Researchbackground
Underthechangesofeconomicenvironmentandfiercecompetition,inthebusinesstobusine ssfield,suppliershaveemployedKeyAccountManagement(KAM)programst o t h e i r b u s i n e s s c u s t o m e r s T h e s e p r o g r a m s a r e d e s i g n e d t o s e r v e s t r a t e g i c o r keycustomerswhocontribute alargeportion intermsofsalesand profit.Such keya c c o u n t s plays u c h amoreimportantrolethantraditionalones(minoraccounts) ( P a r d o , 1997).
Key AccountManagement(KAM)hasbeenreceivedsomany interestsasmosto f salesturnovergeneratedbykeycustomers(ShapiroandMoriarty,1 982;Cespedes,1992).Forenterpriseswhodealinhigh- techindustry,keyaccountsplayastrategicrolei n theirshortandlongrun.Suchstrategiccusto mersdeservetobepaidmoreattentionbys u p p l i e r s S u p p l i e r s h a v e t h e s o u n d r e a s o n s t o i n v e s t m o r e r e s o u r c e s i n t h e keyr e se l l e r s inordertodevelopacloseand valuablerelationship,andmaintainhightrustb e t w e e n t h e dyad.T h e s e a c t i v i t i e s a r e i n c l u d e d i n a s t r a t e g i c w o r k i n g d e s i g n c a l le d KeyAccountManagementProgram.
K u m a r , 1 9 9 6 ; G e y s k e n se t a l ,1 9 9 8 s h o w e d t h a t b u i l d i n g a p r o g r a m l i k e keyaccountt e a m s w i l l l e a d t o a h i g h l e v e l o f t r u s t , a n d t h e n w i l l l e a d t o a l o n g t e r m commitmentbetween th e dyad.T h i s w il lg ene ra tea win- winrelationship fo ra lo ng r u n
Hightechnologyindustryishighlydynamic;it changesveryfastasthespeedoftechnologycircle.Technologicalproductsbecomeo b s o l e t e i n a verys h o r t p e r i o d , valueofsuchproductsdecreasesdaybyday.Doingbusinessinthisindustryrequireshig hcommitmentastheenvironmentiseverchanging.
Vietnamisadevelopingandtransformationaleconomy.Commitmentindoingb u s i n e s s isabigproblemputaheadforsuchfastchangingindustry.Itisarguedtha tVietnameseb u s i n e s s e s j u s t paymorea t t e n t i o n o n t h e s h o r t t e r m b e n e f i t s ; th eyc a n b r e a k theircommitment ateasetoachievetheirgoals.Especially,insuc haunstableand fastchangingenvironmentlikehightechnology,theproblemturnsoutt obequitepopular.Inordertocatchupwiththespeedofchangeintheindustry,andlon gforal o n g termandsustainabledevelopment,businessesshoulddevelopastrategyin b u i l d i n g trustandinturncommitmentamongthosebydevelopingstrategicprogra mssuchaskeyaccountmanagementprograms.
Ina t r a n s itioale c o oml i k e V i e t am,t ee’sa l a c k o f r e s e a r c h e s o n s u c h mentionedconstructs,theeffectsofkeyaccountmanagementprogramsontrustandint u r n commitment Especially, littleat ten ti on has beenpaidinthehigh- techindustry Theq u e s t i o n p u t f o r w a r d i s w h e t h e r s u c h c o n s t r u c t s a f f e c t t o t h e t r u s t a n d c o n s e q u e n t l y commitmentinthehightechindustry,howst rongtheyareandshouldtheydeservetobeinvestedmoreinordertobuildastrategyforlon gtermcooperationbetweendyads.Empiricalresearchisdeservedtobecarriedoutfora brighterviewinordertodrawpracticalimplicationsbyinvestigatingtheeffectsofKAMprogramsontrustandinturncommitment.
Problemstatement
AnumberofstudieshavebeencarriedoutontherolesofKAManditseffectsontrustan d com mitment.Willemetal.(2004)hasinvestigatedtherolesofKAMprogramsinthefast- movingconsumergoodsindustry.FatenBaddarAl-
HusanandRossBrennan( 2 0 0 9 ) havestudiedtheimplementationofstrategicacc ountmanagementinanemergingeconomyintheArabwordtoreasserttheimportantr olesandeffectsofthe key/strategicaccountmanagement programs.Suchmentionedresearchesand literaturee n c o u r a g e s investmentsinkeyaccountmanagementprogramstobuildtrustan dlong- te r m commitmentfromcustomers.InatransitionalandemergingeconomylikeVietn am,s u c h r e s e a r c h e s o n keya c c o u n t m a n a g e m e n t s p r o g r a m s h a s n o t , t o t h e a to’sb e s t k n o w l e d g e , r e c e i v e d muchi n t e r e s t s f r o m r e s e a r c h e r s , especially,i n t h e f i e l d ofhigh-techindustrywithafast-changingenvironment.
Therefore,theproblemaddressedinthisstudyistoinvestigatetheeffectsofkeya cc o u n t managementprogramso n t r u s t a n d t h e n o n c o m m i t m e n t f r o m V i e t n a m e s e d e a l e r s perspectiveinthehigh- techfield,suchastelecommunications,electricalappliances,andinformationtechnology.
Researchquestions
- Wat’steelatiosipbetweekea c c o t maaemetpoa m s ’ factosontrustand consequentlyoncommitment?
Researchobjectives
Theoverallobjectiveofthisresearchistoexamineeffectsofkeyaccountmanagementprograms tocommitmentviatrust.Keyaccountmanagementprogramsareconstitutedo f r es p o n s i ve n e ss , information, logistics, andtailor- madep r o m o t i o n s Therefore, th e specificobjectivesofthisresearcharetoinvestigateth efollowingrelationships:
Thisr e s e a r c h w i l l i n v e s t i g a t e s u c h r e l a t i o n s h i p s fromVie tn ame se d e a l e r perspective.C o n s e q u e n t l y , f i n d i n g s w i l l s h o w somef a c t s , a n d t h e n p r a c t i c a l implicationsareproposed.
ResearchMethodologyandScope
Thisr e s e a r c h f o c u s e s o n surveying8 keya c c o u n t s ( d e a l e r s ) inhigh- techi n d u s t r y locatedinalltheprovincesofVietnamwhereselecteddealershaveoffices andbranches.Totalcorrespondentswillbetargetedatabout210samples.
Ther e s e a r c h c o m p r i s e s 2 s t a g e s : p i l o t a n d mainstudy.I n t h e f i r s t s t a g e a q u a l i t a t i v e approachwasusedtoexplorewhetherthescalesformeasuri ngtheconstructsare suitable or not.T h e n , someamendmentsh a d beenmadewhere isnecessary.
Int h e seconds t a g e , a q u a n t i t a t i v e a p p r o a c h w a s e m p l o y e d Byi n t e r v i e w i n g dealers, d a t a w e r e c o l l e c t e d f o r analysis.T h i s p h a s e i s t o t e s t t h e r e l i a b i l i t y o f t h e m e a s u r e m e n t s c a l e s u s i n g C obac’sa l p h a c o e f f i c i e n t a n d E x p l o r a t o r y F a c t o r Analysis(EFA).MultipleLinearRegressionanalysis(MLR)wasemployedtotestther e s e a r c h modelandhypotheses.SPSSsoftwareversion16was usedfordataanalysis
Structureoftheresearch
Thestructureofthisresearchconsistsoffivechapters:Ch ap t er 1:Intr oduction
Thischapterpresentsresearchbackgroundofthestudy,aswellas,researchproblems,rese archobjectives,researchmethodologyandscope.
Inthischapter,literaturereviewhasbeensummarized.This chapterwouldpres entaresearchmodeloftheresearch.
Basedontheresearchobjectivesandscope,researchmethodologyc o n c e r n e d inc h a p t e r 1 , a n d l i t e r a t u r e r e v i e w a n d e m p i r i c a l modelp r e s e n t e d i n c h a p t e r 2 , t h i s chapterp a r t i c u l a r l y p r e s e n t s t h e r e s e a r c h methodolog y,data, researchd e s i g n a n d r e s e a r c h process.
Thischapterpresentsfindingsofthestudy,practicalimplications,contributionoft her esear ch Somelimitationsoftheresearchwillbementionedanddirectionsarer e c o m m e n d e d forfutureresearch.
Introduction
R e l a t i o n s h i p a m o n g t h o s e c o n s t r u c t s w i l l ber ev iew ed i n t h e s h i n e o f p r i o r s t u d i e s w h i c h w i l l i n c u r s o m e r e l e v a n t t h e o r i e s T h e purposeofreviewingtheliteratureistoclearlydefinetheconstruc tsandtoproposear e s e a r ch model,t he ntoge ne ra te h y p o t h e s e s w h i c h willbe t e s t e d i n t heV ie tna mese high-teci d stfomdeale’spespective
Inamodernbusinesssociety,KAMhasproveditsemergingimportance;literatureh a s d e v e l o p e d w i t h d i f f e r e n t f a c e t s o f K A M N e v e r t h e l e s s , a l t h o u g h em piricalstudieshasbeencarriedout,furtherresearchrecommendationswereurgedtot e s t d e e p e r i n a d i f f e r e n t e x t e n t , p a r t i c u l a r c o n t e x t R e s e a r c h e s ont h e r e l a t i o n s h i p betweentrustandcommitmenthavebeenconductedinthemarketinglitera ture.Geykensetal.
Therefore,themainpurposeinthisresearchistoinvestigatetherelationshi psa m o n g K A M f a c t o r s andtrust then commitment inthe business dyadsespeciallyinthefi eld ofhigh- techindustry.Inthefollowingsection,areviewoftheattributesofhigh- t e c h industryanditseffectswouldbepresented,thenadescriptionofthenatureofkeya c c o u n t managementprograms,trustandcommitment.Followingthisreview,asetofhypothe sesisdeveloped.Afterall,someconclusionswillbedrawnforfurthertestingp u r p o s e s
High-technologyattributesandtheireffects
Hightechnologyattributes
This research focuses on the high-tech industry, emphasizing the need to define the unique attributes of high-tech products that distinguish them from other categories Based on existing literature in high-tech marketing, five key attributes were identified Although numerous attributes have been explored in previous studies, they are interrelated and often appear across different texts These five attributes encompass the primary dimensions discussed in the literature, making it essential to classify the attributes and their effects within the high-tech sector before delving into a detailed literature review of the research model constructs Understanding these attributes will facilitate the formulation of clearer hypotheses, which are outlined in the following section.
Shortp r o d u c t l i f e c y c l e.H i g h - t e c h p r o d u c t s h a v e s h o r t e r l i f e c y c l e s t a g e s i n comparisonw i t h o r d i n a r y pr oducts ( R o s e n a u , 1 9 8 8 ) T h i s meanss u c h p r o d u c t s w i l l increasesalessharplyina veryshortperiodoftimeand decrease quickly.This showsac o n s t a n t technologicalchange,andwithitscontinuouschanges,itsprod uctlifecyclewillbeveryshortforaparticularproductline.
Greaterriskofdiscontinuouschangeinproducttechnology.Adiscontinuousch an g e i sunderstoodasachangethatcreatesatotalchangeinconsumption,customerp r o f i l e s …
Ifthishappens,businesscompetencewillbeeliminatedbecausecurrentkowledei s i c apablet o d e v e l o p a dmakete w p odctsat’sw i - techprodu ctshavegreaterchancesofdiscontinuityandbecomesobsoleteinaveryshortt i m e WeissandHeide,1993referredhigh- teca t t ibteas“unpredictability”I t ’ s ter e s u l t ofdiscontinuousinnovationinhigh- techindustry.
The indispensability of supporting infrastructure is crucial for the successful launch of high-tech products This infrastructure must adapt to the rapid changes in technology According to MacInnis and Heslop (1990) and Moriarty and Kosnik (1989), a well-established service network is essential in the marketing mix for high-tech products For instance, a mobile phone cannot be marketed effectively without a robust mobile network Supporting infrastructure includes complementary products that enhance the functionality of high-tech items, essential supplies and spare parts, and skilled service personnel for setup and repairs Without compatible and available complementary products, a high-tech product may become ineffective, struggle to penetrate the market, and fail to gain acceptance from end users.
Lackofwell-establishedindustrystandards.High- techproductsaredevelopedco n t in u o u sl y tomeetthechangingdemands.Thatmeanssuchproductss houldsatisfyt h e samen e e d s o p e r a t e w i t h d i f f e r e n t s t a n d a r d s T o g e n e r a t e a s t a n d a r d f o r b e cmaki, itsoldtakeavelot i m e I t ’ s ap edictablepocessA podctcurrentlyappearsasdominantdesign,butanewcomerwitharevolutionary designwillc o n f o u n d themarketandtakethedominantposition.AccordingtoUtterback(1994):
“A dominantdesignistheonethatwinstheallegianceofthemarketplace,t h e o n e t h a t c o m p e t i t o r s a n d i n n o v a t o r s s h o u l d a d h e r e t o i f theyh o p e t o com madsii f i c a tmaketsae”
Taketheexample ofA pp le withther e - i n v e n t i o n ofI p h o n e, ithasde fe ate d tosomeextent thelongdominanceofNokiainth emobilephonemarket.
High-tech products often exhibit significant uncertainty regarding their functionality, as highlighted by Moriatry and Kosnik (1989), who describe this phenomenon as "related certainty." End-users frequently struggle to align their needs with the benefits offered by these products Additionally, switching to another product incurs substantial costs A survey by O2 (2012) revealed that the primary functions of smartphones have shifted from making calls to using the internet, social media, music, and games, despite their original design for communication Furthermore, the rapid pace of market changes adds to the high uncertainty surrounding high-tech product functionality.
Effectsofhigh-techattributes
Shorter product life cycles significantly impact consumer segments at each stage, as highlighted by Anyan and Wortzel (1988) When rapid changes occur, firms must adapt their marketing strategies to align with customer segments on the innovation curve (Moore, 1991) As technology evolves, consumers seek new criteria for product evaluation (Christensen, 1997), prompting dealers and retailers to frequently adjust their orientations The shortening of product life cycles also influences pricing dynamics, leading to price declines that affect marketing costs and profit margins within the dyadic relationship Consequently, this necessitates closer cooperation and heightened trust between parties to enhance business performance for both sides.
Effectsduetothegreaterriskofdiscontinuouschangeinproducttechnolo gy.High- techproductsarecharacterizedbyunpredictableandsuddenchanges,suchc h a n g e s are followed byfluctuationonconsumptionpattern,user profile, complementary productsanddemandcurve(Robertson,1971).Thoserequiredealerst o improvethe irexpertisetodealwithsuppliers.Otherwise,dealerswillbeoutof date.
Furthermore,s u p p l i e r s w i l l r i s k l o s i n g maket’sc o fideceI f c l o s e c o o p e atioa dtrustarenotexisted,allabovebadeffectswillcausetroublesforbothsides.
Effectsduetothenon- existenceofindustrystandards.MoriatryandKosnik(1 98 9) s t a t e d t ati t ’ s e a s f os ppliesa dd i s t ibutorst o p e r s u a d e c u s t o m e r s iftee’eexistiidstialstadadsL a c k oftose,cstomeswillspedmoetimea n d e f f o r t i n s e a r c h p r o c e s s Firmsn e e d t o s p e n d morer e s o u r c e s i n c u s t o m e r education.Moreover,purchasingbehaviorinhig h- techproductsrequirescomplicatedp r o c e s s ofseekingandanalyzinginformationateverystage Thatforcesdealerstoc o l l e c t andlearnmoreknowledgetobestservetheircustomersforwi nningthem.Ah ig htrustandcooperationmannerisvitalforachievingthat.
Effectsduetotheindispensabilityofsupportinginfrastructure.Supportingi n f r a s t r u c t u r e developmentisveryimportantforhigh- techproductsadoption.Dealersw i t h closecontactswithcustomerswillgraspthestatus ofsupportinginfrastructureint h e market.B e s i d e s , i n s t a l l a t i o n a n d s e r v i c i n g playkeyr o l e s i n h i g h - t e c h p r o d u c t o f f e r i n g s ( M o r i a t r y a n d K o s n i k , 1 9 8 9 ; M a c I n n i s a n d H e s l o p , 1990).S u p p l i e r s w i t h well- trainedserviceteam,togetherwithgoodcooperationwithdealerswillsupportforthesuccesso fmarketinghigh-techproducts.
Effectsduetotheuncertaintyinproductfunctionality.Customersinhigh- techf i e l d r e a l l y c o n c e r n a b o u t t h e i n s t a l l a t i o n a n d maintenancea s t e c h n o l o g y isverya d v a n c e d , andbecomesobsoletequickly.Moreover,theswitchingc ostisquitehigh.Ins u c h uncertainty,to gainconfidencein customers,marketingmu stfocus oncreatingr e l a t i o n s h i p r a t h e r s e l l i n g p r o d u c t s ( M c K e n n a , 1 9 9 1 )
T h i s o n l y hap pe ns s i n c e suppliersanddealersworkonanu n i t e d o rg an iza ti on Th us, m u t u a l t ru st is required b e t w e e n thedyad.
Trust
[]tefim’sbelieftataotecompa willpefomactiostatwillesltinpositiveoutcomes forthefirm,as well as nottakeunexpectedactionsthatwouldresultinnegativeoutcomesforthefirm(Ander sonandNarus,1990,p.4 5 )
Butler(1991)suggestedtrustcompositionsincludetendimensions.Thoseareintegrity,co nsistency,promise- fulfillment,receptivity,loyalty,fairness,competence,d i s c r e t i o n , openness,andavailabilit y.Inthisresearch,anarrowerviewoftrustisconcerned,w h e r e t r u s t i s n e a r t o e t h i c a l t r e a t m e n t o f s u p p l i e r s r a t h e r t h a n o t h e r dimensionssuchascompete nce,openness,andavailability.Thisresearchmeasureststclosetoiteitadpomiseflfillmetfo mBtle’sdimesios
Trustoccursincognitiveandaffect- basedforms.Incognitiveform,trustimpliesreliableroleperformance,cultural- ethnicsimilarity,andprofessionalcredentials.Inaffect- basedform,trust actsasafunction ofc it ize nsh ip behaviorand interactionfrequenc y(McAllister,1995)(ascitedinRobert,2002)
KeyAccountManagement(KAM)programs
Responsiveness
Responsivenessreferstotheextenttowhichsuppliersdealwithdealers’problemsin an allowedtimeframeandeffectivemanner.Howpatientandwillingsupplierswillactu p o n de alers’complaits
Timeofresponseiswidelyacknowledgedasacompetitiveadvantagebyextantliterature,whic hraisestheimportanceofsupplyingtherightproductsattherightquality,pricewithina minimumlead- time(Stalk,1988).Toachieveresponsiveness,p a r t i c u l a r typesofflexibilitytothemarketsh ouldbeneeded;flexibilityisdefinedbyO x f o dictioaas“ a b i l i t t o a d a p t ” I maaemetl i t e ate,i t i s v i e w e d asreaction againstuncertaintiesinternallyandexternally(Gerwin,1993).
Literaturesuggeststhatsupplierswhocanrespondquicklytochangesincustom erd e m a n d s w i l l s i g n i f i c a n t l y i m p r o v e customers a t i s f a c t i o n ( R o b e r te t a l , 2 0 0 2 ) Asa r e s u l t , t r u s t w i l l b e e n h a n c e d asr e l a t i o n s h i p q u a l i t y a n d l o y a l t y a r e establishedduetoimprovedsatisfaction.Insuchad ynamicandfast–changinge n v i r o n m e n t o f h i g h - t e c h i n d u s t r y w i t h i t s c h a r a c t e r i z e d a t t r i b u t e s , r e s p o n s i v e n e s s appear s tobemoresignificantthananyotherfields.Therefore,
Information
Informationr e f e r s t h e e x t e n t o f i n f o r m a t i o n i s i m p o r t a n t l y e x c h a n g e d b e t w e e n t h e suppliera n d itsbuyer(MohrandSpekman,1994).Informationcontentsa r e shareds u c h asinventory,planning,capacity andquality, logistics, newproduc tknowledge, e t c …
Sharingofinformationrefersto“saiofmeaif ladtimeli fomatiob e t w e e fims
”( A desoa das,1 9 9 0 , p 4 4 ) Ifomatios aii s trulye ss en t ia l fortighteningthedyadr elationship(MohrandNevin,1990).
Informationsharingbringsbenefitstothebuyer- supplierrelationship:in fo rm at ion isdeliveredthroughout allparties,acloser relationship between buyerandsupplier,newinformationisexecutedaccuratelyandtimely(ZhouandBenton,2007).
NarayananandRaman(2004)foundintheirstudiesoninformationsharingthatinsom ecases,informationishiddenbysuppliertobenefitthemselves,buteventuallyg o t f a i l u r e i n t h e w h o l e s u p p l y c h a i n T h e r e f o r e , informations h a r i n g s h o u l d a t t a c h w i t h integritytobuildtrustbetweenthedyadforalong-termcooperation.
(ascitedinTho,2011).Informationsupportfromsupplierscancreatevaluefort h e dyadicrelationships.Oncei nformationflowissmoothlytransferredfromsupplierst o cstomes,cstomescaaticipatespplies’state icmovesadpotetialca e s intheindustry.Inthehigh- techindustry,changesofinformationhappenquicklywithh i g h speed,anaccurateandc ontinuousflowofinformationexchangedfromsuppliersw i l l fosterthemutualrelationshi p,henceincreasetrust.Thus,
Logistics
Logisticalconsiderationsappearinorderstakingandfulfilling.AndersonandWeitz( 1 9 9 2 ) e dsppliesto makee a v ivestmet il o isticssocalled“idioscatici vestmet ”
Negri(1997)suggestedthatlogisticsqualityshouldbetakenintoconsiderationandlogisticseffectivenes sshouldbeevaluatedtogetherwithcustomerorientationby:Analysis,whichistointerpretloisti csfocstome’sdemadadspplie’scapacit; Plai, wicistoassesscstome’sexpectatioadpece ptiooqalit;Production,whichistodefine,designandmanagelogisticscomponent s;Control,w h i c h istoevaluatelogisticsperformanceandqualitylevels.
Loisticsqalits oldbepaticlaizedtos pplie’ssevicefactostos atisfc stome’s e q iemetso s e iclde:sevicepolic, delivess t e m , people,andinternalorganizatio ntoassureessentialfunctions,long-termsupplier-customerrelationship.
Logisticsoperationsalsoreflect theperformanceofdelivery.Tho (2011)assertst h a t d e l i v e r y p e r f o r m a n c e c o n t r i b u t e s t o t h e v a l u e o f dyadicr e l a t i o n s h i p T h e r e a r e three a s p e c t s o f d e l i v e r y p e r f o r m a n c e : o n time,f l e x i b i l i t y a n d a c c u r a c y ( U l a g a a n d E g g e r t , 2006)(ascitedinTho,2011).
Logistics,therefore,playsanimportantroleinbuildingtrustand commitmentbetweent h e dyadonalong-termbasis.Consequently,
Tailor-madepromotions
Tailor-made promotions are customized promotional activities designed specifically for dealers, allowing them to differentiate themselves from other programs This promotional mix includes advertising, direct marketing, personal selling, sales promotions, and public relations Unlike business-to-customer strategies, these promotional activities are specifically tailored for a B2B context, focusing on the needs and preferences of dealers.
Inhigh- techindustry,promotionalactivitiesneededtobetailoredcasebycasefordifferentke y accountsinorderforsuppliertoeffectivelyrunthemarketingcampaigns.Un li ke anyothe rtypesof cus to mer s, keyaccountsplayac r u c i a l rolein supplie’ss a l e s state, p om otioalact iv it iess oldo t be masswici s m o esuitablefortraditionalaccounts.Therefore,
Commitment
Commitmete f e st o “ t ea d o p t i o o f a l o - t e r m o r i e n t a t i o n t o w a r d s t h e elatiosip”(AdesonandWeitz,1992,p.19)andgoesbeyondasimpleevaluationo f t hecostsandbenefitsassociatedwiththerelationship.This describesthewillingnesstomakeshort-termsacrificestorealizelong-termbenefits
Buchanen(1974)suggeststhatcommitmentcomprisessubjectivefacetsof elatiosips“ a p a tfompeli stmetalw o t”F o i st ace,commitmetmaconsistofaff ectivebondsandfeltobligations.
Trust and commitment are essential factors in fostering strong business relationships, leading to positive outcomes such as improved attitudes towards partnerships and enhanced partner performance Positive attitudes include mutual satisfaction and a willingness to collaborate, which encourage cooperative behaviors, higher risk-taking, and a reduced likelihood of opportunistic actions Additionally, commitment is associated with better performance by reducing uncertainty, increasing efficiency, and positively influencing economic results In the high-tech industry, where unique characteristics are prevalent, both trust and commitment are crucial and interconnected for success.
ConceptualModel
( 2 0 0 4 ) ,a c o n c e p t u a l modelisdevelopedandshownintheFigure2.1.Themodeld escribesther e l a t i o n s h i p s betweenfactorsofKAMprogramsandtrust,andconsequ entlyonc o m m i t m e n t
Summaryofhypotheses
H1:ResponsivenesshasapositiveeffectonTrustH2:Inf ormationhasapositiveeffectonTrustH3:Logisticshasa positiveeffectonTrust
Introduction
Theoreticalframeworkoftheresearchwasdiscussed inthepreviouschapter.Int hisc h a p t e r , r e s e a r c h m e t h o d o l o g y w o u l d b e i n t r o d u c e d , i n c l u d i n g r e s e a r c h d e s i g n , co stcts’measurementscales,sampling,statisticaltoolsusedtoanalyzedat aandtestthehypotheses.
Researchdesign
Thestudywascarriedoutin2phases:apilotandamainsurvey.Respondentsw e e d e a l e s’p u r c h a s i n g managers,s h o p / f l o o r managersa n d o w n e r s P r o d u c t t y p e s w e r e mobilephones,informationtechnology,andelectricalappliances.
Measurement
Independentvariables
Independentvariableisalsoconsideredaspredictors.Thisvariablewillhaveaninfluencei n d e p e n d e n t v a r i a b l e i n a p o s i t i v e o r n e g a t i v e manner.I n t h i s study,t h e indepe ndentvariableiskeyaccountmanagementprogramswhichcompriseR e s p o n s i v e n e s s , Information,Logistics,andTailor-madePromotions.
Resposiveessisteextettowicsppliesdealwitdeale’spoblemstimela deffectively.Res ponsivenesswasmeasuredby6criteriaintroducedbyWillemetal.(2004):
Logisticsreflectshowsupplierstakeandfulfillorders,theperformanceofdelivery.Inthisstud y,logisticswasmeasureby5items,takenfromWillemetal.(2004):
L4 the ordersremainadequate eveninthecaseofrisingdemand asa consequenceof promotionalactivities;and
L5 enoughinfomatioa b o tte“odet a k i ”ic a s e delivep oblemsocc
Tailor- madep r o m o t i o n s r e f e r t o promotionala c t i v i t i e s w h i c h a r e t a i l o r e d o r customizedfordealers t o o ff er anadv an tag e of differentiationfromotherprogra ms Tailor-madepromotionsweremeasuredby7items,introducedbyW i l l e m etal.
Tailor- madepromotions (Cronbach’salpha=.889)C o n c e r n i n gtheirpromotionalactivities,firmxhas
Dependentvariables
Inthis studytrustis the dependent variablea n d playsa s am i d d l e r o l e between ke ya c c o u n t managementprogramssub- dimensionsandcommitment.Trustisadependentv a r i a b l e t o keya cc o u n t m a n a g e m e n t p r o g r a m s s u b - d i m e n s i o n s , b u t i s a l s o a n d ep en dent v a r i a b l e t o c o m m i t m e n t I n t h i s study,t r u s t w a s measuredby5 itemsd e v e l o p e d byWillemetal.(2004):
Commitmetitisstde f e sto“teadoptioo f alo- t e r m orientationtowardsthe elatiosip”(A desoadWeitz,1 9 9 2 ,p 1 9 )a dwa s measedb6itemsisscalewastakenfro mWillemetal.(2004)andpartiallyadoptedfromAndersonandWeitz(1992):
Questionnairetranslation
The survey questions were translated into Vietnamese by a committee consisting of the author and his sister, an English teacher at an international language school, to minimize discrepancies in translation After a thorough review of each translation, a group discussion was held to reach a consensus on the meaning of the survey questions Ultimately, a draft of the Vietnamese questionnaire was created for a pilot study.
Thequestionnairewasdistributedtotherespondentsonanonlinesurveybasis( www.docs.google.com ).I n t h e o n l i n e s u r v e y m e t h o d , t h e q u e s t i o n n a i r e w a s made virtuallyasaweb- pagethenthelinksweresenttotherespondentsviaemailormeanso f internetcommunication.
Pilot study
Thisphasewasconductedtorefinethequestionnairetomakeclearallthequestionsinthesur veyinordertoimprovethequalityofthedatacollectedfromrespondents.Thisp h a s e includ es2steps:qualitativeandquantitative.
Inthefirststep,anexploratorywasconductedstudytoassessthemeasurementscale s.Anin- depthdiscussionwith3dealers(purchasingmanagersofkeyaccountsinmobilep h o n e s s e c t o r ) w a s m a d e toclarifya n d makec l e a r t h e m e a n i n g o f s u r v e y q u e st i o n s an d modifythemeasures.This step iscriticalasmeasuresofconstructs wereapp ro priate la d j stedfot is std’scotext
Int h e s e c o n d s t e p , ani n i t i a l c o l l e c t i o n o f 5 0 samplesw a s m a d e t o t e s t t h e r eli abil ity ofthevariablesinordertorefinethemeasures.Cobac’salphareli abilitya n d exploratoryfactoranalysis(EFA)wereemployedtoassessthescales.Co bac’salphaso f a l l t h e v a r i a b l e s w e r e s h o w n t o beh i g h e r t h a n 7 0 F o l l o w i n g N u n n a l l y ( 1 9 7 8 ) ,a n a l p h a o f 7 0 o r g r e a t e r i s d e s i r a b l e f o r e a c h v a r i a b l e toh a v e a l e v e l o f internalconsistency.TheresultsshowedthatCobac’salp hasofthescaleswereallhigherthan.80indicatingallscalespassedthereliabilityrequirement s.
Main study
Thestudywasconductedusingelectronicsurveytechnique,fromwhichquestionnairesw e r e d i s t r i b u t e d v i a emaila s o n l i n e s u r v e y l i n k s s u p p o r t e d byG o o g l e (ww w.d ocs.goog le.com )toalistofrespondentswhoworkatselecteddeales’offices andbrancheslocatedinalltheprovincesofVietnam.Thepurposeofthismainsurveywasto validatethemeasuresandtesttheresearchmodel.
(Nunnally,1978).ItemswhichhaveCobac’salphacoefficientnotlessthan0.7area c c e p t e d (Nunnally,1978).Thefiltereditemsthenwouldbeanalyzedbyexploratoryf a c t o r analysis(EFA)method;itemswhichhaveloadingfactorslessthan0.4shouldber e m o v e d Atlast,multiplelinearregressions (MLR)wase mp lo yed torunthe r emaini n gitems,theresultsthenwereusedtotesttheresearchmodelandhypothesis.
Researchsampling
Samplesize
Itisarguedthatthelargersamplesize,thebetterstudy.However,itcostsmuchtoo.T h e r e f o r e , ana ppropriatesamplesizesoldbedesie dtobalacetetade- offbasedo teexpeieceoftepevioseseaces(, 200,p3HoChu,2005,p263).
Selectingthesamples
Alistof8keyaccounts(dealers)wereselectedtoengageinthestudythroughtheato’sc aeerrelationships,thesedealersarebigaccountsofmanyh i g h - t e c h suppliers,dealingindifferenttypesofproductsinthehigh- techindustry,whicharemobilephonessector(i.e.Nokia,Sams,
…),electronicappliancesandinformationtechnologysector.Thesedealershaveasellingchain systemandaccountforalargep o tioo f s pplie’ssalesesedealeshavebranchesandshopsstretchingalongthe countryandcanbenamedasThếGiớiiĐộng,VinThôngA,NguynKim,Viettel,ĐiệnMáyCh ợLớn,ThiêH o ,PướcLập,FPTRetail.
Respondentsw e r e t h e o n e s w h o h a v e a v o i c e i n buyingd e c i s i o n T h e y we r e p u r c h a s i n g managers,ownersandhadbeenmostlyworkinginHoChiMinhCity,th erestofrespondentswhowereshop/ floormanagershadbeenworkinginotherprovinceso f Vietnam.Thisstudywasconductedtot estthehypothesesandresearchmodelfromp er sp e ct iv e ofdealerswhohaveavoiceinbuyin gdecisionprocess.
Collectingdata
Basedo n t h e p r i n c i p l e s o f c h o o s i n g t h e s c o p e a n d m e t h o d o f s a m p l i n g , w h i c h a r e lowercosts,moreaccurateresults,fastdatacollectionandavailablepo pulation( D o n a l d &Pamela,2003),aconvenientandnon- probabilitysamplingwasused.Thisist h e mostv i a b l e m e t h o d d u e t o l i m i t a t i o n s i n ti mea n d c o s t s H o w e v e r , w i t h eseace’sexpe iecesfoeasiteidst, alistofkeaccot s wasfilteedtoch oosethemostappropriaterespondentstotak epartinthesurvey.
ThemainsurveywascarriedoutfromAugust10,2012toSeptember12,2012bythe authorandsomecolleagues.250linksandcopiesofthequestionnaireweresenttothetargete drespondentsbyemail.Theauthoralsoaskedtherespondentstorecommendthelinktot heircolleaguesatthesamelevel.Afterthequestionnairewass e n t , theauthorhadre mindedtherespondentstoansweruntilthetargetednumberofr e sp o n se s wasmet.
Statisticaltools
Cleaningdataprocess
Datawouldbecleanedbeforeanalyzing.Datacleaningwasmadetopreventany p o s s i b l e mistakeswhichareprobablymissingdataorunreasonableanswers(Nguyen,2 0 1 1 , p.275). Among44multiplechoicequestionspresentedinthequestionnaire,38q u e s t i o n s werequan titativeandtherestsweresocial- demographicqualitative.Theanswerswerereviewedtocheckiftherewasanyillogicalanswert hatconflictedwitht h e w h o l e a n s w e r s Asa l l teq estiosweep ta s “ eqied”,teewouldb e n o missinganswersintheresponses.
Reliability
Totestthereliabilityofthemeasurementscales,Cobac’sAlphawasusedtodefinew h e t h e r t h e m e a s u r e m e n t s meett h e i n t e r n a l consistency.N u n a l l y ( 1 9 7 8 ) s u g g e s t e d thatascalewithCronbac’sAlpha is.70orgreaterisacceptedasinternalconsistency.
ExplanatoryFactorAnalysis
The Cobac Alpha was utilized to assess the reliability of measurements, but it is essential to establish their validity as well Two key types of validity are discriminant and convergent validity, which can be evaluated using exploratory factor analysis (EFA) EFA is an interdependence technique that focuses on the relationships among variables rather than treating them as independent This method refines a group of observations into a more meaningful set, ensuring that items with loading factors below 0.5 are excluded Additionally, items with loading factor differences less than 0.3 should also be removed An eigenvalue of at least 1 is considered the minimum threshold for significance in this analysis.
Incaseafterrunning EF A the numberof factorsis largerthanth e n u m b e r of factorspredictedinthetheoreticalframework,thenewfactorswillbetestedagain intermso f r e l i a b i l i t y a n d t h e r e s e a r c h m o d e l s h o u l d b e a d j u s t e d b e f o r e t e s t i n g t h e r e s e a r c h modelandhypotheses.
Regressionanalysis
Multil i n e a r r e g r e s s i o n ( M L R ) w a s employedt o t e s t t h e e f f e c t s o f k e y a c c o u n t p oams’f a c t o so tsta dc o mmitment.P r i o r t o r u n n i n g t h e r e g r e s s i o n , thev a r i a b l e s werecomputedusingmeanequationandMLRassumptionswerealsotestedf o r appropriateness.
Conclusion
Thischapterdiscussedthemethodology oftherese ar ch ; theprocessofresearc hwasal so introduced.Themeasurementscalesweretestedandthemainstudywas carriedo ut , d a t a w e r e c o l l e c t e d f o r analysis.I n n e x t c h a p t e r , t h e r e s u l t o f t h e r e s e a r c h a n d f i n d i n g s wouldbedrawnfordiscussion.
Introduction
Thischapterpresentsthedemographic andstatisticalanalysisof thesamples,tes toft h e reliabilityofthemeasurementscales,ExploratoryFactorAnalysis,MultipleLinearR e g r e s s i o n analysis used totestthehypotheses.Toolsto beused intheanalysis areMicrosoftExcel,SPSS16.0software.Explanations,answerstotheresearchquestion sa n d otherfindingsofthestudywillbepresented.
Datacleaning
208copiesofresponseswerereceived,acheckofsocialdemographicquestionswa smadeandlogicalcheckingwasalsoconducted.6ofthoseappearedtobeillogicalafterr e v i e w i n g areverse- scoredquestion(question38inthequestionnaire).Theremainingo f2 0 2 q u a l i f i e d sa mplesw a s us e d f or analyzing.N o missingda t a w a s f o u n d i n t h e d a t a table.
Descriptionof thequalifiedrespondents
In a study involving 202 qualified samples, 145 (71.78%) respondents were male and 57 (28.22%) were female The majority of participants worked in the mobile phone sector (78 respondents, 38.61%), IT (70 respondents, 34.65%), and electrical appliances (54 respondents, 26.73%) Most respondents engaged with distributors (139 samples, 68.81%), while the remaining 63 (31.19%) worked directly with brand owners Regarding education, a significant portion of respondents were college and university graduates (146 respondents, 72.28%), with only 4 being business owners Additionally, 59 respondents were purchasing managers, and the rest (68.81%) were shop or floor managers Most respondents operated in branches (127 samples, 62.9%), with the remainder based at the head office Further details on the descriptive statistics of the variables can be found in Appendix II.
Social-demographicvariables(n 2) Frequency Percentage(%) Typesofproductstherespondentsdealin
ReliabilityTestof measurement
FollowingNunally(1978),aCobac’sAlphaof.70orgreaterisdesirableforascalei n terms ofinternalconsistency.Reliabilitytestshowedthatallvariablesweregreaterthan.70,t husthemeasurementscaleswerereliable.
Inparticular,responsivenesswasmeasuredby6items(fromR1toR6)h a d aC ob ac’sAlphaof.949.Informationwasmeasuredby8items(fromI1toI8)hadaC obac’sAl phaof.891.TheCobac’sAlphaofLogisticswhichwasmeasuredby5 items(fromL1 to
The reliability of the measurement scales was assessed using Cronbach's Alpha, with L5 showing a value of 883 Tailor-made promotion programs were evaluated with seven items (P1 to P7), yielding a Cronbach's Alpha of 889 Trust, measured by five items (T1 to T5), had a Cronbach's Alpha of 867 Commitment was assessed using six items (C1 to C6), resulting in a Cronbach's Alpha of 922 A summary of these measurement scales and their respective Cronbach's Alphas is presented in Table 4.3, with more detailed information available in Appendix III.
ExploratoryFactorAnalysis
Afterrunning thetest o f r el ia bi li ty oft he va r i a b l e s, allthe re tai ne d itemst h e n we r e t e s t e d byEFA.Thisstagewascarriedouttofilterandexplorethecomponentsthatcane x pl ain t h e c o r r e l a t i o n s amongv a r i a b l e s E F A w a s r u n t o minimizet h e n u m b e r o f variablesfromalargeroneandenablethenewcomponenttoexplainthemostchara cteristicsoftheoriginalvariables.Thecomponentsextractedcouldrepresentfora discriminantfacetsofthestudiedconstructs.Theextractedcomponentsthencouldbeu sedforfurtheranalysisasindependentvariables.
InEFA,thetwomethodsofextractionhavecommonlybeenusedareprincipalco mponentanalysisandprincipalfactorsanalysis.Ifthegoalofanalysisistodetectst ructure,it ispreferred touse principalfactors analysisand ifthe goalofanalysisistor e d u c e d a t a , i t isr e c o m m e n d e d t o u s e p r i n c i p a l c o m p o n e n t s a n a l y s i s A l t h o u g h, t h e twomentionedmethodsalmostyieldsimilarresults(Statsoft,20 08).
Inthisstudy,theprincipalcomponentsanalysiswithVarimaxrotationtechniquewasused This m e t h o d ap pea re dt o be bet te r as MLRwas i nt en ded torunat a later stage,c hoosingthatmethodcouldreducethevariablestosupportforthenextstepofr eg r es si o n analysis.
EFAresultswereshowninthetable4.4,fromwhich5factorswereextractedinsteadof4f actorsaspredictedintheliteraturereviewandresearchmodel.The5e x t r a c t e d factor shaveeigenvaluesofgreaterthan1,and totalvarianceexplainedof7 39%A l l tefactos’loadis weee a t e t aK M O adBalett’ se s t w e r e
.817(p=.000),representedEFAwasappropriateandallthemeasurescouldbeusedf o r furtheranalysis.However,oneitem(P4)wasdiscoveredtohavealoadifacto’sd i f f e r e n c e lessthan.30(.572-.534),thenitwasdeleted.
ExtractionMethod:PrincipalComponentAnalysis.R o t a t i o n Method:VarimaxwithKaiser Normalization.
Ane wf a c t o r ( c o n s is t e d o f I 8 , I 3 a n d I 4 ) w a s ex t r a c t e d T h e au t h o r c a r e f u l l y c o n s i d e r e d t h e m e a n i n g s o f t h o s e itemsa n d f o u n d t h a t theyb e l o n g t o a g r o u p o f information concerningabouttheproductdevelopment{whichwerepro ductinnovations(I3),newproductintroductions(I4),samplesofin- store promotionmaterials( I 8 ) } T h u s , t h i s n e w f a c t o r w a s d e c i d e d t o k e e p a n d c o n s i d e r e d a s a n independentvariable,namedasProductInformation.T heremainingitems(I1,I2,I5,I 6 , a n d I 7 ) w e r e k e p t a t t h e c u r r e n t f a c t o r , b u t t h e v a r i a b l e n a m e w a s r e v i s e d a s MarketingandSalesInformation.
Ther e l i a b i l i t y o f t h e 2 n e w v a r i a b l e s w a s t h e n r u n t o t e s t i f t h e i r i n t e r n a l consistency validity wasmet.Ifthereliabilityofthetwonewvariablesweremet,thentheywouldbeusedforfurt heranalysis.Testofreliabilityof2newvariablesshowedth at theyw e r e a l l a b o v e
7 0 andw e r e a c c e p t a b l e I n d e t a i l s , M a r k e t i n g a n d S a l e s Informationh a d a Cobac’sA l p h a o f 9 0 1 a n d P r o d u c t I n f o r m a t i o n h a d a Cobac’sAlpha of.845.Table4.5showednewvariableswithCobac’sAlphasofth ei r measurement scalesafterrunningthe EFA.Moredetailson measurementscale reliability’stes tingresultsfornewvariablescanbefoundinappendixIV.
Analysisofcorrelations
Beforet e s t i n g t h e h y p o t h e s e s a n d r e s e a r c h modelp r o p o s e d i n t h e literaturer eviewc h a p t e r , atestofcorrelationbetweendependentvariablesandindepende ntones,andamongd e p e n d e n t v a r i a b l e s w e r e made.S i n c e t h e n , M L R w o u l d b e r u n t o c o n f i r m tho se relationships.Amatrixofcorrelationswasshowninthetabl e4.5,fromwhichitw a s expectedthattherewerepositiverelationshipsbetweenK eyAccountPrograms’f a c t o r s andTrust(H1toH4),andpositiverelationshipbetweenTru standCommitmentas well.
TestofHypotheses
TesttheappropriatenessofmodelandassumptionsforMLR
BeforeM L R w a s r u n t o t e s t t h e h y p o t h e s e s , t h e a p p r o p r i a t e n e s s o f t h e m odela n d v ari ab l es andassumptionsofMLRmustbemet.
Therewasonedependent variable(Trust) forthemodel1torunMLRand it wasq u a n t i t a t i v e v a r i a b l e T h e r e f o r e , t h e a p p r o p r i a t e n e s s o f t h e m o d e l a n d v a r i a b l e s w a smet.
Assumptionso f M L R w e r e t e s t e d t o c h e c k i f t h e r e s u l t s w e r e r e l i a b l e T w o assumpt ions w o u l d bet e s t e d T h e f i r s t o n e i s t h e r e l a t i o n s h i p s b e t w e e n d e p e n d e n t variableandindependentvariables togetherwithhetero skedasticityphenomenon,thesecondoneisnormaldistributionofresidualparts.
TheresultsshowninappendixVI.aprovedthattheassumptionoflinearr el a t io n sh i p andunchangedvariancewasmet.ThediagramQ-
Followingthecorrelationanalysis,therelationshipswereexistedamongthevariables.H o w e v e r , inordertoconfirmthoserelationships,multiplelinearregressionwasemployedto testthehypotheses.ENTERmethodwasusedasthenatureoftheresearchisconfirmatoryratherthan exploratory.
Thef i v e i n d e p e n d e n t v a r i a b l e s , w h i c h w e r e R e s p o n s i v e n e s s , M a r k e t i n g a n d S a l e s Information,ProductInformation,Logistics,Tailor- madePromotions,werea d d e d t o e x a m i n e h o w t h e s e v a r i a b l e s e x p l a i n t h e d e p e n d e n t v a r i a b l e (i.e.Trust).Resultsa p p e a r e d i n t h e t a b l e 4 6 , 4 7 a n d 4 8 T h e r e s u l t s r e p o r t e d t h a t t h e m u l t i c o l i n e a r i t y wasnotviolatedduetoall theVarianceInflationFactorwerelowert h a n 2 2 0 ( V I F < 2 2 0 ) T a b l e 4 6 s h o w e d t h a t t h e i n d e p e n d e n t v a r i a b l e s e x p l a i n e d 74.3%varianceinTrust(adjus tedR 2= 743,F(5,196)7.36,p=.000).Thevalue ofadjustedR 2was ratherhigh,implyingthatthedatawerewellfittedwiththemodel.
1 866 a 750 743 33938 a.Predictors:(Constant),Tailor- madePromotion,R e s p o n s i v e n e s s , ProductInformation,Logisti cs,MarketingandSalesInformation
Model SumofSquares df MeanSquare F Sig.
Total 90.165 201 a Predictors:(Constant),Tailor-madePromotion,Responsiveness,ProductInformation,
Model B Error Beta t Sig e VIF
Withrespectsofthemagnitudeoftheeffects,RegressionresultsshowedthatRe sp o n s i v e n e s s waspositivelyrelatedtoTrust(=.206,p=.000).HypothesisH1was,therefore,supported.ResultsalsosupportedthehypothesesH2a,H2bandH3.T o
Tailor-made Promotions interprettheresultsofthemodel,MarketingandSalesInformationhadapositiveeffectonTrust(
However,t h e r e s u l t s d i d n o t s u p p o r t t h e H 4 , i n t e r p r e t e d t h e f a c t t h a t t h e r e w a s n o statisticallysignificant1relationship b e t w ee n Tailor- madeP r o m o t i o n s an dTrust.F i g u r e 4.2summarizedtheresultsofmodel1.
T r u s t a n d Co m mi t men t ( H 5 ) T h e r e s u l t s were showni n t h e table4.9,4.10a n d
4 1 1 T h e mult ico l in eari ty wasnotviolatedasVIFwasalsolowerthan2.20.
Theresultsintable4.9reportedthattheadjustedR 2is 707,p=.000,atotalv a ria n c e of 70.7%in Commitment wasexplained.RegressionresultssupportedthehypothesisH4,indicatingthattherewasaposit iveeffectofTrustonCommitment(
Model R RSquare AdjustedRS q u a r e Std.Erroroft h e Estimate
Model SumofSq u ares df MeanSquare F Sig.
Total 103.571 201 a.Predictors:(Constant),Trust b.DependentVariable:Commitment
Conclusions
Thischapterhadpresentedtheresultsanalysisofthestudy.ExploratoryFactorAnalysis wasemployedtoreduceinsignificantvariables; statisticalresultsshowedthatt h e r e w a s h y p o t h e s i s w a s n o t s u p p o r t e d a s e x p e c t e d i n t h e l i t e r a t u r e r e v i e w N e w variablesw e r e d e r i v e d f r o m o r i g i n a l v a r i a b l e ( i e I n f o r m a t i o n v a r i a b l e ) , t h e n theycouldbetterexplaint hedependentvariable.
Thischapterpresentsthefindingsofthestudywithdiscussionsintheshineofpreviousstudies.Pra cticalimplicationsofthestudyforbusinessmanagements,contributionsoft h e study,l i m i t a t i o n s a n d r e c o m m e n d a t i o n s f o r f u t u r e r e s e a r c h e s w i l l a l s o b e d i s c u s s e d
Findingsofthestudy
Asstatedinthechapter1,thepurposeofthisstudyistoinvestigatetheeffectsofKeyAccou ntM a n a g e m e n t ProgramstoC o m m i t m e n t v i a T r u s t fomV ie t amesed e a l e ’sp e r s p e c t i v e i n t h e h i g h - t e c h i n d u s t r y T h e r e s u l t s o f analysisr e v e a l e d u n e x p e c t e d outcomes. Notallpredictedhypothesesweresupported,howevertherewerereasonablee x p l a n a t i o n s stoodbehind.
ThefirstresearchquestionregardsabouttherelationshipsbetweenKeyAccountMan ag e m ent Programs(4sub- dimensions)andTrust,andconsequently theeffectofT r u s t onCommitment T he resultsindicate thatsomefactorsof K e y AccountM a n a g e m e n t Programshav epositiveandsignificanteffectsonTrust.Thisfindingisinl i n e w i t h W i l l e me t a l
Responsiveness has a significant positive effect on Trust in the high-tech industry, with a standardized coefficient of β = 206 (p < 000) Following this, Product Information also contributes positively to Trust (β = 189, p < 000), while Logistics has a modest positive impact (β = 144, p = 005) Interestingly, tailor-made promotions, which were expected to significantly influence Trust, do not show a meaningful relationship In the fast-paced high-tech market, where product lifecycles are short, timely and accurate information is crucial for maintaining strong supplier-dealer relationships If suppliers fail to respond quickly to market changes, they risk losing business Continuous updates on product information are essential, especially in the high-tech sector, as consumers increasingly seek new criteria for evaluating products Responsiveness not only reflects how suppliers address issues but also plays a critical role in building Trust, which is confirmed by the research findings Additionally, effective logistics are vital for suppliers to meet customer satisfaction.
Logistics plays a crucial role in building trust and fostering long-term relationships between suppliers and customers, supported by effective service policies, delivery systems, and dedicated service personnel Tailor-made promotions, designed to provide dealers with a competitive advantage, were found to have a positive impact in the FMCG sector, as confirmed by Willemetal (2004) However, in the high-tech industry, the study revealed that tailor-made promotions did not significantly enhance trust, as suppliers often rotate these programs, making them a standard offering rather than a unique contribution Additionally, the study highlighted that trust has a profoundly positive effect on commitment, aligning with findings by Jhih-Ming Lai et al (2009), which indicate that partner trust significantly influences partner commitment.
Thesecondresearchquestionwasalsorevealedinconsiderationthestrengthofe f f ect s ofKeyAccountManagementPoams’sub- dimensions.Resultsreportedthee f f e c t strengthofsuchdimensions inthetable 5.1,fromwhichMa rke ti ng andSales Informationstronglye f f e c t s Trust,thenResp onsiveness,ProductInformationandLogisticshavelowereffectsonTrust.
C o m m i t m e n t supportedbytheresults).Thisrecommendssupplierstopaystrictatte ntiontosuchideaandinvestmoreresourcestoit.AsMarketingandSalesInformationi s d e l i v e edt o d e a l e st o s pplie’ssevicep e o p l e ( i.e.,s a l e s a n d marketingw o r k f o r c e ) , i t i s w o r t h i m p r o v i n g p e r s o n a l iteactiobetwees pplie
’sservicepeopleanddealersinordertoenhancethemutualrelationship,henceimprovet r u s t andlong- termcommitmentassuggestedbyTho(2011).Furthermore,Responsiveness a l s o d e s e r v e s f o r supplierst o t a k e i n t o a c c o u n t f o r t h e i r r e s o u r c e s allocationasits effectonTrustistrulyhigh,thentheotherdimensions,sayLogistics,P r o d u c t I n f o r m a t i o n s h o u l d b e t a k e n f u r t h e r a c c o u n t R e p o r t ofanalysisd o e s n o t recommendforheavyinvestingon Tailor-made
Practicalimplications
Realizingtheimportance ofK e y AccountManagement Programsi n c l u d i n g th esub- d i m en s i o n s , thisstudywasaimedattestingtheeffectsofsuchdimensionsinorderforsupp lierstoallocatetheirlimitedr e s o u r c e s t o b u i l d t r u s t , a n d h e n c e c o m m i t m e n t b e t w e e n t h e d ya d s i n t h e h i g h - t e c h i n d u s t r y T h e s t u d y reveals m e a n i n g f u l p r a c t i c a l implicationsformanagers.
This study highlights the significant impact of trust on commitment within the dynamic high-tech industry To foster long-term, mutually beneficial business cooperation and avoid defaults in transactions, it is essential for managers to adopt cooperative behaviors This is particularly crucial in the high-tech sector, where commitment is vital for achieving strategic benefits (Ji-Ming Lai et al., 2009).
Secodl,io det o w i d e a l e ’st s t , s ppliesmsti n v e s t p r o p e r l y i n KeyAccou ntManagementProgramsattachedbythesub- dimensions.Thestudyalsor e v e a l s thatinsuchthehigh-techindustry,thesub- dimensionsofKeyAccountMa n a g em e n t Programs(includingMarketingandSal esInformation,Responsiveness,
Product information and logistics significantly enhance trust in business relationships, prompting managers to focus resources on these impactful areas The study highlights that marketing and sales information, responsiveness, and product information warrant the largest share of resource allocation This emphasizes the importance of developing sales force competencies to foster trust and build relationships through personal interactions Logistics also plays a crucial role in enhancing trust, while heavy investments in tailor-made promotions are not advisable, as they do not substantially contribute to trust between parties This finding contrasts with previous literature, particularly in the FMCG sector, where promotions are deemed essential for boosting sales The disparity is attributed to the varying nature of industries, with the high-tech sector relying less on promotions compared to FMCG.
Contributionsofthestudy
T r u s t a n d C o m m i t m e n t T h er e f o r e , itcontributestotheliteratureonKeyAccountManage mentPrograms,Trusta n d C o m m i t m e n t F i n d i n g s a r e c o n s i s t e n t w i t h p r e v i o u s r e s e a r c h e s i n l i g h t o f s u c h r el a t io n s h i p s
(2004)toexpandthescopeofstudytomorecountriesandinvestigatelargersampleswith differentbrands fromdifferentproduct categories,t h i s s t u d y w a s c a r r i e d o u t i n t h e c o n t e x t o f high- techi n d u s t r y o f 8 keya c c o u n t s andcontributesthefindingstothecurrentresearchproblem s.
Limitationsandrecommendationsforfutureresearch
First,the author onlyconductedthestudy with8keyaccountsi n thefieldof high- techindustry.Moredealersandindustriesareworthbeinginvestigatedtoreveald if f er en t perspectives.Thus,futureresearchshouldbeconductedtotestthemodelinm oredealersandindustries.
Second,thisstudyisconfirmatory,carriedouttotestthehypothesesandconfirmth emodel.Thestudyemploysexploratoryfactoranalysisandmultiplelinearr e g r e s s i o n t e c h n i q u e s t o r u n t h e t e s t , f u r t h e r r e s e a r c h i s r e c o m m e n d e d t o u s e co n f i rm at o r y factoranalysistoconfirmthereverseeffectsoftheresearchconstructs.
Finally,therespondentsinvolvedinthisstudyaremostlyshopmanagerswhoh a v e the weakervoiceinbuyingdecisionprocess,whilepurchasingmanagersandownerswho havestrongervoiceaccountforlittlepercentage.Futureresearchwhichicldesmoe“stoevoice”es podetsisecommededtocaot.
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ExtractionMethod:PrincipalComponentAnalysis.R o t a t i o n Method:VarimaxwithKaiserNormalization. a.Rotationconvergedin7iterations.
N Minimum Maximum Mean StdDe viation Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Statistic Std.Error Statistic Std.Error
Mean Variance Std.Deviation NofItems
Mean Variance Std.Deviation NofItems
Mean Variance Std.Deviation NofItems
ScaleMeanifIte mDeleted ScaleVarianceifI temDeleted CorrectedItem-
Mean Variance Std.Deviation NofItems
Mean Variance Std.Deviation NofItems
Mean Variance Std.Deviation NofItems
Mean Variance Std.Deviation NofItems
Mean Variance Std.Deviation NofItems
APPENDIXV:ExploratoryFactorAnalysis(EFA)E F A run ningof4independentvariables
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Total %ofVar iance Cumulativ e% Total %ofVa riance Cumulativ e% Total %ofVa riance Cumulativ e%
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InitialEigenvalues ExtractionSumsofSquaredLoadings Total %ofVariance Cumulative% Total %ofVariance Cumulative%
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