1. International Journal of Hospitality Management 30 (2011) 897–907
Contents lists available at ScienceDirect
International Journal of Hospitality Management
journal homepage: www.elsevier.com/locate/ijhosman
Structural effects of cognitive and affective reponses to web advertisements,
website and brand attitudes, and purchase intentions: The case of casual-dining
restaurants
Johye Hwang a,1 , Yoo-Shik Yoon a,∗ , No-Hyeun Park b
a
College of Hotel & Tourism Management, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul 130-701, Republic of Korea
b
Department of E-Digital Information Business, Sejong University, Republic of Korea
a r t i c l e i n f o a b s t r a c t
Keywords: This study investigates the structural relationships among responses to website advertisements, website
Website advertising attitudes, brand attitudes, and purchase intentions in the case of web advertisements for casual-dining
Cognitive response restaurants. Responses toward advertising (Rad) factors were categorized as cognitive responses and
Affective response
affective responses. The SEM model in LISREL was used to examine the interrelationships among the
Website attitudes
proposed hypothesized constructs. Several empirical results were obtained. First, Rad had a positive
Brand attitudes
Purchase intentions effect on website attitudes. Second, website attitudes had a positive effect on brand attitudes. Third,
Structural equation modeling brand attitudes had a positive effect on purchase intentions. Finally, some discussion and implications of
the study are provided.
© 2011 Elsevier Ltd. All rights reserved.
1. Introduction Internet. Our study focuses on understanding the effectiveness of
online advertisements, that have the primary goal of enticing cus-
Websites are now considered as an effective marketing and tomers to buy products and services in restaurants. Customers can
advertising tool to provide information about products and services participate in a process of measuring website effectiveness (Law
(Buhalis and Law, 2008). While navigating a website, customers et al., 2010), based on the observation that the effectiveness of a
have the opportunity to formulate opinions about the products and television or newspaper advertisement can be measured through
services offered as well as the company offering them. Customers viewer or reader reactions (Chen and Wells, 1999). Using such
can respond positively or negatively to a particular advertisement. methods, advertisers and marketers can study consumer reactions
Customers who have more positive attitudes toward advertising and how these reactions influence buying preferences.
are more likely to be persuaded by advertising (Mehta, 2000). How- Advertisement attitude refers to the formation of a positive or
ever, a poor quality web may result in a loss of both potential sales negative reaction to a particular advertisement through exposure
and repeated visits (Cunliffe, 2000). Because electronic commerce to that advertisement (MacKenzie et al., 1986). Various cognitive
applications, such as online advertising, have become a general and and emotional components comprise this reaction. Although each
dominant business model (Yang, 2003), it is important to under- component has received significant attention in the traditional
stand how customers perceive or react to web advertising and what advertising context, they have not been fully investigated in the
components affect their attitudes and behaviors toward products domain of online advertising. In addition, prior research has inves-
and services advertised online. It would also be valuable to know tigated cognitive and affective responses separately rather than
whether the effectiveness of Internet advertising leads to purchases simultaneously. While traditional advertising influences consumer
of the advertised products or services. attitudes through cognitive and affective processes (Lutz, 1985), it
Online advertisements that include banner ads, text ads, inter- remains unclear whether the traditional model that explains the
stitial ads, pop-up ads, and HTML ads exist as the dominant media relationship between advertisements and affective responses still
that companies use to market their products and services via the holds for online advertising. Therefore, it is worthwhile to consider
cognitive and affective responses simultaneously when studying
the impact of online advertising. Through such considerations, we
can clarify which of these two processes is more strongly elicited
∗ Corresponding author. Tel.: +82 2 961 9274.
by online advertising.
E-mail addresses: hwangj@khu.ac.kr (J. Hwang), ysyn@khu.ac.kr (Y.-S. Yoon),
Once an advertisement attitude is formed, it can influence
parknhn@hanmail.net (N.-H. Park).
1
Tel.: +82 2 961 2241. downstream behaviors including brand attitudes and purchasing
0278-4319/$ – see front matter © 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ijhm.2011.01.011

2. 898 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907
Table 1 Researchers have recognized the need for a more sophisticated
Recent five years of studies on eBusiness applications in hospitality and tourism.
model to integrate theories from other disciplines (Law et al.,
Industry sector Focus Author(s) and year 2010). For instance, previous and current studies of website evalu-
Hotel Online booking Chiang and Jang (2007) ation in tourism and hospitality have been limited to quantitative
Dabas and Manaktola (2007) (i.e. counting, automated, numerical computation, and user sat-
Morosan and Jeong (2008) isfaction) and qualitative approaches focusing on attributes of
Noone and Mattila (2009) websites such as information, quality, security, functionality, cus-
Noone and Mattila (2009)
tomer relationships, and responsiveness (Ho and Lee, 2007; Law
Rong et al. (2009)
Online review Vermeulen and Seegers (2009) et al., 2010). Therefore, our study narrows the research gap by
Ye et al. (2009) borrowing a theoretical model that integrates cognitive and affec-
Ye et al. (2011) tive responses from psychology, which has also been applied in
Website Bai et al. (2008)
a traditional advertising context, to understand how customers
quality/effectiveness Chan and Law (2006)
Hashim et al. (2007) form their perceptions toward online advertising in the restaurant
Kaplanidou and Vogt (2006) industry.
Law and Cheung (2006)
Schmidt et al. (2008)
2. Theoretical background
Casino Employee learning through Lema and Agrusa (2009)
website
Travel Travel agent’s Internet Vrana and Zafiropoulos (2006) 2.1. Website advertisement
adoption
Website quality Law and Bai (2008) To create bran images, advertisements inform consumers of
Law et al. (2010)
the uses and benefits of products. Virtual symbols connected with
Park et al. (2007)
Tsang et al. (2010) these products should be clearly explained to effectively promote
Wang et al. (2007) product sales (Ku and Cho, 2000). New kinds of multimedia adver-
Wen (2009) tisements called digital advertisements include the use of computer
Travelers’ information Kim et al. (2007) networks or computer software instead of TV, magazines or news-
searching behavior Lee et al. (2007)
E Word-of-mouth Litvin et al. (2008)
papers. Internet advertising is one kind of digital advertisement
that has become an effective means of marketing communication
because Internet access is widespread, and the number of users
continues to grow. Accordingly, businesses encourage Internet use
intentions. Although researchers have been interested in what
as a tool for value realization and profit creation. In this environ-
impact these attitudes may have on brand attitudes, purchasing
ment, the greatest goal for a company is to have a website that
intentions, and behavior, previous studies have lacked a holistic
generates significant visitor traffic and, hopefully leads to sales.
view that focuses on structural effects among the antecedents and
Internet advertisements are unique in that consumers visit the
precedents of web advertising attitudes. In recognizing this lack, we
advertisements; in the case of traditional print and TV media,
have defined the factors determining consumer attitudes, namely,
advertisements are placed in front of viewers. Web advertisements
both cognitive and affective responses, and explored whether these
can be classified according to seven characteristics: unlimited
two responses were factors in forming opinions about a restau-
open-endedness of time and space, two-way communication, pos-
rant’s website. The study also aims to understand how these two
sible linkage with databases, one-stop shopping, which facilitates
responses ultimately influence consumer reactions to restaurant
product purchases, free sponsorship, and various forms of adver-
brands as well as their purchasing decisions.
tising. Alternatively, Jang (1998) stated that the characteristics of
Numerous studies on Internet marketing have been conducted
Internet advertising include constant availability, low cost, fun,
in hospitality and tourism contexts, but they have been limited
connectivity, internationalization, interaction, and two-way com-
to hotel (Chan and Law, 2006; Chiang and Jang, 2007; Dabas and
munication.
Manaktola, 2007; Hashim et al., 2007; Kaplanidou and Vogt, 2006;
Ducoffe (1996) described the special quality of Internet
Law and Cheung, 2006; Morosan and Jeong, 2008; Noone and
advertising in terms of quick-access to information, customer
Mattila, 2009; Rong et al., 2009; Schmidt et al., 2008; Vermeulen
preference-based information, flexibility to customer preferences
and Seegers, 2009; Ye et al., 2009, 2011) or tourism websites (Kim
and the changing environment, preference and purchase track-
et al., 2007; Law and Bai, 2008; Law et al., 2010; Lee et al., 2007;
ing, and the capability of forming stronger relationships with
Litvin et al., 2008; Park et al., 2007; Tsang et al., 2010; Vrana and
customers. Therefore, web advertisements must be visually capti-
Zafiropoulos, 2006; Wang et al., 2007; Wen, 2009). These studies
vating, share interesting content, and be easy to navigate (Brigish,
have focused on website features that affect how customers book
1993).
hotel rooms or travel destinations. Table 1 briefly describes the top-
ics of such studies on the hospitality and tourism industries from
the last five years. Although the restaurant industry has potential 2.2. Response of website advertising: cognitive and affective
for Internet marketing, including web advertising, studies on online responses
advertising in this industry have been scarce. Though dated, one
exception was an empirical study by Litvin et al. (2005), who con- Attitude-toward-an-advertisement has been defined as ‘a pre-
ducted a survey to determine how travelers used the Internet to disposition to respond in a favorable or unfavorable manner to
select a restaurant in a vacation setting. Although restaurant man- a particular advertising stimulus during a particular exposure
agers have attempted to attract customers by investing in websites, occasion’ (Lutz, 1985, p. 46). It is important to understand cus-
these managers have no knowledge of their preferences and behav- tomer attitudes because attitudes can generally predict customer
iors of their e-customers with respect to website advertisements. purchasing intentions and behavior (Oliver, 1980; Shih, 2004).
Therefore, the results of this study should be useful to restaurant Moreover, consumers are more likely to have a stronger intention to
marketers by examining the conceptual linkages among responses purchase a product when they react favorably to an advertisement
(i.e., cognitive and affective) to web advertisements, websites and about that product (Haley and Baldinger, 2000; MacKenzie and
brand attitudes, and purchase intentions of restaurant customers. Lutz, 1989). This logic has been proven with respect to attitudes-

3. J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 899
toward-a-website (Bruner and Kumar, 2005). However, it still tisement and brand attitudes. However, while Holbrook and Batra
remains unclear how attitudes toward online content are formed (1987) could not prove that affection directly influences brand atti-
because online advertising has only existed for approximately tudes, Burke and Edell (1989) found that the affection inspired by
two decades (Karson et al., 2006). The first study that specifically an advertisement directly influences brand attitudes.
addressed attitudes toward online advertising appears to be a study Although affective responses have been investigated in the con-
by Ducoffe (1996), which explored the antecedents of consumer text of traditional advertising, they have not been fully investigated
attitudes toward website advertising.The most recent studies eval- in the domain of online advertising. It remains unclear whether the
uating website effectiveness and quality in tourism and hospitality traditional model that explains the relationship between an adver-
have focused on website design and performance features (Bai tisement and the affective responses to the advertisement holds
et al., 2008; Baloglu and Pekcan, 2006; Bevanda et al., 2008; Chan for the case of online advertising. With regard to online adver-
and Law, 2006; Han and Mills, 2006; Hu, 2009; Law, 2007; Lu tising, a study by Ducoffe (1996) demonstrated that an affective
et al., 2007; Park et al., 2007; Schmidt et al., 2008; Stockdale and factor, such as entertainment, could still play a significant role in
Borovicka, 2007; Zafiropoulos and Vrana, 2006). Those studies have influencing attitudes. Furthermore, another study by Raney et al.
focused on the features and functions that determine customer (2003) focused on one emotional component, namely, arousal, and
booking behavior. Furthermore, in relation to online advertising, indicated that interactive and entertaining websites that included
the majority of studies have been limited to the impact of online a mini-film of an automotive brand included high arousal, which
advertising characteristics (i.e., format, design, content, and fre- facilitated the processing of brand-related information. Based on
quency) on purchasing behavior (Campbell and Wright, 2008; Coyle this evidence, and in conjunction with the traditional view about
and Thorson, 2001; Johnson et al., 2006; Moe and Fader, 2004; the relationship between affective responses and advertisement
Stevenson et al., 2000). Thus, such approaches fail to identify attitudes, it is reasonable to assume that websites influence vari-
how consumers form attitudes toward online advertising. Previous ous affective responses in addition to arousal.Studies on attitude
studies have focused on the characteristics of online advertis- formation have been mainly conducted with regard to traditional
ing that influence customer attitudes by considering the unique advertising. It appears that both cognitive and affective responses
characteristics of the Internet as opposed to offline advertising are involved in forming attitudes, although it is a matter of debate
(Campbell and Wright, 2008; Coyle and Thorson, 2001; Johnson as to which component influences attitudes more (Brown and
et al., 2006; Peng et al., 2004). These studies identified interac- Stayman, 1992; Zajonc and Markus, 1982). Furthermore, studies
tivity as a unique characteristic that influences attitudes toward involving online advertising have focused on cognitive and affective
online advertising. For example, unlike traditional media such as responses separately, but none have investigated the simultane-
television and radio, online advertising provides a great deal of ous impact of both constructs on attitudes with regard to online
interactivity, and this interactivity has a direct effect on attitudes advertising. It is still uncertain which process (i.e., cognitive or
toward websites. Although there are only a few examples of this affective) is elicited more by online advertising. Therefore, the
type of study, some researchers have addressed antecedents of present study addresses the following questions. Which process,
attitudes toward online advertising (ATOA hereafter), arguing that cognitive or affective, has a stronger effect on attitudes toward
ATOA has both cognitive and affective antecedents (Ducoffe, 1996; online advertising in the restaurant industry? Does the cognitive
Shimp, 1981). Given that traditional advertising influences con- process contribute more to attitude than the affective process or
sumer attitudes through cognitive and affective processes (Lutz, vice versa? A more accurate understanding of the formation of atti-
1985), the same logic can be assumed to apply to online advertis- tudes toward online advertising should offer useful implications for
ing.As a cognitive predictor, belief, which is defined as consumer restaurant marketers who wish to effectively design online adver-
perceptions about the benefits and costs incurred by advertis- tising by positively influencing cognitive and affective responses.
ing, was found to form ATOA (Wang et al., 2009; Wolin et al.,
2002). More specifically, consumer beliefs that Internet advertising 2.3. Relationships among advertisement responses, website
provides information and contributes to economic development attitudes, brand attitudes, and purchase intentions
served to positively influence their attitudes toward online adver-
tising (Wang et al., 2009). Ducoffe (1996) demonstrated that the Studies of traditional advertising have shown that attitudes
ability of Internet advertising to inform contributes to consumer toward advertising carry a positive purchase intention (MacKenzie
attitudes. Due to the highly informative nature of online adver- and Lutz, 1989; MacKenzie et al., 1986). Recent studies of online
tising, cognitive processes might be viewed as a dominant factor advertising have also shown a positive relationship between atti-
composed of attitudes toward online advertising (Schlosser et al., tude and purchase intentions and between attitude and behavior,
1999). such as the likelihood of buying, online visitations, and online shop-
Advertising stimuli can also influence the affective responses of ping frequency (Bruner and Kumar, 2005; Karson and Fisher, 2005;
customers. Studies have indicated a positive relationship between Korgaonkar and Wolin, 2002; Stevenson et al., 2000; Wang et al.,
an advertisement in general and the affective responses of cus- 2009; Wolin et al., 2002). Previous studies have included purchase
tomers (Aaker and Stayman, 1990; Brown and Stayman, 1992). intentions as a key indicator of the success of online advertise-
For example, within the traditional media of advertisements, the ments (Brown and Stayman, 1992; Moe and Fader, 2004; Raney
impact of arousal has long been established (Lang, 1994). An adver- et al., 2003). While it is straightforward that this attitude relates
tisement can create positive and negative feelings, as customers positively to purchase intentions, the factors that mediate the rela-
may find themselves amused, delighted, playful, warm, affection- tionship between attitudes and intentions are unclear.
ate, contemplative, hopeful, critical, defiant, or offended (Edell and Brand attitude is the most prevalent mediator included in mod-
Burke, 1987). Studies have suggested that positive and negative els of advertising attitudes. Brown and Stayman (1992) conducted
feelings about an advertisement are important in explaining the a meta-analysis of the antecedents and consequences of attitude
effects of advertising. Holbrook and Batra (1987) showed that the toward advertising in traditional media. They confirmed the results
affective response has a significant relationship with advertise- of other studies on the direct impact of advertisement attitudes
ment attitudes and brand attitudes. Affection directly influences on brand attitudes and that of brand attitudes on purchase inten-
advertisement attitudes and indirectly influences brand attitudes tions (Homer, 1990; MacKenzie and Lutz, 1989; Stayman and Aaker,
through advertisement attitudes. In addition, Burke and Edell 1988). Furthermore, Ind and Riondino (2001) noted that the inter-
(1989) found that affection directly and indirectly influences adver- active nature of online influences could strengthen the relationship

4. 900 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907
Cognitive Response
(ξ1)
H1a H2a H3a
Website Attitude H4 Brand Attitude H5 Purchase Intention
(η1) (η2) (η3)
H1b H2b H3b
Affective Response
(ξ2)
Fig. 1. The hypothesized proposed model.
between the consumer and the organization, thus contributing between website attitudes and brand attitudes, both of which in
to brand management. It appears that when consumers respond turn are positively related to purchase intentions. Consequently,
positively to websites, they are more likely to remember the cor- the proposed model in this study examines the structural and
responding brands and hold positive brand attitudes (Mitchell and causal relationships among cognitive and affective responses, web-
Olson, 1981; Shimp, 1981). site attitudes, brand attitudes, and purchase intentions.Research
Some studies have tested a model that incorporated brand atti- hypotheses were developed from the proposed model depicted in
tudes as a mediator in the relationship between attitude toward Fig. 1.
a website and purchasing behavior (Miniard et al., 1990; Keller,
H1a. The cognitive response to a web advertisement has a positive
1993). The findings from those studies, however, were not con-
influence (+) on website attitudes.
sistent. While Miniard et al. (1990) and Keller (1993) supported
the mediating role, while Karson and Fisher (2005) did not. Fur- H1b. The affective response to a web advertisement has a positive
thermore, studies on brand attitudes have been limited to specific influence (+) on website attitudes.
products. For instance, Karson and Fisher (2005) tested a model
that incorporated brand attitudes as a mediator in the relation- H2a. The cognitive response to a web advertisement has a positive
ship between the attitude toward a website and the intention to influence (+) on brand attitudes.
repurchase digital cameras (SiPix) and watches (Fossil) and con-
H2b. The affective response to a web advertisement has a positive
tribute to a charity (the Special Olympics). Their findings indicated
influence (+) on brand attitudes.
that the relationship between attitudes and intentions was direct
and independent of brand attitudes. The study’s findings did not H3a. The cognitive response to a web advertisement has a positive
support the traditional view that brand attitudes mediate the rela- influence (+) on purchase intentions.
tionship between attitudes and intentions. The authors explained
that the non-significance of brand attitudes in the relationship can H3b. The affective response to a web advertisement has a positive
be ascribed to the irrelevance of the information provided on the influence (+) on purchase intentions.
website regarding the claims about the brand under consideration. H4. Website attitudes has a positive influence (+) on brand atti-
Furthermore, the study findings could not be generalized to a broad tudes.
line of products because the investigation of the relationship was
limited to specific products. Brown and Stayman (1992) have noted H5. Brand attitudes has a positive influence (+) on purchase inten-
that the product type significantly affects advertisement attitudes tions.
and brand cognitions. So far, few studies on online advertisements
have paid attention to the brands of service organizations, including 3.2. Study method
brands in the restaurant industry.
3.2.1. Measurement scale
3. Methodology A questionnaire was developed based on a thorough review of
the literature and a pilot study using onsite surveys at ten fam-
3.1. The proposed model ily restaurants. Manipulation checks were conducted to ensure the
reliability and validity of the scales.
Based on the literature review discussed in the previous sec- Critical factors for website attitudes were constructed in terms
tion, we propose the following hypothesized model (Fig. 1). We of two parts: cognitive response and affective response. Cognitive
propose that responses to website advertisements, which con- response scales were used to measure responses to 16 items based
sist of cognitive and affective responses, influence advertisement on the adjectives used in the studies by Chen and Wells (1999)
attitudes, brand attitudes, and purchase intentions. Among these and Bruner (2009). Affective response scales were used to measure
conative responses, we propose a strong positive relationship responses to 16 items based on the adjectives used in the studies

5. J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 901
by Edell and Burke (1987) and Bruner (2009), focusing on particu- To examine the proposed research hypotheses regarding the
larly emotional items. Once initial items were selected based on the interrelationships among the constructs, structural equation mod-
literature review, the selected items were examined to find other eling (SEM) with a maximum likelihood (ML) method was
items for revision or addition to target restaurant customers. From employed in the LISREL program. Using SEM procedures, the
this process of ensuring content validity, 32 items, including 16 properties were tested with five constructs (two exogenous con-
cognitive and 16 affective items were developed and finalized for structs for cognitive response and affective responses and three
the questionnaire. These items were measured using a five-point endogenous constructs for website attitudes, brand attitudes, and
Likert’s scale (1 = strongly disagree; 5 = strongly agree). purchase intentions). Two-stage testing processes were adopted.
Website attitude scales were used to measure two items based Covariance matrices were calculated as input data and used to test
on studies by MacKenzie et al. (1986) and Jang (1998): general a hypothesized model. SEM is a reliable and appropriate statistical
website trust and website satisfaction of users toward web adver- technique to evaluate how well a proposed conceptual model that
tisements. These items were measured using a five-point Likert’s contains observed indicators and hypothetical constructs explains
scale (1 = strongly disagree; 5 = strongly agree). The brand attitude or fits the collected data (Bollen, 1989; Yoon and Uysal, 2005; Byrne,
scale measured both general brand trust and satisfaction. The mea- 1998). Following this logic, SEM analysis was adopted to exam-
sured items are the same as those of website attitudes, as listed ine the interrelationships among the constructs as proposed in the
above. These items were measured using a five-point Likert’s scale research hypotheses.
(1 = strongly disagree; 5 = strongly agree). The purchase intention
scale used two items to measure the aroused intention to buy after
seeing a web advertisement (namely, “I will purchase if it is neces- 4. Analysis and results
sary” and “I will visit the store to get what I want to buy”). These
items were measured using a five-point Likert’s scale (1 = strongly 4.1. Demographic profile
disagree; 5 = strongly agree).
According to the results of the reliability tests for the mea- The results of frequency analysis for the respondents (n = 375)
surement scale (i.e. Cronbach’s alpha = .92 for the affective scale showed that there were more females (57.1%, n = 214) than males
and Cronbach’s alpha = .89 for the cognitive scale), the entire mea- (42.9%, n = 161) among the respondents. The proportion of married
surement scale is acceptable and reliable (Nunnally and Bernstein, respondents was 62.3% (n = 233). Completed education levels were
1994). Therefore, further statistical analysis is appropriate using most often bachelor degrees (52.3%, n = 196) or graduate schooling
this scale. (19.8%, n = 74). With regard to the age distribution, 39.7% of the
respondents (n = 149) were 30–39 years old, 35.9% (n = 134) were
3.2.2. Data collection 20–29 years old, and 16.3% (n = 61) were 40–49 years old.
This study employed direct face-to-face surveys. Although an With regard to monthly income level, 25.5% (n = 96) had incomes
onsite survey method is more costly than other methods, this of less than US$2,000, 57% (n = 214) had incomes of US$2001–4000,
method has several benefits, including a high response rate and 11.5% (n = 43) had incomes of US$4001–6000, and 6% (n = 23) had
more accurate responses. Well-trained graduate researchers vis- incomes of over US$6000. Restaurant customers fell into the cate-
ited ten major family restaurants located in the downtown area of gories of families (32.5%, n = 122), friends (21.4%, n = 80), company
Seoul, Korea, and asked their managers to help with our research colleagues (38.6%, n = 145), and other (7.5%, n = 28). Respondents
and survey. The data collection took place from September 1 to stated that reasons for selecting the restaurant included taste
September 30, 2009, with 50% of questionnaires distributed on (59.8%, n = 224), atmosphere (21.7%, n = 81), service (12.8%, n = 48),
weekdays and 50% of questionnaires distributed during weekends. and price (6.5%, n = 24).
The ten restaurants selected for this study are internationally fran-
chised restaurants, including Outback Steakhouse, TGI Friday’s, and
Bennigan’s. These restaurants were selected based on having yearly 4.2. Exploratory factor analysis of cognitive and affective
revenues within the top 20 franchised restaurants according to the responses of website advertisements
Korea Franchise Association (2010). Brand popularity and manager
permission to collect data were also considered. Customers enter- First, the correlation matrix and anti-image correlation were
ing the restaurant and agreeing to participate were first asked if inspected to evaluate the adequacy of exploratory factor anal-
they had experience seeing web advertisements, including banner ysis to check whether the correlation matrix collected for this
ads, text ads, interstitial ads, pop-up ads, and HTML ads for these study was well-suited for factor analysis. Based on the results
targeted family restaurants. If they had seen such advertisements of the correlation matrix with Bartlett’s test of sphericity and
in the month prior to the survey date, they continued to com- the Kaiser–Meyer Oklin (KMO) measure of sampling adequacy
plete the given questionnaires. While they completed the survey (cognitive responses = 0.808, p < 0.001; affective responses = 0.809,
questionnaire, beverages such as soda or cups of coffee were pro- p < 0.001), the variables and data in this study were found to be
vided as a reward. Overall, 400 survey questionnaires were equally appropriate for exploratory factor analysis.
distributed at each of the ten different restaurants (i.e., 40 question- As shown in Table 2, 16 items examining the cognitive responses
naires per restaurant) during the dinner service period of selected of participants to web advertisements were factor-analyzed with
business days. Finally, the study utilized a total of 375 useful ques- a varimax rotation under the principal component method at an
tionnaires after deleting incomplete survey questionnaires. eigenvalue of 1.0. Three factors were extracted that explained 57.8%
of the total variance. After examining the variables and their char-
3.3. Data analysis acteristics in the factor, three dimensions of cognitive responses to
web advertisements were identified: ‘informativeness’ (seven vari-
Basic statistics were conducted as assumption tests for the ables, eigenvalue = 5.486, explained variance = 34.3%) ‘inaccuracy’
study. Missing data, outliers, normality, and multicollinearity were (five variables, eigenvalue = 2.589, explained variance = 16.2%), and
checked to purify the data and remove systematic errors. The ‘reliability’ (three variables, eigenvalue = 1.175, explained vari-
assumption tests showed that no specific outliers or irregularities ance = 7.3%). The Cronbach’s alpha coefficients for the informative
were identified in the measurement scale through an examination response, formative response, and reliable response were 0.86,
of Cook’s distance, student residuals, skewness, and kurtosis. 0.84, and 0.76, respectively.

6. 902 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907
Table 2 Table 4
Results of exploratory factor analysis for cognitive responses of website Results of confirmatory factor analysisa .
advertisement.
Constructs and variables Standardized CCRb AVEc
Cognitive responses Factor Eigenvalue Variance (%) ˛ factor loadings
loading (t-value)
Informativeness 5.486 34.3 .856 Cognitive response ( 1) .821 .744
Knowledgeable .781 Informative response .801(7.162)
Useful .763 Inaccurate response .793(7.360) .700 .608
Intelligent .725 Reliability response .688 (9.116)
Resourceful .721 Affective response ( 2) .742 .638
Informative .644 Negative response .564 (9.516)
Helpful .642 Positive response .720 (7.472) .789 .715
Unique .625 Displeasure .717 (7.500)
Website attitude (Á1) .612 .607
Inaccuracy 2.589 16.2 .837
Website trust .567 (9.888)
Confusing .819
Good impression .710 (8.247)
Messy .791
Website conviction .728(8.137)
Not easy to understanding .745
Brand attitude (Á2)
Not easy to web surfing .735
Good impression .690 (9.056)
Cumbersome .657
Brand conviction .817 (6.569)
Flashy .613
Brand satisfaction .690(9.076)
Reliability 1.175 7.3 .666 Purchase intention (Á3)
Believable .785 I will purchase if it is necessary .652(7.934)
Honest .775 I will visit the store what I want to buy .675(7.007)
Real .490 a 2
= 137.981, df = 64, p < 0.001, GFI = .924, AGFI = .876, RMSR = .0462, NFI = .895,
Total variance extracted (%) 57.8 CFI = .938
b
Composite construct reliability.
Note: Variables in the Factor 2 (Inaccurate response) were reversely coded for the c
Average variance extracted.
analysis.
Subsequently, the three dimensions of cognitive and affective
In terms of exploratory factor analysis for the affective responses responses to website advertisement were examined to investigate
to web advertisements, three factors were extracted that explained interrelationships among the constructs proposed in this study (i.e.,
60.58% of the total variance (Table 3). After the variables and website attitudes, brand attitudes, and purchase intentions).
their characteristics were examined, three dimensions were iden-
tified: ‘negative feeling’ (5 variables, eigenvalue = 5.33, explained 4.3. Measurement model
variance = 33.3%), ‘positive feeling’ (7 variables, eigenvalue = 3.013,
explained variance = 18.8%), and ‘displeasure’ (4 variables, eigen- Overall measurement quality was assessed using CFA (Anderson
value = 1.346, explained variance = 8.4%). The coefficient alphas for and Gerbing, 1992). CFA of the measurement model, which spec-
the positive response, negative response, and evoke were 0.82, 0.87, ifies the posited relationships with the observed indicators to the
and 0.73, respectively. The variables, which loaded in the negative latent constructs, was used to examine convergent and discrim-
responses, were reversely coded for further analysis in confirma- inant validity. In this analysis, we dropped items that did not
tory factor analysis (CFA) and SEM. adequately represent the one-dimensional character of each study
concept based on modification indices (Hair et al., 2009). The results
of CFA are shown in Table 4.
Table 3 All loadings exceeded 0.427, and each indicator t-value
Results of exploratory factor analysis for affective responses of website
advertisement.
exceeded 3.992. The 2 fit statistics was 62.580, with 29 degrees
of freedom (p < 0.001). The root mean square residual (RMSR) was
Affective responses Factor Eigenvalue Variance (%) ˛ 0.056, the comparative fit index (CFI) was 0.920, the goodness-of-
loading
fit index (GFI) was 0.936, the adjusted goodness-of-fit index (AGFI)
Negative feeling 5.330 33.3 .852 was 0.878, and the normed-fit index (NFI) was 0.865. The compos-
Gloomy .848
ite construct reliability (CCR) of all indicators exceeded 0.612, and
Tiresome .847
Prostrated .740 the average variance extracted (AVE) exceeded 0.607. Therefore,
Irritating .685 according to Hair et al. (2009), it can be concluded that the indica-
Trivial .624 tors used in this study are acceptable and have convergent validity
Positive feeling 3.013 18.8 .810 to allow for subsequent analysis. Hair et al. (2010, pp. 708–710)
Fun .779 suggested that three coefficients, such as factor loadings, variance
Interesting .747 extracted, and construct reliability, could be considered to estimate
Exciting .662
the relative amount of convergent validity among item measures.
Nice .654
Comfortable .625 As a rule of thumb, factor loadings of 0.5 or higher, average variance
Cool .587 extracted of 0.5 or higher, and construct reliability of 0.7 or higher
Imaginative .551 are recommended for convergent validity. Yet, construct reliability
Displeasure 1.346 8.4 .756 between 0.6 and 0.7 may be marginally acceptable. Our analyses in
Angry .741 this study indicated that all of the factor loadings were higher than
Terrify .721 0.5 except for one item (see Tables 2 and 3). CCR and AVE were
Terrible .716
higher than 0.6 which is acceptable because other indicators of the
Displeasure .642
model’s construct validity are acceptable (Hair et al., 2009).
Total variance extracted (%) 60.5 Additionally, in a prior study of structural equation modeling,
Note: Variables in the factor 1 (Negative Responses) and factor 3 (Displeasure) were the standardized factor loadings were examined to evaluate con-
reversely coded for the analysis. vergent validity with an associated t-value using the results of CFA

7. J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 903
Table 5
Construct intercorrelations, mean, and standard deviation.
Measures CR AR WA BA PI Mean S.D.
Cognitive response (CR) 1.00 3.4917 .7972
Affective response (AR) .500* 1.00 3.2218 .8062
Website attitude (WA) .577* .489* 1.00 3.3292 .7398
Brand attitude (BA) .522* .478* .650* 1.00 3.4614 .7905
Purchase intention (PI) .441* .442* .429* .502* 1.00 3.5496 .8935
*
p < .01.
(Anderson and Gerbing, 1988). As seen in Table 4, the estimated site attitude improves if the consumer shows a more favorable
coefficient standardized of the factor loadings on their posited affective response (H1b). There was a significant relationship (+)
underlying construct yielded statistically significant results at the between affective response and website attitudes ( 12 = 0.551, t-
level of .05. Each observed indicator exceeded the recommended value = 2.386, p < 0.05). Interestingly, all of the t-values between
t-value (+1.96). Therefore, the measurement scales achieved con- the constructs showed that the cognitive responses to web
vergent validity of the constructs, and they can thus be applied to advertisements were more closely related to website attitudes,
SEM model testing. However, caution should be shown in inter- brand attitudes, and purchase intentions than were the affective
preting the two items that showed weaker SMC, namely, website responses. Based on this result, it is clear that consumers who
trust and negative response. encounter web advertisements develop website attitudes accord-
Evidence of discriminant validity exists when the proportion ing to their web advertising responses, cognitive responses, and
of variance extracted from each construct exceeds the square of affective responses. Therefore, the hypotheses that website atti-
correlation coefficients (˚) representing its correlation with other tude forms based on web advertising responses (H1a and H1b) are
factors (Fornell and Larcker, 1981). supported.
As shown in Table 5, brand attitudes and purchase inten- Second, the cognitive and affective responses to website adver-
tions (˚ = 0.502 and ˚2 = 0.41, respectively) were highly correlated. tisements (H2a and H2b, respectively) have a positive effect on
Website attitudes and brand attitudes (˚ = 0.650 and ˚2 = 0.34, brand attitudes, supporting H2a and H2b. We tested the hypoth-
respectively) were also highly correlated. The AVE in each mea- esis that brand attitude improves if the consumer has a more
surement exceeded the respective correlation estimate between favorable cognitive response to the website (H2a). There was
factors, which provided evidence of discriminant validity. Accord- a significant influential relationship (+) between website cogni-
ing to these assessments, the measurements appear to have tive response and brand attitudes ( 21 = 0.560, t-value = 2.760,
acceptable levels and validities. p < 0.01). In addition, this result shows that brand attitude
improves if the consumer has a more favorable affective response
4.4. Hypothesis testing to the website (H2b). There was a significant relationship (+)
between the affective response to the website and brand attitudes
In this study, data were analyzed using LISREL 8.5, and the ( 22 = 0.658, t-value = 2.415, p < 0.05). Therefore, the hypotheses
covariance matrix was used. The maximum-likelihood estimates H2a and H2b, that cognitive and affective responses to a web adver-
for the various parameters of the overall fit of the model are given tisement positively influence brand attitudes, respectively, are
in Fig. 2. supported.
The statistical analysis of the overall model indicated that 2 Third, the cognitive and affective responses to a website adver-
was 75.130, with 29 degrees of freedom (p < 0.001). The root mean tisement have a positive effect on purchase intentions, which
square residual (RMSR) was 0.045, the comparative fit index (CFI) supports H3a and H3b. Upon testing the hypothesis that consumer
was 0.936, the goodness-of-fit index (GFI) was 0.932, the adjusted purchase intention increases with a more favorable cognitive
goodness-of-fit index (AGFI) was 0.887, and the normed-fit index response to the website (H3a), we discovered that there was a
(NFI) was 0.876. significant relationship (+) between these variables ( 31 = 0.567,
Within the overall model, the estimates of the structural coeffi- t-value = 2.765, p < 0.01). After testing the hypothesis that purchase
cients provide the basis for testing the proposed hypotheses. Based intention improves with a stronger affective response by the con-
on the conceptual model, Table 6 shows the results on the hypoth- sumer (H3b), we found that there was a significant relationship
esis regarding the relationships among consumer advertisement (+) between these variables ( 32 = 0.666, t-value = 2.419, p < 0.05).
attitudes, website attitudes, brand attitudes, purchase intentions Therefore, the hypotheses that cognitive and affective responses
and web advertisement. to website advertisements positively influence consumer purchase
intention (H3a and H3b, respectively) are supported.
4.5. Testing the hypothesized structural models Fourth, website attitude has a positive effect on consumer brand
attitudes, which supports H4. After testing the hypothesis that con-
Fig. 2 and Table 6 show the results of the structural equation sumer website attitude improves if consumer brand attitude is
model. The aforementioned hypotheses (H1–H5) address the ques- more favorable, we found that there was a significant relationship
tion as to whether customer responses to web advertisements (+) between these variables (ˇ21 = 1.194, t-value = 6.577, p < 0.01).
influence brand attitudes and purchase intentions. Therefore, the hypothesis that website attitudes positively influ-
First, the cognitive response and affective response to a ence brand attitudes (H4) is supported.
web advertisement (H1a and H1b, respectively) have a posi- Fifth, brand attitude has a positive effect on consumer purchase
tive effect on website attitudes, thus supporting H1a and H1b. intention, supporting H5. After testing the hypothesis that brand
We tested the hypothesis that website attitude improves if attitude improves when the purchase intention is more positive,
the consumer shows a more favorable cognitive response to we found that there was a significant relationship (+) between
the website (H1a). There was a significant relationship (+) these variables (ˇ32 = 1.011, t-value = 9.388, p < 0.01). Therefore,
between cognitive response and website attitudes ( 11 = 0.469, the hypothesis that brand attitudes positively influence purchase
t-value = 2.717, p < 0.01). In addition, the results show that web- intentions (H5) is supported.

8. 904 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907
.35 .38 .53
CR1 CR2 CR3
.80 .79 .69
Cognitive Response
(ξ1)
.345
.428 (2.330) b
.556 (3.780) a
(4.716)a
.66 WA1 .58
.71 .688 .523
.50 WA2 Website Attitude (3.983) a Brand Attitude (3.357) a Purchase Intention
.70 (η1) (η2) (η3)
.52
WA3 .68 .79 .70 .64 .67
.291 BA1 BA2 BA3
(2.843)a PI1 PI2
.317 .53 .37 .51 .59 .56
(3.065) a
.477
(3.323) a
Affective Response
(ξ2)
.59 .70 .72
AR1 AR2 AR3
.66 .51 .49
a
p<.01, b p<.05. Path Coefficient(t-value)(two-tailed test). χ 2=145.373, df=65, p=.000, GFI=.921, AGFI=.872, RMSR=.044,
NFI=.884, CFI=.927
Fig. 2. Results of structural equation model.
Table 6
Results of relationship between indicators of each hypothesis.
H. Path P.N. C.C. S.D. t-Value
H1a Cognitive response ( 1) → website attitude (Á1) 11 .556 .118 4.716
H1b Affective response ( 2) → website attitude (Á1) 12 .291 .102 2.843
H2a Cognitive response ( 1) → brand attitude (Á2) 21 .428 .113 3.780
H2b Affective response ( 1) → brand attitude (Á2) 22 .317 .103 3.065
H3a Cognitive response ( 1) → purchase intention (Á3) 31 .345 .148 2.330
H3b Affective response ( 2) → purchase intention (Á3) 32 .477 .144 3.323
H4 Website attitude (Á1) → brand attitude (Á2) ˇ21 .688 .173 3.983
H5 Brand attitude (Á2) → purchase intention (Á3) ˇ32 .523 .156 3.357
2
H: hypothesis, P.N.: path name, C.C.: correlation coefficient = 145.373, df = 65, p < 0.01, GFI = .921, AGFI = .872, RMSR = .044, NFI = .884, and CFI = .927.
5. Discussion website attitudes and directly influence brand attitudes and pur-
chase intentions. Our findings regarding the impact of cognitive
This study examined structural relationships among consumer responses support the results of Ducoffe (1996), Schlosser et al.
responses to website advertisements, website attitudes, brand atti- (1999), and Wang et al. (2009). Consumers search for information
tudes, and purchase intentions. We have put forth the following related to the products they plan to purchase. A website offering
conclusions, as supported by the results presented in this study. better information should result in better responses from cus-
First, the responses to advertisements (i.e., cognitive and tomers. Wen (2009) pointed out that information quality is one
affective responses) positively influence website attitudes, brand of the most important dimensions for consideration in effective
attitudes, and purchase intentions. The structural, informational, website design. It has also been noted that unreliable, inaccurate,
and emotional characteristics of a website act as direct causes of and insufficient information can lead to the deterioration of online

9. J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 905
customer trust, which hinders successful customer relationships tising affects attitudes. Importantly, this study narrows a gap in the
(Jarvenpaa et al., 2000; Reichheld and Schefter, 2000). It should literature by exploring the mediating effect of brand attitudes in
also be noted that belief factors stem from web advertisements hospitality e-commerce. Third, this study adds to the limited num-
featuring valuable and clear information, and they are more pow- ber of existing studies on restaurant websites, as we explore the
erful and stable than any other factor in generating and leading full relationships among attitudinal variables related to website
customer behaviors (Yang, 2003). Therefore, marketing managers advertising in the restaurant industry. Despite numerous studies
should consider the importance of cognitive responses, which are on hotel or tourism websites, studies of restaurant websites are
mainly caused by the quality and quantity of information on web- scarce. Indeed, this study may serve as inspiration for future studies
sites, when designing their websites for advertising. on restaurant websites.
Our findings also indicated that affective responses are impor- This study also provides practical implications for the restaurant
tant in forming attitudes. Like traditional advertisements, website industry. In the literature on the restaurant industry, attitude has
advertisements can create both positive and negative feelings. As often been discussed with regard to service. However, the online
Yoo and MacInnis (2005) suggested, positive feelings toward a web environments of restaurants and the responses of their customers,
advertisement enhance the advertisement’s credibility, while neg- including cognitive and affective responses, have not been inves-
ative feelings result in negative evaluations of the advertisement tigated in depth. It is important to understand how customers
and brand. This study also showed that the affective response to perceive restaurant websites because this information can help
a web advertisement influences a customer’s attitude and brand managers increase the effectiveness of website designs and thus
evaluation. Our findings regarding the impact of affective responses improve profitability. Therefore, to enhance the understanding of
also support the results of Ducoffe (1996) and Raney et al. (2003), the formation of customer attitudes, we considered both cogni-
although these studies focused only on one affective component. tive and affective responses to websites. This demonstrates to the
Therefore, the findings of this study support the notion that cogni- restaurant industry the importance of encouraging customers to
tive and affective responses can operate simultaneously. view the information gained from their websites as valuable and
Furthermore, the current study shows that although both useful. The information provided to customers through websites
types of responses are important in forming attitudes, cognitive should be comprehensive to help customers make decisions. If
responses are more significant than affective responses. The impact websites are designed to offer information, it is critical that the
of cognitive responses is stronger than that of affective responses information provided be as credible and meaningful as possible. At
according to the statistical coefficients between the constructs. It the same time, effective websites that are designed to appeal to the
could be said that these results reflect a stronger initial aware- emotions of customers should allow more customer interaction to
ness of an advertisement rather than any predisposition toward induce exceptionally positive affective responses. Advertising on
the advertisement (Belch and Belch, 1998; Stevenson et al., 2000). websites should create a favorable, exciting, fun, and entertaining
Our findings also support the argument by Yoo and MacInnis (2005) image to facilitate the processing of product- and service-related
that cognitive-driven outcomes are more important in represent- information by customers.
ing the effectiveness of an advertisement that is designed to appeal Furthermore, this study helps restaurant managers who par-
to the emotions of viewers. ticipate in e-commerce understand how attitudes formed on web
Second, as a result of testing H4 and H5, we have found that advertisements influence customer behaviors. Our study findings
website attitudes positively influence brand attitudes, which in show that effective website design contributes to building brands
turn positively influences purchase intentions. A more positive and future purchases. Restaurateurs can communicate their brands
website attitude leads to a better brand attitude. In other words, through their websites and positively influence customer selection
if consumers like a website, the represented company’s products of their restaurants. From our findings, it is reasonable to believe
should be better recognized than if consumers do not like a web- that if web visitors like the websites of particular restaurants, they
site. Favorable reactions to a website can increase brand loyalty. are more likely to visit those restaurants. Websites might be the
Furthermore, a more positive brand attitude stimulates purchase first contact point for customers, even before customers phone
intentions. Therefore, the mediating role of brand attitudes for a restaurants for reservations prior to a visit. Accordingly, a positive
restaurant website advertisement between website attitudes and impression due to a convincing and well-designed web advertise-
purchase intention was demonstrated. Consequently, a positive ment creates valuable customers and enhances the restaurant’s
attitude, which was formed through a web-browsing process, leads brand, eventually helping improve market positions.
to stronger purchase intentions online. Our findings are consis- Importantly, this study provides a foundation for restaurant
tent with those of Homer (1990), MacKenzie and Lutz (1989), and managers to develop online marketing strategies. This study
Stayman and Aaker (1988). Based on our results, the mediating role also highlights the importance of investments in web design as
of brand attitudes with respect to specific products holds true for worthwhile efforts; indeed, the expenditures involved can be
restaurant websites. justified. Finally, well-designed websites together with online
advertisements created by considering cognitive and affective
characteristics should enhance customer brand attitudes as well
6. Implications as the long-term profitability and performance of the business.
This study offers theoretical contributions to existing research
on online marketing in the restaurant industry. First, this study 7. Limitations and future research
highlights the simultaneous role of cognitive and affective
responses of consumers to web advertising. While prior studies The study’s findings are subject to the following limitations.
have investigated those two responses, we fully explored how First, given that internationally franchised family restaurants were
both the cognitive and affective responses are formed toward web selected as research sites, the results of our study cannot be gener-
advertising. We found that these responses play important but alized to other types of restaurants. Other restaurant classifications,
asymmetrical roles in influencing attitudes toward web advertise- such as independent restaurants and/or fast food restaurants,
ments. Second, this study focused on the structural effects among would be ideal for a future study to test the proposed model.
the antecedents and precedents of web advertising attitudes. This One aspect of specific interest involves the differing nature of
holistic view allows a better understanding of how website adver- advertising and promotional strategies employed by local fast food

10. 906 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907
restaurants or independent restaurants versus internationally fran- Chan, A., Law, R., 2006. Hotel website optimization: the case of Hong Kong. In: Hitz,
chised restaurants. M., Sigala, M., Murphy, J. (Eds.), Information and Communication Technologies
in Tourism. Springer, Vienna, pp. 60–73.
Second, the sample of ten internationally franchised restaurants Chen, Q., Wells, W.D., 1999. Attitude toward the site. Journal of Advertising Research
limits the study. As a result of this small sample size, additional 39 (5), 27–37.
internationally franchised restaurants should be included by exam- Chiang, C., Jang, S.S., 2007. The effects of perceived price and brand image on value
and purchase intention: leisure travelers’ attitudes toward online hotel booking.
ining operating conditions across multiple domestic locations to Journal of Hospitality Marketing & Management 15 (3), 49–69.
validate the proposed model. Extended research could include Cunliffe, D., 2000. Developing usable websites—a review and model. Internet
comparison and analysis with an additional country or multiple Research 10 (4), 295–308.
Coyle, J.R., Thorson, E., 2001. The effects of progressive levels of interactivity and
countries of operation.
vividness in Web marketing sites. Journal of Advertising 30 (3), 65–77.
Third, while this study clearly showed that the formation of Dabas, S., Manaktola, K., 2007. Managing reservations through online distribution
consumer attitudes regarding website characteristics directly influ- channels: an insight into mid-segment hotels in India. International Journal of
Contemporary Hospitality Management 19 (5), 388–396.
ences purchases, it did not investigate whether positive website
Ducoffe, R.H., 1996. Advertising value and advertising on the Web. Journal of Adver-
attitudes result in actual purchases. Future studies are needed to tising Research 36 (5), 21–35.
create a model that analyzes the correlation between website atti- Edell, J.A., Burke, M.C., 1987. The power of feelings in understanding advertising
tudes and actual purchases. effects. The Journal of Consumer Research 14 (3), 421–433.
Fornell, C., Larcker, D.F., 1981. Evaluation structural equation models with unob-
Last, because there is a limitation in the measurement scale servable variables and measurement error. Journal of Marketing Research 18
regarding convergent validity, a future study should develop and (1), 39–50.
test a more reliable measurement scale for cognitive and affective Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 2009. Multivariate Data Analysis,
7th ed. Prentice-Hall Upper, Saddle River, NJ.
responses to restaurant website advertisement. This effort would Haley, R.I., Baldinger, A.L., 2000. The ARF copy research validity project. Journal of
allow a better understanding of consumer attitudes toward restau- Advertising Research 40 (6.), 114–135.
rant web advertisements and promotions. Han, J.-H., Mills, J.E., 2006. Zero acquaintance benchmarking at travel destination
websites: what is the first impression that national tourism organizations try to
Importantly, a future study could be designed to help under- make? International Journal of Tourism Research 8 (6), 405–430.
standing how online advertising influences the relationship Hashim, N.H., Murphy, J., Law, R., 2007. A review of hospitality website design frame-
between intention and behavior. Additionally, future research works. In: Sigala, M., Mich, L., Murphy, J. (Eds.), Information and Communication
Technologies in Tourism. Springer, Vienna, pp. 219–230.
could be extended to include an analysis of the personal traits
Ho, C.-I., Lee, Y.-L., 2007. The development of an e-travel service quality scale.
of customers as moderating variables in the relationship between Tourism Management 28 (6), 1434–1449.
online advertising and attitudes toward advertisements. For exam- Holbrook, M.B., Batra, R., 1987. Assessing the role of emotions as mediators of
consumer response to advertising. The Journal of Consumer Research 14 (3),
ple, customer involvement in the information search for restaurant
404–420.
selections could presumably be one factor of research interest, Homer, P.M., 1990. The mediating role of attitude toward the Ad: some additional
particularly, with respect to the potential influence of online adver- evidence. Journal of Marketing Research 27 (1), 78–86.
tising on attitude formation. 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 Applications 36 (3), 6439–6445.
Ind, N., Riondino, M.C., 2001. Branding on the web: a real revolution? Journal of
Brand Management 9 (1), 8–19.
References Jang, D., 1998. Positioning and effect of Internet advertising: Competitive effect of the
Internet advertising on the existed medium advertisement and the management
Aaker, D.A., Stayman, D.M., 1990. Measuring audience perception of commercials plan. Broadcasting Advertisement Study Collection of Books 14, 308–318.
and relating them to Ad impact. Journal of Advertising Research 30 (4), 7–17. Jarvenpaa, S.L., Tractinsky, N., Vitale, M., 2000. Consumer trust in an Internet store.
Anderson, J.C., Gerbing, D.W., 1992. Assumptions and comparative strengths of the Information Technology Management 1 (1/2), 45–71.
two-step approach. Sociological Methods and Research 20 (3), 321–333. Johnson, G.J., Bruner, G.C., Kumar, A., 2006. Interactivity and its facets
Anderson, J.C., Gerbing, D.W., 1988. Structural equation modeling in practice: a revisited—theory and empirical test. Journal of Advertising 35 (4), 35–52.
review and recommended two-step approach. Psychological Bulletin 103 (3), Karson, E.J., Fisher, R.J., 2005. Reexamining and extending the dual mediation
411–423. hypothesis in an on-line advertising context. Psychology & Marketing 22 (4),
Bai, B., Law, R., Wen, I., 2008. The impact of website quality on customer satisfaction 333–351.
and purchase intentions: evidence from Chinese online visitors. International Karson, E., McCloy, S.D., Bonner, P.G., 2006. An examination of consumers’ attitudes
Journal of Hospitality Management 27 (3), 391–402. and beliefs towards web site advertising. Journal of Current Issues & Research
Baloglu, S., Pekcan, Y.A., 2006. The website design and Internet site marketing in Advertising 28 (2), 77–91.
practices of upscale and luxury hotels in Turkey. Tourism Management 27 (1), Kaplanidou, K., Vogt, C., 2006. A structural analysis of destination travel intentions
171–176. as a function of web site features. Journal of Travel Research 45 (2), 204–216.
Belch, G.E., Belch, M.A., 1998. Adverting and Promotion: An Integrated Marketing Keller, K.L., 1993. Conceptualizing, measuring, and managing customer-based brand
Communications Perspective. McGraw-Hill, Boston. equity. The Journal of Marketing 57 (1), 1–22.
Bevanda, V., Grzinic, J., Cervar, E., 2008. Analysing the users’ perception of web Kim, D.-Y., Lehto, X.Y., Morrison, A.M., 2007. Gender differences in online travel
design quality by data mining tools. Tourism and Hospitality Management 14 information search: implications for marketing communications on the internet.
(2), 251–262. Tourism Management 28 (2), 423–433.
Bollen, K.A., 1989. Structural Equations with Latent Variables. John Wiley & Sons, Korea Franchise Association, 2010. http://www.ikfa.or.kr/2010/09/15.
New York. Korgaonkar, P., Wolin, L.D., 2002. Web usage, advertising, and shopping: relationship
Brigish, A., 1993. The electronic marketplace: evolving toward 1:1 marketing. Elec- Patterns. Internet Research 12 (2), 191–204.
tronic Marketplace Report 7 (9), 6–7. Ku, J., Cho, B., 2000. The study of the relation between products estimation spe-
Brown, S.P., Stayman, D.M., 1992. Antecedents and consequences of attitude toward cial quality and symbolism of products. Business Management Study 29 (1),
the ad: a meta analysis. The Journal of Consumer Research 19 (1), 34–51. 293–321.
Bruner, G.C., 2009. Marketing Scale Handbook: A Compilation of Multi-item Lang, A., 1994. Measuring Psychological Responses to Media Messages. Hillsdale,
Measures for Consumer Behavior & Advertising Research. GCBII Productions, New Jersey.
Carbondale, IL. Law, R., 2007. A fuzzy multiple criteria decision-making model for evaluating travel
Bruner, G.C., Kumar, A., 2005. Explaining consumer acceptance of handheld Internet websites. Asia Pacific Journal of Tourism Research 12 (2), 147–159.
devices. Journal of Business Research 58 (5), 553–558. Law, R., Qi, S., Buhalis, D., 2010. Progress in tourism management: a review
Buhalis, D., Law, R., 2008. Progress in information technology and tourism man- of website evaluation in tourism research. Tourism Management 31 (3),
agement: 20 years on and 10 years after the Internet—the state of eTourism 297–313.
research. Tourism Management 29 (4), 609–623. Law, R., Bai, B., 2008. How do the preferences of online buyers and browsers differ
Burke, M.C., Edell, J.A., 1989. The impact of feelings on ad-based affect and cognition. on the design and content of travel websites? International Journal of Contem-
Journal of Marketing Research 26 (1), 69–83. porary Hospitality Management 20 (4), 388–400.
Byrne, B.M., 1998. Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Law, R., Cheung, C., 2006. A study of the perceived importance of the overall web-
Basic Concepts, Applications, and Programming. Lawrence Erlbaum Associates, site quality of different classes of hotels. International Journal of Hospitality
Inc., Mahwah, NJ. Management 25 (3), 525–531.
Campbell, D.E., Wright, R.T., 2008. Shut-up I don’t care: understanding the role Lee, H.Y., Qu, H., Kim, Y.S., 2007. A study of the impact of personal innovativeness
of relevance and interactivity on customer attitudes toward repetitive online on online travel shopping behavior—a case study of Korean travelers. Tourism
advertising. Journal of Electronic Commerce Research 9 (1), 62–76. Management 28 (3), 886–897.