anapplicationofanalytichierarchyprocess(ahp)for

Research ArticleAn Application of Analytic Hierarchy Process (AHP) forSustainable Procurement of Construction EquipmentMulticriteria-Based Decision Framework for Malaysia

Muhammad Waris 1 Shrikant Panigrahi2 Abdullah Mengal3 Mujeeb Iqbal Soomro4

Nayyar Hussain Mirjat5 Mehfooz Ullah1 Zarith Sufia Azlan1 and Asadullah Khan 1

1Faculty of Industrial Management Universiti Malaysia Pahang 26300 Gambang Pahang Malaysia2College of Business University of Buraimi Alburaimi PO Box 890 P C512 Oman3Department of Mechanical Engineering Balochistan University of Engineering and Technology Khuzdar 89100Balochistan Pakistan4Department of Mechanical Engineering Mehran University of Engineering amp Technology SZAB Campus KhairpurMirrsquos 66020Sindh Pakistan5Department of Electrical Engineering Mehran University of Engineering and Technology Jamshoro 76062 Pakistan

Correspondence should be addressed to Muhammad Waris warisumpedumy

Received 7 April 2019 Revised 13 August 2019 Accepted 20 August 2019 Published 15 September 2019

Academic Editor Yakov Strelniker

Copyright copy 2019 Muhammad Waris et al )is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Sustainable procurement is an emerging theme in the construction industry across the globe However organizations in theconstruction industry often encounter impediments in improving environmental performance in construction projects especiallyin procurement Besides its other facets procurement of construction equipment is inherited to be capital-intensive and vital formanaging environmental concerns associated with built environment projects In this regard selection criteria in such pro-curement processes are generally supportive of considering cost and engineering specifications as key parameters Howeversustainability apprehensions in todayrsquos Malaysian construction industry have mounted pressure on industry professionals torethink their equipment acquisition strategies )e notion of green or sustainable procurement is still infancy for the Malaysianconstruction industry and facing challenges for embedding it in the current procurement practices )is research aims to addressthese apprehensions by considering six main criteria namely life cycle cost (LCC) performance (P) system capability (SC)operational convenience (OC) environmental impact (EI) and social benefits (SBs) and their 38 subcriteria towards procurementof sustainable construction equipment A multicriteria-based equipment selection framework on the triple bottom line ofsustainability in the context of the Malaysian construction industry has been developed and tested )e application of analyticalhierarchy process (AHP) established the sustainable procurement index with a consistent sensitivity analysis results As such theproposed procurement index shall help decision-makers in the process of the acquisition of sustainable construction equipmentin Malaysia

1 Introduction

)e procurement of construction equipment is a complexand multifaceted process [1] )e main objective in such aprocess is to arrive at the selection of the right equipment forcarrying out scheduled tasks with high efficiency pro-ductivity and economic viability [2] )ese facts are duly

supported in the Malaysian construction industry whereinconstruction equipment selection is termed as a strategicdecision and has a high economic impact on the projectbudget Procurement process is characterised by supplierrsquoscommitment purchase management effective materialdelivery management and efficient bill of quantity [3] )eadvent of technological needs in construction practices

HindawiMathematical Problems in EngineeringVolume 2019 Article ID 6391431 20 pageshttpsdoiorg10115520196391431

demands substantial usage ofmechanized equipment [4] As aresult it is quite complex to make a competitive and bestjudgment during equipment acquisition [5] In addition tojudgment there is a lack of knowledge between industryprofessionals and incompatibility with building componentsleading to higher additional costs and material handling costs[6] A common practice which is adapted for selecting therequired choice is based on comparing available equipmentoptions with the intended tasks Typically such an approach ismeant for taking into account a list of tangible and intangiblefactors such as cost capacity productivity and efficiency [7]In this way an appropriate selection can be carried out onvarying criteria which helps the outcome of the process [8]Earlier Gates and Scarpa [9] have classified the selectionprocedure of earthmoving equipment into four criteria whichinclude based on the spatial relationships soil characteristicscontract provision and logistics A spreadsheet-based modelhas been developed by Chan and Harris [10] for the selectionof construction equipment In their database a detailedtechnical criterion was developed for selecting backhoes andloaders in earthmoving operations However this work ofChan et al [11] focused on material handling equipmentalone Another knowledge-based approach by Haidaret al[12] established that the equipment selection process is afunction of knowledge and its subsequent optimizationthrough genetic algorithms It involves the screening ofprocured equipment from knowledge-based criteria A de-cision support framework for the selection of open-pit miningequipment was also proposed in [13] )is framework wasbased on qualitative and quantitative factors Goldenberg andShapira [14] developed the analytic hierarchy process (AHP)framework which is also based on tangible and intangiblefactors )e tangible factors included technical specificationssite conditions and cost consideration However intangiblefactors are qualitative and include safety considerationcompany policies regarding equipment acquisition marketconditions and environmental constraints )is is the first-ever decision model found in the literature which has takeninto account the soft consideration towards the selection ofconstruction equipment for the building projects

As Malaysia is planning for an increased number ofconstruction projects to meet its infrastructure needs itbecomes crucial for the industry to understand and practicesustainable procurement procedures for reducing the neg-ative environmental impact and hazards Sustainable pro-curement is considered as a key practice of supply chains inmany industrialized countries [15] In such developingeconomies sustainable procurement is considered as a keypractice of supply chains [16] Malaysia is amongst theworldrsquos emerging economies Despite that it has receivedlittle attention in addressing sustainability issues in thesupply chain Works on sustainable procurement have beenperformed in countries such as India [17] South Africa [18]China [19] Saudi Arabia [20] and Brazil [21] Existingstudies on sustainability procurement have been performedparticularly in the developed countries such as UK [22] theUSA [23] and Germany [24] but there is lack of studies intheMalaysian context As a consequence of new governanceMalaysia is poised to work towards sustainability

It is evident from the literature review presented abovethat the equipment selection frameworks and their re-spective criteria have been amply explored in variouscontexts with a diversified scope Most of these studies haveoften considered the techno-economic aspects of equipmentselection rather than environmental and social concerns inthe procurement of the construction equipment As suchthe agenda of sustainability in construction projects havebeen ignored in the entirety In the meantime a new par-adigm of green or sustainable construction emphasizes thatall aspects of the construction process should address thetriple bottom line of sustainability It is therefore em-phasized that the appraisal process of the equipment se-lection must take into account the technical economicenvironmental and social considerations )e rest of thepaper consists of several sections Section 2 is about liter-ature review Section 3 provides details about material andmethods Section 4 elaborates the case study Section 5presents and discusses results Section 6 provides the sta-bility analysis of the results and finally Section 7 concludesthe paper

2 LiteratureReview Sustainable Criteria for theSelection of Construction Equipment

)e concept of sustainability in the equipment selection is aninnovative idea for construction projects )is concept isassociated with several factors such as technical economicenvironment and various social criteria of sustainableconstruction [25] )e fields of sustainable procurement andindustrial sustainability have attracted researchers consid-erably and include topics such as sustainable supply chainmanagement [26] Before taking into account the concept ofsustainability in the construction industry and subsequentlyin the selection of construction equipment it is pertinent tomention that such considerations have already become partand parcel of various modern-day knowledge areas )esustainability concept has origins in the term lsquolsquosustainabledevelopmentrdquo which emerged for the first-ever time in 1987in the Brundtland Commission report of the United Nationsmore commonly known as the United Nations Commissionon Sustainable Development (UNCSD) )e UNCSD sus-tainability framework comprised of social environmentaleconomic and institutional criteria which further com-prised of main and subcriteria )is followed some formalconsideration of the sustainability aspect in various fieldsFor example Mihyeon Jeon and Amekudzi [27] haveaddressed sustainability in the public transportation systemby defining indicators and metrics which emphasized thatconsensus should be developed on the economy environ-ment and social well-being of society while addressing thesustainable trends in transportation Singh et al [25] havealso emphasized that sustainability criteria are not onlysignificant yet are very effective towards the formulation ofstrategy and thus suggested that these criteria are valuable inmaking policy in terms of environment and socio-economicand technological improvements )eir research work fur-ther emphasized that an indicator of sustainable develop-ment should be carefully selected refined and revisited in

2 Mathematical Problems in Engineering

order to maintain its contextual effectiveness In anotherstudy Bradley Guy and Kibert [28] have established thatsustainability criteria provide a systematic approach tomeasure the robustness of a system in a simple and rea-sonable manner

In the construction industry various sustainability cri-teria have been identified in the contemporary literature Forexample Bourdeau [29] had identified economic social andcultural criteria as the key elements of a sustainabilityframework It is emphasized in this study that priorities ofthe sustainability criteria have geographical diversity andthese may as such vary in a different locations and differentcontexts Singhet al [30] have also identified the sustain-ability criteria for a decision support system for the devel-opment of the water utilities in the UK constructionindustry)is study identified two key factors which supportthe identification of the sustainability criteria As such thisstudy emphasis that application of the set of criteria and itspracticability under the agenda of sustainability are twomain concerns Furthermore Akadiri and Olomolaiye [31]have proposed comprehensive guidelines for the identifi-cation of the sustainability criteria for the selection ofsustainable materials According to this study sustainabilitycriteria should be comprehensive and it must cover fourbasic categories ie economic environmental social andtechnical aspects of sustainable construction In addition tothis the selected criteria should be applicable to a broadrange of options with transparency and practicability formeaningful analysis [30 32]

)e above presented precise literature review illustratesthat the majority of the researchers have a common opinionon the fundamental aspects of sustainability Economicenvironmental social and technical aspects are judged askey sustainability criteria )ese findings lay a foundation asa guiding principle for making selection criteria for theprocurement of sustainable construction equipment In thiscontext Waris et al [4] have developed broad-based ef-fective and meaningful criteria which encapsulate thefundamental aspects of sustainability in the selection ofconstruction equipment )eir research has identified sixlatent factors (herewith termed as main criteria) associatedwith the thirty-eight subfactors (herewith termed as sub-criteria) Table 1 illustrates the six dimensions of their cri-teriarsquos which are considered significant and used for thedevelopment of a sustainability index towards the selectionof sustainable construction equipment

21 Framework for Sustainable Procurement Waris et al [4]derived sustainable criteria and subcriteria from the rankingand factor analysis of the expert opinions from theMalaysian construction industry as such it is important tobenchmark the scope of the criteria with the standardequipment selection guidelines In this regard ISO-10987[106] standard for the earthmoving machinery sustainablywas considered as a point of reference for the consideredsustainable criteria )is standard has set out generalprinciples for addressing the sustainability of the earth-moving machinery and played an important role by

establishing sustainable terminologies and identifying sig-nificant sustainability factors for earthmoving machineryAccording to this standard potential sustainability issuesrelevant to the selection of earthmoving machines includethe following but not limited to

(i) Greenhouse gascarbon emissions(ii) Energy use(iii) General processes during design manufacture

machine life and end of life(iv) Management system for sustainability communi-

cation training and development(v) Training for machine use worksite managers

operators and maintenance

Table 1 Indicators of sustainable criteria for constructionequipment

Sustainable criteria ReferencesLife cycle costing

Ownership cost [33ndash37]Operational cost [38ndash40]

PerformanceEquipment capacity [41ndash44]Equipment reliability [44ndash47]Equipment efficiency [47ndash50]Equipment operational life [51ndash53]Equipment productivity [54ndash56]Fuel efficiency [35 57]Equipment age [58 59]

System capabilityImplement system [60 61]Traction system [62ndash64]Power train system [65 66]Control and information system [67ndash69]Equipment standardization [70 71]

Operational governanceSite operating condition [72 73]Job and operational requirement [74 75]Spare parts availability [76 77]Repair and maintenance [36 78]Veracity of equipment [79 80]Haul road conditions [81 82]

Environmental impactsGHG emissions [35 83]Fossil fuel consumptions [84 85]Energy saving [86 87]Noise control [88 89]Vibration control [4 90]Quantity of black smoke emission [91 92]Oil and lube leakage control [93]Use of sustainable fuels [94]Biodegradable lubricant and hydraulic oil [95]Environmental statutory compliance [93]

Social benefitAvailability of local skilled operators [93]Operator health issues [93 96]Safety features [97 98]Operational proficiency [99 100]Training for operators [101 102]Relationship with dealers [103 104]Operator view and comfort [93 105]

Mathematical Problems in Engineering 3

(vi) Social aspect health safety comfort andergonomics

(vii) Noise and vibration (operator)(viii) Impact on the environment noise dust ground

disturbance noise and vibration (spectator)(ix) Manufacturing and remanufacturing(x) Dismantling and recycling(xi) Emissions after treatment(xii) Biofuels and oils(xiii) Hazardous substances

A comparison of the derived sustainability criteria withthe ISO-10987 2017 sustainability factors confirms the extentof the scope in addressing sustainability for constructionequipment As illustrated in Figure 1 the sustainable criteriacan be viewed in the form of three core stages )e primarylevel is the foundation stone of the sustainable agenda for theprocuring organization and enclosed by the second level of sixmain criteria life cycle cost performance system capabilityoperational convenience environmental impact and socialimpact )e outer core or third level reflects the factors whichform the subcriteria and influence the procuring decision forachieving a sustainable strategy )is sustainability frame-work which is derived from the literature and compared withISO-10987 (2017) standard provides a balanced insight toanalyse the same by using a case study for developing sus-tainable procurement index of construction equipment

3 Method

31 Multicriteria Decision-Making (MCDM) MCDM is anoperational research method that is normally used fordealing with complex decision problems MCDM enablesthe assessment and multiple expert judgments and isemployed to overcome the presence of imprecision andvague information in the evaluation process [107] Multi-criteria decision-making (MCDM) requires more than oneset of criteria for establishing a qualitative judgmentMCDM techniques select or rank the alternatives withseveral decision criteria [108] MCDM methods are wellcapable of managing and understanding decision problemsby persuading participatory decision process In addition tothis it also makes it possible for the decision-makers to docompromise or trade-offs between the different availableoptions Hence the quality of judgment is consequentlyimproved [109] MCDM is classified into two broad classesie Multiobjective decision-making (MODM) and Multi-attribute decision-making (MADM) In MODM the pri-orities are first reduced to an optimal set rather thanconsidering all predetermined alternatives )is can be doneby introducing constraints to the objective function In thisway a most agreeable elucidation could be pursued for thedesired solution However MADM generally includes suchattributes which are quantifiable In such a case this set ofattributes is being used for the evaluation alternatives [108]Various researchers have applied MCDM methods in issuespertaining to sustainable agenda as well since it greatly

supports the entire decision-making process by consideringthe significant aspect referred as the triple bottom line ofsustainability which comprises of the people profit andplanet MCDM has found its diverse application in the fieldof sustainable energy planning and environment Loslashken[110] has applied MCDM for managing energy planningissues in the local environment Other researchers such asGreening and Bernow [111] formulated energy and envi-ronment policies by applying MCDM methods HoweverPohekar and Ramachandran [112] have supported thelinking of multiple scenarios with MCDM In addition tothis Tsoutsos et al [113] have also stated that MCDM is anappropriate methodology for dealing with sustainable en-ergy problems According to them MCDM is helpful as itpermits analysis and combination of a unilateral objectivewith many alternatives It encompasses the evaluation cri-teria and corresponding weight of every alternative for ameaningful output AHP methodology has widely been usedfor solving MCDM issues in different sectors such as edu-cation industry and engineering [114ndash116] )ere areseveral MCDM techniques discussed in the literatureHowever each set of techniques has diverse characteristicsand application In this study the analytic hierarchy process(AHP) method of the MADM branch of MCDM is used todevelop a sustainability assessment framework for thesustainable selection of construction equipment

32 Application of Analytic Hierarchy Process Analytic hi-erarchy process (AHP) is considered as the most effective andcommonly used method of MCDM in various studies of thediverse field AHP provides a convenient approach to analysedecision problems It is a method to evaluate subjective andobjective functions in multicriteria decision-making and helpusers to reach on an agreeable solution Another importantfeature of AHP is to achieve consensus in the group decision-making process AHP has the ability to guide the decision-makers for achieving the best and optimal judgment for theirproblem rather than to get ldquocorrectrdquo answers It offers a broadand balanced hierarchical structure for addressing decisionproblems on a common goal and related criteria [117] AHPhasmultiple applications in diversified situations such as choicemaking rank orders prioritization and resource allocationAHP helps quantify the weight of the appraised criteria in theform numeric basis )e criteria weight of each element de-termines its relative importance with the other elements of thehierarchy Hence it facilitates the decision-makers to identifyand prioritize significant factors [31] Besides this the calcu-lation of the inconsistency index is another salient feature ofAHP It makes possible for the decision-makers to check theconsistency of their judgments A higher value of inconsistencyindex ie greater than 010 should not be considered asappropriate and reevaluation is required in such calculations[118] One of the applications of AHP was included by Sub-ramanian and Ramanathan [119] who have classified the AHPinto five broad areas of operation research which includeoperation strategy process product design planning andscheduling resources and project management andmanagingthe supply chain process as prominent decision areas In the


construction industry AHP is considered as a rational toolduring project appraisals phases It has been used in pre-qualification of contractors and in selecting the potentialbidders Besides this AHP applications are also found inmaterial and equipment selection conflict resolution andproject team selection [120ndash122] AHP has also been used ininformation technology (IT) to evaluate the quality of soft-ware systems [123] Mathivathanan et al [15] suggested ap-plication of AHP in the decision-making of farming andagricultural lands in developing countries AHP has also beenapplied heavily in macro and people-oriented issues togetherwith the supply chain management field [107] AHP iscommonly being used in sound judgment decision-makingdue to the linkage of linguistic data [124] )e main stepsrequired in the formulation of AHP framework comprises ofhierarchy construction pairwise comparisons deriving rel-ative weights consistency checking and synthesizing results[118]

321 Step 1 Hierarchy Construction )e construction of thehierarchical structure is a foundation stone of AHP It isconsidered as an important step of AHP and there is nospecialized approach for making a hierarchy)e constructionof hierarchy is a top-down process and comprises of severallevels )e elements of hierarchical levels are managed in sucha way that they are on the same scale and magnitude )eelements of the same hierarchy level must be correlated withthe other corresponding factors of the structure )e forma-tion of AHP hierarchy normally starts from the higher-level

goal and subdivides into lower-level decision factors In anyAHP model the number of hierarchical levels is a function ofproblem intricacy and the degree of quantification for each ofthe element However a typical AHPmodel comprises of fourlevels It starts from Level 1 as objectives or goal its associatedmain criteria as Level 2 subcriteria as Level 3 and Level 4 ofthe hierarchy contains the choices of alternatives Overall thecriteria subcriteria and alternatives options are clustered forachieving the top-notch goal or objective

322 Step 2 Pairwise Comparison After the hierarchyconstruction the next step is to establish the relative im-portance of the main criteria and subcriteria by comparingthem in the form of pairs It is an important step andconsidered as a spine of AHP During this process the itemsin each set of the hierarchy are compared with their cor-responding group members For this a nine-point scale asshown in Table 2 is used to measure the relative importanceof the items )e intensity of this scale ranges from one tonine )ere is no ldquocorrectrdquo or ldquoincorrectrdquo choice whencomparing the items Nevertheless it is the choice ofpreference between two items on the number scale Whenmaking a choice between two items it should be noted thatwhich preference is more important over the other item onthe same level of the hierarchy And the second key aspect isto assign a numerical value to quantify the judgment [125]

)e pairwise judgments are recorded in a decisionmatrix An algebraic representation of a comparison matrixis shown in the below equation

Sustainable procurement of

construction equipment

Environmental impact

(EI)

Social benefit(SB)

Life cycle cost (LCC)

Operational convenience

(OC)

Performance (P)

System capability

(SC)

(LCC)Subcriteria

(P)Subcriteria

(SC)Subcriteria

(OC)Subcriteria

(SB)Subcriteria

(EI)Subcriteria

Figure 1 Framework for sustainable procurement of construction equipment


A

a11 a12 middot middot middot a1n


⋮ ⋮ middot middot middot ⋮

an1 an2 middot middot middot ann

⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦

(1)

)e abovematrix ldquoArdquo represents the judgments or relativeimportance of alternatives as n times n matrix where ldquonrdquo is thenumber of items being evaluated )e entries of matrix ldquoArdquoie aij are the relative judgments between the two alternativesi and j in such a way that the ith row corresponds to the jthcolumn of ldquoArdquo Equations show the characteristics as

aii 1⟺ i j (2)

aij 1aij

(3)

where aij can also be written as

aij wi

wj

(4)

where wi shows the relative weight of the alternative i

323 Step 3 Deriving Relative Weights )is step requiresthe estimation of relative weights for each of the criteria andsubcriteria of decision hierarchy Researchers have developedmany approaches to estimate the relative weights from thecomparison matrix However eigenvector and logarithmicmethods are commonly used for deriving relative weightsSaaty (1991) as a pioneer of AHP has proposed the eigen-vector method which is derived from the matrix theory Inthis method the corresponding weights of decision elementsare determined by comparing the normalized eigenvalue tothe principal eigenvalue [125] As per equations (2)ndash(4) thematrix ldquoArdquo in equation (2) can be represented as

C A1 A2 A3 hellip An

A1 w1w1 w1w2 w1w3 hellip w1wnA2 w2w1 w2w2 w2w3 hellip w2wn

A3

w3w1 w3w2 w3w3 hellip w3wn

prime prime

An wnw1 wnw2 wnw3 hellip wnwn

(5)

here the aim is to find eigenvalues ldquowrdquo where w is

w w1 w2 w3 wn( 1113857 (6)

where ldquowrdquo is the eigenvector and a column matrixDespite many other approaches the geometric mean is

considered as the best choice for generating the eigen-vector It is calculated by multiplying each row of the abovematrix As there is ldquonrdquo number of entries take the nth rootof the multiplication Finally the normalized roots areobtained by deriving the total and subsequently dividethem by the total outcome He has suggested that the ei-genvalues are not consistent with this approach So theconsistency test must be carried out before finalizing theresults [125]

324 Step 4 Checking the Consistency Ratio )emeasure ofldquoConsistency Ratiordquo (CR) is an important aspect of AHP)e optimal decision-making in pairwise comparison ismainly associated with the permissible value of consistencyratio )is step acts as a gateway to observe the consistencyand inconsistency of the decision matrix Normally cardinaland ordinal consistency checks are considered for pairwisecomparison Ordinal consistency requires that if a is greaterthan b and b is greater than c then amust be greater than cHowever cardinal consistency states that a stronger re-lationship is required between the factors to be evaluated Inthis case if a is two times more important than b and b isthree times more important than c then a should be sixtimes more important than c In order to calculate theconsistency ratio an index was formulated to measure theconsistency of weights In this regard the acceptable range ofCR should be equal to or less than 010 However a revisionin the pairwise comparison is compulsory if CR is greaterthan this boundary value [125]

325 Step 5 Synthesizing Results )e final step starts fromthe summation of relative values for each set of alternativeson all hierarchy levels )ese values are combined togetherto establish the overall score or criteria weight of eachalternative As an outcome the normalized local priorityvectors are obtained due to this additional function Nowthe final priorities are synthesized by aggregating theproduct of local priority vector and the relative weights ofthe respective alternative )e process of aggregation startsfrom the bottom level of the hierarchy and proceeds up-wards to the highest level goal It is pertinent to note thatsummation of all weights of alternatives and their corre-sponding importance are equal to 100 )e followingequation shows a simplified arithmetical formulation foraggregation of criteria weights at different levels ofhierarchy

final weight of criteria

1113944[(weight of alternatives wrt criteria)

times(importance of criteria)]

(7)

)is study has adopted the AHP technique for theformulation of an integrated framework )e process flow ofthe proposed AHP-based decision support framework is

Table 2 Numeric comparison scale

Intensity of importance Definition1 Equal importance2 Weak or slight3 Moderate importance4 Moderate plus5 Strong importance6 Strong plus7 Very strong8 Very very strong9 Extreme importance


outlined in Figure 2 and illustrates a top-down relationshipbetween sustainable evaluation criteria and AHP

)is framework indicates that sustainable criteria pro-vide an overall objective and relevant alternatives to developmatrixes for pairwise comparison Now these matrixes helpdetermine the normalized weights of each alternative (iemain criteria and subcriteria) At this stage the measure-ment of consistency ratio (CR) is a gateway for the furtherappraisal of the alternatives Any alternative having the CRvalue less than 010 shall need reassessment with respect toeach other After calculating the consistent normalizedweights of each alternative (ie CRgt 010) the overallweight is determined along with the combined value ofachieved sustainability by the corresponding option Lastlybased on the final sustainability score the most suitable andsustainable equipment is selected

4 Case Study

Case studies allow deeper insights into the real-life problemand can be supportive in determining the empirical in-vestigation through qualitative means [126] )is approachalso provides an effective way to describe theories whereinsufficient information is available Various earlier studieshave also considered a case study-based approach in dealingwith project planning design construction economic is-sues and to study the political phenomenon [127] )e casestudy presented here is based on an intended scenario whichwill implement the AHP technique on the established maincriteria and subcriteria for selection of sustainable con-struction equipment )is case study describes a situationwhich requires the selection of sustainable earthmovingequipment ie a wheel loader for performing earthmovingoperations such as hauling digging and demolishing It issignificantly important equipment used during the con-struction of roads and highways However they produceGHG emissions [128] Generally in a construction project itis the responsibility of a contractor to utilize necessaryequipment and machinery for undertaking complex activ-ities at the site Accordingly during the project biddingprocess contractors list down the anticipated arrangementof equipment and machinery in their technical bidEquipment procurement for the project is often a hugecapital investment by the contractor As such contractorsare always concerned that procured equipment must have ahigh rate of utilization greater efficiency along with mini-mum downtime and repair cost However if these factorswere to add up with the agenda of sustainability the situ-ation becomes multifaceted and complex to select the bestchoice among many alternatives In such a case the con-tractorrsquos management team is responsible for deciding onthe multicriteria basis )us ensuring that the companyrsquosinvestment is being rationally spent on procuring such heavyequipment fulfills operational needs and meets the triplebottom line of sustainability

)ree alternatives of the front-wheel loader (a type ofearthmoving equipment) for carrying out earthwork oper-ations on an infrastructure project have been chosen for thiscase study )e brief synopsis is discussed below

41 AlternativeA )is model of the bucket wheel loader isdesigned and manufactured by ldquoXXrdquo Inc and it is wellcapable of doing earthmoving operations with low cost)e most noteworthy aspect of this model is its ability toprotect the environment It has met the Tier 3 emissionstandard and complies with environmental regulatoryrequirements It lowers routine maintenance whileeliminating waste to the environment )e use of a load-sensing steering system results in a more efficient powersystem thus reducing the reducing fuel consumption andhigher production Besides this demand-driven coolingfans and automatic engine idle shutdown system helpmore efficient fuel management which gradually reducesthe level of emissions

42 Alternative B )is model comprises of environment-friendly enginersquos ie turbo-charged low emissions andhigh torque near idle rpm gives the low fuel consumptionand designed and manufactured by ldquoYYrdquo Ltd Its elec-tronically controlled and hydraulically driven coolingfans only operates at the desired level and economize fuelusages Its turbo-charged engine meets all governingemission requirements according to Stage IIIA in Europeand Tier 3 in the USA )e advanced fuel injection andelectronic engine control make efficient use of every dropof fuel )e smart system for internal exhaust gasrecirculation reduces Nox emissions by lowering peakcombustion temperatures In addition to this load-sensing hydraulics and steering systems contribute tolower fuel consumption It also allows provisions forbiodegradable hydraulic oil that supports environment-friendly operations

43 Alternative C )is innovative model ldquoZZrdquo of the bucketwheel loader offers a wide variety of operational features thatsupport high productivity with minimizing environmentalimpacts )is model complies with the latest EU regulationson emission standards It is fitted with a muffler filter ox-idation catalyst and exhaust temperature control systemwhich capture air pollutants and automatically burn down atdesired temperature )is system is supported by variablegeometry turbocharger that encourages optimal combustionand high volume-cooled EGR (exhaust gas recirculation)which also helps reduce nitrous oxide levels Besides this theuse of optional autoengine shutdown function helps preventfuel wastage by stopping the engine while the wheel loader islong idling

)e three equipment choices described above aresummarized in Table 3 and will be evaluated for the selectionof sustainable earthmoving equipment ie wheel loaderSince the three alternatives have a different purchase pricemanufacturer and somewhat specifications too )e ap-plication of the AHP technique will help in the selection ofthe most sustainable wheel loader for this scenario meetingthe triple bottom line of sustainability )e subsequentsections will illustrate the process of application of AHPmethodology concerning the decision-making problem ofthis paper case study


44 Hierarchy of Decision Problem )is is the first steptowards the mathematical formulation of the AHP frame-work )e user has to define the ultimate goal main criteriaand subcriteria Figure 3 shows the hierarchy of the decisionproblem It is evident from Figure 3 that at the top of alllevels is the goal which is the selection of sustainable con-struction equipment followed by the next level of maincriteria and subsequently subcriteria all altogether related tothe three alternatives All three alternatives shall be weightedbased on each of subcriteria of the main criteria and sub-sequently on the basis of each main criterion to provide thealternative weight as described in the following sections ofthe paper

45 Data Collection for Pairwise Comparison Now the nextstep for developing the AHP framework is to collect data

for the pairwise comparison of all alternatives on eachhierarchy level In order to achieve this aim a question-naire based on Saatyrsquos scale of comparison was developed toundertake the survey )e range of this scale varies fromone to nine which is generally found very appropriate forpairwise comparison )is scale measures the superiority ofeach element with respect to the other elements of thehierarchy )e limitation of the Saaty scale is that it onlyprovides a comparison of one set of criteria at a timeGuidelines on answering instruction and examples hadbeen explicitly mentioned in the questionnaire As regardsthe sample size it may be noted that AHP is a subjectiveapproach for addressing specific issues )erefore a surveyunder this methodology does not require a large samplesize for analysing data A higher degree of inconsistency isusually associated with large sample size )e relevantliterature wherein AHP surveys had also been undertaken

Check stability analysis

LCC

Sustainable selection criteria for construction equipment

P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique

Pairwise comparison of MC and SC

Normalized weight of MS and SC

Calculate consistency ratio (CR)

CR gt 01

CR le 01

Calculate overall weight of alternatives

Calculate sustainability index

Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)

Figure 2 AHP framework for sustainable procurement of construction equipment


considerably comprised of small sample size since it is moreappropriate and reliable for focusing on decision problembeing studied )e tendency to receive arbitrary feedbacksin such case shall be low in this case thus resulting in a highdegree of consistency Accordingly the questionnaireswere sent to the ten respondents of G7 Class A category ofMalaysian contractors who all were well experienced andhad sufficient knowledge of sustainable construction )eserespondents of a questionnaire survey of this study were allfrom the private sector and had relevant qualification andsatisfactory work experience as well All the participants inthe survey had more than 20 years of field experience andhad a minimum of bachelorrsquos degree Some of these re-spondents had also acquired additional postgraduatequalifications )e respondentrsquos credentials show their

involvement in different infrastructure projects such asroads highways bridges and dams )is informationpertaining to the respondent is significant to suggest thatquestionnaires are filled by the experienced and seniorprofessionals having vast experience in constructionprojects )eir opinions and views are quite important andreliable in order to establish the findings

5 Results and Discussion

In this section based on AHP steps for the case studydiscussed and basic model developed in Section 4 of thispaper the results pertaining to pairwise comparison of mainand subcriteria and pairwise of comparison of alternativeand synthesized results are presented

Table 3 Summary of alternatives option

Description Alternative A Alternative B Alternative CProject type Infrastructure Infrastructure InfrastructureOperation type Haulingdiggingdemolishing Haulingdiggingdemolishing HaulingdiggingdemolishingEquipment type Earthmoving Earthmoving EarthmovingCategory Wheel loader Wheel loader Wheel loaderManufacturer XX YY ZZModel XX 00 YY 00 ZZ 00Mode of payment 100 buy 100 buy 100 buy

Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)

System capability (SC)

SubcriteriaMain criteria Alternatives

Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A

Figure 3 Hierarchy of the decision problem


51 Pairwise Comparison ofMainCriteria )e judgments ofthe respondents were listed in the comparison matrix andsubsequently checked for the consistency ratio According toSaaty and Vargas [118] the judgments were accepted if theconsistency ratio (CR) is equal to or less than 010 Out of tenrespondents the judgments of two of them were not in thedesired range of consistency as such their feedbacks weresent them back and requested for a careful examination ofthe judgments After receiving consistent judgments from allthe respondents pairwise comparisons were performed andthe aggregated results were produced by using the geometricmean method Table 4 shows the principal comparisonmatrix and their corresponding priority vectors with respectto the overall objective of the decision problem)e diagonalvalues of the matrix are equal to 1 It shows that the weight ofcriteria with respect to itself is always 1 )e value of CR forthis matrix is 003 As this ratio is less than 10 the matrix istaken as consistent for further consideration and compar-isons)e numerical representations of judgments displayedin bold numbers in the matrix signify that the row element ispreferred to the column element While the judgmentsshown in grey cells revealed that both the row and columnelements are judged as equal in importance It is importantto note that numerical representation of a judgment does notnecessarily mean that one element is preferred to the otherby the numerical amount instead the relative priority vectorsfor all main criteria carry actual importance which is cal-culated and tabulated in the last column of the comparisonmatrix It shows that life cycle cost (LC) has the highest valueof priority vector followed by the performance (P) andsystem capability (SC)

52 Pairwise Comparison of Subcriteria Following havingjudgments in the form of priority vector of main criteria thenext step is to commence the pairwise comparison ofsubcriteria of respective main criteria )is subcriteriacomparison process flow is in a similar fashion as that ofperformed for developing the matrix as a priority vector andconsistency ratio for the main criteria in Section 51Tables 5ndash10 show the pairwise comparison matrix for all ofthe 38 subcriteria with their corresponding elements (noteitalic numbers show that the column elements are preferredwith respect to the corresponding row elements) )esematrices 3 to 8 illustrated the pairwise comparison of allsubcriteria of six main criteria)e CR values of the matricesare well below 010 range Hence the judgments are con-sidered as reliable for the final pairwise comparison ofalternatives

53 Pairwise Comparison of Alternatives and SynthesizingResults In this case study three different types of wheelloaders were considered as possible alternatives for thedecision-makers )ese wheel loaders are from differentmanufacturers and have varying specifications During thesurvey questionnaire the respondents were explicitly in-formed about the manufacturer and model information Inorder to maintain the confidentiality of the manufacturetrademark and model this research paper has used theletters XX YY and ZZ to represent these three alternatives(with a different manufacturer) )e local criteria weights ofthe alternatives are shown in Table 11 Following all thepairwise comparison process the normalized priority vec-tors ie the rating of each criterion subcriteria and al-ternatives that were synthesized to obtain global weights arealso shown in Table 11 A local weight is associated with thesingle criteria and a derivative of a distinct judgmentHowever the global weight of the subcriteria is calculated bythe multiplication of its local priority vector with the cor-responding local weight of the main criteria )is sameapproach is used for determining the global weights of al-ternatives )ese calculations were performed using ExpertChoice 115 version )is software package provides twosynthesis modes ie distributive and ideal An Ideal syn-thesis mode is also known as ldquoopen systemrdquo which assignsthe full weight of each covering objective to the best (highestpriority) alternative for each covering objective )e otheralternatives receive weights under each covering objectiveproportionate to their priority relative to the best alternativeunder each covering objective)ese weights or priorities forall the alternatives are then normalized so that they sum to10 On the contrary the distributive mode is called ldquoclosedsystemrdquo which distributes the weight of each coveringobjective to the alternatives in direct proportion to the al-ternative priorities under each covering objective)e globalweights of the criteria are synthesized to establish the overallpriorities for the selection of the sustainable alternative asshown in Table 11

It is evident from the results tabulated in Table 11 whichare based on the AHP methodology that out of threeavailable alternatives the wheel loader model ldquoYYrdquo hasattained highest priority score of 0368 and thus judged as

Table 4 Comparison matrix and priority vector for the main criteria

Main criteria LCC P SC OC EI SB Priority vector CRLCC 1 3 3 3 4 4 0385

003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069

Table 5 Comparison matrix and priority vector for life cycle cost

Sub criteria LCC1 LCC2 Priority vector CRLCC1 1 1 05 000LCC2 1 05


sustainable earthmoving equipment )is judgment of theldquoYYrdquo manufacturer model of earthmoving equipment beingsustainable is based on the fact that it has performed well onthe majority of the sustainability criteria of this study )eldquoYYrdquo manufacturer model has exceptionally performed wellon operational convenience environment and social ben-efits sustainability criteria )e alternatives ldquoZZrdquo (priorityscore 0347) and ldquoXXrdquo (priority score 0286) have lowerperformance on the sustainability criteria compared to theldquoYYrdquo model as such ranked as second and third best al-ternatives respectively

)ese results are extremely significant both with respectto the methodology and on the basis of the sustainabilitycriteria of this study )e sensitivity analyses of these resultsare further undertaken to determine their stability androbustness in the following section

6 Stability Analysis

)e outcome of the AHP framework is a function of hier-archical structure and weightage of the relative judgments asassigned by the decision-makers It has been observed that achange in hierarchy and judgments may directly affect theframework outcome )erefore the robustness of the AHPframework was duly verified by performing the stabilityanalysis)e stability of the ranking was checked for different

projected scenarios To this end dynamic sensitivityanalyses were undertaken by changing the priorities ofthe objectives and to determine how these changes affectthe ranking of the alternatives )e dynamic sensitivityanalyses were accomplished by increasing or decreasingthe criteria weights which would result in the change ofpriorities of the alternatives In this study seven sce-narios were taken into consideration and simulated fordifferent values of sustainability criteria

61 Scenario 1 In the first simulated scenario the weights ofall the six main criteria were kept uniform in the left-handcolumn of the dynamic sensitive graph as shown in Figure 4

It is observed that by keeping the uniform weights ofthe main criteria the final ranking of the alternative re-mains unchanged as shown in Figure 4 which establishesthe internal consistency of the questionnaire survey andsubsequent pairwise comparison undertaken using AHPmethodology

62 Scenario 2 In the second scenario LCC main criteriahave been assigned a weight of 50 which alters theweights of the other criteria as shown in Figure 5 How-ever as evident the ranking of the alternative is stillconsistent

Table 6 Comparison matrix and priority vector for performance

Sub criteria P1 P2 P3 P4 P5 P6 P7 Priority vector CRP1 1 2 1 1 1 1 1 0122

003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138

Table 7 Comparison matrix and priority vector for system capability

Sub criteria SC1 SC2 SC3 SC4 SC5 SC6 Priority vector CRSC1 1 1 1 1 2 1 0143

003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185

Table 8 Comparison matrix and priority vector for operational convenience

Sub criteria OC1 OC2 OC3 OC4 OC5 OC6 Priority vector CROC1 1 3 1 1 1 1 0138

004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159


Table 9 Comparison matrix and priority vector for environmental impact

Sub criteria EI1 EI2 EI3 EI4 EI5 EI6 EI7 EI8 EI9 EI10 Priority vector CREI1 1 3 3 2 2 3 3 1 1 2 0046

003

EI2 1 1 2 2 2 2 2 2 1 0157EI3 1 2 2 2 2 2 2 1 0157EI4 1 1 1 2 2 2 1 0087EI5 1 1 2 2 2 2 0096EI6 1 1 2 2 2 0108EI7 1 5 5 2 0155EI8 1 1 2 0050EI9 1 2 0050EI10 1 0093

Table 10 Comparison matrix and priority vector for social benefits

Sub criteria SB1 SB2 SB3 SB4 SB5 SB6 SB7 Priority vector CRSB1 1 3 5 5 1 1 1 0062

009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130

Table 11 Overall ratings of sustainable criteria for developing sustainable procurement index

Main criteria Local weight(1) Subcriteria Local weight

(2)Global weight

(3)

Local weight ofalternative

Global weight ofalternative

XX YY ZZ XX YY ZZ

Life cycle cost (LCC) 0385 LCC1 0500 0193 0333 0333 0333 0064 0064 0064LCC2 0500 0193 0333 0333 0333 0064 0064 0064

Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010

Operational convenience(OC)

0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008


63 Scenario 3 In this scenario as shown in Figure 6 thealternative ranking remains stable despite the 50 impor-tance weightage assigned to the performance (P) criteria

64 Scenario 4 In this scenario 50 importance level isassigned to system capability (SC) criteria )e graphicalrepresentation in Figure 7 yet shows YY alternative as asustainable option

65 Scenario 5 In this case a 50 importance level isassigned to operational convenience (OC) criteria )egraphical representation in Figure 8 shows that YY

alternative still attains the highest priority score in this caseas well

66 Scenario 6 In Figure 9 environmental impact (EI)criteria have been assigned at 50 importance level Asdepicted from the graph of Figure 9 the trend of right-handbars is consistent with the preceding scenarios

67 Scenario 7 Finally in this scenario social benefit (SB)has been assigned a 50 importance level and the trend ofalternatives illustrated in Figure 10 shows the consistency ofthe ranking of alternatives

Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ

Environmental impact (EI)

0077 EI1 0046 0004 0250 0500 0250 0001 0002 0001EI2 0157 0012 0250 0500 0250 0003 0006 0003EI3 0157 0012 0250 0500 0250 0003 0006 0003EI4 0087 0007 0500 0250 0250 0004 0002 0002EI5 0096 0007 0500 0250 0250 0004 0002 0002EI6 0108 0008 0200 0400 0400 0002 0003 0003EI7 0155 0012 0333 0333 0333 0004 0004 0004EI8 0050 0004 0250 0500 0250 0001 0002 0001EI9 0050 0004 0333 0333 0333 0001 0001 0001EI10 0093 0007 0333 0333 0333 0002 0002 0002

Social benefits (SBs)

0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002

Total 1000Priority level 0286 0368 0347Alternative ranking 3 1 2

0

167 life cycle cost 275 XX

377 YY

348 ZZ

166 performance

167 system capability

167 operational convenience

167 environmental impact

166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 4 Dynamic sensitivity graph for AHP framework (with all criteria equal weight)


298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 5 Dynamic sensitivity graph for AHP framework (with 50 LCC weight)

251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 6 Dynamic sensitivity graph for AHP framework (with 50 performance weight)

265 XX388 YY346 ZZ

100 life cycle cost99 performance500 system capability

100 operational convenience100 environmental impact100 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 7 Dynamic sensitivity graph for AHP framework (with 50 SC weight)


260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 8 Dynamic sensitivity graph for AHP framework (with 50 OC weight)

287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 9 Dynamic sensitivity graph for AHP framework (with 50 EI weight)

250 XX

382 YY

367 ZZ

100 life cycle cost100 performance




501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05

Figure 10 Dynamic sensitivity graph for AHP framework (with 50 SB weight)


It is therefore evident from the sensitivity analysisundertaken under all of above scenarios of this study that asthe priority of one objective changes the priorities of thealternatives decrease or increase in proportion to theiroriginal value However the ranking of the alternative re-mains unchanged in all these scenarios )e bar chartanalysis also indicates that options YY and ZZ are verymuch close to each other as compared to the option XX)us the assigned criteria weights and indexes are con-sidered as stable Besides this these analyses also suggestthat the alternatives YY and ZZ are evaluated as closealternatives for the selection of the sustainable wheelloader

7 Conclusions

)e concept of sustainable or green procurement is one ofemerging and now largely accepted theme across the globeHowever in Malaysia this concept was only first outlinedin the 10th Malaysian Plan Since then the government isconcerned that sustainability parameters must be embed-ded in the national strategy for achieving Malaysiarsquos so-cietal and economic development It would after all leadtowards a sustainability culture in the country and ensureaccelerated economic growth without compromising theenvironment As such the emphasis has been across theboard at government level to integrate sustainability as-pects in the procurement of products and services forfuture construction projects However subsequent to thesedevelopments the focus of sustainability in the Malaysianconstruction industry is more inclined towards the materialselection structure design and materials recycling ratherthan environmental concerns As such evidently a gapexists between the appraisal of the conventional approachof equipment selection and inclusion of sustainable con-cept in the decision-making during the procurement phaseof a project In order to address this gap this study hasattempted to establish a comprehensive link by proposingan AHP-based assessment framework for developingsustainable procurement index for the procurement ofearthmoving equipment )is framework is based on amultilayered hierarchy and comprised of six main criteriaand thirty-eight subcriteria )e AHP evaluation furthermeasured the indicative sustainable procurement indexvalues for the Malaysian construction industry Amongthem it is found that life cycle cost is an important decisionfactor in the selection of sustainable earthmoving equip-ment and has a percentage weightage 385 It has also thehighest value of priority vector which represents thatdecision-makers have considered it significantly moreimportant It is followed by other main criteria ie per-formance (176) system capability (165) and opera-tional convenience (128) have higher values ofimportance )e indexes weights for environmental impactand social benefits are relatively lower and acquired apriority score of 77 and 695 respectively )e finalresults of the multicriteria-based AHP framework revealedthat alternative ldquoYYrdquo is a best-evaluated option forachieving sustainable practices during the desired

earthmoving operations It offers versatile features in-cluding high efficiency with low cost of operation main-tenance high hour machine life standards and multiplerebuild options for continued uptime and long machinelife Besides this it has many other benefits for the operatoras it minimizes operator fatigue resulting in a safe pro-ductive work site and reduced GHG emissions )e sen-sitivity analysis further depicts that alternatives ldquoYYrdquo andldquoZZrdquo are close to each other and have a stable ranking indifferent scenarios

)e procurement index developed in this study isconsidered a significant first contribution with respect tothe selection of sustainable construction equipment forthe Malaysian construction industry It will help practi-tioners to undertake rational decisions during pro-curement of construction equipment )e proposedsustainability index is expected to greatly assist them tounderstand the decision problem by forming a hierarchyand transforming the qualitative judgments into mean-ingful quantitative weights for ranking the alternatives)e established framework of this study is specificallyrelated to earthmoving equipment which is recom-mended to be extended for other types of nonroad con-struction equipment as well

Data Availability

)e survey questionnaire used to support the finding of thestudy is available from the corresponding author uponrequest

Conflicts of Interest

)e authors would like to mention that they have noconflicts of interest associated with this research endeavor

Acknowledgments

)e authors highly acknowledge the Ministry of HigherEducation Malaysia for Fundamental Research GrantScheme (FRGS) under grant no RDU170134 and UniversitiMalaysia Pahang for their financial and technical support forcompleting this research work

References

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[2] K Govindan S Rajendran J Sarkis and P MurugesanldquoMulti criteria decision making approaches for green sup-plier evaluation and selection a literature reviewrdquo Journal ofCleaner Production vol 98 pp 66ndash83 2015

[3] S O Ajayi and L O Oyedele ldquoWaste-efficient materialsprocurement for construction projects a structural equationmodelling of critical success factorsrdquo Waste Managementvol 75 pp 60ndash69 2018

[4] M Waris M Shahir Liew M F Khamidi and A IdrusldquoCriteria for the selection of sustainable onsite construction


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[6] L Shen Z Zhang and Z Long ldquoSignificant barriers to greenprocurement in real estate developmentrdquo Resources Con-servation and Recycling vol 116 pp 160ndash168 2017

[7] D D Gransberg C M Popescu and R Ryan ConstructionEquipment Management for Engineers Estimators andOwners CRC Press Boca Raton FL USA 2006

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[9] M Gates and A Scarpa ldquoCriteria for the selection of con-struction equipmentrdquo Journal of the Construction Divisionvol 106 no 2 pp 207ndash219 1980

[10] C M R Chan and F C Harris ldquoA databasespreadsheetapplication for equipment selectionrdquo Construction Man-agement and Economics vol 7 no 3 pp 235ndash247 1989

[11] F T S Chan R W L Ip and H Lau ldquoIntegration of expertsystem with analytic hierarchy process for the design ofmaterial handling equipment selection systemrdquo Journal ofMaterials Processing Technology vol 116 no 2-3 pp 137ndash145 2001

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[13] A Bascetin ldquoA decision support system using analyticalhierarchy process (AHP) for the optimal environmentalreclamation of an open-pit minerdquo Environmental Geologyvol 52 no 4 pp 663ndash672 2007

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[65] B H DeWeese G Hornsby M Stone andM H Stone ldquo)etraining process planning for strength-power training intrack and field Part 1 theoretical aspectsrdquo Journal of Sportand Health Science vol 4 no 4 pp 308ndash317 2015

[66] A Lacroix R W Kressig T Muehlbauer et al ldquoEffects of asupervised versus an unsupervised combined balance andstrength training program on balance and muscle power inhealthy older adults a randomized controlled trialrdquo Ger-ontology vol 62 no 3 pp 275ndash288 2016

[67] F Leite Y Cho A H Behzadan et al ldquoVisualization in-formation modeling and simulation grand challenges in theconstruction industryrdquo Journal of Computing in Civil En-gineering vol 30 no 6 Article ID 04016035 2016

[68] X Wang and H-Y Chong ldquoSetting new trends of integratedBuilding Information Modelling (BIM) for construction


industryrdquo Construction Innovation vol 15 no 1 pp 2ndash62015

[69] K Zhou T Liu and L Zhou ldquoIndustry 40 towards futureindustrial opportunities and challengesrdquo in Proceedings ofthe 2015 12th International Conference on Fuzzy Systems andKnowledge Discovery (FSKD) Zhangjiajie China August2015

[70] A Gulghane and P Khandve ldquoManagement for con-struction materials and control of construction waste inconstruction industry a reviewrdquo International Journal ofEngineering Research and Applications vol 5 no 4pp 59ndash64 2015

[71] L Shen and V W Tam ldquoImplementation of environmentalmanagement in the Hong Kong construction industryrdquoInternational Journal of Project Management vol 20 no 7pp 535ndash543 2002

[72] S Mohamed ldquoSafety climate in construction site environ-mentsrdquo Journal of Construction Engineering and Manage-ment vol 128 no 5 pp 375ndash384 2002

[73] T Yang and C-C Hung ldquoMultiple-attribute decisionmaking methods for plant layout design problemrdquo Roboticsand Computer-Integrated Manufacturing vol 23 no 1pp 126ndash137 2007

[74] J L Ashford De Management of Quality in ConstructionRoutledge Abingdon UK 2002

[75] K W Chau M Anson and J P Zhang ldquoFour-dimensionalvisualization of construction scheduling and site utilizationrdquoJournal of Construction Engineering and Managementvol 130 no 4 pp 598ndash606 2004

[76] M Prasad Nepal and M Park ldquoDowntime model devel-opment for construction equipment managementrdquo Engi-neering Construction and Architectural Management vol 11no 3 pp 199ndash210 2004

[77] H Martin A A Syntetos A Parodi Y E Polychronakisand L Pintelon ldquoIntegrating the spare parts supply chain aninter-disciplinary accountrdquo Journal of ManufacturingTechnology Management vol 21 no 2 pp 226ndash245 2010

[78] K Matzler V Veider and W Kathan Adapting to theSharing Economy MIT Cambridge MA USA 2015

[79] A May V Mitchell S Bowden and T )orpe ldquoOpportu-nities and challenges for location aware computing in theconstruction industryrdquo in Proceedings of the 7th InternationalConference on Human Computer Interaction with MobileDevices amp ServicesmdashMobileHCI rsquo05 Salzburg Austria 2005

[80] E Badu D J Edwards and D Owusu-Manu ldquoTrade creditand supply chain delivery in the Ghanaian constructionindustryrdquo Journal of Engineering Design and Technologyvol 10 no 3 pp 360ndash379 2012

[81] A J Lang W Michael Aust M Chad BoldingK J McGuire and E B Schilling ldquoComparing sediment trapdata with erosion models for evaluation of forest haul roadstream crossing approachesrdquo Transactions of the ASABEvol 60 no 2 pp 393ndash408 2017

[82] A Soofastaei ldquoPayload variance plays a critical role in thefuel consumption of mining haul trucksrdquo Aust Resour Investvol 8 no 4 p 64 2014

[83] J Hong G Q Shen Y Feng W S-T Lau and C MaoldquoGreenhouse gas emissions during the construction phase ofa building a case study in Chinardquo Journal of Cleaner Pro-duction vol 103 pp 249ndash259 2015

[84] W Haas F Krausmann D Wiedenhofer and M HeinzldquoHow circular is the global economy an assessment ofmaterial flows waste production and recycling in the

European Union and the world in 2005rdquo Journal of In-dustrial Ecology vol 19 no 5 pp 765ndash777 2015

[85] Z Liu D Guan W Wei et al ldquoReduced carbon emissionestimates from fossil fuel combustion and cement pro-duction in Chinardquo Nature vol 524 no 7565 pp 335ndash3382015

[86] X Ji and B Chen ldquoAssessing the energy-saving effect ofurbanization in China based on stochastic impacts by re-gression on population affluence and technology (STIR-PAT) modelrdquo Journal of Cleaner Production vol 163pp S306ndashS314 2017

[87] Y Zhang C-Q He B-J Tang and Y-M Wei ldquoChinarsquosenergy consumption in the building sector a life cycle ap-proachrdquo Energy and Buildings vol 94 pp 240ndash251 2015

[88] A W A Hammad A Akbarnezhad and D Rey ldquoA multi-objective mixed integer nonlinear programming model forconstruction site layout planning to minimise noise pollu-tion and transport costsrdquo Automation in Constructionvol 61 pp 73ndash85 2016

[89] N Kwon M Park H-S Lee J Ahn and M Shin ldquoCon-struction noise management using active noise controltechniquesrdquo Journal of Construction Engineering andManagement vol 142 no 7 Article ID 04016014 2016

[90] D Efanov G Osadchy D Sedykh D Pristensky andD Barch ldquoMonitoring system of vibration impacts on thestructure of overhead catenary of high-speed railway linesrdquoin Proceedings of the 2016 IEEE East-West Design amp TestSymposium (EWDTS) Yerevan Armenia October 2016

[91] S Yusoff R Nordin and H Yusoff ldquoEnvironmental man-agement systems (EMS) ISO 14001 implementation inconstruction industry a Malaysian case studyrdquo Issues InSocial And Environmental Accounting vol 9 no 1 pp 18ndash31 2015

[92] C K Saha and J Hosain ldquoImpact of brick kilning industry inperi-urban Bangladeshrdquo International Journal of Environ-mental Studies vol 73 no 4 pp 491ndash501 2016

[93] M K Ghorabaee M Amiri E K Zavadskas andJ Antucheviciene ldquoA new hybrid fuzzyMCDM approach forevaluation of construction equipment with sustainabilityconsiderationsrdquo Archives of Civil and Mechanical Engi-neering vol 18 no 1 pp 32ndash49 2018

[94] J Hong G Q Shen S Guo F Xue and W Zheng ldquoEnergyuse embodied in Chinas construction industry a multi-regional input-output analysisrdquo Renewable and SustainableEnergy Reviews vol 53 pp 1303ndash1312 2016

[95] S Z Razali R Yunus S Abdul Rashid H N Lim andB Mohamed Jan ldquoReview of biodegradable synthetic-baseddrilling fluid progression performance and future pros-pectrdquo Renewable and Sustainable Energy Reviews vol 90pp 171ndash186 2018

[96] S S KamaruddinM FMohammad and RMahbub ldquoBarriersand impact ofmechanisation and automation in construction toachieve better quality productsrdquo ProcediamdashSocial and Behav-ioral Sciences vol 222 pp 111ndash120 2016

[97] S J Ray and J Teizer ldquoDynamic blindspots measurement forconstruction equipment operatorsrdquo Safety Science vol 85pp 139ndash151 2016

[98] M Ccedilagdaccedil Arslan B Ccedilatay and E Budak ldquoA decisionsupport system for machine tool selectionrdquo Journal ofManufacturing Technology Management vol 15 no 1pp 101ndash109 2004

[99] R R Cabahug D J Edwards and J Nicholas ldquoClassifyingplant operator maintenance proficiency examining personal


variablesrdquo Building Research amp Information vol 32 no 2pp 119ndash127 2004

[100] Y Fang and Y K Cho ldquoEffectiveness analysis from acognitive perspective for a real-time safety assistance systemfor mobile crane lifting operationsrdquo Journal of ConstructionEngineering and Management vol 143 no 4 Article ID05016025 2016

[101] I J Shin ldquoFactors that affect safety of tower crane in-stallationdismantling in construction industryrdquo SafetyScience vol 72 pp 379ndash390 2015

[102] H Guo Y Yu and M Skitmore ldquoVisualization technology-based construction safety management a reviewrdquo Auto-mation in Construction vol 73 pp 135ndash144 2017

[103] D Silka ldquoDevelopment of organizing and economic mea-sures for monitoring the cost of construction resourcesrdquoMATECWeb of Conferences vol 106 Article ID 08042 2017

[104] J Irwin B Lahneman and A Parmigiani ldquoNested identitiesas cognitive drivers of strategyrdquo Strategic ManagementJournal vol 39 no 2 pp 269ndash294 2018

[105] Caterpillar Caterpillar Performance Handbook CaterpillarPeoria IL USA 2014

[106] International Organization for Standards ISO-10987 Earth-Moving MachinerymdashSustainabilitymdashTerminology Sustain-ability Factors and Reporting International Organization forStandards Geneva Switzerland 2017

[107] M Bouzon K Govindan C M T Rodriguez andL M S Campos ldquoIdentification and analysis of reverselogistics barriers using fuzzy Delphi method and AHPrdquoResources Conservation and Recycling vol 108 pp 182ndash1972016

[108] J Climaco Multicriteria Analysis Springer-Verlag BerlinGermany 1997

[109] M Rogers M Bruen and L Maystre ldquoELECTRE and de-cision support methods and applications in engineering andinfrastructure investmentrdquo Journal-Operational ResearchSociety vol 53 no 12 pp 1396-1397 2002

[110] E Loslashken ldquoUse of multicriteria decision analysis methods forenergy planning problemsrdquo Renewable and SustainableEnergy Reviews vol 11 no 7 pp 1584ndash1595 2007

[111] L A Greening and S Bernow ldquoDesign of coordinated energyand environmental policies use of multi-criteria decision-makingrdquo Energy Policy vol 32 no 6 pp 721ndash735 2004

[112] S D Pohekar and M Ramachandran ldquoApplication of multi-criteria decision making to sustainable energy planningndashareviewrdquo Renewable and Sustainable Energy Reviews vol 8no 4 pp 365ndash381 2004

[113] T Tsoutsos M Drandaki N Frantzeskaki E Iosifidis andI Kiosses ldquoSustainable energy planning by using multi-criteria analysis application in the island of Creterdquo EnergyPolicy vol 37 no 5 pp 1587ndash1600 2009

[114] K Govindan M Kaliyan D Kannan and A N HaqldquoBarriers analysis for green supply chain managementimplementation in Indian industries using analytic hierarchyprocessrdquo International Journal of Production Economicsvol 147 pp 555ndash568 2014

[115] T Harputlugil M Prins A T Gultekin and Y L TopculdquoConceptual framework for potential implementations ofmulti criteria decision making (mcdm) methods for designquality assessmentrdquo in Proceedings of the Management andInnovation for a Sustainable Built Environment MISBE 2011Amsterdam Netherlands June 2011

[116] S Mangla J Madaan and F T S Chan ldquoAnalysis of per-formance focused variables for multi-objective flexible de-cision modeling approach of product recovery systemsrdquo

Global Journal of Flexible SystemsManagement vol 13 no 2pp 77ndash86 2012

[117] A Shapira and M Goldenberg ldquoAHP-based equipmentselection model for construction projectsrdquo Journal of Con-struction Engineering and Management vol 131 no 12pp 1263ndash1273 2005

[118] T Saaty and L Vargas De Logic of Priorities RWS Publi-cations Pittsburgh OA USA 1991

[119] N Subramanian and R Ramanathan ldquoA review of appli-cations of Analytic Hierarchy Process in operations man-agementrdquo International Journal of Production Economicsvol 138 no 2 pp 215ndash241 2012

[120] M J Skibniewski and L C Chao ldquoEvaluation of advancedconstruction technology with AHP methodrdquo Journal ofConstruction Engineering and Management vol 118 no 3pp 577ndash593 1992

[121] M Hastak ldquoAdvanced automation or conventional con-struction processrdquo Automation in Construction vol 7no 4 pp 299ndash314 1998

[122] M Hastak and D W Halpin ldquoAssessment of life-cyclebenefit-cost of composites in constructionrdquo Journal ofComposites for Construction vol 4 no 3 pp 103ndash111 2000

[123] W Ossadnik and O Lange ldquoAHP-based evaluation of AHP-Softwarerdquo European Journal of Operational Researchvol 118 no 3 pp 578ndash588 1999

[124] A Ishizaka and A Labib ldquoAnalytic hierarchy process andexpert choice benefits and limitationsrdquo OR Insight vol 22no 4 pp 201ndash220 2009

[125] T L Saaty and L G Vargas De Logic of Priorities RWSPublications Pittsburgh PA USA 1991

[126] R K Yin Case Study Research Design and Methods SagePublications )ousand Oaks CA USA 3rd edition 2003

[127] B Gillham Case Study Research Methods BloomsburyPublishing London UK 2000

[128] W Rasdorf P Lewis S K Marshall I Arocho andH C Frey ldquoEvaluation of on-site fuel use and emissionsover the duration of a commercial building projectrdquoJournal of Infrastructure Systems vol 18 no 2 pp 119ndash1292012


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demands substantial usage ofmechanized equipment [4] As aresult it is quite complex to make a competitive and bestjudgment during equipment acquisition [5] In addition tojudgment there is a lack of knowledge between industryprofessionals and incompatibility with building componentsleading to higher additional costs and material handling costs[6] A common practice which is adapted for selecting therequired choice is based on comparing available equipmentoptions with the intended tasks Typically such an approach ismeant for taking into account a list of tangible and intangiblefactors such as cost capacity productivity and efficiency [7]In this way an appropriate selection can be carried out onvarying criteria which helps the outcome of the process [8]Earlier Gates and Scarpa [9] have classified the selectionprocedure of earthmoving equipment into four criteria whichinclude based on the spatial relationships soil characteristicscontract provision and logistics A spreadsheet-based modelhas been developed by Chan and Harris [10] for the selectionof construction equipment In their database a detailedtechnical criterion was developed for selecting backhoes andloaders in earthmoving operations However this work ofChan et al [11] focused on material handling equipmentalone Another knowledge-based approach by Haidaret al[12] established that the equipment selection process is afunction of knowledge and its subsequent optimizationthrough genetic algorithms It involves the screening ofprocured equipment from knowledge-based criteria A de-cision support framework for the selection of open-pit miningequipment was also proposed in [13] )is framework wasbased on qualitative and quantitative factors Goldenberg andShapira [14] developed the analytic hierarchy process (AHP)framework which is also based on tangible and intangiblefactors )e tangible factors included technical specificationssite conditions and cost consideration However intangiblefactors are qualitative and include safety considerationcompany policies regarding equipment acquisition marketconditions and environmental constraints )is is the first-ever decision model found in the literature which has takeninto account the soft consideration towards the selection ofconstruction equipment for the building projects

As Malaysia is planning for an increased number ofconstruction projects to meet its infrastructure needs itbecomes crucial for the industry to understand and practicesustainable procurement procedures for reducing the neg-ative environmental impact and hazards Sustainable pro-curement is considered as a key practice of supply chains inmany industrialized countries [15] In such developingeconomies sustainable procurement is considered as a keypractice of supply chains [16] Malaysia is amongst theworldrsquos emerging economies Despite that it has receivedlittle attention in addressing sustainability issues in thesupply chain Works on sustainable procurement have beenperformed in countries such as India [17] South Africa [18]China [19] Saudi Arabia [20] and Brazil [21] Existingstudies on sustainability procurement have been performedparticularly in the developed countries such as UK [22] theUSA [23] and Germany [24] but there is lack of studies intheMalaysian context As a consequence of new governanceMalaysia is poised to work towards sustainability

It is evident from the literature review presented abovethat the equipment selection frameworks and their re-spective criteria have been amply explored in variouscontexts with a diversified scope Most of these studies haveoften considered the techno-economic aspects of equipmentselection rather than environmental and social concerns inthe procurement of the construction equipment As suchthe agenda of sustainability in construction projects havebeen ignored in the entirety In the meantime a new par-adigm of green or sustainable construction emphasizes thatall aspects of the construction process should address thetriple bottom line of sustainability It is therefore em-phasized that the appraisal process of the equipment se-lection must take into account the technical economicenvironmental and social considerations )e rest of thepaper consists of several sections Section 2 is about liter-ature review Section 3 provides details about material andmethods Section 4 elaborates the case study Section 5presents and discusses results Section 6 provides the sta-bility analysis of the results and finally Section 7 concludesthe paper

2 LiteratureReview Sustainable Criteria for theSelection of Construction Equipment

)e concept of sustainability in the equipment selection is aninnovative idea for construction projects )is concept isassociated with several factors such as technical economicenvironment and various social criteria of sustainableconstruction [25] )e fields of sustainable procurement andindustrial sustainability have attracted researchers consid-erably and include topics such as sustainable supply chainmanagement [26] Before taking into account the concept ofsustainability in the construction industry and subsequentlyin the selection of construction equipment it is pertinent tomention that such considerations have already become partand parcel of various modern-day knowledge areas )esustainability concept has origins in the term lsquolsquosustainabledevelopmentrdquo which emerged for the first-ever time in 1987in the Brundtland Commission report of the United Nationsmore commonly known as the United Nations Commissionon Sustainable Development (UNCSD) )e UNCSD sus-tainability framework comprised of social environmentaleconomic and institutional criteria which further com-prised of main and subcriteria )is followed some formalconsideration of the sustainability aspect in various fieldsFor example Mihyeon Jeon and Amekudzi [27] haveaddressed sustainability in the public transportation systemby defining indicators and metrics which emphasized thatconsensus should be developed on the economy environ-ment and social well-being of society while addressing thesustainable trends in transportation Singh et al [25] havealso emphasized that sustainability criteria are not onlysignificant yet are very effective towards the formulation ofstrategy and thus suggested that these criteria are valuable inmaking policy in terms of environment and socio-economicand technological improvements )eir research work fur-ther emphasized that an indicator of sustainable develop-ment should be carefully selected refined and revisited in
























3 Method













(EI)

Social benefit(SB)



(OC)

Performance (P)

System capability

(SC)

(LCC)Subcriteria

(P)Subcriteria

(SC)Subcriteria

(OC)Subcriteria

(SB)Subcriteria

(EI)Subcriteria



A





⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦

(1)


aii 1⟺ i j (2)

aij 1aij

(3)


aij wi

wj

(4)





A3


prime prime


(5)


w w1 w2 w3 wn( 1113857 (6)








(7)







4 Case Study












LCC


P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique




CR gt 01

CR le 01



Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)









Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018






























3 Method













(EI)

Social benefit(SB)



(OC)

Performance (P)

System capability

(SC)

(LCC)Subcriteria

(P)Subcriteria

(SC)Subcriteria

(OC)Subcriteria

(SB)Subcriteria

(EI)Subcriteria



A





⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦

(1)


aii 1⟺ i j (2)

aij 1aij

(3)


aij wi

wj

(4)





A3


prime prime


(5)


w w1 w2 w3 wn( 1113857 (6)








(7)







4 Case Study












LCC


P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique




CR gt 01

CR le 01



Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)









Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018
















(EI)

Social benefit(SB)



(OC)

Performance (P)

System capability

(SC)

(LCC)Subcriteria

(P)Subcriteria

(SC)Subcriteria

(OC)Subcriteria

(SB)Subcriteria

(EI)Subcriteria



A





⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦

(1)


aii 1⟺ i j (2)

aij 1aij

(3)


aij wi

wj

(4)





A3


prime prime


(5)


w w1 w2 w3 wn( 1113857 (6)








(7)







4 Case Study












LCC


P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique




CR gt 01

CR le 01



Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)









Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018








A





⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦

(1)


aii 1⟺ i j (2)

aij 1aij

(3)


aij wi

wj

(4)





A3


prime prime


(5)


w w1 w2 w3 wn( 1113857 (6)








(7)







4 Case Study












LCC


P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique




CR gt 01

CR le 01



Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)









Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018










4 Case Study












LCC


P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique




CR gt 01

CR le 01



Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)









Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018












LCC


P OC SC EI SI

LCC 1

-2

P 1-7

OC 1

-6

SC1-

6

EI1-

10

SI1-

7

AHP technique




CR gt 01

CR le 01



Select best option

Yes

No

Main criteria (MC)

Subcriteria (SC)









Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018














Social benefit(SB)

Susta

inab

le ea

rthm

ovin

g eq

uipm

ent


(EI)



(OC)

Performance (P)



Option C

SB1 SB2 SB3

SB4 SB5 SB6

SB7

EI1 EI2 EI3

EI4 EI5 EI6

EI7 EI8 EI9

OC1 OC2 OC3

OC4 OC5 OC6

SC1 SC2 SC3

SC4 SC5 SC6

P1 P2 P3

P4

LCC1

LCC2

P5 P6

P7

EI10

Option B

Option A









003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018














003

P 1 1 2 2 3 0176SC 1 2 2 2 0165OC 1 2 3 0128EI 1 1 0077SB 1 0069














003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018


















003

P2 1 3 3 1 2 1 0232P3 1 1 2 2 1 0117P4 1 2 2 1 0117P5 1 2 1 0183P6 1 1 0093P7 1 0138



003

SC2 1 2 1 1 2 0163SC3 1 2 2 2 0100SC4 1 1 1 0178SC5 1 2 0231SC6 1 0185



004

OC2 1 1 1 1 1 0203OC3 1 2 1 1 0186OC4 1 2 1 0168OC5 1 1 0146OC6 1 0159




003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018










003




009

SB2 1 4 4 1 2 1 0098SB3 1 4 4 6 1 0354SB4 1 3 5 1 0217SB5 1 1 1 0076SB6 1 1 0062SB7 1 0130



(2)Global weight

(3)



XX YY ZZ XX YY ZZ


Performance (P)

0176 P1 0122 0021 0168 0349 0484 0004 0007 0010P2 0232 0041 0169 0443 0387 0007 0018 0016P3 0117 0021 0169 0387 0443 0004 0008 0009P4 0117 0021 0333 0333 0333 0007 0007 0007P5 0183 0032 0169 0443 0387 0005 0014 0012P6 0093 0016 0169 0387 0443 0003 0006 0007P7 0138 0024 0333 0333 0333 0008 0008 0008


0165 SC1 0143 0024 0260 0413 0327 0006 0010 0008SC2 0163 0027 0260 0413 0327 0007 0011 0009SC3 0100 0017 0260 0413 0327 0004 0007 0006SC4 0178 0029 0260 0413 0327 0008 0012 0009SC5 0231 0038 0169 0443 0387 0006 0017 0015SC6 0185 0031 0333 0333 0333 0010 0010 0010


0128 OC1 0138 0018 0163 0540 0297 0003 0010 0005OC2 0203 0026 0169 0443 0387 0004 0012 0010OC3 0186 0024 0333 0333 0333 0008 0008 0008OC4 0168 0021 0333 0333 0333 0007 0007 0007OC5 0146 0019 0196 0493 0311 0004 0009 0006OC6 0159 0020 0200 0400 0400 0004 0008 0008








Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018














Table 11 Continued


(2)Global weight

(3)



XX YY ZZ XX YY ZZ




0069 SB1 0062 0004 0333 0333 0333 0001 0001 0001SB2 0098 0007 0200 0400 0400 0001 0003 0003SB3 0354 0024 0163 0297 0540 0004 0007 0013SB4 0217 0015 0260 0413 0327 0004 0006 0005SB5 0076 0005 0333 0333 0333 0002 0002 0002SB6 0062 0004 0143 0429 0429 0001 0002 0002SB7 0130 0009 0192 0634 0174 0002 0006 0002


0


377 YY

348 ZZ

166 performance




166 social benefit

01 02 03 04 05 06 07 08 09 1 0 02 040301 05



298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018








298 XX

359 YY

342 ZZ

500 life cycle cost

100 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


251 XX383 YY

366 ZZ

100 life cycle cost

501 performance




99 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


265 XX388 YY346 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05



260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018








260 XX391 YY349 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


287 XX383 YY330 ZZ



0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05


250 XX

382 YY

367 ZZ





501 social benefit

0 01 02 03 04 05 06 07 08 09 1 0 02 040301 05




7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018









7 Conclusions




Data Availability




Acknowledgments


References




















































































































































Journal of












Journal of







Volume 2018






Volume 2018






















































































































































Journal of












Journal of







Volume 2018






Volume 2018








anapplicationofanalytichierarchyprocess(ahp)for

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