898 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907Table 1 Researchers have recognized the need for a more sophisticatedRecent 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 useintentions. 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 thatintentions, 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 theprecedents 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 advertisementsboth cognitive and affective responses, and explored whether these can be classiﬁed according to seven characteristics: unlimitedtwo 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 facilitatesresponses 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 InternetLaw and Cheung, 2006; Morosan and Jeong, 2008; Noone and advertising in terms of quick-access to information, customerMattila, 2009; Rong et al., 2009; Schmidt et al., 2008; Vermeulen preference-based information, ﬂexibility to customer preferencesand 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 withLitvin 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 fromthe last ﬁve years. Although the restaurant industry has potential 2.2. Response of website advertising: cognitive and affectivefor Internet marketing, including web advertising, studies on online responsesadvertising in this industry have been scarce. Though dated, oneexception 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 toselect a restaurant in a vacation setting. Although restaurant man- a particular advertising stimulus during a particular exposureagers 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 customeriors 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 tomarketers 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 andbrand attitudes, and purchase intentions of restaurant customers. Lutz, 1989). This logic has been proven with respect to attitudes-
J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 899toward-a-website (Bruner and Kumar, 2005). However, it still tisement and brand attitudes. However, while Holbrook and Batraremains 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 bytwo 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 investigatedattitudes toward website advertising.The most recent studies eval- in the domain of online advertising. It remains unclear whether theuating 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 holdset 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 affectiveet al., 2007; Park et al., 2007; Schmidt et al., 2008; Stockdale and factor, such as entertainment, could still play a signiﬁcant role inBorovicka, 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, andbooking behavior. Furthermore, in relation to online advertising, indicated that interactive and entertaining websites that includedthe majority of studies have been limited to the impact of online a mini-ﬁlm of an automotive brand included high arousal, whichadvertising characteristics (i.e., format, design, content, and fre- facilitated the processing of brand-related information. Based onquency) on purchasing behavior (Campbell and Wright, 2008; Coyle this evidence, and in conjunction with the traditional view aboutand Thorson, 2001; Johnson et al., 2006; Moe and Fader, 2004; the relationship between affective responses and advertisementStevenson 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 attitudestudies have focused on the characteristics of online advertis- formation have been mainly conducted with regard to traditionaling that inﬂuence customer attitudes by considering the unique advertising. It appears that both cognitive and affective responsescharacteristics 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 andet al., 2006; Peng et al., 2004). These studies identiﬁed interac- Stayman, 1992; Zajonc and Markus, 1982). Furthermore, studiestivity as a unique characteristic that inﬂuences attitudes toward involving online advertising have focused on cognitive and affectiveonline 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 onlineinteractivity, and this interactivity has a direct effect on attitudes advertising. It is still uncertain which process (i.e., cognitive ortoward websites. Although there are only a few examples of this affective) is elicited more by online advertising. Therefore, thetype 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 towardATOA has both cognitive and affective antecedents (Ducoffe, 1996; online advertising in the restaurant industry? Does the cognitiveShimp, 1981). Given that traditional advertising inﬂuences con- process contribute more to attitude than the affective process orsumer 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 foring.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, websiteprovides information and contributes to economic development attitudes, brand attitudes, and purchase intentionsserved 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 attitudesability of Internet advertising to inform contributes to consumer toward advertising carry a positive purchase intention (MacKenzieattitudes. Due to the highly informative nature of online adver- and Lutz, 1989; MacKenzie et al., 1986). Recent studies of onlinetising, 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 purchasetomers (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; Raneyimpact of arousal has long been established (Lang, 1994). An adver- et al., 2003). While it is straightforward that this attitude relatestisement 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) conductedfeelings about an advertisement are important in explaining the a meta-analysis of the antecedents and consequences of attitudeeffects of advertising. Holbrook and Batra (1987) showed that the toward advertising in traditional media. They conﬁrmed the resultsaffective response has a signiﬁcant relationship with advertise- of other studies on the direct impact of advertisement attitudesment 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
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 into 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 andresponding 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 intudes 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 positive1993). The ﬁndings from those studies, however, were not con- inﬂuence (+) on website attitudes.sistent. While Miniard et al. (1990) and Keller (1993) supportedthe mediating role, while Karson and Fisher (2005) did not. Fur- H1b. The affective response to a web advertisement has a positivethermore, studies on brand attitudes have been limited to speciﬁc inﬂuence (+) on website attitudes.products. For instance, Karson and Fisher (2005) tested a modelthat incorporated brand attitudes as a mediator in the relation- H2a. The cognitive response to a web advertisement has a positiveship 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 positivetribute to a charity (the Special Olympics). Their ﬁndings indicated inﬂuence (+) on brand attitudes.that the relationship between attitudes and intentions was directand independent of brand attitudes. The study’s ﬁndings did not H3a. The cognitive response to a web advertisement has a positivesupport the traditional view that brand attitudes mediate the rela- inﬂuence (+) on purchase intentions.tionship between attitudes and intentions. The authors explainedthat the non-signiﬁcance of brand attitudes in the relationship can H3b. The affective response to a web advertisement has a positivebe 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 waslimited 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 advertisementshave paid attention to the brands of service organizations, including 3.2. Study methodbrands in the restaurant industry. 3.2.1. Measurement scale3. 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 termstion, we propose the following hypothesized model (Fig. 1). We of two parts: cognitive response and affective response. Cognitivepropose that responses to website advertisements, which con- response scales were used to measure responses to 16 items basedsist 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 measureconative responses, we propose a strong positive relationship responses to 16 items based on the adjectives used in the studies
J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 901by Edell and Burke (1987) and Bruner (2009), focusing on particu- To examine the proposed research hypotheses regarding thelarly 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 wasitems for revision or addition to target restaurant customers. From employed in the LISREL program. Using SEM procedures, thethis 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 threethe questionnaire. These items were measured using a ﬁve-point endogenous constructs for website attitudes, brand attitudes, andLikert’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 teston studies by MacKenzie et al. (1986) and Jang (1998): general a hypothesized model. SEM is a reliable and appropriate statisticalwebsite trust and website satisfaction of users toward web adver- technique to evaluate how well a proposed conceptual model thattisements. These items were measured using a ﬁve-point Likert’s contains observed indicators and hypothetical constructs explainsscale (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 theabove. These items were measured using a ﬁve-point Likert’s scale research hypotheses.(1 = strongly disagree; 5 = strongly agree). The purchase intentionscale used two items to measure the aroused intention to buy afterseeing a web advertisement (namely, “I will purchase if it is neces- 4. Analysis and resultssary” and “I will visit the store to get what I want to buy”). Theseitems were measured using a ﬁve-point Likert’s scale (1 = strongly 4.1. Demographic proﬁledisagree; 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 malesand Cronbach’s alpha = .89 for the cognitive scale), the entire mea- (42.9%, n = 161) among the respondents. The proportion of marriedsurement scale is acceptable and reliable (Nunnally and Bernstein, respondents was 62.3% (n = 233). Completed education levels were1994). Therefore, further statistical analysis is appropriate using most often bachelor degrees (52.3%, n = 196) or graduate schoolingthis 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) were3.2.2. 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 incomesonsite 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) hadmore 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), companySeoul, Korea, and asked their managers to help with our research colleagues (38.6%, n = 145), and other (7.5%, n = 28). Respondentsand survey. The data collection took place from September 1 to stated that reasons for selecting the restaurant included tasteSeptember 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, andBennigan’s. These restaurants were selected based on having yearly 4.2. Exploratory factor analysis of cognitive and affectiverevenues within the top 20 franchised restaurants according to the responses of website advertisementsKorea Franchise Association (2010). Brand popularity and managerpermission to collect data were also considered. Customers enter- First, the correlation matrix and anti-image correlation wereing 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 thisads, text ads, interstitial ads, pop-up ads, and HTML ads for these study was well-suited for factor analysis. Based on the resultstargeted family restaurants. If they had seen such advertisements of the correlation matrix with Bartlett’s test of sphericity andin the month prior to the survey date, they continued to com- the Kaiser–Meyer Oklin (KMO) measure of sampling adequacyplete 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 bevided 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 responsesnaires per restaurant) during the dinner service period of selected of participants to web advertisements were factor-analyzed withbusiness days. Finally, the study utilized a total of 375 useful ques- a varimax rotation under the principal component method at antionnaires 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%), andchecked 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 informativewere 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.
902 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907Table 2 Table 4Results 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 investigateto 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 modelvariance = 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 (Andersonvalue = 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 theand 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 nottory 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-valueResults of exploratory factor analysis for affective responses of websiteadvertisement. 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
J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 903Table 5Construct 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 favorablecoefﬁcient 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 betweent-value (+1.96). Therefore, the measurement scales achieved con- the constructs showed that the cognitive responses to webvergent 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 affectivepreting the two items that showed weaker SMC, namely, website responses. Based on this result, it is clear that consumers whotrust 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, andof 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) arefactors (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 onWebsite 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 moresurement exceeded the respective correlation estimate between favorable cognitive response to the website (H2a). There wasfactors, 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 response4.4. 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 hypothesescovariance 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, arein 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, whichsquare residual (RMSR) was 0.045, the comparative ﬁt index (CFI) supports H3a and H3b. Upon testing the hypothesis that consumerwas 0.936, the goodness-of-ﬁt index (GFI) was 0.932, the adjusted purchase intention increases with a more favorable cognitivegoodness-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 purchasecients 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 relationshipesis 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 responsesand 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 ismodel. The aforementioned hypotheses (H1–H5) address the ques- more favorable, we found that there was a signiﬁcant relationshiption 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 purchasetive effect on website attitudes, thus supporting H1a and H1b. intention, supporting H5. After testing the hypothesis that brandWe 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 (+) betweenthe 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 purchaset-value = 2.717, p < 0.01). In addition, the results show that web- intentions (H5) is supported.
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 6Results 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 2H: 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 informationtudes, and purchase intentions. We have put forth the following related to the products they plan to purchase. A website offeringconclusions, 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 oneaffective responses) positively inﬂuence website attitudes, brand of the most important dimensions for consideration in effectiveattitudes, 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
J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907 905customer 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 inalso 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 theerful and stable than any other factor in generating and leading full relationships among attitudinal variables related to websitecustomer behaviors (Yang, 2003). Therefore, marketing managers advertising in the restaurant industry. Despite numerous studiesshould consider the importance of cognitive responses, which are on hotel or tourism websites, studies of restaurant websites aremainly caused by the quality and quantity of information on web- scarce. Indeed, this study may serve as inspiration for future studiessites, 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 restauranttant in forming attitudes. Like traditional advertisements, website industry. In the literature on the restaurant industry, attitude hasadvertisements can create both positive and negative feelings. As often been discussed with regard to service. However, the onlineYoo 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 customersand brand. This study also showed that the affective response to perceive restaurant websites because this information can helpa web advertisement inﬂuences a customer’s attitude and brand managers increase the effectiveness of website designs and thusevaluation. Our ﬁndings regarding the impact of affective responses improve proﬁtability. Therefore, to enhance the understanding ofalso 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 theTherefore, the ﬁndings of this study support the notion that cogni- restaurant industry the importance of encouraging customers totive 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 websitestypes of responses are important in forming attitudes, cognitive should be comprehensive to help customers make decisions. Ifresponses are more signiﬁcant than affective responses. The impact websites are designed to offer information, it is critical that theof cognitive responses is stronger than that of affective responses information provided be as credible and meaningful as possible. Ataccording to the statistical coefﬁcients between the constructs. It the same time, effective websites that are designed to appeal to thecould be said that these results reﬂect a stronger initial aware- emotions of customers should allow more customer interaction toness of an advertisement rather than any predisposition toward induce exceptionally positive affective responses. Advertising onthe advertisement (Belch and Belch, 1998; Stevenson et al., 2000). websites should create a favorable, exciting, fun, and entertainingOur ﬁndings also support the argument by Yoo and MacInnis (2005) image to facilitate the processing of product- and service-relatedthat 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 ﬁndingswebsite attitudes positively inﬂuence brand attitudes, which in show that effective website design contributes to building brandsturn positively inﬂuences purchase intentions. A more positive and future purchases. Restaurateurs can communicate their brandswebsite attitude leads to a better brand attitude. In other words, through their websites and positively inﬂuence customer selectionif consumers like a website, the represented company’s products of their restaurants. From our ﬁndings, it is reasonable to believeshould be better recognized than if consumers do not like a web- that if web visitors like the websites of particular restaurants, theysite. Favorable reactions to a website can increase brand loyalty. are more likely to visit those restaurants. Websites might be theFurthermore, a more positive brand attitude stimulates purchase ﬁrst contact point for customers, even before customers phoneintentions. Therefore, the mediating role of brand attitudes for a restaurants for reservations prior to a visit. Accordingly, a positiverestaurant 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’sattitude, 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 restauranttent with those of Homer (1990), MacKenzie and Lutz (1989), and managers to develop online marketing strategies. This studyStayman and Aaker (1988). Based on our results, the mediating role also highlights the importance of investments in web design asof brand attitudes with respect to speciﬁc products holds true for worthwhile efforts; indeed, the expenditures involved can berestaurant websites. justiﬁed. Finally, well-designed websites together with online advertisements created by considering cognitive and affective characteristics should enhance customer brand attitudes as well6. Implications as the long-term proﬁtability and performance of the business. This study offers theoretical contributions to existing researchon online marketing in the restaurant industry. First, this study 7. Limitations and future researchhighlights the simultaneous role of cognitive and affectiveresponses 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 wereboth 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 ofholistic view allows a better understanding of how website adver- advertising and promotional strategies employed by local fast food
906 J. Hwang et al. / International Journal of Hospitality Management 30 (2011) 897–907restaurants 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 Researchlimits 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. Internetcomparison 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 andcountries 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 distributionconsumer 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. 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