Road Safety Risk Assessment

30 Pages·2017·5.49 MB·English

sustainability
Article
Road Safety Risk Assessment: An Analysis of
Transport Policy and Management for Low-, Middle-,
and High-Income Asian Countries
SyyedAdnanRaheelShah1,2,NaveedAhmad1,YongjunShen3,*,AliPirdavani2,4 ID,
MuhammadAamirBasheer2andTomBrijs2 ID
1 TaxilaInstituteofTransportationEngineering,DepartmentofCivilEngineering,
UniversityofEngineering&Technology,Taxila47050,Pakistan;[email protected]
2 TransportationResearchInstitute(IMOB),HasseltUniversity,Agoralaan,B-3590Diepenbeek,Belgium;
[email protected](A.P.);[email protected](M.A.B.);[email protected](T.B.)
3 SchoolofTransportation,SoutheastUniversity,Sipailou2,Nanjing210096,China
4 FacultyofEngineeringTechnology,HasseltUniversity,Agoralaan,B-3590Diepenbeek,Belgium
* Correspondence:[email protected];[email protected];Tel.:[phone]
Received:18December2017;Accepted:22January2018;Published:2February2018
Abstract: Roadsafetyassessmenthasplayedacrucialroleinthetheoryandpracticeoftransport
managementsystems. ThispaperfocusesonriskevaluationintheAsianregionbyexploringthe
interactionbetweenroadsafetyriskandinfluencingfactors. Inthefirststage,adataenvelopment
analysis(DEA)methodisappliedtocalculateandranktheroadsafetyrisklevelsofAsiancountries.
Inthesecondstage,astructuralequationmodel(SEM)withlatentvariablesisappliedtoanalyze
theinteractionbetweentheroadsafetyrisklevelandthelatentvariables,measuredbysixobserved
performanceindicators,i.e.,financialimpact,institutionalframework,infrastructureandmobility,
legislationandpolicy,vehicularroadusers,andtraumamanagement. Finally,thispaperillustrates
theapplicabilityofthisDEA-SEMapproachforroadsafetyperformanceanalysis.
Keywords:riskanalysis;safety;accidents;GIS;dataenvelopmentanalysis;structuralequationmodel
1. Introduction
Roadtrafficaccidentsareoneofthemostcriticalproblemsforhumanlife. Despitewidespread
measuresbeingusedtocontrolandminimizethisproblem,roadtrafficaccidentsarefacingagrowing
trend,daybyday. AccordingtotheWorldHealthOrganization(WHO)reportonroadsafetyfor2015,
roadtrafficinjuriescausemorethan1.25milliondeathseachyearandhaveanenormouseffecton
humanlifeanddevelopment[1,2]. Morespecifically,theseeventsarethemajorcauseofdeathamong
young people aged between 15 and 29 years [3]. The cost associated with deaths and injuries is
approximately3%oftheGDPinlow-andmiddle-incomecountries. Inspiteofthishugehumanand
economicloss,actionstofightthisglobalchallengearestillinsufficient[4,5].
Addressing the preventable problem of inadequate road safety requires the dedicated
action of multiple ministries, most notably law, planning, transport, education, public
information,andhealth. Therangeofmeasurestoensureroadsafetyincludesimproving
the built environment (e.g., safer road design, regulating sidewalks and traffic lights,
introducingsafebicyclelanes),lawenforcementandeducationtoincreaseseatbeltuseand
helmet wearing while reducing speeding and drink driving, better vehicle standards,
and improved post-crash response. Road safety measures that provide safer, more
sustainable public transport options are also particularly promising and can support
synergiesbetweenhealth,transportandcarbonemissionreductiontargets[6].
Sustainability2018,10,389;doi:10.3390/su10020389 www.mdpi.com/journal/sustainability
Sustainability 2018, 10, x FOR PEER REVIEW 2 of 30
Sustaipnaubibliltiyc2 t0r1a8n,1s0p,o38r9t options are also particularly promising and can support synergies between2 of30
health, transport and carbon emission reduction targets. [6]
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Figure 1. Comparative analysis of road safety of Low-Income, Middle-Income, and High-Income
Figure1.ComparativeanalysisofroadsafetyofLow-Income,Middle-Income,andHigh-IncomeAsian
Asian Countries (source: World Health Organization (WHO)).
Countries(source:WorldHealthOrganization(WHO)).
To control road traffic accidents, countries have developed and implemented various road safety
Tocontrolroadtrafficaccidents,countrieshavedevelopedandimplementedvariousroadsafety
programs. It is important to note that developed countries have succeeded in controlling traffic
programs. It is important to note that developed countries have succeeded in controlling traffic
accidents. These attainments are the product of making infrastructure safer, improving the safety of
accidents. These attainments are the product of making infrastructure safer, improving the safety
vehicles [9], and executing a number of other interventions recognized to be effective at reducing
ofvehicles[9],andexecutinganumberofotherinterventionsrecognizedtobeeffectiveatreducing
road traffic injuries. Having good quality data to monitor the impact of these efforts is also critical to
roadtrafficinjuries. Havinggoodqualitydatatomonitortheimpactoftheseeffortsisalsocriticalto
signifying their accomplishment. However, developing and less-developed countries have not yet
signifyingtheiraccomplishment. However,developingandless-developedcountrieshavenotyet
achieved this level of success [10,11]. Regular road inspections are an important measure that help to
achievedthislevelofsuccess[10,11]. Regularroadinspectionsareanimportantmeasurethathelpto
ensure the quality of roads and road surfaces [12]. Considering some major factors (i.e., (1)
ensurethequalityofroadsandroadsurfaces[12].Consideringsomemajorfactors(i.e.,(1)institutional
institutional framework; (2) alcohol usage and speeds; (3) protective systems; (4) vehicles; (5)
framework;(2)alcoholusageandspeeds;(3)protectivesystems;(4)vehicles;(5)infrastructureand
infrastructure and roads; and (6) trauma management, etc.), the focus of this study is to statistically
roads;and(6)traumamanagement,etc.),thefocusofthisstudyistostatisticallydevelopandexplore
develop and explore the relationships between the predictors of road traffic fatalities resulting from
therelationshipsbetweenthepredictorsofroadtrafficfatalitiesresultingfromsuchevents.
such events.
Asmoothandgood-conditionedroadpromisesgreaterdrivingandroadsafetyascomparedto
A smooth and good-conditioned road promises greater driving and road safety as compared to
poor-conditionedroadswhichincreasetheprobabilityoftrafficaccidents. Similarly,speedlimitsalso
poor-conditioned roads which increase the probability of traffic accidents. Similarly, speed limits also
playanimportantroleinroadsafety. Restrictingspeedlimitsinhigh-densityareashelpstopromote
play an important role in road safety. Restricting speed limits in high-density areas helps to promote
roadsafety. Therefore,anexplorationoftheassociationofriskandroadsafetymanagementindicators
road safety. Therefore, an exploration of the association of risk and road safety management
willhelpustoscientificallydiscusstherelationshipbetweenthemandwillalsoprovideinsightinto
indicators will help us to scientifically discuss the relationship between them and will also provide
designingeffectiveandefficientroadsafetypolicy. Inthisstudy,weaimtoevaluatetheroadsafety
Sustainability2018,10,389 3of30
risk of low-, middle-, and high-income Asian countries, a region with a combined population of
4.4billion(60%oftheworld),withGDPUS$35.334trillion(Nominal)andUS$57trillionpurchasing
power parity (PPP) [13,14]. Considering the importance of this area, a structural equation model
(SEM-)analysis-basedapproachisalsoappliedtoassessthestatisticalrelationshipbetweentheriskand
thefactorsinvolvedinriskincrement.Theprimeobjectiveofthisstudyistoanalyzetheroadsafetyrisk
situationofAsiancountrieswithreferencetotheireconomiccondition(Low,Middle,orHighLevel).
Furthermore,weevaluatetherelationshipoffinancialimpact,institutionalframework,infrastructure
andmobility,legislationandpolicy,roaduser–vehicularimpact,andtraumamanagementwiththe
risklevelsofAsiancountries.
2. RelatedStudies
2.1. RiskandRoadSafetyAnalysis
Roadsafetyanalysisisrelatedtothesurvivalofhumansonroadsand,duringroadsafetyrisk
evaluation,‘risk’isassociatedwithanumberoffatalitiesandknownasaroadsafetyoutcome. Inthe
fieldofroadsafety,theriskisdefinedas‘theroadsafetyoutcometotheamountofexposure’,asshown
inEquation(1):
RoadSafetyOutcome
Risk= . (1)
Exposure
Researchers have calculated exposure according to the availability of data; some have used
passengerkilometerstraveled,population,numberofregisteredvehicles,etc.[15,16]. Riskassessment
is necessary for road safety performance analysis. Previously, road safety outcome was directly
relatedwithandcalculatedusingthedifferentexposurevariables,buthandlingthemultiplevariables
remained a problem. It is necessary to evaluate the risk and its relationship with the road safety
performanceindicators. TheconceptofSafetyPerformanceIndicators(SPIs)wasdevelopedbythe
EuropeanTransportSafetyCouncil(ETSC)[17].
ThereasonfortheSPIsdevelopmentwastheassumptionthataccidentsandinjuriesareonlythe
tipoftheicebergbecausetheyoccurasthe‘worstcase’resultofunsafeoperationalconditionsinthe
roadtrafficsystem. Thus,SPIscanbedefinedasmeasuresthatarecausallyrelatedtoaccidentsor
injuriesandareusedinadditiontothefiguresaboutaccidentsorinjuries,inordertoindicatesafety
performanceorunderstandtheprocessesthatleadtoaccidents[18].
2.2. DEAandRoadSafetyRiskAnalysis
DataEnvelopmentAnalysis(DEA)isoneofthenonparametricapproachesdevelopedbyChames,
Cooper,andRhodes[19]in1978,andisanestablishedtechniqueinthefieldofroadsafety. Asgiven
in[20],itsmathematicalexpressionisasfollows.
maxE =∑m vx
0 i=1 i i0
s
Subjectto ∑ u y =1
r r0
r=1 (2)
m s
∑ vx − ∑ u y ≤0, j=1,L, n
i ij r rj
i=1 r=1
u ,v ≥0,r=1,L,S, i=1,L,m
r i
Previously, risk evaluation was based on different parameters like public risk and traffic risk.
Thepublicriskwascalculatedonthebasisoftheratiobetweenfatalitiesandpopulation,andtraffic
riskwascalculatedonthebasisofregisteredvehicles. Theprocessofproducingacompositevalueof
theriskmeanvaluewasundertakentoevaluatetherisk,butDEAprovidesanopportunitytocombine
multiplevariables. ThisisbecauseDEAisatechniquethatmaintainsamechanismofmultipleinputs
andmultipleoutputsfortheevaluationofrisk[20]. AconceptualdiagramoftheDEAmodelisshown
inFigure2. Itisalinearprogrammingtechniqueformeasuringtherelativeperformanceofentities
Sustainability 2018, 10, x FOR PEER REVIEW 4 of 30
Sustainability2018,10,389 4of30
multiple inputs and multiple outputs for the evaluation of risk [20]. A conceptual diagram of the DEA
model is shown in Figure 2. It is a linear programming technique for measuring the relative
orunitsofasimilarpattern. CountriesareconsideredtobeDecision-MakingUnits(DMUs)forthe
performance of entities or units of a similar pattern. Countries are considered to be Decision-Making
applicationoftheDEAmodel,andtheriskleveliscalculatedbyapplyingtheroadsafetyoutcome
Units (DMUs) for the application of the DEA model, and the risk level is calculated by applying the
andexposurevariables.
road safety outcome and exposure variables.

FFiigguurree 22. .BBaassicic DDaatata EEnnvveeloloppmmeennt tAAnnaalylyssisis ((DDEEAA)) MMooddeel lCCoonncceeppttuuaall DDiiaaggrraamm. .
In this concept, while calculating risk in the traffic safety field, the lowest level has been
Inthisconcept,whilecalculatingriskinthetrafficsafetyfield,thelowestlevelhasbeenconsidered
considered as the frontier of safety. In the case of efficiency evaluation, Efficiency is calculated by
asthefrontierofsafety. Inthecaseofefficiencyevaluation,Efficiencyiscalculatedbymaximizing
maximizing output and minimizing input, while, for calculating risk, we minimize the output and
outputandminimizinginput,while,forcalculatingrisk,weminimizetheoutputandmaximizethe
maximize the input. The simplest form of calculating Efficiency by DEA is as follows.
input. ThesimplestformofcalculatingEfficiencybyDEAisasfollows.
Efficiency: The basic concept of the DEA Efficiency calculation is as in Equation (3).
Efficiency: ThebasicconceptoftheDEAEfficiencycalculationisasinEquation(3).
(cid:1849)(cid:1857)(cid:1861)(cid:1859)ℎ(cid:1872)(cid:1857)(cid:1856)(cid:1845)(cid:1873)(cid:1865)(cid:1867)(cid:1858)(cid:1841)(cid:1873)(cid:1872)(cid:1868)(cid:1873)(cid:1872) (cid:1839)(cid:1853)(cid:1876)(cid:1861)(cid:1865)(cid:1861)(cid:1878)(cid:1857)(cid:1841)(cid:1873)(cid:1872)(cid:1868)(cid:1873)(cid:1872)
(cid:1831)(cid:1858)(cid:1858)(cid:1861)(cid:1855)(cid:1861)(cid:1857)(cid:1866)(cid:1855)(cid:1877)= = (3)
W(cid:1849)ei(cid:1857)g(cid:1861)(cid:1859)htℎe(cid:1872)d(cid:1857)(cid:1856)S(cid:1845)u(cid:1873)m(cid:1865)o(cid:1867)f(cid:1858)O(cid:1835)(cid:1866)u(cid:1868)t(cid:1873)p(cid:1872)ut (cid:1839)M(cid:1861)(cid:1866)(cid:1861)a(cid:1865)x(cid:1861)i(cid:1878)m(cid:1857)i(cid:1835)z(cid:1866)e(cid:1868)O(cid:1873)(cid:1872)utput
Efficiency = = (3)
WeightedSumof Input Minimize Input
Following the above-explained concept, Risk is calculated as in Equation (4):
Followingtheabove-explainedconcept,RiskiscalculatedasinEquation(4):
Weighted Sum of Output MinimizeOutput RoadSafetyOutcome
Risk= = = . (4)
Weighted Sum of Input MaximizeInput Exposure
WeightedSumofOutput MinimizeOutput RoadSafetyOutcome
Risk= = = . (4)
During the apWpeliicgahttieodn Soufm thoef IDnEpAut modeMl, aLxiinmgoiz esoInftpwuatre was useEdx (pporsougrreamming-based),
which produced the risk values for each Decision-Making Unit (DMU), i.e., Asian country, in our
During the application of the DEA model, Lingo software was used (programming-based),
case. DEA was introduced by researchers in the field of road safety by assigning weights for the
which produced the risk values for each Decision-Making Unit (DMU), i.e., Asian country, in our
construction of composite performance indicators; then, for the evaluation of road safety rankings, a
case. DEA was introduced by researchers in the field of road safety by assigning weights for the
risk value was calculated. That risk value was based on outputs and inputs considering road fatalities
constructionofcompositeperformanceindicators;then,fortheevaluationofroadsafetyrankings,
per million inhabitants [21]. Further, an improvement was tested in the model by testing it along with
ariskvaluewascalculated.Thatriskvaluewasbasedonoutputsandinputsconsideringroadfatalities
six inputs: alcohol, speed, protective systems, infrastructure, vehicles, and trauma management [22].
permillioninhabitants[21]. Further,animprovementwastestedinthemodelbytestingitalongwith
The application of DEA in this manner further encouraged the use of multiple inputs and multiple
sixinputs: alcohol,speed,protectivesystems,infrastructure,vehicles,andtraumamanagement[22].
outputs, and it was then tested with 13 inputs and 4 outputs. The concept of a multiple-layer DEA
TheapplicationofDEAinthismannerfurtherencouragedtheuseofmultipleinputsandmultiple
(MLDEA) was also tested [23]. Previously, the European region was targeted for learning and
outputs,anditwasthentestedwith13inputsand4outputs. Theconceptofamultiple-layerDEA
research due to the availability of detailed data from agencies. Population, passenger kilometers, and
(MLDEA)wasalsotested[23]. Previously,theEuropeanregionwastargetedforlearningandresearch
number of registered cars were considered as inputs, while fatalities were used as outputs. The
duetotheavailabilityofdetaileddatafromagencies. Population,passengerkilometers,andnumber
concept was further strengthened by the application of cross-efficiency for the final risk scores [20].
ofregisteredcarswereconsideredasinputs,whilefatalitieswereusedasoutputs. Theconceptwas
Researchers considered applying this concept at a more local level by using it for Annual Road Safety
furtherstrengthenedbytheapplicationofcross-efficiencyforthefinalriskscores[20]. Researchers
Authority budget allocation and assessing road safety teaching hours’ impact on involvement of
consideredapplyingthisconceptatamorelocallevelbyusingitforAnnualRoadSafetyAuthority
drivers in crashes at the municipality level [24]. At the State level within the country of Brazil, this
budget allocation and assessing road safety teaching hours’ impact on involvement of drivers in
model was calibrated and tested by using mortality rates and fatality rates as outputs. Another
crashesatthemunicipalitylevel[24]. AttheStatelevelwithinthecountryofBrazil,thismodelwas
calibration of this DEA model was performed for 27 police departments in Serbia by following the
calibratedandtestedbyusingmortalityratesandfatalityratesasoutputs. Anothercalibrationofthis
previous concept of public and traffic risk, comparing the road safety performance of 27 sectors [25].
DEAmodelwasperformedfor27policedepartmentsinSerbiabyfollowingthepreviousconceptof

publicandtrafficrisk,comparingtheroadsafetyperformanceof27sectors[25].
SSuussttaaiinnaabbiilliittyy 22001188,, 1100,, 3x8 F9OR PEER REVIEW 55 ooff 3300
2.3. SEM and Road Safety Risk Analysis
2.3. SEMandRoadSafetyRiskAnalysis
Structural Equation Modelling (SEM) is a technique that can handle a large number of
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(ixn1dticilaltxo1r0s )a.nTdh edreevlealtoiopnss aarme roenpgrethseenbtuedil dbsya anrdroawmso. nIng sPtLinSd-SicEaMto,r tshaen adrrdoewves ldopepseanredarebplyr efsaecntoterd inb ya
asorrloitwarsy. IhneaPdLiSn-gS, EsMpe,atkhienagr rtoo wa sddireepcetinodnaabl lryelfaatcitoonrsihnipa. sAolrirtoawrys hpeoaidnitningg, sipne aa ksionlgitatorya bdeiarericntigo naarel
rreelsapteiocntesdh ibpy. aA prrreodwicstipvoei ncotinnngeicntioans oanlidta, riyf tbheearrei nshgoaurled raersipsee catned ocbcyurarepnrceed iocft iav esocloidn nheycptoiothneatincdal,
iefstthaberlieshshmoeunltd, tahreisye caann obcec uinrtreernpcreeotefda asso lciaduhsaylp cootnhneteicctaiolnesst. aAbtl ilsahsmt, ethnet, ethrreoyr ctaenrmbse (ien.tge.r, per7e oterd e8a)s,
craefulseaxlivceolnyn ceocntinoencst.eAd ttola stht,et heenderorgoerntoeurms sco(en.sgt.r,uec7t,o proer8t)r,arye flneoxniv-cellayricfioendn cehctaendgteo wthheenen tdhoeg ceonuorusse
cfoornmstsr uacrte, epsotrimtraaytendo [n2-8c]l.a rifiedchangewhenthecourseformsareestimated[28].

FFiigguurree 33.. AA CCoonncceeppttuuaall SSttrruuccttuurraall PPaatthh MMooddeell..
As per elaboration in Figure 3, a PLS course mannequin comprises of two components:
Structural mannequin (additionally called internal model concerning PLS-SEM), which proves the
Sustainability2018,10,389 6of30
AsperelaborationinFigure3,aPLScoursemannequincomprisesoftwocomponents: Structural
mannequin (additionally called internal model concerning PLS-SEM), which proves the relations
(ways)betweentheconstructs;andtheestimatingdesigns(likewisealludedtoasexternalformsin
PLS-SEM),whichalludestotherelationsbetweenthedevelopsandtheindicatingfactors(rectangles).
Theestimationofthemodeloffersobservationalmeasuresoftherelationsbetweentheconstructs
(basicmodel)andbetweentheindicatorsandconstructs(estimatingmodels)[28]. Theexperimental
measures allow contrasting the auxiliary models and the hypothetically settled reality. Thus, the
wellnessofthehypothesistotheinformationcanberesolved. Thus,utilizingPLS-SEM,theanalysts
relyuponmeasuresthatdemonstratetheprescientlimitofthemodeltojudgeitsquality.Moreprecisely,
theappraisalofthesubsequentauxiliaryandestimatingmodelsinPLS-SEMlaysonanarrangementof
non-parametricevaluationcriteria,utilizingmethodologylikebootstrappingandblindfolding. Inthis
regard,theappraisalofmeasuringmodels(relationsbetweentheindicatorsandconstructs)includes
compositereliability;varianceextracted;indicatorreliability;anddiscriminantvalidityifthereshould
beanoccurrenceofreflexivemodels; andvarianceextracted; collinearityamongstindicators; and
the significance and importance of outer weights in developmental models. The appraisal of the
basicmodel(relationsbetweenconstructs), thenagain, considers: thecoefficientofdetermination
(R2)[28,30,32–35]. Hence,thePLS-SEMapproachnotjustoffersascopeoffavorablecircumstances
inexaminationwiththeoriginalmultivariatemethods,beingexceptionallyadaptableregardingthe
premises and test dimensioning; yet additionally gives a few likenesses OLS Regressions [28,30].
Analysts have recently utilized it in recent publications. Moreover, it has a phase wise structure,
asdiscussedintheintroductionofSEM.IthasprovidedanedgeovertheconventionalOLSanalysis
techniqueswhichhasagapregardingtheoccasionalignoranceofrelationsofXandYvariablesofthe
modelsunderanalysis,andlackofcontrolofdirectandindirectimpactintherelationsdependentand
independentofmoderatingandmediatingeffectsindevelopedmodels. Thesemodelscausepotential
difficultytofullyunderstandtherelationshipsofinterest[28,30].
DuringtheapplicationofSEMinthefieldofroadsafety,“accidentlocation(wheretheaccident
tookplace),pavementtype,horizontalalignment,verticalalignment,vehicletype,driver’sgender,
driver’s age, road surface condition, the day (weekend or weekday), weather condition, day or
nighttimeweremodelledagainstthenumberofdeaths,thenumberofinjuredpersons,thenumber
ofinvolvedvehicles,andthenumberofdamagedvehicles. Findingsendupwiththeanalysisthat
roadfactors,driverfactorsandenvironmentalfactorswerestronglyrelatedtotheaccidentsize”[26].
A similar type of analysis was conducted to evaluate the relationship between accident severity
and accident type [36], between gender, anxiety, depression, reward sensitivity, sensation seeking
propensityandriskydriving[37],betweenpsychologicalsymptoms,sensationseeking,aggression,
dysfunctional drinking habits, aberrant driving behavior, speed and accidents [38]. So SEM is an
establishedtechniqueforcrashdataanalysisforroadsafetyresearch. ThroughtheapplicationofSEM,
wecananalyzethelargedatavariablesrelatedtoroadsafetysituationsinAsiancountries. Analysis
of risk level with reference to road safety indicators will be helpful in understanding road safety
performanceofcountries.
2.4. DEA-SEMCombination
When the DEA is used as a risk analysis tool, Decision Making Units (DMUs) are viewed as
alternativeswhileinputs/outputsareregardedascriteria. InusingDEA,theriskscoreofanyunit
iscalculatedastheminimizationofaratioofweightedoutputstoweightedinputs, subjecttothe
conditionthatallunitsoftheavailabledatasetshouldhavesimilarpatterns[39]. Aftercalculationof
theriskscorewiththehelpofDEA,applicationofSEMtoanalyzetherelationshipoflargedatasets
ofimportantfactorswiththecalculatedriskcanbehelpfulinunderstandinganddecisionmaking
regardingfactorscanbehelpfulinreducingtherisk. AsimilarcombinationofDEAwithSEMhas
beenusedforeducationalanalysisthatpublicexpenditureoneducationasapercentageofGDPisthe
mosteffectiveoutputvariableforliteracylevel[40]. Operatingexpensesisanimperativemanagement
Sustainability2018,10,389 7of30
taskforproductivityimprovementofhotels[39], environmental‘sustainability’ofintensivedairy
farming depends on particular farming systems and circumstances [41]; environmental efficiency
negativelyimpactsonprofitwhileprofitpositivelyimpactsonenvironmentalefficiencyinthetextile
industry[42]. SousingthisDEA-SEMcombinationwillbeanewapplicationinthefieldofroadsafety
andwillbehelpfulfordecisionmaking.
2.5. AdvantagesofUsingDEA-SEMMethod
Since DEA offers some benefits to other approaches such as: (1) DEA is able to handle
multipleinputsandoutputs;(2)DEAdoesnotrequireafunctionalformthatrelatestoinputsand
outputs; (3) DEA optimizes each individual observation and compares them against best practice
observations; (4) DEA can handle inputs and outputs without knowing a price or weights and;
(5)DEAproducesasinglemeasureforeveryDMUthatcanbeeasilycomparedwithotherDMUs,
andalsohavesomelimitationas: (1)DEAonlycalculatesrelativeefficiencymeasures;and(2)Asa
nonparametrictechnique,statisticalhypothesestestsarequitedifficult[43,44]. However,PartialLeast
Square-StructuralEquationModel(PLS-SEM)offersfrequentbenefitstoresearchersasitisefficient
with: (1)abnormaldata;(2)smallsamplesizes;and(3)formativemeasuredconstructs[28]. PLSis
characterizedasatechniquemostsuitablewheretheresearchpurposeisapredictionorexploratory
modeling. Ingeneral,covariance-basedSEMispreferredwhentheresearchpurposeisconfirmatory
model [34,45]. Furthermore, it has the ability to model multiple dependents as well as multiple
independents, ability to handle multicollinearity among the independents, robustness in the face
of data noise and missing data, and creating independent latent variables directly on the basis of
cross-productsinvolvingtheresponsevariable(s),makingforstrongerpredictions. However,“PLSis
lessthansatisfactoryasanexplanatorytechniquebecauseitislowinpowertofilteroutvariablesof
minorcausalimportance”[46].
2.6. ResearchGap
SinceDEAisacommonbenchmarkingtoolforefficiencyandriskevaluation[47,48],ithasbeen
popularwithitsmultistagepropertybutithasshortcomingwithrespecttoitshypothesistesting,
whichreducesitsapplication. Therefore,apowerfultechniqueSEM(PLS)hasbeenjoinedwithDEA
tofillthatgap. Finally,thepredictivepotentialofSEMandtheoptimizationcapacityofDEAperforms
complementaryfeatures,thusenvisioningaprominentmodelingoption[47,48]. Usingthestrengthof
SEMtechniquetodealwithnon-normaldataandformativelymeasuredconstructs[28]willimprove
thedecision-makingprocess.Now,itistimetoapplythisperformanceevaluationDEA-SEMtechnique
inthefieldofroadsafetyforthedecision-makingprocess. Thisisthefirststudyforapplicationof
DEA-SEM(PLS)approachforroadsafetyperformanceanalysisforacasestudyofAsiancountries
which will lead decision makers to better visualize the Riskiest countries and key factors for road
safetyconditionimprovement.
3. ConstructionofHypothesisandModel
Conceptualmodelandhypothesisdevelopmentisoneofthemajortasksforanalyzingtheroad
safety performance and the impact of interrelation of latent contributing variables. Following the
SafetyNet [49], concept of using road safety performance indicators, the detailed hypothesis is
explainedasfollows:
3.1. H1: FinancialImpact→Risk
Economist have also termed loss of human lives as a huge loss of economy under certain
circumstances. Theyhaveexplainedasitdirecteconomiccostsandindirecteconomiccosts. Thevalue
oflifeperseroadsafetyfactoraswell[50]. Thedirectcostincludesmedical,legalemergencyand
propertyrelateddamages,whilesometimegoesonifthesefactorshavecontinuity[51]. Theindirect
economiccostofaccidentsrelatedtothoseservicesandproductswhichareproducedonlybecauseof
Sustainability2018,10,389 8of30
crashoccurrence[52]. StatisticianshaveestimatedthatinthetheAsianESTcountriescrashrelated
costshavebeenabout1.1%ofGDPin2010forfatalitiesand3.6%ofGDPforcrashesin2010only[52].
Soanevaluationoffinancialimpactisnecessarywiththeriskleveloflow,middleandhighincome
Asiancountries.
3.2. H2: InstitutionalFramework→Risk
Institutionalframeworksarethemajorfactors,whicharerelatedtothesafetylevel. Therefore,it
isnecessarytoanalyzetheimpactofrelationshipofpresenceofleadagencytodealwithroadsafety
situations,mechanismofavailabilityoffundinginnationalbudgets,existenceofnationalroadsafety
strategy for funding to implement strategy and fatality reduction targets. A proper framework is
neededtodealwiththeroadsafetysituationandrisklevel[3]. Theworldisfocusingonreducing
traffictoa50%fatalityreductiontarget(fivemillionfatalitiesand50millionseriousinjuries)bytheend
of2020[53]byfollowingaproperinstitutionalframework,sotheimpactofinstitutionalframework
onrisklevelisneededtobeinvestigated[3].
3.3. H3: Infrastructure&Mobility→Risk
Infrastructureandmobilityaredirectlyrelatedtoroadfatalitieswhichisbackedbyastreamlined
roadsafetyauditmechanism,policiesforpromotingwalkingandcyclingandinvestmentinpublic
transport[3]. Forpreventingcrashesorreducingtheirseverity, roadsafetyauditistheprocessas
aneffectiveroadsafetytool[54]. Aroadsafetysystemisdesignedforsafetyofthepublicandtheir
mobility. Usually,roadsafetyauditisnecessaryandarelationofthisfactorwiththerisklevelneedsto
beinvestigated. Roadconditionandmobilityfacilitiesareofmajorconcernforroadsafetyconditions.
3.4. H4: LegislationandPolicy→Risk
Speed limit is one of the major factors of road traffic safety issues [55–57]. The effectiveness
ofspeedrelatedfactorsisrelatedtoenforcementoflimit[15]. Sectorwiseimpactofspeedlimitis
influentialonurbanandruralroadsespeciallyonmotorways. Reducingspeedlimithasasignificant
impact on reducing fatalities and injuries [58]. Importance of protection systems like motorcycle
helmets,seatbeltandchildrestraintlawisalsodirectlyrelatedtotherisklevelofcountries[3,59].
Overall,crashesarealsorelatedtothesemechanismsofprotections.
3.5. H5: Vehicular-RoadUser→Risk
Vehicles are designed for a safer road mobility. Sometimes quality and fitness of vehicles are
compromisedinlow-incomecountries. Roaduser’svehicularcategory,whichisinvolvedinalarge
numberoffatalities,isrelatedtocarandcycleusers. Anotherassumptiontobeinvestigatedisthat
thereisarelationshipbetweenroaduser’svehicularimpactandtherisklevel. Thereisarelationship
betweentypeofvehicleandcrashes[56,59,60],asoccupantsofnewcarsarethreetimeslessinvolved
incrashesthanthoseofoldvehicles[1].
3.6. H6: TraumaManagement→Risk
Trauma management is related to the system responsible for rapid response to the medical
treatmentofinjuredpeopleinthecrashes[17]. Thefacilityoftraumamanagementisconnectedwith
theavailabilityofmedicaltreatmentforthesurvivaloflifeaftercrashes. Especiallyindeveloping
countries,injurycrashesresultinfatalities. Researchershaveconcludedthat50%offatalitiesoccur
duringthecrasheswhileothersarewithinafewhoursofthecrashes[61]. Ifapropermedicalfacility
isavailable,thentherisklevelofthecountrycanbeimprovedbyreducingfatalities. Pharmacareand
medicaltreatments,andintimeavailabilityofmedicalaidandproperhospitalemergencytreatment
asachainprocess,cannotonlysavelivesbutalsodisabilities[62]. Theconceptualmodelisshownin
Figure4.
Sustainability2018,10,389 9of30
Sustainability 2018, 10, x FOR PEER REVIEW 9 of 30
Financial Impact
Institutional Framework
H:1
H:2
Infrastructure & Mobility
H:3
RISK
H:4
Legislation & Policy
H:5
H:6
Vehicular-Road User
Trauma Management

Figure 4. Conceptual Research Model.
Figure4.ConceptualResearchModel.
4. Materials and Methods
4. MaterialsandMethods
4.1. Study Area
4.1. StudyArea
Asia is considered among the largest parts of the world and largest continent of the world with
aAlmsioasti sacpopnrosxidimeraetedlya m4.5o nbgilltiohne ilnahrgaebsittapntasr t(s20o1f6t)h, wehwicohr ladccaonudntlsa rfgore satlmcoonstt i6n0e%n toof ftthhee hwumoralnd with
almopsotpauplaptrioonx iomf tahtee lgylo4b.e5. bAislilaio cnovinerhs aabni taarneats o(f2 4041,567)9,,w00h0 iscqhuaarcec okumn (t1s7,f2o1r2,a0l0m0 omsit2)6, 0a%bouotf 3t0h%e ohfu man
popuElaarttiho’ns tooftatlh leangdlo abreea. Aansdia 8c.7o%v eorfs tahne Eaarertah’osf t4o4ta,5l 7su9r,0fa0c0e saqreuaa. rAesk fmata(l1it7y, 2r1a2te,0s 0o0f tmhei2 S),oaubtho-uEats3t0 %of
Asian Region is 17 per 100,000 population higher than the European Region which is 9.3 (almost half),
Earth’stotallandareaand8.7%oftheEarth’stotalsurfacearea. AsfatalityratesoftheSouth-East
it is necessary to evaluate the road safety situation in this largely populated region. Globally, due to
AsianRegionis17per100,000populationhigherthantheEuropeanRegionwhichis9.3(almosthalf),
road traffic injuries, more than 1.2 million people die each year, and this has a huge impact on human
itisnecessarytoevaluatetheroadsafetysituationinthislargelypopulatedregion. Globally,dueto
life and development. According to the WHO, the majority of the causalities are aged between 15 and
roadtrafficinjuries,morethan1.2millionpeopledieeachyear,andthishasahugeimpactonhuman
29 years, and cost reaches almost 3% of GDP; for low- and middle-income countries it increases up
lifeatno d5%d e[3v]e. lAocpcmorednint.g Atoc tchoer dWiHngO,t o“Tthhee rWiseH inO g,ltohbealm roaajodr tirtayffoicf dtheaethcsa uhassa lbiteieens laarregealyg eddrivbeent wbye en15
andt2h9e yeesacarsla,tainngd dceoastthr etoalcl hoens raolamdos sitn 3l%owo afnGdD mPi;dfdolre-lionwco-maen dcomunidtrdielse—-inpacrotmicuelacroluy nintr ieemseirtgiinncgr eases
uptoec5o%no[m3]ie.sA wchcoerred uinrbgatnoiztahteioWn aHndO ,m“oTtohreizraitsieonin acgcloombaplanroya rdaptirda feficcondoematich sgrhoawsthb”e e[n3].l aSrog, efolyrtyd riven
bythoenee sccoaulnattriinegs odfe Aatshiatno Rlleogniornosa hdasvein bleoewn saenledctmedi dfodrl reo-iandc soamfeetyc aonuanlytrsiies sa—ndp aarreti gcuroluarpleydi none mthee rging
econboamsisie osf winhcoemreeu lervbealn (liozwat,i monidadnled amndo htoigrhiz).a Atioccnoradcicnogm top tahney Wroarpldid Beacnokn, “olmowic-ingcroomwet hec”o[n3o]m. Sieos, forty
are defined as those with a GNI per capita, calculated using the World Bank Atlas method, of $1025
onecountriesofAsianRegionshavebeenselectedforroadsafetyanalysisandaregroupedonthe
or less in 2015; lower middle-income economies are those with a GNI per capita between $1026 and
basisofincomelevel(low,middleandhigh). AccordingtotheWorldBank,“low-incomeeconomies
$4035; upper middle-income economies are those with a GNI per capita between $4036 and $12,475;
aredefinedasthosewithaGNIpercapita,calculatedusingtheWorldBankAtlasmethod,of$1025
high-income economies are those with a GNI per capita of $12,476 or more” [63]. The fatality data
orlessin2015;lowermiddle-incomeeconomiesarethosewithaGNIpercapitabetween$1026and
with reference to income group, population and registered vehicles of the selected forty-one countries
$403a5r;eu sphpowernm ini dthdel eT-aibnlceo 1m. eeconomiesarethosewithaGNIpercapitabetween$4036and$12,475;
high-incomeeconomiesarethosewithaGNIpercapitaof$12,476ormore”[63]. Thefatalitydatawith
referencetToabinlec o1.m Deesgcrrioptuiopn, opf oBpasuicl aRtoioadn Saanfedtyr Degatias tfoerr eAdsiavne Rheicglioens wofithth reefsereelneccet etod Infocormtye- oGnroeucpo. untriesare
shownintChoeunTtaryb le1F.atalities Pop(M) TRV(M) IG Country Fatalities Pop(M) TRV(M) IG
Afghanistan 4734 30.5 0.66 1 Maldives 12 0.3 0.06 2
TabAlzee1rb.aDijaens cripti9o4n3 ofBasi9c.4R oadS1a.1f4e tyDa2t aforMAosnigaonliaR egion5w97i threfer2e.8n cetoI0n.c68o meG2r oup.
Bahrain 107 1.3 0.55 3 Burma 10,809 53.2 4.31 1
Bangladesh 21,316 156.5 2.09 1 Nepal 4713 27.7 1.18 1
Country Fatalities Pop(M) TRV(M) IG Country Fatalities Pop(M) TRV(M) IG
Bhutan 114 0.7 0.07 2 Oman 1881 21.6 5.99 3
AfghanistCaanmbod4ia7 34 2635 30.5 15.1 0.66 2.46 11 PMakiasltdaniv es 25,781 12 182.1 0.3 9.08 0.062 2
AzerbaijanChina 943 26,13679 .4 1385.5 1.14250.14 22 PhMilipopnigneosl ia 10,3795 97 98.3 2.8 7.69 0.682 2
BahrainGeorgia1 07 514 1.3 4.3 0.55 0.95 32 QBatuarrm a 3301 0,809 2.1 53.2 0.65 4.313 1
BangladeshIndia2 1,316207,55115 6.51252.1 2.09159.49 12 SaudiN Aerpabaila 78984 713 28.8 27.7 6.60 1.183 1
BhutanIndonesia1 14 38,2790.7 249.8 0.07104.21 22 SingOapmoraen 1971881 5.4 21.6 0.97 5.993 3
Cambodia 2635 15.1 2.46 1 Pakistan 25,781 182.1 9.08 2
China 26,1367 1385.5 250.14 2 Philippines 10,379 98.3 7.69 2
Georgia 514 4.3 0.95 2 Qatar 330 2.1 0.65 3
Sustainability2018,10,389 10of30
Table1.Cont.
Country Fatalities Pop(M) TRV(M) IG Country Fatalities Pop(M) TRV(M) IG
India 207,551 1252.1 159.49 2 SaudiArabia 7898 28.8 6.60 3
Indonesia 38,279 249.8 104.21 2 Singapore 197 5.4 0.97 3
Iran 24,896 77.4 26.87 2 SriLanka 3691 21.2 5.20 2
Iraq 6826 33.7 4.52 2 Tajikistan 1543 8.2 0.41 1
Sustainability 2018, 10, x FOR PEER REVIEW 10 of 30
Japan 5971 127.1 91.38 3 Thailand 24,237 67 32.48 2
Sustainability 2018, 10, x FOR PEER REVIEW 10 of 30
Jordan 19Ir1an3 247,.8296 771.4. 26 26.87 2 2 TSriim Laonrk-aL este 3691 18821.2 1.51.20 2 0.06 2
Kazakhstan 39IIrr8aaq3n 216486,82.9466 37373..74. 93 246.5.827 2 22 TSarij TiLkuaisnrtakknae y 13564931 6687281.2.2 7405...94210 121 7.94 2
Kuwait J6aI2rpa9aqn 56398.72316 132371..71. 8 4 941..5328 3 32 TuTTahrjkaikimliasnteadnn istan2145,24337 91486.72 53.022..4418 21 0 .85 2
Kyrgyzstan 1JJo2arp2da0ann 15599.17531 172.702. 1.9 6 911.2.368 2 23 TiTmhoariU-laLAnedsEt e 241,82837 102116.71 93.032.0.468 22 2.67 3
Laos KaJz9oa7rkd1hasnta n 31999.81733 176.1.24 . 44 31..9236 2 22 TimTVuorirke-Leteyns atem 6168887 22,417914..19 91107..6.0964 224 0.79 2
Lebanon KaK1z0uawk8h8asitta n 34692.8893 136.13.4 . 68 13..8943 2 32 TurTkmuYreeknmeiys teann 6961847 5248754.2.9 2410.7.48.954 22 1 .20 2
KyKrguywzasitta n 1622290 53..53 01..9864 23 TurkUmAeEni stan 1901241 95..32 20..6875 32
Malaysia Ky7rL1ga2yoz9ss tan 2199272.170 952..753 .82 10..4946 2 22 ViUetAnaE-m 2120,42119 - 991..36 4-20..6779 23 - -
LeLbaaonso n 1907818 49..87 11..6484 22 VYieemtneanm 2522,44189 2941..46 410.2.709 22
MLeablaaynsoina 71102898 249..87 213..6882 22 Yem- en 52-4 8 24- .4 1.-2 0 2-
ForthevisMuaalalyisziaa tion7o12f9 ther2o9a.7d saf2e3.t8y2 dat2a ,GIS-b- asedmap- shave- beenpr- oduce- d. Roadtraffic
For the visualization of the road safety data, GIS-based maps have been produced. Road traffic
fatalitieswithreferencetopopulationareshowninFigure5and,withreferencetoincomegroupare
fataliFtioers twhiet hv irseufaerlieznacteio tno opfo tphuel arotiaodn saarfee styh odwatna ,i nG FISig-buarsee 5d amndap, ws hitahv ree bfeereenn cper otod uincceodm. Re ogardo utrpa affriec
shown,inFigure6.
sfahtoawlitnie, sin w Fiitghu rreef e6r.e nce to population are shown in Figure 5 and, with reference to income group are
shown, in Figure 6.

Figure 5. Road safety of Asia fatalities on the basis of populations within regions.
Figure5.RoadsafetyofAsiafatalitiesonthebasisofpopulationswithinregions.
Figure 5. Road safety of Asia fatalities on the basis of populations within regions.

Figure 6. Road safety of Asia fatalities on the basis of income group within regions.
Figure 6. Road safety of Asia fatalities on the basis of income group within regions.
Figure6.RoadsafetyofAsiafatalitiesonthebasisofincomegroupwithinregions.