HOCHIMINH CITY 2022 MINISTRYOFEDUCATIONAND TRAINING STATEBANKOFVIETNAM HOCHI MINHUNIVERSITYOFBANKING PHAMLEQUYNHHOA FACTORSAFFECTING THE CUSTOMER’S PURCHASE INTENTIONIN THE PAID MUSIC STREAMING SERVIC[.]
Backgroundofthestudy
AccordingtoaQ&Mereportthatconductedasurveybasedon1500peopleincluding 18to44yearsoldnationwidein2021,musicisthemostfavoritee n t e r t a i n m e n t medium of Vietnamese people with more than 70% of people listening to the surveymusicformorethan30minutesaday.Currently,thepopularmusiclisteningapplications of Vietnamese people are mostly non-paid applications such as YoutubeMusic,ZingMp3,NhacCuaTui,etc.Thisisnotdifficulttounderstandwhen Vietnamis a country that has not had any copyright protection laws for products ranging frommusic to movies But in recent years, the emergence of international music applicationssuch as Spotify, Apple Music, Itunes, has changed the landscape for the Vietnamesemusic market.
%of the total revenue of the global music industry - a marked increase on the prior year‘sgrowth rate (+24.3%), and had over 532 millions user of paid subscription accounts,accordingtoareportreleasedbytheInternationalFederationofPhonographicRecordi ngs (IFPI) The development of streaming contributes to building a civilizedmusic environment because it is closely tied to the interests of artists, music listenersand product copyrights In Vietnam, streaming is at an early stage with great potential:39,6% of people listen to music streaming services, the average music streaming timeper day is about 1 hour and 11 minutes (Updated January 2022 of WeAre Social).Revenue in the Music Streaming segment is projected to reachUS$26.70m in 2022 andexpected to show an annual growth rate (CAGR 2022-2027) of 6.66%, resulting in aprojectedmarketvolumeofUS$36.85mby2027.Theracetowintheheartso f listeners is not only in the criteria of copyright or monopoly business but also intechnicalandtechnologicalfactorstooptimizetheuser'slisteningexperience.
ResearchesonMusicStreamingServiceshaveattractedspecialattentionf r o m domestican dforeignresearchers.Studieshaveshownalotofdifferentf a c t o r s affecting the intention to buy as well as use paid music services Dửrr et al (2010)examined different service features‘ influence on people‘s willingness to pay for MaaSservices by surveying 132 MaaS users Dửrr (2012) applied the Theory of PlannedBehavior (TPB) to look behind music pirates‘ intentions to use MaaS and to pay forsuch services A total of 132 music pirates would use the basic, free version but hadvery littleintentiontopay forthepremiumversion.Users‘subjectivenorms andattitudestowardstheserviceprovedtohavethemostpredictivepowerw h e n explaining people‘s intention to use MaaS MaaS‘s relative advantage over illegaldownloading influenced users‘ attitudes towards the service Wagner, Benlian, andHess (2013) used the Dual Mediation Hypothesis to investigate whether free versionsoccur as advertisements for premium versions within freemium business models Theirresults indicate that there is no advertising effect between free and premium versions.No other studies have explained users‘ willingness to pay for a service that is alsoavailable for free Aapeli (2016) applied the UTAUT2 model to suggests that paidMaaS services should focus on providing their users a good price value and hedonicpleasure, while exploiting consumers‘ tendency for habitual system usage. Also usedthemodelUTAUT2,MarianaandPedro(2021)confirmthathabit,performanceexpecta ncy and price value play themost important role ini n f l u - e n c i n g t h e i n t e n t i o n to use a paid music streaming service Simultaneously, new dimensions such as person-alisation, attitude towards piracy and perceived freemium-premium fit arise as havinganadditional relevant role inadopting this type of service.
Inthisthesis,theauthorchosestheTheoryofPlannedBehavior(TPB)asthetheoreticalframe workfortheconceptualmodel.TheTPBbelongstothem o s t powerfulpredictivepersuasio ntheoriesandhasbeenusedseveraltimesintheInformationSystemsfieldtomeasureuserac ceptanceandadoption.Oneadvantageof theTPBisitsflexibility inallowingnewvariables(Ajzen,1991).Inpaststudiesregardingtheacceptanceofmusicdistri butionchannels,theTPBwasusedandextendedsuccessfully(e.g.,d‘Astous,Colbertand Montpetit,2005;PlowmanandGoode,2009).According to
Ajzen(1991)theactualbehavioris guidedbythreefactors:evaluationso f t h e b e h a v i o r a l o u t c o m e s ( a t t i t u d e ) , b e l i e f s a b o u t t h e n o r m a t i v e expectationsofothers(subjectivenorm),andbeliefsaboutth efactorsthatcouldstrengthenorweakentheperformanceofthebehavior(perceivedbehavioralc ontrol).
Thiss t u d y i n h e r i t s a n d d e v e l o p s t h e T P B t h e o r y w i t h a g e , g e n d e r , a n d o c c u p a t i o n being the moderating effects on the intention to use paid Music Streaming Services(MSS) of individual customer in Ho Chi Minh City The use of this theory to study theinfluence of factors on the adoption of MSS has been studied in other countries, but thecontext of different countries, different levels of economic development, cultures haveshown that the research results are different, so the previous research results are notsuitable for the context of Vietnam and especially Ho Chi Minh City In the face of therapid development of the music industry, the development of music applications hasbeen focused by companies in the industry. However, the percentage of people payingfees to use the service is still modest.
Specific studies in the context of Vietnam fromtheperspectiveofcustomersareprettyrare.
On that basis, studying the factors affecting purchase decisions of customers in paidmusic streaming services in Ho Chi Minh City is very important.T h e f i n d i n g s f r o m this study can help companies come up with solutions tailored to specific customersegments Stemming from the above reasons, the author will use the TPB model withadjustments and supplements to suit the Vietnamese situation to answer the researchquestionsw h i c h f a c t o r s a f f e c t t o t h e d e c i s i o n s t o p u r c h a s e s e r v i c e s o f c u s t o m e r s , application usage behavior in Ho Chi Minh, the degree of influence of each factor onthed e c i s i o n t o p a y f e e s o r n o t i n t h e t h e s i s w i t h t h e t o p i c : F a c t o r s A f f e c t i n g T h e
Research ObjectivesandResearchQuestions
Identifyt he f a c t o r s o f p a i d m u s i c s t r e a m i n g s e r v i c e s a f f e c t o n t h e c u s t o m e r ‘ s purchaseintentioninthepaidmusicstreaming servicesinHoChi MinhCity.
This research is aimed to probe the factors of paid music streaming servicesw h i c h have significant impact on customers‘ intentions to purchase services in Ho Chi MinhCity.Theresearchquestionsare:
A study of investigating of factors of paid music streaming services which havesignificantimpact oncustomers‘intentionsto purchaseservicesinHoChiMinhCity.
This study was carried out using a combination of qualitative and quantitative researchmethods.
- Qualitativeresearchmethod:Conductedintheperiodofreviewingandsummarizing previously published works at home and abroad in order to clarifyresearch concepts and build questionnaires Next, individual in-depth interviewtechniques are used to explore and build observed variables used in measuringresearch concepts andb u i l d i n g t h e o r e t i c a l m o d e l s f o r r e s e a r c h T h e c o l l e c t i o n ofinformationisdonethroughtheform ofasurveyofthes ubjects, basedontheoutlineoutlinedinadvance.
- Quantitative research method:It is carriedout based on the application oftechniques such as Crobach's Alpha reliability test, exploratory factor analysisEFA,andstructuralmodelinglinearSEM.Informationwascollectedbyques tionnaire to survey the opinions of consumers in Ho Chi Minh City Ho ChiMinh.Theestimatedsamplesizeis300.Quantitativeresearchresultsare usedto verify the discovery results from qualitative research, thereby, evaluate andconcludeabout the research problem
The combination offactors inthetheoreticalmodelofTheory ofplannedbehavior(Ajzen,1985,1991)andthetheoryofPerceivedValue,Perceived Risktosynthesizenew observed variablesthathavenever beenconsidered in theprevious study.previousstudies in Vietnam on factors affecting the decision to buy paid online music services.Thetopiccontributes todetermining the factors affectingcustomers' inte ntiontobuyonlinemusicservices,specificallys t u d y i n g theimpactofcustomerpsycho logicalaspects,risksinusingtheproduct.Thetopicappliesresearchresultsforbusiness estohavea s u i t a b l e o r i e n t a t i o n i n t h e p r o c e s s o f p r o m o t i n g c u s t o m e r s t o p a y f o r o n l i n e musicservices.
Chapter1:ResearchOverviewChap ter 2:Literature ReviewChapter 3:
In chapter 1, the author presented the content of the research issues, including thereasons for choosing the topic, the research objectives and scope, the research methodsandtheoveralllayoutofthe researchtopic This isthebasisforthenextc haptersinthisstudy.
Chapter 1 gave an overview of the study In chapter 2, this chapter will present thetheoreticalbasisoftheresearchesrelatedtothefactorsaffectingthec u s t o m e r ' s decis ion to buy paid online music services From there, the author presents a researchmodel and research hypotheses about the impact of the factors affecting the purchasedecisionofpaidmusicservicesofcustomers.
In―PaidMusicStreaming:WhatDrivesCustomers‘Choice?‖by(VafaSaboori- DeilamiandChangSeobYeo,2019)investigatesfactorsthatdeterminethechoice ofconsumersinselectingonlinemusicstreamingservices,and factors thataffectthecustomer‘schoicetooptforapaidmusicstreamingservice.Thispaperexpl ainsthatcustomer‘schoiceisaffectedbyseveralperceivedelementswhich couldbecategorizedassubjectiveandobjective Subjective factorsmainly dealwitht h e p s y c h e o f t h e c u s t o m e r , w h e r e a s o b j e c t i v e f a c t o r s a r e c o n c e r n e d w i t h characteristicsofthestreamingservice.Resultsofthisstudyshowthatper ceivedvalueactsasame dia to r betweenquality ofse rv ice andlikelihoodtos ubscribe.Onem a j o r i m p l i c a t i o n o f t h i s f i n d i n g f o r p r a c t i t i o n e r s i s t h a t a l t h o u g h h i g h e s t quality might be very appealing to customers, quality would always be factored inthev a l u e o f t h e s e r v i c e T h e r e f o r e m a i n t a i n i n g a b a l a n c e b e t w e e n q u a l i t y a n d value is crucial to convince customers to subscribe to a music streaming service.However,thisresearchhassomelimitations,amongwhichonecanreferto onlyinvestigatingt h e t o p t h r e e m u s i c s t r e a m i n g s e r v i c e s A l t h o u g h
A p p l e M u s i c , Spotify,andPandoracontrolmorethanhalfofthepaidmusicstre amingmarket,theresultsofthisstudywouldbebyfarmoreconclusiveifallpaidmusicstre amingservicewereexamined.Anothershortcomingofthisresearchisuseofprimary dataastheonlysourceforanalysis.Althoughthesamplesizewaslarge enoughforastudy ofthistype,theresultswouldpossesshighervalidity ifmultiple methods of data collection were used in this study As a suggestion forfuture research, authors suggest using secondary information or qualitative data inconjunctionwithprimarydatatocorroborate theresults.
Figure1 -Proposed Conceptual Modelby Vafa Saboori-Deilamiand Chang SeobYeo (2019)
In ―Digital Music: A Study Of Factors In Influencing Online Music StreamingServicePurchaseIntention‖by(JYChai,LKKKen,KHChan,SXWan1a ndTTTing,2022)identifiesthefactorsthatwill affectthewillingnessoftheconsumers to subscribe to online music streaming service (Purchase
Intention).OnlinequestionnaireisconductedandtheresultisanalysedbyPearsonCorrelati on and Cohen‘s f2, effect size To test the hypotheses, data are collectedby distributing the online questionnaire prepared in Google Form (adopted fromBarros‘research(2017).Thisstudyhasaccumulateddatafromatotal200responde nts who are all Malaysian.The findings show that PerceivedValue,TangibilityPreference,MusicAffinityandMusicPiracyAwarenessarethe factorsthatwillsignificantly influencetheconsumers‘PurchaseIntentioninonline musicstreamingservice.
This research has some limitations First and foremost, the research method that isusedinthisresearchisanonlinequestionnaire.Thebenefitoftheonlinequestionnaire is that it could significantly reduce the time needed to collect data.As a downside, this method of data collection may only limit the questionnairerecipient to only Internet users and since most of the Internet users are students,their responses are confined into a single pattern whichmightcauses biasedresults.Therefore,thefindingsofthisstudymightnotrepresenttheentirepopulati on.Thefindingsofthisstudycanbefurthervalidatedbyincludingrespondents of different age groups and ethnic to provide an even broader view ofthestudy.
MusicS t r e a m i n g S e r v i c e ( O M S S ) H o w e v e r , t h e p l a t f o r m t h a t i s c h o s e n to be used for the OMSS is not studied. Therefore, it would be better if furtherresearch can include the research on which platform is chosen by each respondentso that the weaknesses and strengths of each of the platforms is able to provide aclearer image on the Purchase Intention Besides, this study does also not includeevery factor that might affect consumers‘ purchase intention and only measuresthe declared intention This is because it would be impracticable to include a largenumber of factors in one survey due to its increased complexity Therefore, adifferent set of factors for predicting consumers‘ Purchase Intention should beconsidered in the further research such as sense of fashion, economic status, ageand gender On the other hand, interesting research topics can be studied in thefuture such as research on the effect of advertising on the consumers‘d e c i s i o n andalsofactors ofin-apppurchases.
Figure 2 - Conceptual Model by J Y Chai, L K K Ken, K H Chan, S X Wan1 and T T
Alsoin―Musicstreamingservices:understandingthedriversofcustomerpurchasean dintentiontorecommend‖by(MarianaLopesBarataandPedroSimoes Coelho, 2021) examines the factors that influence music consumptionthrough streaming platforms, particularly studying the intention to adopt premium(paid) versions of a music streaming service and recommend them An extensionof the UTAUT2 model (version of the Unified Theory of Acceptance and Use ofTechnology, applied to the consumer side) was created Based on data collectedfrom 324 music streaming services users, the framework of this study was testedusing structural equation modelling (SEM) Research also included indepth semi-structured interviews in order to generate a more profound knowledge about theprofile, behaviours and motivations of the new music consumer The findingsconfirmthathabit,performanceexpectancyandpricevalueplaythemostimpor tant role in influencing the intention to use a paid music streaming service.Simultaneously,newdimensionssuchasperson- alisation,attitudet o w a r d s piracy and perceived freemium-premium fit arise as having an additional relevantrole in adopting this type of service The research contributes insights into musicstreamings e r v i c e s c o n s u m e r b e h a v i o u r , p r o v i d i n g s e v e r a l t h e o r e t i c a l a n d practicalimplicationstomusicstreamingservicesproviders.
Figure3-Conceptual ModelbyMarianaLopes BarataandPedro SimoesCoelho(2021)
In―WhatDrivesUserstoPayforFreemiumServices?ExaminingPeople‘sWillingness toPay for MusicServices‖by (ThomasM.Wagnera n d T h o m a s Hess, 2013) developed a research model to identify antecedents of consumers‘intentions and attitudes towards the premium version of music services when afree version is available based on the Theory of Planned Behavior The results ofour survey with 157 participants show that using the free version has a negativeimpact on users‘ intention to pay for the premium version.T h i s s t u d y i s t h e f i r s t to investigate users‘ intention to pay for a premium service in the presence of afreeb a s i c s e r v i c e O n a t h e o r e t i c a l l e v e l , w e h a v e o n c e m o r e d e m o n s t r a t e d t h e
TPB‘s applicability to new research contexts Overall, we were able to explain49.6%ofthevarianceinpeople‘sintentionstousepremiumMaaS.
The intention to use the free service showed the strongest negative influence onthe intention to use the premium service People seem to be satisfied with the freeversion and therefore see no need to pay for the service MaaS providers shouldmake the full premium service available to users for a free trial period so that theybecome accustomed to the use of MaaS After a certain amount of time, the trialperiod will end and users will be forced to pay for further access to the service.Thiswouldbeatime- limitedfreemiumandcontradictthehitherto-practicedfeature-limited freemium, which promotes both the free and premium products Inaddition to intentions, attitude has the strongest impact on users‘ willingness topay for premium products, followed by subjective norm Users are influenced bythe choices of their families, friends, etc MaaS providers should use marketingtechniques, like sponsored links on Facebook, to show potential users that theirfriends are using MaaS too Spotify, for example, has allowed its users to shareplaylists via social media from the start and forces them to connect their SpotifyaccountswithFacebook.
However, this study has some limitations The sample consists of students and isnot representative of the MaaS services user base The general model was testedusingMaaSas an example,whichiswhy it isnotp o s s i b l e t o g e n e r a l i z e t h e results to all freemium services Other industries in the internet business also usefreemiummo de ls H o w e v e r , t h e y use d i f f e r e n t t ech ni que s t o f or ce u s e r s t o p a y forpremiumproducts(e.g.,betterqualityofarticlesinnewspapers,ortimeadv antagesingames).Ourmodeldidnotincludesuchspecificattributes;however,aslongasits applicabilitywasnottestedinotherindustries,ageneralizationisnotpossible.Ourresult sindicatethatseparatingfreeandpremiump r o d u c t s c a n i n c r e a s e p e o p l e ‘ s i n t e n t i o n t o u s e t h e p r e m i u m v e r s i o n
However, lock-in effects resulting from the free version may also have a positiveeffect on users‘ willingness to pay Future studies should therefore focus on habitandthe resultinglock-ineffectindetail.
Theory of planned behavior (Ajzen, 1985, 1991) states that human behavior is aproduct of behavioral intentions This theory posits that these intentions in turn aredrivenbyhumanattitudetowardsthespecificbehavior.Theoryofp l a n n e d behavi or also states that two other factors, subjective norm, and behavioral control,also influence the behavioral intention Ajzen (1991, p.188) defines the attitudetowardsthebehavioras―thedegreetowhichapersonhasafavorableorunfavorable evaluation or appraisal of the behavior in question‖ Attitude is formedthrough the evaluation of individual‘s beliefs about the outcomes of the behaviorand the assessment of the appropriateness of those outcomes In other words, theindividual‘sattitudetowardcertainbehaviorcouldbemeasuredastheprodu ctof perceived consequences for the individual and the level of desirability for thoseconsequences.
According to Ajzen (1991, p.188), subjective norm surrounding the performance ofthe behavior are ―the perceived social pressure to perform or not to perform thebehavior‖ In other words, subjective norm is reflective of the individual‘s mindsettowards whether people who are significant to him or her, believe that this specificbehavior should or should not be performed The more an individual is willing tocomply with the opinion of the important referent, the higher the weight of theiropinion Therefore, total subjective norm is the product of individual‘s perceptiontowards referent‘s judgment and the willingness of the individual to comply withreferents‘perceivedbelief.
ResearchSubjects andTheScopeofResearch
Previous EmpiricalStudies
In―PaidMusicStreaming:WhatDrivesCustomers‘Choice?‖by(VafaSaboori- DeilamiandChangSeobYeo,2019)investigatesfactorsthatdeterminethechoice ofconsumersinselectingonlinemusicstreamingservices,and factors thataffectthecustomer‘schoicetooptforapaidmusicstreamingservice.Thispaperexpl ainsthatcustomer‘schoiceisaffectedbyseveralperceivedelementswhich couldbecategorizedassubjectiveandobjective Subjective factorsmainly dealwitht h e p s y c h e o f t h e c u s t o m e r , w h e r e a s o b j e c t i v e f a c t o r s a r e c o n c e r n e d w i t h characteristicsofthestreamingservice.Resultsofthisstudyshowthatper ceivedvalueactsasame dia to r betweenquality ofse rv ice andlikelihoodtos ubscribe.Onem a j o r i m p l i c a t i o n o f t h i s f i n d i n g f o r p r a c t i t i o n e r s i s t h a t a l t h o u g h h i g h e s t quality might be very appealing to customers, quality would always be factored inthev a l u e o f t h e s e r v i c e T h e r e f o r e m a i n t a i n i n g a b a l a n c e b e t w e e n q u a l i t y a n d value is crucial to convince customers to subscribe to a music streaming service.However,thisresearchhassomelimitations,amongwhichonecanreferto onlyinvestigatingt h e t o p t h r e e m u s i c s t r e a m i n g s e r v i c e s A l t h o u g h
A p p l e M u s i c , Spotify,andPandoracontrolmorethanhalfofthepaidmusicstre amingmarket,theresultsofthisstudywouldbebyfarmoreconclusiveifallpaidmusicstre amingservicewereexamined.Anothershortcomingofthisresearchisuseofprimary dataastheonlysourceforanalysis.Althoughthesamplesizewaslarge enoughforastudy ofthistype,theresultswouldpossesshighervalidity ifmultiple methods of data collection were used in this study As a suggestion forfuture research, authors suggest using secondary information or qualitative data inconjunctionwithprimarydatatocorroborate theresults.
Figure1 -Proposed Conceptual Modelby Vafa Saboori-Deilamiand Chang SeobYeo (2019)
In ―Digital Music: A Study Of Factors In Influencing Online Music StreamingServicePurchaseIntention‖by(JYChai,LKKKen,KHChan,SXWan1a ndTTTing,2022)identifiesthefactorsthatwill affectthewillingnessoftheconsumers to subscribe to online music streaming service (Purchase
Intention).OnlinequestionnaireisconductedandtheresultisanalysedbyPearsonCorrelati on and Cohen‘s f2, effect size To test the hypotheses, data are collectedby distributing the online questionnaire prepared in Google Form (adopted fromBarros‘research(2017).Thisstudyhasaccumulateddatafromatotal200responde nts who are all Malaysian.The findings show that PerceivedValue,TangibilityPreference,MusicAffinityandMusicPiracyAwarenessarethe factorsthatwillsignificantly influencetheconsumers‘PurchaseIntentioninonline musicstreamingservice.
This research has some limitations First and foremost, the research method that isusedinthisresearchisanonlinequestionnaire.Thebenefitoftheonlinequestionnaire is that it could significantly reduce the time needed to collect data.As a downside, this method of data collection may only limit the questionnairerecipient to only Internet users and since most of the Internet users are students,their responses are confined into a single pattern whichmightcauses biasedresults.Therefore,thefindingsofthisstudymightnotrepresenttheentirepopulati on.Thefindingsofthisstudycanbefurthervalidatedbyincludingrespondents of different age groups and ethnic to provide an even broader view ofthestudy.
MusicS t r e a m i n g S e r v i c e ( O M S S ) H o w e v e r , t h e p l a t f o r m t h a t i s c h o s e n to be used for the OMSS is not studied. Therefore, it would be better if furtherresearch can include the research on which platform is chosen by each respondentso that the weaknesses and strengths of each of the platforms is able to provide aclearer image on the Purchase Intention Besides, this study does also not includeevery factor that might affect consumers‘ purchase intention and only measuresthe declared intention This is because it would be impracticable to include a largenumber of factors in one survey due to its increased complexity Therefore, adifferent set of factors for predicting consumers‘ Purchase Intention should beconsidered in the further research such as sense of fashion, economic status, ageand gender On the other hand, interesting research topics can be studied in thefuture such as research on the effect of advertising on the consumers‘d e c i s i o n andalsofactors ofin-apppurchases.
Figure 2 - Conceptual Model by J Y Chai, L K K Ken, K H Chan, S X Wan1 and T T
Alsoin―Musicstreamingservices:understandingthedriversofcustomerpurchasean dintentiontorecommend‖by(MarianaLopesBarataandPedroSimoes Coelho, 2021) examines the factors that influence music consumptionthrough streaming platforms, particularly studying the intention to adopt premium(paid) versions of a music streaming service and recommend them An extensionof the UTAUT2 model (version of the Unified Theory of Acceptance and Use ofTechnology, applied to the consumer side) was created Based on data collectedfrom 324 music streaming services users, the framework of this study was testedusing structural equation modelling (SEM) Research also included indepth semi-structured interviews in order to generate a more profound knowledge about theprofile, behaviours and motivations of the new music consumer The findingsconfirmthathabit,performanceexpectancyandpricevalueplaythemostimpor tant role in influencing the intention to use a paid music streaming service.Simultaneously,newdimensionssuchasperson- alisation,attitudet o w a r d s piracy and perceived freemium-premium fit arise as having an additional relevantrole in adopting this type of service The research contributes insights into musicstreamings e r v i c e s c o n s u m e r b e h a v i o u r , p r o v i d i n g s e v e r a l t h e o r e t i c a l a n d practicalimplicationstomusicstreamingservicesproviders.
Figure3-Conceptual ModelbyMarianaLopes BarataandPedro SimoesCoelho(2021)
In―WhatDrivesUserstoPayforFreemiumServices?ExaminingPeople‘sWillingness toPay for MusicServices‖by (ThomasM.Wagnera n d T h o m a s Hess, 2013) developed a research model to identify antecedents of consumers‘intentions and attitudes towards the premium version of music services when afree version is available based on the Theory of Planned Behavior The results ofour survey with 157 participants show that using the free version has a negativeimpact on users‘ intention to pay for the premium version.T h i s s t u d y i s t h e f i r s t to investigate users‘ intention to pay for a premium service in the presence of afreeb a s i c s e r v i c e O n a t h e o r e t i c a l l e v e l , w e h a v e o n c e m o r e d e m o n s t r a t e d t h e
TPB‘s applicability to new research contexts Overall, we were able to explain49.6%ofthevarianceinpeople‘sintentionstousepremiumMaaS.
The intention to use the free service showed the strongest negative influence onthe intention to use the premium service People seem to be satisfied with the freeversion and therefore see no need to pay for the service MaaS providers shouldmake the full premium service available to users for a free trial period so that theybecome accustomed to the use of MaaS After a certain amount of time, the trialperiod will end and users will be forced to pay for further access to the service.Thiswouldbeatime- limitedfreemiumandcontradictthehitherto-practicedfeature-limited freemium, which promotes both the free and premium products Inaddition to intentions, attitude has the strongest impact on users‘ willingness topay for premium products, followed by subjective norm Users are influenced bythe choices of their families, friends, etc MaaS providers should use marketingtechniques, like sponsored links on Facebook, to show potential users that theirfriends are using MaaS too Spotify, for example, has allowed its users to shareplaylists via social media from the start and forces them to connect their SpotifyaccountswithFacebook.
However, this study has some limitations The sample consists of students and isnot representative of the MaaS services user base The general model was testedusingMaaSas an example,whichiswhy it isnotp o s s i b l e t o g e n e r a l i z e t h e results to all freemium services Other industries in the internet business also usefreemiummo de ls H o w e v e r , t h e y use d i f f e r e n t t ech ni que s t o f or ce u s e r s t o p a y forpremiumproducts(e.g.,betterqualityofarticlesinnewspapers,ortimeadv antagesingames).Ourmodeldidnotincludesuchspecificattributes;however,aslongasits applicabilitywasnottestedinotherindustries,ageneralizationisnotpossible.Ourresult sindicatethatseparatingfreeandpremiump r o d u c t s c a n i n c r e a s e p e o p l e ‘ s i n t e n t i o n t o u s e t h e p r e m i u m v e r s i o n
However, lock-in effects resulting from the free version may also have a positiveeffect on users‘ willingness to pay Future studies should therefore focus on habitandthe resultinglock-ineffectindetail.
TheoreticalBackgroundand HypothesisDevelopment
Theory of planned behavior (Ajzen, 1985, 1991) states that human behavior is aproduct of behavioral intentions This theory posits that these intentions in turn aredrivenbyhumanattitudetowardsthespecificbehavior.Theoryofp l a n n e d behavi or also states that two other factors, subjective norm, and behavioral control,also influence the behavioral intention Ajzen (1991, p.188) defines the attitudetowardsthebehavioras―thedegreetowhichapersonhasafavorableorunfavorable evaluation or appraisal of the behavior in question‖ Attitude is formedthrough the evaluation of individual‘s beliefs about the outcomes of the behaviorand the assessment of the appropriateness of those outcomes In other words, theindividual‘sattitudetowardcertainbehaviorcouldbemeasuredastheprodu ctof perceived consequences for the individual and the level of desirability for thoseconsequences.
According to Ajzen (1991, p.188), subjective norm surrounding the performance ofthe behavior are ―the perceived social pressure to perform or not to perform thebehavior‖ In other words, subjective norm is reflective of the individual‘s mindsettowards whether people who are significant to him or her, believe that this specificbehavior should or should not be performed The more an individual is willing tocomply with the opinion of the important referent, the higher the weight of theiropinion Therefore, total subjective norm is the product of individual‘s perceptiontowards referent‘s judgment and the willingness of the individual to comply withreferents‘perceivedbelief.
Perceived behavioral control is the most pivotal concept in the theory of plannedbehavior According to Ajzen (1991) this is what makes the theory of plannedbehavior different from the theory of reasoned action (Fishbein and Ajzen, 1980).In the theory of reasoned action Fishbein and Ajzen (1980) argued that intentionsare only driven by subjective norm and attitudes towards behavior. Ajzen (1991,p.183) defines perceived behavioral control as ―people‘s perception of the ease ordifficultyofperformingthebehaviorofinterest.‖
According to this theory, people perceive that they have different levels of controlover their behaviors These perceived controls vary on a range from behaviors thateasily could be performed to behaviors that demand significant amounts of effortsand assets Ajzen argues that in fact, there is an association between the actualbehavioral control and behavior However since measuring actual control incursconsiderable difficulties, perceived behavioral controls h o u l d b e u s e d a s a p r o x y forassessingthe actualcontrol.
Technology acceptance model (Davis, 1989) is one of the most widely used andempirically tested theoretical models for explaining the user behavior in differentcomputer systems applications (Davis et al., 1989; Mathieson 1991;
Szajna 1996;Hu et al., 1999; Koufaris, 2002) According to the technology acceptance model,users‘attitudestowardsthecomputersystemaffecttheirintentiontouset h e system which in turn leads to the actual use of the computer system (Davis, 1989).Technology acceptance modelproposes that when users are faced with anewtechnology, two factors influence their attitude and consequently their decisionaboutthe usage ofthenew technology.
―perceivedusefulness‖ofthenewtechnology.Davis(1989,p.320)definesperceived ease of use as ―the degree to which a person believes that using aparticular system would be free from effort‖ and the perceived usefulness as ―thedegree to which a person believes that using a particular system would enhance hisorher job performance‖.
Technology acceptance model has been repeatedly revised by scholars
(Venkateshand Davis, 2000; Venkatesh and Bala, 2008; Venkatesh at al., 2003).
Venkateshand Davis (2000) explained the reasons for users‘ perceived usefulness and ease ofuse in more details Specifically they broke down the reasons to three time framesof before implementation, after implementation, and long after implementation.They argued that main foundations for creating perceptions towards usefulness of acomputersystemaretheusers‘mentaljudgmentofthealignmentb e t w e e n essential objectives at work and the results of conducting the task related to one‘sjob using the computer system Results of their study showed that their findings arevalidinvoluntaryandcompulsoryworkenvironments.
Since customers of online music streaming services are in effect computer users,therefore,t h e i r b e h a v i o r s , d e c i s i o n s , a n d r e a c t i o n s t o w a r d s t h i s n e w d i s r u p t i v e technology could be well explained by a behavioral information system theory liketechnologyacceptancemodel.
Perceived value is the overall utility value of a product or service that a consumerperceivesbasedonacost-benefittrade- off(Zeithmal1988).Successandtheadoption of a technology or service is based on specific values that a consumerperceives or desires from a service These values can be related to functional,product, or technical aspects of a technology or service Several studies aimed tomeasure these values from a consumer‘s perspective (Praveena & Thomas, 2014;Pal & Triyason, 2017) However, determining the impact of specific values derivedfromtheuseoftechnologies,streamingservices,etc.,willbemorebeneficialfr oma consumer‘s viewpoint Perceived value as a concept is discussed in a number ofprevious studies in relation to information systems (Singh et al., 2020), mobileservices(Singhetal.,2017),streamingservices(Shinetal.,2 0 1 5 ) , b r a n d be haviour (Peng et al., 2014), etc These studies discussed either perceived value asa whole, for example, the unidimensional price-based value theory (Marchand &Hennig-Thurau, 2013) or multidimensional perceived value theory based on effects,namely consumption value theory, means-end theory, etc (Sheth et al., 1991).Originally, five broad aspects of perceived value (social, emotional, conditional,epistemica n d f u n c t i o n a l ) w e r e i n c l u d e d b y Sh et h e t a l
( 1 9 9 1 ) i n t h e i r s t u d y I n later years, functional value was improved with two categories – monetary andconveniencevalues– thatmakeitmoreappropriatetoonlineservices.T h e s e aspects were found most suitable and relevant in a number of studies as theyconsidered value as ‗experience‘ and measured the cognitive aspects of valueresulting from continuous use of online services (Gummerus,2013; Chen et al.,2017;Ali,2018).
Variousaspectsofperceivedvaluetheoryareapplicableinthecontexto f streamingservi cesduetothefollowingreasons:Atfirst,streamings e r v i c e s provide personalized streaming experiences that include personal, situational, andrelativec h o i c e s f o r e a c h v i e w e r t h r o u g h v i d e o o r m u s i c c o n t e n t H e n c e , t h e y shouldbeperceivedas‗experience‘(Oyedele&Simpson,2018) Next,multidimensionalaspectsofperceivedvaluearelikelytobesignificantt o streami ngs e r v i c e s F o r e x a m p l e , c o n v e n i e n c e v a l u e i s i m p o r t a n t d u e t o t h e f a c t thatstreamingservicesallowease,speedandaccessibilityinlisteningordownloading videos anywhere on multiple devices (Sheth et al., 1991) Monetaryvalue is also important as it measures or compares the cost aspects of streamingservices with traditional media devices such as DTH (Direct to Home) or TVs(Praveena & Thomas, 2014) Next, emotional value is crucial to streaming servicesbecause it provides fun or an enjoyable service experience to viewers This is alsomeasured in a number of studies as perceived enjoyment (Davis et al., 1992; Changet al., 2017) However, social value is not directly important to streaming services,but it may influence or enhance a viewer‘s social identity as a music or video lover(Oyedele & Simpson, 2018) Third, perceived value theory is relevant in the Indiancontext because India is a low middle-income country where consumers comparethe values they derive after using various products or services and express theirpreferred choices (Singh et al., 2020) In recent years, a few researchers tried toinclude values to measure perceptions towards online media services but withlimited efforts to identify the various dimensions of perceived value (Borja et al.,2015; Lee et al., 2016; Chen et al., 2017; Pal & Triyason, 2017; Cai et al., 2018,Yang & Lee, 2018) Still, to our understanding, no study in the Indian context hasusedmulti- dimensionalaspectsofvaluetheoryrelatedtoviewer‘scontinuedintentiontousestreami ngservices.
Perceived risk according to Schierz et al (2010) is the expectation of losses. Thelarger the expectations of losses are, the higher the degree of risk consumers willperceive Laroche et al (2005) specified perceived risk as the negative insights ofthe unpredicted and changeable results from the purchased products. Meanwhile,Ko et al (2004) defined the concept of perceived risk as the consumers‘ perceptionon changeable and contrary outcomes of buying a product or service The conceptincludest w o e l e m e n t s , w h i c h a r e t h e i n d e c i s i o n s a n d c o n s e q u e n c e s I n d e c i s i o n s aredefinedastheprobability ofunfavorableoutcomes,andconsequencesaredefined as the importance of losses (Laroche et al., 2005) Kim et al (2003) addedthat consumers‘ beliefs about the changeable outcomes are derived from onlineshoppingtransactions.
Perceived risk has a significant part in determining consumer purchase intentions.Consumers‘ perception toward risk is crucial in determining their evaluations andpurchasing behaviors (Ko et al., 2004) Consumers perceived a higher level of riskwhen buying online as compared to buying at physical stores. Lee and Tan (2003)stated that consumers with higher perceived risks are not likely to purchase onlineproducts or services It can be concluded that perceived risks have a negativeinfluence on consumer intentions to purchase via the internet (Liu and Wei, 2003).As argued by Kim and Lennon (2013), the greater the perceived risk of shopping atonline retailers, the weaker the consumer‘s purchase intentions toward the onlineretailer Akhlaq and Ahmed (2015) found that perceived risk has a negative effecton consumer intentions to purchase online This suggests that consumers‘ intentionto purchase online is suppressed when consumers find out that the transaction isrisky (Akhlaq and Ahmed,
2015) Similarly, in this study, consumers are morelikely not to purchase apparel online when they perceived the risk to be high. Pastresultsindicatethatperceivedriskisnegativelyrelatedtoonlinepurchaseintentions, as pointedou tbyZhaoetal.(2017)andAkhlaq andAhmed, (2015).
Thus, it also verified that perceived risk plays a negative role in online purchaseintentions.
FeathermanandPavlou(2003)proposedthatperceivedriskcomprisesperformance, financial, time, safety, social and psychological risks Besides that,Garner (1986) states that there are an additional six dimensions of perceived risk,namely, includes social, financial, physical, performance, time and psychologicalrisks (Ko et al., 2004) Bhukya and Singh (2015), on the other hand, examined fourdimensions of perceived risks in their studies on purchase intention, which includesfunctionalrisk,financialrisk,physicalriskandpsychologicalrisk.Intheco ntextofonlinemarketplace,HanandKim(2017)examinedamultidimensionalperceive dr i s k w h i c h i n c l u d e s f i n a n c i a l , p r i v a c y , p r o d u c t , s e c u r i t y , s o c i a l / psychological and time With the framework of online shopping as more intensivethanotherdimensions,Almousa(2011)emphasizesonproduct,financialandsecurity riskstobethemostinfluential.
Intrinsic rewards include feeling good about one's performance, feeling goodabout improving the department's situation, or satisfaction in representing others.Ifimportantintrinsicrewardscanbeobtainedbyparticipating,thent h e individ ual should be more likely to participate and more likely to influence thechoice (Tanner at al, 1993) In the context of Music Streaming Services, theintrinsic rewards that customers receive are positive emotions when using theservice.
In previous studies, most of the authors tested the extent to which intrinsicrewardsaffectsemployeeproductivityincorporateandorganizationalenvir onments.However,therehasbeennoresearchtotesttheinfluenceofthis factor on customer behavior in deciding to pay for music streaming services.HenceIhypothesizethat:
H1: Intrinsic rewards is positively related to Purchase Intention to use PaidMusicStreamingService.
( A n d e r s o n andChambers,1985).Rewardsfromtheformalorganizationw ouldresultfroma positive evaluation of performance by the participant's manager (Anderson andChambers1985).Foranindividualhowever,thoserewardswouldaffectbehavior only if seen as important and awarded as a result of participation. Theimportanceofparticipatingtoobtainsuchrewards,calledextrinsicrewardexpect ancy, shouldinfluence participation.
In this study, extrinsic rewards was defined as the extent to which extrinsicrewardsinfluence the incentiveto payformusic streamingservices.
H2: Extrinsic rewards is positively related to Purchase decision to use PaidMusicStreamingService.
ResearchProcess
The research is carried out for the purpose of discovering, adjusting and supplementingthe observed variables used to measure the research concepts Corresponding to thefollowingstepsandinterpretationforFigure3.1:
Step1:Research topic andbackgroundofthe topic
Step 3:Once the theoretical is available, the author adjusts and adds appropriateobservedvariablestomeasurethesurveyfactorsandestablishesaformalques tionnaireforthevariablesintheresearchmodel.TheseareIntrinsicRewards (IR),
Extrinsic Rewards (ER), Identity Salience (IS),
PsychologicalOwnership(PO),FinanceRisk(FR),TimeRisk(TR),ProductRisk(PR ),SecurityRisk(SR).
Quantitativeresearchiscarriedoutafterqualitativeresearch,ther e s u l t s obtainedf romqualitativeresearcharethebasisforadjustingtheobservedvariables in each factor From there, build a questionnaire to conduct an officialsurvey of customers in Ho Chi Minh City Formal questionnaires were used tocollectdatausingface-to- faceinterviewsoremailing.Fromtheofficialquestionnaire and conducted a formal survey of 251 customers (formal study).TheofficialsurveydataisconductedthroughSPSS22.0softwaretogivestatisti cal results, including the next steps after qualitative research based onFigure3.1asfollows:
Step4:After obtaining data from the customer survey process The authorentered the data, removed the inappropriate questionnaires, cleaned the data andcheckedthenormaldistributionof thedata.Fromthere,analyzethereli ability ofCronbach'sAlphaofthescaletoeliminateinappropriateobservations.Reliabilityte stresultshavetwocases:
• Case1:Thescalesdonotreachtheappropriatereliability,thengobac ktostep1toproceed fromthebeginning.
• Case 2: The scales achieve the appropriate reliability, then proceed to thenextstep,whichistheexploratoryfactortest.
Step 5:Test the EFA exploratory factor for the independent and dependentvariables to measure the convergence of observations and select representativefactorsforgroupsofobservedvariables.Fromthere,theauthortakesthe representativefactor todothenextanalysissteps.
Step 6:From the representative factors from the EFA factor test, the author usesas variables to run the results of the regression model and then discusses theresults of this regression model.
Also test the regression model defects such asmulticollinearity,autocorrelationandvariablevariance.
Step7:Fromtheresultsoftheregressionmodel,authorwilldiscussandcompare these results with previous research, from which there are suggestionsforpolicyimplications.
Survey Design
This scale has been recalibrated after the results of group discussion in the preliminarystudy Specifically, rebuilding the scales of 8 groups of factors according to experts'suggestions To measure the observed variables, the topic uses a 7-level Likert scalefromstronglydisagreetostronglyagree,expressedfrom1to7.Inwhich,1 correspondst o the choicestronglydisagreeand7correspondsto stronglyagree.
Table3.1:Summary ofscalesof factors in theresearchmodel
MusicStreaming Services(MSS)makes mehappy.
(11) Itis considered p r es t i g i o u s inm y communityto u se paidMSS
(14) Isensethat paidMSSismine PO1 Brown et al.
(22) Iha vea har d t i m e fi nd in gp ai d M S S t h a t w or ks f o r me.
(28) Companiesth at pr ov id eP ai d M S S m a y disclosem SR3 y
No Items Code Reference information
(34) Iintendtocontinueto usepaidMSS Int1 Venkateshet al.2012
DataAnalysisMethods
ThescaleofresearchconceptsisevaluatedforreliabilitybyCronbach'sAlphacoefficient. This is a statistical test of the quality of the scale used for each observedvariable. Cronbach's𝛼coefficient is a statistical test of how closely the items in thescale correlate with each other According to Hoang Trong and Chu Nguyen MongNgoc and many researchers, when Cronbach's Alpha from 0.8 or higher is close to 1,the measurement scaleis good; from 0.7 ton e a r l y 0 8 i s u s a b l e H o w e v e r , t h e r e a r e alsomany researcherswhosuggest thatC r o n b a c h ' s A l p h a c o e f f i c i e n t f r o m 0 6 o r higher can be used in case the concept of the scale is new or new to the user respond inthecontext ofresearch,(Peterson,1994; Slater,1995).
However, Cronbach's Alpha coefficient only evaluates the reliability of the scale. Toknow which observed variables should be removed, which should be kept, we use theitem-total correlation coefficient, which observed variables have variable correlationcoefficient - total < 0.3 will be type However, according to Nguyen Dinh Tho andNguyenT h i M a i T r a n g ( 2 0 0 8 ) , t h e r e m o v a l o r n o t o f a n o b s e r v e d v a r i a b l e i s n o t merely looking at the statistics, but must consider the content value of the concept.Accordingly,i f t h e s c a l e c a s e m e e t s t h e r e q u i r e m e n t s o f C r o n b a c h ' s A l p h a s t a n d a r d and if the variable with variable correlation is removed - sum < 0.3, it leads to violationof the content value (the remaining observed variables do not contain enough content)thevariableshouldnotbetyped.
Accordingly,ifthe scale casemeets therequirementsofC r o n b a c h ' s A l p h a s t a n d a r d and if the variable with variable correlation is removed - sum < 0.3, it leads to violationof the content value (the remaining observed variables do not contain enough content).oftheconcept)thevariableshouldnotbetyped.
Exploratory factor analysis (EFA) aims to test and redefine groups of variables in theresearchmodel.Inthisstudy,factoranalysisisappliedtosummarizethesetofobservedvari ablesintocertainfactorsthatmeasuretheattributesoftheresearchconcept.Criteriaforapplyinga ndselectingvariablesforEFAexploratoryfactoranalysisinclude:
Bartlett criteria and the KMO (Kaiser-Mayer-Olkin) system are used to evaluate thesuitability of EFA Accordingly, the hypothesis H0 (variables are not correlated witheach other in the population) is rejected and therefore EFA is called appropriate when:0.5≤𝐾𝑀𝑂≤1 and the significance level of the Bartlett test ≤0.05 In case KMO≤0.5,factoranalysisislikelytonotfitthedata.
The factor extraction criteria include the Eigenvalue index - representing the amount ofvariation explained by the factors and the Cumulative index - indicating how much ofthe factor analysis explains and including percentage is lost Factors with Eigenvalue 0.3 is considered minimal, Factor loading > 0.4 is consideredimportant, Factor loading > 0.5 is considered significant In addition, the author alsorecommendsthefollowingcriteria forthesample:iffactorloading >0.3iss elected, the sample size should be at least 350, if the sample size is about 100, thef a c t o r loading>0.55,ifthesamplesizeisabout50,thenthesamplesizeshould bearound
100 factor loading must be > 0.75 In this study with 470 samples, the Factor loadinglevelwas 0.3.
However,justlikeinCronbach'sAlphaanalysis,theremovalorrejectionofanobserved variable must also consider the content value of that variable If the observedvariablehasalowfactorloadingorisextractedfordifferentfactors,theweightdifference is very small, butm a k e s a n i m p o r t a n t c o n t r i b u t i o n t o t h e c o n t e n t v a l u e o f theconceptit measures,thenitisnotnecessarytodiscardthevariable.
In this study, the SEM linear structural model analysis method is used to test theresearch model SEM is a very general statistical modeling technique that is widelyused in behavioral science It can be seen as a combination of factor analysis andregressionorpathanalysis.ThestrengthoftheSEMstructuralmodelisthatitallo wsto measuretheimpactrelationshipbetweenthe researchvariables.
This thesis examines the mediating role of information perception in user- reviewedproduct videos on students' purchase intention The SEM structure model was used toexaminethesecorrelations.
Chapter3presentedtheresearchprocessfromwhichtoconductresearchandevaluate6 corresponding research hypotheses and test the influence The research was carriedoutwitha2- stepprocessincludingqualitativeresearchandquantitativeresearch.Preliminary research has built a scale to conduct the survey The official study wasconducted to survey with a sample of customers living and working in Ho Chi MinhCity Chapter 3 also presents the analytical methods, data processing and calculationcoefficientsusedinthe studyaswellasthestandardsusedtoassesstheconformity.
Source:CalculationresultsfromSPSSsoftwareAcco rding totheresultsofTable4.1,outof251peoplesurveyed,themalegenderis67 people, accounting for 26.7%, the female gender is 174 people, accounting for69.3%, and Other is 10 people, accounting for 4 % Under the age of 18 is 6 people,accountingfor 2.4%, from 18 to 22years old is 136p e o p l e , a c c o u n t i n g f o r 5 4 2 % ; from 22 to 26y e a r s o l d , t h e r e a r e 7 4 p e o p l e , a c c o u n t i n g f o r 2 9 5 % ; T h e a g e g r o u p from26to30yearsoldis27people,accountingfor10.8%andtheagegroupove r30 yearsoldis8people,accountingfor3.2%.Incomeunder5millionVNDis93people,account ingfor37.1%;from5to10millionVNDis63people,accountingfor25.1%; from10to20m il li on V N D is71people, accounting for28.3%and income o ver 20millionVND is24people,accountingfor9.6%.
The correlation coefficient matrix shows the individual correlation between the pairs ofvariables in the model The results show that the independent variables in the model IR,ER,IS,PO,FR,PR,SR,TRhaveastatisticallysignificantcorrelationwiththedependentvari ableInt The independent variables IR,ER,I S , P O , F R , P R , S R , T R have a positive correlation at 1% significance level with the dependent variable Int.Thus, Intrinsic rewards are positively correlated with customers' intention to buy paidmusicservices.
After testing the reliability of Cronbach's Alpha of the components of the scale, thestudy continued to perform EFA analysis for the scales The purpose of the EFAanalysistechniqueistodeterminewhichfactorsreally representtheobservedvariables inth e s c a l e s Th e f a c t o r s r e p r e s e n t 3 6 o b s e r v e d v a r i a b l e s o b t a i n e d f r o m E x p l o r a t o r y FactorAnalysis.TheEFAanalysiswasperformedthroughthefollowingtests:
K M O = 0 8 7 4 s a t i s f i e s the condition 0.5 < KMO < 1, showing that the EFA analysis is appropriate for theactual data The results of Bartlett's test have a Sig significance level less than 0.05shows that the observed variables have a linear correlation with the representativefactor The factors and observed variables in each specific factor are presented in thefactorrotationmatrixtable.Theobservedvariablesineachfactorsatisfytherequirement offactorloadingfactorgreaterthan0.55.
The coefficient KMO = 0.874 satisfies the condition 0.5 < KMO < 1, showing that theEFA analysis is appropriate for the actual data Table 4.4 shows the results ofBartlett'stest with Sig coefficient less than 0.05 shows that the observed variables have a linearcorrelation with therepresentative factor.
The validity of the model and the interactions among the constructs were investigatedusing structural equation modeling (SEM) This data analysis was carried out using theAMOS program All of the statistics for the model fit were satisfied to an excellent oreven high degree, as seen in this path diagram: Chi-square = 1504.347; df
RMSEA=0.051.Thestudymodel'sNormedX2/ dfwas1.828(Bagozzi,1988),suggestingthatitwaseffective.
In chapter 4, the results of empirical research on the factors affecting the intention tobuy online music services of customers in Ho Chi Minh City have been presented. Theauthor conducted a survey at Banking University of Ho Chi Minh City from November16,2021toNovember22,2022bysendingsurveyquestionnairesdirectlyandindire ctlythroughemailingthequestionnaire.question.Thetotalnumberofquestionnairessen tt o t h e s ur ve y was30 0, af te rr em ov in gt he in va li dq ues ti on na ir es, thesamplesizeforanal ysiswas251observations.
Conclusion
Theresultsofthemeasurementmodelsshowthat,afterhavingbeenaddedandadjusted, the scales have reached their reliability and allowable values This result hasthefollowingmeanings:
In terms of research methods, this study contributes to the measurement system ofIntrinsicRewards,ExtrinsicRewards,IdentitySalience,PsychologicalOwnership,Finance Risk, Time Risk, Product Risk, Security Risk and purchase intention in theworld by adding to it a scale system of Intrinsic Rewards, Extrinsic Rewards, IdentitySalience, Psychological Ownership, Finance Risk, Time Risk, Product Risk, SecurityRisk and intention to buy in the market Vietnam This helps academic and appliedresearchers in the field of consumer behavior in Vietnam and around the world have ascale system to conduct their research in the Vietnamese market Moreover, this scalesystem can serve as a basis for forming a unified scale system in multinational studiesonconsumerbehavior.Thisplaysanimportantroleinthefieldofinternationalmarketi ng research because at present, one of the difficulties in this research field is thelackofbaselinescalesystemineachcountrytoestablishequivalentsystem.measurement,es peciallyindevelopingcountries(Craig&Douglas2000).
It should also be noted that the main implication of this result is that measuring a latentconcept (variable) with multiple observed variables (measured variables) will increasethevalidityandreliabilityofthemeasurement,butnotnecessarily.thatd e s i g n cor rectly measures the number of observed variables used in this study These observedvariables can be adjusted and supplemented to suit each specific market and serviceindustry.Thereasonis thateachservicehasitsownuniqueproperties.
Next, the results of the measurement model in this study contribute to stimulatingresearchersinthefieldofbehavioralscienceingeneralandmarketinginp articularin our country in measurement That is, the measurement scales in the research must beevaluated for validity and reliability when using them to measure If this is not doneproperly,thevalidityoftheresearchresultswillbeanissuethatneedstobereconsidered.
The test results show the suitability of the theoretical model with market information aswellastheacceptanceofthehypothesisproposedinthisstudy.
This study shows that the impact of factors on the intention to buy onlinemusicservices of customers in Ho Chi Minh is studied from the perspective of consumerpsychologyinsteadoffactorsfromcompanies, enterprise.
Implication
Basedo n t h e r e s u l t s o f t h i s s t u d y ont h e f a c t o r s a f f e c t i n g t h e d e c i s i o n t o b u y o nlinemusic services, the solutions are given to administrators and businesses as follows:Firstly,theISfactoristhefactorthathasthestrongestimpactont h e p u r c h a s e intent ionofcustomers.Thus,thisisthecomponentthatbusinessesneedtop a y attentiontomostwh enimplementingstrategiestomotivatec u s t o m e r s t o b u y services This means that the more strongly customers are influenced by the
IdentitySaliencefactor,thehighertheintentiontob u y t h e s e r v i c e C o m p a n i e s a n d businessescanconsideranumberofmeasuresasfollows:Promotelinks withsocialnetworkingsitestocreatemusiclisteningc o m m u n i t i e s f o r c u s t o m e r s T h a n k s t o that,peoplecanbothlistentomusicandinteractwitheachothero n t h e s a m e platform.Besides,businessesc a n c o n s i d e r r e c o m m e n d i n g u n i q u e s o n g s t o customerstomakecustomersfeelthattheyarespecial,havetheirownmusictast e,andrepresentthecustomer'spersonality.Thiswillmakecustomersfeelunderstood andcaredfor,helpingcustomersstaylongerwiththeservice.Implementprogramssu mmarizingcustomer'smusictaste.Thiswillmakecustomerslearnandseetheirow npersonalityandpersonalitythroughtheirmusictaste.
Second, the PO factor also has an impact on customers' intention to buy onlinemusic services This means that customers have a very high ownership mindset.Therefore,businessesneedtotakemeasurestofurtherimprovethelevelo f custo merownership,suchasallowingcustomerstousethesongstheyhavepurchased according to their preferences, or customers are allowed to donate songs.their own to others Allow customers the freedom to create their own playlists andshare them with the community At the same time, companies and businesses canconsiderinteractingbetweencustomers,forexample,theycantext,reactt o playlistsc reatedbyusers.
Besides, customers will have the feeling that they own a special relationship with aproduct when they understand all aspects of the product, so businesses can create asense of belonging for customers by creating loyalty programs for them to enjoydiscounts.
Third,businessesalsoneedtopaymuchattentiontoimprovingtheirservicefeatures, such as: sound quality,applicationi n t e r f a c e , s o n g p l a y b a c k f e a t u r e s , e t c tohel pi mp ro ve t h e cu st ome r ex p e r i e n ce T h u s, c u s t o m e rs w il l e as i l y getuse dt o theapplicationmore quicklyandwillspendmoremoneytobuy.
RESEARCHLIMITATIONS
Third,whenrespondingtoasurvey,respondents mayanswerhonestly or lackinterest,leadingtoabigimpactontheresearchresults.
FURTHERRESEARCHDIRECTIONS
First,thenextstudywillexpandthescopeofthestudytothewholeofVietnamandinc reasethe sample size for broader research.
Second,fu rt he r researchshouldexpand t h e r e s e a r c h m o d e l in a newdire ctionandadd new factorstogetmore comprehensivefactors.
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Tôisửdụngdịchvụphátnhạctrựctu yến (MSS) vì tôithấynó thú vị
IusedMusicStreaming Services (MSS) because I found itenjoyable.
I used Music Streaming Services(MSS)becauseMusicStrea ming
(MSS) because Music StreamingServices(MSS)makesm ehappy.
Tôithấy hàohứngkhisử dụngMSS IusedMusicStreaming Services
(MSS) because Music StreamingServices(MSS)is exciting.
Iused MSS becauseIwanted to savetime
Tôi có thể thu thập thông tin âmnhạcdễdànghơnthôngquacácdịchv ụphátnhạctrựctuyếncótrả phí
I can acquire music informationmore easily through paid musicstreamingservices
Itwould takemealot of time to switchfrompaidMSStofreeMS S
Tôisẽtốnrấtnhiềutiềnđểchuyểnt ừMSS trảphí sangMSS miễnphí
Itwould costmealotofmoneytoswitchfrom paid MSSto free
Iwill feeluncertain if Ihaveto choosefreeMSSinsteadofpaidMS S
FR1 Tôic ó xu h ư ớ n g c hi t i ê u q u á m ứ c chodịch vụnghenhạccótrảphí
Dịchv ụ c ó t h ể k h ô n g x ứ n g đ á n g vớisố tiền tôi đãbỏ ramua
Paid music Streaming Servicesmaynot beworththemoneyI spent
TR2 Tôik h ó t ì m m ộ t M S S t r ả p h í p h ù hợp với mình
Tôik h ô n g t i n t ư ở n g c ô n g t y c u n g cấpdịch vụ nghenhạctrựctuyến có trảphí
I do not trust the online companyprovidingPaid MSS
Tôicóthểkhông nhậnđượcchấtlượngđúngvớisốtiềnmà tôibỏra chodịch vụnghenhạccótrảphí
I might not get the right qualityformymoneyfor PaidMSS
Tôicảm t h ấ y r ằ n g t h ô n g t i n t à i khoảnthanhtoánứngdụngM S S trảph í củatôi khôngđượcbảo mật
SR2 Trangwebcó thểkhôngantoàn Thewebsite maybe insecure
SR3 Cáccông tycungcấpM SS t rả phí có thể tiết lộ thôngtin củatôi
Companiesthat providePaid MSS maydisclosemyinformation SR4
Thông tin về công ty cung cấp
Information about the companyprovidingthePaidMSS maynot besufficient
Isense thatpaid MSS is MINE.
I feel a very high degree ofpersonalownershipforpaidMSS.
I feel a very high degree ofpersonalownershipforthepaid MSS that Ibought.
IS2 ViệcsửdụngMSStrảphíđượccoi là cóuytíntrong cộngđồngcủa tôi
Sửd ụ n g M S S t r ả p h í c ả i t h i ệ n u y tíncủatôiđốivớinhữngngười quen biết trên mạngxãhội
Using paid MSS improves mycredibilityamongsocial acquaintances
People in mycommunityare proudto usepaid MSS
Tôi đánh giá cao các dịch vụ pháttrựctuyếnnhạccótrảphívìchúng nângcao vị thế nganghàngcủa tôi.
I value paid music streamingservicesbecausetheyenh ancemy peerstatus.
Tôi đánh giá cao việc sử dụng cácdịch vụ phát nhạc trực tuyến có trảphívì chúnggiúp tăngkết nối của tôi trên mạngxãhội.
I value paid music streamingservices because they helpincreasemyconnectionsonsoci al media.
Tôi đánh giá cao việc sử dụng cácdịch vụ phát trực tuyến âm nhạc cótrảphívì chúngphổbiếntrongsố cácdịch vụphát trựctuyến củatôi.
I value paid music streamingservices because they are popularamongmypeers.
Tôi đánh giá cao các dịch vụ pháttrực tuyến nhạc có trả phí vì chúngcảithiệnhình ảnhcủatôigiữabạn bèvà giađình.
I value paid music streamingservices because they improve myimage amongmyfriends and family.
Int Ýđịnhtiếp tụcsửdụngdịchvụ nghenhạccó trảphí
Int1 Tôiđịnh tiếp tụcsửdụng MSScó trảphí.
Int2 Tôinghĩ rằngtôisẽ sửdụngMSS cótrảphí trongvòngsáutháng.
Int3 Tôinghĩ rằngtôisẽ sửdụngMSS có trảphítrongvòngmột năm.
Tôi là Phạm Lê Quỳnh Hoa, sinh viên ngành Quản trị kinh doanh, hệ đào tạo Chất lượng cao,trường Đại học Ngân hàng TP.HCM Hiện tại tôi đang thực hiện khóa luận tốt nghiệp về đề tài “Khảo sát các nhân tố tác động tới quyết định mua dịch vụ nghe nhạc có trả phí của kháchhàng tại Hồ Chí Minh” Các nội dung được đề cập trong bảng câu hỏi này liên quan đến cácđánhgiá, quan điểm vềviệcmua vàsửdụngdịchvụ cácứngdụngnghenhạctrựctuyến.
Xin lưu ý rằng không có câu trả lời đúng hay sai, tất cả ý kiến đóng góp chân thành của anh/chị đều có ích và hỗ trợ rất nhiều vào mục đích nghiên cứu Tôi xin cam đoanm ọ i t h ô n g t i n thuthập đượcbảo mật tuyệt đốivàchỉ sửdụngtrongkhuônkhổđềtài nghiên cứu này.
Anhchị hiện có trảtiềncho bất kỳdịch vụ phát trựctuyếnnhạcnào không?
Nếucó trảphícho cácdịch vụ nghenhạc, thìđó là ứng dụngnào?
Nếuanh chị khôngtrảphí cho cácdịch vụ nghenhạc,phiền anhchị chobiếtlýdo?
IR1 Tôisửdụngdịchvụphátnhạctrực tuyến (MSS) vìtôi thấynóthú vị
Tôi có thể thu thập thông tin âmnhạcdễdànghơnthôngquacácdịchv ụphátnhạctrựctuyếncótrả phí
SC2 Tôisẽtốnrấtnhiềutiềnđểchuyển từMSS trảphí sangMSS miễnphí
FR1 Tôic ó xu h ư ớ n g c hi t i ê u q u á m ứ c chodịch vụnghenhạccótrảphí
FR3 Dịchv ụ c ó t h ể k h ô n g x ứ n g đ á n g vớisố tiền tôi đãbỏ ramua
TR2 Tôik h ó t ì m m ộ t M S S t r ả p h í p h ù hợp với mình
Tôik h ô n g t i n t ư ở n g c ô n g t y c u n g cấpdịch vụ nghenhạctrựctuyến có trảphí
Tôic ó t h ể k h ô n g n h ậ n đ ư ợ c c h ấ t lượngđúngvớisốtiềnmà tôibỏrachodịch vụ nghenhạccótrảphí
Tôicảm t h ấ y r ằ n g t h ô n g t i n t à i khoảnthanhtoánứngdụngM S S trảphí củatôi khôngđượcbảo mật
SR3 Cáccông tycungcấpM SS t rả phí có thể tiết lộ thôngtin củatôi
SR4 ThôngtinvềcôngtycungcấpMSS trảphí có thể khôngđủ
IS2 ViệcsửdụngMSStrảphíđượccoi là cóuytíntrong cộngđồngcủa tôi
Sửd ụ n g M S S t r ả p h í c ả i t h i ệ n u y tíncủatôiđốivớinhữngngườiquen biết trên mạngxãhội
IS4 Mọingườitrongcộngđồngcủatôi tựhào khi sử dụngMSStrảphí
Tôiđánhgiá caocácdịchvụphát trực tuyến nhạc có trả phí vì chúngnângcaovịthếnganghàngcủatôi.
Tôi đánh giá cao việc sử dụng cácdịch vụ phát nhạc trực tuyến có trảphívì chúnggiúp tăngkết nối của tôi trên mạngxãhội.
Tôi đánh giá cao việc sử dụng cácdịch vụ phát trực tuyến âm nhạc cótrảphí vì chúngphổ biếntrongsố cácdịch vụphát trựctuyến củatôi.