Performance Efficiency Measurement of Airports: A Comparative Analysis of Airports Authority of India and Public Private Partnership

DOI: 10.4018/IJSDS.2018040102



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Performance Efficiency

Measurement of Airports:

A Comparative Analysis of Airports Authority

of India and Public Private Partnership

Anil Kumar, School of Management, BML Munjal University, Gurgaon, India

Manoj Kumar Dash, Behavioural Economics Experiments and Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India

Rajendra Sahu, Indian Institute of Information Technology and Management, Gwalior, India

ABSTRACT Thisarticledescribeshowtoimprovetheoverallefficiencyandeffectivenessoftheaviationsector andalsotosourceextrafunding,theGovernmentofIndiahaspavedthewayforprivateinvestors throughtoaPublicPrivatePartnership(PPP)modelsincethe1980s.Thisliberalizationstepinthe Indianaviationmarkethasminimizedtheinstitutionalbarrierswhichhavehinderedthefreedomand flexibilityofairtransportoperationsamongprivateinvestors.Now,competitionwithintheaviation sectorhasbecomefiercer;theAirportsAuthorityofIndia(AAI)andPublicPrivatePartnership (PPP)inIndianairportsarenotonlyprovidingvariedservices,butalsoattractingconsumers withnewinfrastructureandfullmodernfacilities.Theimportanceofthisarticleisbecauseafter privatization,nostudieshavebeenconductedtoexaminetheefficiencyofIndianairportsbyusing DataEnvelopmentAnalysis(DEA).Anoutput-orientedDEAmodelisemployedtodeterminethe efficiencyscoreofairportsbytakingasampleof15airports,includingairportsrunbyPPP,for comparison.Output-orientedDEAcalculatestheefficiencybymaximizingtheoutputsforagiven levelofinputs.Therefore,thisarticlecontributestotheexistingliteratureonIndianairports.Basedon availabledata,threevariables-lengthofrunways,terminalsizeandnumberofcheck-incounters,are usedasinputsandtwovariables-passengermovementandaircraftmovement,areusedasoutputs. KEywoRDS

Data Envelopment Analysis (DEA), Efficiency, Privatization, Public Private Partnership (PPP)

INTRoDUCTIoN Thetransportsectorisseenasthelifelineofaneconomy(Koçak,2011).Toalargeextent,thegrowth anddevelopmentofaneconomyisdependentonthegrowthofthetransportsector.Thetransport sectorconsistsofroad,railways,portsandairports.Theairportsectorisconsideredasoneofthe essentialelementsofthetransportsector,asgrowthoftheairportsectoriscrucialfortheoverall growthofthetransportsectorandtheIndianeconomy.Modernandfull-facilityairportscanhelp

Indiatomoveforwardasoneofthemostpowerfuleconomiesoftheworld(Kumaretal.,2017a; Kumaretal.,2017b).Airportsandairlineshavehistoricallybeenconsideredasvitalcomponentsof thenationalaviationsystem,andthereforebothareregardedaspublicutilities.Anearliertraditional airportmanagementmodelwasmoreprevalentbutgovernmentsrealizedthatitisanunsustainable modelinthelongrunbecauseofinefficiencyandtheburdenoffinancingairports.Sincethe1980s, airportshavebeenprivatizedinanefforttobecomemoreefficientandtoallowgovernmentsto usefundinginotherways.Currently,thegovernmentregardsairportsaspotentialprofit-making enterprisesinsteadofjustconsideringthemassuppliersofinfrastructure.

Airport Infrastructure in India

EarlierIndianairportswereadministeredbytheCivilAviationDepartment,GovernmentofIndia, tillthecreationoftheInternationalAirportsAuthorityofIndia(IAAI)in1972andsubsequently theNationalAirportsAuthority(NAA)in1986.AirportsAuthorityofIndia(AAI)wasconstituted byanActofParliamenton1stApril1995.ItcameintobeingbymergingtheerstwhileNational AirportsAuthorityandtheInternationalAirportsAuthorityofIndia.Throughthemerger,adistinct organizationevolvedbeingresponsibleforcreating,improving,maintainingandsupervisingcivil aviationinfrastructure(AirportAuthorityofIndia).AAImanages125airports,whichinclude11 InternationalAirports,8CustomsAirports,81DomesticAirportsand27CivilEnclavesatDefence airfields.ThereportquotedfromAAI(AirportAuthorityofIndia)ontraffictrendsatallairportsof AAIshowsthatintheyears2002-2003,2003-2004and2004-2005passengertrafficincreasedby 9.35%,11.56%and21.5%respectively.Similarly,therewasalsorapidgrowthinfreightandaircraft traffic.Cargotrafficgrewby14.64%,9.1%and19.8%whileaircraftmovementincreasedby9.9%, 14.4%and11.88%respectively. AccordingtothereportoftheInvestmentCommission(InvestmentStrategyforIndia,2006), theencouragingstatisticsonthetrendofhumanpopulationandrapidgrowthintheeconomypoints toacontinuedexpansionindomesticpassengertrafficandinternationaloutwardtraffic.Therisein trafficandcargomovementleadstoover-crowdingsituationsatdifferentairportsinIndia.Thisis apparentinChennai,Delhi,Bangalore,Hyderabad,KolkataandMumbai.That’swhythecountry requiresmodernizationofmetroairports,developmentofnewairports,generationoftechnologyfor efficienttreatmentofpassengers,cargoandbetterpracticesinmanagement.

Public Private Partnership in Indian Airports

SincetherevenuegeneratedbyAAIwasfoundtobeinadequatetosatisfyspendingrequirements, publicprivatepartnershipbecameessentialtobridgethefundinggap.PublicPrivatePartnership(PPP) projectsdeliveraninfrastructureservicewhichisbasedonalong-termcontractbetweengovernment orlegalentityononesideandaprivatesectorcompanyontheother.Itisparticularlytargetedtowards financing,designing,implementingandoperatinginfrastructurefacilitiesandservicesintheState. TheaimofPPPsistoachievetheobjectivesofbothhighgrowthandequityonasustainablebasis. ThroughPPPs,alargenumberofprojectshavebeenacceleratedtomeetthedeficitininvestments; thus,itisanessentialtool.Thecriticallinkbetweeninfrastructurefacilitiesandeconomicgrowth wasrealizedfromtheFirstFiveYearPlanonwardswithoutcomesgivenahighpriorityandmore emphasisplacedonthedevelopmentofinfrastructure.TheIndustrialPolicyResolutionof1956 reservedinfrastructuresolelyforthepublicsectorandasaresult,theGovernmentofIndiatookon theresponsibilityforthedevelopmentofinfrastructure.Iftheoverallinfrastructuredevelopmentis fullyanalyzed,itcanbeseenthatdevelopmentwaslackingtillthebeginningofthe1990s;thereason forthiswasthescarcityofresources.Theliberalizationoftheeconomyintroducedbythegovernment in1991placedspecialemphasisonthedevelopmentofinfrastructureastherewasrecognitionthat ifIndiawastoemergeasastrongnation,theninfrastructurestandardsshouldmatchinternational levels.Infrastructurecoversinvestmentsinroads,highways,airports,portsandrailways.

PPPaddressestheproblemsofinsufficientgroundhandlingsystems,obsoleteinfrastructure, nightlandingfacilitiesandpoorpassengerservices.Otherobjectiveswhichprivateparticipation hastargetedarebuildingairportstobemoreuser-friendlythusachievingahigherlevelofcustomer gratification,buildingworldclassairportsequippedwithmoderntechnologyandbettermanagement practices,focusingoninfrastructuredevelopmentinremoteareas,anticipatingdemandandbuilding airportcapacityaccordinglyandgreatercompetenceinairportoperations.Accordingtothereport bythePlanningCommission(FinancingPlanforairports,2006)metroairportsatDelhi,Mumbai, Bangalore,Hyderabad,ChennaiandKolkataaretobedevelopedthroughPPP.Themajorprojects (PositionpaperontheairportssectorinIndia,2009)developedthroughPPPare: • CochinInternationalAirportisthefirstairportinIndiasetupunderaPPPmodel.The airportcameaboutasamodelenterprisewithequityparticipationfromtheGovernmentof Kerala,industrialists,financialinstitutions,airportserviceproviders,NRIsandthepublic (CochinInternationalAirportLtd.,2007)withatotalspendofaboutRs283crore,occupying approximately1300acresofland.Ithasbeenconstructedinsuchawaythatanytypeoflarge bodiedaircraftcaneasilytakeoffandland.Theairportissituatedsothatthreenationalhighways whichpassthroughKeralaareeasilyaccessible.Theairportwasbuiltinphasestoaccommodate investmentstreamsandtogenerateprofitattheearliestopportunity; • BangaloreInternationalAirportwasbuiltunderaPPPmodel.Theequityparticipationfrom theconsortiumofcompaniessuchasLarsenandToubro,SiemensandZurichAirportis74% whiletheAAIholdstheremaining26%.TheconcessionagreementbetweentheGovernment ofIndiaandBangaloreInternationalAirport.Limited(BIAL)wassignedinJuly2004.BIAL hasexclusiverightstocarryoutthedevelopment,design,financing,construction,management andoperationoftheairportforaperiodof30yearsfromitsopeningdate,withanoptionto extendtheconcessionforanother40years(BengaluruInternationalAirport,2010).Airportarea isapproximately4000acres.TheinitialphaseofairportdevelopmentwascompletedinMarch 2008.Justonephaseofthemasterplaniscompleteandthereisampleexpansionscope.The airporthasarunwaylengthof4000mwhichis60mwideandhasthreerapidexitswhichlead aircrafttoleavetherunwayjustafterlanding.Inthiswaythereisoptimumuseoftherunway; • HyderabadInternationalAirport:TheassociationofGMRInfrastructureLimitedandMalaysia AirportsHoldingsBerhadwaschosentodevelopGreenfieldInternationalAirportatShamshabad nearHyderabad.TheGMRgroupholds63%oftheequity,MalaysiaAirportsHoldingsBerhad 11%whiletheGovernmentofAndhraPradeshandAAIhold13%each.Theprojectisprepared onaBuild,Own,OperateandTransferbasis(HyderabadRajivGandhiInternationalAirport, 2013).Theairportareaisapproximately5400acres.Theairporthasworldclassfacilitiesand infrastructure.ItismadeinaccordancewithICAOstandards.Ithasthecapacitytohandlelarge aircraft;otherfacilitiesincludeself-checkincounters,CUTEsystemsandmodernITsystems. ThetotalcostoftheprojectisRs2,370crore; • MumbaiInternationalAirportisanassociateofGVKIndustriesLtdandAirportsCompany SouthAfrica,assignedwiththetaskofdevelopingtheexistingMumbaiAirportinFebruary 2006.TheequityparticipationoftheGVKledconsortiumis74%withAAIholding26%.The airportcurrentlyhasthreedomesticandtwointernationalterminals.MIALisnowimplementing amasterplantobuildanintegratedterminal.Aftermodernization,thenewintegratedterminal willbereferredtoasT2andwillbeabletoaccommodate40millionpassengersperannum; • DelhiInternationalAirportisoneofthemajorinternationalairportsfromthepublicprivate

partnership initiative. It is a joint venture of AAI, Fraport, Eraman Malaysia and GMR Infrastructure, tasked with modernizing the airport. DIAL entered into an Operations, ManagementandDevelopmentAgreement(OMDA)onApril4,2006withtheAAI(Delhi IndiraGandhiInternationalAirport,2013).Theinitialtermoftheconcessionis30yearswhich canbefurtherextendedbyanother30years.Thedevelopmentofthenewdomesticdeparture

terminal1D(T1D)wascompletedon26thFebruary,2009.Thisterminalhasseenanincrease inthecapacityofdomesticdeparturesto10millionpassengersperannum.Terminal3,opened inMarch2010,isastate-of-the-artintegratedterminalwithcapacitytoaccommodate60million passengersperannum.Ithasothersalientfeaturessuchasanareaof5.4millionsquarefeet,95 immigrationcounters,over20,000squaremetresofretailspaceandarecord78aerobridges. Thisformedthefirstphaseoftheairportdevelopment.Withanincreaseintrafficandpassenger demand,moreterminalsandrunwayswillbeaddedinwhichaUshapedbuildingwillbe developedinamodularmanner. Muchinvestmenthasbeenmadebythegovernmenttodeveloptheinfrastructuresincethestatus ofphysicalinfrastructureclearlyaffectsacountry’syield,competitivenessinglobalmarketsand powertodrawforeigninvestments.Butinvestmentsininfrastructurerequireahugeamountoffunds duetothelargesumsofmoneyinvolved;henceitisdesirabletocombinetheskills,proficiencyand experienceofboththepublicandprivatesectors.Sincethe1990stherehasbeenaspeedygrowth ofPPPsaroundtheworld.PPPrepresentsawin-winsituationasthegovernmentearnsrevenueby rentingstate-ownedassetsorinsteadpaystheprivatesectorforimprovedinfrastructureandbetter deliveryofservice;oftentheprivatesector,byuseofitsskillsandexpertise,candothejobmore effectivelyandefficientlyandcanthuslowerprices.Theprivateoperatoraimsforpaybackfor expensesincurredeitherbygovernmentorconsumersfordoingitswork,ataprofit.But,thereare severalproblemswithPPPaswellaslimitationsandchallengestobefaced.Therehavebeenmany casesoffailureofprojectsduetocost-overrun,time-overrunandunacceptablequalityofoutcome. Therefore,itbecomesincreasinglyimportanttolookintotheimpactandeffectivenessoftheprojects undertakenthroughthePPPmodeltodeterminetheextentofsuccess.Asforthecurrentstatusof PPP,thenumberofprojectsintheairportsectorcomprisesjust1%ofthetotalprojects.Thissector hasalotofpotentialforgrowthasconsumersdemandairportswithexcellentandmodernfacilities; thisgrowthleadstothebettermentoftheeconomy.Nodiscussionisavailableinexistingliterature aboutmeasuringthecomparisonefficiencyofIndianairports.Therefore,thisstudyisanattempt toplugthisgapwithDEAtechniquesusedtocomparetheefficiencyofprivatizedairportswith airportsunderAAI. Therestofthisstudyisorganizedasfollows.Insection2,previousrelatedstudieshavebeen reviewed.Insection3,methodologyispresented.Insection4,analysisanddiscussionareexplained. Insection5,theresearchfindingsarediscussedwithmanagerial/practicalimplicationsdrawnup. LITERATURE REVIEw Theliteraturereviewofthisstudyisdividedintotwoparts1)publicprivatepartnershipstudies,and 2)airportefficiencystudies.Adescriptionofthesestudiesfollows.

Public Private Partnership Studies

Pillai(2008)identifiestheimportanceofefficientandhigh-qualityinfrastructureforbalanced developmentoftheIndianeconomy.ItsfindingsaretillJune2006when837projectswerecomplete. ThetotalexpenditureincurredfortheseprojectswasaboveRs.20crandthetotalestimatedinvestment amountedtoRs.369499cr.Theseinvestmentswerespreadacross16strategicallyimportantsectors oftheIndianeconomy.Accordingtothisstudytherehasbeenasignificantdeclineinthecostoverrun ofvariousprojects,indicatingimprovedimplementalefficiencyoftheprojects. Manzoor(2010)discussestheimportance,challengesandcriticismsregardingIndianairports. Heconcludesthatsincetherewasahugegrowthintraffic(bothpassengerandcargo),thegovernment feltitnecessarytodevelopairportinfrastructure.In2007,MumbaiandDelhihandled25.2million and23.3millionpassengersrespectively.In2006theseairportswererankedastheworld’s55th

and61stbusiestairports.Tocreateinfrastructuretohandlesuchtraffic,thegovernment,lackingin funds,optedforPPP.ManyoftheIndianairportsfaceseriousinfrastructureconstraints.Someof theseconstraintsarepoorlymaintainedrunways,lackofInstrumentLandingSystems,runwaysnot suitabletoaccommodatetheworld’slargestaircraft,e.g.thesuperjumboairbusA-380andlackof nightlandingfacilities.Hence,efficiencyisthemostcommonandimportantmotivationtoprivatize theairports.Anothermajorproblemispoorconnectivitytotheairports.Privatizationcanhelpin providingfundstoaddressthis.Otherbenefitsofprivatizationareexpandingtheoperationofduty-freeshops,creatingmorerevenueandjobsandprovidingefficientcargofacilities.Thecriticisms highlightedarethatprivatizationwillleadto40%joblessandhigherunemployment,itwillhurt nationalsecurityandAAIwillloseitsimportance.Supporters’viewsonairportprivatizationare thatmodernairportinfrastructurewillleadtobetterperformanceoftheIndianeconomy,increased operatingefficiency,developmentinthetourismindustry,recruitmentofqualifiedandtalented employeesandprovisionofgreatercustomersatisfaction. Ohri(2009)givesthejustificationforairportprivatizationinIndia,drawingfrominternational experience,withafocusonthedevelopingcountries.ThegapsbetweenIndianandinternational airportsiscalculatedbyusingarangeofoperatingandfinancialmetricstoidentifypossibleareas forimprovement.ThereportcomparedtheUniqueZurichgroup,Brusselsairport,Vienna,Indian airportsandtheBritishAirportAuthorityonvariousoperatingandfinancialfigures(2004-2005) onthreebroadfactors.Thesefactorsare1)Revenuebasedfactorswhichincludefiguressuchas totalrevenueperpassenger,totalrevenueperemployeeetc.2)Profitbasedfactorswhichinclude operatingprofitperpassenger,returnoncapitalemployedetc.and3)Input-outputbasedfactorssuch astotalcostperairtransportmovement,staffcostperpassenger,staffcostperemployeeetc.The reportfoundthatIndianairportshaveahighpercentageofaeronauticalrevenue,lowcommercial revenueperpassenger,verylowrevenueperemployee,lowoperatingprofitperpassenger,lowstaff costperemployeeandahighpercentageofstaffcostinthetotalcost.Thereportconcludedthat workforcerationalizationandincreasingcontributionofnon-aeronauticalrevenuearethetwomajor developmentsforthebusinessmodelsofIndianairportstofocuson. ThereareanumberofstudiesfromJuan(2005)andButton(2006)supportingthefactthat carefullydesignedconcessioncontractsandbuildingappropriatecontrolsareessentialforeffective privatization.ButinthecaseofbiddingprocessesofbothDelhiandMumbai,theprocessitselfwas questionedatvariouslevels.Pandeyetal.(2010)identifiedtheproblemsfacedinthebiddingprocesses ofDelhiandMumbaiairports.AnoriginalcompletiondateofSeptember2004wasmissedduetoa varietyofreasons;theprocesswasthenpostponedwithfinalbidsreceivedbySeptember2005.After takingadvicefromexperts,thefinaldecisionwasmadeinJanuary2006bytheempoweredgroupof ministers.Ministerscompromisedonsomeoftheirownsetofparameters.Oneofthelosingbidders (Reliance)hadappealedtotheHighCourtagainstthedecisionoftheselectionofjointventurepartners. TheHighCourtdismissedtheappealandtheairportprivatizationeffortscontinued.Therefore,it isconcludedthattherearevariousfactorsonwhichtheefficiencyofairportprivatizationdepends. Airport Efficiency Studies

Thereareseveralstudieswhichfocusondeterminingairportefficiency.Thereareonlyafewstudies onairportefficiencybefore2000;theseincludeParker(1999)andGillenandLall(1997).Mostofthe studiesonairportefficiencyhavebeenconductedafter2000.Thisindicatesthatthisareaofstudyhas becomemorepopularinrecentdecades.Thismaybeduetoincreasedcompetition,increasedpressure oftrafficandprivatizationofairports.Therearevariousmethodstodetermineairportefficiencysuch asPartialFactorProductivity(PFP),TotalFactorProductivity(TFP),StochasticFrontierAnalysis (SFA)andDEA(DataEnvelopmentAnalysis). PartialFactorProductivitydealswiththeratioofoneoutputtotheratioofanotherinput(Oum etal.,2004).Thistechniqueissimpletousebutthedrawbackisthatitdoesnotgiveanyideaabout overallefficiency.ThemostcommonusedoutputsinPFAtechniquearethenumberofpassengers,

ATMsandcargomovements.PFAfocusesonlabor,capitalandfinancialproductivity.TotalFactor Productivityestimatestheoverallefficiencyofairports.Thistechniqueweightsinputsandoutputs accordingtotheirimportanceinproductionfunctionandbuildsupanindexfortheendresult. StochasticFrontierAnalysisisaparametrictechniquewhichcalculatestherelativeefficienciesof airports.Butthedrawbackwiththistechniqueisthatitrequiresaproductionfunctionofanairport toconstructaproductionfrontier.OntheotherhandDEAdoesnotrequirethespecificationofa productionorcostfunctiontoestimatetheproductionfrontier.ThisisthereasonwhyDEAisthe mostwidelyacceptedtechniquefordeterminingairportefficiency.

Different research studies have used different methods and models to determine airport efficiencies.Parker(1999)usedDEA-CCRandBCCmodelstodeterminetheperformanceof BritishAirportAuthoritybeforeandafterprivatization.Thestudyusedinputssuchasnumberof employees,operatingcostandcapitalinputandoutputssuchasnumberofpassengers,turnoverand cargo.ItanalyzedthechangesintechnicalefficiencyofBAAovertimefrom1979/80to1995/96. TheresultsshowedthattherewasnosignificantimprovementinefficiencyofBAAoverthisperiod. Someresearchpapersdeterminedairportefficiencyinsegments(Pelsetal.,2003;GillenandLall, 1997).Foreachsegmentofstudy,theseresearchershaveuseddifferentinputsandoutputs.In1997, GillenandLallusedtwosegmentstodetermineairportefficiency;theseareterminalservicesand movementmodel.Fortheterminalservicessegments,thenumberofrunways,numberofgatesand terminalareawereusedasinputs;outputswerenumberofpassengersandcargo.Themovement modelusednumberofrunways,runwayarea,airportareaandnumberofemployeesasinputs; outputswereaircargomovements.Anoutput-orientedmethodwasusedtodeterminethechanges inefficiencyofairports.HeriBezić(2010)analyzedtheoverallefficiencyofCroatianairportsover afiveyearperiodfrom2004to2008.Thestudyusedinputssuchasoperatingcostandnumberof employees;outputwastotalrevenue.Thisrevealedthatonlytwoairportswereefficientperformers whencomparedtotheotherairports. Sarkis(2000)assessedtheoperationalefficienciesof44majorU.S.airports.Theinputmeasures takenforstudywerenumberofairportemployees,airportoperationalcosts,gatesandrunways;output measuresincludepassengerflow,operationalrevenue,commercialandgeneralaviationmovement andtotalcargotransportation.Theresultsofthestudyshowthatoverallmeanefficiencyofmajor USairportsincreasedthroughtheyearsfrom1990to1994withasmalldroprecordedin1993. Koçak(2011)determinedtheefficiencyofTurkishairportsfortheyear2008byusingaDEA approach.Theinputvariablestakenareoperationalexpenses,numberofpersonnel,flighttrafficand numberofpassengers;outputvariablesarenumberofpassengers/area,flighttraffic/runway,total loadandoperationalrevenue.ItusesbothCCRandBCCmodelstodetermineefficiency.Outof40 airports,only7airportsarefoundtobeefficient.Thereareseveralotherstudieswhichhaveused differentinputsandoutputsbasedontheavailabilityofdata.InastudybyPelsetal.(2003)todetermine theefficiencyofEuropeanairports,bothDEAandSFAmethodshavebeenused.Accordingtohis study,bothmethodsshowedroughlythesameresults.Numerousresearchpapersinthisareashow thatdeterminingairportefficiencyisimportantandthatDEAisawidelyacceptedtechniqueforthis. METHoDoLoGy Data Description Inthisstudy,15internationalairportsaretakentoensurecomparisonofefficiency.The15airports include5privatizedairports;theseareDelhi,Bangalore,Hyderabad,NagpurandCochin.10are AAIairports.TheinputdataofAAIairportsistakenmostlyfromtheAirportAuthorityofIndia databasewhiletheinputdataofprivatizedairportsistakenfromvariousrelevantsources.Theoutput dataofalltheairportsisobtainedfromtheAAIdatabase.Basedontheavailabilityofdata,three variablesaretakenasinputs-lengthofrunways,terminalareaandnumberofcheck-incounters

(includingcommon-useself-servicekiosks).Theoutputvariablesarecomprisedoftwovariables -totalpassengermovementsandtotalaircraftmovements.Theinputdatahasbeenobtainedfrom varioussourcesfortheyear2012andtheoutputdatarecordedfortheperiodApril2011toMarch 2012.Table1displaysthedataobtained. AsthestudyisconcernedwiththeuseofDEAtodeterminethetechnicalefficiencyofairports, adetaileddescriptionofthetechniqueisdiscussed.

Data Envelopment Analysis (DEA)

Inliterature,DataEnvelopmentAnalysisisdefinedasatooltomeasureefficiencyfornon-parametric frontier-efficiency(Charnesetal.1978).Forhomogenousentities,DEAdeterminestherelative efficiencyofasetofDMUs.Cooperetal.(2011)definedrelativeefficiency.“DMUistoberated asfully(100%)efficientonthebasisofavailableevidenceifandonlyiftheperformancesofother DMUsdoesnotshowthatsomeofitsinputsoroutputscanbeimprovedwithoutworseningsomeof itsotherinputsoroutputs.”Itisnotedthatthisdefinitiondoesnotmentionanykindofassumptions suchastherequirementofweightsoranykindofrelationthatexistsbetweeninputsandoutputs. Thisbasicefficiencyistermedas“technicalefficiency”(DuandSim,2016).Thisefficiencycanbe extendedtootherareassuchasallocativeefficiencyandeconomicefficiency,whendatarelatedto unitcost,price,etc.isavailable.DEAanalyzestheefficiencyofaDMUbycomparingitwiththe bestDMUinthegroupofunitsunderconsideration. ThebasicideainDEAistodevelopthe“bestpractice”productionfrontier(DuandSim,2016). Withreferencetothisfrontier,thepositionofinefficientunitsisdeterminedandalsothesource andamountofinefficiencycanbeidentified.DEAisanimportantproductivityanalysistoolthatis extensivelyappliedinthecaseofmanufacturingandserviceoperationstoevaluatetheirperformance. Sincethistechniquerequiresveryfewassumptions,itcanbeappliedinthosecontextswhereother Table 1. Data of international airports in India

Name of Airports

Inputs Outputs

Length of Runways (m) _{Size (sq.m.)}Terminal Counters _{Checkin Movements}Passenger _MovementsAircraft

Delhi 11053 536676 256 35881965 295491 Bangalore 4000 73347 71 12698343 118431 Hyderabad 7967 105000 146 8444431 99013 Nagpur 5138 17500 20 1415739 15322 Kolkata 6466 65355 94 10303991 99843 Chennai 5690 62120 93 12925218 120127 Amritsar 3658 4000 30 892104 9208 Jaipur 2797 22709 16 1828304 18603 Ahmedabad 3505 70423 62 4695115 40506 Guwahati 2743 8655 14 2244684 28088 Trichy 2480 11700 12 908771 9583 Calicut 2860 118981 35 2209716 16150 Thiruvananthpuram 3398 45863 48 2814799 27239 Goa 3480 15897 37 3521551 27430 Cochin 3400 53698 27 4717650 40181

techniquescan’toperatebecauseofthecomplexitiesinvolvedinthem.In1957,Farrellextended theconceptofproductivityandintroducedtheconceptof“efficiency”.BasedonFarrell’swork,in 1978,Charnesetal.proposedtheinitialmodelofDEAknownastheCCRmodelwithassumption aninputorientationandassumedconstantreturnstoscale(CRS).

CCR and VRS DEA MoDEL

AccordingtothestudybyTalluri(2000)theefficiencyscoreinthepresenceofmultipleinput-outputs canbedefinedas:

Efficiency = weighted sum of outputs

weighted sum of inputs  (1)

AssumethattherearenDMUstobeevaluated.EachDMUhasminputsandoutputs.The relativeefficiencyofatestDMUpcanbeobtainedbythemodelproposedbyCharnesetal.(1978): max u y v x k kp k s j jp j m = =

∑

∑

1 1  s t u y v x i k ki k s j ji j m . = =

∑

∑

≤ ∀ 1 1 1  (2) u v_{k j} ≥0 ∀k j, ,wherei=1……n y_{ki=amountofoutputkproducedbyDMUi} x_{ji=amountofinputjconsumedbyDMUi} u v_k, _j=weightgiventooutputkandinputj,respectively Theabovemaximizationproblemcanhaveaninfinitenumberofsolutions.Ifu v*_, *_{aresolutions}

tothisproblemthenitcanbeshownthatanyθ θ, _u*_andθv*_{arealsosolutionstothesameproblem.} Henceθcannotbeidentified.So,inordertoavoidthisproblem,ithasbeenconvertedfromafractional programintoalinearprogrammingequivalent: max

∑

s_k= µ_{k kp}y 1  s t.

∑

m_j=1v x_{j jp}=1 µ_{k ki} m_{j j jp} k s y − ₌v x ≤ ∀i =

∑

∑

1 1 0  µ_{k j}v ≥ ∀0 k j, 

Theaboveformisknownasmultiplierformofalinearprogrammingproblem.Theproblem isrunntimes,onelinearprogrammingproblemforeachDMU.EachDMUselectsitsinputand outputweightssothatitsefficiencyscoreismaximized.AccordingtothestudybyCharnes etal.(1978),DEAassignsascoreof1orlessthan1.Ascoreof1meansthatwhentheDMU iscomparedwiththeotherunitsinthesamplethereisnoindicationofinefficiencyinany inputoroutput.Ascoreoflessthan1meansthattheDMUisrelativelyinefficienti.e.alinear combinationofotherunitsunderconsiderationcanproducethesameoutputvectorbyusing asmallerinputvector.Usingthedualityinlinearprogramming,theequivalentenvelopment formofthisproblemis: minθ s t x x j y y k i ji jp i n i ki kp i n . λ θ λ θ − ≤ ∀ − ≤ ∀ = =

∑

∑

0 0 1 1  (4) λ_i ≥0 ∀i whereθistheefficiencyscoreandλ=dualvariables. Thedualityformhaslessconstraintthanthemultiplierformandhenceitisapreferredmethod touse.Coelli(1996)hassimplifiedthedualityformbytakingtheinputsandoutputsinvectorform. AssumingthatthereisdataonKinputsandMoutputsoneachofNDMUs,thenforthei-thDMU theinputandoutputarerepresentedbyvectors.TheinputmatrixX(K×N)andtheoutputmatrixY (M×N)representthedataofallNDMUs.Thentheenvelopmentformis: min_{θ λ,} θ s t. − +y_i λY ≥0 θx_i−Xλ≥0 (5) Λ ≥0 whereλisaN×1vectorofconstantsandθisscalar.Θwillgivetheefficiencyscoreofthei-thDMU. The above envelopment and multiplier models are input-oriented i.e. how much input can be proportionally reduced without altering the output quantity. In the case where the DMUshavelesscontrolovertheoutputside,input-orientedmodelsareused.Asopposedto theinput-orientedmodels,output-orientedmodelsexistwhichdeterminebyhowmuchthe outputquantitiescanbeproportionallyexpandedwithoutalteringtheinputconsumed.Itmay beusedincaseswhereDMUsaregivenafixedquantityofresourcesandtheyneedtoproduce asmuchoutputaspossible.Theoutputorientedenvelopmentmodelis(Cooperetal.,2011) wheremrepresentsanumberofinputs,sanumberofoutputsandnthenumberofDMUs. ThentheefficiencyofDMUocanbedeterminedconsideringDMU_jconsumesx_ijofinputi andproducesy_rjofoutputr:

maxΦ subjectto: λ λ φ j ij io j n j rj ro j n j x x y y − ≤ − ≥ = ≥ =

∑

∑

0 0 1 0 1 Λ  (6)

whereivariesfrom1tom, rfrom1tos, jfrom1ton. Multiplierformofoutput-orientedmodelis: minq=

∑

_im₌₁u x_{i io}  subjectto: v x_{j ij r}s _{r rj}y i m − ₌ ≥ =

∑

∑

_{1 1}µ 0 µ_{r ro} r s y = =

∑

₁ 1 µ_{r i}v > ∀0 r i,  (7) Therefore,basedonwhichquantitythemanagershavemorecontrolover,theappropriate orientationcanbeselected.Figure1and2showthetechnicalefficiencyfrominputorientation andoutputorientationrespectively.Figure1showsanillustrationbyFarrell(1957)usingasimple exampleinvolvingtwofirmsusinginputsx1andx2toproduceasingleoutputy.SS´representsthe efficiencyfrontier.SinceDMUQliesonthefrontier,thismeansthatitsefficiencyscoreis1.On theotherhand,thefirmPisinefficientsinceitliesabovethefrontier.ThedistanceQPrepresents Figure 1. Technical efficiency from input-orientation (Coelli, 1996)

thetechnicalinefficiencyofthefirm.TheratioQP/OPrepresentsthepercentagebywhichallinputs couldbereduced.ThetechnicalefficiencyofthefirmisdefinedasOQ/OP. Similartotheabovecasetheoutput-orientedmeasurecanbeillustratedbytakingthecasewhere thefirmproducestwooutputsy1andy2andconsumesoneinputx1.ThecurveZZ´representsthe efficientfrontieri.e.theupperboundaryofproductionpossibilities.SincetheDMUBliesonit, itistechnicallyefficientandhasanefficiencyscoreof1.DMUAliesbelowthecurve;henceitis inefficient.ThetechnicalinefficiencyofDMUAisrepresentedbydistanceAB.Hencetheoutput orientedtechnicalefficiencyforDMUAisOA/OB.Theinput-orientedandoutput-orientedmeasures willgiveanequivalenttechnicalefficiencyscoreinthecaseofconstantreturnstoscalebuttheywill beunequalwhenincreasingordecreasingreturntoscaleexists.Iftheconstraint(8)(Coelli,1996) isaddedthenitisknownastheBCCmodelafterBankeretal.(1984).VRSandCRSDEAoperate onthesamedata.IfthereisadifferencebetweenthetwoscoresthismeansthattheDMUisnot operatingatoptimalscale: λ_j j n = =

∑

₁ 1 (8) CRSmodelefficiencyscoreisfurtherbrokendowntoscaleefficiencyandpuretechnicalefficiency: E_CCR =E_SCALE *E_BCC (9) Figure3(Pelsetal.,2003)showsboththeproductionfrontiersVRSandCRS.Thetechnical efficiencyscoreforthepointDunderCRSisAB/AD,whilethetechnicalefficiencyscoreunder VRSisAC/AD.TheefficiencyscoreunderVRSisalwaysgreaterthanorequaltotheCRSscore becauseVRSformsaconvexhullofintersectingplaneswhichenvelopethedatamoretightly.The scaleefficiencyisECCR/EBCC.So,scaleefficiencyscoreisAB/AD.Thedrawbackwiththismeasure ofscaleefficiencyisthatitdoesnotindicatewhethertheDMUisoperatingatanincreasingreturn toscaleoradecreasingreturntoscale.Todeterminethis,constraint(8)ischangedto: λ_j j n ≤ =

∑

1 1 

IfthescoreobtainedbyaddingthisconstraintisthesameastheVRStechnicalefficiencyscore, thendecreasingreturnstoscaleexistandiftheyareunequalthenincreasingreturnstoscaleexist. CRSassumesthatincreaseininputsleadtoproportionateincreaseinoutputs.Thismeansthatin whicheverscaletheunitoperates,itsefficiencywillnotchange.ButinthecaseofVRS,increasing ordecreasingreturnstoscaleexist.Increasingreturnstoscalemeanthatanincreaseinunitinput leadstogreaterthanproportionateincreaseinitsoutputswhiledecreasingreturnstoscalemeanthat anincreaseinunitinputleadstolowerthanproportionateincreaseinoutputs.

ANALySIS AND DISCUSSIoN

Anoutput-orientedDEAmodelisusedfordeterminingtheefficiencyscoreofairports.Output-orientedDEAcalculatestheefficiencybymaximizingtheoutputsforagivenlevelofinputs.Inthe caseofairports,factorsofproductionarefixedorsemi-fixed;anoutput-orientedmodelshowshow intensivelyairportresourcescanbeutilized.Also,itisnoteasyformanagerstodisinvestoncecapital isdedicatedtoconstructingnewrunways,terminalsandotherinfrastructure.Itisassumedthatthe DMUsoperateatoptimalscalesotheCRSmodelisused.Inordertocomputeefficiencyscores,the DEAPVersion2.1computerprogramisused.Table2showstheresultsobtainedfromtheprogram. CRSscorescanbefurtherbrokendownintoVRSefficiencyandscaleefficiency.Theresults obtainedbyapplyingtheVRSmodelareshowninTable3.InthecaseoftheVRSmodel,efficiency scorerisesasinthiscase,airportsofsimilarsizearecomparedwitheachotherandnotwiththebest onesinthesampletaken. ItisnotedthatinthecaseoftheBCCmodel7outof15airportshaverelativeefficiencyscore of1.These7airportsaremadeupof3privatizedairports-Delhi,BangaloreandCochinand4AAI airports-Chennai,Amritsar,GuwahatiandTrichy.Inthecaseofprivatizedairports,thelowest efficiencyscoreisatNagpuri.e.0.422.Thismeansitis42.2%efficientwhencomparedtotheairports withanefficiencyscoreof1.Publicairportsefficiency(exceptairportshavingefficiencyscore1) variesfrom0.362to0.954.ThelowestefficientAAIairportisThiruvananthapuramaccordingto theresults.Itisfoundthat8airportsareoperatingatincreasingreturnstoscale,3withdecreasing returnstoscaleand4ofconstantreturnstoscale.Scaleefficiencyvariesfrom0.442to1.Inthecase Figure 3. Production frontier

Table 2. Efficiency scores under CRS model

Airports CRS Efficiency Score

Delhi 1 Bangalore 1 Hyderabad 0.524 Nagpur 0.417 Kolkata 0.778 Chennai 1 Amritsar 0.86 Jaipur 0.659 Ahmedabad 0.423 Guwahati 1 Trichy 0.442 Calicut 0.353 Thiruvananthpuram 0.341 Goa 0.931 Cochin 0.977

Table 3. Efficiency scores under VRS model

Airports CRSte VRSte Scale Delhi 1 1 1 -Bangalore 1 1 1 -Hyderabad 0.524 0.728 0.720 drs Nagpur 0.417 0.422 0.988 irs Kolkata 0.778 0.823 0.945 drs Chennai 1 1 1 -Amritsar 0.860 1 0.860 irs Jaipur 0.659 0.699 0.942 irs Ahmedabad 0.423 0.53 0.799 irs Guwahati 1 1 1 -Trichy 0.442 1 0.442 irs Calicut 0.353 0.573 0.616 irs Thiruvananthapuram 0.341 0.362 0.942 irs Goa 0.931 0.954 0.980 drs Cochin 0.977 1 0.977 irs te = technical efficiency

ofTrichyairport,theinefficiencyisduetoscaleonly.Theaverageefficiencyscoreinprivatized airportsis0.83whileinAAIairportsitis0.79i.e.agapofaround4%.Thisshowsthatprivatized airportsonaveragearebetterinefficiencywhencomparedtopublicairports. Table4illustratesthesummaryofoutputtargetsandinputtargetsforeachairport.Itshows thetargetstobeachievedsothattheairportscanoperateatanefficiencyscoreof1.Thus,for exampleHyderabadcouldhaveachievedtheoutputtargetofpassengermovementofpassenger movementsofapproximately14999547.081andaircraftmovementof135972byreducingthe inputsi.e.lengthofrunwayto6174m.Table4showsthepeersforeachairport.Thenumber oftimesanairportactsaspeerhelpsinidentifyingthebestpracticeswithinthesector.Peers identifythesetofefficientairportswhichmakeuptheappropriatefrontierforagivenairport. Airports which are technically efficient don’t have other airports as peers while inefficient airportshaveabenchmarkwhichiscomposedbyotherDMUs.Apeercanbeidentifiedasmore orlessimportantbasedontheweightassignedtoitintheBCCmodelwhichisexpressedby “lambda(λ)”.ItisseenthatBangaloreappears6timesasatargetfortherestoftheairportsand hencecanbeconsideredasabenchmark.Managersoflessefficientairportsshouldimprove theirperformancebylearningfromtheexperiencesofthoseairportswhicharedoingbetter- Bangalore,Guwahati,Delhi,ChennaiandCochin.

The technical efficiency score obtained shows that four out of 15 airports are efficient airports,havingmaximumefficiencyvalueof1.Thismeansthattheseairportscouldneither increasetheiroutputwithoutincreasingtheirinputsnorreducetheirinputswithoutreducing theoutput.Thesefourairportscomprisetwoprivatizedairports-DelhiandBangaloreandtwo publicairports-ChennaiandGuwahati.Thisshowsthatoutoffiveprivatizedairports,two airportshaveefficiency1,whileinthecaseofpublicairportstwoairportshaveefficiency1 outofatotalof11airports.Thetechnicalefficiencyofotherpublicairportsvariesintherange Table 4. Summary of airports with peers

Airport PEERS With Optimal Lamdas (λ)

Delhi 1 Delhi

Bangalore 1 Bangalore

Hyderabad 0.91 Chennai 0.09 Delhi

Nagpur 0.843 Guwahati 0.067 Cochin 0.09 Bangalore

Kolkata 0.004 Bangalore 0.007 Delhi 0.989 Chennai

Chennai 1 Chennai

Amritsar 1 Amritsar

Jaipur 0.027 Cochin 0.944 Guwahati 0.029 Bangalore

Ahmedabad 0.674 Bangalore 0.326 Trichy

Guwahati 1

Tiruchirapalli 1

Calicut 0.75 Trichy 0.25 Bangalore

Thiruvananthapuram 0.224 Guwahati 0.565 Bangalore 0.211 Trichy

Goa 0.865 Guwahati 0.135 Chennai

from0.34to0.97.Ofthemajorairportsi.e.Delhi,Bangalore,Hyderabad,Kolkata,Chennai andCochin-Delhi,BangaloreandChennaiarefoundtoberelativelyefficientwithanefficiency scoreof1whileCochinandKolkatahavehighrelativeefficiencyscoreswhencomparedwith Hyderabad.ThemeanefficiencyscoreundertheCRSmodelis0.714.Theaverageefficiency scoresinprivateairportsis0.788whileinpublicairports,thescoreis0.678.Thegapisaround 11%.ComparativeefficiencyscoresarealsoshowninFigure4.

THEoRETICAL AND MANAGERIAL IMPLICATIoNS

Therehavebeenresearchworksinthepastwhichdealwithassessingworldwideairportefficiency. ThisresearchdealsprimarilywithapplyingDataEnvelopmentAnalysistoassesstheefficiencyof Indianinternationalairportsbytakingasampleof15airports.Sincesomeofthemajorinternational airportssuchasDelhi,Bangalore,Hyderabad,CochinandMumbaiarebeingdevelopedthrough publicprivatepartnership,thestudyaimstofindoutwhetherairportsoperatingunderPPPare relativelymoreefficientwhencomparedtotheairportsmanagedbytheAirportAuthorityofIndia. Todeterminetherelativeefficiencyscoreanon-parametric,linearprogrammingbasedDEAtechnique isutilized.Anoutput-orientedCCRmodelisusedtoestimatetheefficiencyof15Indianairports fortheyear2011-2012. NoneoftherecentresearchworkshaveusedDEAtoanalyzetheefficiencyofIndianairports afterprivatization.Therefore,thisstudyisusefulincontributingtotheexistingliteratureon Indianairports.Basedontheavailabledatathreevariables(input)-lengthofrunways,terminal sizeandnumberofcheck-incounters-areusedasinputsandtwovariables(output)-passenger movementsandaircraftmovements-areusedasoutputs.TheresultsoftheDEAshowthatof thefiveprivatizedairportstakenforthestudyi.e.Delhi,Bangalore,Hyderabad,Cochinand Nagpur,theefficiencyscoreofthreeairports-DelhiBangaloreandCochinisfoundtobe1;in thecaseofpublicairports,theefficiencyofChennai,Amritsar,GuwahatiandTrichyisfound tobe1.Theaverageefficiencyscoreinprivatizedairportsis0.83whileinAAIairportsitis 0.79i.e.agapofaround4%.Thisshowsthatprivatizedairportsare,onaverage,moreefficient whencomparedtopublicairports.Thetargetvaluesfromtheanalysisshowthevaluetowhich theoutputscanbeincreasedtoenhanceefficiency. Thisresearchworkcanbefurtherextendedtoincludemoreinputssuchasoperatingcostsand numberofemployeesandmoreoutputssuchasoperatingrevenue,cargohandled,etc.Sincesome Figure 4. Relative efficiency score of the airports

oftheseairportservicesandinfrastructureaspiretocompetewithworld-classairports,thenitwill beinterestingtocomparethesemajorIndianairportstoairportsofcomparablesize,andasimilar environmenttodeterminehowfarIndianairportshaveprogressed. ACKNowLEDGMENT Theauthorswouldliketothanktheanonymousreviewersandtheeditorfortheirinsightfulcomments andsuggestions.

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Anil Kumar is a faculty member of Decision Science in the School of Management at BML Munjal University, Gurgaon, India. He completed his PhD in Management from Indian Institute of Information Technology and Management, Gwalior. He holds an MBA, MSc (Mathematics) and Graduation in Mathematics-Honors. He also qualified UGC-NET. He has published more than 30 research papers/book chapters and four books. His research interest includes operation management, marketing analytics, multi-criteria decision making, fuzzy multi-criteria decision making, fuzzy optimization, application of soft-computing, econometrics modelling, fuzzy multi-criteria decision-making applications in sustainability, customer retention, sustainable, development, performance management, and decision modelling.

Manoj Kumar Dash is currently an Assistant Professor in the Department of Management at ABV-Indian Institute of Information Technology and Management, Gwalior, India. He earned his MA, MPhil, PhD and MBA in Marketing from Berhampur University, Berhampur (Orissa). He published more than 60 research papers in various journals of International and National repute. He is the author of three books and edited five books. He was involved as Chair Member in conducted International Conference of Arts and Science held at Harvard University, Boston (USA). His areas of research are: marketing science, consumer behavior, behavior economic, decision making modelling, fuzzy multi-criteria optimization, and marketing research.

Rajendra Sahu is a Professor in the Department of Management at ABV-Indian Institute of Information Technology and Management, Gwalior, India. Dr. Sahu has done his PhD from IIT, Kharagpur after completing his MSc (Engg.) and MIM. He has been associated with the teaching profession for the past 20 years, and has been closely involved with industrial consultancy projects, and as an external Consultant for IIT, Kharagpur. Management Consultancy has been his forte. He has been associated with prestigious projects in the past and has also published about 90 papers in his areas of proficiency and interest. His primary areas of interest are Systems Approach to Management, Business Process Management, Business Analytics, e-Commerce, and IT enabled Services. He is currently the Secretary of Systems Dynamics Society of India.