American Journal of Industrial and Business Management, 2013, 3, 674-680
Published Online December 2013 (http://www.scirp.org/journal/ajibm)
http://dx.doi.org/10.4236/ajibm.2013.38076
Open Access AJIBM
Factors Affecting Brand Identification and Loyalty in
Online Community
Chieh-Min Chou
Graduate Institute of Management of Technology, Feng Chia University, Taichung, Taiwan.
Email: cmchou.fcu@gmail.com
Received October 22nd, 2013; revised November 22nd, 2013; accepted November 29th, 2013
Copyright © 2013 Chieh-Min Chou. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accor-
dance of the Creative Commons Attribution License all Copyrights © 2013 are reserved for SCIRP and the owner of the intellectual
property Chieh-Min Chou. All Copyright © 2013 are guarded by law and by SCIRP as a guardian.
ABSTRACT
This study explores the factors of online community characteristics which affect customer loyalty through the mediate
effects of brand identification. By employing online questionnaire survey, hundreds of observations were collected from
online brand co mmun ities in Taiwan for hypothetical model test. Research results sho w that brand loyalty is positively
affected by stronger online brand id entificatio n wh ich is enhanced by onlin e commun ity interactiv ity, satisfied custo mer
relationship and platform quality. Based on the findings, th is study sugg ests that online brand manag ers should focus on
providing a rich interactive community environment for establishing satisfied customer relationship on a high quality
platform to enhance brand identificatio n thereby to earn customer’s brand loyalty.
Keywords: Online Commun ity; Brand Identification; Brand Loyalty
1. Introduction
The development of the Internet re-shapes the communi-
cation methods among people and companies. Before the
World Wide Web appeared, consumers made purchase
decision with information provided by television or radio
advertising, outdoor billboards or word-of-mouth. Inter-
net technologies enable companies to easily establish offi-
cial website to provide consumers with product informa-
tion in 24 × 7 manners. Although it broke the time and
geographical limitations to approach consumers, the
communication is still a one-way type. Until the web2.0
technologies are emerging, the interactive and collabora-
tive online environment promotes many online commu-
nities established for information exchange and relation-
ship building. Clever companies quickly found the po-
tential and advantages of using online community to
strengthen customer relationship and brand identification
in order to enhance loyalty.
By analyzing the online brand community member
behavior, this study observed consumers having different
perception on community characteristics while interact-
ing with company and other members, and that influences
the generation of identity, shared value and relationship.
Companies now are facing a fuzzy industry demarca-
tion and intense competition, which makes brand estab-
lishment become a necessity to maintain competitiven ess.
Two Taiwanese global PC manufacturers, ASUS and
ACER for example, started to establish online commu-
nity to strengthen brand identification and cultivate loy-
alty customers for improving profit structure. Brand eq-
uity is an invisible asset that increases the supply value
of product or service, and this value belongs to compa-
nies and customers [1]. Nowadays many companies at-
tempt to increase the brand value by excellent brand
management practice which was realized on efficient and
effective online community platform. It is a new phe-
nomenon to set up online brand communities to promote
and advertise products or services based on brand identi-
fication [2]. Many companies use online brand commu-
nity to promote brand awareness and deliver brand,
product and service information. In addition, the compa-
nies which establish long-term relationship with custom-
ers not only increase brand comprehension of potential
customers, but also cultivate loyalty customers in this
relationship process. For brand managers, it is a chal-
lenge to successfully deliver brand identity, impression
and invisible value to customers for earning brand loy-
Factors Affecting Brand Identification and Loyalty in Online Community 675
alty in online brand community. Hence, the purpose of
this paper is to explore the factors of online community
characteristics which affect customer loyalty through the
mediate effects of brand identification.
2. Theoretical Background
2.1. Online Community
People assemble together because of having common
topic, interest or idea in human society. With Internet
emergence, people interaction and contact have become
tendency gradu ally in the online communiti es. Rheingold
[3] defines online communities as Internet social aggre-
gate in earliest period. A group of people who have emo-
tional interaction and information exchange with each
other will develop an interpersonal relationship network,
and then online community is beginning to take shape.
Many scholars proposed the different definitions of
online community. Armstrong and Hagel [4] defined that
online community gathers people and let them trust each
other from interaction continually. The human commu-
nication and information sharing by Internet and elec-
tronic media is a burgeoning society phenomenon [5].
When Internet users having common interest of emotion,
they will exchange information and establish interper-
sonal relationship through participating discussion [6,7].
After interpersonal relationship being built, the people
have common willing are formin g Internet virtu al society
organization based on obligation and common objective
[8]. Community members communicate with each other
for obtainment common opinion, sharing common value,
and developing continual relationship [9]. Armstrong and
Hagel [4] proposed virtual community resources should
include brand, customer relationship and content.
2.2. Online Brand Community
The online br and community is society-oriented that was
derived from trade-oriented or economic-oriented com-
munity [9]. In community members exchange informa-
tion, sharing product knowledge and supply problem
solutions [6,10]. The online brand community comprises
a group of people with brand knowledge and has no geo-
graphical limitations in the structure form [11]. More and
more companies believe that online brand community
providing great opportunities to communicate with cus-
tomers, and access benefits of valuable ideas [12].
Online brand community can be categorized as two
types, 1) consumer-initiated communities which are vol-
untarily built by their member s and 2) company-initiated
communities which are built by the company that owns
the brand in order to establish a relationship with con-
sumers and induce productive feedback from them [12].
The hosting type may be one of the most important fac-
tors in classifying online communities because it results
in different operating mechanisms [2,13]. In this paper,
the company-initiated online brand communities which
established by the companies to gather potential custom-
ers and building long-term relationship with existing
customers were studied.
There are many different perspectives of the online
brand community characteristic in literature. Lee and
Kim [14] claimed that online brand community charac-
teristic including information quality, service quality,
rewards and member interaction. Jang et al. [12] believed
that online brand community characteristic contains in-
formation quality, system quality, interaction, and re-
wards.
2.3. Brand Identification
Drawn from social identity theory, identification is es-
sentially a perception of oneness with a group of people
or an organization. To extend the concept, brand identi-
fication can be described as a person who perceives the
degree to which one defines oneself by the same attrib-
utes held by the brand. Not all identifications invo lve the
contractual parts of organizations, although they could be
important drivers of member’s behavior [15]. Good
reputation can positively influence consumer’s brand
identification because individuals usually cognitively
identify themselves with a winner. Corporate communi-
cation such as to provide customers with relevant infor-
mation is another way to enhance identification [16].
Satisfied customer relationship can generate emotional
and cognitive response to brand identification [17]. Con-
sumers that have better relationship with brand-company
and are satisfied with its products and services will be
more likely to posit positive brand identification.
This study focused on online brand community char-
acteristics which are possible to influence brand identifi-
cation. Based on the literature review, this study con-
cluded information quality, system quality, interactivity
as focal factors and incorporate information quality and
system quality into a generalized construct platform
quality. This research also inclu des customer relationship
which is antecedent of brand identification as one of fo-
cal factors to further understand the correlation in online
context.
2.4. Interactivity
Either in real world or in cyberspace, the community
members always interact with each other to deepen rela-
tionship and interchange message which significantly
increase information flow [18]. Interactivity consists of
man-machine interaction and inter-person interaction.
The man-machine interaction refers to the users interact
with the website or other information systems, and the
Open Access AJIBM
Factors Affecting Brand Identification and Loyalty in Online Community
676
inter-person interaction is user-centered that people in-
teract with other users in cyberspace.
When interaction between information dispatcher and
receiver is going frequently, the virtual community is
deemed a society space, and the participants can gain the
emotional support and information exchange [19]. The
interaction between website and customers will influence
customer loyalty in the virtual world [18,20]. If compa-
nies want to increase customer satisfaction and develop-
ing long-term relationship, they can regard website as
communication channel that people contact directly.
However, the website must have the mechanism of con-
versation and feedback. The more frequent interactivity
of websites or communities offer, the higher trust and
commitment of users will be built [21]. In the research of
interactivity, Cooley [22] found that interactivity charac-
teristic of website can increase interaction with custom-
ers and bring four advantages: benefit of company image,
easy public opinion collectio n, customer desire reflection
and enhancement company responsibility. Based on
above perspective, the interactivity of online community
can positively influence members’ perception on brand
prestige and understandings of corporate communication,
hence to affect brand identification.
H1: Online community interactivity positively influ-
ence brand identification.
2.5. Platform Quality
Online brand community members search and share in-
formation through Internet application systems. To pro-
vide excellent use experience, it is necessary to ensure
the high information quality and system stability. Huiz-
ingh [23] pointed out that website information quality
can be assessed by content and website design. Delone
and Mclean [24] proposed information system success
model that expect system quality and information quality
will influence the user satisfaction. Sakaguchi and Frol-
ick [25] pointed out high quality system quality should
have integration function to integrate different informa-
tion sources and satisfy user from different units. The
user satisfaction is influenced by information system
quality hence the platform should not only provide reli-
able information but update information to satisfy users
[26].
Liu and Arnett [27] claimed high information quality
can make user feel satisfaction. And the information of
website can help customers reduce groping time and en-
hancement the value of information. Park and Kim [28]
discovered information quality positively influencing
relationship benefits. Customers’ perception of online
brand community p latform quality will associate with the
perceived reputation of brand, therefore the platform
quality will also influence brand identification.
H2: Online community platform quality positively
influence brand identification.
2.6. Customer Relationship
Evan and Laskin [29] defined the customer relationship
is customer-centric that company tends to main tain long-
term business relationships with customers. Satisfied
customer relationship brings lots of positive benefits to
company such as higher profitability, customer loyalty,
brand identification and more efficient business planning
[30]. Customer relationship management is a philosophy
of customer-oriented management that continually cre-
ates satisfied customers and maintains actively p rofitable
long-term relationship.
In real world environment, customers can contact with
company by face-to-face. But in virtual world, the online
community has not geographical limitations and time
limitations because customers can interact with company
through Internet. Ryan [31] pointed out that the users
satisfied obtainment of interpersonal relationship when
participate in the virtual community which means online
community provides interpersonal characteristics that
user will feel satisfaction. Piskorski [32] pointed ou t that
a successful community strategy should be able to help
establishment of customer relationships. When compa-
nies began to build online brand communities, they not
only concerned about the relationship between customer
and company but among customers that strengthen the
relationship between customers and products or services.
McAlexander et al. [33] proposed the concept of cus-
tomer-centric brand community model which identified
customer-product relationship, customer-brand relation-
ship, customer-company relationship and customer-cus-
tomer relationship. If customers and community establish
higher degree of relationship, they will participate in the
brand community easily and generate brand loyalty.
These satisfied relationships will affect customer’s iden-
tification of brand. Therefore this study posits a hypothe-
sis:
H3: Satisfied online community relationship posi-
tively influence brand identification.
2.7. Brand Loyalty
Brand loyalty means the customers are will to promote a
company’s products or services proactively and exhibit
some loyal behaviors [34]. Brand loyalty can reduce
marketing costs and strengthen the relationship between
distributors and themselves that reduce threat of com-
petitors. Literature indicates that a loyal customer will
purchase more products and services and recommend
them to others. Customers identifying with a brand
community tend to be supportive and positively recom-
mend the brand as well. Hence,
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Factors Affecting Brand Identification and Loyalty in Online Community 677
H4: Online community brand identification positively
influence bran d loyal t y .
In addition, because satisfied online customer rela-
tionship was argued having positive impacts on brand
loyalty by previous studies, this study also posit a hy-
pothesis on the direct effect from satisfied customer rela-
tionship and brand loyalty.
H5: Satisfied customer relationship positively influ-
ence brand loyalty.
The hypothesis research model is shown in Figure 1.
3. Research Method and Data Analysis
In order to test the research hypotheses, this study used
an online survey method to collect data from an online
sport community in Taiwan. The on line sport community
has more than four thousand active members, and this
study sampled 500 members randomly from the full list.
This research measured online brand community partici-
pants’ perception on online community interactivity, sat-
isfied customer relationship, platform quality, brand
identification and brand loyalty in order to examine the
influence paths. The respondents of this study all have
experience of using online brand community. Total 281
filled questionnaires return ed and 33 questionnaires were
discarded because of a lack of integrity in some of the
answers, which gives a final sample size of 248 observa-
tions for the data analysis. The sample profile is shown in
Table 1.
3.1. Reliability and Validity Analysis
For instrument validation, a confirmatory factor analysis
was performed to assess convergent and discriminate
validity. The factor loadings of all measurement items
ranged from 0.71 to 0.84, which indicates that conver-
gent validity is moderately acceptable (the details of the
validation information are given in Table 2). This study
also assessed construct reliability by calculating compos-
ite reliability to respective latent variables as suggested
by Segars [35]. The estimates of composite reliability of
latent variables ranged from 0.76 to 0.91, significantly
higher than the th reshold of 0.7 suggested by Jör eskog &
Sörbom [36]. The Cronbach’s α of all the latent variables
Figure 1. Conceptual framework.
Table 1. Demographic statistic.
Attributes Values Frequency Percentage
Male 117 47.18
Gender Female 131 52.82
Under 20 22 8.87
21 - 30 119 47.98
31 - 40 96 38.71
Age
Over 40 11 4.44
High school or
below 26 10.48
University 123 49.60
Education
Graduate school 99 39.92
Under one month 29 11.69
1 - 3 months 43 17.34
4 - 6 months 51 20.56
7 - 12 months 44 17.74
13 - 24 months 41 16.53
Time of participating
the online brand
community
Over 25 months 40 16.13
Note: The number of respondents = 248.
Table 2. Factor loadings and cross-loadings.
Scale Items ITA PFQ SCR BI BL
ita1 0.84 0.58 0.42 0.35 0.35
ita2 0.76 0.35 0.41 0.25 0.26
ita3 0.73 0.41 0.38 0.30 0.28
pfq1 0.27 0.73 0.41 0.37 0.36
pfq2 0.38 0.79 0.37 0.36 0.30
pfq3 0.53 0.78 0.47 0.40 0.37
scr1 0.43 0.48 0.73 0.40 0.37
scr2 0.37 0.46 0.71 0.44 0.45
scr3 0.34 0.33 0.75 0.45 0.42
bi1 0.25 0.38 0.49 0.81 0.57
bi2 0.35 0.40 0.43 0.79 0.61
bi3 0.28 0.40 0.40 0.78 0.61
bl1 0.31 0.37 0.38 0.55 0.79
bl2 0.23 0.30 0.37 0.56 0.78
bl3 0.32 0.40 0.44 0.61 0.72
Note: ITA: Interactivity; PFQ: Platform Quality; SCR: Satisfied Customer
Relationship; BI: Brand Identi f ication; BL: Brand Loyalty.
exceeded 0.7, which is the threshold suggested by
Sharma [37].
Nevertheless, composite reliability cannot reflect the
extent to which variance is captured by the constructs.
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Factors Affecting Brand Identification and Loyalty in Online Community
678
Therefore, an average variance extracted (AVE) esti-
mate is adopted to acquire this information. Fornell and
Larcker [38] suggested that an acceptable AVE estimate
should be higher than 0.5 for a construct’s measure. In
this study, all AVE estimates, with ranged from 0.54 to
0.61, were above this cut-off value (detailed information
of measurement reliability and validity are shown in Ta-
ble 3).
3.2. Model Fitness Testing
In general, to evaluate the appropriateness of a structural
model actually is to consider the fitness between actual
data and theoretical model. Statistician developed lots of
indices to assess model fitness such as Goodness of Fit
Index (GFI), χ2/df, Adjusted Goodness of Fit Index
(AGFI), Root Mean Square Residual (RMR), Normed Fit
Index (NFI) and Comparative Fit Index (CFI) are com-
mon suggested [39,40]. Therefore, this study calculates
all the indices in Table 4 for evaluation.
3.3. Hypotheses Testing
The study employed the structural equation model (SEM)
method to test the research hypotheses using IBM soft-
Table 3. Correlation matrix, AVE and composite reliability.
Cronbach’s a AVE CR ITA PFQ SCR BIBL
ITA 0.86 0.63 0.81 0.79
PFQ 0.92 0.65 0.85 0.59 0.81
SCR 0.87 0.74 0.76 0.52 0.58 0.86
BI 0.84 0.61 0.91 0.39 0.49 0.59 0.78
BL 0.82 0.71 0.89 0.39 0.47 0.56 0.770.84
Note: Squ are of root of AVE for each construct is shown in the diago nal of
the correlation matrix. ITA: Interactivity; PFQ: Platform Quality; SCR:
Satisfied Customer Relationship; BI: Brand Identification; BL: Brand Loy-
alty.
Table 4. The fitness indices between model and data.
Fitness
Indices Acceptance
Range Result of
model Meet
Requirement
χ2/df <3 2.231 Yes
GFI >0.9 0.915 Yes
AGFI >0.9 0.901 Yes
RMSEA <0.08 0.071 Yes
RMR <0.08 0.035 Yes
NFI >0.9 0.869 No
CFI >0.9 0.922 Yes
Note: χ2/df: Chi-Square Goodness of Fit; GFI: Goodness of Fit Index; AGFI:
Adjusted Goodness of Fit Index; RMSEA: Root Mean Square Error of
Approxima tion; RMR: Root Mean
ware Amos 18. The test results show that satisfied cus-
tomer relationship (SCR) and Interactivity (ITA) signify-
cantly influence a member’s online brand identification
(BI) at the significant level 0.01; online commu nity plat-
form quality (PFQ) influence a member’s online brand
identification (BI) at the significant level 0.05, which
support hypotheses H1, H2 and H3. The R2 of the online
brand identification is 0.388; therefore, the overall online
community factors can explain 38.8% variance of the
online brand community member’s brand identification.
The path from the brand identification to brand loyalty
(BL) is significant with a 0.01 level with a path coeffi-
cient 0.421, hence hypothesis H4 is supported. Online
community satisfied customer relationship (SCR) has
significant positive impact on brand loyalty as well,
which supports the H5. The R2 of brand loyalty is 0.227,
which indicates that onlin e bran d iden tificatio n is a major
mediating factor if a company wants to enhance brand
loyalty in onlin e brand community (the mo del test results
are shown in Figure 2).
4. Discussion
4.1. Theoretical and Managerial Implications
Several theoretical implications can be drawn from these
results. To our knowledge, the relationships between
online community characteristics, brand identification
and brand loyalty have not been discussed in the context
of online communities in pr ior studies. The results of this
study are a starting point for relevant research and estab-
lish basic understandings of consumer behavior in online
brand communities. Furthermore, the mediating effect of
brand identification in this theoretical model is recon-
firmed in this study. This study also expanded on the
model proposed by Kim et al. [9], which only examined
the effects of online community characteristics on com-
mitment. This research integrated prior studies for pro-
posing a new model, the results of which contribute to
our understanding of how to enhance brand loyalty
through online brand community operation and man-
agement.
This study also has implications for practitioners and
business managers. First, establishing an online brand
community is an effective way to enhance a company’s
Figure 2. The model test results.
Open Access AJIBM
Factors Affecting Brand Identification and Loyalty in Online Community 679
brand loyalty as long as brand identification is strength-
ened. Second, to build satisfied customer relationship
will not only increase brand identification but directly
enhance brand loyalty. Third, although with lower influ-
ence coefficient, platform quality is still a significant
factor to brand identification, which implies that online
brand managers should be cautious when deciding which
online platform over where they will set the brand com-
munity up.
4.2. Limitations and Suggestions
This study has certain limitations although steps were
taken during both hypotheses development and data col-
lection. First, despite the fact that this study referred to
previous research for developing a measure scale of con-
structs, some original items were dropped because they
did not pass the convergent validity test. Second, Third,
although the index of broadband penetration in Taiwan
ranks in the top six in the world, which implies that co n-
sumer behaviors in online communities are worth study-
ing, cultural factors were not included in this study, and
should be taken into account when applying the research
results. Given the above limitations, further research
should be cautious when explaining and applying the
research results.
5. Conclusions
Internet and web 2.0 technologies materialize social
network platforms, which allow people to easily establish
identity and share values in virtual brand community.
Through intensive interaction for corporate communica-
tion in cyber space, online brand community members
can build satisfied relationships with the brand, product
and company on a high quality online platform thereby
increasing brand identification. With more and more
companies establishing online brand communities to
strengthen brand identification and brand loyalty, this
study reveals and endorses the positive marketing value
of online brand community management.
This hypothesis model test result exhibits that brand
loyalty is significantly enhanced by stronger online brand
identification, which in turn is strengthened by the fol-
lowing online community characteristics: interactivity,
platform quality and satisfied customer relationship. The
findings of the study, therefore, support all the hypothe-
ses at statistical significant level 0.01 except for the H2 at
significant level 0.05. Satisfied customer relationship has
both positive effects on brand identification and brand
loyalty.
REFERENCES
[1] D. A. Aaker, “The Value of Brand Equity,” Journal of
Business Strategy, Vol. 13, No. 4, 1992, pp. 27-32.
http://dx.doi.org/10.1108/eb039503
[2] A. Muniz and T. C. O’Guinn, “Brand community,” Jour-
nal of Consumer Research, Vol. 27, No. 4, 2001, pp. 412-
432. http://dx.doi.org/10.1086/319618
[3] H. Rheingold, “The Virtual Community: Homesteading
on the Electronic Frontier,” Addison-Wesley, New York,
1993.
[4] A. Armstrong and J. Hagel, “The Real Value of Online
Community,” Harvard Business Review, Vol. 74, No. 5,
1996, pp. 134-141.
[5] C. Romm, N. Plickin and R. Clarke, “Virtual Communi-
ties and Society: Toward an Integrative Three Phase
Model,” International Journal of Information Manage-
ment, Vol. 17, No. 4, 1997, pp. 261-270.
http://dx.doi.org/10.1016/S0268-4012(97)00004-2
[6] R. P. Bagozzi and U. M. Dholkia, “Open Source Software
User Communities: A Study of Participation in Linux
User Group,” Management Science, Vol. 52, No. 7, 2006,
pp. 1099-1115. http://dx.doi.org/10.1287/mnsc.1060.0545
[7] A. M. Chang, P. K. Kannan and A. B. Whinston, “Elec-
tronic Communities as Intermediaries: The Issues and
Economics,” Proceeding of the 32nd Hawaii Interna-
tional Conference on System Sciences, Hawaii, 5-8 Janu-
ary 1999, pp. 1-10.
[8] F. T. Rothaermel and S. Sugiyamanb, “Virtual Internet
Communities and Commercial Success: Individual and
Community-Level Theory Grounded in the Atypical Case
of Ti mezone. com,” Journal of Management, Vol. 27, No.
3, 2001, pp. 297-312.
[9] J. W. Kim, J. Choi, W. Qualls and K. Han, “It Take a
Marketplace Community to Raise Brand Commitment:
The Role of Online Communities,” Journal of Marketing
Management, Vol. 24, No. 3-4, 2008, pp. 409-431.
http://dx.doi.org/10.1362/026725708X306167
[10] A. Muniz and H. J. Schau, “Religiosity in the Abandoned
Apple Newton Brand Community,” Journal of Consumer
Research, Vol. 31, No. 4, 2005, pp. 737-747.
http://dx.doi.org/10.1086/426607
[11] D. H. McKnight, V. Choudhury and C. Kacmar, “The
Impact of Initial Consumer Trust on Intentions Transact
with a Web Site: A Trust Building Mode,” The Journal of
Strategic Information Systems, Vol. 11, No. 3, 2002, pp.
297-323.
http://dx.doi.org/10.1016/S0963-8687(02)00020-3
[12] H. Jang, L. Olfman, I. Ko, J. Koh and K. Kim, “The In-
fluence of Online Brand Community Characteristics on
Community Commitment and Brand Loyalty,” Interna-
tional Journal of Electronic Commerce, Vol. 12, No. 3,
2008, pp. 57-80.
http://dx.doi.org/10.2753/JEC1086-4415120304
[13] L. L. Berry, “Relationship of Services: Growing Interest,
Emerging Perspectives,” Journal of the Academy of Mar-
keting Science, Vol. 23, No. 4, 1995, pp. 236-245.
http://dx.doi.org/10.1177/009207039502300402
[14] J. Y. Lee and Y. G. Kim, “Community Characteristics
Effect Customer Commitment and Loyalty in the Online
Consumer Community,” Proceedings of the Korea Soci-
Open Access AJIBM
Factors Affecting Brand Identification and Loyalty in Online Community
Open Access AJIBM
680
ety of Management Information System Conference, Ko-
rea, 2005, pp. 841-848.
[15] S. Kuenzel and S. V. Halliday, “Investigating Antece-
dents and Consequences of Brand Identification,” Journal
of Product & Brand Management, Vol. 17, No. 5, 1992,
pp. 293-304.
http://dx.doi.org/10.1108/10610420810896059
[16] A. Smidts, A. Pruyn and C. B. M. van Riel, “The Impact
of Employee Communication and Perceived External
Prestige on Organizational Identification,” The Academy
of Management Journal, Vol. 44, No. 5, 2001, pp. 1051-
1062. http://dx.doi.org/10.2307/3069448
[17] D. Arnett, B. German and S. D. Hunt, “The Identity Sali-
ence Model of Relationship Marketing Success: The Case
of Nonprofit Marketing,” Journal of Marketing, Vol. 67,
No. 2, 2003, pp. 89-105.
http://dx.doi.org/10.1509/jmkg.67.2.89.18614
[18] R. T. Watson, S. Akselsen and L. F. Pitt, “Attractors:
Building Mountains in the Flat Landscape of the World
Wide Web,” California Management Review, Vol. 40, No.
2, 1998, pp. 36-43. http://dx.doi.org/10.2307/41165932
[19] G. Burnett, “Information Exchange in Virtual Communi-
ties: A Typology,” Information Research, Vol. 5, No. 4,
2000. http://informationr.net/ir/5-4/paper82.html
[20] J. Deighton, “The Future of Interactive Marketing,” Har-
vard Business Review, Vol. 74, No. 11, 1996, pp. 151-
161.
[21] M. L. Kent, “Does Your Website Attract or repel Cus-
tomers?” Public Relations Quarterly, Vol. 43, No. 4,
1998, pp. 31-33.
[22] T. Cooley, “Interactive Communication-Public Relations
on the Web,” Public Relations Quarterly, Vol. 43, No. 2,
1999, pp. 41.
[23] E. K. R. E. Huizingh, “The Content and Design of Web
Sites: An Empirical Study,” Information & Management,
Vol. 37, No. 3, 2000, pp. 123-134.
http://dx.doi.org/10.1016/S0378-7206(99)00044-0
[24] W. H. Delone and E. R. Mclean, “Information Systems
Success: The Quest for the Dependent Variable,” Infor-
mation System Research, Vol. 3, No. 1, 1992, pp. 60-95.
http://dx.doi.org/10.1287/isre.3.1.60
[25] T. Sakaguchi and M. N. Frolick, “A Review of the Data
Warehousing Literature,” Journal of Data Warehousing,
Vol. 2, No. 1, 1997, pp. 34-54.
[26] R. Y. Wang and D. M. Strong, “Bey ond Accuracy: What
Data Quality Means to Data Consumers,” Journal of
Management Information Systems, Vol. 12, No. 4, 1996,
pp. 5-34.
[27] C. Liu and K. P. Arnett, “Exploring the Factors Associ-
ated with Web Site Success in the Context of Electronic
Commerce,” Information & Management, Vol. 38, No. 1,
2000, pp. 22-34.
http://dx.doi.org/10.1016/S0378-7206(00)00049-5
[28] C. H. Park and Y. G. Kim, “Identifying Key Factors Af-
fecting Consumer Purchase Behavior in an Online Shop-
ping Context,” International Journal of Retail & Distri-
bution Management, Vol. 31, No. 1, 2003, pp. 16-29.
http://dx.doi.org/10.1108/09590550310457818
[29] J. R. Evans and R. L. Laskin, “The Relationship Market-
ing Process: A Conceptualization and Application,” In-
dustrial Marketing Management, Vol. 23, No. 5, 1994, pp.
439-454.
[30] M. Holmlund and S. Kock, “Relationship Marketing: The
Importance of Customer-Perceived Service Quality in
Retail Banking,” Service Industries Journal, Vol. 16, No.
3, 1996, pp. 287-304.
http://dx.doi.org/10.1080/02642069600000029
[31] R. M. Ryan, “Psychological Needs and the Facilitation of
Integrative Processes,” Journal of Personality, Vol. 63,
No. 3, 1995, pp. 397-427.
http://dx.doi.org/10.1111/j.1467-6494.1995.tb00501.x
[32] M. J. Piskorski, “Social Strategies That Work,” Harvard
Business Review, Vol. 89, No. 11, 2011, pp. 117-122.
[33] J. H. McAlexander, J. W. Schouten and H. F. Koening
“Building Brand Community,” Journal of Marketing, Vol.
66, No. 1, 2002, pp. 38-54.
http://dx.doi.org/10.1509/jmkg.66.1.38.18451
[34] S. Kuenzel and S. V. Halliday, “The Chain of Effects
from Reputation and Brand Personality Congruence to
Brand Loyalty: The Role of Brand Identification,” Jour-
nal of Targeting, Measurement and Analysis for Market-
ing, Vol. 18, No. 3-4, 2010, pp. 167-176.
http://dx.doi.org/10.1057/jt.2010.15
[35] A. H. Segars, “Assessing the Unidimensionality of Meas-
urement: A Paradigm and Illustration within the Context
of Information Systems Research,” Omega, Vol. 25, No.
1, 1997, pp. 107-121.
http://dx.doi.org/10.1016/S0305-0483(96)00051-5
[36] K. G. Jo¨reskog and D. So¨rbom, “LISREL 7 User’s Ref-
erence Guide,” Scientific Software, Chicago, 1989.
[37] S. Sharma, “Applied Multivariate Techniques,” John
Wiley & Sons Inc., New York, 1996.
[38] C. Fornell and D. F. Larcker, “Evaluating Structural
Equation Models with Unobservable Variables and
Measurement Error,” Journal of Marketing Research, Vol.
18, No. 1, 1981, pp. 39-51.
http://dx.doi.org/10.2307/3151312
[39] H. T. Chen and T. W. Lin, “How a 3D Tour Itinerary
Promotion Affect Consumers’ Intention to Purchase a
Tour Product?” Information Technology Journal, Vol. 11,
No. 10, 2012, pp. 1357-1368.
http://dx.doi.org/10.3923/itj.2012.1357.1368
[40] J. F. Hair, R. E. Anderson, R. L. Tatham and W. G. Black,
“Multivariate Data Analysis,” Prentice Hall International,
Upper Saddle River, 1998.