risk assessment pro-
cess (Ardeshir et al.2014; Wang et al.2016; Topuz and van Gestel 2016; Debnath et al.
2016; Othman et al.2016; Gul et al.2017b; Gul et al.2017c; Raviv et al.2017).
In the study by Arslan (2009), AHP was used for prioritizing the precautions in order to
clarify the risk assessment on chemical tanker operations. Fera and Macchiaroli (2010)
developed a new approach for small and medium sized enterprises (SMEs) using frequency
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1729
and consequence indexes combined with AHP. The application results of the study show
that risk prioritization from the proposed risk assessment model is better than the one
resulting from traditional methods. Badri et al.(2012) presented a risk-factor-based AHP
approach for integrating OHS into project risk evaluation. The proposed approach was
tested using a case study and the calculations were made by the decision-aid software Expert
Choice
©
. The approach was considered as easy to implement in SMEs without requiring a
major investment.
Aminbakhsh et al.(2013) dealt with a risk assessment framework based on AHP and
the theory of cost of safety for prioritization of safety risks in construction projects. A real-
life construction project was demonstrated for the applicability of the method. In order to
create a rational budget and set realistic goals without compromising safety, the proposed
method is considered as a robust method for prioritization of safety risks in construction
projects. Kang et al.(2014) proposed a new risk assessment method that combines major
hazards method, AHP, fuzzy comprehensive evaluation, and risk matrix for oil storage tank
zones. An illustrative example to validate the feasibility and effectiveness of the proposed
model was also performed. Dong and Cooper (2016) developed an orders-of-magnitude
AHP based ex-ante supply chain risk assessment model. The proposed model includes three
phases: Risk identification, risk assessment, and risk ranking and analysis. A case study was
provided to demonstrate the efficacy of the proposed framework. A sensitivity analysis was
also carried out for robustness. Topuz and van Gestel (2016) studied an environmental risk
assessment model for engineered nanoparticles using AHP and fuzzy inference models. A
hierarchy was established to evaluate the sub factors of occurrence likelihood, exposure
potential, and toxic effects. The proposed model was applied for two different nanoparticles
as case study. Debnath et al.(2016) proposed an AHP–ANFIS combined method for OHS
risk assessment in construction industry. A Takagi-Sugeno type fuzzy inference system was
used. Safety levels of each type of injury prone body parts were evaluated by using AHP. The
combined method is applied to few selected construction sites in India. Othman et al.(2016)
presented a structured methodology for incorporating prioritization in HAZOP analysis
using AHP. The hazards of a process identified using HAZOP were quantitatively weighted
and ranked by AHP. The method was applied to a simple reactor unit and a more complex
system of dividing wall column pilot plant as case studies.
Ardeshir et al.(2014) combined FTA, AHP, and fuzzy sets for a risk assessment study.
FTA was used to identify the main causes of events and incidents. Fuzzy sets were injected
to FTA to calculate the possibility of incidence and the severity of the risk. AHP was then
applied to estimate the significance of time, cost, quality, and safety factors. A case study in a
water conveyance tunnel was performed. Wang et al.(2016) made a new dynamic environ-
mental hazard evaluation model including AHP-FCE for hazard installations of the Nansi
Lake Basin of China. Recently a study by Kokang€
ul et al.(2017) was carried out regarding
the usability of the class intervals in Fine Kinney risk assessment method for the results
obtained with AHP method. A case was performed for a large manufacturing company.
Regarding marine risk assessment and management, three studies were reviewed (Akyuz
and Celik 2015; Akyuz and Celik 2016; Akyuz et al.2016). In these studies, AHP was hybrid-
ized with HEART methodology. Akyuz and Celik (2016) proposed a hybrid human error
probability determination approach for cargo loading operation in oil/chemical tanker ship.
Similarly, Akyuz and Celik (2015) conducted a hybrid human reliability analysis for cargo
tank cleaning operation on board chemical tanker ships. In Akyuz et al.(2016), a multi-
1730 M. GUL
dimensional human error assessment and reduction approach to determine marine-specific
error-producing conditions was carried out. Reviewed AHP based risk assessment
approaches are listed in Table 2.
Based on the review on the risk assessment, AHP is a good choice, because it has the
advantages in theory and application as follows: (1) It is an efficient method in determining
the importance levels of the hazards in risk assessment studies. Moreover, as in Kokang€
ul
et al.(2017), it is used to determine whether the hazard levels are acceptable and into which
classes the hazards are sorted. (2) It is easy to be hybridized with other classical methods
(FTA, FCE, FIS, FMEA, HAZOP, 5 £5 risk matrix), in particular, in the phase of determin-
ing the weights sets of multi-level risk factors. (3) It is useful to minimize inconsistencies in
risk analysts’judgments, within the subjective phases of assessment. As in Badri et al.
(2012), it is preferred to minimize the inconsistencies in analysts’judgments and to support
approaches that use mixed qualitative–quantitative assessment data. It is not simply based
on verbal judgments but also makes use of quantitative evaluations (Fera and Macchiaroli
2010). (4) It is used in prioritizing hazards identified in some qualitative (HAZOP as in
Othman et al.2016) or quantitative risk analysis methods (FMECA as in Fera and Macchiar-
oli 2010). (5) Risk weights assignment during the pairwise comparison phase is subjected to
analyst’s preference and thus, is carried out by a good OHS teamwork participation from the
lowest level worker to the highest-level manager. (6) Besides its theoretical advantages; its
applications to the following areas are common: Manufacturing (Badri et al.2012), chemis-
try (Arslan 2009), transportation (Akyuz and Celik 2015), and environment (Wang et al.
2016). Therefore, it is less applicable or not applied, especially to the following areas: Health-
care, information technology, and education. It is simply linked to the lack of studies in the
literature in those areas. This is not related to the fact that problems mainly encountered in
those sectors do not comply with the requisites of AHP-based approaches. As a general
future direction for application of risk analysis, costs of hazards should be considered in
order to manage safety and precautions accurately after applying risk analysis. While consid-
ering commonly used risk parameters in weight determination phase of AHP, a parameter
directly related to “costs of hazard”should be included in the analysis. Another remark is
regarding the assessment of residual risks. In the reviewed papers, no researcher takes into
consideration “residual risk assessment (re-assessment)”using the same or an alternative
MCDM-based approach.
On the other hand, AHP-based approaches have the following limitations: (1) It is used
on a 1–9 scale of Saaty (1990). This scale has some limitations regarding ability of capturing
the magnitude of differences between the probability and severity of identified risks. In order
to eliminate this drawback, Dong and Cooper (2016) propose a new method called orders-
of-magnitude AHP. This approach allows decision-makers to reduce the number of required
comparisons and improve the consistency in the pairwise comparison matrices.
FAHP is a most widely applied MCDM methodology which combines fuzzy logic with
AHP. Since traditional AHP cannot present a subjective thinking manner, FAHP is pro-
posed in order to solve hierarchical problems under fuzziness and uncertainty. In the related
knowledge, many FAHP methods are proposed such as van Laarhoven and Pedrycz (1983),
Buckley (1985), and Chang (1996). For a recent comprehensive literature review on FAHP,
see Kubler et al.(2016). FAHP is used in OHS as a risk assessment tool, as well as in
manufacturing, engineering, and education sectors. As in AHP-based risk assessment stud-
ies, FAHP is applied in order to determine weights of risk factors and sub-factors in
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1731
Table 2. AHP-based risk assessment approaches.
Authors (Year) Application area Specific objective Other tool(s) used Parameters/Factors
Kokang€
ul et al.(2017) Manufacturing Using AHP in determination of Fine–Kinney risk classes Fine–Kinney Likelihood, exposure, and consequence
Kang et al.(2014) Energy Oil storage tank zones risk assessment FCE, Risk matrix Consequence and probability
Topuz and van Gestel (2016) Natural resources and
environment
Environmental risk assessment for engineered
nanoparticles
FIS Occurrence likelihood, exposure potential, and
toxic effects
Dong and Cooper (2016) Transportation and Supply
Chain
Orders-of-magnitude AHP based ex-ante supply chain risk
assessment
Risk matrix Probability and consequence severity
Fera and Macchiaroli (2010) Manufacturing Risk assessment for SME FMECA, SCEBRA Frequency and consequence
Debnath et al.(2016) Construction OHS risk assessment in construction industry ANFIS Accident percentage, accident severity, safety
level, and expenses
Othman et al.(2016) Chemistry and biochemistry Prioritizing HAZOP using AHP HAZOP Flow, temperature, and pressure
Badri et al.(2012) Manufacturing Integrating OHS into project risk evaluation MOSAR Probability of an undesirable event and impact
of an undesirable event
Arslan (2009) Chemistry and biochemistry Chemical tankers risk assessment during cargo operations —Frequency and consequence
Ardeshir et al.(2014) Natural resources and
environment
Combined risk assessment including FTA, AHP, and fuzzy
sets
FTA Probability and severity
Aminbakhsh et al.(2013) Construction Prioritization of safety risks in construction projects Theory of cost of
safety
Probability, severity, and magnitude
Wang et al.(2016) Natural resources and
environment
Risk assessment for hazard installations of the Nansi Lake
Basin, China
FCE Risk source, environmental, personnel, and
preventive ability factors
Akyuz and Celik (2016) Transportation and Supply
Chain
Human error probability determination for cargo loading
operation in oil/chemical tanker ship
HEART N/A
Akyuz and Celik (2015) Transportation and Supply
Chain
Human reliability analysis for cargo tank cleaning
operation on board chemical tanker ships
HEART N/A
Akyuz et al.(2016) Transportation and Supply
Chain
Human error assessment and reduction to marine-specific
error-producing conditions
HEART, HFACS N/A
Raviv et al.(2017) Construction Developing an AHP-based analysis of the risk potential of
safety incidents in construction industry
—N/A
1732 M. GUL
imprecise hierarchical structures or find precedence of risk factors (Da
gdeviren and Y€
uksel
2008; Celik and Cebi 2009; Zou and Lee 2010; Zheng et al.2012; Tian and Yan 2013; Ozkok
2015; Djapan et al.2015;Anet al.2016; Qiaoxiu et al.2016). In some researches, FAHP is
integrated with other tools such as FIS (Topuz et al.2011; Acuner and Cebi 2016), FRA (An
et al.2011; Verma and Chaudhri 2014), ER (Lavasani et al.2011; John et al.2014), FMEA/
FFMEA (Hu et al.2009; Abdelgawad and Fayek 2010;
€
Ozfırat 2014) and FTA (Yazdi 2017;
Yazdi and Kabir 2017).
FAHP is used to develop models for behavior-based safety management (Da
gdeviren and
Y€
uksel 2008). In this work, level of faulty behavior risk in work systems were determined
using Chang’s extent analysis method and a case study in a real manufacturing company
was performed. Since parameters affecting work system safety such as tendency of risky
behavior, insufficient responsibility, ostentation, monotony, and job completion pressure
have non-physical structures, a triangular fuzzy number supported AHP was proposed in
order to represent the real problem more realistically. Chang’s extent analysis has limitations
on obtaining zero weight in weight determination in general. Therefore, Celik and Cebi
(2009) applied Buckley’s FAHP to their study. They integrated FAHP with HFACS frame-
work by providing an analytical foundation and group decision-making ability in order to
identify the role of human errors in shipping accidents. A case study for a casualty investiga-
tion report from a bulk cargo ship was carried out. By the study of Celik and Cebi (2009), it
was seen that FAHP can be used as incorporated with human behavior based risk analysis
tools like HFACS. Similarly, Acuner and Cebi (2016) dealt with marine risk assessment using
FAHP. They developed an efficient risk preventive model in accordance with OHS regula-
tions for shipyards. FAHP was used to determine severities and likelihoods. Apart from sim-
ilar works in the literature, severity was taken into consideration in terms of three
sub-parameters as harm to employee, harm to system, and harm to environment. The tradi-
tional methods such as 5 £5 matrix method and Fine–Kinney utilize only one parameter
for risk severity combining all types of severities. The plus of the approach proposed by Acu-
ner and Cebi (2016) is that the severity of any accident can be considered in detail and so
precautions can be better designed. FIS was used to calculate risk magnitudes. The proposed
approach was applied to a shipyard in order to illustrate the applicability of the model.
Topuz et al.(2011) used a FAHP and FIS based approach integrating environmental and
human health risk assessment for industries using hazardous materials. Priority weights of
risk parameters were determined by using pairwise comparison manner of FAHP in order
to infer a more realistic risk magnitude.
FMEA as an up-to-date risk analysis method is also used with FAHP in risk assessment
processes of mining, manufacturing, and construction sectors. In
€
Ozfırat (2014), risks
defined were evaluated according to the parameters of FMEA which are probability, severity
and detection and importance coefficients of risks were obtained. Then, these coefficients
were turned into degrees defined in FMEA and risk priority numbers (RPNs) were calcu-
lated. In order to reduce subjectivity of FMEA method, FAHP was utilized in evaluation of
three risk parameters of FMEA. Hu et al.(2009) proposed an FMEA approach based on
FAHP for green components to hazardous substance. FAHP was applied to determine the
relative weighs of occurrence, severity, detection, and frequency of green component used
by project factors. Then, a green component RPN was provided by FMEA for the first time
in the literature. Abdelgawad and Fayek (2010) proposed an FMEA model to risk manage-
ment in the construction industry using FAHP. The creative contribution of this study is
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1733
adopting of FAHP to solve the MCDM problem in which the cost impact, time impact, and
scope/quality impact are required to be aggregated into “severity”term of FMEA. Regarding
FMEA–FAHP incorporated studies, researchers should head towards applying of various
versions of fuzzy sets theory with AHP systematic. Intuitionistic fuzzy sets, hesitant fuzzy
sets, type-2 fuzzy sets, and as well as stochastic fuzzy sets theory combined with AHP sys-
tematic can be adapted to implement in evaluation of FMEA components for future studies.
However, the current risk assessment knowledge is saturated with applications of classical
type-1 fuzzy sets theory and AHP incorporation. In this context, the abovementioned studies
separate from each other by the aspect of application domain based novelty.
Verma and Chaudhri (2014) studied for mining risk assessment as in
€
Ozfırat (2014). A
novel approach, which is integration of FRA and FAHP for evaluation of risk levels associated
with identified hazard factors in mining industry, is proposed in their paper. The FRA method
is applied to evaluate the risk levels associated with hazard factors. Then, pairwise comparison
of FAHP is performed to obtain priority weights for the hazard factors. Final priority of haz-
ards based on severity of level of risk associated with them is obtained considering the outcome
of FRA approach in terms of risk score for the hazards, combined with the priority weights
obtained from AHP technique. Lavasani et al.(2011)andJohnet al.(2014)appliedERintheir
FAHP-based risk models. Lavasani et al.(2011) proposed a model for determining the aggrega-
tive risk for an offshore well with objective or subjective data. In this study, risk factors of likeli-
hood and severity were expressed by using fuzzy linguistic variables. AHP was used to assign
weights required for grouping non-commensurate risk sources. ER was utilized to incorporate
new data for updating current risk estimates. John et al.(2014) proposed a novel fuzzy risk
assessment approach for determining the disruption risk of a seaport’s operations. To account
for uncertainties associated with the system operation and provide the flexibility needed to rep-
resent the vague information resulting from the lack of data, FAHP was used in this study. An
et al.(2011)andAnet al.(2016), in their research works, proposed methods for railway risk
assessment. In the first study, FAHP was considered with FRA which is used to estimate the
risk level of each hazardous event in terms of failure frequency, consequence severity, and con-
sequence probability. Then, FAHP was incorporated into the risk model in determining the rel-
ative importance of the risk contribution. A case study on shunting at Hammersmith depot
was performed to illustrate the application of the proposed risk assessment model. In the sec-
ond one, a modified FAHP was developed that employs fuzzy multiplicative consistency
method for the establishment of pairwise comparison matrices in risk decision-making analy-
sis. In applying FAHP, the risk analysts often face a huge number of pairwise comparison
matrices. With the number of risk parameters increasing, the numbers of pairwise comparisons
are increased rapidly. As a result, the judgements of OHS management team are likely to
become highly inconsistent. Therefore, this study is considered as a useful method in solving
the laborious and highly unrealistic situation.
In some studies, FAHP is applied solely to the risk assessment related issues in order to
assign weights of risk factors. In the study of Zheng et al.(
2012), a FAHP-based approach to
evaluate the work safety in hot and humid environments, the fuzzy weights of the 3 factors
(work, environment, and workers) and 10 sub-factors were determined. The proposed
approach contributes to FAHP based risk assessment literature by both methodological and
application aspects as follows: (1) Trapezoidal fuzzy numbers are adopted to measure the
qualitative parameters rather than crisp numbers. This can make the decision-making closer
to reality in terms of real human decision-making. (2) It gives not only work safety
1734 M. GUL
performance of the hot and humid environments but also the safety performances of the fac-
tors and sub-factors. As Tian and Yan (2013) proposed a risk assessment model to general
assembling of satellite. The weights of various risk factors in satellite general-assembling pro-
cess were determined using FAHP. Ozkok (2015) determined risk weights of the activities
carried out at pin jig work unit using a FAHP relating risk assessment framework.
Apart from the abovementioned tools used with FAHP, Zou and Lee (2010) benefited
from a risk checklist in assessing risks for a subway project. Similarly, Qiaoxiu et al.(2016)
used LFPP method for mining risk assessment. Djapan et al.(2015) applied if-then rules in
determining risk level on the workplaces in Serbian SMEs.
In chemical industry, FAHP is used integrated with FTA, which, is a well-known and
commonly used method in chemistry to identify the basic events to reach top event (Yazdi
2017; Yazdi and Kabir 2017). In Yazdi (2017), FAHP was used to compute the failure proba-
bilities of a specified top event with respect to fuzzy FTA. In other words, fuzzy set theory
was used to compute the failure probability of top event for both the classical AHP and the
FTA. In a chemical process plant case study, the results of the proposed model demonstrated
that the failure probability of top event was decreased in comparison with the classical
model. However, the dependency between each basic event was not taken into account. To
overcome this limitation, a fuzzy Bayesian Network based risk analysis model was employed
(Yazdi and Kabir 2017).
To summarize, FAHP-based approaches have following several strengths in OHS risk
assessment: It is frequently preferred by researchers to weight risk factors in a hierarchical
risk assessment and management process or risk parameters of traditional risk assessment
methods such as FMEA, Fine–Kinney, and decision matrix. It can provide decision-makers
obtain more realistic results and be considered as an excellent tool to handle qualitative
assessments by using fuzzy numbers instead of using crisp numbers.
Besides its strengths, it has some drawbacks and limitations. A general deficiency of
FAHP is regarding the possible inconsistency in the comparison matrices with fuzzy num-
bers. Also, risk assessment processes which are demonstrated hierarchically can include fac-
tors or sub-factors that include relationship. This situation was not taken into consideration
(as in Qiaoxiu et al.2016).
Reviewed FAHP based risk assessment approaches are listed in Table 3 including extra
information about application area and used risk parameters/factors.
3.2. ANP- and FANP-based approaches
ANP is a suitable approach to solve decision-making problems including interaction and
dependence between criteria and sub criteria (Chang et al.2012). This approach provides
feedback and dependence between criteria and alternatives. By this approach, complex deci-
sion environments can be modelled. In classical ANP method, decision-makers are faced
with a number ambiguity in evaluating possible alternative columns. Due to these ambigui-
ties and uncertainty, the pairwise comparisons in classical ANP are inadequate for echoing
the real thoughts of decision-makers. Fuzzy logic can be predicated on the pairwise compari-
sons to overcome this inadequacy. For this reason, this integrated method is entitled FANP.
In risk assessment knowledge, ANP has also an important place, but not as AHP. It is
applied in order to determine weights of risk parameters in FMECA (Silvestri et al.2012),
3 main factors and 10 sub-factors of a risk assessment in foundry industry (Ilangkumaran
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1735
Table 3. FAHP-based risk assessment approaches.
Authors (Year) Application area Specific objective Other tool(s) used Parameters/Factors
Djapan et al.(2015) Manufacturing Determining risk level on the
workplaces of SMEs
Fuzzy rule base N/A
An et al.(2016) Transportation and Supply Chain Railway risk assessment Fuzzy multiplicative consistency N/A
Qiaoxiu et al.(2016) Energy Mining risk assessment LFPP Environment, human factor, management and
technology, equipment
Zheng et al.(2012) Energy Work safety in hot and humid
environments
—Work, environment, and workers factors
Da
gdeviren and Y€
uksel (2008) Manufacturing Behavior-based safety
management
—Organizational, personal, job related and
environmental factors
Tian and Yan (2013) Manufacturing Risk assessment to general
assembling of satellite
—Organization, individual, task, environment and
equipment factors
Topuz et al.(2011) Natural resources and environment Environmental and human
health risk assessment for
hazardous materials industry
FIS Planned emission, accidental emissions, and
indoor air emissions
Ozkok (2015) Construction Risk assessment of pin jig work
unit in shipbuilding
—Crane movements, welding, grinding, and
mounting
Zou and Lee (2010) Transportation and Supply Chain Risk assessment for subway
projects
Check list Economic and financial risk, planning risk,
contractual and legal risk, design risk,
geological risk, and construction risk
An et al.(2011) Transportation and Supply Chain Railway risk assessment FRA Failure frequency, consequence severity, and
consequence probability
John et al.(2014) Transportation and Supply Chain Risk assessment in seaport
operations
ER Likelihood and severity
€
Ozfırat (2014) Energy FMEA integrated with FAHP FMEA Probability, severity, and detection
Lavasani et al.(2011) Energy Risk assessment for an offshore
well
ER Likelihood and severity
Verma and Chaudhri (2014) Energy Robust hybrid risk assessment
for mining industry
FRA Consequence of severity, level of exposure, and
frequency of occurrence
Hu et al.(2009) Manufacturing FMEA based on FAHP for green
components to hazardous
substance
FMEA Occurrence, severity, detection, and frequency
of green component used by project
Abdelgawad and Fayek (2010) Construction Risk management in the
construction industry
FFMEA Impact, probability of occurrence, and
detection/control
Acuner and Cebi (2016) Transportation and Supply Chain Model proposal of OHS
regulations for shipyards
FIS Probability and severity
1736 M. GUL
Celik and Cebi (2009) Transportation and Supply Chain Human error assessment in
shipping accidents
HFACS N/A
Kececi and Arslan (2017) Transportation and Supply Chain Developing a fuzzy SWOT AHP
method in the examining of
root causes of ship accidents
SHARE, SWOT N/A
Yazdi (2017) Chemistry and biochemistry Highlighting the utility of fuzzy
set theory and AHP to failure
probability analysis in a
chemical plant case study
FTA Failure probability
Yazdi and Kabir (2017) Chemistry and biochemistry Combining fuzzy set theory and
expert knowledge with FTA
through Bayesian Network
modeling to enable risk
assessment of complex
systems with ambiguous
failure data
FTA, Bayesian Network Failure probability
Zhou et al.(2017) Transportation and Supply Chain Developing a quantitative
CREAM method with
stakeholder-graded protocols
for tanker shipping safety
application
CREAM N/A
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1737
et al.2015), causal factors of a grounding accident case (Akyuz 2015) and accident causes
related to the human error in a real-ship incident case (Akyuz 2017). Yucel et al.(2012)
developed a new predictive risk assessment model for a hospital information system (HIS).
The proposed method used ANP, reality–design gap evaluation, and FIS. A case study was
performed in a research and education hospital in Istanbul, Turkey. AHP method assumes
that the risk criteria or sub-criteria should be independent from each other. Since, in the
HIS implementation, some of the risk criteria were related to each other, ANP was used
instead of AHP. Liu et al.(2013) proposed a fuzzy synthetic evaluation approach for scien-
tific drilling project risk assessment. AHP and ANP were used to determine sensible weights
of probability, severity, non-detectability, and worsening factors. Fuzzy synthetic evaluation
approach was applied to obtain the evaluation of each risk and a risk index was calculated to
indicate the level of each risk. A case study on risk analysis in Jilin University, China was
tested to demonstrate the procedure of the method and to validate the proposed method.
Due to probing-specific situation, four risk parameters were taken into consideration for this
study unlike similar contributions in the literature such as Yucel et al.(2012) (likelihood and
severity) and Silvestri et al.(2012) (severity, occurrence, detection). The fundamental benefit
of ANP/FANP based approaches to OHS risk assessment is that hhierarchical risk assess-
ment processes can occasionally depend on interrelated factors or sub-factors. ANP/FAHP
based approaches are fully appropriate and solution producing for these problems. In
Table 4, a summary of ANP-based risk assessment approaches is provided.
Liu and Tsai (2012) proposed an integrated approach benefiting from a two stage QFD,
FANP, and FFMEA for occupational hazards in the construction industry. This is the only
study reviewed within the scope of this review that uses FANP in OHS risk assessment. In
this current study, QFD was first used to obtain the relationships among construction items,
hazard types, and hazard causes. Second, FANP was used to identify important hazard types
and hazard causes. Finally, FFMEA was performed to assess the risk value of hazard causes
based on the fuzzy inference approach. A case study in a telecom engineering company in
southern Taiwan was also performed.
3.3. TOPSIS- and FTOPSIS-based approaches
TOPSIS is a powerful, technical MCDM method that was first developed by Hwang and
Yoon (1981) to determine the best alternative based on the concepts of the compromise
solution. The compromise solution can be regarded as choosing the solution with the short-
est distance from the ideal limit and the farthest distance from the negative ideal limit. It is a
distance-based method (Jozi and Majd 2014). Since the evaluated ratings usually refer to the
subjective uncertainty, it is natural to extend TOPSIS to consider the situation of fuzzy num-
bers (Gul and Guneri 2016). Both TOPSIS and its fuzzy version FTOPSIS are commonly
preferred risk assessment tool. In this sub-section, TOPSIS and FTOPSIS based approaches
are reviewed.
Through the risk assessment knowledge, TOPSIS or FTOPSIS are applied in order to pri-
oritize the emerged risks or risk groups/types (Jozi et al.2012; Ali and Maryam 2014; Jozi
and Majd 2014; Saffarian et al.2015; Jozi et al.2015).
Assessment of environmental risks is one of the risk management issues that emphasize
potentially negative environmental effects of human activities and include identification
and quantification of environmental risks. Therefore, using MCDM-based solutions in
1738 M. GUL
Table 4. ANP-based risk assessment approaches.
Authors (Year) Application area Specific objective
Other tool(s)
used Parameters/Factors
Silvestri et al.(2012) Manufacturing A new methodological approach
called the safety improve risk
assessment
FMECA, AHP Occurrence, severity, and
detection
Ilangkumaran et al.(2015) Manufacturing Work safety in hot environments
of foundry industry
—Work, environment, and workers factors
Liu et al.(2013) Manufacturing Scientific drilling project risk
assessment
AHP Probability, severity, detectability, and worsening factor
Yucel et al.(2012) Health, safety, and medicine Risk assessment for a hospital
information system
FIS Severity and likelihood
Akyuz (2015) Transportation and
Supply Chain
Accident analysis in marine
industry
AcciMap Government policy and budgeting; regulatory bodies and associations; company
management; technical and operational management; physical
processes and actor activities; and equipment and surroundings
Akyuz (2017) Transportation and
Supply Chain
Accident analysis for potential
operational causes in cargo
ships
HFACS Organizational influences, unsafe supervision, precondition for
unsafe acts, and unsafe acts
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1739
assessment of environmental risks can be frequently used in the literature. Jozi et al.(2012)
proposed an integrated Shannon’s entropy–TOPSIS methodology for environmental risk
assessment of the Helleh protected area in Iran. In the current study, first, the risks existing
in the region were identified. Then, Delphi method was applied for final identification of the
risks. Finally, prioritization of risks was determined by Shannon’s entropy and TOPSIS
methodologies. Ali and Maryam (2014) studied on an environmental risk assessment of
dams by using AHP and TOPSIS methods. The environmental risk factors in the Polrood
dam, Iran were initially identified by Delphi and then rated using TOPSIS. AHP was applied
to classify the risk factors into categories. In order to identify and prioritize the most impor-
tant risks affecting a gas power plant, Saffarian et al.(2015) and Jozi et al.(2015) used TOP-
SIS combined with AHP and Delphi, respectively. Results of the first study indicated that
gas and oil pipes, dust storm, and terrorism had the first to third priorities among the other
risks. On conclusion of the second study, the most important safety, health environmental
risks in the studied power plant were determined. Jozi and Majd (2014) applied an OHS and
environmental risk assessment model to steel production industry. The main contribution
of this study is that health, safety, and environmental risks of steel industry are assessed by
TOPSIS for the first time. Apart from the abovementioned TOPSIS based risk assessment
approaches, Ji et al. (2015) aimed to model to risk assessment of 10 national hydropower sta-
tions along the Xiangxi River in China. This study was considered as the first attempt of the
integrated fuzzy entropy-weight MCDM model to risk assessment of hydropower stations.
In summary, TOPSIS-based risk assessment approaches are presented in Table 5.
As in TOPSIS-based approaches, researchers pay attention to FTOPSIS-based risk assess-
ment approaches. It is mostly used with FAHP (Taylan et al.2014; Gul and Guneri 2016;
Akyildiz and Mentes 2017). Taylan et al.(2014) evaluated risks of construction projects at
King Abdulaziz University (KAU). Gul and Guneri (2016) prioritized 23 various hazard
groups in an aluminium plate manufacturing plant. The likelihood and severity parameters
were weighted by FAHP, then the orders of priority of 23 various hazard groups were deter-
mined by using FTOPSIS. Results showed that the most important three hazard groups for
the factory were determined as suffocation from gas, getting an electric shock, and falling of
objects. In the study of Akyildiz and Mentes (2017), cargo vessel safety assessment was per-
formed by the combined approach. Grassi et al. (2009) contributed to the risk assessment
knowledge by proposing a new fuzzy based method taking into account effects of human
behaviour and environment on risk value. They used five risk parameters as injury magni-
tude, occurrence probability, undetectability, sensitivity to non-execution of maintenance,
and sensitivity to non-utilization of personal protective equipment (PPE). A case study for
the evaluation of risks in production process of a well-known Italian sausage was carried out
and a comparison with the classical model was discussed. Mahdevari et al.(
2014) studied in
underground coal mining industry using FTOPSIS. TOPSIS was used to analyse and assess
the risk of working in the mines. Three underground coal mines namely Hashouni, Hojedk,
and Babnizu located at the Kerman coal deposit in Iran were selected as case studies. Eighty
six risky events were analysed. Control measures were suggested for each of them. Ebrahim-
nejad et al.(2010) made a risk assessment for build–operate–transfer projects by FLINMAP
and FTOPSIS. Both methods were used to rank high risks in BOT projects and compared in
four respects: Separation among alternatives, fuzzy error in criteria’s weights, risk response
planning, and numerousness of alternatives in proportion to criteria. As a methodological
contribution to the FTOPSIS-based risk assessment approaches, Braglia et al.(2003)
1740 M. GUL
Table 5. TOPSIS-based risk assessment approaches.
Authors (Year) Application area Specific objective
Other tool(s)
used Parameters/Factors
Saffarian et al.(2015) Energy Gas power plant risk assessment AHP Topography, geology, climatology, hydrology,
vegetation, wildlife, habitat, limnology, zoning,
economic, social, and cultural factors
Jozi et al.(2012) Natural resources and
environment
Environmental risk assessment Shannon’s
entropy
Severity, probability of occurrence, and vulnerability
Ali and Maryam (2014) Natural resources and
environment
Environmental risk assessment of dams AHP Intensity and probability
Jozi and Majd (2014) Manufacturing OHS and environmental risk assessment in steel
industry
—Air quality, water, soil, biological environment,
socioeconomic and cultural environment, and health
and safety of the employees
Ji et al.(2015) Energy Hydropower stations risk assessment Fuzzy entropy Thirteen indices (average annual flow, the rain area,
hydraulic head, etc.)
Jozi et al.(2015) Energy OHS and environmental risk assessment in gas
power plant
Delphi Noise, vibration, lighting, thermal stress, harmful rays,
ergonomics, dust, and chemical steams
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1741
suggested a FMECA based on FTOPSIS. In order to validate the suggested approach, an
application case study was presented in an Italian domestic appliance manufacturing com-
pany. Carpitella et al.(2018) followed a similar methodology with Braglia et al.(2003). They
combined FMECA and MCDM methods (FTOPSIS and AHP) to optimize maintenance
activities of a street cleaning vehicle. The main difference between these two studies is
stemmed from the selected risk parameter. Carpitella et al.(2018) used three evaluation
parameters that differ from those traditionally involved in RPN computation in classical
FMECA (i.e., severity, occurrence, and detection). Two criteria refer to the maintenance
management reflecting the operational time taken by the maintenance activity performed
after the occurrence of a specific failure, and the way such an action is executed. The third
criterion reflects the classical frequency of the occurrence of failures. Table 6 shows FTOP-
SIS-based approaches briefly explained above in terms of aims and contributions.
Detailed reviewing of both TOPSIS and FTOPSIS based risk assessment approaches
show that they are commonly used methods by researchers due to their compromise solu-
tions. In general, prioritization of hazards and associated risks are performed by using
TOPSIS/FTOPSIS. They also can be hybridized with other MCDM methods (AHP, FAHP,
Fuzzy entropy, Delphi, and Shannon’s entropy) in pre-assessment of hazards in evaluation
of risk parameters. Researchers seek to contribute to the literature theoretically by extend-
ing TOPSIS method towards various versions of fuzzy sets. For example, Jozi and Majd
(2014) extended the TOPSIS method to solve MCDM problems in interval-valued intui-
tionistic fuzzy environment. The main advantages of using FTOPSIS for OHS risk assess-
ment studies can be explained as follows: FTOPSIS-based approaches allow the analysts to
assign judgments to the hazard groups with respect to risk parameters of a traditional or
another MCDM-based method by means of linguistic terms, which are better interpreted
by humans, fuzzy in nature and then transferred into fuzzy numbers. In most of above-
mentioned studies, FTOPSIS is applied in order to analyze the hazards with health and
safety of various application domains, since it has more capability in handling uncertain-
ties, simultaneous consideration of the positive and the negative ideal points, simple com-
putation and logical concept.
3.4. VIKOR- and FVIKOR-based approaches
The VIKOR method was developed by Opricovic (1998)asaMCDMmethodtosolvea
discrete multi criteria problem with non-commensurable and conflicting criteria (Opri-
covic and Tzeng 2004). In this method, it is aimed to determine a compromise solution
for ranking and selecting considering conflicting criteria. The compromise solution is a
feasible solution which is the closest to the ideal solution like TOPSIS methodology (Opri-
covic and Tzeng 2004). For a recent comprehensive literature review on VIKOR and its
fuzzy extensions on applications, researchers may refer to Gul et al. (2016). The fuzzy ver-
sion of this method FVIKOR involves fuzzy assessments of criteria and alternatives in
VIKOR.
In the risk assessment literature, both methods are used by researchers in order to deter-
mine priorities of the risk groups/failure modes (Liu et al.2012; Mandal et al. 2015; Gul
et al.2017a; Gul et al.2017b; Gul et al.2017c; Mohsen and Fereshteh 2017; Ozdemir et al.
2017). Liu et al.(2012) proposed a risk assessment based on FFMEA and VIKOR. In the cur-
rent study, fuzzy linguistic variables were used to assess the ratings and weights for the risk
1742 M. GUL
Table 6. FTOPSIS-based risk assessment approaches.
Authors (Year) Application area Specific objective
Other tool(s)
used Parameters/Factors
Gul and Guneri (2016) Manufacturing Risk assessment in aluminum industry FAHP Likelihood and severity
Grassi et al.(2009) Manufacturing Proposing a new fuzzy based method taking
into account effects of human behavior
and environment on risk value
—Injury magnitude, occurrence probability, undetectability, sensitivity to non-
execution of maintenance, and sensitivity to non-utilization of PPE
Taylan et al.(2014) Construction Evaluation of risks of construction projects FAHP Time, cost, safety, quality, and environmental sustainability
Mahdevari et al.(2014) Energy Human health and safety risk assessment for
underground coal mines
—Likelihood and consequence
Ebrahimnejad et al.
(2010)
Construction Risk assessment for build–operate–transfer
projects
FLINMAP Probability, impact, quickness of reaction toward risk, event measure quantity,
and event capability
Braglia et al.(2003) Manufacturing FMECA-based FTOPSIS risk assessment FMECA Chance of failure, chance of non-detection and severity
Akyildiz and Mentes
(2017)
Transportation and
Supply Chain
Risk assessment for cargo vessel safety FAHP Level of understanding, quality of knowledge, uncertainty level of cargo ship
accidents, and sensitivity levels of model parameters
Carpitella et al.(2018) Manufacturing Combination of FMECA and MCDM methods
(FTOPSIS and AHP) to optimize
maintenance activities of a street cleaning
vehicle
AHP, FMECA Time of operation, modality of execution, frequency of occurrence
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1743
factors occurrence, severity and detection and the extended VIKOR was used to determine
risk priorities of the failure modes. A case was carried out in a general anesthesia process. As
a shortcoming of the proposed approach, no sensitivity analysis was carried out in order to
demonstrate the validity. Mandal et al. (2015) developed a method for performing human
errors and risks assessment including HTA, SHERPA, FMEA, and FVIKOR with an applica-
tion to overhead crane operations. The main difference between this study and Liu et al.
(2012) stems from identification of errors. In this phase of risk assessment, Liu et al.(2012)
used HTA and SHERPA methods as a novelty. SHERPA method divides human errors into
five categories namely: Action errors, checking errors, information retrieval errors, commu-
nication errors, and selection errors. Gul et al.(2017a) and Gul et al.(2017c) suggested a
risk assessment model using FAHP–FVIKOR incorporation for hospitals and arm
manufacturing plants, respectively. In the first study, FAHP was used to determine weights
of the five risk factors used by Grassi et al. (2009). FVIKOR was then applied for determina-
tion of risk groups in each department of the case study hospital. The study proposed by
Gul et al.(2017a) considers five parameters which are severity, occurrence, undetectability,
sensitivity to maintenance non-execution, and sensitivity to PPE non-utilization different
from traditional OHS risk assessment methods (e.g., decision matrix, Fine–Kinney, and
FMEA). From the application point of view, it is an initial attempt in health risk assessment
using MCDM-based approaches (FAHP, FVIKOR) and expected to provide a basis for deci-
sions and policies that must be taken by hospitals in their healthcare process. But, in the sec-
ond study, the core deficiency of current literature on risk assessment and methodological
contribution to the knowledge are based on elimination of its drawbacks. Moreover, the cur-
rent study executes a comparison of the proposed framework with traditional Fine–Kinney
and reveals its strengths by the aid of compromised solutions of FVIKOR. In order to
empower the consistency, a comparison with FTOPSIS (which is a compromising MCDM
method such as FVIKOR based on displaying the shortest distance from the positive-ideal
solution and the farthest distance from the negative ideal solution) is also provided. In times
of potential difficultness in capturing the decision-maker’s judgment with respect to the risk
parameters and evaluating hazards using a single set of fuzzy linguistic terms, researchers
can consider the application of various versions of fuzzy sets theory for resolving this issue
in their future contributions. The study by Ozdemir et al.(2017) is an important contribu-
tion to the development of various versions of fuzzy sets in risk assessment area. They incor-
porate 5S methodology, FMEA, interval type-two fuzzy sets, AHP, and VIKOR in risk
assessment of the university laboratory operations. 5S is used in determination of failure
modes. AHP is injected into interval type-two fuzzy sets in the phase of evaluation and
weighting of severity, occurrence, and detectability parameters of classical FMEA. By apply-
ing interval type-2 FVIKOR, it is aimed at prioritizing the emerged hazards in the chemical
laboratory of a university in Turkey.
3.5. Other MCDM-based approaches
Apart from the three aforementioned most widely used MCDM methods, there are other
methods that are rarely employed in OHS risk assessment. In this sub-section, we put
together these MCDM-based approaches such as DEMATEL, FDEMATEL, MACBETH,
MULTIMOORA, fuzzy MULTIMOORA, TODIM, COPRAS, DEA, FPROMETHEE, WGA,
and CFPR. Among these approaches, the most widely applied method is DEMATEL and its
1744 M. GUL
fuzzy version FDEMATEL (Zhou et al.2014; Meknatjoo and Omidvari 2015; Akyuz and
Celik 2015; Mentes et al.2015).
Zhou et al.(2014) proposed a novel hybrid MCDM approach to evaluate the hydro-
power-construction-project safety. Interdependence relationships and relative weights of
factors in high-risk hydropower-construction-project work systems were obtained by ANP
and DEMATEL methods. The DEMATEL method is not only interested in pairwise influ-
ence between risk factors, but also takes into account the indirect effect relationship in all
risk factors. In addition, the classical method adopts normalization for the weighted super-
matrix in the ANP procedure by assuming equal weights for each cluster; however, this
ignores the different effects among clusters. A combined DEMATEL–ANP approach over-
comes this unreasonable assumption of equal weights, thus providing a more suitable
approach than the classical method. Finally, the weights of construction-accident factors cal-
culated by the ANP model and the causal graph derived from the DEMATEL method can
both provide guidance for safety management.
Moreover, FDEMATEL-based approaches are developed in marine (Akyuz and Celik
2015; Mentes et al.2015) and manufacturing industries (Meknatjoo and Omidvari 2015).
While Akyuz and Celik (2015) studied to evaluate critical operational hazards in gas freeing
process, Mentes et al.(2015) developed a risk method for cleaner and safer maritime trans-
port at coast and open seas of Turkey. In these studies, FDEMATEL was used to identify
and evaluate the potential hazards of gas freeing process with respect to causal-effect relation
diagram and driving factors like geographical locations at the time of the incident and failure
modes causing fatality for cargo ships, respectively. Meknatjoo and Omidvari (2015) identi-
fied risk factors and influencing sub-factors on ranking of risk levels in the William–Fine
and FDEMATEL incorporated model in machining processes.
Kuo and Lu (2013) presented a multi criteria risk assessment model for a metropolitan con-
struction project. CFPR was used to measure and investigate the relative impact on project per-
formance of 20 identified risk factors included in 5 risk dimensions. The proposed approach
was applied to a metro system construction project in the city of Taipei. Chang et al.(2013)
proposed a risk assessment by 5S activitiesforsemiconductormanufacturingforthefirst time
in the risk assessment literature. A novel method of FMEA and 2-tuple method as well as
WGA operators was proposed to apply for 5S audit in semiconductor manufacturing plant.
Liu et al.(2014) applied a new risk priority model based MULTIMOORA and fuzzy sets. In
this current study, it was extended and applied the MULTIMOORA method to FMEA. A case
study of preventing infant abduction was presented. A comparison among fuzzy MULTI-
MOORA, crisp MULTIMOORA, and classical FMEA was also carried out. Bentaleb et al.
(2015) analysed and assessed risk factors within the dry port-seaport system using MACBETH.
The model was applied through a Moroccon dry port-seaport system. Rezaee et al.(2017)and
Efe et al.(2016) used DEA and FPROMETHEE in their risk assessment studies. Both methods
used FMEA as an auxiliary method. Rezaee et al.(2017) proposed an approach using FMEA
and DEA for failures in stone processing industry. First, by using FMEA, failures in the stone
industry in Iran were identified. Secondly, the parameters of FMEA and the imposed costs
related to any failure in the system were considered as the inputs and output of DEA model. A
real case was also studied. Efe et al.(2016) applied FMEA and FPROMETHEE for failures in
construction industry. Linguistic variables were used to assess occurrence, severity, and detec-
tion factors related to weights. For selecting the most serious failure modes, FPROMETHEE
was used. Table 7 shows other MCDM-based approaches applied in OHS risk assessment.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1745
Table 7. Other MCDM-based risk assessment approaches.
Authors (Year) Application area Specific objective
Applied MCDM
method Other tool(s) used Parameters/Factors
Zhou et al.(2014) Construction Hydropower-construction-project safety
management
DEMATEL ANP Enterprise influence, safety
management, field work related
factors and construction
personnel unsafe acts
Bentaleb et al.(2015) Transportation and Supply
Chain
Dry port-seaport system risk assessment MACBETH —Operational, professional,
organizational, technical, security
and financial risks
Liu et al.(2014) Health, safety and medicine Proposing new risk priority model based
MULTIMOORA and fuzzy sets
MULTIMOORA FMEA Probability, severity and detection
Rezaee et al.(2017) Manufacturing Stone processing industry risk analysis DEA FMEA Occurrence, severity and detection
Efe et al.(2016) Construction Risk assessment in construction industry FPROMETHEE FMEA Occurrence, severity and detection
Chang et al.(2013) Manufacturing Risk assessment by 5S activities for
semiconductor manufacturing
WGA FMEA, 5S Occurrence, severity and detection
Meknatjoo and Omidvari
(2015)
Manufacturing Identifying risk factors in machining processes FDEMATEL William–Fine model Exposure, probability, and
consequence
Kuo and Lu (2013) Construction Metropolitan construction project risk
assessment
CFPR —Engineering design, construction
management, construction safety-
related, natural hazards, social
and economic factors
Akyuz and Celik (2015) Transportation and Supply
Chain
Critical operational hazards evaluation in gas
freeing process
FDEMATEL —N/A
Mentes et al.(2015) Transportation and Supply
Chain
Maritime transport risk assessment at coast and
open seas of Turkey
FDEMATEL OWGA Severity and occurrence
Wang et al.(2017) Transportation and Supply
Chain
Developing a new risk ranking model for FMEA
based
on soft set theory and COPRAS method
COPRAS FMEA, Choquet
integral
Occurrence, severity, and detection
Liu et al.(2017) Health, safety and medicine Proposing an FMEA based risk analysis model
using cloud model theory and PROMETHEE
method
PROMETHEE FMEA, Cloud model Occurrence, severity, and detection
Huang et al.(2017) Manufacturing Developing a new FMEA model based on
linguistic distribution assessments (entropy
and FAHP) and a modified TODIM method to
ameliorate the shortcomings of the
traditional FMEA
TODIM FMEA, FAHP, Entropy Occurrence, severity, and detection
Fattahi and Khalilzadeh
(2018)
Manufacturing Combination of FMEA, extended MULTIMOORA
and AHP methods under fuzzy environment
for risk evaluation in steel industry
Fuzzy MULTIMOORA FMEA, FAHP Occurrence, severity, and detection
1746 M. GUL
4. Discussion
Sections 4.1–4.5 present graphical representations of MCDM-based OHS risk assessment
approaches by the following points of view: (1) publication trend, (2) published journal, (3)
main application area, (4) risk parameters/factors, and (5) MCDM tools used.
4.1. Distribution of papers by publication trend
The reviewed papers are handled to model the evolution of MCDM-based risk assessment
approaches in time, by adjusting the distribution of the number of studies during the period
of 2003–2017 through a polynomial regression analysis which is determined with 95% confi-
dence level. The year 2018 was not included in the analysis. From Figure 2, it can be easily
seen that after 2014 there is an important increase in the production of papers. The trend
shows more pronounced with a higher R
2
value (93%), indicating that the MCDM-based
approaches related papers have increasingly better reception within the risk assessment
literature.
When investigated distribution of papers by time period on a yearly basis in terms of pro-
posed approaches, AHP/FAHP based approaches related papers have highly increased.
Besides, papers related to ANP/FANP, TOPSIS/FTOPSIS, and VIKOR/FVIKOR based
approaches are published after the year 2012. In general, regarding AHP/FAHP based
approaches, the first paper was published in 2008. Number of papers reached to the peak of
nine papers in 2016 in various application areas. Regarding the TOPSIS/FTOPSIS based
approaches, the first paper was published in 2003 in field of manufacturing and the number
of papers decreased between 2014 and 2017. The information of publication years and
approaches is provided in Figure 3.
4.2. Distribution of papers by published journal
Figure 4 provides the list of journals ordered on the basis of the number of papers (from
those journals) that have been reviewed and integrated to our review study (ND80, and
associated percentage % D100, standing for the total number of papers). Safety Science
has the most publications on MCDM-based risk assessment approaches (21; 26%),
Figure 2. Distribution of papers by publication year.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1747
Figure 3. Distribution of papers by publication year and approaches.
Figure 4. Distribution of papers in terms of journals.
1748 M. GUL
followed by Expert Systems with Applications (6; 8%), Human and Ecological Risk Assess-
ment (6; 8%), Journal of Loss Prevention in the Process Industries (5; 6%), and Process
Safety and Environmental Protection (3; 4%).Ofthejournals,AccidentAnalysisandPre-
vention, Environment International, Environmental Monitoring and Assessment, Infor-
mation Science, International Journal of Project Management, Reliability Engineering and
System Safety and Brodogradnja/Shipbuilding have two papers (3% per each). Other jour-
nals contain one entry (1% per each). From Figure 4, it can be seen that the first five
ranked journals provide a comprehensive resource for professionals researching and
assessing hazards to both humans and ecological systems except Expert Systems with
Applications. Risk assessment and management related topics are also welcomed to some
journals whose focus are regarding exchanging information relating to expert and intelli-
gent systems such as Expert Systems with Applications, Information Science and Applied
Soft Computing.
4.3. Distribution of papers by main application area and MCDM tools used
Regarding the application areas, “Manufacturing”constitutes nearly more than a quarter of
the total papers. Twenty seven percent of total papers (nD21) are concentrated in this
application area (Table 8). They focus on specific problems in aluminum, stone processing,
drilling, semiconductor manufacturing, and machining processes. Another most studied
application areas are “Transportation & Supply chain,”“Construction,”and “Energy”by
25% (nD20), 15% (nD12), and 14% (nD11) of total papers. “Natural resources and envi-
ronmental,”“Health, safety and medicine,”“Chemistry and biochemistry,”and “Policy,
social and education”are probably in the most delicate disciplines.
From the summary of MCDM tools used in each application areas, the following impor-
tant findings can be extracted: (1) The FAHP-based approaches play a dominant role among
all approaches with a rate of 28% (nD22/80). The most widely applied approach among all
application areas is FAHP in transportation and supply chain area. (2) FANP and VIKOR
based approaches are the least applied among all application areas. While FANP is only
applied in construction industry, VIKOR is used in health, safety, and medicine areas as a
risk assessment tool. (3) AHP is applied to almost all application areas excluding agriculture,
health, safety and medicine and policy, social and education, while FAHP is applied to five
of the eight application areas.
Table 8. Summary of MCDM tools used in each application area.
Application areas/MCDM tools used AHP FAHP ANP FANP TOPSIS FTOPSIS VIKOR FVIKOR Others Total
Chemistry and biochemistry 2 2 —— — — — — — 4
Construction 3 2 —1—2—1312
Energy 1 5 —— 31—1—11
Health, safety and medicine —— 1—— — 11 25
Manufacturing 3 4 3 —14—1521
Natural resources and environment 3 1 —— 2————6
Transportation and Supply Chain 4 8 2 —— 1—1420
Policy, social and education ———— — — — 1—1
Total 16 22 6 1 6 8 1 6 14 80
“Others”refers to CFPR, DEA, DEMATEL, FDEMATEL, PROMETHEE, MACBETH, MULTIMOORA, Fuzzy MULTIMOORA, TODIM, COPRAS,
and WGA
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1749
In all reviewed papers, various MCDM-based approaches have been applied in numer-
ous application areas for solving following problems: (1) Hazard and associated risk
assessment of manufacturing processes such as aluminum plate manufacturing process,
food production process, general-assembling process of a satellite, steel production pro-
cess, and stone processing; (2) risk assessment of gas power plant, oil storage tank zones,
underground coal mines, hot and humid environments, offshore wells and hydropower
stations related to energy; (3) construction risk analysis in hydropower plants, universi-
ties, crane operations, pin jig work unit of shipbuilding and metro systems; (4) risk
assessment on reactor units and chemical tanker operations related to chemistry and bio-
chemistry; (5) transportation risk analysis in railways, dry port-seaport systems, subways,
cargo vessels, shipyards, oil/chemical tanker ships and cargo ships; (6) environmental
risk assessment in dams, protected areas, water conveyance tunnels, and lake basins; (7)
risk assessment of healthcare facilities and processes in hospitals and (8) risk assessment
of university research laboratories.
In the reviewed papers, singular or hybrid MCDM/fuzzy MCDM based approaches
are proposed. When all are investigated, it is concluded that AHP and FAHP methods
are mostly utilized as a single method or combined with traditional risk assessment
methodssuchasFine–Kinney,riskmatrix,FMEA,HAZOP,FTA,HEART,HAFCS,
and check-list. On the contrary, TOPSIS and FTOPSIS methods are hybridized with
AHP, FAHP, entropy, and Delphi since these are preferred in order to assign risk
parameters’weights. In VIKOR and FVIKOR based approaches, the trend is similar.
They are hybridized with FAHP models for weighting risk parameters in the risk
assessment problems.
4.4. Distribution of papers by risk parameters/factors
In risk assessment studies, researchers use quantitative risk relations in order to priori-
tize the hazards/hazardous situations. These relations contain various parameters/fac-
tors. In this review study, we categorize risk parameters/factors under the following five
classes: Papers with 2 parameters (W2P), papers with 3 parameters (W3P), papers with
4 parameters (W4P), papers with 5 parameters (W5P) and others. A list of guide risk
parameters and their citations applied in MCDM-based risk assessment studies is pre-
sented in Table 9.
From the distribution of studies in terms of risk parameter/factor classes as stated in
Figure 5, it is inferred that: The W3P is the most frequently used risk parameter class among
five classes (excluding Others and N/A classes) with a rate of 34% (nD27). It is followed by
W2P, W4P, and W5P classes. The class of Others includes (1) work, environment, and
worker factors (Ilangkumaran et al.2015; Zheng et al.2012), (2) organizational, personal,
job related and environmental factors (Tian and Yan 2013;Da
gdeviren and Y€
uksel 2008),
economic and financial risk, planning risk, contractual and legal risk, design risk, geological
risk and construction risk (Kuo and Lu 2013; Zou and Lee 2010) and so on. The class of N/A
represents studies without any relating risk parameters widely used by researchers in the
knowledge.
More research can be done in terms of four or five risk parameters. Most reviewed papers
on risk assessment are limited to considering sensitivity to non-execution of maintenance
and sensitivity to non-utilization of PPEs.
1750 M. GUL
4.5. Overall assessment on current state, main challenges, and open areas
for improvement
Many authors (Kokang€
ul et al.2017; Akyildiz and Mentes 2017;Anet al.2016; Othman
et al.2016; Gul et al.2017a; Gul and Guneri 2016; Mandal et al. 2015; Meknatjoo and Omid-
vari 2015;
€
Ozfırat 2014; Liu et al.2014; Abdelgawad and Fayek 2010; Grassi et al. 2009; Hu
et al.2009) have highlighted the shortcomings of traditional OHS risk assessment methods
(Fine–Kinney, 5 £5 matrix, FMEA, HAZOP, etc.). These can be summarized as follows:
Table 9. Risk parameters used in MCDM-based risk assessment studies.
Risk parameters/factors Cited by
Likelihood Kokang€
ul et al.(2017); Gul and Guneri (2016); Topuz and van Gestel (2016);
John et al.(2014); Mahdevari et al.(2014); Lavasani et al.(2011); Yucel
et al.(2012)
Probability Gul et al.(2017a); Acuner and Cebi (2016); Rezaee et al.(2017); Dong and
Cooper (2016); Meknatjoo and Omidvari (2015); Mandal et al. (2015);
€
Ozfırat (2014); Ali and Maryam (2014); Ardeshir et al.(2014); Kang et al.
(2014); Liu et al.(2014); Liu et al.(2013); Aminbakhsh et al.(2013); Jozi
et al.(2012); Badri et al.(2012); An et al.(2011); Abdelgawad and Fayek
(2010); Grassi et al.(2009); Gul et al.(2017b); Gul et al.(2017c)
Occurrence Efe et al.(2016); Mentes et al.(2015); Verma and Chaudhri (2014); Chang
et al.(2013); Liu and Tsai (2012); Silvestri et al.(2012); Liu et al.(2012);
Hu et al.(2009); Fattahi and Khalilzadeh (2018); Huang et al.(2017);
Liu et al.(2017); Mohsen and Fereshteh (2017); Ozdemir et al.(2017);
Wang et al.(2017)
Severity Acuner and Cebi (2016); Efe et al.(2016); Rezaee et al.(2017); Dong and
Cooper (2016); Gul and Guneri (2016); Mandal et al.(2015); Mentes et al.
(2015);
€
Ozfırat (2014); John et al.(2014); Liu et al.(2014); Ardeshir et al.
(2014); Liu et al.(2013); Chang et al.(2013); Aminbakhsh et al.(2013);
Liu and Tsai (2012); Jozi et al.(2012); Silvestri et al.(2012); Liu et al.
(2012); An et al.(2011); Yucel et al.(2012); Lavasani et al.(2011); Hu
et al.(2009); Braglia et al.(2003); Fattahi and Khalilzadeh (2018); Huang
et al.(2017); Liu et al.(2017); Mohsen and Fereshteh (2017); Ozdemir
et al.(2017); Wang et al.(2017)
Consequence Kokang€
ul et al.(2017); Meknatjoo and Omidvari (2015); Kang et al.(2014);
Mahdevari et al.(2014); Verma and Chaudhri (2014); Fera and
Macchiaroli (2010); Arslan (2009); Gul et al.(2017b); Gul et al.(2017c)
Magnitude Gul et al.(2017a); Aminbakhsh et al.(2013); Grassi et al.(2009)
Frequency An et al.(2011); Arslan (2009); Gul et al.(2017b); Gul et al.(2017c);
Carpitella et al.(2018)
Exposure Kokang€
ul et al.(2017); Meknatjoo and Omidvari (2015); Verma and
Chaudhri (2014)
Detection Efe et al.(2016); Rezaee et al. (2017); Mandal et al.(2015);
€
Ozfırat (2014);
Liu et al.(2014); Liu et al.(2013); Chang et al. (2013); Silvestri et al.
(2012); Liu et al.(2012); Abdelgawad and Fayek (2010); Hu et al.(2009);
Fattahi and Khalilzadeh (2018); Huang et al. (2017); Liu et al.(2017);
Mohsen and Fereshteh (2017); Ozdemir et al.(2017); Wang et al.(2017)
Undetectability Gul et al.(2017a); Liu and Tsai (2012); Grassi et al.(2009); Braglia et al.
(2003)
Sensitivity to non-execution of maintenance Gul et al.(2017a); Grassi et al.(2009)
Sensitivity to non-utilization of PPE Gul et al.(2017a); Grassi et al.(2009)
Intensity Ali and Maryam (2014)
Impact Badri et al.(2012); Abdelgawad and Fayek (2010)
Vulnerability Jozi et al.(2012)
Worsening Liu et al.(2013)
Toxic effect Topuz and van Gestel (2016)
Chance of failure Braglia et al.(2003)
Frequency of green component Hu et al.(2009)
Failure probability Yazdi (2017); Yazdi and Kabir (2017)
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1751
(1) Traditional methods mostly need numerical data in their risk assessment process. In
some situations, it may be difficult to achieve numerical data. In such cases, expressing
the risks verbally based on decision-maker’s opinions and judgments rather than
numerical data can be possible by applying risk assessment approaches with MCDM
or fuzzy based MCDM.
(2) Among the abovementioned MCDM methods, (F)AHP or (F)ANP are usually pre-
ferred to assign weights to risk parameters used to overcome shortcomings of a crisp
risk parameter calculation and the inconsistency in decision-making. Unlike tradi-
tional OHS risk assessment methods, decision-makers assign parameter weights by
fuzzy linguistic scales and pairwise comparison style (F)AHP or (F)ANP.
(3) In traditional risk assessment methods, assigning of different weights for the risk
parameters (which applies to all classes: W2P, W3P, W4P, and W5P) is not possible.
To solve this problem, researchers apply (F)AHP, (F)ANP, entropy method and (F)
DEMATEL methods.
(4) While prioritizing hazards with traditional methods, a controversial risk value calcula-
tion with completely different meanings may be obtained. That is, hazards with high
probability and low severity may be classified at the same level as hazards with low
probability and high severity. To overcome this, a group decision-making process can
be activated in assessing risks by using linguistic terms and under full consensus. To
this end, (F)TOPSIS, (F)VIKOR, and other MCDM-based risk assessment approaches
are used efficiently.
(5) Another limitation is regarding insufficiency of risk parameters/factors. Number of
the MCDM-based risk assessment studies using parameters over three is indeed less.
Ergonomic factors in terms of workers and worksites are mostly neglected by the
researchers. Therefore, it can be possible to develop a complete risk assessment tool
by taking into account more parameters and producing a very suitable final rank of
hazards.
(6) Non-inclusion of a sensitivity analysis as part of the MCDM-based risk assessment
process is a serious limitation through most of the reviewed papers. Sensitivity analysis
presents the flexibility for the analyst to review the risk parameter weights in assessing
Figure 5. Distribution of studies in terms of risk parameter/factor classes.
1752 M. GUL
hazards. This will directly aid in determining risk priorities. Execution of a sensitivity
analysis can provide validity of the proposed approach (Goerlandt et al.2017).
Having said that, MCDM-based risk assessment area is still obviously non-saturating and
expanding day by day, the following future directions being summarized as follows:
(1) This review study highlights that most of the studies related to MCDM-based risk
assessment approaches is being done in manufacturing, transportation and supply
chain, construction, and energy. Natural resources, environment, chemistry, bio-
chemistry, health, safety and medicine, and policy, social and education have not
been drawn attention enough to significant extent regarding development of
approaches for risk assessment. Moreover, implementation of MCDM-based risk
assessment approaches have not been yet adapted to the business management,
information technology, financial management, and agriculture. However, these
approaches are considered as more sophisticated, robust, and generalized (Verma
and Chaudhri 2016).
(2) As a result of abovementioned shortcomings of traditional risk assessment methods,
approaches which can reflect the human reasoning process and ambiguity of the envi-
ronment are kept in the forefront. Traditional methods are incapable of evaluating the
OHS performance effectively in any industry. When a comprehensive insight is
ensured regarding MCDM-based approaches in OHS risk assessment and manage-
ment, it can be extended considering fuzzy extensions related studies, development of
any new aggregation functions, and stochastic nature of MCDM concept. If any poten-
tial difficultness in capturing the decision-maker’s judgment with respect to the risk
parameters using a single set of fuzzy linguistic terms has been emerged, it can be con-
sidered the usage of various versions of fuzzy sets. Up to now, little attention has been
paid to the MCDM-based approaches dealing with hesitant, intuitionistic, interval
type-2 and stochastic fuzzy sets in assessing risks.
(3) It is also shown that most of the studies related to MCDM-based risk assessment
approaches are applied by an integration of alternative auxiliary tool. With increase in
complexity of manufacturing and service systems, it is difficult to implement a single
method enough to take into account evaluation of every possible risks. Therefore, using
hybrid methods can help the decision-makers to carry out an efficient assessment serv-
ing their purposes.
(4) More attempts are essential to suggest response policy, risk allocation, and risk residual
assessment. Most reviewed papers on MCDM-based risk assessment are limited to
analyzing the results for the risk residuals. We found limited number of studies on risk
assessment with response policies and coherent control measures in managing risks.
Increase of studies in this direction would allow researchers to gain experience for the
management in any particular risk decision process.
(5) In most of the reviewed papers, risk scores associated with hazards are provided with-
out considering the group decision-making rationale. It is assigned equal weights to all
analysts. This may cause inconsistency in decision-making processes. In order to pre-
vent this inconsistency, incorporation of each analyst’s experience level should be con-
sidered during risk assessment.
(6) There is an actual and serious gap in developing decision support systems and specific
software to MCDM-based risk assessment.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 1753
5. Concluding remarks
OHS concerns the science of the anticipation, recognition, evaluation, and control of hazards
arising in or from the workplace that could impair the health and well-being of workers and
taking into account the possible consequences on the environment. As one of the most cru-
cial processes of OHS, risk assessment has emerged as an important stage identifying sources
of risk and determining control measures. MCDM methods are widely applied for risk
assessment as quantitative tools and provided an understanding of the process of risk assess-
ment in hazardous industries. The current study reveals MCDM methods’availability and
practicability to the literature regarding the OHS risk assessment. Generally, occupational
health and workplace safety for the companies operating in risky industries like manufactur-
ing, construction, energy, transportation, and maritime sectors are vital because they are
directly related with the workers’health and life. Thus, an OHS risk assessment should be
implemented by the companies in order to control their risks and improve their safety
performance.
Since capability of solving real world problems with multiple, conflicting, and incom-
mensurate criteria and taking into consideration human decision-making, MCDM and
fuzzy MCDM based approaches are often applied to OHS risk assessment problems in
various sectors. Although traditional risk assessment methods involve a number of
shortcomings, these approaches remain in the foreground and very popular. Their pop-
ularity is enriched by their flexibility to be hybridized with other tools and their sim-
plicity of implementation. By virtue of plenty of scientificpapersusingMCDM-based
approaches in risk assessment knowledge, and as of the time of writing there is no crit-
ical literature review, we perform such a literature review in this article. With this
review study, we aim to uncover the recent trends of MCDM-based risk assessment
approaches and applications over the last 14 years. This includes the distribution of
studies in terms of year of publication, source, application area, methods used, main
objective, sensitivity analysis, and risk parameters class.
We review, classify, and make discussion about a total of 80 papers published in interna-
tional high cited journals between 2003 and 2017. A classification under eight application
areas and by the points of publication trend, published journal, risk parameters/factors, and
tools used is carried out. Results of the literature review show that: (1) Usage of MCDM-
based approaches in the risk assessment knowledge is obviously following an increasing
trend. (2) Safety Science has the most publications on MCDM-based risk assessment
approaches with 26%. (3) The FAHP-based approaches play a dominant role among all
approaches with a rate of 28%. (4) Manufacturing is the area where most risk assessment
studies are carried out and constitutes nearly more than a quarter of the total papers by 27%.
(5) Researchers mostly prefer risk parameters/factors class which have three parameters
with 34%.
This literature review study has some limitations. The first limitation is that the data of 80
papers are gathered from high-cited journals of six important databases. The study does not
cover conference proceedings, thesis, and book chapters. Second limitation concerns the lan-
guages of the papers. We did not include any papers written in a language other than
English.
In future works, the researchers should continue to propose different MCDM-based
approaches in order to apply for assessing risks in various sectors. Hence, the number
1754 M. GUL
of applications and approaches related with MCDM and fuzzy MCDM based risk
assessment approaches is being expected to rise. Methods such as VIKOR, PROME-
THEE, ELECTRE, and DEMATEL remain superior methods in risk assessment and
management due to their flexibility. Also, the integration of analyst’s experience level,
inclusion of the sensitivity analysis, decision support system or software based risk
assessment proposals in MCDM-based risk assessment applications should be consid-
ered for future works.
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