Revista
de
Administração
http://rausp.usp.br/ RevistadeAdministração51(2016)310–322
Marketing
The
commercial
cycle
from
the
viewpoint
of
operant
behavioral
economics:
effects
of
price
discounts
on
revenues
received
from
services
O
ciclo
comercial
visto
pela
economia
comportamental
operante:
Efeitos
dos
descontos
nos
pre¸cos
sobre
a
receita
recebida
de
servi¸cos
El
ciclo
comercial
desde
la
perspectiva
de
la
economía
conductual
operante:
efectos
de
los
descuentos
de
precio
en
los
ingresos
de
servicios
Rafael
Barreiros
Porto
∗UniversidadedeBrasília,Brasília,DF,Brazil
Received23January2014;accepted11February2016
Abstract
Therelationshipbetweensupplyanddemandgeneratescommercialcycles.Operantbehavioraleconomicsexplainthatthesecyclesareshaped bythree-termbilateralcontingencies–situationsthatcreatesupplyanddemandresponsesandwhich,inturn,generatereinforcingorpunitive consequencesthatcanmaintainormitigatethese.Researchshowshowthecommercialcycleofacompanyoccursandinvestigateshowprice discountsaffectbasicanddifferentiatedservicerevenuesaccordingtoseasonality.Basedonalongitudinaldesign,twotime-seriesanalyseswere performedusingtheARIMAmodel,whileanotherwascarriedoutusingaGeneralizedEstimatingEquationsdividedintoseasonalcombinations. Theresultsshow,amongotherthings,(1)thatacompanyhandlesmostofthemarketingcontextstrategiesandprogrammedconsequencesof servicesusedbyconsumers,creatinganewcommercialsituationforthecompany,(2)theeffectsofpricediscountsonsophisticatedserviceshave apositiveimpactandproducehigherrevenuesduringthelowseason,whilethoserelatedtobasicserviceshaveagreaterimpactandproduce greaterrevenueduringthehighseason;and(3)theseasonalityofthegreatestpurchasingintensityexertsamorepositiveinfluenceonrevenues thantheseasonalityofdemandcharacterizedbyheterogeneousreinforcements.Thesefindingsareusefulfortheadministrationofpricediscounts togeneratemaximumrevenueandmakeitpossibletohaveabetterunderstandingofthewaythecommercialcycleofacompanyfunctions. ©2016DepartamentodeAdministrac¸˜ao,FaculdadedeEconomia,Administrac¸˜aoeContabilidadedaUniversidadedeS˜aoPaulo–FEA/USP. PublishedbyElsevierEditoraLtda.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).
Keywords: Commercialcycle;Behavioraleconomics;Revenue;Pricediscount;Seasonality;Servicemarketing
Resumo
Asrelac¸õesentreofertaedemandageramcicloscomerciais.Aeconomiacomportamentaloperanteexplicitaqueelessãoformadosporcontingências bilateraisdetrês termos–contextoscriadores decondic¸õesàsrespostasdo ofertanteedemandanteque,porsua vez,geramconsequências reforc¸adorasoupunitivascapazesdemantê-lasouatenuá-las.Apesquisademonstracomoocorreociclocomercialdeumaempresa,averigua oefeitodosdescontosdeprec¸onareceitadeservic¸osbásicosediferenciados comdiferentessazonalidades.Comdelineamentolongitudinal, fizeram-seduasanálisesemsériestemporaiscommodeloARIMAeoutracomEquac¸õesdeEstimativasGeneralizadasdivididasemcombinac¸ões desazonalidades.Osresultadosdemonstram,dentreoutros,queaempresamanipulaboapartedoscontextosdemarketingedasconsequências programadasdeusodeservic¸opelosconsumidoresdaempresa,criaumnovocontextocomercialparaela;osefeitosdosdescontosemservic¸os sofisticadossãopositivamentemaioresnareceitadurante embaixatemporada,enquantodosservic¸osbásicossãopositivamentemaioresem
∗Correspondenceto:UniversidadedeBrasília,CampusUniversitárioDarcyRibeiro,70910-900Brasília,DF,Brazil.
E-mail:rafaelporto@unb.br
PeerReviewundertheresponsibilityofDepartamentodeAdministrac¸ão,FaculdadedeEconomia,Administrac¸ãoeContabilidadedaUniversidadedeSãoPaulo –FEA/USP.
http://dx.doi.org/10.1016/j.rausp.2016.06.005
altatemporada;easazonalidade demaior intensidadedecompra exercemaior influênciapositivasobreareceitado quea sazonalidadede heterogeneidadedereforc¸osdaquelesque compram.Osresultadosauxiliamagestãodedescontonagerac¸ãodamáxima receitaepermitem compreenderocomportamentodociclocomercialdeumaempresa.
©2016DepartamentodeAdministrac¸˜ao,FaculdadedeEconomia,Administrac¸˜aoeContabilidadedaUniversidadedeS˜aoPaulo–FEA/USP. PublicadoporElsevierEditoraLtda.Este ´eumartigoOpenAccesssobumalicenc¸aCCBY(http://creativecommons.org/licenses/by/4.0/).
Palavras-chave:Ciclocomercial;Economiacomportamental;Receita;Descontoemprec¸o;Sazonalidade;Marketingdeservic¸o
Resumen
Lasrelacionesentreofertaydemandagenerancicloscomerciales.Laeconomíaconductualoperanteexplicaqueéstosseformanporcontingencias bilateralesdetrestérminos-contextosquecreancondicionesparalasrespuestasdeofertaydedemandaque,porsuparte,danorigenaconsecuencias querefuerzanopunen,yquesoncapacesdemantenerlasomitigarlas.Elestudiodemuestracómoseproduceelciclocomercialdeunaempresa yaveriguaelefectodelosdescuentosdepreciosenlosingresosdeserviciosbásicosydiferenciadosendistintasestacionalidades.Pormediode dise˜nolongitudinal,sellevaronacabodosanálisisenseriesdetiempoconmodeloARIMAyotroconecuacionesdeestimacióngeneralizadas divididosencombinacionesdeestacionalidad.Losresultadosmuestranqueelofertantemanejaloscontextosdemarketingylasconsecuencias programadasdelautilizacióndeserviciosporlosdemandantes,creandounnuevoentornocomercialparaél;losefectosdelosdescuentosen serviciossofisticadossonpositivamentemásaltosenlosingresosdurantelatemporadabaja,mientrasquedescuentosdeserviciosbásicossonmás altosypositivosentemporadaalta;ylaestacionalidaddemayorvolumendecomprasejerceunainfluenciamáspositivaenlosingresosquela estacionalidaddeheterogeneidadderefuerzosdelosquecompran.Losresultadoscontribuyenalagestióndedescuentosparagenerarmayores ingresosypermitencomprenderelcomportamientodelciclocomercialdeunaempresa.
©2016DepartamentodeAdministrac¸˜ao,FaculdadedeEconomia,Administrac¸˜aoeContabilidadedaUniversidadedeS˜aoPaulo–FEA/USP. PublicadoporElsevierEditoraLtda.Esteesunart´ıculoOpenAccessbajolalicenciaCCBY(http://creativecommons.org/licenses/by/4.0/).
Palabrasclave: Ciclocomercial;Economíaconductual;Ingresos;Descuentoenprecios;Estacionalidad;Marketingdeservicios
Introduction
Thedifferentiationsofservicesareatthecoreofanydebate about the exclusivity, luxury and sophistication that a com-panycanoffer consumers(Brun &Castelli, 2013; Veríssimo &Loureiro,2013).However,ingeneral,theseservicescharge higherpricessincetheyofferconsumersgreaterbenefits(Kohli & Suri, 2011). On the other hand, the supply of basic ser-vicesthatsucceedinattractingademandarelessexpensiveand makeitpossibletomatchsupplyinrelationtoothercompetitor servicesuppliers(Abrate,Fraquelli,&Viglia,2012).Between oneextremeandanother of acompany’sservice portfolio,if the price discounts are well applied (Yao, Mela, Chiang, & Chen,2012),thesecanincreasemorethanproportionallythe
numberofconsumersas comparedtothenon-implementation
of such actions. A company that offers a range of market
products(Elmaraghy&Elmaraghy,2014)thatinclude differen-tiatedandbasicservices,combinedwithanadequatediscount policy,canincrease their revenueand, inturn,their financial profits.
However,eachserviceprovidedbythesamecompanycan
involve different consumers. These may face restrictions as regardspayingthecontractpriceofferedanddependonaprice discounttobeabletomakepurchases(Kohli&Suri,2011).This, inturn,hasadifferentimpactaccordingtotheseason surround-ingthecompanyofferings.Thus,thedemandforaservicetends tooscillate(Hanssens,Parsons,&Schultz,2003),withlowand highmomentsandwithor withoutaheterogeneousstructure. Inordertomeetdemand,supplyisthereforecontrolledbythe availabilityofthenumberofservices,theirdifferentials,periods whentheseareofferedandpricesgiventothem.Thus,revenue
management (Talluri &Ryzin, 2005)ends upcontrolling the cashflowsfrom theservicesandthesecanappealtoalarger segmentofconsumers,therebyensuringprofits.
In the hospitality industry, managers of hotels, resorts, flatsandguesthouses experience thisroutineon adailybasis (Menezes & Silva, 2013). During the low season, reduced pricesareusuallyofferedtogeneratesufficientaccommodation occupancyratesandtherebyboostincome,thoughthisisnot necessarily thecaseforallhabitationunits,especiallyas het-erogeneityexistsbetweendifferentconsumers.Pricevariations attractacertaingroupofconsumersmorethananotherandthese mayormaynotbeeffectiveingeneratingthemaximumpossible revenue.
InadditiontoService-DominantLogic(SDL)inmarketing (Lusch&Vargo,2014),whereinteractionbetweentheconsumer andthecompanyisessentialinordertoattainbettercompany performances,theconsumersandthecompaniesco-createand
co-produce theservicesoffered.By meansof knowledgeand
ability,managercanoperationalizethesupplyofservices,inthe hopeofgeneratinggreaterrevenuesandprofitsforthecompany, whichtheywillonlydoifconsumerspayfortheirservices.This researchusesatheoreticalframeworkthatisbothcoherentand complementarytoSDL.Itiscoherentbecauseitmeetsallthe
basic SDL requirementsand it complementsSDL because it
addsbehavioralaspectstotheconsumer–companyrelationship, bringing together empirical findings on an individual analy-sis level with elements on an organizational and contextual level.
forenterprisesandhowlongtheseeffectswill last.Thisisat the heart of the working ability of a marketing professional (Theodosiou,Kehagias,&Katsikea,2012),whichmayormay not be efficient and effective (Keh, Chu,& Xu, 2006). This researchshowswhatcanbedoneinsuchasituation.The spe-cificobjectiveofthisresearchwastoevaluatetheeffectthatprice discountshaveonrevenuederivedfromdifferentiatedandbasic servicesduringdifferentseasons.In generalterms,theaimof thisstudywastoshowhowthecommercialcycleofacompany operatesfromanoperanteconomic-behavioralviewpoint,with theinvestigationofwhatmarketingprofessionalsactuallydoto stimulatesalesofservices.Thus,thisworkservesasanaidto servicemanagerswhoaimtoincreasetheirincomeandadjust theirpricestomeetthedemandforeachoneoftheirservices.
Operantbehavioraleconomics:explainingthe relationshipbetweenthesupplyanddemandof products/servicepricing
An area known as behavioral economics has researched
a wide variety of firm-related issues, both from a
cogni-tive(Angner&Loewenstein,2010)andanoperantviewpoint (Madden, 2000). Both adopt the premise of actors having boundedrationality(Simon,1972).However,thelatter concen-tratesmoreontherelationshipexperiencesbetweenthebehavior
and consequences to consumers, entrepreneur, investors and
managerswhentheyareindividualeconomicunits–whichcan includedaggregateddata(Pindyck&Rubinfeld,2009)–than ontheirthoughtprocesses,withgreateremphasisontheformer. Theoperantperspectivesupportstherelevanceofaneoclassical analysistounderstandeconomicbehavior,butnotinanacritical way.Onthecontrary,thisshowsthat,evenwithouttakinginto
accountrationalassumptions,themicro-economicphenomena
can be explained by means of the evolutionary relationships between behavior andits environment in asingle behavioral theoreticalframework(Foxall,2015).
In actualterms,the theories involvedinthisareaare con-cernedwithdescribingandexplaininghowenvironmentscreate thenecessaryconditionsfortheseeconomicunitbehavior
pat-terns to occur and the consequences of these relationships
(Franceschini & Ferreira, 2013). In addition, these investi-gateconsumerpatterns,expenses,savings,investments, brand choices,thecontextsthatcanaffectthese(e.g.pricediscounts, income)aswellastheconsequencesoftherelationshipsoftime andspacebetweenbehavioralpatternsandtheircontexts;which mayormaynotbemediatedbythesocialenvironment(Foxall, 2010;Foxall,Oliveira-Castro,James,&Schrezenmaier,2007; Franceschini&Ferreira,2013;Madden,2000).
In spite of the fact that this economic area has
mathe-matically and empirically shown the relationships that exist betweentheabove-mentionedconcepts(Pindyck&Rubinfeld, 2009),thereisnointegratedmodel thatcanexplainwhyand how these are related. On the otherhand, by using an oper-antapproach,combinedwithtraditionalDarwinianprinciples, abehavioralanalysisrepresentsasolidbasis(Oliveira-Castro& Foxall,2005).Itusesconceptsandfindingsproducedthrough experimentalresearch,usuallyconductedinlaboratories,testing
Supplier/Marketing professional
Demand/Consumer
SDsuppllier ResponseSupplier S Rsupplier
SPsupplier
SDdem ResponseDem
SRdem SPdem
Fig.1.Bilateralcontingencies(Foxall,1999),adaptedbytheauthor.
bothhumanaswellasinfrahumansubjects[e.g.:monkeys,rats (Baum, 2005)],that translate andspecify economic concepts intobehavioraloperations.Thishasmadeitpossibletoexplain andintegrateinnumerableeconomicphenomenainamore sub-stantialandparsimoniousmanner.
The conceptual model most often used is described by
Skinner (1974) as being a3-term contingency, that specifies theconditions(Term1)forwhicharesponse(Term2)produces oneorseveralconsequence(s)(Term3).Thismodelwasduly complementedandcontextualizedtoillustratetherelationship betweenindividualeconomicunits(e.g.consumer,family, com-pany)byFoxall(1999)–ascanbeseeninFig.1.Thisinvolves a3-termbilateralrelationship,inthatthetopcontingencyrefers tothesupplier(sup)ormarketingprofessionalandthelowerone referstothedemand(dem)orconsumer.
Foxall(1999)statesthatrelationshipsofeconomicexchange are necessaryandsufficientinthemselvestoensurethat mar-keting activities exist within a company. Thus, in the lower sectionofFig.1,consumerbehavior(e.g.purchaseresponse)is precededbyacontextformedbydiscriminantstimuli–SDdem (e.g.availabilityofproductorserviceforaprice)andincludes consequences(e.g.utilityoftheproductorserviceacquired – utilitarian), whichcanbe reinforcers (SRdem)or punishments (SPdem).Theformerincreasesthepossibilityofthesame con-sumerpurchaseresponseonfutureoccasionswhenforexample the product ends or the services terminate, while the latter reducesthesechances.VellaandFoxall(2011)alsosuggestthat theconsumerreinforcerscanbeutilitarianandinformational,in thattheformerismediatedbytheuseoftheproductorservice itself,suchascomfortandconvenience(Foxall,2010)whilethe latterconsistsofsocialreinforcers,suchasluxury(Yeoman& Mcmahon-Beattie,2006),sophistication(Liu,2010), exclusiv-ity(Brun&Castelli,2013),amongothers.
productsorservices,etc.).Whentheofferordothis,reinforcers –SRof(profit)orpunishment–SPof(forexample,financialloss) consequencesaregeneratedforhim.
Theconsumer’spayment response, inthe aggregate, func-tions as a discriminant stimulus for the offeror, generating revenue for the company (SDof). This discriminant stimulus servesas thesituation for thesupplier’s subsequentbehavior, enablinghimtoberemuneratedand/orextract profitfromhis business.The situation or contexthasmultipledimensions, a temporaldimension being oneof these. Thereare periods of theyearwhenagreaternumberofconsumersbuyproductsand
periodswhenfewerconsumersbuy them.If higherpayments
aremadeduringeachcycle,thecompanywouldgrowin
com-mercialterms,andmonetaryexchangewouldthereforebethe sourceofacompany’sfinancialgrowth.
Inturn,therearealsoperiodswhenacompanywillattract consumerswhoseekdifferentreinforcers(e.g.exclusivity), cre-atingasituationwheretheofferorworkstoprovideconsumers withnewanddistinctoffers(Evans,2003;Smith,1956).If prop-erlydone,thiswillproduceincomeandapositivereinforcerin theformofprofits(orpunishmentasloss)forthesupplieratthe endofhisbehavioralchain.Thisprofit(orloss)canfeedback intothesystem.
Thesupplierresponsecangenerateprofitsfortheofferorand cancreateasituation for futureconsumer purchases depend-ingonhowwellhecarriesouthismarketingactivities.Thatis tosay,thisdependsonhowsuccessfullyheoffershisproducts orservices,whichcangeneratereinforcesthatareincreasingly
adapted to suit each demand, as well as pricing each
prod-uctandmakingitpossibletoincreasesales.VellaandFoxall (2013)characterizetheseasreinforcementandpunishment con-trol(SRdemandSPdem,respectively)andconsumersituation(or scenario)control(SDdem).Thus,theeffectivenessofamarketing professional’sperformance,orthatofasupplierasawhole,can bemeasuredbythewayhegeneratesreinforcersandreduces
companypunishmentsand, atthe sametime, generates more
attractivesituations,allocatesreinforcersandreducesthe pun-ishmentprocessfortheconsumer.
Thismakes the workof the offeror (commercial
adminis-tratorormarketingprofessional)extremelytechnical,withthe capabilityofbeingeffectiveorotherwise.Eachtaskperformed (operantsupplierresponses)withtheseaimshasfunctional fea-tures(Catania, 1973), butwhichvary as regardstopography: frequencyof emission(how oftenisthe samefunctionaltask undertaken),forceormagnitude(degreeofeffort,orhowmuch techniqueortechnologyisneededtoperformafunctionaltask), duration(thetimeittakestoperformanoperationaltask)and periodof latency(thetimeittakestoissuethefirstfunctional response).Dependingon howeffectivelythesecharacteristics areemployed,theresultoftheworkservesasasourceforthe demandcontext(SDdem)and,ifthisleadstoanincreaseinthe numberofconsumersandtheirshoppingrates(demandresponse frequencyormagnitude),revenueswillincrease(SDof).
The variety of products/services that a company offers is directlyassociatedwiththeirconsumeracceptance(Elmaraghy &Elmaraghy,2014).Thisacceptanceisreflectedinshopping rates. Companies offering the greatest variety of products/
servicesmeetthedemandforawidevarietyoffeaturesatthe sametimeandtherebytendtoincreasetheirrevenue(SDof).This occursbecauseoftheavailability(Responseof)ofdifferentiated sophisticated products/servicesofferedby abusiness (magni-tudeofaresponsethatgeneratesahighlevelofreinforcement
tomeetdemand) aimedatcreatingtemporary monopoliesby
providingcustomerswithexclusiveorsingularproducts(atype of SRdem) (Brun & Castelli, 2013). Thiscan avoid the need to reduce prices (responseof), and, in turn, a fall in revenue
(reductionofSDof)ifthesamenumberofclientsismaintained
(aggregatedresponseDem),whenlocalcompetitorsreducetheir
prices(Responseof alternative)(Becerra,Santaló,&Silva,2013). Inturn,byofferingbasicservices(Responseof),offering
min-imum quality (magnitude of response that generates low or
averagereinforcementfordemand),ensuresaconstantdemand ifpricedatalowervalue(loworaverageSPdem).
Inthisway,boththedifferentiatedservicesofferedandthe basic services offeredare market strategies that can increase
revenues, by means of monetary exchanges withconsumers,
thoughtheseattractdifferentaspectsasregardsthisincreasein revenue.Thefirstchargesamuchhigherprice(ordoesnotmake asignificantpricereductionwhentherearecompetitors),while
the second aims tobecome more competitive in attracting a
higherdemandforalowerprice.Byusingbothtacticstogether, a companywill manage toincrease the intensity and variety of demand. These strategies can produce different effects on revenueand,sometimes,onecanrepresentabetteroptionthan theothersoastoincreaseit.Thesearethefocuspointsofthis researchstudy.
Inaddition,thesamecompanywithitsportfolioofservice can offermorethan onetypeof differential, while maintain-ing one basic service. This means that the typeof influence acompany makesis far from clear. Thus,thisresearch aims toexamineabasicnon-differentiatedservice(lowreinforcers for demand)andtwo typesof service differentials(consumer servicesthat offerhighdifferentialandconcurrentreinforcers forthedemand).Thiscancharacterizediscriminativestimulus (Catania, 1998)forconsumers: whenpresent,thisindicatesa reinforcerthatisdifferentfromwhenanotherstimulusispresent (whichindicatesanotherreinforcer).
Foreach daythat aproduct or service is offered,there is
anassociated programmedpunishmentfortheconsumer(e.g.
topaythe price).The marketing professionalcanincreaseor reducethisandhistaskiseffectiveifhispricingmakesit pos-sible to increase subsequent revenue. Traditionally, the price discounts(Yaoetal.,2012)makeitpossibletoreducethe con-sequencesofademandpunishment(SPdem),makingapurchase behaviormorelikelytooccur.Thus,theexactlevelofdiscount thatmakesitpossibletoincreasemorethanproportionallythe demandwithoutreducingrevenue,isessentialsothata commer-cialcyclecanoccur.Thislevelofdiscountcanbedesignedto haveanimmediateresponseoradelayedresponse(Hanssens& Dekimpe,2012).Thepresentresearchexaminedthe effective-nessanddurationofthesediscountsondifferenttypesofmarket offers,withtheaimofgeneratingmoreincome.
However,thepaymentsmadetoacompanybyawide
periods.Thisischaracterizedastemporalcommercialcontexts thatconsumersgenerateinbenefitofthesupplier(intensityof responsedemofaggregatedpurchasesovertimeandtheperiod ofgreatestnumberofvariedreinforcers(SRdemvaried)associated withresponsesdem).
Depending on these contexts, conditions are created that makeiteithereasierormoredifficulttoobtainanincreasein rev-enue(SDof).Thesearedimensionsofthemarketsegmentations – heterogeneity andconsumerintensity (Evans, 2003;Smith, 1956).Thus,characteristicsofseasonality,lowandhighseason (Nadal,Font,&Rosselló,2004)andcommercialworkingdays andweekends(Jeffrey&Barden,2000)aretemporalsituations thatcaninterfereintheeffectthatdiscounts(punishment reduc-tion)haveoneach service(Hanssens etal.,2003).Thisisan issuecoveredandisalsopresentinthisresearchstudy.
Inthelanguageofoperantbehavioraleconomics,thepurpose of thisresearchis totestthe effectofthe supplier’sresponse ingeneratingfuturecommercialcontextsover time,inaway thatisfavorabletotheofferor(greater revenue),reducingthe financialpunishmentassociatedwiththedegreeofreinforcers programmedbythesupplierforconsumers(basicand differen-tialservicediscounts)withindistincttemporaldemandcontexts. Thatistosay,thisresearchaimstotestthecommercialcycleof theModelshowninFig.1duringperiodswhenthereisa varia-tionintheintensityofdemandresponsesandtheheterogeneity ofreinforcesallocatedtotheseresponses.
ThisproposaloffersacomplementtotheServiceDominant Logic (Lusch & Vargo, 2014), by providing a general con-textualizationformatterspreviouslydescribed,andtheuseof behavioraltermstoexplainthisphenomena.Theareaof mar-ketingisoftencriticizedfornotusingtheoreticalargumentsto explainits phenomenon(Hunt,2010),eventhoughthere isa
gooddealofempirical evidencetoshowhow marketing
phe-nomenoncanbeusefultoorganizationsandconsumersalike. Keyevidence,includingtheeffectthatsalesdiscountshave onsalesandservicedemands,hasbeenwelldocumented(Line & Runyan, 2012; Yoo, Lee, & Bai, 2011). It is known that companiesthat describethemselves as service leaders imple-ment more pricing strategies and that these produce greater customerperceptionasregardsrevenue,profitandbrand aware-ness(Indounas,2015).Inaddition,thehigherthelevelofprice discounts,thegreaterperceptionacustomerhasasregards sav-ings,purchaseintentionandquality(Hu,Parsa,&Khan,2006, chap.2).
However,thesestudiesoffernoexplanationastowhythese occurand,inparticular,theireffectivenessingeneratingrevenue foracompanyasaresultoftheinteractionbetweenservicesand pricing.Enz,Canina,andLomanno(2009)areamongtheonly researcherswhotestedtheeffectsthatpricinghasontherevenue ofahospitalityservicecompany,usingactualdata,overaperiod oftime.Theyfoundthatthereisprice-revenueinelasticityinthis typeofserviceandthatthebeststrategytoincreaserevenueis tomaintainhighprices,eventhoughthesedonotleadtoahigh demand (highoccupancyrate). Theseauthorsalsofoundthat pricediscountsencourageincreasedoccupancyrates,butdonot increaserevenueandmacro-economicdatahavelittleeffecton revenue.
Inspiteofthisstudy,variousaspectsrelatedtoservice pri-cing remain open, including issuesrelated tothe moderating effects of the price-revenue relationship, longitudinal studies withactualpricesonadailybasis,theallocationofdifferential pricestrategiessothatthesamecompanycanofferconsumers different benefits, control the role that seasonality playsover shorterperiodsoftime(monthlyanddaily)andemploy objec-tivemetrictoevaluateperformance,whicharerarelyusedinthis area,etc.Byshowinghowthecommercialcycleoccursusing anoperantapproach,marketingcapabilities,whichoriginatein thetechnicalabilitiesoftheprofessionalsinvolvedinthis activ-ity,canbeexplainedandtheselimitationsovercome.Marketing professionalsdonotcarryouttheirworkinavacuumor with-outapurposeinobservance.However,thereisstillvery little theoretical knowledge available toexplainthe nature of their objectives.Thepresentstudythereforeaimstoremedythislack ofinformation.
Method
Thisexpostfactoresearchstudywasconducted1usinga lon-gitudinaldesign.Everyday,theresearcherregistereddatafrom amedium-sizecompanybelongingtothehotelsectorlocated intheCentralWestregionofBrazil.Thisfirmrepresentsover 150 collaborators,including the generalmanager anda man-agerforeachoneofitsdepartments.Secondarycompanydata wasobtainedbymeansofaregionaloperationaland commer-cial systemof sales information, prices, and accommodation
occupancy rates, among others. Once the general
manage-menthadgiventheirauthorization,thedatawasorganizedand arranged so that adailytemporal seriesof analysescould be conducted.
With regardstothe townresearched,business tourismand events occur with greater frequency than leisure activities (Lemes,2009).Thehotelchosenforthepurposeofthisresearch reflectedthistypeofdemandcharacteristicduringcommercial workingdaysforthisconsumersegment.However,inaddition tothese,therewasalsoleisuretourismattheweekends.
Datausedincludedinformationaboutthehotelsinceits inau-gurationinthattown,aswellasasamplingofthehotelservices during120 consecutivecalendardays.Thepowerof the mul-tipleregressionsamplingtest(averageeffectf2=0.15)with3 predictors(pricediscountfactors)cametoaround95.2%.That istosay,evenwithareducedsamplesize,thiswasenoughto dismisstheincidenceofaTypeIIErrorinthisresearchstudy.
The discountswerecalculatedinpercentagesbasedonthe price paidfor eachroomdivided by thepricesshownon the listofdailyrates.Thiswassubtractedbyoneandmultipliedby onehundred.Sincethe priceofthe roomsvaried,aPrincipal ComponentsAnalysiswasconductedsoastoshowthefactors involved,ascanbeseeninTable1.Thisshowsthatthedifferent discounts implemented bythe hotel chainare based onthree factors.
1This research study has received financial support from the Brazilian
Table1
Factorloadingsforpricediscountfactors.
Discountonnon-differentiated services(standardizedinrelation tootherhotels)
Discountonsophisticated differentiatedservices (presidentialsuites)
Discountondifferentiated servicesthatare environmentallyfriendly
Crombach’salpha 0.76 0.63 0.84
Discountonasuperiorsuite 0.91 Discountonastandarddoubleroom 0.90 Discountonadeluxeroom 0.80 Discountonastandardsingleroom 0.57
Discountonapresidentialsuite-cer 0.78 Discountonapresidentialsuite-pan 0.68 Discountonapresidentialsuite-mat 0.66 Discountonapresidentialsuite-exe 0.55 Discountonapresidentialsuite-ama 0.36
Discountonadoublegreensuite 0.88
Discountonadeluxegreensuite 0.82
Discountonadeluxegreensuite 0.72
Discountonananti-allergicgreensuite 0.71
Discountonasinglegreensuite 0.68
KMO=0.73
Totalvarianceexplained=58%
Source:Preparedbytheauthorofthisarticle.
These discounts take into account the levels of
accom-modation differentials. The “Discount on non-differentiated services”,withα=0.76,average=22.6%andstandard
devia-tion=8.2%,consistsofroomsthataresimilartothoseofother hotels of the same level (standardsingle and double rooms, deluxeandmastersuites)withstandardservicesandreception. The factor “Discount on sophisticated differential services”, withα=0.63,average=19.5%andstandarddeviation=22.7%,
consistsofcustomizedpresidentialaccommodationwith
recep-tion and exclusive happy hour services available, as well
as tea-service, bath robes and slippers, and may include
aJacuzzi.
The third and final factor “Discounts for differentiated
services that are environmentally friendly, with α=0.84,
average=8.8%andstandarddeviation=10.5%,consistsof dis-countsfor hotelrooms thatvalue well-beingandharmonyas partoftheaccommodationtheyoffertheirguests,with100%of theirfloorsestablishedasno-smokingareas,withfragrant atmo-spheresandincluding special amenities,such as anti-allergic roomsandtheuseofecologicalmaterials.
Thus,thesethreefactorsconstitutethediscountfactors
cov-ered by this study, each one measured on the basis of an
averagepercentage.Theaveragepriceoftheservice ratesfor non-differentialroomswasequivalenttoUS$207.75(standard deviation=US$62.65).Therateforaroomwithsophisticated differentialfeatureswas equivalenttoUS$1450.00(standard deviation=US$497.05), andinthe caseof aroom with dif-ferentiatedandenvironmentallyfriendlyservices,thepricewas equivalenttoUS$186.50(standarddeviation=US$53.26).
Thetotaldailyincome(revenue)wascalculatedonthebasis ofthesumtotalofthenumberoftimeseachserviceoritemwas soldmultipliedbythepricepaidbyeachoneperday.Thiswas subdivided in partial daily revenue, namely: revenue derived from non-differentiated services, revenue from sophisticated
differentiated services and revenue from differentiated envi-ronmentallyfriendlyservicesusingthesameformulausedfor thetotalrevenue,thoughrestrictedtotheseservicesalone.The hotelchain’srevenueaveragedUS$25,616.90perday,witha standarddeviationequaltoUS$16,373.40.
In this researchstudy, the sum totalof dailyrevenue was averagedoutbytheaveragemonthlyrevenue.Inthisway, val-uesequaltooneareincludedintheaveragemonthlyrevenue, above(below)onearehigher(lower)thanthemonthlyaverage monthly.Therelativedailyrevenue,adependentvariableinthis study, showed anaverage equaltoone andastandard devia-tionequalto9.6.Theoveralloccupancyratewasmeasuredby thenumberof roomsoccupieddividedbythetotalnumberof rooms availableonadailybasis,whichwasalso sub-divided intodifferenttypesofaccommodation.
AdescriptivedataanalysisisshowninTable2.Ascanbe seen,thisshowsthattherewasareasonableoveralloccupancy rate. In addition,the rooms withthe highestoccupancy rates were those without differential features, in spite of the high standarddeviations.Thegreatervariancerevenueswerethose offeringsophisticateddifferentiatedservices,whilethose offer-ingsmallerdiscountswerethosethatprovideddifferentiatedand environmentallyfriendlyservices.
Inall,thisarticlepresentsthreestatisticalanalyses.Thefirst
aims toshow theeffectof eachdiscounts onaccommodation
service provided (reducing monetary punishmentsassociated
with different degrees and types of reinforcers that the sup-plierprogramsfortheconsumer)inthecompositionofrevenues (compositionofSDof).
The second aimstoshow the effectsthat typesof season-ality(intensityof responsesdemforaggregated purchasesover timeandtheperiodofthegreatestnumberofvariedreinforcers (SRdemvaried)associated withresponsesdem)have onthe total
Table2
Descriptivedataanalysis.
Descriptivedata Average Standarddeviation Minimum Maximum
Generaloccupancyrate(%) 51.7 29.0 8.1 99.6
Occupancyrateofnon-differentialrooms(%) 50.9 28.3 0.8 100 Occupancyrateforroomswithsophisticateddifferential(%) 35.2 0.3 0.0 100 Occupancyrateofenvironmentallyfriendlyaccommodation(%) 34.9 0.3 0.0 100
Totalrevenue(relative) 1.0 0.6 0.1 2.6
Revenuefordifferentialservices(relative) 1.0 0.6 0.1 2.4 Revenueforsophisticateddifferentialservices(relative) 1.0 1.9 0.0 11.4 Revenueforenvironmentallyfriendlydiff.services(relative) 1.0 1.0 0.0 3.2
Discountsfornon-differentialservices(%) 22.5 8 0 43
Discountsforsophisticaldiff.services(%) 19.5 22.7 0 95 Discountsforenvironmentallyfriendlydiff.services(%) 8.8 10.5 0 70 Source:Preparedbytheauthorofthisarticle.
The third analysis, derived from the two previous analy-ses, was to establish the everyday effects that discounts of eachservice (reducingmonetarypunishmentsassociatedwith different levels and types of reinforcers programmed by the supplierfortheconsumer)hadontotalrevenue(SDof),in accor-dancewithseasonaldemanddimensions(intensityofpurchase responsesdemaggregatedovertimeandtheperiodofthe great-estnumberofvariedreinforcers(SRdem varied)associatedwith
responsesdem).Theanalyticalunitofeachanalysisisbasedon
dailyrevenue.
In the first analysis, an autoregressive integrated moving
average – ARIMA model was used for each composition of
revenue. Thiswas necessary as the revenue data(partial and total)were showntobe auto-correlated (Durbin–Watson var-ied between 0.8 and 1.3, the reference value being=2) and non-stationarity(theAugmentedDickey–Fullertestswere non-significantforp>0.05fortwopartialrevenues).However,itwas necessarytointegratetheARIMAmodelbythefirstdifference. The normality assumptions of the independent variables(the
Kolmogorov–Smirnov testswere non-significant for p>0.05)
andhomoscedasticityweremet (WhiteLM Testwereall
sig-nificantforp≤0.05).Themodelsthatbetteradaptedtothedata aredescribedinTable3ofthesefindings.Forrevenuederived from non-differential services (Sof from the low magnitude
responseof),thebestmodelwastheonewith=1;difference=0
numberofauto-regressiveterms.
For revenue earned from non-differentiated services (Sof derivedfromlowmagnituderesponsesof),thebestmodelwasthe onewithautoregressivetermof=1;difference=0;andamoving averagetermnumberof=0.Inthecaseofrevenuederivedfrom differentialsophisticatedservices(Sofderivedfromahigh mag-nituderesponseof),thebestmodelwastheonewithanumberof autoregressivetermof=1;difference=1;andamovingaverage term of=0. For revenuederived fromdifferentiated environ-mentallyfriendlyservices(Sofderivedfromanalternativehigh magnituderesponseof),thebestmodelwastheonewitha num-berofautoregressivetermsof=0;difference=1;andamoving averagetermof=0.
In the second analysis (Table 4), in order to demonstrate theaggregatedeffectofconsumerpurchaseresponsesinterms
of revenue, the ARIMA Model was also used (number of
autoregressiveterms=2;difference=0;amovingaverageterm of=7), the explicative variables being the seasonal dimen-sions(highseasonversuslowseasonandcommercialworking
days versusweekenddays) weredichotomizedandtreatedas
eventvariables.Anaverageofthetotalrelativizedrevenuewas
used as a dependent variable. It was seen that the monthly
seasonality (Nadaletal.,2004)measurestheperiodofhigher intensity of purchase responsedem andthe weekly seasonality
measuresthe period of thegreatest numberof varieties/types ofreinforcersavailabletoconsumers,sinceduringcommercial workingdayshotelguestsgenerallyconsistofbusinessorevent tourists and, duringweekends,of guests whohadconsidered the previous two options, as well as leisuretourists (Lemes, 2009).
In the third analysis (Fig. 3), in order to demonstrate the overall effects of the commercial cycle on revenue, the
variable seasons were used as environmental variables that
interact with discount strategies. For this, a sample
sep-aration for each season dimension combination was used
and the effects of the three service discount factors were
tested for the total revenue, by means of a Generalized
Estimating Equation. Thus, in each seasonality combination,
there is an equation with independent discount variables
[Ytssea=logB(Disc1tssea)+logB(Disc2tsea)+logB(Disc3tsea)].
A log-linear model was used, with a matrix work structure
AR(1),consideredtobethebestforthesedata(lowerQIC). Thefourcombinationsofthetwodimensionsofseasonality involvedinthisthirdanalysiswereasfollows:(1) lowseason
demandduringweekends(LSWE),whenthereisalownumber
of consumerswith highheterogeneity of reinforces available
to meet demand; (2) low seasonduring commercialworking
days (LSWD), which presents a low number of consumers
withlowheterogeneityofreinforcersavailabletomeetdemand;
(3) highseasonduringweekends(HSWE) thatpresentahigh
numbers of consumers with low heterogeneity of reinforcers
availabletomeetdemand;and(4)highseasonandcommercial
working days (HSWD) that present a high number of
Results
Theeffectofdiscountsforeachserviceonthecomposition ofrevenue
Table3showsfindingsrelatedtotheimpactcausedby reduc-ingmonetarypunishmentsassociatedwithdifferentlevelsand typeofreinforcers,whichareprogrammedbytheofferorto con-sumers,inrelationtothecompositionofthecommercialcontext (revenues)receivedbytheofferor.
Thepartialrevenuesearnedlaggedinoneday,from differ-entiatedservicesandfromsophisticateddifferentiatedservices, hada positiveeffect onthe current revenue, whichindicates an upwardtrend in their predicted value.Thus, the previous SDof increase (previous commercialcontext) tendsto gener-ateanincreaseinthesubsequentSDof(subsequentcommercial context).However,thepartial revenuesderivedfrom environ-mentallyfriendlyservicesdonotpresentthesameeffect.That istosay,thepreviouscontextinthiscasedidnotgeneratethe subsequentcontext.
All the explanatory variables (discounts for each service, whichare also known as offeror’s responses) had a positive influenceontheirrespectiverevenues,withgreater impactfor services that offered advanced differentials, environmentally
friendlydifferentialsandthosewithoutdifferentialsinrelation tootherhotels,respectively.Thatistosay,discountsonservices offering advanced differentials had afar greater impact than thosegivenforotherservices.Theeffectsofthesediscountswere temporary–lastingonlyonthedaytheywereimplemented(very short-termtemporaldiscriminationof).Thesedidnot,therefore presentlongtermeffects.
However,inthecaseofnon-differentialservicesand environ-mentallyfriendlydifferentialservices,theeffectsofadiscount occuronedaylater(shortlatencypurchaseresponsedemto
gener-atesubsequentSDof).Thisisduetothefactthatclientsonlysettle
theiraccountswhentheycheckoutofthehotel.Suchdelaysare notobservedinthecaseof differentialsophisticatedservices, sincepaymentsaremadebeforetheclientoccupiestheroom.
Duetothenon-stationarynatureofthedataforARIMA mod-elsfor differentialservices,anintegrationorderequivalentto onewasallocatedtothis.Asaresult,thenon-stationaryeffects
were corrected. The adjusted residuals of the (Ljung–Box)
models werehigher thanp>0.05,whichshowstherewas no significantautocorrelation betweenthem.The datawasbetter adjusted for services with sophisticated differentials (R2 sta-tionary=98.2%)andthe datafortheotherrelationships were reasonablywell-adjusted.Thesecanbemoreeasilyvisualized inFig.2,representedbyGraphicsA,BandC.
Table3
Effectsofeachdiscountonthe(partial)revenue.
Variables Estimate Standarderror Ljung–Box R2stationary DV:Revenuefromnon-differential
accommodation
Constant 0.74* 0.09
28.6** 64%
Autoregressive Lag1 0.55* 0.08
Factor:Discountfornon-differential accommodation
Delayed 1
Currenteffect Lag0 0.45* 0.15
DV:Revenuefromsophisticated differentiatedaccommodation
Constant −0.13* 0.05
19.7** 98.2% Autoregressive Lag1 0.30* 0.10
Factor:discountforsophisticated differentiatedaccommodation
Orderofintegration 1
Currenteffect Lag0 0.78* 0.15
DV:Revenuefromenvironmental friendlydifferentiatedaccommodation
Constant −0.02 0.05
26.4** 53.8%
Orderofintegration 1 Factor:discountforenvironmentally
friendlydifferentiatedaccommodation
Delayed 1
Currenteffect Lag0 0.62* 0.29
Source:Preparedbytheauthorofthisarticle.
* p≤0.01. ** p>0.05.
Table4
Effectsthattypesofseasonalityhaveonrevenue(total).
Variables Delay Estimate Errorstandard Ljung–Box R2stationary
DV:Total RevenueRelative
Autoregressive Lag1 1.24
* 0.03
8.00** 78.7%
Lag2 −0.99* 0.03 Movingaverage
Lag2 −0.26* 0.10 Lag3 −0.47* 0.10 Lag4 −0.70* 0.09 Lag7 −0.32* 0.10
Season Lowseason=0;Highseason=1 Lag0 1.02* 0.12
Daysoftheweek Weekends=0;Commercialworkingdays=1 Lag0 0.21* 0.08
Source:Preparedbytheauthorofthisarticle.
13
Relativ
e re
ven
ue (basic ser
vice)
Observed Prediction adjusted
Graph A
Date
Date
Date Graph B
Graph C Observed
Prediction adjusted
Observed Adjusted prediction
Relativ
e re
ven
ue (ser
vice with sophisticated
diff
erential)
Relativ
e re
ven
ue (ser
vice with
en
viron
u
mentally fr
iendly diff
erential)
12 11 10 9 8 7
5 4 3 2 1 0
1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96101106111116
1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96101106111116
1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96101106111116 6
13 12 11 10 9 8 7
5 4 3 2 1 0 6
13 12 11 10 9 8 7
5 4 3 2 1 0 6
Fig.2.Adjustmentforthediscountpredictionforeachservicesthatmakeup thesalesrevenue.
Source:Preparedbytheauthorofthisarticle.
GraphAshowstheadjustmentsmadeforpartialrevenuesfor non-differential servicesover time(duringconsecutivedays), basedonthepredicteddiscounts.GraphBshowstheadjustments madeforpartialrevenuesforsophisticateddifferentialservices,
while Graph Cshows theadjustments made for revenuesfor
environmentallyfriendlydifferentialservices.
Theeffectsthattypesofseasonalityexertonrevenue
Thenon-stationaritycorrectedintheARIMAmodelforthe effectsthatdiscountshaveoneachtypeofservices,showthat theseareduetotheseasonalityintherevenuedata.Thus,allthe partialrevenuedatawasaggregatedintototalrevenueand exist-ingseasonalitiestested.Table4showstheeffectsoftheintensity
of purchase responsedemover timeonrevenue(SDof)andthe effectscreatedbythegreatestnumberofvariedreinforcers avail-abletoconsumers(SRdemvaried)overtimeonrevenue(SDof).
With regards tothe hotelresearched, the lowseason (LS) occursinthemonthofJanuaryandthehighseason(HS)during therestoftheyear.Therewerehigherpeaksinroomoccupancy duringcommercialworkingdays(WD)ratherthanatweekends (WE).Thus,boththeseasonalitydimensionshadacurrenteffect (latency responsedem aggregatedtogeneratesubsequent SDof)
on revenue and, together with the lagged revenue, showed a
78.7%stationaryexplanatoryvariance.Inaddition,theseasonal effect(intensityofpurchaseresponsedemaggregatedovertime) is much stronger on revenue, almost five times greater,than duringweekdays(periodofgreaternumberofvariedreinforcers (SRdemvaried)associatedwithpurchaseresponsesdem).
Theeffectofdiscountsofeachserviceonrevenuein differentseasonaldemands
Fig.3showstheeffectsofreducingmonetarypunishments associated withdifferentdegrees andtypesofreinforcersthat the offeror programsfor the consumer, inasubsequent com-mercial context by the offeror (revenue)in temporal context
combinations of demand. Every reduction made of the
pun-ishments programmed by the offeror for each service has a
positive impact on revenue, bearing in mind the delay of
oneday fornon-differential services andfor environmentally friendly services, as found in the first analysis. Combining
both seasonal demands, we find the dimensions of service
demand responses (average occupancy rate LSWE=20.3%,
LSWD=38.8%,HSWE=41.1%andHSWD=72.3%).
Implementingapricediscountstrategyfor non-differential servicesissimilarduringalltheseasonalperiods,beinggreater inperiodsofhighseasonandduringcommercialworkingdays (HSWD).Thus,adiscountof10%inthecostoftheseservices generatesatotalincomeofaround2.8timestheaveragerevenue ofacompany.Whilethesameproportionalincreaseindiscounts generates2.61timestheaveragerevenueobtainedatweekends duringthehighseason(HSWE).Thisstrategydoesnot signifi-cantlyaffectrevenueinthelowseasonandduringcommercial
workingdays(LSWD).
Aprice discountstrategy forsophisticated differential
ser-vices is implemented more often in the low season during
commercialworkingdays (LSWD)and,thereafter,duringthe
lowseasonattheweekends(LSWE).Thus,adiscountof10%
inthepriceoftheseservicesgeneratesatotalincomeofaround 3.31timestheaveragerevenueofacompany.Meanwhile,the sameproportionalincreaseindiscountsgenerates1.44timesthe
average revenueduringcommercialworkingdaysinthehigh
season(HSWD).Thisstrategyproducesnosignificantimpact
duringthehighseasonandatweekends(HSWE).
The implementationof aprice discount strategy for envi-ronmentallyfriendlydifferentialsisgreaterduringcommercial
working days inthe highseason (HSWD) than at any other
1.40∗ 1.58∗ 1.36∗
0.25 2.01∗
0.42∗
0.05
2.75∗
0.66∗
1.16∗
0.52∗
0.10
Low season High season
High season Low season
Working week days (HSWD)
Weekend (LSWE) Working week days (LSWD) Weekend (HSWE)
Discounts for simple accommodation (t+1)
Discounts for sophisticated differential accommodation (t)
Discounts for differentiated environmental accommodation (t+1)
Fig.3.Effectofdiscountsforeachservice(Estimates)onrevenue(total)forseasonaldemand.*p≤0.01.
Source:Preparedbytheauthorofthisarticle.
generates1.64times acompany’saveragerevenueduringthe highseasonatweekends(HSWE).Thisstrategyshowsno sig-nificanteffectsinthe lowseasonduringcommercialworking
days(LSWD).
Discussion
Thesefindingsshowthattheeffectsthatdiscountshaveon revenuedependontheservicedifferentialsinvolved,thepolicy acompanyusestochargeitscustomersandtheseasonalityof demand.Theoperanteconomic-behavioraltheoryexplainsthese findings.
Howthecommercialcycleisexplainedbythethree-term
bilateralcontingency
Onthewhole,thesefindingsshowhowacommercialcycle occursfromanoperantbehavioraleconomyviewpoint(Foxall, 1999;Vella&Foxall,2013).Thisresearchshowshowservice differentials (the offeror’s response when programming dif-ferent levels of reinforcers to consumers) generate different
impactsinthe subsequent revenueof acompany(subsequent
commercial context for an offeror derived from aggregated
purchaseresponses fromconsumers), dependingon theprice
discountsallocatedtothesepurchases(offerorsresponsewhen
programmingreducedmonetarypunishmentstoconsumers).In
generalterms,thiscreatesacommercialcycle.Thus,theeffort involvedinofferingconsumersdifferentdiscriminativestimuli thatreleasedifferentlevelsofreinforcementsandreduce mon-etary punishments, generates avariety of customer purchase chargesthat,ifaggregated,generatenewcommercial discrim-inativestimulifor theofferor. This, inturn,creates favorable situationsforthegrowthofthecompanyitselfandenablesthe offerortoprovidenewcustomerresponses.
Thus,thebehavioroftheofferorcontrolsagooddealofthe behavioralcontextsofthecompany’scustomersandtheofferor iseffectivewhenestablishingmonetarypunishmentassociated withthemagnitudeofthereinforcersreleasedthroughservices, which, in turn,return to create newcommercial contextson
thepartoftheofferor.However,theconsumersdonotdirectly controlthereleaseoftheofferor’sreinforcers(profit)or punish-ments(losses).Thisrelease dependsonthelowfinancial cost oftheofferor’sownresponsewithexistingresourcestoperform his role as the personwhocontrols andregulatesdemand. If theofferorsthemselvesareeffective,theycanappropriatethe reinforcers–profits(Vella&Foxall,2011).
ThissupportstheassumptionscontainedintheService Dom-inantLogic(Lusch&Vargo,2014).Theusebyservicemanagers ofspecializedabilitiesandknowledgeformsthebasisofa
fun-damentalunit ofexchange,whichprovidesconsumerswitha
contextandprojectsreinforcers.Theconsumersreciprocateby
payingmoremoney. So,thisinteraction betweenaconsumer
andthecompanyisexplainedthroughafunctionalrelationship ofdependencebetweenoneandtheother,sothatbothparties
can obtain mutualbenefits. The managers implementpricing
strategies andofferservicesinanattempttoencourage these mutualbenefits.
Theeffectsobtainedbyreleasingreinforcers(services)and
reducingpunishments(discounts)fortheconsumer
Consumers did not generalize the offeror’s discriminative stimuli(Catania,1998).Thatistosay,acompany’sserviceshad differentpurchasingrates(inthiscase,occupancyrates).Each reinforcer(typesofservice)programmedbytheofferor gener-atesdistinctresponsestodemand.However,theeffectsobtained byreducingmonetarypunishments(discounts)andthetimeit takestogeneratenewcommercialcontextsfortheofferor,are muchthesame(greatergeneralization).
Thisresearchshowsthatofferingclientsdiscountsonthese servicesisthebestwaytocreateahighimpactonrevenue. Dis-countsthatreducethesizeofthepunishmentconsumershave topay(Oliveira-Castro,2003;Porto&Silva,2013;Rossiter& Foxall,2008),makeiteasiertoobtainreinforcersthatare util-itarianandsociallymediatedbyotherconsumers.Atthesame time,thesecreateadiscriminativestimulus(revenue)thatrelease reinforcers – profit (Talluri & Ryzin, 2005; Vella & Foxall, 2011).
Asimilarexplanationcanbegivenfor theotherdiscounts givenonotherservices.Thisiscorroboratedbythesame posi-tiveeffectobtainedthroughdiscountsgivenonenvironmentally friendly differentialandbasicservices, whichcanbe
charac-terized as a form of consumption that promotes a sense of
well-being (Lima &Partidário, 2002),or hedonic inthe first caseandmaintenanceinthe secondcase(Foxall,2010). Ser-vices that have sustainable features identify a company that adoptsenvironmentalmanagement(Felix&Santos,2013)and whichpromotespositivefeelings.Discountsmakechoiceseasier forconsumerswhoseekreinforcersrelatedtotheirwell-being, inparticularattractingthosewhocouldstayinnon-differential hotelrooms,duetothesimilarityinprices.
Non-differentialservices,ontheotherhand,representbasic conditionsofhospitality(João,Merlo,&Morgado,2010).Inthis researchstudy,thesearepricedlowerinrelationtosophisticated services,thus,discountsrelatedtotheseserviceshave propor-tionallylessimpactonrevenue. However,discounts givenon thistypeofaccommodationcancreategreatercompetitiveness inrelationtootherhotelsofthesamesize(Abrateetal.,2012) andthereforefunctiontoattractmoreconsumerswhoseekbasic hotelservices.
Policiesinvolvedinhowclientsarerequestedtosettletheir accounts relatestoresponselatency(Catania, 1973)fromthe offerorhimself,soastocreatenewcommercialcontextsforthe company(Vella&Foxall,2011),indicatinggreatergeneralized reinforcers(Kanfer,1960)– profit.Thisresearchstudy shows thatthiseffectisdelayedbyonedayforservicesthatinvolvea lowermagnitudeofrevenuetotheofferorandhasanimmediate effectinthecaseofthoseoflargermagnitude.
In addition, the duration of the effectof adiscount – the timeittakesforanoperantresponse(Catania,1973)–on rev-enueisshort(lastingonlyonthedayofthediscount).Revenue returns tosimilarlevelswhen the pricegoes backtonormal, whichisqualifiedasabusinessasusualstrategy(Hanssens& Dekimpe,2012).Thisisbecauseatemporarydiscountstrategy createsincrementalandtemporaryrevenue.Thenon-stationarity foundinnon-differentialservices,whichwouldmeanthat rev-enuedidnotreturntothesamelevel,isduetoseasonality,which iscorrectedintheARIMAmodelbythemethodofdifference (integrationinthetimeseries).
Howseasonalityaffectsrevenue
Theseasonalityfoundisduetothedemandforhotel accom-modationservices.Studiesabouttheeffectsofseasonalityhave nothadmuchofatheoreticalbasis(Koenig-Lewis&Bischoff, 2005), but the findings of this study can help explain how
discounts for each service (differential or otherwise) have a majorandpositiveimpactonrevenuedependingonthe seasona-lityofdemand.Itwasshownthatcreatingrevenueforacompany
by means of a commercial cycle depends on an adjustment
beingmadetoaggregatedconsumerpurchaseresponses,bethis either toattract different segments (consumer heterogeneity),
or to attract more consumers from the same segment
(num-ber/consumerintensity)(Evans,2003;Smith,1956).
These combinations of seasonal demands derive from the
periodicityofaggregatedpurchases.Thesecreatecontextsthat eitherincreaseordecreasetheeffectivenessoftheresponsesto theprogrammedreinforcersandpunishmentsthattheofferors makeavailabletoconsumers.Thus,duringperiodswhenthere isalowlevelofconsumerpurchases,discountsonsophisticated differentialservices havemorepowertogenerategreater rev-enuethanduringperiodsofhighintensityofpurchasesandalso representstheonlydiscountstrategythathasasignificanteffect
ontheLSWD.
Fromaconsumer’spointofview,sincethistypeofservice involvesgreaterpunishments(higherprices)andhighutilitarian andsocialreinforcers(Foxall,2010),apricediscountgenerates an increaseinrevenueduetoan increaseinhoteloccupancy rates.Thisiswhatoccurs,especiallyduringperiodswhenthere isalowvolumeofconsumers(lowseason),aperiodthatismore beneficialtodemandthantosupply(Parker,2013).
Inthecaseofdiscountsfornon-differentialservices,theseare generatedastheresultofgreaterincomebeingobtainedwhen there is a highintensity of consumers, butwith slightly less impactthanthediscountcapacityforsophisticateddifferentials duetothefact thatthereareasmallernumberofconsumers. ThesealsohaveareasonableimpactontheLSWE.Again,from aconsumer’spointofview(Foxall,2010),sincetheseservices offerbasichospitalityreinforcersandareofferedatlowprices (lowlevelofpunishment),reducingtheseincreasesthe aggre-gatedconsumerpurchaseresponse,butnotasmuchinrelation toservicesthatoffergreaterreinforcers.Analogicallyspeaking, butfromtheviewoftheofferor(Vella&Foxall,2013),these services are designed togenerategreater revenuessince they attractahigherintensityofconsumerpurchaseswhileinvolving lesspunishmentsfortheconsumer.Reducingpriceswouldnot havesuchaneffectinincreasingrevenue,becausethesealready representlowlevelsofpunishment. However,duringthehigh season,thesewouldattractproportionallyagreaternumberof consumers,whichwouldmakethisworthwhiletotheofferor.
Andfinally,discountsforenvironmentallyfriendlyservices create lessimpactthanthe two servicesdescribed above,but createamuchgreaterpositiveimpactasregardsHSWD.These differentialsinservicesattractpeoplewhoseekhedonistic rein-forcers(Foxall,2010)orthosethatpromoteasenseofwell-being (Lima&Partidário,2002).Reducingtheirpricesdoesnotmake as muchdifference as other services,probably because there wasstillnotagreatdemandfortheseatthetimeandplacethis researchwasconducted,forconsumerswhoareawareofthese reinforcers(Peattie,2010),leadingtolowroomoccupancyrates, eventhoughthesecostless.
strongmacro-economicfactorsinthehospitalityservice com-panyrevenues.Itispossiblethatthiswasbecausetheydidnot investigateshorterseasonalperiodsortheinteractionthatexists betweenseasonalityandpricingstrategiesforeachservice,for whichthepresentstudyhasobtainedresults.
Conclusion
Thisresearchshowsthat(1)acommercialcycleforservices canbeexplainedby behavioraleconomics,inparticularby a three-termbilateralcontingency;(2)pricediscountshavea pos-itiveanddistinct impactwithregardstothecompositionof a company’srevenue;(3)theeffectsthatdiscountshaveon rev-enuearevery short-term– onlylastingas longasthe dayon whichtheyare implemented; (4) thereis adelay of one day beforeitispossibletoestablishwhateffectsdiscountshavehad ondailyrevenuefromsomeoftheservices,duetocheck-out pro-cedures(paymentsarereceivedonlyaftertheserviceshavebeen used);(5)theeffectsthatdiscounthaveonrevenuearegreater for services that are more differential thanfor those that are lessdifferential;(6)revenuedatashowsnon-stationaryeffects, whichrequirestheireliminationfromtheARIMAforecast;(7) non-stationarityisduetoseasonality,andthishastwo
dimen-sionsrelatedtodemand–thenumberof purchasesmade and
theheterogeneityofthereinforcersofthebuyers;(8) seasona-litythat representstheperiodofpurchasingintensity,exertsa muchmorepositiveeffectonrevenuethantheseason,which representstheperiodwiththegreatestorlesserheterogeneityof reinforcersofthosewhobuytheseservices;(9)theeffectsthat discountshaveonrevenuefornon-differentialservicesare simi-larduringworkingdaysatthehighseasonandduringweekends atthe lowseason;(10)theeffects ofdiscountsondifferential andsophisticated services are greater during the lowseason; and(11)the effects of discounts onenvironmentally friendly anddifferentialservicesaregreaterduringthehighseasonand
oncommercialworkingdays.
Servicemanagers,especiallythoseinvolvedintourism,can evaluateandadjusttheirpricediscountpoliciesbyestablishing ifthereisaparticulartrendintheircompany’srevenueovertime and,ifso,tocontrolthesetoascertaintherealeffectsofthese discounts.Thesearepricestrategiesthatattractdemandinthe short-termandthatneedtobeusedcontinuallyinorderto gener-ateongoingeffectsonrevenue.However,thesehaveadifferent effectonacompany’srevenuedependingontheservice differ-entialsandthe seasonalperiods of demand.Discounts create agreater impactonsophisticateddifferentialservices thanon thosewithfewdifferentials,sothatagoodstrategywouldbeto generatethemostrevenueinperiodswhendemandislow.Inthe absenceofdifferentials(basicservices),thesediscountshave lit-tleimpact,butevensoarestillpositiveandsimilartoalmostall otherperiodsoftheyear,exceptforcommercialworkingdays duringthelowseason.
Theeffectiveness of discounts canbe ascertained inorder toestablishbetter pricingstrategies andtoenhance thevalue of the companyby commercializing its products or services.
This research study can therefore help business, marketing
and/orcontrollermanagerstobetterevaluatetherightperiodsto
implementpricediscountpolicies.Usingonlythedatarelatedto aservice(hospitality)andonlyasmallamountofdatacollected during the low season represent a limitation in the case of thisresearch.However,thisstudyusedup-to-dateinformation providedbythecompanyanalyzed.Inaddition,thefindingsare generalizedforsituationswhenclientspayonthesamedayor immediatelyafterusingtheservices.In thisway,the findings couldbesimilartootherresearcheswithinthesecontexts.
Conflictsofinterest
Theauthordeclaresnoconflictsofinterest.
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