Safety risk assessment using analytic hierarchy process (AHP) during planning and budgeting of construction projects

This paper presents a safety risk assessment framework based on the theory of cost of safety (COS) model and the analytic hierarchy process (AHP) for prioritization of safety risks in construction projects to create a rational budget and to set realistic goals without compromising safety.

Safety risk assessment using analytic hierarchy process (AHP) during
planning and budgeting of construction projects
Saman Aminbakhsh,Murat Gunduz⁎, Rifat Sonmez
Department of Civil Engineering,Middle East Technical University,06800 Ankara,Turkey
a b s t r a c ta r t i c l e i n f o
Article history:
Received 5 October 2012
Received in revised form 1 May 2013
Accepted 22 May 2013
Available online 6 June 2013
Keywords:
Occupational health and safety
Analytic hierarchy process
Risk assessment
Finance
Prioritization
Introduction: The inherent and unique risks on construction projects quite often present key challenges to
contractors.Health and safety risks are among the most significant risks in construction projects since the
construction industry is characterized by a relatively high injury and death rate compared to other industrie
In construction project management, safety risk assessment is an important step toward identifying potenti
hazards and evaluating the risks associated with the hazards.Adequate prioritization of safety risks during
risk assessment is crucial for planning,budgeting,and management of safety related risks.Method: In this
paper,a safety risk assessment framework is presented based on the theory of cost of safety (COS) model
and the analytic hierarchy process (AHP).The main contribution of the proposed framework is thatit
presents a robust method for prioritization of safety risks in construction projects to create a rational budge
and to set realistic goals without compromising safety. The impact to the industry: The framework provides
decision toolfor the decision makers to determine the adequate accident/injury prevention investments
while considering the funding limits. The proposed safety risk framework is illustrated using a real-life con-
struction project and the advantages and limitations of the framework are discussed.
© 2013 National Safety Council and Elsevier Ltd.All rights reserved.
1. Introduction
Risk managementhas been studied extensively in construction
project management in recent years due to its practical importance. In
today's world, where changes rapidly take place with underlying immi-
nent risks, the prerequisite for survival is to have profound knowledge
of the environment and to be capable of making flawless decisions.
The construction industry is recognized to be highly prone to risks
and is characterized to be very complex,dynamic,and unique where
uncertainties arise from various sources.Along with being highly
risky, construction projects engage firm financing to bear the direct
and the indirect costs. These costs include charges associated with var-
ious aspects of construction processes, such as managements of safety
and risk.
Numerous methods have been proposed to assist contractors and
project managers in selection and management of projects.Applica-
tion of these methods enables project managers to avoid potential
problems.Occupationalhealth and safety problems (e.g.,falling of
materials or people from heights,stepping on objects,injuries by
hand tools, explosions,electricalaccidents) have been one ofthe
major challenges in the construction industry.Within this context,
safety risk assessmenthas become a very importanttopic in the
construction project management in recent years.
A novel framework is proposed in this paper to facilitate the safety
risk assessmentprocess.The proposed method is intended to aid
decision makers during evaluation of the impacts of different safety
risk items.In the framework,the safety risk items are prioritized by
the experts by means of the analytic hierarchy process (AHP).This
framework assists project managers in planning, budgeting, and man-
agement of safety related risks.The proposed method is illustrated
using a case project.
The remainder of the paper is organized as follows: Section 2 is
devoted to the literature review and cost of safety (COS) model,and
background on AHP is presented in Section 3.The proposed frame-
work is described in Section 4 and a case study is presented in
Section 5. Finally, concluding remarks are made in Section 6.
2. Literature review
Numerous techniques have been proposed for risk analysis and as-
sessment ranging from simple classical methods to fuzzy approaches.
Howard and Matheson (1981) used influence diagram method for
risk analysis.Sensitivity analysis technique was adopted by Norris
(1992) to forecast the effect of variation of a single independent var-
iable on the dependent variable.Monte Carlo simulation (PMBoK,
2004) was also suggested to assess concurrent change in multiple
independent variables.Decision analysis bearing decision matrices
and decision trees (PMBoK,2004) along with multicriteria decision
making techniques such as the simple multiattribute rating technique
(Von Winterfeldt & Edwards, 1986) and the analytic hierarchy
Journal of Safety Research 46 (2013) 99–105
⁎ Corresponding author.
E-mail addresses: [e-mail] (S.Aminbakhsh),[e-mail]
(M. Gunduz), [e-mail] (R.Sonmez).
0022-4375/$ – see front matter © 2013 National Safety Council and Elsevier Ltd.All rights reserved.
http://dx.doi.org/10.1016/j.jsr.2013.05.003
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process (AHP; Saaty,1990) were used to facilitate making decisions
under risky or uncertain situations.
Occupational health and safety (OHS) risk is defined as the signif-
icance of a hazard in terms of the probability and severity of an injury/
illness that varies from one industry to another. The term ‘risk’ was de-
fined by OHSAS as a combination ofthe probability and the conse-
quences ofthe occurrence ofa specified dangerous event(OHSAS
Project Group,2007).Woodruff (2005) considered risk as the chance
that someone or something that is valuated will be adversely affected
by the hazard. The construction industry is characterized by relatively
high fatal and non-fatal injuries compared to other industries.Pinto,
Nunes,and Ribeiro (2011) indicated that occupationalinjuries and
illnesses not only affect safety and health,but also impact economics
because ofhigh costs related with work injuries.When considered
within the context ofconstruction projects,the injuries account for
7.9–15% of the cost of non-residentialprojects (Everett & Frank,
1996).Hence,proper implementation of safety risk assessment tech-
niques is important to promote project success.
Historical data were used in numerous studies to develop OHS risk
models.Gürcanliand Müngen (2009) and Pinto,Nunes,and Ribeiro
(2010) proposed qualitative models to conduct health and safety risk
assessmentbased on fuzzy logic approach.Gürcanli and Müngen
(2009) dealt with uncertain and insufficient data through adoption of
the subjective judgments ofexperts,and using the existing safety
level of a construction project.
A substantial part of safety literature focused on identifying and
describing various methods forimproving occupationalsafety on
site. Hallowell (2008) developed and validated a formalmethod to
evaluate construction safety risk. Hallowell's (2008) method assumed
that every construction activity is associated with specific safety risks
and that each safety program is able to mitigate a portion of these
risks. Fung, Tam, Lo, and Lu (2010) attempted to improve the system-
atic risk assessment approach by introducing procedures to check the
reliability of the decisions made. The severities of the accidents were
decided using three parameters: man-days lost,fracture or amputa-
tion, and compensation.In measurement of safety risks, Mitropoulos
and Namboodiri (2011) introduced an observational method provid-
ing an objective assessment of an activity's task demand based on
observable risk factors and production variables.Mitropoulos and
Namboodiri (2011) also reflected on the difficulties to perform activ-
ities safely.Hallowell and Gambatese (2009) performed a study to
facilitate determination of the relative effectiveness of safety program
elements through quantification of their individual ability to mitigate
construction safety and health risks using Delphi process.Krallis and
Csontos (2007) examined the internal and external factors that
shape individuals'perception and explored the relevance between
risk perception and safe behavior and suggested possible initiatives
for the organizations.Although the majority of the mentioned risk
management techniques can be applied to any kind of risk assess-
ment process,very few of these studies focused on quantitative
assessment of safety risks in the construction industry.
2.1.Cost of safety (COS) model
Costs of construction injuries can have a substantial impact on the
financial success of construction organizations and may increase the
overall construction costs up to 15% (Everett & Frank,1996).Hence,
investing in accident/injury prevention is important not only for
OHS management but also for decreasing costs of construction pro-
jects.However,there is a point where additional investment yields
diminishing returns and the return on investment becomes negative;
thus,it is crucial for construction organizations to objectively evalu-
ate the cost–benefit of investments in accident/injury prevention
through a robust process.
The cost of safety (COS) model was introduced by Chalos (1992)
to conceptually describe the cost–benefit analysis of accident/injury
prevention.The COS modelis illustrated in Fig.1. According to the
COS model, there is a theoretical equilibrium point at which the
total costs of prevention and detection are equal to the total costs of
injuries,and this point reflects the optimum investment.COS model
also supports the presumption that some levelof safety risk must
be considered as acceptable to maintain an organization's financial
stability. Manuele and Main (2002) support this assumption and
state that there exists some levelof inherent risk in most of the
work processes and that the costs of mitigating such risk can be over-
whelming.Subsequently,in practice,beyond a certain levelof very
high safety, the goal of zero accidents imposes significant investments
in the accident/injury appraisal and prevention; that is, appraisal and
prevention costs must be substantially increased to either achieve
zero accidents or to get close to zero accidents.Consequently,the
COS model aims to provide a structure for the managers to analyze
costs, prepare budgets,and to set realistic goals.
3. The analytic hierarchy process (AHP)
Analytic hierarchy process (AHP) is a structured multi-attribute
decision method (Saaty,1990). The main advantage ofAHP is its
capability to check and reduce the inconsistency of expert judgments.
While reducing bias in the decision making process, this method pro-
vides group decision making through consensus using the geometric
mean of the individual judgments.AHP derives scales of values from
pairwise comparisons in conjunction with ratings and is suitable for
multi-objective,multi-criterion,and multi-actor decisions with any
number of alternatives.AHP involves assessing scales rather than
measures; hence,it is capable of modeling situations that lack mea-
sures (e.g.,modeling risk and uncertainty). AHP is comprised of
three main principles: decomposition ofthe structure,comparison
of judgments,and hierarchical composition (or synthesis) of priori-
ties. Decomposing a decision problem into its constituent parts facil-
itates building hierarchies of criteria to determine the importance of
each criterion.
AHP was used for OHS initially by Freivalds (1987) and Henderson
and Dutta (1992).Padma and Balasubramanie (2009) used AHP to
develop a decision aid system in order to rank risk factors associated
with the occurrence of musculoskeletal problems in the shoulder and
neck. AHP was also adopted by Zhang, Zhan, and Tan (2009) to com-
pare risk factors associated with human error and with the causes of
accidents in the maritime transport sector.Kim, Lee,Park, and Lee
(2010) proposed a safety risk assessment methodology considering
the risk influence factors of construction sites using expert surveys
and the AHP. Badri, Nadeau, and Gbodossou (2012) proposed a proce-
dure for evaluation ofthe OHS risks based upon the multi-criteria
analysis techniques (e.g., AHP) and expert judgment.
Safety Budget
Level of Safety
Prevention Costs
Injury Costs
Optimal Equilibrium
Point
Fig. 1. COS model.
100 S.Aminbakhsh et al./ Journal of Safety Research 46 (2013) 99–105

3.1.The theoretical background of AHP
In AHP, the decision problem is usually divided into a hierarchy of
sub-problems,each of which can be analyzed independently.The
elements ofthe hierarchy can relate to any aspect ofthe decision
problem. Once the hierarchy is built,a numerical scale is assigned to
each pair of n alternatives (Ai, Aj) by the experts (see Table 1). Numer-
ical scales are attributed by making pairwise comparisons among the
alternatives with respect to their impact on an element placed in a su-
perior level in the hierarchy.The term aijk expresses the individual
preference of expert k regarding alternative Ai compared to alterna-
tive Aj.
Once the overall expert judgments are created and computed
using the geometrical mean (1),they are inserted into the compari-
son matrix D (2):
aij ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
aij1Xaij2X…Xaijn
n
q
ð1Þ
D ¼
a11 a12 … a 1n
a21 a22 … a 2n
… … … …
an1 an2 … a nn
2
6
6
4
3
7
7
5: ð2Þ
Matrix D is a comparison matrix and has the following properties:
aij > 0; aij ¼ 1
aji
; ∀ i where j ¼ 1; 2; …; n: ð3Þ
Matrix D is considered as consistent when its elements meet con-
dition (4) while satisfying condition (3):
aij:ajk ¼ aik; ∀k where i; j ¼ 1; 2; …; n: ð4Þ
The ordering of alternatives is taken as a result of the approxima-
tion of comparison matrix D using matrix P:
P ¼
p11 p12 … p 1n
p21 p22 … p 2n
… … … …
pn1 pn2 … p nn
2
6
6
4
3
7
7
5: ð5Þ
The elements of matrix P are consistent judgments presented in
the form of weight ratios among alternatives:
pij ¼pi
pj
where i; j ¼ 1; 2; …; n: ð6Þ
pi signifies the weights of the alternatives of the order vector p:
p ¼ p1; p2; …; pnð Þ
T: ð7Þ
The standardized order vector after the arithmetic normalization
is obtained as follows:
p ¼ p 1; p2; …; pn
T ð8Þ
where:
pi ¼ pi
∑ n
i¼0pi
: ð9Þ
Saaty (1990) proposed using the maximum eigenvalue method to
determine the judgment matrices as:
D:p ¼ λmaxp ð10Þ
where; λmax is the maximum eigenvalue of matrix D.For a reliable
comparison, it is important to note that the inconsistency of the com-
parison matrix D must be less than 10%,that is,the number of times
condition (4) is not met must be below 10%.According to Saaty
(1990), the consistency ofjudgments can also be evaluated using
the Eq.(11):
Consistency ratio ¼ CR ¼
CI
RC ð11Þ
and,
Consistency index ¼ CI ¼
λmax−n
n−1 : ð12Þ
RC (random consistency index) can be acquired from Table 2.
Since the column(s) of any 1 × 1 or 2 × 2 comparison matrices are
dependent,RC is assumed to be 0.This means division by zero in
Eq. (11) and causes CR to tend toward infinity; that is,matrices of
sizes 1 and 2 are always consistent.
4. AHP in construction safety risk management
Project safety risk assessment is a fundamental component of the
project management since construction projects are prone to diverse
occupational health and safety problems such as falling of materials
or people from heights,electricalaccidents,and so forth.However,
only a few studies have been carried out using the AHP method
along with the safety risk assessment techniques. In previous studies,
the most prevalent topic was the use of AHP throughout the decision
making process for evaluation of the alternatives (viz.: projects, con-
tractors, etc.). Badri et al. (2012) focused on assessment of magnitude
of the OHS risks for the sake of risk ranking; but, there was no explicit
consideration regarding AHP's application from the financial perspec-
tive. On the other hand, the cost of occupational injuries may account
for 15% of overall costs and adequate investments in accident/injury
prevention can affectthe competitiveness ofan organization.Al-
though investing in safety is critical to safety success,there is a
Table 1
AHP scale for combinations.
Numerical scale Definition Verbal explanation
1 Equal significance of the two elements Two elements contribute equally to the property
3 Low significance of one element compared to another Experience and personal assessments favor one element slightly over another
5 Strong significance of one element compared to another Experience and personal assessments favor one element strongly over another
7 Confirmed dominance of one element over another One element is strongly favored and its dominance is borne out in practice
9 Absolute dominance of one element over another The evidence favoring one element over another appears irrefutable
2, 4, 6, and 8 Intermediate values between two neighboring levels The assessment falls between two levels
Reciprocals (1/x) A value attributed when activity i is compared to activity j
becomes the reciprocal when j is compared to i
Table 2
Random consistency (RC) index [n = size of the reciprocal matrix].
n 1 2 3 4 5 6 7 8 9 10
RC 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49
101S.Aminbakhsh et al./ Journal of Safety Research 46 (2013) 99–105

point beyond which additional investment yields diminishing returns
and the return on investment becomes negative,which bears ineffi-
ciency from the financial standpoint. Besides, even though it is within
the scope of any organization to have zero accidents, this goal is rath-
er unachievable in practice due to limits in project budgets.In this
context the COS model presents a theoretical equilibrium point that
reflects the optimum investment on occupational accident/injury
prevention.Hence,cost–benefit analysis for safety investment em-
powers decision makers to ensure low workers' compensation insur-
ance premiums,which is an adequate level of indirect costs to help
achieve competitiveness during the bidding stage.
A safety risk management framework is presented in this paper
for effective management of safety risks.This framework integrates
occupational health and safety into project risk evaluation by using
a multi-criteria comparison technique.The proposed approach uses
the AHP method for the paired comparison of the risk factors allowing
reliable prioritizing of identified risks by inquiring objective judg-
ments.The framework provides a decision tool for determining the
adequate investments for accident/injury prevention. This framework
is developed by integrating the concepts of the COS model along with
the AHP technique.
The framework first divides the decision problem into a hierarchy
of more easily comprehended sub-problems, each of which can be an-
alyzed independently. The elements of the hierarchy are set in accor-
dance with the construction safety risk problems. Once the hierarchy
is built, experts assign a numerical scale to each pair of alternatives by
making pairwise comparison with respectto their impact on the
element placed in the higher level in the hierarchy.A priority index
for each expert's judgment is determined by converting evaluations
of risks into numerical values.Then,using the processed weights of
the AHP, numericalvalues are compared and risk items are priori-
tized. This prioritization of risk items empowers the decision makers
to recognize the most significant and the least significant risk items.
Hence,the project management team can determine the safety risk
items to be invested in while considering the project funding limits.
The proposed framework enables decision makers to create a rational
budget and to set realistic goals for the project without compromising
safety.
5. Application of the proposed framework in a real-life project
The proposed AHP framework was illustrated using a real-life
construction project.First a risk-based hierarchy consisting ofthe
potential risk items threatening the construction safety was prepared
as shown in Fig.2. The hierarchy was constructed comprising three
criteria, each of which was further divided into three sub-levels.
Four reciprocal matrices were constructed to guide the expertin
making pairwise comparisons among the elements of the hierarchy.
The first pairwise comparison was made among the parameters of
the criteria influencing the top levelin the hierarchy.In this level,
various hazards were compared to each other to identify their impact
on the overall construction safety (Fig. 3). In order to ensure the con-
sistency of the judgments in all the reciprocal matrices,consistency
ratios (CRs) were calculated using the largesteigenvalues ofthe
eigenvectors Eqs. (14) to (17).
λmax ¼ 3:038→
yields CI ¼ 0:019
CR ¼ 0:032b10%
: ð14Þ
‘Accident hazard’ was perceived as the most significant risk category
followed by ‘Physical hazard’and ‘Chemical hazard’,respectively.The
same procedure was applied to each of the sub-criteria to determine
their influence on the main criteria. Pairwise comparisons were made
to prioritize sub-criteria placed beneath each criterion in the hierarchy.
For the ‘Accident hazard’ category, ‘Trips & falls’ was identified to bear
more impact than the other two elements. In this category, ‘Electricity
& lighting’was assessed to be more important in comparison to ‘Fire
& explosions’ (Fig. 3).
λmax ¼ 3:009→
yields CI ¼ 0:0045
CR ¼ 0:007b10%
: ð15Þ
In the ‘Physical hazard’category,the elements were ranked from
most significant to least important as ‘Machinery & equipment’,
‘Vibration’,and ‘Temperature’(Fig. 3).
λmax ¼ 3:032→
yields CI ¼ 0:016
CR ¼ 0:027b10%
: ð16Þ
Finally, in the ‘Chemical hazard’ category, the element ‘Neurological’
was perceived as a more hazardous element followed by ‘Burns’and
‘Ventilation’ respectively (Fig. 3).
λmax ¼ 3:010→
yields CI ¼ 0:005
CR ¼ 0:008b10%
: ð17Þ
The normalized weights for each of the elements in the hierarchy
were calculated according to their perceived contribution to an
unsafe situation during the construction phase (Fig.4). The overall
prioritization revealed that ‘Trips & falls’had an overall weight of
0.34, and was perceived as the item with the most significant impact.
Second, third, and fourth significant impacts were identified as
‘Electricity & lighting’,‘Machinery & equipment’,and ‘Fire & explo-
sions’and these items had an overall weight of 0.19,0.18,and 0.10,
respectively.The risk items ‘Vibration’ and ‘Neurological’ranked
lower and had an overall weight of 0.06.The items with the lowest
perceived impact were ‘Burns’,‘Temperature’,and ‘Ventilation’since
these items had an overall weight between 0.02 and 0.03.
The normalized weight for each risk element was used to determine
the severity of risks. The risk item with the highest normalized weight
(‘Trips & falls’) was assigned a severity scale of 5 and the risk items
with the lowest normalized weight(‘Vibration’and ‘Neurological’)
were assigned a severity scale of 1.
The severity values of remaining risk items were determined
according to their normalized weights using linear interpolation as
shown in Table 3. A probability value between 1 and 3 (1 = low,
2 = medium, 3 = high probability) was assigned to each risk item
Construction
Safety
Accident hazard
Trips & Falls
Electricity &
Lighting
Fire &
Explosions
Physical hazard
Machinery &
Equipment
Vibration
Temperature
Chemical
hazard
Ventilation
Burns
Neurological
Fig. 2. Hierarchy of risks affecting construction safety.
102 S.Aminbakhsh et al./ Journal of Safety Research 46 (2013) 99–105

by the expert considering the possibility of occurrence of each risk in
the project. The magnitude of each risk item was calculated by multi-
plying the severity value by the probability value.
The results indicate that with a risk magnitude of15, the item
‘Trips & falls’ requires the most significant investment among the
nine risk items. The risk item ‘Machinery & equipment’ has the
second highest risk with a magnitude of 9.00 followed by the item
‘Electricity & lighting’,which has a magnitude of 6.25. The items
‘Fire & explosions’, ‘Vibration’, and ‘Neurological’ have risk magnitudes
between 3 and 4,and are classified as the risk items with a medium
0.17 0.15 0.18
0.33 0.28 0.27
0.5 0.57 0.55
0.17
0.29
0.54
Weigh
ting
Ventilation
Burns
Neurological
Ventil
ation Burns
Neuro
logica
l
1 1/2 1/3
2 1 1/2
3 2 1
Ventilation
Burns
Neurological
Ventil
ation Burns
Neuro
logica
l
0.72 0.75 0.63
0.18 0.19 0.27
0.1 0.06 0.1
0.7
0.21
0.09
Weigh
ting
Machinery &
Equipment
Vibration
Temperature
Machi
nery
&
Equip
ment
Vibrat
ion
Temp
eratur
e
1 4 7
1/4 1 3
1/7 1/3 1
Machinery &
Equipment
Vibration
Temperature
Machi
nery
&
Equip
ment
Vibrat
ion
Temp
eratur
e
0.55 0.57 0.5
0.27 0.29 0.33
0.18 0.14 0.17
0.54
0.3
0.16
Weigh
ting
Trips & Falls
Electricity &
Lighting
Fire &
Explosions
Trips
&
Falls
Electri
city &
Lighti
ng
Fire &
Explo
sions
1 2 3
1/2 1 2
1/3 1/2 1
Trips & Falls
Electricity &
Lighting
Fire &
Explosions
Trips
&
Falls
Electri
city &
Lighti
ng
Fire &
Explo
sions
0.65 0.69 0.56
0.22 0.23 0.33
0.13 0.08 0.11
0.63
0.26
0.11
Weigh
ting
Accident hazard
Physical hazard
Chemical hazard
Accid
ent
hazard
Physic
al
hazard
Chemi
cal
hazard
1 3 5
1/3 1 3
1/5 1/3 1
Accident hazard
Physical hazard
Chemical hazard
Accid
ent
hazard
Physic
al
hazard
Chemi
cal
hazard
(a)
(b)
(c)
(d)
Fig. 3. Pairwise comparison matrices.
103S.Aminbakhsh et al./ Journal of Safety Research 46 (2013) 99–105

magnitude.Finally the items ‘Burns’,‘Temperature’,and ‘Ventilation’
have risk magnitudes between 1 and 1.38,and are classified as the
risk items with a low magnitude.The risk magnitudes provide crucial
information for the project decision makersduring planning and
budgeting ofaccident/injury prevention investments.Depending on
the project characteristics and funding limits,the project decision
makers may give more priority on investing for the items with higher
risk magnitudes after mandatory accident/injury prevention invest-
ments for all of the categories completed.
6. Conclusions
In this paper, a framework was proposed to assist in safety risk as-
sessment and accident/injury prevention budgeting process; a frame-
work that reduces biased decision making while facilitating consensus
decision making by a group ofdecision makers.In the framework,
AHP was adopted conjointly with the COS theory. The proposed frame-
work was applied to a real-life construction project to illustrate how the
framework can guide the decision makers through safety risk assess-
ment. In the framework, the AHP method served as a tool for checking
and reducing the inconsistencies of safety risk severities assigned by
the expert. The proposed framework decomposed the decision problem
into a hierarchy of more easily comprehended sub-problems that en-
hanced assignment of weights to the criteria and sub-criterions.The
AHP method provided a robustmethod for prioritization of safety
risks,and the COS theory enabled a procedure for creating a rational
budget along with setting realistic goals without compromising safety.
This framework can guide the decision makers to create a realistic
budget for accident/injury prevention through determination of
the major risk items prior to construction phase.After mandatory
Construction
Safety
Accident hazard
Trips & Falls
Electricity &
Lighting
Fire &
Explosions
Physical hazard
Machinery &
Equipment
Vibration
Temperature
Chemical
hazard
Ventilation
Burns
Neurological
0.63 0.26 0.11
0.54
0.3
0.16
0.7
0.21
0.09
0.17
0.29
0.54
0.34 0.18 0.02
0.19 0.06 0.03
0.10 0.02 0.06
Subordinate weighting
Overall weighting
Fig. 4. Magnitude appraisal for safety risk items.
Table 3
Safety risk magnitudes assessed through risk matrix.
Items to be assessed Risk items Probability Severity Magnitude
• Ladders in good condition with proper dimensions and not slippery
• Handrails and mid rails placed to prevent falls
• Building entrance roofing to prevent falls
Trips & falls 3 5.00 15.00
• Scaffolding in good condition with proper dimensions,anchored,and not slippery
• Handrails,mid rails,and toe-boards placed
• Openings protected with handrail,mid rail,and toe board
• Covered and marked floor openings
• Proper barriers placed in excavations
• Excavations protected against collapsing
• Adequate artificial lighting
• Cables and electrical distribution boards in good condition and properly protected
Electricity & lighting 2 3.13 6.25
• Machinery and equipment in proper condition and clean
• No damaged electrical wires with proper footing and support
• No loading above maximum capacity
Machinery & equipment 3 3.00 9.00
• Available fire extinguishers with proper size and type
• Flammable and burnable materials protected
• No smoking near combustible materials
• Marked emergency exits
Fire & explosions 2 2.00 4.00
• Avoidance of hand vibration through less vibrating tools
• Proper maintenance of tools
• Limited exposure time of the of the crew to vibrations
Vibration 2 1.50 3.00
• Trained workers to work safely
• Proper means of rescue
Neurological 2 1.50 3.00
• Proper isolation to prevent penetration of dangerous materials to workplace Burns 1 1.38 1.38
• Hot works (welding,grinding,etc.) conducted with specific safety equipment
• Radiation,high or low temperature, etc.meet the safety regulations and standards
Hot works & temperature 1 1.00 1.00
• Local exhaust ventilation
• Crew wearing respirators,gloves,masks,etc.
• Atmosphere tested,cleaned and ventilated before entrance
Ventilation 1 1.00 1.00
104 S.Aminbakhsh et al./ Journal of Safety Research 46 (2013) 99–105

accident/injury prevention precautions are taken,the risk items can
be financed in accord with their comparative rankings.As for the
case project,more precautions were financed to alleviate hazardous
situations related to more significantrisk items such as ‘Trips &
falls’, ‘Machinery & equipment’, and ‘Electricity & lighting’, compared
to less threatening risk items such as;‘Burns’,‘Temperature’,and
‘Ventilation’.
The proposed framework presents a robust method for prioritization
of safety risks to create a rational budget for accident/injury prevention
during planning and budgeting of construction projects.However,the
framework might require too many pairwise comparisons for large and
complex projects,which may require longer implementation times.
Hence, more research is needed to develop a procedure for accelerating
the pairwise comparison process for large and complex construction
projects.
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Saman Aminbakhsh is a graduate student ofthe Civil Engineering Department at
Middle East Technical University.
Dr. Murat Gunduz is a professor of the Civil Engineering Department at Middle East
TechnicalUniversity.He completed a Master's degree in Construction Engineering
and Management at Georgia Institute of Technology,USA in 1998.He completed his
Ph.D. in the same area at the University ofWisconsin, Madison, USA in 2002. His
Bachelor'sdegree in Civil Engineering was obtained from Middle East Technical
University in 1996.He is an editorial board member of the ASCE Journal of Manage-
ment in Engineering.
Dr. Rifat Sonmez is an associate professor of the CivilEngineering Department at
Middle East TechnicalUniversity.He completed a Master's degree in Construction
Engineering and Management at Iowa State University,USA in 1992.He completed
his Ph.D.in the same area at Iowa State University,USA in 1996.His Bachelor's de-
gree in Civil Engineering was obtained from Middle East TechnicalUniversity in
1990.
105S.Aminbakhsh et al./ Journal of Safety Research 46 (2013) 99–105