Content uploaded by Taiwo Temitope Lasisi
Author content
All content in this area was uploaded by Taiwo Temitope Lasisi on Nov 06, 2020
Content may be subject to copyright.
The Impact of Travel 2.0
on Travelers Booking and
Reservation Behaviors
Alev Elci1
A. Mohammed Abubakar1
Mustafa Ilkan2
Eluwole Kayode Kolawole2
Temitope Taiwo Lasisi2
Abstract
The Internet offers a rich atmosphere for prospective travelers to gain familiarity, and harvest and
retrieve travel-related information and resources. An increasing number of tourism and hospitality
firms have turned their attention to new business opportunities on the Web. Travel 2.0 has emerged as
a new tool for competitive advantage. This study draws on social cognitive theory and the DeLone and
McLean Information Systems (D&M IS) success model to diagnose the impact of websites design quality
on booking/reservation intentions from a travelers’ perspective. This research model was tested with
700 valid data collected from travelers using Travel 2.0 websites through online survey using SPSS v18
for the analysis. The results of the data analysis provided support for the hypothesized relationships
of e-service and system quality with booking/reservation/purchase behavioral intention implying that
an e-travel site’s quality is an essential success factor for tourism enterprises. However, information
quality of an e-travel site is negatively related to booking/reservation intention. Cross-sectional design
and self-report measures are the shortcomings of the study. Little research has been done on the
relation between websites design (e-service, information, and system) quality, and booking/reservation
intention. This article presents new insights into how these variables may influence potential tourist.
Keywords
Travel 2.0, Turkey, reservation, booking, purchase intention
Business Perspectives
and Research
5(2) 1–13
© 2017 K.J. Somaiya Institute of
Management Studies and Research
SAGE Publications
sagepub.in/home.nav
DOI: 10.1177/2278533717692909
http://bpr.sagepub.com
Article
Corresponding author:
Mohammed Abubakar, Department of Management Information System, Aksaray University, Aksaray, Turkey 68100.
E-mail: mohammedabubakar@aksaray.edu.tr
1 Department of Management Information System, Aksaray University, Turkey.
2 Eastern Mediterranean University, Famagusta North Cyprus via Mersin, Turkey.
2 Business Perspectives and Research 5(2)
Introduction
Mankind has traveled over borders for various reasons ranging from education, medical purposes, and
for leisure and recreation. There is an increase in the number of visitors worldwide as a result of
changes in mankind’s economic and socio-political status as well as social activities. All of the afore-
mentioned factors can be noted in a certain aspect of our lives, namely, urbanization, increase in income,
demographic change, change in consumption behavior, and improved labor rights. According to
Merinero-Rodríguez and Pulido-Fernández (2016), travel or tourism is a relational phenomenon, in
other words, a social phenomenon; this is primarily due to its relationship and interaction with various
social elements.
The basal component of tourism/travel that makes it a distinct sector is its intangible nature, that is,
tourism/travel represents service products, unlike physical goods. The intangibility of tourism/travel prod-
ucts makes it hard for consumers to access the service quality before consumption, as such risk and uncer-
tainty tend to be high (Abubakar, 2016). To overcome this uncertainty, potential visitors often search for
information (Casaló et al., 2015). Werthner and Klein (1999) argued that tourism is an information-intense
industry because potential tourists are constantly in search of information.
Drawing on the aforementioned theoretical and empirical arguments, it would not be wrong to say
that full functional websites are essential for all tourism/travel enterprises due to modern traveler’s infor-
mation demands prior to the purchase of tourism-related products and services via the Internet
(Marcussen, 2009). Intuitively speaking, consumers who shop online require a functional website with
good performance and easy navigation with detailed instructions. Perhaps, there is no doubt that travel-
ers who intend to travel expect the content of a website to be properly designed, attractive in terms of
information provision, and should be user-friendly (Vander-Heijden, 2003).
Subsequently, Lu (2004) emphasized that potential travelers require web pages to provide user-
friendly, timely, and reliable product and service information. In a nutshell, there is an expectation both
from tourists and tourism firms. Thus, in order to enhance online travel planning experience, tour plan-
ners need to develop operational and conceptual websites that will address voyagers’ information
demands, meet their expectations, and attract them (Park & Gretzel, 2007). A notable way to ensure
information quality, e-service quality, and service quality of a travel website is to have a well-designed
travel website as argued by Law and Bai (2008); that travel website quality enhances user’s
satisfaction.
Buhalis and Law (2008) stated that hypermedia and the Internet have become the indispensable chan-
nel for individuals seeking to use travel information, thus posing a question regarding how this informa-
tion may affect global tourist reservation, booking, and purchase behaviors. The article is looking into
the possible impact of information quality, e-service quality, and system quality on a potential traveler’s
intention to book or purchase a tourism product or service. The article contributes to our understanding
of these factors as a sustainable strategy that tourism enterprises can utilize to boost their market share.
Literature Review and Hypothesis Development
The travel industry in Turkey has contributed significantly to the social and cultural course. Within the
last decades, Turkey has experienced huge foreign and local investment in travel and tourism infrastruc-
ture. TURSAB (2014) reports showed that Turkish travel industry will continue to experience growth
higher than the European counterparts. The development in Turkish travel industry is also related to
other natural and geographical nature of the country. Turkey lies between the two continents of Asia and
Elci et al. 3
Europe from the East and West, respectively—the Black Sea in the northern part of the country and the
Mediterranean Sea located in the south as well as numerous mountains and rivers.
Turkey has various climate conditions—from the temperate rainy climate in the north to heavy snow-
fall in central and eastern Anatolia to Mediterranean climate in the south—magnificent landscapes, and
diverse flora/fauna; the flora varies from lush forests, steps to typical Aegean and Mediterranean vegeta-
tion. Perhaps, Turkey is a botanical paradise. Porter (2001) stated that technological advances and travel
industry have been going parallel for years, during the 1980s; information and communication technolo-
gies (ICTs) have been changing travel globally.
High quality, useful, and reliable information, as well as functionality, are the basal stimulants encour-
aging people to visit websites (Cai, Card, & Cole, 2004; Ho & Lee, 2007; Park, Gretzel, & Sirakaya-
Turk, 2007). Functional and fashionable web pages help in conveying effective marketing and
promotional messages; they also expatiate on and enhance the perceived quality of products and
services, which in turn builds a brand image for an enterprise (Perdue, 2002). Firms conveying false
information on their sites can endanger their business reputation with accrued devastating consequences
on their products and services. Kasavana, Knuston, and Polonowski (1997) noted that the Internet is
changing the way in which the travel industry plans, controls, operates, and integrates the majority of its
business activities, ranging from branding, marketing, and promotional activities. As a result, more than
two-thirds of travel companies see their websites as a significant competitive weapon within their
industry. Moreover, about 60 percent describe the Internet as playing a major role in acquiring new cus-
tomers (Mullen, 2000).
Travel 2.0 consists of latest innovative technologies like blogs, web forums, podcasting and online
videos (vlogs), customer ratings, and evaluation systems (Xiang & Gretzel, 2010). Specifically, manag-
ers and academicians consider forums and blogs as the most prominent themes within travel industry
(Pudliner, 2007). Xiang and Gretzel (2010) noted that online travel domain may consist of informational
elements associated with travel and tourism products and services. Furthermore, Tussyadiah and
Fesenmaier (2009) demonstrated that social media contents in multimedia sharing sites such as Flickr
and Facebook have the ability to transform travel experience.
Travel 2.0 websites are distinct in their design such that they are structured to incorporate interactivity
between service providers (e.g., hoteliers) and potential customers. This feature of Travel 2.0 websites
implies that users can access travel information from varying perspectives of actual customers and can
then make travel decisions more readily. Most popular of such websites is TripAdvisor with over
5,000,000 attractions, destination, and hotel reviews written by travelers who had experienced the
services. The efforts to provide informative and functional web pages led to changes in the behaviors and
consumption of travelers, as well as power shift in the marketplace (Abubakar, 2012).
Information provided on the Internet is mostly free, accessible anywhere, anytime, and diffuses faster.
Travelers are taking over the control of how the actual production and dissemination of travel-related
information takes place on the Internet. This is because everyone has the ability to publish information
online. Therefore, it is important to understand the changes brought by modern technology and its sub-
sequent impact on tourists. Having a complete understanding provides a critical stepping-stone for the
creation of effective promotional programs and efficient management of information systems (IS)
(Xiang, Wober, & Fesenmaier, 2008) for decision makers.
The Internet atmosphere can provide vital information needed by potential tourists whose desires
include browsing the web for the sake of familiarity or to find and use information related to their inter-
ests. The advantages of online tourism information search include the relatively low cost, customized
information, ease of product comparison, interactivity, virtual community formation, and 24-hour acces-
sibility (Wang, Head, & Arthur, 2002).
4 Business Perspectives and Research 5(2)
Social cognitive theory explains consumer behavior vividly; the theory assumes that consumers’
actions in particular environments rely on personal cognition (Hsu et al., 2007), and personal cognition
relies on expectation or self-efficacy. Hypermedia is designed to support and promote individualism,
self-directed connectivity, and individual empowerment (Qu & Lee, 2011). Arsal, Backman, and Baldwin
(2008) revealed that potential tourists often seek information from hypermedia to assist their travel-
related decisions considering various offers and to shape their conception and image concerning a
destination.
Scholars (e.g., Ayeh, Au, & Law, 2013; Xiang & Gretzel, 2010; Ye et al., 2011) have argued that
consumer testimonies are not only useful in travel planning and information search but also provides
certain beneficial implications for travel businesses, for example, online reservations, bookings for
hotels, and tickets purchase. Breitenbach and Van Doren (1998) stated that an e-travel site must provide
satisfactory online experience, a reason to visit, and a reason to return.
Another factor that may affect reservation intention is site quality, for example, ease of navigation,
download speed, visual attractiveness, and subpages accessibility (Breitenbach & Van Doren, 1998).
Furthermore, Cai et al. (2004) pointed out that information content is one of the key factors attracting
visitors to an e-travel site. Without doubt, scholars and practitioners have turned their attention toward
reengineering and design of websites to facilitate marketing which in turn facilitates performance and
efficiency, and subsequent success of the tourism enterprises. A good travel website design will strengthen
customer’s trust (Lowry et al., 2008), and the presence of trust leads to purchase and sales as well as
revisit intentions. In line with the extra 3P’s that is “Physical appearance” - such as ambience, facility
design, mobile support, signage, displays and others. Next, “process” - refers to the methods in a travel
site employ to provide relevant and supportive services to their customer in order to give them more
satisfaction for their patronage. Finally, “people” - which subsumes the behavior and attitudes of employ-
ees and customers of the sites.
Lots of Internet-based business communication and transaction studies have utilized DeLone and
McLean (D&M) IS success model to measure the success of online systems (Bernroider, 2008; DeLone
& McLean, 2002; Dwivedi, Wade, & Schneberger, 2012; Fang, Chiu, & Wang, 2011; Lin, 2007; Petter
& McLean, 2009; Wang & Liao, 2008). Since Travel 2.0 presents a new business opportunity to travel
and tourism industry via the Internet, this study, therefore, aligned with other scholars and adopted the
D&M IS success model to evaluate the impact of system quality, e-service quality, and information
quality on traveler’s booking/reservation/purchase intention (Delone & Mclean, 2004; Lin, 2007; Wang
& Liao, 2008). Based on D&M IS success model, six dimensions are used to measure the success of IS
(DeLone & McLean, 2002). System quality, information quality, and service quality are three out of the
six dimensions adopted for the purpose of this study.
Adaptability, usability, reliability, availability, and response time are few examples of the qualities a
website must possess for them to be perceived as valuable by the users (Wang & Liao, 2008). This, however,
represents the system quality dimension of D&M IS success model. Furthermore, the relevance,
scope, personalization, completeness, and ease of understanding of the content of a travel website are
perceived as information quality of the website, which is also another dimension of D&M IS success
model. As the model goes through validation processes, several recommendations for improvement are
given. One of such recommendations was the inclusion of service quality to the dimension of the original
D&M IS success model (DeLone & McLean, 2002, 2003). This dimension was accepted and has also
been validated by several studies. The findings of these studies suggest that service quality perfectly
measures the success of IS system. We, therefore, propose e-service quality, which is the perception of
flexibility, responsiveness, assurance, empathy, truthfulness, and reliability of a travel website, as another
important dimension to measure the impact of Travel 2.0 on traveler’s booking/reservation/purchase
intentions.
Elci et al. 5
System quality: It refers to the functional attributes of an e-travel site; system quality has a signifi-
cant influence on travelers’ online purchase intention (Liu, Arnett, & Litecky, 2000). Basically, potential
visitors surf the net either in search of information on a particular travel product and/or services or with
the intention to book/reserve/purchase a travel product and/or services. Academicians (e.g., Ho & Lee,
2007; Wen, 2009) have argued that “travel site quality in terms of functionality has a strong relationship
with customer satisfaction, loyalty or trust,” and, in our opinion, relying on the extant theory, travel site
quality has an impact on booking/reservation/purchase intentions.
Information quality: As mentioned above, travelers usually surf the Internet to look for information
about specific tourism destinations. In order to solicit booking/reservation/purchase intention or
decision, tourist information needs should be provided (Jeong, Oh, & Gregoire, 2003). Therefore, infor-
mation quality has been and will remain a critical factor shaping potential travelers beliefs (Smith, 2004).
Hashim, Murphy, and Law (2007) also realized that information quality ranked the highest in travel
website features that is considered effective by the users. Similarly, other scholars (e.g., Ho & Lee, 2007;
Jeong et al., 2003; Lin & Lu, 2000; Park et al., 2007; Shchiglik & Barnes, 2004) stated that information
quality, response time, and system accessibility affect tourist perceptions and behavioral intentions to use
online travel agencies, hotel, and airline sites.
E-service quality: is another important domain in e-travel website quality and has a huge impact on
customer satisfaction and online purchase intention (Yi & Gong, 2008). The prior literature demonstrated
that relevance of information content in e-travel sites is an important indicator for website traffic. Scholars
like Cai et al. (2004), Park et al. (2007), and Wan (2002) supported the motion. Perhaps, e-travel sites
perceived that ease of use and usefulness will influence travelers trust perception and may lead to subse-
quent booking or purchase. Relying on the extant literature, we came up with the following hypotheses.
H1: Information quality is positively related to booking/reservation/purchase intention.
H2: System quality is positively related to booking/reservation/purchase intention.
H3: E-service quality is positively related to booking/reservation/purchase intention.
Figure 1 below shows the relationships and interdependencies of information, e-service quality and system
quality as predictors of booking/reservation/revisit intention.
Information
quality
System
quality
H1
H2
H3
E-Service
quality
Booking/
Reservation/
Purchase
intention
Figure 1. Conceptual Model
Source: Authors’ own.
6 Business Perspectives and Research 5(2)
Methodology
Data Collection and Scale I ̇ tems
Random sampling technique was utilized for collecting data and scaling items. To achieve the study
objectives, a self-administered survey questionnaire was developed in English and back-translated to
Turkish. We conducted a pilot study with six participants; the aim was to increase data accuracy and to
diagnose the respondents’ understanding. No changes were made because it appears that they all under-
stand the questions. Four filter questions were used in selecting the respondents; the aim was to select
those who had prior online travel purchase experience. System quality was measured with five items
adopted from Ho and Lee (2007). Information quality was measured with two items adopted from Jeong
et al. (2003) and Shchiglik and Barnes (2004). E-service quality was measured with six items adopted
from Baloglu and Pekcan (2006) and Park et al. (2007). The reservation/booking/purchase intention was
measured with five items adopted from Lin (2010). The questionnaire also contains demographic vari-
ables such as age, gender, education, income, and marital status. Data analyses were carried out using
SPSS (version 18).
Results and Data Analysis
We contacted the participants through emails and various social media outlets in the republic of Turkey.
Four filter questions were used to enable us to get the target population and to facilitate a reliable
response. The first question was whether the participants travel or go for holidays domestically and the
number of times they did travel. If the response was yes, then the participant was redirected to the next
question. Otherwise, a message saying “thank you for your interest, but you are not among the target
audience” was displayed.
Based on the results 64 percent (449) travels 1–3 times per year, 29 percent travels 4–6 times per year,
and the rest travels 6 times or more per year. The third question was where the respondents purchased
flight tickets and booked hotel rooms and tours; 67 percent of them made reservation and purchased
online, while 33 percent conducted their transactions through travel agencies. Two respondents volun-
teered to add comments; they stated that they conducted transactions via travel agencies in order to reduce
uncertainty and risks. The fourth filter question was “Do you check websites like TripAdvisor before your
booking or reservation?” Seventy-five percent of the respondents said yes, while others said no.
A total of 2,114 participated in the online survey that lasted for two months between June and August
2014. At the end, only 700 valid questionnaires were used for data analysis; we eliminated those with
missing data. The response rate was 33 percent. Table 1 presents the demographic breakdown of the
sample (n = 700). Most of the respondents were male 76 percent, thus highlighting male dominance in
oriental countries like Turkey. The overwhelming majority (94 percent) of the respondents aged between
21 years and 30 years, 4 percent of the respondents aged between 41 years and 50 years, and the rest rep-
resented 1 percent of their group, respectively. Forty-six percent of the respondents have a monthly income
between 2000 and 4000TRY and 32 percent of the respondents’ monthly income is below 2000TRY.
Seventy-seven had bachelor’s degrees, 17 percent had higher degrees (Master/PhD). In respect to occupa-
tion, 52 percent of the respondents were students, while 25 percent were employees (Table 1).
Elci et al. 7
Table 1. Respondents’ Profile (n = 700)
Frequency Percentage
Gender
Female 169 24.1
Male 531 75.9
Total 700 100.0
Age
Under 20 8 1.1
21–30 657 93.9
31–40 8 1.1
41–50 27 3.9
Total 700 100.0
Income in TL
Below 2000 222 31.7
2000–4000 319 45.6
4000–6000 95 13.6
Above 6000 64 9.1
Total 700 100.0
Education
High school 47 6.7
Bachelor’s degree 536 76.6
Higher degree 117 16.7
Total 700 100.0
Occupation
Student 362 51.7
Employer 24 3.4
Employee 178 25.4
Retired/Not working 136 19.4
Total 700 100.0
Source: Detailed result of the analyses of authors’ survey instrument.
Exploratory factor analysis utilizing principal component analysis (PCA) with varimax rotation was
applied on all items. The results in Table 2 indicate that all factors were significant, the factor loadings
of the items ranged from 0.48 to 0.93 with Eigenvalue greater than 1. However, one item each was elimi-
nated from e-service and system quality, respectively; this is because the items had cross-loadings. The
analysis yielded two factors which collectively explained 58.95 percent of the variance. The items were
forced to load on one single factor in order to check common method bias (Harman’s single-factor test);
one factor accounts for 38.91 percent of the variance suggesting that the potential threats of common
method bias do not exist (McFarlin & Sweeney, 1992). Alpha values were higher than the cutoff level
0.70 (Nunnally, 1978). The inter-item correlation coefficients presented in Table 2 among the variables
were all below 0.85, suggesting evidence for discriminant validity (Kline, 2005). Thus, the scale items
indicate evidence of internal consistency, convergent, and discriminant validity.
8 Business Perspectives and Research 5(2)
Table 2. Scale Items and Exploratory Factor Analysis Results
Scale Items Factor Loadings Eigenvalue % of Variance α
System Design Quality 6.99 35.66 0.79
e-Service Quality
eSerQual1 0.76
eSerQual 2 0.69
eSerQual3 0.74
eSerQual4 0.75
eSerQual5 *
eSerQual6 0.48
System Quality 0.71
Sys Qual1 0.64
Sys Qual2 *
Sys Qual3 0.67
Sys Qual4 0.86
Information Quality 0.76
InfoQual1 0.83
InfoQual2 0.80
Reservation/Purchase
Intentions 1.95 23.29 0.88
PurInt1 0.92
PurInt2 0.91
PurInt3 0.93
PurInt4 0.76
PurInt5 0.60
Source: Detailed result of the analyses of authors’ survey instrument.
Notes: KMO measure of sampling adequacy = 0.84; Bartletts’ test of sphericity = 9494.1, df = 136, p < 0.001. The total variance
explained by all factors is 58.95 percent. * Dropped as a result of exploratory factor analysis.
Table 3 presents standard deviations, means, and correlation coefficients of the research variables.
According to the evidence, e-service quality positively and significantly relates with booking/reservation/
purchase intention (r = 0.29, p < 0.01). System quality positively and significantly relates with booking/
reservation/purchase intention (r = 0.26, p < 0.01). Information quality positively and significantly relates
with booking/reservation/purchase intention (r = 0.20, p < 0.01). This provides preliminary support for
hypotheses 1, 2, and 3.
To adequately test the hypotheses, we carried out regression analyses (see Table 4). The results show
that e-service quality is positively and significantly related to booking/reservation/purchase intention
(
β
= 0.28, t = 4.16, p = 0.00), that system quality is positively and significantly related to booking/reser-
vation/purchase intention (
β
= 0.18, t = 2.66, p = 0.05), and that information quality is negatively related
Elci et al. 9
to booking/reservation/purchase intention (
β
= –0.17, t = –2.55, p = 0.05). In order to validate our find-
ings, we conducted bootstrapping analysis with a resampling of 10,000 respondents and we have a simi-
lar observation. When the results in Tables 3–5 are collectively considered, this study provides evidence
that H1 and H2 were supported, while H3 was rejected.
Table 3. Means, Standard Deviations (SD), and Correlations of Study Variables
Variables Mean SD 1 2 3 4
1. e-service quality 4.61 0.47 –
2. System quality 4.60 0.57 0.81** –
3. Information quality 4.65 0.63 0.80** 0.80** –
4. Booking/reservation/purchase 4.12 0.90 0.29** 0.26** 0.20** –
Source: Detailed result of the analyses of authors’ survey instrument.
Notes: Composite scores for each variable were computed by averaging respective item scores. ** Correlations are significant
at the 0.01 level.
Table 4. Regression Results: Direct Effects
Dependent Variables and Standardized Regression Weights
Booking/Reservation/Purchase Intention
Step 1
β
t
Variables
e-Service Quality 0.28 4.16**
System Quality 0.18 2.66**
Information Quality –0.17 –2.55*
F25.9** –
∆R20.09 –
Source: Detailed result of the analyses of authors’ survey instrument.
Note: * p < 0.05, ** p < 0.01.
Table 5. Bootstrapping Simulation (10,000)
Direct Effect Value Se LL 95% CI UL 95% CI Significance
e-service quality → purchase intention 0.540 0.239 0.378 0.726 0.000
System quality → purchase intention 0.283 0.088 0.115 0.447 0.001
Information quality → purchase intention –0.239 0.069 –0.379 –0.106 0.000
Source: Detailed result of the analyses of authors’ survey instrument.
Discussion of Findings
Our study result shows that system quality and e-service quality are positively related to booking/reser-
vation/purchase intentions. This finding is aligned with prior study of consumer behavior of travel web-
site users (Law & Bai, 2008). The current study also supports the notion that e-service quality will
10 Business Perspectives and Research 5(2)
influence tourists’ booking/reservation/purchase behaviors; and the finding is in line with prior studies
(Fassnacht & Köse, 2007). As a next step, the findings also asserted that system quality significantly
influences tourists’ booking/reservation/purchase intention. Prior studies also noted that system quality
has the potentials to influence booking, or reservation behaviors of tourists (Kim & Niehm, 2009).
Finally, the study also supports the notion that information quality will influence tourists’ booking/
reservation/purchase behaviors. However, the current findings show that the relationship is negative.
This is surprising as prior scholars have shown a positive relationship between the variables in question
(e.g., Lin & Lu, 2000). A possible explanation for the contradicted findings might arise from the sample
in our study, in the sense that they had a bad experience with travel websites.
Fundamental difference has been found between male and female orientation toward the use of social
media and travel website. Wolin and Korgaonkar (2005) argued that men are more disposed to online
advertisement than women. Abubakar (2012) however opined that women lurk online more than men.
Our demographic result showed 75.9 percent men to women ratio, indicating a significant male domi-
nant study context; hence, we inferred that the negative association between information quality and
booking/reservation/purchase intention is largely attributed to the masculinity of our study sample.
Similarly, 93.3 percent of our respondents had bachelor’s degree or higher level of education.
This implies that our study sample comprises of highly educated and knowledgeable individuals who
can easily filter out vital information, hence a possible justification for negative association of informa-
tion quality to booking/reservation/purchase intention.
Lastly, Kotler and Keller (2006) argued that generational cohort relate, act, behave and have similar
outlook and values. Generation Xers known for their technology competence and use of website and the
Internet in general accounts for 93.9 percent of our sample. This implies that the expectation of genera-
tion Xers in travel websites will be more inclined toward the system quality and design than information
quality, hence providing a further support for the result of our third hypothesis.
Conclusion
Given the fact that e-travel sites are a competitive business tool, we examined the effectiveness of web-
sites design quality on booking/reservation/purchase behavioral intentions from a traveler’s perspective.
Our research aims to extend the body of knowledge regarding the effect of e-service, system, and infor-
mation quality on booking/reservation/purchase intention, due to the fact that travelers plan trips with the
help of the Internet. The credo behind this study is to provide tourism enterprises a nuanced understand-
ing regarding the interaction of the aforementioned variables.
System quality can be measured by tourist perceived degrees of user-friendliness in e-travel sites;
thus, the perception of positive online system quality is very critical. The impact of previous, present,
and potential travelers’ positive experiences is not only limited in determining the continued intention to
do business with the firm but also increases trust and incite confidence. On the other hand, unpleasant
experience ruins the image and changes the travelers’ impressions about system quality of the e-travel
site; thus, this may discourage them from returning to the website. Prompt replies, answering of inqui-
ries, return policies, and security assurance may enhance e-service quality. E-service quality is essential
for the retention of customer’s e-travel sites; hence, marketers and managements should apply effective
relationship management systems. E-service quality and system quality exert a greater influence on
travelers’ retention, long-term relationship, as well as increased loyalty. Information quality is essential
in both stages (pre and post purchase): it is one of the critical success factors for e-travel sites; for
example, prices of airline tickets keep changing.
Elci et al. 11
Managerial Implication
Firms should take note that travelers uses the attributes of information, that is, information format and
content to interpret the message communicated and their understanding of it. Thus, tourism managers
should make sure that e-travel sites’ format and content are in accordance with customers’ perspectives, for
example, by conducting customer polls. In this respect, the online atmosphere has to accommodate infor-
mation seekers or travelers by offering better e-service, system, and information qualities. Tourism policy
planners and marketers should also consider taking account of this in order to enhance their competitive
advantage because their success depends on the volume of transaction.
Hoteliers and hospitality managers should pay more attention to the perception of travelers
through their contribution via Travel 2.0 website. This is because the strong perception of e-service
quality and system quality will result in improved business for the industry. E-service quality should
not be considered as a mere measure of customer satisfaction but should be regarded as an overall
experience of service excellence.
Limitation and Future Direction
Cross-sectional design and self-report measures are the shortcomings of the study. In addition, the study
was conducted online; thus, the validity and suitability of the respondents may be questionable. Finally,
the study is only applicable to Turkey. The article also failed to consider the effects of website trust and
brand image. Hence, the outcome of this study should be considered with caution. We encourage future
researchers to investigate the impact of website trust as a moderator in the relationship between informa-
tion system and e-service quality and booking/reservation/purchase intention. In addition, there is a need
to evaluate and research how businesses can integrate and encourage Travel 3.0 in their business model.
References
Abubakar, A.M. (2012). Impact of IT on business: eWOM and the three w’s (who, why, and what) (Thesis). Eastern
Mediterranean University, Famagusta, North Cyprus.
———. (2016). Does eWOM influence destination trust and travel intention: A medical tourism perspective.
Economic Research-Ekonomska Istraživanja, 29(1), 598–611. doi: 10.1080/1331677X.2016.1189841
Arsal, I., Backman, S., & Baldwin, E. (2008). Influence of an online travel community on travel decisions.
In P. O’Connor, W. Höpken, & U. Gretzel (Eds), Information and communication technologies in tourism
(pp. 82–93). New York, NY: Springer Wien.
Ayeh, J.K., Au, N., & Law, R. (2013). Predicting the intention to use consumer-generated media for travel planning.
Tourism Management, 35, 132–143.
Baloglu, S., & Pekcan, Y.A. (2006). The website design and Internet site marketing practices of upscale and luxury
hotels in Turkey. Tourism Management, 27(1), 171–176.
Bernroider, E.W.N. (2008). IT governance for enterprise resource planning supported by the DeLone–McLean
model of information systems success. Information and Management, 45(5), 257–269.
Breitenbach, C., & Van Doren, D. (1998). Value-added marketing in the digital domain: Enhancing the utility of the
Internet. Journal of Consumer Marketing, 15(6), 558–575.
Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10
years after the Internet the state of Tourism research. Tourism Management, 29(4), 609–623.
Cai, L., Card, J.A., & Cole, S.T. (2004). Content delivery performance of world wide websites of US tour operators
focusing on destinations in China. Tourism Management, 25(2), 219–227.
Casaló, L.V., Flavián, C., Guinalíu, M., & Ekinci, Y. (2015). Do online hotel rating schemes influence booking
behaviors? International Journal of Hospitality Management, 1(49), 28–36.
12 Business Perspectives and Research 5(2)
DeLone, W.H., & McLean, E.R. (2002). Information systems success revisited. In System Sciences, 2002. HICSS.
Proceedings of the 35th Annual Hawaii International Conference on (pp. 2966-2976). IEEE.
———. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of
Management Information Systems, 19(4), 9–30.
———. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success
model. International Journal of Electronic Commerce, 9(1), 31–47.
Dwivedi, Y.K., Wade, M.R., & Schneberger, S.L. (2012). Information systems theory (pp. 323–347). Vol. 2. New
York, NY, USA: Springer.
Fang, Y.H., Chiu, C.M., & Wang, E.T.G.G. (2011). Understanding customers’ satisfaction and repurchase intentions:
An integration of IS success model, trust, and justice. Internet Research, 21(4), 479–503.
Fassnacht, M., & Köse, I. (2007). Consequences of web-based service quality: Uncovering a multi-faceted chain of
effects. Journal of Interactive Marketing, 21(3), 35–54.
Hashim, N.H., Murphy, J., & Law, R. (2007). A review of hospitality website design frameworks. In M. Sigala, L.
Mich, J. Murphy (Eds), Information and Communication Technologies in Tourism 2007 (pp. 219–230),
Proceedings of the International Conference in Ljubljana, Slovenia, 2007.
Ho, C.I., & Lee, Y.L. (2007). The development of an e-travel service quality scale. Tourism Management, 28(6),
1434–1449.
Hsu, M.H., Ju, T.L., Yen, C.H., & Chang, C.M. (2007). Knowledge sharing behavior in virtual communities: The
relationship between trust, self-efficacy, and outcome expectations. International Journal of Human-Computer
Studies, 65(2), 153–169.
Jeong, M., Oh, H., & Gregoire, M. (2003). Conceptualizing website quality and its consequences in the lodging
industry. International Journal of Hospitality Management, 22(2), 161–175.
Kasavana, L.K., Knuston, B., & Polonowski, S.J. (1997). Netlurking: The future of hospitality internet marketing.
Journal of Hospitality & Leisure Marketing, 5(1), 31–44.
Kim, H., & Niehm, L.S. (2009). The impact of website quality on information quality, value, and loyalty intentions
in apparel retailing. Journal of Interactive Marketing, 23(3), 221–233.
Kline, R. (2005). Principles and practice of structural equation modeling (2nd ed.). New York, NY: The Guilford
Press.
Kotler, P., & Keller, K.L. (2006). Marketing management 12e. New Jersey.
Law, R., & Bai, B. (2008). How do the preferences of online buyers and browsers differ on the design and content of
travel websites? International Journal of Contemporary Hospitality Management, 20(4), 388–400.
Lin, H.F. (2007). Measuring online learning systems success: Applying the updated DeLone and McLean model.
Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and
Society, 10(6), 817–820.
Lin, C. (2010). Examining e-travel sites: An empirical study in Taiwan. Online Information Review, 34(2), 205–228.
Lin, J.C.C., & Lu, H. (2000). Towards an understanding of the behavioral intention to use a website. International
Journal of Information Management, 20(3), 197–208.
Liu, C., Arnett, K.P., & Litecky, C. (2000). Design quality of websites for electronic commerce: Fortune 1000
webmasters’ evaluations. Electronic Markets, 10(2), 120–129.
Lowry, P.B., Vance, A., Moody, G., Beckman, B., & Read, A. (2008). Explaining and predicting the impact of
branding alliances and website quality on initial consumer trust of e-commerce websites. Journal of Management
Information Systems, 24(4), 199–244.
Lu, J. (2004). Development, distribution and evaluation of online tourism services in China. Electronic Commerce
Research, 4(3), 39–221.
Marcussen, C. (2009). Trends in European internet distribution: Of travel and tourism services. Retrieved March
25, 2010, from http://www.crt.dk/UK/staff/chm/trends.htm
McFarlin, D.B., & Sweeney, P.D. (1992). Distributive and procedural justice as predictors of satisfaction with
personal and organizational outcomes. Academy of Management Journal, 35(3), 626–637.
Merinero-Rodríguez, R., & Pulido-Fernández, J.I. (2016). Analysing relationships in tourism: A review. Tourism
Management, 54, 122–135.
Elci et al. 13
Mullen, T. (2000). Travel’s long journey to the web. Internet Week, 835, 103–106.
Nunnally, J.C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
Park, Y.A., & Gretzel, U. (2007). Success factors for destination marketing websites: A qualitative meta-analysis.
Journal of Travel Research, 46(1), 46–63.
Park, Y.A., Gretzel, U., & Sirakaya-Turk, E. (2007). Measuring website quality for online travel agencies. Journal
of Travel & Tourism Marketing, 23(1), 15–30.
Perdue, R.R. (2002). Internet site evaluations: The influence of behavioral experience, existing images, and selected
website characteristics. Journal of Travel & Tourism Marketing, 11(2/3), 21–38.
Petter, S., & McLean, E.R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An
examination of IS success at the individual level. Information and Management, 46(3), 159–166.
Porter, M. (2001). Strategy and the Internet. Harvard Business Review, 79(3), 63–78.
Pudliner, B.A. (2007). Alternative literature and tourist experience: Travel and tourist weblogs. Journal of Tourism
and Cultural Change, 5(1), 46–59.
Qu, H., & Lee, H. (2011). Travelers’ social identification and membership behaviors in online travel
community. Tourism Management, 32(6), 1262–1270.
Shchiglik, C., & Barnes, S.J. (2004). Evaluating website quality in the airline industry. Journal of Computer
Information Systems, 44(3), 17–25.
Smith, A.D. (2004). Information exchanges associated with Internet travel marketplaces. Online Information
Review, 28(4), 292–300.
TURSAB. (2014). Development Of Turkish Tourism In Brief. Retrieved September 4, 2014, from http://www.tursab.
org.tr/en/statistics/development-of-turkish-tourism-in-brief/turkish-tourism-industry-today_1075.html
Tussyadiah, I., & Fesenmaier, D.R. (2009). Mediating tourist experiences: Access to places via shared videos.
Annals of Tourism Research, 36(1), 24–40.
Van der-Heijden, H. (2003). Factors influencing the usage of websites: The case of a generic portal in the Netherlands.
Information & Management, 40(6), 541–549.
Wan, C.S. (2002). The web sites of international tourist hotels and tour wholesalers in Taiwan. Tourism Management,
23(2), 155–160.
Wang, F., Head, M., & Arthur, N. (2002). E-tailing: An analysis of web impacts on the retail market. Journal of
Business Strategies, 19(1), 73–93.
Wang, Y.S., & Liao, Y.W. (2008). Assessing egovernment systems success: A validation of the DeLone and McLean
model of information systems success. Government Information Quarterly, 25(4), 717–733.
Wen, I. (2009). Research in brief factors affecting the online travel buying decision: A review. International Journal
of Contemporary Hospitality Management, 21(6), 752–765.
Werthner, H., & Klein, S. (1999). Information technology and tourism: A challenging relationship. Vienna: Springer.
Wolin, L.D., & Korgaonkar, P. (2005). Web advertising: Gender differences in beliefs, attitudes, and behavior.
Journal of Interactive Advertising, 6(1), 125–136.
Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management,
31(2), 179–188.
Xiang, Z., Wober, K., & Fesenmaier, D.R. (2008). Representation of the online tourism domain in search engines.
Journal of Travel Research, 47(2), 137–150.
Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An
empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human
Behavior, 27(2), 634–639.
Yi, Y., & Gong, T. (2008). The electronic service quality model: The moderating effect of customer self-efficacy.
Psychology and Marketing, 25(7), 587–601.
