HOCHI MINHCITY,2020 MINISTRYOF EDUCATION ANDTRAINING STATEBANKOFVIETNAMBANKINGUNIVERSITYOFHOCHIMINH CITY CANTHUKIET FACTORS AFFECTING THE CREDIBILITY OFONLINEREVIEWS ON TIKI BACHELORTHESIS MAJOR BUSIN[.]
Problemstatement
Int h e i n t e r n e t e r a , t h e d e v e l o p m e n t o f i n f o r m a t i o n a n d c o m m u n i c a t i o n technology has opened up new opportunities for service providers and consumers toshare information with each other In this context, online reviews, a special kind ofelectronic word of mouth (eWOM), have emerged as a new and increasingly popularcommunicationc h a n n e l ( K u a n e t a l , 2 0 1 5 ; P a r k a n d N i c o l a u , 2
0 1 5 ; W a n g e t a l , 2018) Today, online reviews are one of the most influential sources of information forconsumers when making purchase decisions (Chevalier and Mayzlin, 2006; Lee andShin,2014).
Previous research has shown that online user reviews have a significant impact oncustomerp u r c h a s i n g b e h a v i o r ( C h e v a l i e r a n d M a y z l i n , 2 0 0 6 ; C l e m o n s e t a l , 2 0 0 6 ) , and thus affect product sales (Chen and Xie, 2008) Previous studies indicate that theinformation generated by consumers, such as online reviews, is more persuasive thanthe information created by the marketer because consumers do not have a benefit andtherefore more independent and reliable (Park et al., 2007; Plotkina and Munzel, 2016;Reimer and Benkenstein,
2016) Besides, previous studies have shown that reliabilityplays an important role in consumer decision making and reduces uncertainty (Awadand Ragowsky, 2008; Fan et al., 2013; Nan et al., 2017) According to Baek et al.(2015, p 293), credibility is also the most significant factor in electronic word-of-mouth (eWOM) adoption For this reason, the credibility of online reviews seemscrucial when making purchase decisions based on those reviews Due to the importanceofcredibilityinthecontextofonlinereviewsandassociatedpurchasede cisions.Thatiswhyonlinereviewscredibilityisamajorconcernforbothconsumersandmarke ters.
Today, as online reviews becomemore accessible to internet users,m a n a g e r s needtonotonlypromotepositiveonlineinformationaboutt heirbrands/productsbut also need to do reduce the unwanted impact of negative online information on theirbrands/products.Therefore, the reputation and useofonline reviewand reviews i t e s can be threatened in the long term, if consumer concerns and uncertainties continue tospread and consolidate Munzel (2016, p 96) states that “The increasing practice offake reviews posted online not only jeopardize [sic] the credibility of review sites asimportant information sources for individuals but also endangers a valuable source ofinformation for service providers.” So as to counteract this development initiated bythose rogue companies, it is vital for reliable companies to understand how shoppersperceive and assess the credibility of online reviews, and particularly, to grasp whatfactorsdeterminereviewcredibilityfromtheconsumers’pointofview.
However,uptonow,thereisverylittleresearchinVietnamonthistopic.Therefore, this research aims to find out factors affecting the credibility of onlinereviewsonthee-commercewebsiteTIKI.
Researchobjectives
Researchquestion
Researchsubjectandscope
The respondents of this study focus on people who made a purchase on TIKI.Especially young people, who often shop on e-commerce sites, have high internetaccess Based on research by Nielsen.com (2015), aged 15-34 (58%) chose to shop one-commercesites.
The study was conducted in Ho Chi Minh City, where e-commerce is the mostdeveloped in Vietnam Ho Chi Minh City is a suitable place to carry out this researchwith high internet users and literacy levels The study was conducted fromOctober toJanuary2020.
Significantofthestudy
Scientificsignificance
The paper provides anoverview ofeWOM,e s p e c i a l l y c r e d i b i l i t y r e v i e w o n l i n e on the platform of e-commerce sites At the same time, the paper becomes a referencetohelpotherresearchersdeveloptheirresearch.
Practicalsignificance
This study helps marketers, especially e-commerce sites, understand the impact ofonlinereviewsandbuildmarketingandbrandingstrategies.
Researchmethod
- Qualitativeresearch:conductedtoidentifyresearchconcepts,buildquestionnaires,measure and collect necessary information related to the researchobjecttoservethequantitativeresearch.
- Quantitative research: This study is to test the research model and the hypothesesin the model The sample size is n = 449 Data will be collected and encryptedwith the support of SPSS 20 software Then, will be tested reliability of the scale(Cronbach'sAlpha),Exploratoryfactoranalysis(EFA)andMultiplelinearregres sion.
Structureofthestudy
Theoreticalbackground
DeterminantsBasedonArgumentQuality
When the central route ofp e r s u a s i o n i s t r i g g e r e d d u r i n g i n f o r m a t i o n e x p o s u r e , theprocessingofconsumers'onlineassessmentsisinfluencedbythequalityo fargument.Based on p r e v i o us r esea rc h, t he k e y elements o f a r g u m e n t q ual it y i ncludetheaccuracy,completeness,andtimelinessofonlinereviews.
Accuracy primarily refers to the reliability and correctness of online reviews andrepresents one of its main influencing factors (Jamil and Hasnu, 2013; Wang andStrong,1996).Themoreaccuratethemessage,thehighertheusefulnessofthe information received Therefore, Accuracy plays an important role when consumersprocessinformationononlinereviews,especiallyregardingcredibility.
According to Luo et al (2013), completeness refers to the degree that a review iscomprehensiveandprovidessatisfactorydata.Oncerecipientsrealizethatonlinereviews have valid arguments, they will think about online reviews to be positive andreliabledata(Cheungetal.,2009)
In the process of seeking information, consumers may encounter large amounts ofrelevant information that is related to a specific timestamp, leading to the concept oftimeliness research Timeliness relates to the novelty and updating of online reviews,thus reflecting the current state of the product or service (Filieri and McLeay, 2013;Jamil and Hasnu, 2013) Because online reviews are available at any time and are oftenone of the first sources of information on new products and services, they have adecisive advantage in time overprint media or traditional word of mouth (Filieri andMcLeay,2013).Fromaconsumer'spointofview,astimegoesby,theaverageusefulnessof reviewsdecreases(Liu,2006).
DeterminantsBasedonPeripheralCues
When the peripheral persuasion route is activated during information exposure,consumers process online reviews with peripheral cues Unlike argument quality, theperipheralc u e s d o n o t f o c u s o n t h e a r g u m e n t o f o n l i n e r e v i e w s , b u t o n l y r e f e r t o simple rules or truncation of information, such as brand image and the attractiveness ofsources that consumers use to evaluate recommendations (Filieri and McLeay, 2013, p.46).
This issue refers to the number of online reviews out there for a selected productor service on the review website (Filieri and McLeay, 2013) The quantity of onlinereviews is usually much higher on review sites than in offline environments, becauseonlyreviewwebsitesstoreonlinereviewsandmakethemavailabletor e c i p i e n t s (Zhang et al., 2014) A large amount makes online reviews additionally discernible(Cheung and Thadani, 2010) and contributes to supportive individual online reviews,constituting a very important consider the context of peripheral cues (Zhang et al.,2014).
Review consistency relates to the extent to which information in a review isconsistent with information in other reviews (Chang et al., 2015) Consumers easilycomparerelatedreviewsononlinereviewsites.Bycomparingthemessagew i t h simil ar messages, individuals can evaluate a message with other similar messages, andthe information presented by multiple reviewers may be considered more credible. Onthecontrary,consumersaremorelikelytobeskepticalofreviewsthatdon o t consistent with most other reviews Cheung et al (2012) show that recipients perceivethose online reviews as more likely and useful that assess the same products or servicessimilarovertime.
AccordingtoFang(2014),reviewerexpertisedescribestheextenttowhichrecipients perceive reviewers as competent with regard to the online review of productsands e r v i c e s I t i s a n a w f u l l y n e c e s s a r y f a c e t t o r e c i p i e n t s o f a r e v i e w , s i g n i f i c a n t l y once the knowledge searched shall support them within the decision-making processes(Gilly et al.,1998; Liu and Park, 2015) Previous research confirms that recipientsperceiveonlinereviewswrittenbyexpertsasmoreusefulandthatsuchreviewsha vea greater impact on recipients’ purchase intention than those of reviewers without expertknowledge (Racherla and Friske, 2012; Jamil and Hasnu, 2013; Fang, 2014; Zhu et al.,2014;ChengandHo,2015).
The rating of products and services is an assessment supported by pictograms(Filieri and McLeay, 2013) In this way, online reviews on e-commerce websites, suchas TIKI are complemented by a star rating the upper the number of stars during a starrating, the higher the rating of the product or service (e.g., Mudambi and Schuff, 2010;TIKI Ireland Ltd., 2016b) Star ratings of products or services can be considered as ageneral assessment of conclusions Review websites combination all individual ratingsofonlinereviewswithregardtoaproductandservicetoanoverallrating,t h u s allowing statements about the average rating of all online reviews During this manner,online reviews on review websites, the upper the number of stars rating, the higher theratingoftheproductorservice.
The reputation of a website depends heavily on its popularity and integrity.Themore known and reputable a website is, the more people will accept it (Park andLee,2009b) and that the latter often rely on reputations when assessing the credibility ofpresentedinformation(Chihetal.,2013;Metzger,2007).
Credibleonlinereviews
According to Sen and Lerman (2007), online client reviews are a type of word ofmouth involving positive or negative statements given to the merchandise by shoppersin online shopping malls Reviews involving products written by shoppers in the onlinecommunityareoneofthemostnecessaryformsofwordofmouth.
Consumers often rely on outside sources such as customer reviews online due tolimitedd ir ect in fo rm at io n a b o u t t h e q ual it y ofs e r v i c e p r o v i d e d ( Vi gl ia et a l , 2 0 1 6 )
CredibilityisaveryimportantissuerequiredtojudgethestrengthofeWOMinformation (Cheung et al., 2012; Luo et al., 2013; Ma and Atkin, 2017; Matute et al.,2016;Shan,2016;Qiuetal.,2012).Gunther(1992,p.148)statesthatcredibilit ycanbe defined as “not as an objective property of the source [of information], but as areceiver perception” In other words, credibility can be considered as the opinion of thepeopleontherealityoftheassessment(ErkanandEvans,2016).
In brief, credible online reviews can be defined as the degree to which consumersperceivethereviewsastruthful,logicalandbelievable(Cheungetal.,2009).
TIKI
Founded in 2010, TIKI.vn is a business-to-consumer e-commerce platform inVietnam The beginning of TIKI was just an online bookstore website But in March2012, Soichi Tajima, CEO, and chairman of CyberAgent Ventures Inc, decided toinvesti n T I K I W i t h t h i s c a p i t a l c o n t r i b u t i o n , C y b e r A g e n t V e n t u r e s I n c w i l l h o l d a 20% stake in TIKI With this investment, TIKI gradually expanded into an e-commerceplatform.
TIKI operates under the B2C (Business to Customer) business model, whichmeans that TIKI is an intermediary that connects consumers and businesses/sellerstogether Creating a friendly, convenient and easy online shopping environment forbothbuyersandsellers.
Brands/businesses/traders/sellers will register to open TIKI booth to sell theirproducts Besides, TIKI itself directly sells and distributes many products of genuinebrandsthroughTIKITrading.
In exchange with e-commerce platforms like Shopee, Sendo, Lazada often usecheap prices to attractconsumers.With TIKI, it isdifferent, this business alwaysattacheshighimportancetogoodsquality.For productssoldbyTIKITraddi ng,TIKI imports products directly from brands and is censored For sellers who register to sellon TIKI, they must clearly commit the origin of the goods, and all products must bedelivered to TIKI's warehouse before being delivered to customers, so the quality ofgoodsismoreassured.
Previousresearch
Study1:Influencing factorsofonlinereviews:anempiricalanalysisofdeterminant s of purchase intention(Thomas, M J., Wirtz, B W., & Weyerer, J C.,2019)
Thiss t u d y e x a m i n e s t h e d e t e r m i n a n t s o f t h e u s e f u l n e s s o f o n l i n e r e v i e w s a n d their impact on the intended purchase of recipients Based on the elaboration likelihoodtheory, this research has developed and tested a model that applies structural equationmodelingtodatacollectedfrom282Yelpusers.Thefindingsshowthateaseofcomprehensio n,accuracy,opposingviewpoints,completeness,relevancea n d timeliness are significant dimensions of argument quality while review quantity andconsistency,reviewerreputationandexpertise,product/servicerating,aswellaswebsite reputation, are crucial peripheral cues In addition, the study identified thequality of arguments and peripheral signals as a determining factor in the usefulness ofreview,whichwaseventuallyfoundtohaveapositiveeffectonther e c i p i e n t ' s purcha seintent.
Study2:Determinants ofonlinereviewcredibilityanditsimpactonconsumers’ purchaseintention(Thomas,M J.,Wirtz,B.W.,&Weyerer, J.C , 2019)
Basedontheabilitytoconstructtheory,Thomas,Wirtz,&Weyerer(2019)developed a research model and tested it by modeling structural equations with datacollected from 282 users of Yelp online review site The results show that argumentquality including accuracy, completeness, and quantity of online reviews, as well asperipheralcues,includingreviewerexpertise,product/serviceratingandwebsitereputatio n,b o t h i m p a c t o n l i n e r e v i e w c r e d i b i l i t y , w h i c h h a v e a positivee f f e c t o n consumers'buyingintent
Study 3: Is this review believable? A study of factors affecting the credibilityofonlineconsumerreviewsfrom anELMperspective (Cheung,C M.Y.,Sia,C L.,&Kuan,K.K.,2012)
This study looks at four information cues used to evaluate the credibility of onlinereviews based on a building capacity model (ELM) including Argument quality, sourcecredibility,reviewconsistency,andreviewsidedness,underdifferentlevelsofinvolvement and expertise To test the research model, this study conducted an onlinesurvey involving users of Epinions.com, a popular online consumer rating website Theresults show thatargument quality, a central cue, is themainfactor affecting thecredibility of the review Participants also relied on peripheral cues such as sourcereliability,reviewconsistency,andreviewsidednesswhenevaluatingconsumerrevie ws online Review sidedness has a stronger effect on the review credibility whenrecipients have low levels of involvement and high qualifications However,otherinteractioneffectsarenotsignificant.
Study 4: The impact of electronic word-of-mouth: The adoption of onlineopinions in online customer communities(Cheung, C M., Lee, M K., &
This study uses dual-process theories, an information acceptance model that hasbeen developed to test the factors that influence the information acceptance of onlineopinion seekers in the customer communities The model has been empirically testedusingasampleof154experiencedusersintheonlinecustomercommunity,Openrice.c om Users are required to complete a survey regarding online consumerreviewsreceivedfromthevirtualsharingplatform.Theresultsshowthatcomprehe nsiveness and relevance are the most effective components of the researchmodel'sargumentquality,makingthemthekeyinfluencersintheapplicationofinfor mation However, only 46 percent of the variance is explained by the constructsduetoitsintentionalsimplicity.Thiswillindicatethattherearemoreactorsinmotiv ating information adoption than solely information usefulness This article is oneof the first to develop and experimentally experiment with a theory-driven informationadoption model for opinion seekers in the online customer community It also uniquelybreaksdownandexaminesthecomponentsofargumentqualitytod i s t i n g u i s h i mportantmotivatingfactors.
Hypothesis
Accuracy
Previousstudiesoftenconceptualizedaccuracywithinthecentralrouteofpersuasion and confirmed it as a meaningful factor of argument quality, especially inthe context of social media (Cheung et al., 2008; Filieri and McLeay, 2013; Jamil andHasnu, 2013; Flanagin and Metzger, 2013) According to Jamil and Hasnu (2013), ifthose aspects already known to the consumer are accurately represented in the onlinereview, consumers will most likely also assume unknown aspects of online reviews areaccurate. However, if aspects known by consumers in online reviews deviate from theconsumer experience, consumers will most likely reject both known and unknownaspectso f o n l i n e r e v i e w s , c o n t e s t i n g t h e c r e d i b i l i t y o f t h e w h o l e r e v i e w B a s e d o n thesedeliberations,proposingthefollowinghypothesis:
Hypothesis 1 (H1): The accuracy of an online review positively influences itscredibility.
Completeness
Previous studies suggest that completeness is an important factor of argumentquality and thus can be assigned to the central route of information processing
(ChengandHo,2015;LiandZhan,2011;McKinneyetal.,2002;Yangetal.,2 0 0 5 ) Accord ing to Cheung et al (2009), when recipients find that online reviews have validarguments,theyarelikelytoregardonlinereviewstobepositiveandreliableinformation Therefore, investigates the influence of completeness on the credibility ofonlinereviewsasadimensionofargumentquality,proposingthef o l l o w i n g hypothesi s:
Timeliness
The various studies in social media documents have conceptualized timeliness asthe influence factor of online reviews (Cheung et al., 2008; Filieri and McLeay, 2013;JamilandHasnu,2013;Cheung,2014)andplaysaveryimportantroleint h e credibility oftheinformation(Abdullaetal.,2002).Similartothecompleteness,timeliness improves the standard of online reviews and thus also supports the strengthof argument, therefore probably enabling a lot of favorable angles to online reviews,including a more positive perception of credibility. Therefore, proposing the followinghypothesis:
Hypothesis 3 (H3): The timeliness of an online review positively influences itscredibility.
Reviewquantity
Previous research also provides empirical evidence that review quantity has beenfrequently applied as a peripheral cue and considered the influencing factor with regardtoon li ne re vie ws i n t hes oci al m e d i a an de - c o m m e r c e l it er at ur e( Zh an ge tal , 2 0 1 4 ; Fan et al., 2013; Fang et al., 2013; Filieri and McLeay, 2013; Obiedat, 2013; Zhou etal.,2013).Therefore,proposingthefollowinghypothesis:
Hypothesis 4 (H4): Review quantity positively influences the credibility of anonlinereview.
Reviewconsistency
Thepreviousstudyprovidesempiricalevidencethatreviewconsistencyhasalreadybee nsubjecttostudiesinsocialmediaande-commerceliteraturea n d confirmed as an important peripheral cue related to online reviews (e.g., Munzel, 2016;Luo et al., 2015; Chang et al., 2015; Baek et al., 2012; Cheung et al., 2012) Whencomparing online reviews, highly consistent reviews make shoppers more likely to feeltheyaremorecredibility.Therefore,proposingthefollowinghypothesis:
Hypothesis 5 (H5): Review consistency positively influences the credibility ofanonlinereview.
Reviewerexpertise
Reviewer expertise represents another element of online reviews that have beenanalyzedspecifically inthe contextofsocialmediaresearch (e.g., ChengandH o , 2015;Fang,2014;JamilandHasnu,2013;RacherlaandFriske,2012).Previo usresearch has shown that experts are more reliable than laypersons The reviewers’expertiseisveryimportantforrecipients,especiallywhentheysearchfortheinfor mation that is supposed to assist them in the decision-making process (Gilly et al.,1998; Liu and Park, 2015) According to Cheung and Thadani (2012) and Fang (2014),the reviewers’ expertise is not only an important aspect of their credibility buta l s o have a positive impact on the credibility of online reviews In other words, if the source(reviewer) of the online review is deemed to be reliable, then the product (the onlinereview) of the source is also likely to be perceived as being trustworthy by consumers.Therefore,proposingthefollowinghypothesis:
Hypothesis 6 (H6): Reviewer expertise positively influences the credibility ofanonlinereview.
Productorservicerating
The rating of products or services is another factor of online reviews that havebeen often examined within social media and e-commerce research (e.g., Baek et al.,2012; Filieri and McLeay, 2013; Liu and Park, 2015) Previous research by Cheung etal (2009) and Fang (2014) show that such rankings can affect the way consumersperceivethecredibilityofonlinereviews.Therefore,proposingthefollowinghyp othesis:
Websitereputation
Website reputation is a well-established structure in e-commerce research andsocialmediaanddescribesthepopularityofareviewsiteamongonlinereviewrecipients (Hsiao et al., 2010; Lee et al., 2011; Chih et al., 2013; Lee and Shin, 2014).The more known and reputable a website is, the more people will accept it (Park andLee, 2009b) Flanagin and Metzger (2008) and Chih et al (2013) demonstrate thatwebsitereputationhasadecisiveinfluenceonthecredibilityofonlinereviews.
Hypothesis 8 (H8): Website reputation positively influences the credibility ofanonlinereview.
Table 2.1 Overview of Exogenous Constructs and Relevant Sources for
Studies on online reviews usingrespectiveconstructs
Cheung et al., 2008; Filieri andMcLeay,2013;JamilandHasnu ,2013;RacherlaandFriske,2012
Positive effect of argumentquality on review credibility(Cheung et al., 2009;Cheung et al., 2012; Fang,2014;Luoetal.,2015) Completeness
Cheung, 2014; Cheung etal., 2008; Filieri and McLeay,2013; Flanagin and Metzger,2013; Jamil and Hasnu, 2013;Kuan et al., 2015; Li and Zhan,2011;LiuandPark,2015;Luo etal., 2013; Racherla and Friske,2012
Cheung, 2014; Cheung et al.,2008;Filierietal.,2018;Filieri and McLeay, 2013; Jamil andHasnu,2013
Fan et al., 2013; Fang et al., 2013;FilieriandMcLeay,2013;Obied at,2013;Zhangetal.,2014;Zhouetal.,
Positive effect of reviewquantity on reviewcredibility(Fanetal.,2
Cheung et al., 2009;Cheung et al., 2012;
Kuan et al.,2015;Luoetal.,2015;Munzel,
Positive effect of reviewconsistency on reviewcredibility (Chakrabortyand Bhat, 2018a, 2018b;Cheung et al., 2009;Cheungetal.,2012;Lu oetal.,2015)
ChengandHo,2015;Cheungetal.,2 008;Fang,2014;Jamiland Hasnu, 2013; Liu and Park, 2015;RacherlaandFriske,2012
Baek et al., 2012; Chang et al.,2015;Fang,2014;Filierietal., 2018;FilieriandMcLeay,2013;Flana ginandMetzger,2013
Positive effect of reviewrating on review credibility(Cheung et al., 2009;
WebsiteReput ation Chihetal.,2013;Hsiaoetal.,2010 Positiveeffectofweb- sitereputation on reviewcredibility(Chih et al.,2013)(Source:M.J.,Wirtz, B.W.,&Weyerer,J.C.,2019)
ConceptualModel
B W., & Weyerer, J C (2019) As shown in Figure below, the variables include:accuracy,completeness,timeliness,reviewquantity,reviewconsistency,reviewere xpertise,product/serviceratingandwebreputation.
Researchvariables
Cardinal numbers Symbol Indicators Sources
Nelson et al. 2005;Cheung et al. 2008;FilieriandMcLeay2
2 ACC2 Online reviews on TIKI are thoroughlywritten.
4 ACC4 Online reviews on TIKI are preciselyformulated.
5 COM1 OnlinereviewsonTIKIcontainalltheinfor mationneededaboutthereviewd Yangetal.2005; products/services Cheung et al
Online reviews on TIKI contain verydetailedinformationaboutthereviewe dproducts/services.
9 TIM1 OnlinereviewsonTIKIarecurrent Somers et al.
There is a great number of reviewsfrom different authors about manyproducts/servicesonTIKI.
KangandKim2006;Zh ang et al 2014;Filieri2015
13 RQ2 Thereisavarietyof reviewsaboutmanyproducts/servicesonTI KI.
14 RQ3 There is a multitude of informationaboutmanyproducts/service sonTIKI.
16 RC1 Different online reviews about aproduct/serviceonTIKIareoften Cheungetal.2012; consistentwitheachotherintermsofcontent Changetal.2015;L uoetal.2015
Different online reviews about aproduct/service on TIKI overlap tosomeextentwitheach otherintermsofcontent.
Thereareanumberofoverlapsamongdiffer ent online reviews about aproduct/serviceonTIKI.
19 RE1 Reviewers of online reviews on
Reviewers of online reviews on TIKIseemtohaveenoughinsightstomak eanassessment.
Theratingofproducts/servicesonTIKIby means of stars has narrowed downthenumberofalternativeproducts/se rvices that are interesting tome.
Theratingofproducts/servicesonTIKIby means of stars has allowed me tofind products/services that satisfy myneeds.
24 PSR3 Theratingofproducts/ servicesonTIKIbymeansofstarshasallow edmeto findwell-ratedprod-ucts/services.
The rating of products/services on TIKIby means of stars has allowed to me getaquickoverviewofproducts/services.
Researchdesign
Conducting qualitative research through discussion techniques with instructorsand hand-to-hand discussions with subjects selected by the convenient method thatyoungpeoplehaveusedonlineshoppingservicestoevaluateandadjustthequestionnaire. Inaddition,qualitativeresearchisalsoaimedatconsideringtheappropriatescaleandadjustin gthescaletosuittheresearchtopic.
This is done through quantitative methods Aims to retest the research model andresearch hypotheses The data is cleaned and processed on SPSS 20.0 software. Theseobservedv a r i a b l e s w e r e a s s e s s e d b y t w o c r i t e r i a :
( I ) a s s e s s i n g t h e r e l i a b i l i t y o f t h e scale (Reliability Analysis) through Cronbach's alpha coefficient and (II) explainingfactorofEFA(ExploratoryFactorAnalysis).Observedvariablesthatsatisfythecondit ions will be used for formal research (official scales) Then, conduct model testsandresearchhypothesesusinglinearregressionmodels.
Sampleanddatacollectionmethod
Samplesize
To ensure that the sample size is consistent with the EFA analysis method,thenumber of observations must be at least 4-5 times the number of variables With33observedvariablesofthispaper,thesamplesizeis33*55ormore.However,to increasetherepresentativenessofthestudy,andtoreduceerrorswhenapplyingconvenientsa mpling,thetopicwilltake250ormoresamples.
Selectsurveysubjects
Ho Chi Minh City These are the audience with a large number of socialnetwork users as well as often conducting online shopping activities so they can answerobjectively, exactly what they have experienced The prerequisite when choosing asurveyobjectisthattheconsumerisusingsocialnetworking,hasbeenbuyinggo odsonthee-commercewebsiteTIKIinVietNam.
Questionnairedesign
There are three ways to get a scale used in scientific research: (i) Use the originalscale available, built from previous researchers; (ii) Use existing, built, but adjustedscales to suit the study objects; and (iii) Develop a completely new scale (Creswell,2003).
The author uses the originally available scale, built from previousr e s e a r c h e r s The research questionnaire is based on the questionnaire of Thomas, M J., Wirtz, B.W.,&Weyerer,J.C.(2019).
Initially,theauthorwillbuildacontentdiscussiononeononewitht a r g e t audienceas mentionedabove(orseedetailsatAPPENDIXA)
Review Whatisthenumberofonlinereviews?Istherealotornot?Doall quantity productshaveahighnumberofreviewsorjustafewofthem?
Review credibility Inyouropinion,areonlinereviews onTIKIreliable?
Part 1 is called evaluation Includes questions designed to measure independentvariablesincludingaccuracy,completeness,timeliness,reviewquantity,revie wconsistency, reviewer expertise, product/service rating and web reputation Using theLikert scale, respondents were asked to rate their responses from 1 strongly disagreewith 5 to 5 strongly agree in each statement In this section, each element will have acorrespondingnumberofquestions.
Part2iscalledthepersonalinformationusedtocollectinformationaboutrespondents,including gender, age, occupation and monthly income and frequency ofpurchasesonTIKI.
Datacollectionmethod
TheauthorselectedtheresearchsubjectswhohavebeenusingtheTIKIe-commerce site, used a convenient sampling method but still ensure the full range ofgender, age, income and frequency purchase The data collection process is carried outin7weeks,fromNovember11,2019,toDecember26,2019.
There are two common methods of collecting samples: direct survey and onlinesurvey (via social networks, email, google form tool ) For this study, in order toensure high quality, reliable data, high response rate, the author sent the survey tofriends,r e l a t i v e s a n d s o c i a l r e l a t i o n s h i p s i n H o C h i M i n h C i t y t h a t t h e y h a v e b e e n using TIKI At the same time, the author also conducted the survey directly throughgoingtouniversitiesandcafeshopstoaskthesubjectstoconductsurveys.
Dataanalysismethod
Cronbach’sAlpha
Cronbach's coefficient alpha provides an indication of the average correlationbetween all items that make up the scale Theoretically, Cronbach alpha results willprovide a number between 0 and 1, but can also receive negative numbers.
A negativenumber indicates that something is wrong with the data Nunnally (1978) recommendsa minimum level of 0.7, with higher values indicating greater reliability. George andMallery(2003),thefollowingrulesareconsideredregardingreliabilitycoefficient:
The item-total correlation is used to see if any of the tests or questions ("items")do not have responses that vary in line with those for other tests across the population.Loiaconoetal.(2002)eliminateanItem-Totalcorrelationoflessthan0.4.
- Testing the reliability of the scale through Cronbach’s Alpha coefficient and thescaleisacceptedasCronbach'salphareliabilitycoefficientgreaterthan0.7.
Exploratoryfactoranalysis(EFA)
Explorefactoranalysis(EFA)helpsexaminetheconvergentvalueanddiscriminant value EFA has no dependent variable and independent variables, it onlyreliesoncorrelationsbetweenvariablestogether(interrelationships).Inthefactoranalysis,m ethodsofextractionPrincipalComponentsAnalysis,Varimaxrotationmethodusedisthemos tpopular(Mayers,LS,Gamst,G.,AJGuarino,2000)
Hair,Andersonetal.(1995a)categorizedtheFactorloadings as0.3=minimal, 0.4 = important, and 0.5 = practically.If the Factor loadings are less than 0.3, then itshould be reconsidered if Factor Analysis is a proper approach to be used for theresearch (Hair, Anderson et al 1995a; Tabachnick and Fidell 2001) If the correlationmatrix is an identity matrix (there is no relationship among the items) (Kraiser 1958),EFAshouldnotbeapplied.
The sampling adequacy can be assessed by examining the Kaiser- Meyer -Olkin(KMO) (Kaiser 1970) It ranges from 0 to 1, while KMO 0.5 considered suitable forEFA (Hair, Anderson et al 1995a; Tabachnick and Fidell 2001) On the other hand,according to Netemeyer, Bearden et al 2003, a KMO correlation above 0.6 – 0.7 isconsideredadequateforanalyzingtheEFAoutput.
Bartlett’s Test of Sphericity (Bartlett 1950) provides a chi-square output that mustbe significant It indicates the matrix is not an identity matrix and accordingly it shouldbe significant (p < 0.05) for factor analysis to be suitable
- Percentage of variance in Extraction Sums of Squared Loadings > 50%:Showpercentagevariationoftheobservedvariables.
CorrelationAnalysis
Correlation analysis is a statistical method used to evaluate the strength of therelationship between two quantitative variables A high correlation means that two ormorevar ia bl esar e closely related,w hi le awe akc or re la ti on m e a n s t h a t the v a ria bl es are almost unrelated The correlation coefficient ranges in value between -1.0 and +1.0thatindicatestowhatextent2metricvariablesarelinearlyrelated(spss-tutorials.com).
- A correlation of -1 is a perfect negative correlation Indicates a perfect lineardescending relationship: a higher score on one variable means a lower score onanother.
- A correlation of 1 is a perfect positive correlation Indicates a perfectly linearrelationship: a higher score on one variable is associated with a higher score onanother.
Regressionanalysis
Multiple linear regression (MLR), also known simply as multiple regression, is astatistical technique that uses several explanatory variables to predict the outcome of aresponsevariable.Thegoalofmultiplelinearregression(MLR)istomodelthelinear relationshipbetweentheexplanatory
Inessence, m u l t i p l e regressionis t he extensionof o r d i n a r y least- squares(OLS) regressionthatinvolvesmorethanoneexplanatoryvariable.
Yi=β0+β1xi1+β2xi2+ +βpxip+ ϵ Where,fori=𝘮observations:
Linear regressionis simply a functionthatallows ananalyst orstatisticiant o make predictions about one variable based on information known about another. Linearregressioncanonlybeusedwhenavariablehastwocontinuousvariables.Anindependentv ariableandadependentvariable.Theindependentvariableistheparameter used to calculate the dependent variable or result A multiple regressionmodelextendstoanumberofexplanatoryvariables.
One-wayAnova
ANOVA test the null hypothesis that the samples in all groups were drawn frompopulations with the same mean In other words, ANOVA is used to testing groups toseeifthere’sadifferencebetweenthem.One-way
ANOVAhasoneindependentvariable (with2 levels) andTwo-way hastwo independentvariables (itcanhavemultiplelevels).
According to Gosset (1908), one-way ANOVA is used to check for differencesbetween at least three groups, as the two group cases may be covered by the t-test.When there are only two means to compare, the t-test and the F-test are equivalent; TherelationshipbetweenANOVAandtisgivenbyF= t2.
Introduction
The sample collected consisted of 460 surveys Of which, 11 votes were invaliddue to omitting the answer Therefore, the final exact number of valid samples selectedwas449andwasimportedintoSPSS20softwaretoperformquantitativeanalysis.
Descriptiveanalysis
Gender
According to the results of table 4.1, the total number of participants in this studywas449people.Inparticular,thenumberofmenaccountedfor53.2%.
Age
According to the data in Table 4.2, the survey respondents were mostly aged 18-
22 (accounting for 66.8%) and followed by 23-26 years (accounting for 26.1%) This isthe age group that the author is targeting from the beginning because it is suitable forthetargetaudiencewhooftenchoosetoshoponline.
Occupation
According to the results of table 4.3, 307 respondents were students (accountingfor68.4%),correspondingtotheagegroupof18-
Income
Look at the results in Table 4.4, in general, most of the respondents have less than3 million VND as income because students take a large proportion of all respondents(38.1%) People who earn 3 to
6 million VND per month take the second largestproportion(23.6%),andmorethantenmillionVNDasincometakethel e a s t proport ionof449respondents(8.9%).
Frequency
Source: SPSS 20 statisticsAccordingtotheresultsofTable4 5 , m o s t o f t h e r e s p o n d e n t s h a v e o n l i n e shoppingh a b i t s 1 - 2 t i m e s / m o n t h ( 5 7 2 % ) T h e n u m b e r o f p e o p l e w h o h a v e o n l i n e shoppingh a b i t s a f e w t i m e s a m o n t h a c c o u n t f o r 2 9 % T h e m i n i m u m n u m b e r o f purchasesis6-10times/month(0.9%).
Reliabilityofscale
Cronbach'scoefficientalphaprovidesanindicationoftheaveragecorrelationbetween all items that make up the scale In order for Cronbach's alpha to be valid, thefollowingcriteriaarerequired:
- Testing the reliability of the scale through Cronbach’s Alpha coefficient and thescaleisacceptedasCronbach'salphareliabilitycoefficientgreaterthan0.7(Nunnall y,1978).
FromtheresultsofTable4.6,Cronbach'sAlphacoefficient>0.7andtheCorrected Item-Total Correlation > 0.4 Therefore, the scale of subjective variables isreliable.
EFAfactoranalysis
Explorefactoranalysis(EFA)helpsexaminetheconvergent valueanddiscriminantvalue.EFAmustsatisfythefollowingrequirements:
According to table 4.7, the results of factor analysis show that the KMOindex is0.781> 0.5, which proves that the data used for factor analysis isperfectlyappropriate.
Barlett’s test result is 528 with Sig = 0.000 < 0.05 Therefore, reject thehypothesis H0: the observed variables have no correlation with each other in thewhole So, variables are correlated with each other and satisfy factor analysisconditions.
Theresultsshowedthat33observedvariablesweregroupedinto9groups.Valueo fthetotalvarianceextractedf,350>50%:satisfactory;thenitcanbesaidthat these9 factorsexplain66,350%ofthedatavariability.
Extraction Method: Principal Component Analysis.RotationMethod:VarimaxwithKaiserNormalization. a.Rotationconvergedin6iterations.
According to the results of Table 4.9, Factor loadings are greater than 0.5, andthere is no case in which the upload of both factors at the same time has a close loadfactor.S o , f a c t o r s t h a t e n s u r e t h e c o n v e r g e n c e a n d d i f f e r e n t i a t i o n w h e n a n a l y z i n g EFA In addition, there is no disturbance of factors, meaning that one question cannotbec o n f u s e d w i t h a n o t h e r S o , a f t e r fac to r a n a l y s i s , t h e s e i n d e p e n d e n t f a c t o r s r e m a i n thesame,withoutbeingaddedorreduced.
CorrelationAnalysis
A (Pearson) correlation is a number between -1 and +1 that indicates to whatextent 2 metric variables are linearly related The correlation coefficient has a valuebetween-1and1withthefollowingmeanings:
ACC COM TIM RQ RC RE PSR WR RCRE
Pearson correlation analysis results show from table 4.10 that several independentvariables are correlated with each other Therefore, the regression analysis should payattentiontotheproblemofmulti-collinearity.
According to the results of table 4.10, the strongest correlation is between COM(completeness)andRCRE(ReviewCredibility)wellbeing:r=0.577>0.Itisb asedonND9andsig=0.000.Therefore,COMandRCREhaveapositivecorrelation(r
> 0) The second significant correlations in the table are 0.511 which represents WR(Websitereputation)andRCRE(ReviewCredibility).
However, there are 2 variables ACC (accuracy) and RE (reviewer expertise) withsig> 0.05,twovariablesarenotcorrelatedwithdependentvariables.
MultipleLinearRegressionAnalysis
Linear regressionis simply a functionthatallows ananalyst orstatisticiant o make predictions about one variable based on information known about another. TheFormulaforMultipleLinearRegressionis:
Yi=β0+β1xi1+ β2xi2+ +βpxip+ϵ Where,fori=𝘮observations:
The coefficient of determination (R-squared) is a statistical metric that is used tomeasure how much of the variation in outcome can be explained by the variation in theindependent variables R2 always increases as more predictors are added to the MLRmodeleventhoughthepredictorsmaynotberelatedtotheoutcomevariable.
R2 by itself can't thus be used to identify which predictors should be included in amodel and which should be excluded R2 can only be between 0 and 1, where 0indicates that the outcome cannot be predicted by any of the independent variables and1 indicates that the outcome can bepredicted without error from the independentvariables.
1 ,702 a ,493 ,484 ,69538 1,802 a Predictors:(Constant),WR,RQ,TIM,RE,ACC,RC,PSR,COM b DependentVariable:RCRE
From table 4.11, R-square shows 49.3% of the complete variance of thedependentvariable(ReviewCredibility)thatcanbeinterpretedbyeightindepende ntfactors(Accuracy,Completeness,Timeliness,ReviewQuantity,ReviewConsiste ncy,Reviewer Expertise,Product/ServiceRating,and Website
Reputation) The remaining is 50.7% are due to factors outside the model andrandomerrors.
For n = 33, k' = 8, look up Durbin-Watson table, dL = 0.757, dU = 1,874.AttachedtotheDWvaluebar,0.757