Customers’ perceived website service quality and its effects on e-loyalty

Abstract

Purpose: This study aims to examine determinants of perceived website quality and associations among consequences of perceived website quality. Adopting the framework of loyalty development, causal links are investigated among the website quality, customers’ perceived service quality, their satisfaction, return intention and loyalty in the context of the lodging industry. Design/methodology/approach: An online field survey is conducted with internet bookers. A confirmatory factor analysis and a parameter estimate analysis using structural equation modeling are adopted to analyze the data. Findings: The progression of the phases of loyalty proceeds in a linear fashion on a lodging website. Mediation effects of customer satisfaction and return intention are detected. Moderation effects of gender were also detected in the relationships among website service quality and consequences of website service quality. Research limitations/implications: Caution is advised in generalizing findings of this study due to convenience sampling, although findings of the study do confirm results of previously conducted studies. Practical implications: This study provides practical tips for website development for hospitality management to understand the e-loyalty formation process so that appropriate marketing strategies can be established to accommodate the type and degree of individual customer’s loyalty as well as gender-specific expectations from prospective customers. Originality/value: This study demonstrates that customer loyalty formation in both physical and online environments has identical processes in the context of the lodging industry. The male group, compared to the female group, appears to be more sensitive in perceiving the effects of functionality of a lodging website, tends to develop customer satisfaction when perceiving website service quality and inclines to develop customer loyalty when having return intention.

Full text

Customers’ perceived website
service quality and its effects
on e-loyalty
Myunghee Mindy Jeon
Bertolon School of Business, Salem State University, Salem,
Massachusetts, USA, and
Miyoung Jeong
School of Hotel, Restaurant, and Tourism Management,
University of South Carolina, Columbia, South Carolina, USA
Abstract
Purpose –This study aims to examine determinants of perceived website quality and associations among
consequences of perceived website quality. Adopting the framework of loyalty development, causal links are
investigated among the website quality, customers’ perceived service quality, their satisfaction, return
intention and loyalty in the context of the lodging industry.
Design/methodology/approach –An online eld survey is conducted with internet bookers. A
conrmatory factor analysis and a parameter estimate analysis using structural equation modeling are
adopted to analyze the data.
Findings –The progression of the phases of loyalty proceeds in a linear fashion on a lodging website.
Mediation effects of customer satisfaction and return intention are detected. Moderation effects of gender were
also detected in the relationships among website service quality and consequences of website service quality.
Research limitations/implications –Caution is advised in generalizing ndings of this study due to
convenience sampling, although ndings of the study do conrm results of previously conducted studies.
Practical implications –This study provides practical tips for website development for hospitality
management to understand the e-loyalty formation process so that appropriate marketing strategies can be
established to accommodate the type and degree of individual customer’s loyalty as well as gender-specic
expectations from prospective customers.
Originality/value –This study demonstrates that customer loyalty formation in both physical and online
environments has identical processes in the context of the lodging industry. The male group, compared to the
female group, appears to be more sensitive in perceiving the effects of functionality of a lodging website, tends
to develop customer satisfaction when perceiving website service quality and inclines to develop customer
loyalty when having return intention.
Keywords e-loyalty, Customer satisfaction, Lodging websites, Perceived website service quality,
Phases of loyalty
Paper type Research paper
1. Introduction
Skyrocketing growth of online users and online transactions provides clear evidence that the
Internet is now the center of the current commercial environment. The lodging industry has
adopted the Internet as an effective communication channel with its customers (Diaz and
Koutra, 2013;Law et al., 2010). Certainly, for businesses, a website is a useful tool to promote
their products and services to generate revenues from prospective customers (Akincilar and
Dagdeviren, 2014) and retaining them. Considering the competitive environment of the
industry, hotel management aims to design its website to be a dynamic marketing tool and
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0959-6119.htm
IJCHM
29,1
438
Received 9 February 2015
Revised 23 July 2015
28 November 2015
13 March 2016
Accepted 19 June 2016
International Journal of
Contemporary Hospitality
Management
Vol. 29 No. 1, 2017
pp. 438-457
© Emerald Publishing Limited
0959-6119
DOI 10.1108/IJCHM-02-2015-0054

utilize it as a means of inuencing its customers’ decision-making (Herrero and San Martin,
2012). Sustaining an effective website is, therefore, crucial for businesses to both attract and
retain loyal customers (Law et al., 2010). Hotels generate repeat business through loyal
customers, who are committed while less sensitive to price (Bowen and Chen, 2001).
McMullan and Gilmore (2008) argue that loyal customers inuence the hotel’s bottom line
and are key constituents of favorable word of mouth (WOM).
Although studies have attempted to understand the links between customer motivation,
satisfaction and loyalty (Yoon and Uysal, 2005), there is little information about the development
of customer loyalty (Mason et al., 2006;McMullan and Gilmore, 2008). Further, despite numerous
studies on the evaluation of website quality (Bai et al., 2008;Hsu et al., 2012), there is to date no
well-developed model evaluating websites (Ip et al., 2011). Specically, little research has been
performed to assess impacts of website service quality on customers’ perception and the
evolvement of customer loyalty. Thus, integrated studies of the impact of online service quality
on customers’ loyalty are expected (Fassnacht and Koese, 2006).
Consequently, this study attempts to investigate factors that determine website service
quality and examines consequences of those factors within the structured framework of
loyalty development. More specically, this study’s main purposes are as follows:
• to determine the inuence of service quality on customers’ perceptions of a lodging
website;
• to investigate associations between customers’ perceptions of website service quality
and its consequences using Oliver’s (1999) loyalty framework (cognitive–affective–
conative–action phase);
• to contribute to the body of literature in website service quality and e-customer loyalty;
and
• to offer insights into perceived website service quality and customers’ e-loyalty
strategies to hotel management.
2. Literature review
2.1 Website service quality
Customers expect quality service of websites when making online purchases (Law and
Cheung, 2006). This suggests that maintaining quality websites is crucial to retaining
customers and their revisits, which will eventually secure customer loyalty with lodging
websites. Owing to the dramatic growth in the number of Internet users, numerous studies
have discussed website service quality. Specically, many studies have not only examined
functional aspects including information quality, ease of use and accessibility (Baloglu and
Pekcan, 2006;Herrero and San Martin, 2012) but have also attempted to assess relationships
between website service quality, personalized experiences (Chiou et al., 2010;Hu, 2009), and
the reputation of a lodging institution/website (Casalo et al., 2008;Kim and Lee, 2004).
Website service quality has become an important issue for hotel management to attract
online customers these days (Jeong et al., 2003).
2.2 Theoretical background
In an effort to better understand a lodging website’s users’ intentions and actual behaviors,
two theoretical frameworks are used to underpin this study. The theory of reasoned action
(TRA), initially introduced by Ajzen and Fishbein (1980), has been considered a well-dened
framework that effectively explains computer users’ behaviors (Davis, 1989). The
framework for TRA refers to a person’s particular behavior identied by one’s behavioral
intentions (BI). BI appears to be identied by a person’s attitudes (A) and subjective norms
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(SN), which mean the individual’s perceptions that are identied by a person’s beliefs about
the results of his/her behavior. Davis (1989) introduces the technology acceptance model
(TAM) in his study of computer technology adoption based on TRA, using constructs of
usefulness, ease of use, user attitudes, intentions and behaviors.
2.3 Studies of loyalty
Behavioral, attitudinal and composite methods are proper approaches to measure customer
loyalty (Bowen and Chen, 2001). The frequency or volume of purchases indicates mainly
behavioral loyalty, but does not explain customers’ underlying motivation of purchasing
behaviors (Riley et al., 2001). Repeat purchases do not always result from customers’
emotional commitment (Bowen and Chen, 2001). Therefore, using the behavioral
measurement approach alone is difcult to explain the underlying motivations of spuriously
loyal customers’ patronage (Baloglu, 2002;Grifn, 2002). Spuriously loyal customers
demonstrate repeat patronage without emotional attachment, such as current applications of
loyalty programs of hotels or airlines (Shoemaker and Lewis, 1999). An approach of
attitudinal measurement indicates customers’ emotional or psychological attachment to a
product/brand, but does not always result in behavioral outcomes (Riley et al., 2001) such as
frequent purchases. Meanwhile, latently loyal customers are highly related to attitude mode,
although it demonstrates low repeat purchases (Dick and Basu, 1994). While true loyalty is
captured by a one dimensional approach, spurious and latent loyalties are hard to capture by
only one dimension, either the attitudinal or the behavioral approach.
Adopting the attitudinal approach, types of loyalty – true, latent, spurious and low
loyalty – are identied by Dick and Basu (1994).Oliver (1999) proposes the development of
phases of loyalty using cognitive, affective, conative and action phases that become the
framework for studies of loyalty. Johnson et al. (2006) investigate the development of loyalty
in their longitudinal observations and nd that loyalty evolves in a pattern of cognitive–
affective–conative stage. Olson (2002) also nds a strong relationship among the quality
(cognitive), satisfaction (affective) and loyalty (action) in loyalty frameworks.
Some hospitality studies also adopt phases of loyalty, including casino customers’ loyalty
using the framework of quality, trust and loyalty (McCain et al., 2005), the framework of trust and
commitment to measure attitudinal loyalty (Baloglu, 2002) and behavioral outcome (Asatryan
and Oh, 2008). Huang (2015) nds that relationship marketing affects customer gratitude
signicantly, which predicts behavioral loyalty. Bowen and Chen McCanin (2015) discuss the
demographic shift occurring today in the lodging market and suggest development of customer
loyalty models for Millennials. Martinez (2015) explores the relationship among trust,
satisfaction, overall image and loyalty in the green environment context, assessing how green
marketing strategies increase green loyalty in the hospitality industry. Kandampully et al. (2015),
considering the impact of the evolving role of engaged customers, recommend that companies
create emotionally engaged, loyal brand ambassadors.
2.4 Studies of e-loyalty
Adopting three loyalty phases from Oliver’s framework (1999) – cognitive, affective and
conative – Yoo et al. (2015) nd online WOM (eWOM) and e-quality of the website positively affect
purchase decisions that support satisfaction and, in turn, e-loyalty. Wu (2013) investigates
customers’ intentions to complain, based upon the degree of their satisfaction, in the online
shopping environment. Applying the ow theory to booking experiences, researchers (Bilgihan
et al., 2015) investigate e-loyalty in an integrated model using hedonic and utilitarian features,
ow, trust and brand equity in online booking services. Ladhari and Leclerc (2013) examine
gender role in the relationship among e-loyalty, e-satisfaction and e-trust with online nancial
services for customers. Llach et al. (2013) investigate the impact of e-quality on customer loyalty
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in online ticket purchasing in the context of the airline industry. Kim et al. (2011) investigate the
mediation effects of trust and satisfaction on loyalty, using the variables of navigation
functionality, perceived security and transaction costs.
Nonetheless, few studies in e-loyalty have been conducted in the context of lodging websites.
Hence, adopting Oliver’s (1999) four phases of the loyalty framework for the grounding theory,
this study posits that determinants of website quality are considered as key driving factors for
perceived service quality (PSQ), which is a strong predictor for customer satisfaction (CS), return
intention (RI) and customer e-loyalty (CL) toward a lodging website.
3. Dimensions of perceived website service quality
3.1 Functionality
This study considers four aspects to determine the functionality of a lodging website that
affects customers’ perceptions of service quality: usefulness of information, ease of use,
accessibility and website security/privacy.
Usefulness of information is identied with a wide range of adequate information and
comprehensive coverage (Ho and Lee, 2007). Perceived information usefulness for online
customers will lead to customer satisfaction and positive attitudes toward the particular website
(Jeong and Lambert, 2001). Several studies of information quality focus on the content’s relevance
and usefulness, timeliness, adequacy and current and accurate information (Park and Gretzel,
2007;Zeithaml et al., 2002). Adequate, accurate information is considered useful and is extremely
inuential for online customers’ potential buying intentions.
Ease of use refers to users’ beliefs that using a particular system is effortless (Davis, 1989).
To assess perceived ease of use, various factors including website structure, user interface
and easy navigation are adopted (Bevanda et al., 2008;Sanchez-Franco and Roldan, 2005).
Often, navigation is considered as key to determine quality of e-service. According to Madu
and Madu (2002), the perceived ease of use is one of the pivotal components to inuence users
to return to the website. Simplicity and interactivity are also signicant determinants of
usability of websites (Lee et al., 2015).
Accessibility is one of the important technical adequacies that determines website service
quality (Harison and Boonstra, 2009). Users look for availability of website services (Yang
et al., 2005), easily and quickly linked to relevant websites or available resources (Dolatabadi
and Pool, 2013) and capable to accommodate purchase intentions (Jeong and Lambert, 2001).
Website privacy and security issues have been frequently discussed in the current online
environment. Website customers are sensitive to a website’s capacity to be trustworthy for
users when making transactions online (Zeithaml et al., 2002) because websites often store
customers’ personal information to allow better service at their repeat visits. Websites
should secure the safety of customers’ transactions and their private information of payment
methods because their purchases occur online with no physical exchange of money (Liao
et al., 2006;Pizam, 2013). Therefore, the following hypothesis has been derived:
H1. Functionality of a website inuences a lodging website customer’s PSQ.
3.2 Customer experience
Customers also expect fun and enjoyment while surng on a website. Perceived customer
experiential value leads to customers’ satisfaction (Shobeiri et al., 2013). Customer experience
involves cognitive, physiological and emotional reactions (Bitner, 1992) in the service
environment (servicescape). According to Mattila and Wirtz (2001), the service environment
may cause customers’ emotional reactions and directly inuence their attitudes and
behavior. This study assumes that customer experiential aspects are derived from their
emotional reactions when experiencing a website’s aesthetics and customization elements.
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Customers are more satised if they nd the ambiance to be aesthetic, whether or not it is
physical or online environment (Vilnai-Yavets and Rafaeli, 2006). The aesthetics and design
aspects of websites signicantly affect their appearance (Sanchez-Franco and Roldan, 2005),
which, in turn, inuences users’ emotional reactions. Kuo et al. (2015) nd misleading hotel
website photos create lower brand trust for an upscale hotel. Thus, aesthetically designed
websites make customers linger longer and surf more, which eventually increases the
chances for online purchases.
Customized website service enhances customers’ perceptions of a website’s service
quality (Chang and Chen, 2007;Srinivasan et al., 2002), letting customers spend less time and
feel convenient (Loiacono et al., 2007;O’Cass and Carlson, 2010), which encourages
customers to revisit (Chang and Chen, 2007). The customization feature is an important
ingredient for success on travel websites along with the playfulness feature (Nusair and
Kandampully, 2008). Customization of a website is a useful tool for businesses because
information gathered by the website administrator is saved and utilized by customers at
their next visits. It is important that lodging websites are capable of providing customized
services to fulll customers’ desires. Thus, this study posits the following:
H2. Customer experiential aspects inuence a lodging website customer’s PSQ.
3.3 Reputation of a brick and click hotel
Reputation entails a global perspective associated with the credibility of a certain
organization that is seen as representing the entire company as well as its website (Casalo
et al., 2008). Kim and Lee (2004) nd in their study that reputation affects customers’
perceived website service quality. It is generally believed that customers consider a
company’s reputation before making a purchase decision (Zeithaml, 2000), which establishes
customers’ trust, leading to their intentions to purchase online (Ha and Stoel, 2009). As Kim
and Lennon (2013) discuss, companies establish their reputation typically through media
exposure, branding, customer WOM or eWOM that is transforming the way companies earn
a reputation today via social networking sites (Facebook, Twitter, BizRate.com and blogs).
Therefore, this study considers reputation as a whole for a lodging company resulting from
WOM, eWOM or brand recognition through media advertisements and individual
customers’ past experience.
WOM in ofine or online communities is considered as social inuence (Liu, 2006). eWOM
is typically viewed by prospective customers to be reliable information sources (Herrero
et al., 2015) in the virtual community (Shih and Huang, 2014). Lately, consumer generated
media have gained a reputation as a powerful tool in sharing eWOM (Jeong and Jeon, 2008).
More specically, eWOM typically does not take the form of oral communication because
customers write their reviews online that do not vanish immediately (Marui and Minazzi,
2013) and are read by millions (Libai et al., 2010). Kim et al. (2015) nd signicant drivers of
eWOM intentions from self-construal value, while service qualities positively inuence
opinion leaders’ eWOM intention. Online reviews often signicantly inuence prospective
customers’ purchasing travel services (Nielsen Consumer Report, 2010).
Lodging companies strive to establish their brand recognition through multiple avenues,
including media exposure. Many international branded hotels or franchises advertise on TV
or travel magazines these days (i.e. Residence Inn, Sheraton). Advertisements are helpful in
building customers’ awareness and company recognition (Aaker, 1991). Brand awareness
and recognition built through repeated advertisements and positive publicity inuence
perceptions of customers of a lodging website’s service quality (Brown and Stayman, 1992).
For instance, TV commercials for luxury hotel brands and positive news about hotels will
establish positive perceptions, enabling customers to enjoy visiting such lodging websites.
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In the study of online and social-media empowered hospitality recruitment, Ladkin and
Buhalis (2016) suggest employers consider enhancing website attributes, fairness issues in
the recruitment process and brand reputation.
Customers’ positive impressions are derived from their positive past experiences with a
website. When customers have pleasant experience with a lodging website, they will tend to
return to the website. Perception of website quality is affected by website performance and
other intangible features; accordingly, one of the major goals of a website is to exceed
customer expectation, which brings them back to the same website (Madu and Madu, 2002).
Hence, it is proposed:
H3. Reputation of a website positively inuences a lodging website customer’s PSQ.
3.4 Perceived service quality (cognitive phase)
Perceived service quality (PSQ) refers to a common judgment of attitude that is related to
superior service (Parasuraman et al., 1988). This study views that PSQ is determined by
website function, customer experience and reputation of a brick-and-click hotel.
The cognitive phase of loyalty is the status of perception of performance (Oliver, 1999), in
which satisfaction is not processed yet. The perceived service quality of websites
signicantly affects customers’ intentions of patronage (Ho and Lee, 2007). A study of a web
portal site nds that customers’ satisfaction is directly inuenced by perceived service
quality (Yang et al., 2005). Website customers’ perceived service quality (cognitive phase)
seems to be a precursor to customers’ satisfaction (affective phase). Hence, it is hypothesized:
H4. PSQ affects a lodging website customer’s CS.
3.5 Customer satisfaction (affective phase)
Typically, customers are committed to a brand or product in this phase of loyalty (Oliver,
1999). Customer satisfaction results from customers’ perceived service quality and is an
antecedent of e-loyalty (Rachjaibun, 2007). It can be measured by the degree of fulllment of
customers’ needs and their satisfaction with the website’s services. This results in longer
stays of customers, instead of searching for competitor’s information. It is typically believed
that customers’ satisfaction strengthens the relationship of perceived website service quality
with customers’ return intention. Therefore, it is hypothesized:
H5. Customer satisfaction mediates the relationship between a lodging website
customer’s PSQ and RI.
H6. Customer satisfaction inuences a lodging website customer’s RI.
3.6 Return intention (conative phase)
Customers in this phase of loyalty are willing to repurchase (Oliver, 1999). Customer
satisfaction is considered as the major predictor of customer return intention, which is itself
a precursor of loyalty. Studies on website quality have sought to develop frameworks that
measure antecedents and consequences of perceived website service quality that lead to
customers’ patronage (Ho and Lee, 2007;Wolnbarger and Gilly, 2003). Studies (Reicheld
and Schefter, 2000) apply the construct of e-trust to measure the conative stage of loyalty
evolved from the customer satisfaction (affective) phase. In this study, however, customer
return intention is considered as a precursor stage to action loyalty. In other words, it is
viewed that customer loyalty is derived from customers’ return intention to a lodging
website. Hence, this study hypothesizes:
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H7. A lodging website customer’s return intention mediates the relationship between CS
and CL.
H8. A lodging website customer’s return intention inuences CL.
3.7 Customer e-loyalty (action phase)
Loyalty refers to the likelihood of customers’ returning to an organization and their
willingness to be partners to the organization (Bowen and Shoemaker, 1998). Loyal
customers inuence the company’s bottom line as intangible assets, including
recommending to others (Morgan and Hunt, 1994). Further, customers’ emotional
attachment to a brand/product and their repeated purchases are two critical factors
determining loyalty (Grifn, 2002). Thus, customers’ actual engagements in repurchasing
are identied as action loyalty (Oliver, 1999). Ultimately, loyalty appears reected in
customers’ emotional attachments and repeated purchasing activities.
Meanwhile, e-loyalty has been dened as customers’ favorable attitudes toward online sellers,
which results in repeated purchasing behavior (Srinivasan et al., 2002). E-loyalty appears to be
strongly related to customers’ perceived website service quality and its consequences.
E-loyal customers are protable and comparably less price sensitive (Porter, 2001;
Reicheld and Schefter, 2000). They typically recommend others visit particular websites,
which may contribute to increased purchase decisions. Considering the competitiveness of
online market these days, however, it is challenging for hospitality management to capture
customer’s e-loyalty.
Consequently, the conceptual framework of this study identies positive, direct relationships
among a lodging website customer’s PSQ, CS, RI and CL. Additionally, mediation effects are
proposed in the linear process of the loyalty development as cognitive ⬎affective ⬎conative ⬎
action (see Figure 1).
4. Methodology
4.1 Instrument and study design
The measurement items of the questionnaire were adopted from studies previously
conducted (Ho and Lee, 2007;Yang et al., 2005). A seven-point Likert-type scale was used,
ranging from 1 (strongly disagree) to 7 (strongly agree). There were three sections in the
questionnaire. The rst part consisted of a question to discern the eligibility of respondents.
The survey was allowed to proceed to those who have purchased a hotel room(s) using
websites during the past half a year. A total of 25 measurement items were presented in the
H7
H5
H8
H6
H1
Perceived
Service
Quality
[cognitive] Return
Intention
[conative]
Overall
Customer
Satisfaction
[affective]
Consequences of PSQ
Customer
E-loyalty
[action]
Reputation (REP)
Personalization/
Customization (PC)
H2
H3
H4
Website Functionality
(FUNC)
Antecedents of PSQ
Note: Mediation effects are indicated as dotted lines
Figure 1.
A framework of
loyalty evolvement on
a lodging website
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next part to assess website quality, PSQ, CS, RI to a website and CL. Respondents
demographic questions were included in the third section.
Using a pilot study, the clarity of wordings and reliability of each measurement construct
are assessed. Descriptive statistics and normality tests were done followed by a conrmatory
factor analysis (CFA) using SPSS version 21 and AMOS 17. A CFA was helpful in identifying
convergent and discriminant validities; whether the measurement items were associated
with each other within the construct; and constructs were distinct from each other (Hair et al.,
2010). To test the hypotheses, a structural equation modeling (SEM) method was conducted.
4.2 Data collection and sample
A web-based survey was conducted with complete anonymity, on a voluntary basis, using a
convenience sampling method. Approximately, 5,000 potential respondents were randomly
selected from an alumni email list of a Midwestern university in the USA and invited to the
surveyguizmo.com. Respondents who accepted the invitation were guided to visit the survey
link provided in the email. A total of 292 usable data were left, yielding a 5.84 per cent
response rate after removing 433 responses with an answer of “no” to the screening question
and incomplete surveys.
5. Results
5.1 Demographic characteristics of the respondents
Male respondents (57 per cent) slightly outnumbered their female counterparts. Among
respondents, nearly 60 per cent appeared to make US$100,000 or greater for their annual
household income. A total of 34 per cent were executives/managers, 22 per cent professionals
and 14 per cent educators. Owing to the convenience sampling with alumni group of a US
state university, most respondents held either a bachelor’s or a graduate degrees (Table I).
The study’s sample showed similar demographic patterns to current online users in terms
of their age group and annual household income. Online hotel guests earned around
US$78,200 annually, which was greater than the average traveler’s income of US$73,900.
Also, the majority of online guests belonged to the age groups of Baby Boomers and
Generation Xers (aged between 37 and 67 years) (Harteveldt, 2014).
5.2 Descriptive analysis/normality test
To assess cohesiveness of measurement item (internal consistency), a reliability test was
conducted using Cronbach’s
␣
, which was higher than 0.70, indicating reliable internal
consistency (Creswell, 2005). Also, the test indicated the mean value (3.89 to 5.67) with the
standard deviation (1.19 to 1.76), showing about a 0.57 dispersal range.
The skewness for most measurement items was smaller than ⫾2, which reasonably
represented the normal distribution (George and Mallery, 2001). However, there were several
items with high kurtosis values, specically the “highest education” variable, implying the
curve was steeper than a normal distribution. This high kurtosis value (3.0) was caused by
the homogeneous characteristics of the participants as university alumni, whose minimum
education was a college degree.
5.3 Measurement statistics
A CFA was conducted using 25 items. Owing to cross-loading and low factor loadings, three
items (one for functionality, one for customer experiential aspects and one for return
intention – see Table II) were removed from the dataset; the remaining 22 items were retained
for further analysis. The measurement model exhibited an acceptable model t (
␹
2
(292) ⫽
475.85, d/f ⫽210, p⫽0.000, CMIN/DF ⫽2.26, CFI ⫽0.95, TLI ⫽0.94, NFI ⫽0.92, TLI ⫽0.94
and RMSEA ⫽0.066). The composite reliability for the measurement variables was greater
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than 0.71. The standardized loading values for all items exceeded 0.57. All factor loadings
appeared to be signicant (p⬍0.001, t ⬎3.27), suggesting satisfactory convergent validity
for each construct. Also, the average variance extracted (AVE) for all seven constructs
exceeded the threshold value of 0.50, meeting the expected cut-off value (Fornell and Larcker,
1981). This meant the convergent validity of the measurement items was achieved. The
discriminant validity was marginally achieved. AVEs for all seven constructs exceeded the
0.50 value. All AVEs should exceed the largest multiple squared correlation (Fornell and
Larcker, 1981) to achieve discriminant validity.
Comparably high correlations were noticed among some variables (i.e. functionality,
perceived service quality, customer satisfaction and loyalty). To examine common method
variance (CMV) of the dataset, Harman’s single-factor test was conducted. It is considered as
the most commonly used test by researchers to conrm that their research is not pervasively
affected by CMV despite concern for its insensitivity (Chang et al., 2010). The total variance
of a single factor was explained by 38 per cent, which was lower than 50 per cent threshold.
The measurement properties, including the correlations for construct, squared multiple
correlations (SMC); mean, standard deviation, composite liability, AVE and squared root of
the AVE are displayed (Table III).
Table I.
Respondents’
demographic prole
Demographic characteristics No. (%)
Gender (n ⫽287)
Female 124 43.2
Male 163 56.8
Age (n ⫽287)
Older than 61 21 7.3
Between 46 and 60 156 54.4
Between 31 and 45 60 20.9
Up to 30 50 17.4
Highest education (n ⫽289)
College 142 49.1
Graduate (Master’s degree, PhD) 147 50.9
Annual household income (n ⫽260)
Less than $30,000 9 3.5
$30,001-$50,000 17 6.5
$50,001-$80,000 38 14.6
$80,001-$100,000 41 15.8
Higher than $100,000 155 59.6
Occupation (n ⫽287)
Executive/manager 100 33.5
Professional 58 21.6
Teacher/professor 37 13.6
Self-employed 22 8.0
Government/military 16 5.6
Salesman/buyer 14 5.2
Secretary/clerk 8 2.8
Others
a
27 9.7
Note:
a
Others include retires, homemakers, students, artists and so on
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5.4 Parameter estimates analysis
To assess the relationships of determinants of website service quality and customer
behaviors on a website, multivariate data analysis was conducted adopting the SEM method
(Hair et al., 2010). The t indices (
␹
2
(292) ⫽478.68, d/f ⫽201, p⫽0.000, RMSEA ⫽0.069,
NFI ⫽0.92, TLI ⫽0.94, CFI ⫽0.95) implied an acceptable model t. CMIN/DF was 2.38
(smaller than 3), indicating an adequate t (Gefen et al., 2003). CFI, NFI and TLI showed
values larger than 0.90 and were acceptable, while values larger than 0.95 were viewed as a
good t. RMSEA (0.069) was close to the cut-off value of 0.06 and was an acceptable t (Hu
and Bentler, 1999). The degree of explanation of variances of the data was assessed by SMC
(R
2
). The analysis of parameter estimates is summarized in Figure 2.
Table II.
The measurement
instrument
Measurement item Cronbach’s
␣
Functionality (FUNC) 0.81
Information from the lodging website was helpful to make my purchase decisions
The lodging website described complete information about the hotel’s services
The lodging website provided a wide range of information about the hotel and its
services, such as room amenities, facility information, location, area attractions, etc.
It was easy for me to navigate the lodging website
The lodging website is retrieved in no time
Customer experiential aspects (CE) 0.77
The website design is comfortable to look at
The lodging website recognized me when returning and my search preferences
were remembered
Reputation (REP) 0.79
People I know recommended this lodging website to me
I read many good comments about the hotel on the customers’ evaluations site such
as TripAdvisor.com
I received a good impression about the website through the lodging facility’s
advertisement in the media (TV or magazine)
I expected a quality lodging website, due to the lodging facility’s impressive
advertisement on the media
Perceived service quality (PSQ) 0.95
Overall, the services on this website were excellent in quality
The lodging website provided the exact service quality I expected or desired
The lodging website’s service offerings matched the hotel’s rating
Overall customer satisfaction (OCS) 0.86
All in all, I was very satised with the hotel website’s services
The lodging website greatly fullled my needs at the time I used it
I didn’t think I needed to visit other lodging websites to search for more information
to book a room
Return intention (RI) 0.71
I want to reuse this lodging website to book my next trip
I want to revisit this lodging website to search for hotel information
Customer e-loyalty (CL) 0.90
I use this lodging website frequently
I am committed to this lodging website
I want to recommend this lodging website to my family, friends, and acquaintances
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Table III.
Correlations, SMCs
and AVE (n⫽292)
Measures FUNC CE REP PSQ CS RI CL AVE
FUNC 1.00 0.72
CE 0.21** (0.04) 1.00 0.55
REP 0.31* (0.10) 0.23** (0.05) 1.00 0.54
PSQ 0.72** (0.52) 0.19** (0.04) 0.38* (0.14) 1.00 0.85
CS 0.48** (0.23) 0.17** (0.03) 0.46** (0.21) 0.61** (0.37) 1.00 0.73
RI 0.26** (0.07) 0.17** (0.03) 0.44** (0.19) 0.39** (0.15) 0.64** (0.41) 1.00 0.55
CL 0.26** (0.07) 0.17** (0.03) 0.36** (0.13) 0.39** (0.15) 0.60** (0.36) 0.73** (0.53) 1.00 0.76
Mean 5.87 5.36 4.59 5.59 4.9 4.2 4.4
SD 1.02 1.98 0.98 1.35 1.4 1.73 1.66
Composite Reliability 0.88 0.71 0.79 0.95 0.86 0.71 0.90
Notes: ** p⬍0.01, * p⬍0.10; the squared root of AVE are displayed along the diagonal
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Figure 2 indicates results of data analyses conrmed that the website functionality (FUNC)
inuenced the perceived website service quality (PSQ) (
␤
⫽0.56, t⫽12.17, p⬍0.001);
customer experiential aspects (CE) signicantly affected perceived service quality
(
␤
⫽0.33, t⫽7.17, p⬍0.001); and reputation dimension (REP) also inuenced the perceived
website service quality (
␤
⫽0.11, t⫽2.77, p⬍0.01). Therefore, H1,H2 and H3 were
supported. Findings also identied that perceived service quality (PSQ) positively affected
customer satisfaction (CS) (
␤
⫽0.71, t⫽12.47, p⬍0.001); customer satisfaction signicantly
inuenced customer return intention (
␤
⫽0.64, t⫽11.18, p⬍0.001); customer satisfaction
fully mediated the relationship between PSQ and return intention (
␤
⫽⫺0.01, t⫽⫺0.21,
p⬎0.05). Thus, H4,H5 and H6 were all supported.
Parameter estimate of the path from return intention (RI) to customer loyalty (CL) was
determined as a signicant, positive association (
␤
⫽0.77, t⫽14.11 p⬍0.001). Also, a
mediation effect was detected for the path from customer satisfaction (CS) to customer
loyalty (CL) (
␤
⫽0.03, t⫽1.02, p⬎0.05), showing that return intention mediated the
relationship between customer satisfaction and customer loyalty. Therefore, H7 and H8
were also supported.
The path from PSQ to RI was mediated by CS (r⫽0.39) and the path from CS to CL was
mediated by RI (r⫽0.60). SMC indicated the perceived service quality variable explained 68
per cent of the variances in the analysis (R
2
⫽0.68); customer satisfaction, 36 per cent (R
2
⫽
0.36); return intention, 41 per cent (R
2
⫽0.41); and customer loyalty, 83 per cent (R
2
⫽0.83).
5.5 Examining moderation effects by group comparisons
To examine moderation effects by gender and age cohorts, a series of group comparisons
was conducted. Comparing a constraint model against a free model is recommended in
addition to evaluating the overall model t and parameter estimates (Kline, 1998). To assert
the strength of the explaining power of interaction effects, a constraint model was tested
using two gender groups (male and female) as well as two age cohorts (Generations X and Y
vs Baby Boomers and Seniors).
Age cohort comparison showed no signicant differences between the two groups.
Gender comparisons, however, indicated moderation effects with three paths. First, the
–0.01
PSQ
CL
FUNC
RI
SQ1 SQ2 SQ3
F2
F3
F4
F5
LO3
LO1
LO2
RI2
RI1
CE
C1
C2
REP
R1
R2
R3
R4
CS
CS1 CS2 CS3
F1
0.56***
0.33***
0.11**
0.71***
0.64***
0.77***
0.03
R2 = 0.83
R2 = 0.41
R2 = 0.68
R2 = 0.36
Notes: *p < 0.10; **p < 0.01; ***p < 0.001; Model fit (χ2 = 526.39, d/f = 221,
p
= 0.000, CMIN/DF = 2.38, RMSEA = 0.069, TLI = 0.94, CFI = 0.95)
Figure 2.
Parameter estimates
analysis
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regression weight for the path from functionality (FUNC) to perceived service quality (PSQ)
for the male group (
␤
⫽0.82, CR ⫽10.06, p⬍0.000) appeared to be higher than that of the
female group (
␤
⫽0.78, CR ⫽5.30, p⬍0.000). Second, the path coefcient of perceived
service quality (PSQ) and overall satisfaction (OS) for the male group (
␤
⫽0.96, CR ⫽18.16,
p⬍0.000) was higher than that of the female group (
␤
⫽81, CR ⫽10.77, p⬍0.000). Third,
the male group (
␤
⫽0.94, CR ⫽4.67, p⬍0.000) showed higher regression weight than the
female group (
␤
⫽0.78, CR ⫽5.30, p⬍0.000) in the path from return intention (RI) to
customer loyalty (CL).
Chi-square (
␹
2
) tests indicated that the free model (
␹
2
⫽750.07, d/f ⫽398, p⬍0.000) was
superior to the constraint model (
␹
2
⫽755.26, d/f ⫽399, p⬍0.000). The free model showed
a smaller
␹
2
value but also had a smaller degree of freedom than the constraint model did.
The difference in the
␹
2
value was much larger than the difference in the degree of freedom
(⌬
␹
2
⫽5.2,
␹
2
0.05 (1) ⫽3.84).
6. Discussion and conclusions
6.1 Discussion
This study’s ndings conrm that loyalty evolves as proposed in the framework, from the
cognitive (perceived website service quality) to the affective (customer satisfaction) to the
conative (return intention) and nally to the action (customer loyalty) phase. Specically,
direct linkages among the four loyalty phases are noticed in the course of their linear
relationships. Perceived website service quality appears to be a precursor to customer
satisfaction that leads to customer return intention. Customer intention to reuse the website
service is strongly related to building customers’ loyalty with the lodging website.
Results also imply that when customers perceive the website to be providing useful and
convenient functions, experiential aspects and favorable reputation, they recognize high
website service quality. This means that customers will perceive a lodging website’s service
quality based upon their experiences with the website’s practical functions, the pleasantness
of the website’s environment and the reputation of the brick and click hotel.
Moderation effects have been detected by examining differences between the two gender
groups. A series of group comparison analyses indicates signicant differences with three
associations: FUNC and PSQ; PSQ and CS; and RI and CL. The male group appears to better
perceive effects of website functionality on perceived service quality, compared to the female
group. It can be interpreted that the male group believes the perceived service quality affects
overall customer satisfaction of website quality stronger than the female group does.
Further, the male group views that their return intention affects their loyalty more than the
female group does. Finally, ndings of this study indicate that the effects of return intention
on customer loyalty are much stronger in the male group than in the female group.
6.2 Theoretical implications
To the authors’ best knowledge, this study uniquely adopts the concepts of Oliver’s (1999)
four phases of the loyalty framework into the context of lodging websites and conrms a
linear relationship of the customer e-loyalty development process. Customers’ behaviors are
considered consequences of perceived service quality, including repurchase intentions,
WOM and loyalty (Baloglu, 2002;Zeithaml et al., 1996).
The framework of four different typologies of loyalty has been adopted in several studies
(Dick and Basu, 1994) – true, latent, spurious and low loyalty. Their ndings show that
loyalty measurement of four different typologies is supported in the context of the travel
industry. Unlike other loyalty studies, this study attempts to incorporate Oliver’s (1999)
loyalty framework into customers’ behaviors and conrms that the concept of loyalty in
general is also applicable in the context of the lodging business. Consequently, this study’s
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ndings support the literature that the four loyalty phases follow a linear pattern from the
cognitive stage to the affective stage, then proceeds to the conative stage and, nally, evolves
to the action stage. Both affective (customer satisfaction) and conative (return intention)
stages of loyalty have been found to play roles in this study as mediators in their
relationships with other criterion variables.
Two mediators in the study’s framework, customer satisfaction and return intention, are
key constructs that enhance the explanatory power of the overall framework, in particular,
for measuring the progression of loyalty formation in an online environment. As
demonstrated in previous studies which indicate the important roles of customer satisfaction
and return intention in assessing customers’ psychological behavior, this study reconrms
their ndings that both customer satisfaction and return intentions are key predictors to
measure or form customer loyalty, which ultimately affects a company’s bottom line.
Regardless of the transactional setting whether on-line or off-line, customers’ psychological
and booking behaviors turn out to be identical.
6.3 Practical implications
Besides its theoretical implications, this study provides hospitality management with
insightful practical tips that can increase customers’ revisits to the company’s website.
Designing a lodging website more tailored to customers’ expectations and needs is a denite
means to encourage repeated use of the same website, creating “stickiness”. Although it is
challenging to develop an effective website to meet customers’ expectations (Chung and Law,
2003) and achieve a competitive advantage sustaining a website (Law et al., 2010), hospitality
management should establish and maintain effective websites that encourage customers to
make the right decisions (Kim and Fesenmaier, 2008). To ensure the perceived service quality
of a lodging website, management must develop constant dialogs with its customers by
asking whether the website is comparable to other lodging websites in offering the best
service tailored for its customers and competitive enough to attract more customers to the
website for its better service and customized products. As this study implies, management is
responsible for providing functional, pleasurable surng and a reputable website to its
customers.
Understanding an attitude-behavior matrix and utilizing it as a marketing tool may assist
hotel management in developing effective marketing strategies. Hotel management must
develop the most relevant and appropriate communication strategies to cater to each
customer’s phase of loyalty toward the hotel based upon an individual customer’s’ level of
loyalty. Each customer can be contacted with a different channel or method of
communications according to his/her loyalty level. Thus, it can be a hotel’s key responsibility
to have an up-to-date customer data in its customer relationship management system to
identify each customer’s loyalty type and behavior.
As lodging companies try to develop a streamlined digital market encompassing various
social media, it would be ideal to establish a website of high quality. In particular, hotels must
identify ways to maximize customers’ digital experience while online. Carefully monitoring
customers’ online behaviors can provide educated insights into customers’ online behavior.
As ndings of the study indicate, the male group, compared to the female group, appears to
be more sensitive in their perception of functionality of website service quality, relationship
between service quality and satisfaction, and return intention to customer loyalty.
Depending upon their target customer groups, hotel management is encouraged to develop
and implement distinctive marketing strategies such as gender-based marketing strategies
to capture a wider range of target markets. Specically, business hotels can execute specic
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marketing strategies to appeal to the majority of their customers who may be male business
travelers.
6.4 Limitations and suggestions for future research
This study has some reservations, limiting interpretation of its ndings, despite its thorough
review of previous research and methodological enhancement. Caution is advised in
generalization of its ndings. A random sample might have been better to avoid the
skewedness of this study’s demographic prole (i.e. higher educational level of attaining at
least a college degree because of the sample population of university alumni).
The instrument could have included additional variables that measure different website
quality dimensions. Additional factors that may be considered for future research include
customers’ afliation with a hotel (i.e. membership) and brand awareness of the hotel
because customers’ loyalty is believed to become established through experience.
Also, data that are collected in a cross-sectional method may be insufcient to advocate
the direction of loyalty development with customers’ behaviors, which requires caution
when interpreting the results. To better detect the development of customer loyalty, an
attempt to investigate customers’ behaviors, using longitudinal data, may be more
appropriate.
References
Aaker, D. (1991), Managing Brand Equity: Capitalizing on the Value of the Brand Name, Free Press,
New York, NY.
Ajzen, I. and Fishbein, M. (1980), Understanding Attitudes and Predicting Social Behavior, Prentice Hall,
Englewood Cliffs, NJ.
Akincilar, A. and Dagdeviren, M. (2014), “A hybrid multi-criteria decision-making model to evaluate
hotel websites”, International Journal of Hospitality Management, Vol. 36 No. 1, pp. 263-271.
Asatryan, V. and Oh, H.M. (2008), “Psychological ownership theory, an exploratory application in the
restaurant industry”, Journal of Hospitality and Tourism Research, Vol. 32 No. 3, pp. 363-386.
Bai, B., Law, R. and Wen, I. (2008), “The impact of website quality on customer satisfaction and
purchase intentions: evidence from Chinese online visitors”, International Journal of Hospitality
Management, Vol. 27 No. 3, pp. 391-402.
Baloglu, S. (2002), “Dimensions of customer loyalty: separating friends from well wishers”, Cornell Hotel
and Restaurant Administration Quarterly, Vol. 43 No. 1, pp. 47-59.
Baloglu, S. and Pekcan, Y.A. (2006), “The website design and internet site marketing practices of
upscale luxury hotels in Turkey”, Tourism Management, Vol. 27, pp. 171-176.
Bevanda, V., Grzinic, J. and Cervar, E. (2008), “Analyzing the users’ perceptions web design quality by
data mining tools”, Tourism and Hospitality Management, Vol. 14 No. 2, pp. 251-262.
Bilgihan, A., Nusair, K., Okumus, F. and Cobanoglu, C. (2015), “Applying ow theory to booking
experiences: an integrated model in an online service context”, Information and Management,
Vol. 52 No. 6, pp. 668-678.
Bitner, M. (1992), “Servicescapes: the impact of physical surroundings on customers and employees”,
Journal of Marketing, Vol. 56, pp. 57-71.
Bowen, J. and Chen McCanin, S. (2015), “Transitioning loyalty programs: a commentary on ‘the
relationship between customer loyalty and customer satisfaction’”, International Journal of
Contemporary Hospitality Management, Vol. 27 No. 3, pp. 415-430.
Bowen, J. and Chen, S. (2001), “The relationship between customer loyalty and customer satisfaction”,
International Journal of Contemporary Hospitality Management, Vol. 13 No. 5, pp. 213-217.
IJCHM
29,1
452

Bowen, J. and Shoemaker, S. (1998), “The antecedents and consequences of customer loyalty”, Cornell
Hotel Restaurant and Administration Quarterly, Vol. 43 No. 1, pp. 12-25.
Brown, S. and Stayman, D. (1992), “Antecedents and consequences of attitude toward the ad: a
meta-analysis”, Journal of Consumer Research, Vol. 19 No. 1, pp. 34-51.
Casalo, L., Flavian, C. and Guinaliu, M. (2008), “The role of perceived usability, reputation, satisfaction
and consumer familiarity on the website loyalty formation process”, Computers in Human
Behavior, Vol. 24 No. 2, pp. 325-345.
Chang, H.H. and Chen, S.W. (2007), “Consumer perception of interface quality, security, and loyalty in
electronic commerce”, Information and Management, Vol. 46 No. 7, pp. 411-417.
Chang, S.J., van Witteloostuijn, A. and Eden, L. (2010), “From the editors: common method variance in
international business research”, Journal of International Business Studies, Vol. 41 No. 2,
pp. 178-184.
Chiou, W.C., Lin, C.C. and Perng, C. (2010), “A strategic framework for website evaluation based on a
review of the literature from 1996-2006”, Information and Management, Vol. 47 No. 5,
pp. 282-290.
Chung, T. and Law, R. (2003), “Developing a performance indicator for hotel websites”, International
Journal of Hospitality Management, Vol. 22 No. 1, pp. 119-125.
Creswell, J.W. (2005), Educational Research: Planning, Conducting, and Evaluating Quantitative and
Qualitative Research, 2nd ed., Pearson Education, Upper Saddle River, NJ.
Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information
technology”, Management Science, Vol. 13 No. 3, pp. 319-340.
Diaz, E. and Koutra, C. (2013), “Evaluation of the persuasive features of hotel chains websites: a latent
class segmentation analysis”, International Journal of Hospitality Management, Vol. 34 No. 1,
pp. 338-347.
Dick, A.S. and Basu, K. (1994), “Customer loyalty: toward an integrated conceptual framework”, Journal
of the Academy of Marketing Science, Vol. 22 No. 2, pp. 99-113.
Dolatabadi, H.R. and Pool, J.K. (2013), “Analysis electronic service quality through E-S-Qual scale: the
case study of Nowshahr hotel”, Research Journal of Applied Sciences, Engineering and
Technology, Vol. 5 No. 7, pp. 2321-2326.
Fassnacht, M. and Koese, I. (2006), “Quality of electronic services: conceptualizing and testing
hierarchical model”, Journal of Service Research, Vol. 9 No. 1, pp. 19-37.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable
variables and measurement error”, Journal of Marketing, Vol. 18 No. 1, pp. 39-50.
Gefen, D., Straub, D. and Boudreau, M. (2003), “Structural equation modeling and regression: guidelines
for research practice”, Communications of the Association for Information Systems, Vol. 4 No. 1,
pp. 1-77.
George, D. and Mallery, P. (2001), SPSS for Windows Step by Step: A Simple Guide and Reference 10.0
Update, Allyn and Bacon, Toronto.
Grifn, J. (2002), Customer Loyalty: How to Earn It, How to Keep It, 2nd ed., Jossey-Bass Publication,
San Francisco, CA.
Ha, S. and Stoel, L. (2009), “Consumer e-shopping acceptance: antecedents in a technology acceptance
model”, Journal of Business Research, Vol. 62 No. 5, pp. 565-571.
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L. (2010), Multivariate Data Analysis,
6th ed., Prentice Hall, Upper Saddle River, NJ.
Harison, E. and Boonstra, A. (2009), “Essential competencies for technochange management: towards
an assessment model”, International Journal of Information Management, Vol. 29 No. 4,
pp. 283-294.
453
Website
service quality

Harteveldt, H. (2014), “Who’s sleeping with you: detailed look into the US online hotel guest”, available
at: www.slideshare.net/wysetc/detailedlookintotheusonlinehotelguest20132014
Herrero, A. and San Martin, H. (2012), “Developing and testing a global model to explain the adoption of
websites by users in rural tourism accommodations”, International Journal of Hospitality
Management, Vol. 31 No. 4, pp. 1178-1186.
Herrero, A., San martin, H. and Hernandez, J. (2015), “How online search behavior is inuenced by
user-generated content on review websites and hotel interactive websites”, International Journal
of Contemporary Hospitality Management, Vol. 27 No. 7, pp. 1573-1597.
Ho, C. and Lee, Y. (2007), “The development of an e-travel service quality scale”, Tourism Management,
Vol. 28 No. 6, pp. 1434-1449.
Hsu, C.L., Chang, K.C. and Chen, M.C. (2012), “The impact of website quality on customer satisfaction
and purchase intention: perceived playfulness and perceived ow as mediators”, Information
System of E-Business Management, Vol. 10 No. 4, pp. 549-570.
Hu, L.T. and Bentler, P.M. (1999), “Cutoff criteria for t indexes in covariance structure analysis:
conventional criteria versus new alternatives”, Structural Equation Modeling, Vol. 6 No. 1,
pp. 1-55.
Hu, Y.C. (2009), “Fuzzy multiple-criteria decision making in the determination of critical criteria for
assessing service quality of travel websites”, Expert Systems with Application, Vol. 36 No. 3,
pp. 6439-6445.
Huang, M.H. (2015), “The inuence of relationship marketing investments on customer gratitude in
retailing”, Journal of Business Research, Vol. 68 No. 6, pp. 1318-1323.
Ip, C., Law, R. and Lee, H. (2011), “A review of website evaluation studies in the tourism and hospitality
elds from 1996-2009”, International Journal of Tourism Research, Vol. 13, pp. 234-265.
Jeong, M. and Jeon, M.M. (2008), “Customer reviews of hotel experiences through customer generated
media (CGM)”, Journal of Hospitality and Leisure Marketing, Vol. 17 Nos 1/2, pp. 121-137.
Jeong, M. and Lambert, C.U. (2001), “Adaptation of an information quality framework to measure
customers’ behavioral intention to use lodging websites”, International Journal of Hospitality
Management, Vol. 20 No. 2, pp. 129-146.
Jeong, M., Oh, H. and Gergoire, M. (2003), “Conceptualizing web site quality and its consequences
in the lodging industry”, International Journal of Hospitality Management, Vol. 22 No. 2,
pp. 161-175.
Johnson, M., Herrmann, A. and Huber, F. (2006), “The evolution of loyalty intentions”, Journal of
Marketing, Vol. 70 No. 2, pp. 122-132.
Kandampully, J., Zhang, T. and Bilgihan, A. (2015), “Customer loyalty: a review and future directions
with a special focus on the hospitality industry”, International Journal of Contemporary
Hospitality Management, Vol. 27 No. 3, pp. 379-414.
Kim, H. and Fesenmaier, D.R. (2008), “Persuasive design of destination web sites: an analysis of rst
impression”, Journal of Travel Research, Vol. 47 No. 3, pp. 3-13.
Kim, W. and Lee, H.Y. (2004), “Comparison of web service quality between online travel agencies and
online travel suppliers”, Journal of Travel and Tourism Marketing, Vol. 17 Nos 2/3, pp. 105-116.
Kim, J., and Lennon, S.J. (2013), “Effects of reputation and website quality on online consumers’ emotion,
perceived risk and purchase intention: based on the stimulus-organism-response model”, Journal
of Research in Interactive Marketing, Vol. 7 No. 1, pp. 33-56.
Kim, M.J., Chung, N. and Lee, C.K. (2011), “The effect of perceived trust on electronic commerce:
shopping online for tourism products and services in South Korea”, Tourism Management,
Vol. 32 No. 2, pp. 256-265.
IJCHM
29,1
454

Kim, D., Jang, S. and Adler, H. (2015), “What drives café customers to spread eWOM? E: examining
self-relevant value, quality value, and opinion leadership”, International Journal of
Contemporary Hospitality Management, Vol. 27 No. 2, pp. 261-282.
Kline, R.B. (1998), Principles and Practice of Structural Equation Modeling, Guilford Press, New York,
NY.
Kuo, P., Zhang, L. and Cranage, D. (2015), “What you get is not what you saw: exploring the impacts of
misleading hotel website photos”, International Journal of Contemporary Hospitality
Management, Vol. 27 No. 6, pp. 1301-1319.
Ladhari, R. and Leclerc, A. (2013), “Building loyalty with online nancial services customers: is there a
gender difference?”, Journal of Retailing and Consumer Services, Vol. 20 No. 6, pp. 560-569.
Ladkin, A. and Buhalis, D. (2016), “Online and social media recruitment: hospitality employer and
prospective employee considerations”, International Journal of Contemporary Hospitality
Management, Vol. 28 No. 2, pp. 327-345.
Law, R. and Cheung, C. (2006), “A study of the perceived importance of the overall website quality of
different classes of hotels”, International Journal of Hospitality Management, Vol. 25 No. 3,
pp. 525-553.
Law, R., Qi, S. and Buhalis, D. (2010), “Progress in tourism management: a review of website evaluation
in tourism research”, Tourism Management, Vol. 31 No. 3, pp. 297-313.
Lee, D., Moon, J., Kim, Y. and Mun, Y. (2015), “Antecedents and consequences of mobile phone usability:
linking simplicity and interactivity to satisfaction, trust, and brand loyalty”, Information &
Management, Vol. 52 No. 3, pp. 295-304.
Liao, C., Palvia, P. and Lin, H. (2006), “The roles of habit and web site quality in e-commerce”,
International Journal of Information Management, Vol. 26 No. 6, pp. 469-483.
Libai, B., Bolton, R., Buegel, M.S., de Ruyter, K., Goetz, O., Risselada, H. and Stephen, A.T. (2010),
“Customer-to-customer interactions: broadening the scope of word of mouth research”, Journal of
Service Research, Vol. 13 No. 3, pp. 267-282.
Liu, Y. (2006), “Word of mouth for movies: its dynamics and impact on box ofce revenue”, Journal of
Marketing, Vol. 70 No. 3, pp. 74-89.
Llach, J., Marimon, F., del Mar Alonso-Almeida, M. and Bernardo, M. (2013), “Determinants of online
booking loyalties for the purchasing of airline tickets”, Tourism Management, Vol. 35 No. 1,
pp. 23-31.
Loiacono, E., Watson, R. and Goodhue, D. (2007), “WebQual™: an instrument for consumer evaluation
of web sites ”, International Journal of Electronic Commerce, Vol. 11 No. 3, pp. 51-87.
McCain, S., Jang, S. and Hu, C. (2005), “Service quality gap analysis toward customer loyalty: practical
guidelines for casino hotels”, International Journal of Hospitality Management, Vol. 24 No. 3,
pp. 465-472.
McMullan, R. and Gilmore, A. (2008), “Customer loyalty: an empirical study”, European Journal of
Marketing, Vol. 42 Nos 9/10, pp. 1084-1094.
Madu, C.N. and Madu, A.A. (2002), “Dimensions of e-quality”, International Journal of Quality and
Reliability Management, Vol. 19 No. 3, pp. 246-258.
Martinez, P. (2015), “Customer loyalty: exploring its antecedents from a green marketing perspective”,
International Journal of Contemporary Hospitality Management, Vol. 27 No. 5, pp. 896-917.
Marui, A.G. and Minazzi, R. (2013), “Web reviews inuence on expectations and purchasing intentions
of hotel potential customers”, International Journal of Hospitality Management, Vol. 34,
pp. 99-107.
Mason, D., Tideswell, C. and Roberts, E. (2006), “Guests perceptions of hotel loyalty”, Journal of
Hospitality and Tourism Research, Vol. 30 No. 2, pp. 191-206.
455
Website
service quality

Mattila, A.S. and Wirtz, J. (2001), “Congruency of scent and music as a driver of in-store evaluations and
behavior”, Journal of Retailing, Vol. 77 No. 2, pp. 273-289.
Morgan, R.M., and Hunt, H. (1994), “The commitment-trust theory of relationship marketing”, Journal of
Marketing, Vol. 58 No. 3, pp. 20-38.
Nielsen Consumer Report (2010), “A global trend in online shopping”, available at: www.nielsen.
com/us/en/insights/reports/2010/Global-Trends-in-Online-Shopping-Neilsen-Consumer-R
eport.html (accessed 25 November 2014).
Nusair, K. and Kandampully, J. (2008), “The antecedents of customer satisfaction with online travel
services: a conceptual mode”, European Business Review, Vol. 20 No. 1, pp. 4-19.
O’Cass, A. and Carlson, J. (2010), “Examining the effects of website-induced ow in professional
sporting team websites”, Internet Research, Vol. 20 No. 2, pp. 115-134.
Oliver, R. (1999), “Whence consumer loyalty?”, Journal of Marketing, Vol. 64 No. 4, pp. 33-44.
Olson, S. (2002), “Comparative evaluation and the relationship between quality, satisfaction, and
repurchase loyalty”, Journal of the Academy of Marketing Science, Vol. 30 No. 3, pp. 252-261.
Parasuraman, A., Zeithaml, V. and Berry, L. (1988), “SERVQUAL: a multiple-item scale for measuring
consumer perceptions of service quality”, Journal of Retailing, Vol. 64 No. 1, pp. 12-40.
Park, Y.A. and Gretzel, U. (2007), “Evaluation of emerging technologies in tourism: the case of travel
search engines”, in Hits, M., Sigala, M. and Murphy, J. (Ed.), Information and Communication
Technologies in Tourism 2006, Springer-Wien, New York, NY, pp. 371-382.
Pizam, A. (2013), “Hotel online privacy”, International Journal of Hospitality Management, Vol. 35, A1.
Porter, M. (2001), “Strategy and the internet”, Harvard Business Review, Vol. 97 No. 3, pp. 62-78.
Rachjaibun, N. (2007), “A study of antecedents of e-relationship quality in hotel websites”, unpublished
doctoral dissertation, OK State University, Stillwater, OK.
Reicheld, F. and Schefter, P. (2000), E-loyalty: Your Secret Weapon on the Web, Harvard Business School
Press, Boston, MA.
Riley, M., Niinine, O., Szivas, E. and Wills, T. (2001), “The case for process approaches in loyalty
research in tourism”, International Journal of Tourism Research, Vol. 3 No. 1, pp. 23-32.
Sanchez-Franco, M. and Roldan, J. (2005), “Web acceptance and usage model: a comparison between
goal-directed and experiential web users”, Internet Research, Vol. 15 No. 1, pp. 21-48.
Shih, H. and Huang, E. (2014), “Inuences of Web interactivity and social identity and bonds on the
quality of online discussion in a virtual community”, Information Systems Frontiers, Vol. 16
No. 4, pp. 627-641.
Shobeiri, S., Laroche, M. and Mazaheri, E. (2013), “Shaping e-retailer’s website personality: the
importance of experiential marketing”, Journal of Retailing and Consumer Services, Vol. 20 No. 1,
pp. 102-110.
Shoemaker, S. and Lewis, R. (1999), “Customer loyalty: the future of hospitality marketing”,
International Journal of Hospitality Management, Vol. 18 No. 4, pp. 345-370.
Srinivasan, S., Anderson, R., and Ponnavolu, K. (2002), “Customer loyalty in e-commerce: an exploration
of its antecedents and consequences”, Journal of Retailing, Vol. 78 No. 1, pp. 41-50.
Vilnai-Yavets, I. and Rafaeli, A. (2006), “Aesthetics and professionalism of virtual servicescapes”,
Journal of Service Research, Vol. 8 No. 3, pp. 245-259.
Wolnbarger, M. and Gill, M. (2003), “eTailQ: dimensionizing, measuring and predicting etail quality”,
Journal of Retailing, Vol. 79 No. 3, pp. 183-198.
Wu, I.L. (2013), “The antecedents of customer satisfaction and its link to complaint intentions in online
shopping: an integration of justice, technology, and trust”, International Journal of Information
Management, Vol. 33 No. 1, pp. 166-176.
IJCHM
29,1
456

Yang, Z., Cai, S., Zhou, Z. and Zhou, N. (2005), “Development and validation of an instrument to measure
user perceived service quality of information presenting web portals”, Information and
Management, Vol. 42 No. 4, pp. 575-589.
Yoo, C.W., Kim, Y.J. and Sanders, G.L. (2015), “The impact of interactivity of electronic word of mouth
systems and e-quality on decision support in the context of the e-marketplace”, Information and
Management, Vol. 52, pp. 496-505.
Yoon, Y., and Uysal, M. (2005), “An examination of the effects of motivation and satisfaction on
destination loyalty: a structural model”, Tourism Management, Vol. 26 No. 1, pp. 45-56.
Zeithaml, V., Berry, L. and Parasuraman, A. (1996), “The behavioral consequence of service quality”,
Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
Zeithaml, V.A., Parasuraman, A. and Malhotra, A. (2002), “Service quality delivery through web sites:
a critical review of extant knowledge”, Journal of the Academy of Marketing Sciences, Vol. 30
No. 4, pp. 362-410.
Zeithaml, V.A. (2000), “Service quality, protability, and the economic worth of customers: what we
know and what we need to learn”, Journal of the Academy of Marketing Science, Vol. 28 No. 1,
pp. 67-85.
Corresponding author
Myunghee Mindy Jeon can be contacted at: mjeon@salemstate.edu
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