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REVIEWING FACTORS AFFECTING CONSUMERS' TRUST IN E-COMMERCE:
A UNIFIED MODEL
• NGUYEN THI MAI ANH - PHAM THI THANH HUONG
ABSTRACT:
Prior researches have found that trust plays a significant role in shaping purchase intentions of a consumer (Oliveira, et al., 2017). Based on an extensive review of hterature, this study explored main factors affecting the trust of consumers when they do online shopping. Nine constructs of three dimensions were identified as factors affecting the consumers' overall trust after intensively reviewing related literature. Given the dimensions and sources of trust, a research model for developing consumers' trust in e-commerce is suggested. This study makes a contribution to the development of a theoretical undersianding of consumers' trust in e-commerce. The concepts presented in this study can be used to carry out further empirical researches and also be used by managers to improve their customers' trust.
Keywords: E-commerce, online shopping, trust, Vietnam.
1. Introduction
In recent year, thanks to the rapid expansion of intemei and the development of various quick and easy online payment methods, e-commerce has emerged as a new shoppmg channel which could rival and even replace some sections of the long- e\isied mortar and brick stores. Via e-commerce, con^umers are able to access larger .selection of product and .service, sometimes even at better price because the cost for physical store ean be avoided in case of online shop. Another advantage ihai make e-commerce popular is that it grants users the ability to shop whenever and wherever they want.
E-commerce is the sale of products and services over the Intemet. Since the transactions take place without personal contact, consumers are generally concerned of the legirimacyof the vendor and authenticity of the product or service.
Consequently, consumer trust in the Intemei vendor is an issue of major concern. A majority of consumer use the intemet to browse for information concerning their future purchase item on Intemet shopping websites, however, only a small number of them actually buy that item online (Chen & Barnes. 2007. Johnson, 2007). Lack of trust has been cited as the primary hindrance to e- commerce in numerous past research (Chen &
Bames, 2007 and Lee & Turban, 2001). The intention to purchase online of shoppers is considerably influenced by the degree of trust ihey have on the e-vendors (Kim el al. 2008). Grabner- Krauter (2002) highlighted the significance of trust in e-commerce's growth in the long run. Hence, it is important that Intemet vendors fully understand how customer perceive their trust in e-commerce in order to build and win customer trust so as to survive and realize financial success.
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This siud\ 1^ going lo undertake an exien^ne revieu of the existing literature to identitS dimension-s of the trust construct major sources of consumer tmst formation, and propose causal relationships beiween tmst dimensions and overall online irusi. The paper makes two contributions to studies on tmst. Flr^t. it establishes a conceptual basis for undertaking empirical work on consumer tmst in E-commerce. Second, it proposes theoretically sound relationships between various attnbules, which can help Inlemet vendors to consider issues for forging tmslworthy relationships.
2. Trust and sources of trust 2.1. Trust
Interpreting dimensions of a conscmct is to understand the meaning of the concept. This helps in exactly delineate what is included and whal Is excluded from iis domain. An examination of tmst- relaied literature reveals that in spite of significant interest in researching tmst issues, there is no universally accepted scholarly definition of trust.
For example, in psychology. Roller (1967) defined that interpersonal inisl is expectancy held b\ an individualoragroupthat the word, promise, \erbal or w ritien slaiemeni of another individual or group can be relied upon. In management theor\. Silkin and Roth (1993) define tmst as one's belief and expeclaiion about the likelihood of having a desirable action performed by the trustee.
Cummings and Bromiley (1996). Ring and van de Ven (1992). and Sabel (1993) defined trust as one's assessment of others' goodwill and reliabilily. Larzerele and Huston (1980) contended
;hat tmst is a behavioral intention, which refiects the dependence on a partner. It is a strong belief in lhe fact that the olher can be relied upon, is straightforward, benevolent, and honest.
Although there is significant diversity in the definitions. Rousseau et al. (1998) extracted common ihemes in the different conceptual definitions of irust lo siiLigcst ihat trust is a
••ps\cho!ogical slate comprising the intention to accept \ulnerability based upon positive expectations of the intentions or behavior of another under conditions of risk and interdependence" There are se\eral important
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issues in this definition that are worthy of being emphasized. Firsi. trusi is a ps\ chological slate thai researchers in different disciplines interpret in tenns of beliefs, confidence. posiii\ c expectations, or perceived probabilities. Second, trust is not a behavior (e.g.. cooperation), or a choice (e.g., taking a risk), but an underlying psychological condition that can cause or result from such actions. Third, tmst has positive outcomes. Fourth, trust is developed under specific conditions - risk and interdependence. Tmst under conditions of risk suggests thai a person who trusts assesses the vulnerability and uncertainty of whether the other party intends to and will act appropriately. Trust would not be needed if actions could be undertaken with complete certainly and no risk, and the one who tmsts is not in a vulnerable position.
Although Rousseau et al.'s (1998) conception of tmst has been well received by many authors, there are others who have argued that this definition is too abstract to be useful for conceptual or empirical work and called for specifying the domain and connotative meaning of the tmst construct in the context of a certain discipline, This inherited nature in mo.st definitions of tmst has resulted in two streams of insight: one group of scholars insist thai tmst construct be measured by one single dimension, such as reliability (Seines, 1998), or motivation (Anderson and Nams, 1990), while the other group of scholars contend that the trust constmct is multi-dimensionai. For instance, Ganesan and Hess (1997) proposed two dimensions of trust: credibility, the main partner's intention and ability to keep promises; and benevolence, evidence of genuine concern for the partner through sacrifices ihat exceed a purely egocentric profit motive. These authors also provide empirical support for the discriminant validity of these tmst dimensions. Barber (1983) proposed that tmst expectations likely include evaluations of (1) technica competent role perfomiance (e,g. by the ser-. . p „ „ y e ) , and (2) carrying ou, obligations „„d responsibilities by placng others (e.g.. consu.ncrs, ,„terest befot.
^e,r own. Other researchers pr„p„„„^ , . ^ ^ „ ^ , „ ^ of tr„st include Morgan ,.r.: H„„ „
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suggesi tmst to be composed of reliability and miegniy and Zaheer et al. (1998) who consider mLsi being formed ihrough reliability, honest)', and predictability. Clearly tmst is a multidimensional construct
The nature of e-commerce does not include face-to-face interaction. This prevents consumers from assessing the imstworthiness of an e-vendor which can be done with ease in a direct interaction.
Hence, trust is even more cmcial in the e- commerce context (Reichheld & Schefter 2000).
Prior research suggests that consumers generally avoid buying from Ihe online shop they perceived as untnistworthy (Reichheld & Schefter 2000).
2 J. Sources of trust
According to Kooli et al (2014), components of online trust can be divided into three big groups based on its sources. They are personal based tmst.
cognilive-based trust, and institutional based trust groups. Three faclors belong to personal based Inisl are e-vendors' compeience, inlegrily, and benevolence. Smiilariy, situation nomialily.
assurance, and website quality are the name of ihree dimensions in cognitive-based trust group.
Lasil), an institutional based trust includes reputation. cost/benefit calculation. and predictability (Kooli et al (2014), Corritore et al (2005)).
Personal based trust
Competence, integrity, and benevolence have been idenlified as three d-usting beliefs that form lhe inist faclors in online shopping by various past research (McKnight et al, 2002; Chen & Dhillon.
:()0.1. Palvia. 2009: Oliveira el al, 2017). When consumers perceive a company as competent in a specific area, that company should be able to smoothly operate in the said department (Lu. Zhao
& Wang. 2010). Competence refers to the ability of an e-vendor to dehver products and services at the desired quality for customers (Wang &
Emurian. 2005). handle the transaction and fulfill ils promises made to cheats (Chen & Dhillon, 2003). Integrity is a trusting belief concerning vendors' attitude towards consumers while doing business Companies achieve integrity when the\' prove to act consistent, truthful and genuine when
•reating consumers (Chen & Dhillion. 2003).
Oliveira et al (2017) fiirther explained that integrity is when internet suppliers keep iheir promises and commitments and do not overcharge consumers. In short, an e-vendor with integrity should follow its predetermined set of rules and promises. Many faclors form benevolence characteristic of an online shop, namely attention.
empathy, belief and acceptance (Kim et al. 2005).
Lu. Zhao & Wang (2010) define benevolence as the dedication of companies (trustees) in caring and doing good deeds for its consumers (trustors).
The situation at which iniemel vendors place consumers' interesi higher than their own interest, trj' to improve customers" satisfaction rather than merely aim at maximizing profit is the description of benevolence by Oztiiren. 2013). (2013).
Consumers decide whether an online supplier is tmstworthy or not via their perception of its competence. inlegrily. and benevolence (McKnighl etal. 2002: Oliveira et al, 2017).
Cognitive based trust
Cognitive based trust is built Ihrough people use of their common knowledge - own mind or asking relatives or friends- when they want to purchase online a particular produci. Cognition- based trust is a moderator in Ihe relationship between cognitive contlict and decision outcomes.
It arises from first impression rather than experiential personal interactions. Based on this first impression. Li et al. (2008), and Mcknight et al. (2002) and Jar\'enpa et al. (1999) emphasised reputation of web vendor as being an antecedent factor of cognitive based.
Reputation is an element Ihat affects tmst directly (Anderson & Weitz, 1989; Doney &
Cannon. 1997: Grazioli & Jarvenpaa, 2000). The reputation of companies is gained by caring and acting truthful lowards their consumers (Doney &
Cannon, 1997) According to Jarvenpaa &
Tracnnsky (1999). consumers are more likely to trust a companv with good reputation. Gefen (2000) implied that people are going to use reputation to base their imst in a company in case they do not have enough inlbrmalion and experience with it.
Doney et al. (1991) added calculative or cost and benefit calculation dimensions as an
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aniecedeni of cogniu\e based tmst. Furthermore.
Shapirro et al. (1992) stated that calculative based tmsi IS driven b\ economic principles, when people .shaped by iheir rational assessment of the COS! and benefils of another part)' cheating or cooperating in the relationship. Moreover, people tend 10 tmst when the trustee is thought to have nothing to gain, or the cost overwhelms the benefit, from being unlmstworthy (Shapiro et al.. 1992).
Paul and McDaniel (2004) evaluated calculative tmst in an initial interpersonal tmst context and argued lhal as long as the tmstor is vulnerable to the non-performance of the tmstee. calculative tmst is effective.
Il is believed predictability has contribution to consumers' evalualion regarding e-vendors' imstworthiness (Salam el al. 2005: Ozturen. 2013).
Tan & Sutherland (2004) clarified that predictability is the confidence of online shoppers in the consistency of online vendors. Al first glance, predictability and integrity seem similar;
however, prediclabiliiy is lowards the belief of consumers that e-vendors will acl consistently and fulfill their guarantee.
Institutional based trust
Bachmann and Inkpen (2011) claimed that institutions can be an important and efficient facilitator of tmst thai develop through legal provision, corporate reputation, certification exchange partners and community norms, structures and procedures. Mcknight et al. (2003, p.
339) defined Institutional based tmst as "the belief that needed stmclural conditions are present (e.g., in the Intemet) to enhance the probability of achieving a successful outcome in an endeavor like e-commerce". According to Mcknight et al.
(2003) there are two dimensions of institution tmst based which are: stmcturai assurance and situational normality. Assurance is a facior that improves consumers' iriisi and confidence in the companies iRunyan iV Smith. 2008). Zucker (19S6t staled that b\ utilizing the jssurancc s>slem through guarantees, regul.uinns, legal documenls and other procedures, consumers feel safer and more secure when dealing with companies Additionally, clients calculate the cost and benefit the other party gain before placing their imst m
anotiier party (Shapiro et al. 1992). In an economic exchange, people only participate in die deal only if tiie outcome is satisfactory to ihem; specit ically.
when tiie expected gain surpasses the expected cost (Blau. 1964). Tmst is also driven by situational factors (Hagen & Chloe 1998). In regard to e- commerce. if tiie users believe that tiie situation, tiiey face is a typical or favorable consequence to them, they are likely to trust online environment (Mcknight el aL 2002).
According to Corbitt et al. (2003); McKnight et al. (2002), the quality of tiie website influence consumers' tmsts on intemei vendors. In e- commerce, the website is tiie replacement of salesperson created by vendors. A well-presented websiie enhances users' experience and perception of the e-vendor. Users later use lhe experience tiiey gain from using the website to assume the nature and imstworthiness of companies (Koufaris & Hampton-Sosa, 2002).
There is a number of factors that build up the quality of website including navigation function (Cheskin/Sapient, 1999), visual design (Kim and Moon, 1998) and overall appearance of tiie website (Belanger et al, 2002; Kim and Stoel, 2004). In short, a well-designed website can assist e-vendors in building trust and relationship with consumers.
3. Findings from literature
As suggested in the literature overall trust of a consumer in an Intemet vendor is determined along three main dimensions (personal based trust;
cognitive based trust and institutional based tmst) including nine constructs: competence, integrity, benevolence, reputation, assurance, cost/ benefit calculation, sil normality, website quality and predictability. These nine constructs are expected to be the driven factors to consumers' overall trust on internet vendors. Detailed description of the constructs has been presented in previous sections.
Furtiiermore, a lot of past research had proved that tiiere is apositive relationship between overall tmst of consumers on e-vendors and their intention to purchase online (Gelen, 2000; Jarvenpaa et al, 2000: Lim et al, 2006; McKnight et al- 2002) It is concluded thai trust can shape the willingness to purchase onlme of shoppers. <M more an e-vendor
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figitB 1: Factors affecting online ttust
Personal based trust
Competence Integrity Benevolence
Online purchase intention
Institutional based trust
Situation normality
Website Quality
IS perceived as trustworthy, the more consumers are likely to purchase at tiiat e-vendor (Jarvenpaa etal, 2000).
h is therefore authors propose the relationships between these constructs in the figure I. This could be seen as a research model for further empirical study in this field.
4. Conclusions
This paper has idenlified three main dimensions of trust making from nine constmcts. It has been argued that overall consumer tmst for an Intemet vendor can be built by focusing on each of lhe.se constructs. In a final synthesis a research
raodei for developing consumer trust is presented.
The concepts presented in this paper will surely benefit both academics and practitioners. For lhe academics, the paper sketches out a theoretical and a conceptual map of the literature on consumer tmst as it relates to E-commerce. Opportunities exist to empirically test the propositions presented in the paper and develop measure of consumer trust in E-commerce. For the practitioners, the trust dimensions and sources of tmst, organized in a research model, serve as an evaluative framework lo assess current emphasis and idenlify opportunities for improvement •
REFERENCES:
/. Anderson. E. and Weitz. B.. 1989. Delennincmts ofccmlinuity in convendonal industrial channel dyads. Markeling science. 8(4). pp.310-323.
2. Belanger. F.. Hiller. J.S. and Smilh, W.J., 2002. Trustworthiness in eiecironic commerce: the role of privacy.
security, and iiteauributes. The journal of sirciiegic Information Sysiems, 11(3-4). pp.245-270.
3. Blau, H.. 1964. The Impossible Theater- A Manifesto. Macmillan.
4 Chen. SC. and Dhillon. G.S.. 2003. Inlerpreling dimensions of consumer iritsl in e-commerce. Information
"chnology and management. 4(2-3). pp.303-318.
5. Chen. Y.H. and Bames. S.. 2007. Inilial tmst and online buver behaviour. Industrial management & dala .'{yslemx 107(1). pp.21-36.
So 2-Thang 2/2020 145
TArCIICdNGTII^OFNG
6 Cheskin Research and Studio Archeiype/Sapieni (1999) Ecommerce Trust Sludy. <htip:/Av\\» ^.'/"<nucmi/che- skm accessed 5/9/2000>
7. Corhiu. B.J., Vianasankit. T. andYi H.. 2003 Tmst and e-commerce: a sludy of consumer perceplions. Electronic commerce research and applications, 2( 3 ),pp.203-21:-.
S Corriiore. CL. .Marble R.P.. Wiedenbeck S.. Kracher. B. and Chandran, A.. 2005. Measuring cmline Irust of websites: Credibiliiy. perceived ease of use. and risk. AMCIS 2005 Proceedings. p.370.
9. Doney. P.M. and Cannon, LP.. 1997. .\n examinalion of the nature of mist in buyer-seller relaiionships. the Joumal of Markeling. pp.35-5L
10. Gefen. D, 2000. E-coitunerce: lhe role of familiarity and trust. Omega. 28(6). pp.725-737.
11. Gefen. D. Karahanna. E. and Straiib, D.W.. 2003. Tmst and TAM m online shopping: An integrated model. MIS quanerly, 27(1), pp.51-90.
12. Grabner-Krauler. Sonja (2002). 'The Role of Consumers Trust in Online Shopping', Joumal Business Ethics.
39.43-."^)
13. Grazioli. 5. and Jan'enpaa. S.L. 2000. Perils of Inlemet fraud: An empirical investigation of deception and Irusi wilh experienced Iniemel con.sumers. IEEE Transactions on Sysienu, Man, and Cybemelics-Parl A: Systems and Humans, 30(4). pp.395-410
14 Hagen, J.M. and Chae, S.. 1998. Trust in Japanese inleifirm relalions: Insiilulional sanctions mailer Academy of management Review. 23(3), pp.589-600.
15 Jarvenpaa. S.L. Traclinsky, N. and Saarinen, L, 1999. Coiiiumer Irusi in an Iniemel slore: A cross-cultural validalicm. Jcmmal of Computer-Mediated Communication. 5(2), pp.526.
16. Jarvenpaa. S.L. Traclinsky. N. and Viiale, M., 2000. Consumer Irusl in an Iniemel store. Infomialion technology and mcmagemeni, l(l-2).pp.45-7l.
17. Johnscm, D.S.. 2007. Achieving customer value from electronic channels Ihrough identity commitment, calculaiive commiimeni, and Irusl in lecbnolog\. Joumal of inleraclive markeling, 21(4), pp.2-22.
18. Kim. D.J.. Ferrin. D.L and Rao. H.R. 2008. A trust-based consumer decision-making model in electronic commerce: The role ofirusi. perceived risk, and Iheir anieeedenis. Decision support sysiems, 44(2), pp.544-564.
19. Kim. J. and Moon. J.Y., 1998. Designing towards emolional usabiUiy in cusiomer inletfaces-lrustworlhiness of e-vlwr-banking system interfaces. Interacling wiih compulers, 10(1), pp.1-29.
20 Kim, S. and Stoel. L, 2004. Apparel retailers: website quality dimensions and salLsfacdon. Jcmrnal pf Retailing and Consumer Sen ices, 11(2), pp.109-} 17.
21. Knoll. K. Ben Manscmr. K. and Utama. R.. 2014. Deierminanls of online Irusl and their impact an cmline purchase inieniion. International Joumal ofTechnology Marketing 5, 9(3), pp.305-319.
22. Koufaris. M. and Hampion-Sosa, W., 2002. Customer Irusl online: examining the role of lhe experience wilh lhe Web-siie. Depanment of Slatisiics and Compuier Informadon Sysiems Working Paper Series, Zicklin School of Business, Baruch College. New York.
23. UI. Y.. 2Jiao. L and Wang. B.. 2010. From vinual community members to C2C e-commerce buyers: Trust in virtual ccmimunities and its effeci on consumers' purchase intention. Electronic Commerce Research and Appbcaiion.s. 9(4). pp.346-360.
24. Mi-Knight. DH. Choudhury. \\ and Kacmar, C, 2002. Developing and validating Irust measures for e-cimmerce. .\ii iniegraiive typology. Information sysiems research, 13(3). pp 334-359.
25. Oliveira, T, Alhinho. M. Rilu. P. and Dhillon. G.. 2017. Modelling and tesling consumer trust dimensions in c-commerce. Computers in Human Behavior. 7l.ppJ53-164.
26. Ozturen. -A., 2013 Eff, • s ofelectrcwi, irust on pun base intentions in online social review networks: The case of Tnpadvisor torn.
27 Palvia. P. 20(N. TL. role of truu m e-commerce relational exchange: A unified in,..,ti Information &
management. 4614), pp 213-220
2S. Reichheld F.I and S, lHtic< P, Zmm L-IOMIII\ • vcnir secret weapcm on lhe well iiu,^urd h,. • 7Si4).pp.W5.IL\ '^'^^rd business review, 29. Salam.,X.T. A./ L. Palau. P ami Sm-h R . 21)05. Tru.u in e-commerce. Cammunu ..•„„. ,,,, , ^ „ , „ , , , pp,72-77 "I "'c ACM. 48(2).
146 So 2 - T h d n g 2/2020
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!0. Staptra. D.L. SIteppard. B.H attd Oterasklit. L. 1992. Buslttess oti a Itandsliake. Neeotiatlatt ioutital SI4i pp.XS-177.
11. Tail. FB. and Sutherlattd P.. 2004. Ottllrte cottsuitter tntsi: a tnultl-dititcttsiottal tttadel. Jotmtai ofElectwttlc Ctmtteire Itt Organlzatloits iJECO). 2(3i. pp.40-58.
.12. V/img. r.D. attd Ettturlait. H.H.. 2005. Alt overvltnt of online tmst: Concepts, elements, and Itttpllcattons.
Computers In ituntan heliavior. 2111), pp. 105-125.
13. Zailcr. LG. I9S6. Production of trust: Institutional sources of economic structure. 1840-1920 Researcli In orttmtitittlonal behavior.
Receiving dale: 20/12/2019 Reviewing date: 30/12/2019 Accepting date: 14/1/2020
Author Information:
1. Ph.D. NGUYEN THI MAI ANH Hanoi University of Science and Tectinoiogy 2, MBA. PHAM THI THANH HUONG Hanoi University of Science and Technology
CAC YEU TO ANH Hl/dNG DEN NIEM TIN c£jA N G U O I T I E U D U N G Kffl MUA HANG TREN MANG:
MO HINH H0P NHAT
• TS. N G U Y I N TH! MAI ANH TrUdng Bgi hpc Bach khoa Ha Ngi
• ThS. PHAM TH! THANH Hl/CiNG TfUdng Dgi hoc Bdch l<hoa Ha Npi T6M TAT:
Cdc nghidn ctfu tnrSc day da chi ra rang: niem tin ddng vai tro rat quan trong va anh htfdng idn den dtf dinh mua cua ngtfcfi tieu dung (Oliveira va dong nghiep, 2017). Muc tieu ciia bai nghien ctfu nay IS nhan di6n cac ye'u to chinh anh htfdng de^n niem tin cua ngtftJi tieu dung khi mua hSng tr§n mang bang each tong hop nhtfng nghien ctfu trtfdc day. Chin yeu to'anh htfdng thupc ba nhdm tac ddng da dtfdc phat hien. Md hinh nghien ctfu ve tac dong cua cac ye'u td' nay d^n ni^m tin chung cua ngtfdi tieu dung cung dtfdc de xua't. Nghien ctfu nay khdng nhtfng giup lilm tang stf hieu bie't ve ly thuyd't, ma cdn giup cac nha nghien cu^ de dang kiem nghiem tren thtfc td'va cdcnha quan tri biet each tang niem tin dd'i vdi nhtfng khach hang trdn mang.
TiJ khda; Thtfdng mat didn ttf, mua hang trdn mang, niem tin, Viet Nam.
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