The antecedents of online brand trust: Malaysian evidence/Pasitikejimo internetines prekes zenklu praeitis: Malaizijos pavyzdys.
Alam, Syed Shah ; Yasin, Norjaya Mohd.
1. Introduction
Nowadays many consumers are turning to the Internet for most of
their shopping needs and concerns. This has created many business
opportunities. However, online retailing in Malaysia is still in the
early stages of development and its full potential has not been reached
yet (Chua Phaik Harn et al. 2006). According to Economist Intelligence
Unit (2006) companies whose business plans relied completely on online
operations have found it difficult to survive, especially in the
business-to-consumer (B2C) area. In 2005 less than 5% of SMEs in
Malaysia were involved in B2C businesses. On the other hand, a higher
Internet usage has been noted and this paves the way for possible
business opportunities of the Internet. This is a positive indicator for
the Asian online retailers. Companies should try to instill trust in
their brands in order to boost the confidence of consumers to buy their
services or products.
Research on brand is becoming more important in the marketing arena
as firms are facing competitions both locally and globally. Recently
researchers have developed many useful constructs and measurements on
brand personality, brand community, brand trust and brand attachment
(Carrol and Aaron 2006; Thomson and McInnis 2005; Delgado-Ballester
2003; McAlexander et al. 2002). An empirical study by Chlivickas and
Smal-iukiene (2009) have analyzed both emotional and cognitive
components of the brand origin. The study mainly tested the direct
effects of attributes of local brands on the brand origin of telecoms
and food industries in the Baltic Sea region. Another study by
Maiksteniene and Auruskeviciene (2008) mainly measured the levels of
baby diaper consumer purchase decision involvement in Lithuania. Results
show that consumers with differing purchase involvement levels differ in
their relative valuation of manufacturer and retailer brands in the same
product category. In the present study we are trying to identify the
antecedents of online brand trust.
In the past few years several studies on brand trust have been
carried out. Scholars are increasingly becoming interested in the issues
presented in this area of research due to the fact that consumers are
playing the main role for any transactions. For example consumers are
willing to transact, and market could function well if consumers trust
any brand and the company (Zucker 1986). In any business transaction,
brand trust is very important for several reasons. For instance,
according to Schurr and Ozanne (1985), trust creates more favorable
attitudes towards suppliers as well as customer loyalties. It also helps
partners project their exchange relationships into the future (Doney and
Cannon 1997). Trust increases competitiveness, reduces searching and
transaction costs, and mitigates opportunism in uncertain contexts
(Doney and Cannon 1997). Reast (2005) suggests that brands that are
trustworthy will benefit more than their less trustworthy competitors.
Online trust is also an important phenomenon in both
business-to-business (B2B) and business-to-consumers (B2C). With the
evolution of new e-business models and the advances in information
technology, it brings more challenges than solutions for establishing
and maintaining trust in the electronic marketplace (Xiling and
Xiangchun 2005). Forrester Research survey in year 2000 found that 51%
of companies would not trade with parties they do not trust over online.
Goodwin (1996) points out that trust is the grease that keeps the wheels
turning. The reason online consumers have yet to shop online in large
numbers is that consumers simply do not trust most web providers enough
to engage in "relational exchanges" involving money and
personal information (Hoffman et al. 1999). Consumers are reluctant to
reveal their personal information online. Brands have to establish a
certain amount of trust with customers, in order to make the Internet a
viable commerce medium. Internet users want to feel that their privacy
is being protected. Providing information about how their personal data
are used and exploring the possibilities of offering consumers privacy
preference are among the issues the consumers think should be addressed
(Rubin 1995).
The growth of interest in preferring the Internet as a shopping and
information medium has created interest among many researchers. It will
be essential for the retailers to know what influences the online users
to purchase services online. In this study the focus would be on
Malaysian Internet users making purchase transactions online. In
addition, this study also tries to identify the acceptance and
possibility of a consumer accepting a particular brand online. It is to
find out what makes them view a particular brand as trustable.
The steady growth of online consumer purchasing in service
categories is a driving force that convinces businesses that they should
make firm commitment to Internet branding (Breakenridge 2001). Although
there is a larger audience on the Internet, the companies must take into
account the consumer's perception of brand trust online. With the
rise of ecommerce, online brand trust has often been identified as a
critical component and has increased in importance among the Internet
users. A number of researchers have suggested that brand trust is a
critical factor in stimulating purchases over the Internet (eg. Quelch
and Klein 1996; Corbitt et al. 2003).
The Malaysian online users at the moment are still in the
experimental stage in brand trust online. They are still exploring the
brands online and see what these brands can offer them. In the tourism
industry, most of the airline travelers are still buying their tickets
from traditional agents. The users are not yet convinced of the benefits
of the brands that are available online. However, now the purchasing of
air tickets online is becoming more popular among the Malaysians due to
its convenience and cost-saving.
The findings of this study should assist marketers and academicians
in their understanding of the development of brand trust especially in
an Internet-based shopping environment. It will also help the retailers
to better understand what influences the consumers to purchase certain
products or services online. The study also hopes to shed some light on
retailers who are trying very hard to achieve success in the competitive
online business world. It is important for them to recognize the factors
so that they can take the necessary steps to boost their sales. The
results of this study should also enlighten marketers in planning their
marketing strategies. The online retailers will be more knowledgeable in
the brand orientation and the preference of consumers. Online retailers
may take the necessary corrective actions to provide better services.
This will serve as a platform that will lead to the sustained confidence
of the consumers of brands online.
2. Literature Review
Chaudhuri and Holbrook (2001) defined brand trust as 'the
willingness of the average consumer to rely on the ability of the brand
to perform its stated function. In this study, brand trust is simply the
trust a consumer has in a specific brand, a definition based on Ha
(2004). For a consumer to establish a relationship with a particular
brand, trust is crucial because without trust, development of
consumer's commitment to a brand may not be possible. A consumer
who trusts in the brand is more willing to remain loyal to it, to pay a
premium price for the brand as well as buying new products in the
existing or new categories that carries the same brand name, and to
share some information about his or her tastes, preferences and behavior
(Chaudhuri and Holbrook 2001; Busacca and Castaldo 2003 as cited in
Horppu et al. 2008). Considering brand trust as expectancy, it is based
on the consumer's belief that the brand has specific qualities that
make it consistent, competent, honest, and responsible and so on, which
is in line with the research on trust (Andaleeb 1992; Doney and Cannon
1997; Larzelere and Huston 1980). Their research suggests that trust is
based on the dispositional attributions made to the partner about
his/her intentions, behaviors and qualities. The key issue, then, is to
know which specific attributions form brand trust.
Yague-Guillen et al. (2003) reported two-dimensional idea of trust
such as i) technical and ii) intentional nature, which is more commonly
found in management and marketing literature (Doney and Cannon 1997;
Ganesan 1994; Morgan and Hunt 1994). Therefore, the first dimension of
brand trusts technical or competence-based nature, involving the ability
and willingness to keep promises and satisfy consumers' needs. The
second dimension comprises the attribution of good intentions to the
brand in relation to the consumers' interests and welfare, for
example when unexpected problems with the product arise. Consequently, a
trustworthy brand is one that consistently keeps its promise of value to
consumers through the way the product is developed, produced, sold,
serviced and advertised, and even in bad times when some kind of brand
crisis arises.
Srinivasan (2004) believes that people trust a brand based on their
own past experience as well as by third party recommendations. While
another researcher Ha (2004) who studied on factors influencing consumer
perceptions of online brand trust has found that brand trust is affected
by the following Web purchase-related factors: security, privacy, brand
name, word-of-mouth, good online experience and quality of information.
This is similar to two of the factors that have been stated by Ha (2004)
which is word-of mouth and good online experience. In the trust model
done by Srinivasan (2004) it also shows the use of security in building
consumer trust for an e-business. The findings from both researches are
very similar and the factors they stated are the same too.
In a large scale empirical study by Sultan et al. (2002) uncovered
three underlying dimensions of trust, namely, credibility/reliability,
emotional comfort and quality of the company. The study reveals that
consumer's perceptions of trust are determined by Web site and
consumers characteristics, and thus trust mediates the relationship
between these determinants and customer action behavior. Nine Web site
factors, namely, navigation, advice, no error, fulfillment, community,
privacy/security, trust seals, brand and presentation drive trust. Four
consumer factors, namely, self-confidence/Internet savvy, past behavior,
Internet shopping experience, and entertainment experience also affect
trust.
Lee and Turban (2001) proposed that consumer trust in Internet
shopping is driven by trustworthiness of Internet merchant,
trustworthiness of Internet shopping medium and contextual factors and
that individual trust propensity moderated each of the relationships
between the antecedents of trust. Lack of trust is frequently the key
reason why people do not make purchases online (Lee and Turban 2001).
There is no clear distinction between the underlying dimensions and
antecedents of online trust in most of the studies on online trust i.e.
although Dayal et al. (1999) discuss security, merchant legitimacy and
fulfillment as important determinants of online trust, they also allude
to them as the core elements of online trust. Elements and determinants
of online trust are used interchangeably in many studies. For instance,
Fogg et al. (2001) claim that trustworthiness affects credibility, but
these two constructs are blurred and not well differentiated.
Based on the previous research and differentiate among the
different constructs, a model of online trust developed by Shankar et
al. (2002) included three broad groups namely, Web site characteristics,
user characteristics and other factors. Fourteen Web site
characteristics are navigation and user friendliness, advice,
error-freeness, fulfillment, community, privacy (third party
statements), security (credit card protection), trust seals and refund
policies, brand, presentation, site longevity, selection of items,
timeliness of information, links to other relevant sites. User
characteristics are Internet savvy, Internet shopping behavior,
entertainment experience, place of Web usage, long-term orientation,
predisposition to technology and feeling of control. Other
characteristics include online medium, trustworthiness of firm,
perceived size of firm, perceived reputation of firm, dependence on the
firm, human service, communication, personalization and collaboration.
Assessing the end-user trust in online environment, Salo and
Karjaluoto (2007) developed a conceptual model of trust in the online
environment based on some internal and external factors. In this
instance, external factors including consumer characteristics,
product/service characteristics, different markets/cultures/countries,
perception of risk and past experience are likely to have some effect
towards online trust. Clearly, the internal factors including past
experience, trustworthiness, reputation, website quality, perceived
usefulness, perceived ease of use, training, trusted seal, experts,
peers, legislation, and non-government association have significant
effects on online trust (Shankar et al. 2002; Lee and Turban 2001;
Sultan et al. 2002; Ha 2004; Andaleeb 1992; Doney and Cannon 1997).
Although doing business on the Internet has been around for quite
some time now, most Malaysians still do not feel comfortable in
revealing their personal information online and some just prefer the
traditional physical store where they can see the goods or services that
they are purchasing. Malaysian consumers prefer to see the goods that
they are purchasing before they are willing to pay for them. It is still
unclear on how to change the mindset of the Malaysian Internet users
into purchasing online. In order to understand what influences the
online users to purchase a certain brand online we must first find out
the factors that are influencing consumers' perception of brand
trust online. Malaysian is very skeptical about revealing their personal
information to unknown people especially when it involves money. Indeed,
this study is focused on the online trust among consumers in a
developing country like Malaysia.
3. Theoretical Framework
In this study, six factors have been identified, based on past
research, as factors influencing online brand trust namely good online
experience, the quality of information provided by the website,
word-of-mouth by friends and family, brand reputation, security of the
website (Ha 2004) and perceived risk of purchasing online (Salo and
Karjaluoto 2007). The first factor to be investigated in this study is
security/privacy. In making business transactions online, it is
important for consumers to feel secure in giving personal information
including credit card details. This would certainly affect their trust
on the brands that they are purchasing online. Past research have proven
that security influences consumers' brand trust (e.g. Reichheld and
Schefter 2000; Salisbury et al. 2001 as cited in Ha 2004). Ha (2004) has
found that consumers tend to associate higher security feelings with a
higher level of brand trust.
Another factor affecting brand trust is consumers' perceived
risk. Consumers' trust on a brand is influenced by the level of
risk that they perceived inherent in the product. In the context of this
research, consumers' perceived risk can be classified in terms of
economic risk, that is monetary loss from a buying decision made online;
performance risk, that is when products or services purchased online do
not meet consumer expectations (Ha 2004) and purchasing risk, that is,
consumers feelings of insecurity in making a purchase online. The amount
of risk that consumers perceived in online purchase transaction would
certainly affect the level of trust that they may have in a particular
brand.
Word-of-mouth (WOM) has been said to be very influential on
consumer behavior than other forms of marketing communications such as
advertising and publicity. WOM has been shown to influence awareness,
expectations, perceptions, attitudes, behavioral intentions and behavior
(Ha 2004). Thus, it is a determinant of brand trust. Many researchers
have found that WOM communications do affects brand trust (e.g.
Reichheld and Schefter 2000; Parasuraman et al. 1988). We assume that
positive WOM about a particular brand helps consumers to cultivate brand
trust.
According to Ha and Perks (2005) consumers' satisfaction and
loyalty develops as a result of the consumers' positive experience
with the brand which will positively affects brand commitment and
re-purchase intentions (Fullerton 2005) and improves brand reputation
(Selnes 1993). Alba and Hutchinson (1987) study reveals that
consumers' brand experience refers to their knowledge of and
familiarity with a brand or brand category. Ha and Perks (2005) defined
brand experience as displaying a relatively high degree of familiarity
with a certain subject area. There is some evidence that brand trust may
be positively related to customer experience (Papadopoulou et al. 2001
as cited in Ha 2004) but the relationship in the context of e-commerce
is still unclear.
A good website usually delivers relevant and quality information
which will provide consumers with a positive experience. This will
induce consumers to establish a bond between the consumers and the brand
on the website. Besides, providing quality information will increase
consumers' knowledge and awareness as well as their perception of
the brand (Keller 1998) which will influence their level of trust.
Another factor that determines consumers' online brand trust
is the brand reputation. Generally, the better the reputation of the
brand, as perceived by the consumers, the higher should be the level of
trust that consumers have on the brand. Brand reputation is related to
brand name which according to Keller (1998) is one of the factors that
facilitate the development of brand awareness or familiarity which will
lead to higher level of brand trust.
Based on the above discussion, we represent the research model in
the following regression equation:
y = [[beta].sub.1]SP + [[beta].sub.2]PR + [[beta].sub.3]WOM +
[[beta].sub.4]OE + [[beta].sub.5]QI + [[beta].sub.6]BR,
where y = brand trust online, SP = Security and Privacy, PR =
Perceived Risk, WOM = Word-Of-Mouth, OE = Online Experience, QI =
Quality Information, and BR = Brand Reputation.
4. Hypotheses of the study
The general research aim of this paper is to understand the
relationship between various influencing factors on consumer trust of
online brand in the Malaysian context. This objective was addressed
through quantitative analysis. After looking at the literatures, this
research posits six hypotheses were derived to examine the objective of
this study:
H1: Security/privacy positively influences online brand trust
H2: Consumers' perceived risk negatively influences online
brand trust.
H3: Word-of-mouth communications positively influences online brand
trust
H4: Good online experience positively influences online brand trust
H5: Quality of information positively influences online brand trust
H6: Brand reputation positively influences online brand trust.
5. Methodology
5.1. Sample and Data Collection
Data for this study was gathered in March to April 2009 by primary
data collection method through consumer survey administered among
working people in Malaysia. Working people were chosen because they are
the ones who normally own a credit or debit card and online transaction
requires the usage such as cards. Buying online, credit card is the
single most common payment method in the world. Data for this study was
gathered through personal administered questionnaire which were
conveniently distributed among the working people in different place in
Selangor. The product category chosen for this study is 'airline
service' (e.g. Malaysia Airlines, Air Asia) as airline service is
highly demanded and tickets are commonly purchased through Internet in
Malaysia. The airline industry is chosen because it is one of the most
competitive and strategic industries in the world using the Internet to
its fullest extent.
Through selling tickets online, the airline company gains economies
of scale and tremendously reduces its operating costs. Target
respondents for this study were anybody who buys airline ticket online.
Respondents were initially screened as to whether they had current
access to the Internet and have experience in purchasing air tickets
online, before being asked to participate in the study.
Of the 252 respondents who were eligible for the study, 224
(88.88%) agreed to complete the survey. However, 15 were discarded due
to incomplete responses; the final sample was 209 for an effective
response rate of 93.30 percent. Table 1 shows demographic information of
the respondents. The majority of the respondents were female (61.7
percent), Chinese group was the highest contributors of the total
respondents (50.72 percent). Their age ranged from 24 to 55 with mean
age of about 37.8 years old. Most of them were bachelor degree holder
representing 60.8% of the total sample.
5.2. Measures
An extensive literature review was performed in order to identify
various factors influencing online brand trust. Then, questionnaires
were developed and divided into three parts. The first part deals with
general usage patterns of the Internet. Part 2 includes dependent and
independent variables of the study. The dependent variable was online
brand trust. The modified scale was developed based on Swan et al.
(1988). Some items of independent variables were developed by the
researchers, while some were adopted or modified from previous research
(Ha 2004; Chen 2006; Shim et al. 2001; Jarvenpaa et al. 1999). All items
used response categories of 1 (strongly disagree) to 6 (strongly agree)
focusing on factors influencing online brand trust. Final part includes
a number of demographic information of the respondents.
Table 2 shows the number of items measuring each variable and the
Cronbach's alpha for scale reliability obtained for our sample.
Reliability from our sample showed a reasonable level of reliability
([alpha]>0.60). The complete measurement of variables is available in
the Appendix.
5.3. Test for content and construct validity of the study
Content validity was tested by experts of two academicians, two
research fellows at the Graduate Business School (Universiti Teknologi
MARA, Malaysia), and three online retailers in Malaysia as suggested by
Hair et al. (1998). Their feedback, both positive and negative, helped
shaped the final version of the questionnaire.
To test the construct validity a factor analysis was conducted on
all the independent variables in order to develop factors that help in
explaining the role of experience and reference group in online brand
trust.
As suggested by Hair et al. (1995), six factors were identified for
the factor analysis using the eigen value criteria that suggest
extracting factors with an eigenvalue of greater than 1.0. In conducting
the factor analysis we followed Hair et al. (1995) and Alfansi and
Sargeant (2000). The rotated factor matrix is displayed in Table 3. The
six factors identified explain 70.46 percent of the total variance. The
extraction method used was principal axis factoring with Varimax
rotation. This method has been widely accepted as a reliable method of
factor analysis (see, Alexander and Colgate 2000). In our survey, the
Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy score (0.86) was
well above the recommended 0.5 level (Malhotra 1999). Moreover, the
Bartlett's test of sphericity indicated that there was adequate
correlation among the chosen variables ([X.sup.2.sub.(209)] = 24.21, p
< 0.01).
Extraction Method: Principal Axis Factoring. Rotation Method:
Varimax with Kaiser Normalization.
However one item of security/privacy, one item of good online
experience loaded together with other items and not meaningful and we
decided to remove from all subsequent analysis.
5.4. Normality of Data and Multi-collinearity
This study involves a relatively large sample (209 respondents) and
therefore, the Central Limit Theorem could be applied and hence there is
no question on normality of the data. Two major methods were utilized in
order to determine the presence of multicol-linearity among independent
variables in this study. These methodologies involved calculation of
both a Tolerance test and Variance Inflation Factor (VIF) (Kleinbaum et
al. 1988). The results of these analyses are presented in Table 4. As
can be seen from this data, i) none of the Tolerance levels is < or
equal to 0.01; and ii) all VIF values are well below 10. Thus, the
measures selected for assessing independent variables in this study do
not reach levels indicating multicollinearity. The acceptable
Durbin--Watson range is between 1.5 and 2.5. In this analysis, the
Durbin--Watson value of 1.946, which is within the acceptable range,
shows that there were no auto correlation problems in the data. Thus,
the measures selected for assessing independent variables in this study
do not reach levels that indicate the existence of multicollinearity.
6. Hypotheses Testing
Table 5 presents results of a multiple regression analysis used to
evaluate the strength of the proposed relationship. Six hypotheses were
formulated and all the variables retain after filtering with factor
analysis. The individual hypothesis was tested using a multiple
regression prediction model following the guidelines established by Hair
et al. (1998) with online brand trust as the dependent variable. The
results obtained, as shown in Table 5, revealed that H1, H2, H3, H5, and
H6 were found to be positive and significant in the prediction model.
Effects of perceived risk were tested by H4, which was rejected by this
test. This result indicates that online good experience would not affect
online brand trust. The results provide support for hypotheses H1, H2,
H3, H5, and H6, that is, the relationship between security/privacy
([beta] = 0.126; p < 0.05), perceived risk on online brand trust
([beta] = -0.146; p < 0.05), word-of-mouth on online brand trust
([beta] = 0.208; p < 0.01), quality of information with online brand
trust ([beta] = 0.215; p < 0.01) and brand reputation ([beta] =
0.220; p < 0.001) with online brand trust.
7. Discussion
This study was carried out to investigate the factors that
influence Internet user's online brand trust. The study depicted
that perceived security/privacy has a significant effect on online brand
trust. This result supports the earlier findings by Ha (2004) and
Srinivasan (2004). It is evident that security and privacy have to be
vital components of effective commercial Web sites. In addition to that,
security and privacy are then directly related to trust, which remains a
competitive advantage in the online environment. According to the
results, many of the respondents perceived the Internet to be insecure
and thus they are reluctant to entrust their personal or financial
information to the online retailers. Although there are some who do not
worry about their privacy being invaded but online retailers must
instill brand trust in order to banish the sense of insecurity among the
consumers.
From the results of this study, perceived risk has a significant
and negative effect on online brand trust. This means that the lower the
perceived risk the higher the level of brand trust the consumer will
have. This result is in line with previous studies done by other
researchers (Ha 2004; Jarvenpaa et al. 1999; Hoffman et al. 1999). This
might be the reason why the results are significant. When the
respondents do have actual experience in purchasing service online,
their perception will tend to be different from those who actually had
experiences before.
It is also interesting to note that the respondents in this study
feel that their monetary loss resulting from purchasing online is high.
They also expect that the Web site would fail to perform their service
after they purchased it. Their confidence on Web sites is not relatively
high. This might be due to the fact that most of the respondents are
working people who do not go online regularly and the Internet seems
like an unfamiliar channel for them. In fact most of them think it is
risky to buy from the websites.
The study also confirmed that word-of-mouth has a significant
affect on level of brand trust. The relationship is a positive
relationship which means the better the word-of-mouth the higher the
level of brand trust the consumer has. The results are similar to those
in the literature and word-of-mouth does indeed prove to be a powerful
marketing tool. In this study, the respondents agree that information
about brands online given by their friends and relatives are
trustworthy. Recommendation by friends and relatives also prove to be
effective in promoting brand trust. At the end of the day, it all comes
down to the trust that the respondents have in their friends and
relatives. When we think of trust information in the real world instead
of online, word-of-mouth information is considered to be very important.
Word of mouth is probably the most powerful form of communication in the
business world. It can either hurt a company's reputation or make
it.
From the results of this study, it is found that good online
experience has no direct and significant effect on online brand trust.
This result contradicts with those of previous studies done by other
researchers studies like those carried out by Salo and Karjaluoto
(2007); Ha (2004); Srinivasan (2004); Venkatesh et al. (2002) have
generally shown that good online experience has a positive and
significant influence on the level of brand trust online. This
contradicting result might be due to the fact that not many of the
respondents actually shop online. They do not see it as a factor that
will affect online brand trust because they do not have good experience.
Most of the items under this factor indicate expectation of failure of
service when they purchase the service from the airline website. This
might be the reason why the results are contradictory. When the
respondents do not have much experience in purchasing service online,
their perception will tend to be different from those who actually have
much prior experience. However, the positive sign of the beta shown in
the regression results indicates that if there is a relationship it will
be a positive one. This means that the higher the good experience online
the higher the level of brand trust the consumer will have and vice
versa.
The acceptance of both H5 (quality information) and H6 (brand
reputation) is in agreement with a wide range of previous findings (Ha
2004; Venkatesh et al. 2002; Lee and Turban 2001; Sultan et al. 2002;
Andaleeb 1992; Doney and Cannon 1997). The study result indicating that
quality information and brand reputation have a positive effect upon
level of online brand trust. All of the previous studies suggest that
the better the quality of information a web site provides, the higher
the level of brand trust the consumer has. Similarly the results also
show a positive relationship between brand reputation and level of
online brand trust, which means a better brand reputation, will lead to
a higher level of brand trust. Hence, brands must be very careful to
maintain their good reputation at their sites in order to sustain brand
trust and create customer loyalty.
8. Limitations and Future Research Directions
We recognize that our study has two main limitations. First, this
study was conducted with working people only and may not reflect the
views of other non-working people in Malaysia. Thus, in order to reveal
behavioural differences, it would be interesting to repeat study in
different groups such as non-working people. Secondly, this study only
covers Klang Valley in Malaysia only with relatively small sample size.
Thus, the respondent might not reflect the whole scenario in Malaysia.
We would suggest strengthening by increasing the sample size and
including participants in other geographical areas. Furthermore, no
studies have been made on online brand trust in Malaysia, thus, there
are no proven examples that can be followed or referred. This limitation
also leads the researchers to face difficulty when collecting extra
information that can give a support to the current studies. Therefore,
the researchers have to study the previous researches, which more
focused on developed country as well and come out with new framework of
the research. Finally, potential correlations between some of the
independent variables (e.g. gender, race, working experiences,
educational level) need to be reported in a future study.
9. Conclusion
The purpose of this study is to investigate factors affecting on
online brand trust in the working people of Klang Valley in Malaysia.
This study also contributes to and extends our understanding of the
Internet as a medium for commercial use in the service arena,
identifying the rationales for trust on online purchasing. From a
managerial viewpoint, the findings provide support for investment
decisions, and for decisions relating to the development of Internet
services that address and take the concerns and needs of companies into
consideration.
The research was done under theoretical framework developed based
on the previous study. The multiple regression analysis shows that
security/privacy, perceived risk, word-of-mouth, quality of information
and brand reputation are significant elements affecting online brand
trust in the airline industry in Malaysia. The model explains 53 per
cent of the variance in online brand trust.
This information is particular helpful for online retailers who
have yet to convert non-loyal consumers to loyal consumers of their
brands. Until then, experiences and stories of online shopping failures
will continue to put off some potential consumers from purchasing the
brand online. Trust is also very crucial in order to compete among
business organizations in today's global business world.
Finally, understanding consumers' perception on brand trust
online is not an easy task and will always create challenges to most
online retailers. Online retailers should develop effective plans and
strategies by taking into account the various factors that were
explained in this study. In order to achieve success, online retailers
must take into account the demographic variables and other factors
related to the Malaysian online consumer market. In short, the online
retailers should have a thorough understanding of the factors
influencing consumers' perception of online brand trust.
doi: 10.3846/jbem.2010.10
Received 30 June 2009, accepted 3 March 2010
References
Alba, J. W.; Hutchinson, W. 1987. Dimensions of consumer expertise,
Journal of Consumer Research 13(4): 411-453. doi:10.1086/209080
Alexander, N.; Colgate, M. 2000. Retail financial services:
transaction to relationship marketing, European Journal of Marketing
34(8): 938-953. doi:10.1108/03090560010331432
Alfansi, L.; Sargeant, A. 2000. Marketing segmentation in the
Indonesian banking sector: the relationship between demographics and
desired customer benefits, International Journal of Bank Marketing
18(2): 64-74. doi:10.1108/02652320010322976
Andaleeb, S. S. 1992. The trust concept: research issues for
channels of distribution, Research in Marketing 11: 1-34.
Breakenridge, D. 2001. Cyberbranding: brand building in the digital
economy. Upper Saddle River: Prentice Hall.
Busacca, B.; Castaldo, S. 2003. Brand knowledge, brand trust and
consumer response: a conceptual framework, in 2nd Workshop "Trust
Within and Between Organizations ", special session "Trust in
Marketing", Amsterdam, 23-24.
Carroll, B. A.; Aaron, A. 2006. Some antecedents and outcomes of
brand love, Marketing Letters 17(2): 79-89.
doi:10.1007/s11002-006-4219-2
Chen, C. 2006. Identifying significant factors influencing consumer
trust in an online travel site, Information Technology and Tourism 8:
197-214. doi:10.3727/109830506778690849
Chlivickas, E.; Smaliukiene, R. 2009. International region as a
brand origin: conceptualization and review, Journal of Business
Economics and Management 10(2): 141-148.
doi:10.3846/16111699.2009.10.141-148
Chua Phaik Harn, A.; Khatibi, A.; Ismail bin, H. 2006. E-commerce:
A study on online shopping in Malaysia, Journal of Social Sciences
13(3): 231-242.
Chaudhuri, A.; Holbrook, M. B. 2001. The chain of effects from
brand trust and brand affect to brand performance: the role of brand
loyalty, Journal of Marketing 65(2): 81-93.
doi:10.1509/jmkg.65.2.81.18255
Corbitt, B. J.; Thanasankit, T.; Yi, H. 2003. Trust and e-commerce:
a study of consumer perceptions, Electronic Commerce Research and
Applications 2(3): 203-215. doi:10.1016/S1567-4223(03)00024-3
Dayal, S.; Landesberg, H.; Zeisser, M. 1999. How to build trust
online, Marketing Management (fall) 8: 64-69.
Doney, P. M.; Cannon, J. P. 1997. An examination of the nature of
trust in buyer-seller relationships, Journal of Marketing 61(2): 35-51.
doi:10.2307/1251829
Economist Intelligence Unit 2006. Overview of e-commerce in
Malaysia [online] [cited 20 April 2008]. Available from Internet:
<http://globaltechforum.eiu.com/index.asp?
layout=printer_friendly&doc_id=8706>.
Fogg, B. J.; Marshall, J.; Laraki, O.; Osipovich, A.; Varma, C.;
Fang, N.; Paul, J.; Rangnekar, A.; Shon, J.; Swani, P.; Treinen, M.
2001. What makes web sites credible? A report on a large quantitative
study, in Proceedings of CHI'01, Human Factors in Computing
Systems, 61-68.
Fullerton, G. 2005. The impact of brand commitment on loyalty to
retail service brands, Canadian Journal of Administrative Sciences
22(2): 97-110.
Ganesan, S. 1994. Determinants of long-term orientation in
buyer-seller relationships, Journal of Marketing 58: 1-19.
doi:10.2307/1252265
Goodwin, N. R. 1996. Economic Meanings of Trust and Responsibility.
The University of Michigan Press, Ann Arbor, MI.
Ha, H. Y. 2004. Factors influencing consumer perceptions of brand
trust online, Journal of Product & Brand Management 13(5): 329-342.
doi:10.1108/10610420410554412
Ha, H. Y.; Perks, H. 2005. Effects of consumer perceptions of brand
experience on the web: Brand familiarity, satisfaction and brand trust,
Journal of Consumer Behavior 4(6): 438-452. doi:10.1002/cb.29
Hair, J. F.; Anderson, R. E.; Tatham, R. L.; Black, W. C. 1995.
Multivariate Data Analysis With Readings. Prentice Hall, Englewood
Cliffs, NJ.
Hair, J. F.; Anderson, R. E.; Tatham, R. L.; Black, W. C. 1998.
Multivariate Data Analysis. 5th ed. California: Prentice-Hall
International Inc.
Hoffman, D.; Novak, T.; Peralta, M. 1999. Building consumer trust
online, Communications of the ACM 42(4): 80-85.
doi:10.1145/299157.299175
Horppu, M.; Kuivalainen, O.; Tarkianen, A.; Ellonen, H. K. 2008.
Online satisfaction, trust and loyalty, and the impact of the offline
parent brand, Journal of Product & Brand Management 17(6): 403-413.
doi:10.1108/10610420810904149
Jarvenpaa, S. L.; Tractinsky, N.; Saarinen, L. 1999. Consumer trust
in an internet store: a crosscultural validation, Journal of
Computer-Mediated Communication 5(2): 59-88.
Keller, K. L. 1998. Strategic Brand Management: Building,
Measuring, and Managing Brand Equity. Upper Saddle River, New Jersey:
Prentice Hall.
Kleinbaum, D. G.; Kupper, L. L.; Muller, K. E. 1988. Applied
Regression Analysis and Other Multivariate Methods. Boston: PWS.
Larzelere, R.; Huston, T. L. 1980. The dyadic trust scale: toward
understanding interpersonal trust in close relationships, Journal of
Marriage and Family (August): 595-604. doi:10.2307/351903
Lee, M. K. O.; Turban, E. 2001. A Trust model for consumer internet
shopping, International Journal of Electronic Commerce 6(1): 75-91.
Malhotra, N. 1999. Marketing Research: An Applied Orientation.
Prentice-Hall, Sydney.
Maiksteniene, K.; Auruskeviciene, V. 2008. Manufacturer and
retailer brand acceptance under different levels of purchase
involvement, Inzinerine Ekonomika--Engineering Economics (1): 90-96.
McAlexander, J. H.; John, W. S.; Harold, F. K. 2002. Building brand
community, Journal ofMarketing 66(1): 38-54.
doi:10.1509/jmkg.66.1.38.18451
Morgan, R. M.; Hunt, S. D. 1994. The commitment-trust theory of
relationship marketing, Journal of Marketing 58: 20-38.
doi:10.2307/1252308
Parasuraman, A.; Zeithaml, V. A.; Berry, L. L. 1988. A multi-item
scale for measuring consumer perceptions of service quality, Journal of
Retailing 64: 12-40.
Papadopoulou, P.; Kanellis, P.; Martakos, D. 2001. Investigating
trust in e-commerce: a literature review and a modelfor its formation in
customer relationship, in Proceedings of the 7th Americas Conference on
Information System, 3-5 August, Boston.
Quelch, J. A.; Klein, L. R. 1996. The internet and international
marketing, Sloan Management Review 37(3): 60-75.
Reast, J. D. 2005. Brand trust and brand extension acceptance: the
relationship, Journal of Product & Brand Management 14(1): 4-13.
doi:10.1108/10610420510583707
Reichheld, F.; Schefter, P. 2000. E-loyalty: your secret weapon on
the web, Harvard Business Review: 105-114.
Rubin, M. R. 1995. Private Rights, Public Wrongs: The Computer and
Personal Privacy. John Wiley and Sons, New York, NY.
Salisbury, W. D.; Pearson, R. A.; Pearson, A. W.; Miller, D. W.
2001. Perceived security and World Wide Web purchase intention,
Industrial Management & Data Systems 101(4): 165-177.
doi:10.1108/02635570110390071
Salo, J.; Karjaluoto, H. 2007. A conceptual model of trust in the
online environment, Online Information Review 31(5): 604-621.
doi:10.1108/14684520710832324
Schurr, P. H.; Ozanne, J. L.1985. Influences on exchange processes:
buyers' preconceptions of a seller's trustworthiness and
bargaining toughness, Journal of Consumer Research 11: 939-953.
doi:10.1086/209028
Selnes, F. 1993. An examination of the product performance on brand
reputation, satisfaction and loyalty, European Journal of Marketing
27(9): 19-35. doi:10.1108/03090569310043179
Shankar, V.; Sultan, F.; Urban, G. L.; Bart, I. 2002. The Role of
Trust in Online Customer Support. Working Paper, Sloan School of
Management, MIT, Cambridge, MA 02142.
Shim, S.; Eastlick, M. A.; Lotz, S. L.; Warrington, P. 2001. An
online prepurchase intentions model: The role of intention to
search--The Sixth Triennial AMS/ACRA Retailing Conference, 2000, Journal
of Retailing 77(3): 397-416. doi:10.1016/S0022-4359(01)00051-3
Srinivasan, S. 2004. Role of trust in e-business success,
Information Management & Computer Security 12(1): 66-72.
doi:10.1108/09685220410518838
Sultan, F.; Urban, G. L.; Shankar, V. and Bart, I. Y. 2002.
Determinants and role of trust in ebusiness: A large scale empirical
study, MIT Sloan Working Paper, 4282-02 [online], [Cited 27 November
2007]. Available from Internet: <http://papers.ssrn.com/sol3/
papers.cfm?abstract_id=380404#paperdownload>.
Thomson, M.; McInnis, D. J.; Park, C. W. 2005. The Thies that bind:
measuring the strength of consumer's emotional attachments to
brands, Journal of Consumer Psychology 15(1): 77-91.
doi:10.1207/s15327663jcp1501_10
Venkatesh, V.; Speier, C.; Morris, M. G. 2002. User acceptance
enablers in individual decision making about technology: toward an
integrated model, Decision Sciences 33(2): 297-316.
doi:10.1111/j.1540-5915.2002.tb01646.x
Xiling, Z.; Xiangchun, L. 2005. Effective User Interface Design for
Consumer Trust: Two Case Studies. Unpublished MSc thesis, Lulea
University of Technology, Department of Business Administration and
Social Sciences [online], [cited 19 November 2007]. Available from
Internet: <http://epubl.ltu.se/1404-5508/2005/097/
LTU-SHU-EX-05097-SE.pdf.>.
Yague-Guillen, M. J.; Munuera-Aleman, J. L.; Delgado-Ballester, E.
2003. Development and validation of a brand trust scale, International
Journal of Market Research 45(1): 35-54.
Zucker, L. G. 1986. Production of trust: Institutional sources of
economic structure, 1840-1920, Research in Organizational Behavior 8:
53-111.
Syed Shah Alam (1), Norjaya Mohd. Yasin (2)
(1) Faculty of Economics and Business, Universiti Kebangsaan
Malaysia, 43600 UKM Bangi, Selangor, Malaysia (2) Graduate School of
Business, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor,
Malaysia E-mails: (1)
[email protected] (corresponding author);
[email protected]
Syed Shah ALAM is a senior lecturer at the Faculty of Economics and
Business, Universiti Kebangsaan Malaysia (National University of
Malaysia). Prior to joining to the National University of Malaysia in
June 2009, he also served as a full-time lecturer at Universiti
Teknologi MARA (UiTM) Malaysia. Before, moving to Universiti Teknologi
MARA in January 2007, he was working as a lecturer at Multimedia
University Malaysia. He also served there as a coordinator of
postgraduate program at the same time. He has authored a few books on
E-Commerce, Internet marketing and more than 30 academic and
professional articles in the reputed journals and international
conferences. His research work involves the development of E-commerce in
the business field. He has been awarded the Joint Conference of
e-Commerce, e-Administration, e-Society, and e-Education best paper
award in 2008. His future research will focus on Internet marketing,
E-commerce, mobile Ecommerce, Internet and Mobile advertisement,
Internet Banking and mobile banking.
Norjaya Mohd. YASIN is an Associate Professor at the Graduate
School of Business, Universiti Kebangsaan Malaysia (National University
of Malaysia). Her research interests include issues related to consumer
behavior, marketing management and branding, and she has been involved
in a variety of academic projects and consultancy in this regard.
Table 1. Demographic background of the respondent
Frequency Per cent
Gender
Male 80 38.3
Female 129 61.7
Age group (years)
24 years and below 37 17.7
25-34 114 54.5
35-44 45 21.5
45-54 10 4.8
55 years and above 3 1.4
Race
Malay 72 34.46
Chinese 106 50.72
Indian 28 13.39
Others 3 1.43
Educational level
Diploma and below 72 34.5
Undergraduate 127 60.7
Master Degree and Ph.D. 9 4.3
Others 1 0.5
Table 2. Reliability Analysis
Variables No. of Items Coefficient
Alpha
Online Brand Trust 5 0.799
Security/privacy 6 0.816
Perceived Risk 3 0.771
Word-of-mouth 4 0.887
Good online experience 3 0.741
Quality of information 3 0.773
Brand reputation 3 0.834
Table 3. Factor Analysis showing the combined impacts of the
independent variables
Conditions Factors/variables Factors
1 2 3
Security/privacy Security 1 0.691
Security 2 0.813
Security 3 0.730
Security 4 0.633
Security 5 0.626
Security 6 0.407
Security 7 0.299
Risk Risk 1
Risk 2
Risk 3
Risk 4
Word-of-mouth WOM 1 0.838
WOM 2 0.833
WOM 3 0.841
WOM 4 0.727
Online experience Online experience 1
Online experience 2
Online experience 3
Quality Quality of Info 1 0.786
information Quality of Info 2 0.737
Quality of Info 3 0.528
Conditions Factors/variables Factors
4 5 6
Security/privacy Security 1
Security 2
Security 3
Security 4
Security 5
Security 6
Security 7 0.687
Risk Risk 1 0.489
Risk 2 0.837
Risk 3 0.833
Risk 4
Word-of-mouth WOM 1
WOM 2
WOM 3
WOM 4
Online experience Online experience 1 0.561
Online experience 2 0.461
Online experience 3 0.646
Quality Quality of Info 1
information Quality of Info 2
Quality of Info 3
Table 4. Test of Collinearity
Variable Tolerance VIF
Security/privacy 0.663 1.509
Perceived Risk 0.543 1.842
Word-of-mouth 0.628 1.592
Good online experience 0.700 1.428
Quality of information 0.569 1.759
Brand reputation 0.580 1.723
Table 5. Regression Results
Variables Beta t-value p-value
Security/privacy 0.126 2.172 0.031
Perceived Risk -0.146 2.289 0.023
Word-of-mouth 0.208 3.510 0.001
Good online experience 0.079 1.399 0.163
Quality of information 0.215 3.447 0.001
Brand reputation 0.220 3.568 0.000
Dependent Variable: Online Brand Trust
