The antecedent role of online satisfaction, perceived risk online, and perceived website usability on the affect towards travel destinations

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Research Paper

The antecedent role of online satisfaction, perceived risk online, and perceived website usability on the affect towards travel destinations ⁎

Juan Miguel Alcántara-Pilara, , Francisco Javier Blanco-Encomiendab, Tanja Armenskic, Salvador Del Barrio-Garcíad a University of Granada, Department of Marketing and Market Research, Faculty of Education, Economy and Technology, C/ Cortadura del Valle, s.n., 51001 - Ceuta, Spain b University of Granada, Department of Quantitative Methods for Economics and Business, Faculty of Education, Economy and Technology, C/ Cortadura del Valle, s.n., 51001 - Ceuta, Spain c University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Dositeja Obradovića Square 3, 21000 - Novi Sad, Serbia d University of Granada, Department of Marketing and Market Research, Faculty of Economics and Business Administration, Campus Cartuja, s.n., 18071 - Granada, Spain

A R T I C L E I N F O

A B S T R A C T

Keywords: Affect Usability Satisfaction Online risk Website experience

Tourists nowadays rely predominantly on the Internet for their travel decision-making and for purchasing travel products. Given this, websites have become the most important medium to induce positive affect towards a destination, through safe and satisfactory online experiences. However, some travelers are still reluctant to purchase travel products online due to perceived risk. The aim of this study is to explore whether consumer satisfaction during online browsing, consumer risk perception online, and perceived usability of the travel website can predict consumers’ affect towards a travel destination. A website promoting a fictional travel destination was used for data-collection purposes. Confirmatory factor analysis was used to test the validity and reliability of user satisfaction, perceived risk online, perceived website usability, and affect towards a travel destination, while a regression model was employed to explore the predictive power of these constructs on users’ emotional response towards the target destination displayed on the website. Results show that a higher level of consumer satisfaction with the online browsing experience and greater perceived website usability generate positive affect towards a travel destination. In the conclusions section, the practical implications of these findings are discussed in relation to destination marketing and branding.

1. Introduction Online searching starts long before a decision is made about where or how to travel for over 65% of leisure travelers, according to the Google-commissioned Ipsos MediaCT report (2014). Within this context, the Internet remains a predominant source of information for travel planning and for choosing a travel destination, with 74% of tourism-related information searches being conducted on the Internet. Given the rapid growth of the Internet and e-commerce, websites have also become the most important medium for eliciting positive affect towards travel destinations. Affective evaluations of a destination website correspond to individuals’ feelings about a travel destination and, consequently, their future travel behavior (Költringer & Dickinger, 2015). Since the images displayed by destination websites have a substantial impact on consumer purchasing behavior, the role of images from the destination has been extensively examined in tourism and

⁎

hospitality research (Beerli-Palacio & Martín-Santana, 2017; Bott, 2014; Chung, Lee, Lee, & Koo, 2015; Moufakkir, 2013). However, while many previous studies explore the images of the destination in the context of traditional promotion, far fewer do so in the online realm (Choi, Lehto, & Morrison, 2007; Lepp, Gibson, & Lane, 2011). It is still unclear which elements and website components can elicit positive feelings towards a travel destination in the virtual environment. It is important to understand how users perceive or emotionally react to websites, not only because tourism is an experience-based product of unknown quality prior to consumption (Jalilvand, Samiei, Dini, & Manzari, 2012) but also because the Internet is a predominant communication channel that strongly affects consumer purchase behavior (Frías-Jamilena, Del Barrio-García, & López-Moreno, 2013). Here it should be noted that, in a virtual environment, cognitive evaluation of a destination website and its affective appraisal are strongly influenced by the website design and characteristics

Corresponding autor. E-mail addresses: [email protected] (J.M. Alcántara-Pilar), [email protected] (F.J. Blanco-Encomienda), [email protected] (T. Armenski), [email protected] (S. Del Barrio-García).

http://dx.doi.org/10.1016/j.jdmm.2017.09.005 Received 24 October 2015; Received in revised form 25 September 2017; Accepted 29 September 2017 2212-571X/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Alcantara-Pilar, J.M., Journal of Destination Marketing & Management (2017), http://dx.doi.org/10.1016/j.jdmm.2017.09.005

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Destination image is one of the most widely explored constructs in the field of tourism and hospitality (Gallarza, Gil, & Calderón, 2002; Moufakkir, 2013). Since the first work of Hunt (1971), there have been numerous and varied approaches to defining destination image. However, in general, it is accepted among scholars that image comprises at least two closely-related components: cognitive evaluation and affective appraisal. The cognitive component refers to an individual's knowledge and beliefs about an object (Pike & Ryan, 2004), while the affective component corresponds to an individual's feelings toward that object (Baloglu & Brinberg, 1997). There is general consensus that tourists build their feelings as a function of beliefs and opinions about a given destination of interest. Furthermore, some authors also argue that a third, behavioral (conative), component should also be included in the conceptualization of destination image. The conative component of image is analogous to the real action of choosing a destination (brand purchase) and/or actually traveling to that destination (Nicoletta & Servidio, 2012). The three hierarchically-interrelated components represent behavioral manifestation on the part of the traveler in the process of destination image-formation (Zhang, Fu, Cai, & Lu, 2014). This theoretical framework has guided many studies on destination image. However, Mazanec (2009) argued that such a wide conceptualization of destination image, considering all its components, might ‘dilute’ the construct to the extent that it fits every type of semantic content. Hence, many researchers have relied predominantly on a cognitive (Pike & Ryan, 2004; Stepchenkova & Mills, 2010) or/and cognitive–affective-centered measurement approach (San Martín & Rodríguez del Bosque, 2008). Some scholars, such as Yu and Dean (2001), have noted indications that affect is a better predictor of behavioral intention than cognition, because behavior may be influenced by the affective quality of an environment, rather than directly by its objective properties (Russell & Snodgrass, 1987). Therefore, several scholars who support this notion have recently focused on the affective component when exploring destination image in an online context (AlcántaraPilar & Del Barrio-García, 2015; Kim & Stepchenkova, 2015).

(Alcántara-Pilar, Del Barrio-García, Porcu, & Crespo-Almendros, 2015). Nielsen and Loranger (2006) noted that good design, in terms of website usability, is related to the speed and ease with which users are able to carry out their tasks on a given site. Achieving high usability requires the site design to focus on Internet users’ needs and organize browsing to make the online shopping experience easier. Therefore, highly usable destination websites provide a positive browsing experience to users through appropriate content organization, clear and concise information on the products and services at the destination, easy browsing, and so on (Nielsen & Norman, 2000). Furthermore, a positive browsing experience contributes to online consumer satisfaction, which is widely accepted to be one of the most influential components of post-purchase behavior and a key element in building successful, long-lasting relationships with consumers (Valkonen, 2009). It is generally acknowledged that individuals’ level of overall satisfaction with browsing will positively affect their perception of the destination website (Szymanski & Hise, 2000), heighten their affect towards the travel destination, and enhance their intention to visit the destination (Castañeda, Muñoz-Leiva, & Luque, 2007). Therefore, users’ affect towards a destination is strongly influenced by how satisfied they feel during their browsing experience (McKinney, Yoon, & Zahedi, 2002; Szymanski & Hise, 2000), the relevance of the information available on the website (Chen & Tsai, 2007), and the site's perceived usefulness (Castañeda et al., 2007). Despite the factors positively related to affective image, previous studies have reported perceived risk online to be one of the key factors that can make users feel unsure and vulnerable during their online experience and, hence, distract them from purchasing (Chung et al., 2015; Vainikka, 2013). Shankar, Urban, and Sultan (2002) noted that consumers’ perception of risk online is negatively related to good usability and positive image, which are both considered to be experiences of trust online. The aim of the present study is therefore to examine whether consumer satisfaction during browsing, perceived risk online, and perceived usability of travel websites can influence consumer affect towards a travel destination. While the majority of previous works focus on the website's functionality (Kaplanidou & Vogt, 2006), little empirical work has been devoted to exploring whether the particular features of a website and the outcomes of its use can elicit positive affect towards a travel destination.

2.2. Tourist satisfaction during browsing and affect towards a travel destination Customer satisfaction is considered to be a basic parameter for evaluating the performance of tourist products and services. According to Oliver (1993, 2010), customer satisfaction involves evaluation and judgment of a product or service that successfully provides a pleasurable level of consumption-related fulfillment. The relationship between satisfaction and travelers’ future intentions has been firmly theoretically established by a number of previous works confirming a significant positive relationship between satisfaction and continuous use and/or repeat-visit intention (Assaker, Vinzi, & O'Connor, 2011; Sirgy & Su, 2000; Valkonen, 2009). In those studies, satisfaction was studied either as a direct predictor of continuous use and/or repeat-visit intention (Anderson & Sullivan, 1993; Anderson, Fornell, & Lehmann, 1994; Churchill & Surprenant, 1982) or as a mediator variable of relationships that lead to continuous use and/or repeat-visit behavior (Anderson & Srinivasan, 2003; Assaker et al., 2011; Bigne, Sanchez, & Sanchez, 2001; Jalilvand et al., 2012). Consumer satisfaction in an online context can be defined as the user's contentment with their purchasing experience on the Internet (Anderson & Srinivasan, 2003). The use of new online intermediaries has brought dramatic changes and increased the complexity of the tourism market. The rapid growth of the online tourism market has been tracked by a number of publications on consumer satisfaction with online services (Anderson & Srinivasan, 2003; Bai, Law, & Wen, 2008). All these works empirically prove that a satisfactory online experience

2. Literature review 2.1. Affect towards a travel destination Affect as a conscious, subjective aspect of an emotion has been studied for many decades, mainly in psychology (Nowlis, 1965; Russell, 1980; Schlosberg, 1952) but more recently in a wide range of behavioral sciences (Hwang, Yoon, & Park, 2011; Pappas, Kourouthanassis, Giannakos, & Chrissikopoulos, 2016; Servidio, 2015). In the context of tourism and hospitality research, affect has been mainly used to describe emotional states, feelings, or moods in relation to an object of interest. However, it should be noted that this construct has been used interchangeably in the conceptualization of attitude towards a destination (Kim & Stepchenkova, 2015), response to advertisement, and brand attitude (Hwang et al., 2011). In the present work, emotions towards a travel destination are examined in the context of the affective image of the destination, generated by specific website features and functional characteristics. It is important to understand how potential travelers build positive feelings towards a destination in a web-based environment, and – perhaps even more challenging for marketing practitioners – how to create a satisfactory browsing experience that will lead to favorable affect towards a destination website.

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advertising and transactions, the importance of consumers’ awareness of risk has been placed center-stage by academics and destination practitioners (Yang & Nair, 2014). Kim, Kim, and Shin (2009) affirmed that perceived risk is a critical factor that exerts a significant influence on the user's decisions when visiting or revisiting a website. Similarly, Ting, Chen, and Lee (2013) confirmed the importance of perceived risk online in users’ acceptance of websites. Blain, Levy, and Ritchie (2005) noted that effective branding evokes positive associations with a place and reduces the subjective level of perceived risk online. While the importance of trust in the online environment is acknowledged, there is still limited theoretical support for its role in evoking positive emotions towards a place during tourism website browsing. Yang and Nair (2014) noted that traditional cognitive approaches to risk perception tend to underestimate or fragment emotion from an understanding of the users’ website experience, although many psychology studies have documented that, when it comes to the moment of making a decision in a risky or uncertain situation, human cognition and emotions act in a divergent way, whereas in many cases, emotional reaction outweighs cognitive evaluation (Kobbeltved & Wolff, 2009; Loewenstein, Weber, Hsee, & Welch, 2001; Slovic, Finucane, Peters, & MacGregor, 2007). On this point, Clore and Parrott (1994) argued that, depending on the characteristics of each alternative evaluated, along with the human limitations for information-processing, affect-rich processing and emotional evaluative feelings will be more likely driven by decision-making requiring more complex choices and related to a higher risk perception (due to high costs), such as in the case of evaluation and choice of a travel destination online. Furthermore, Loewenstein et al. (2001), who introduced the risk-as-feelings theoretical framework, noted that those alternatives perceived by the user to be less risky or more secure are more likely to provoke positive emotional responses in their evaluation than those perceived to be more risky. This direct inverse relationship between risk perception and affective response towards an evaluated object is well established and documented in the psychology literature (Alhakami & Slovic, 1994; Kobbeltved & Wolff, 2009; Slovic, 1987; Weber & Johnson, 2008). However, this direct link between the two constructs is still under-researched in the existing body of tourism literature. Some authors have found a negative relationship between perceived risk and other variables close to affect, such as perceived quality or perceived value of the destination (Sabiote-Ortiz, Frías-Jamilena, & Castañeda-García, 2016). Quintal, Lee, and Soutar (2010) found a negative relationship between the perceived risk of traveling to a destination – assessed in financial, security, or physical terms – and the attitude towards that destination, assessed in affective terms. To bridge this literature gap, the present study examines whether perceived risk online is negatively related to affect towards a travel destination. Hence, the following hypothesis is proposed:

plays a crucial role in users’ overall evaluation of website quality and their future online purchase intention (Tang & Jang, 2008). As noted by Chung et al. (2015), apart from being the most commonly used communication medium for accessing information about destinations, destination websites provide the setting in which potential travelers build their first impression of a place. If the quality of a website is perceived as unsatisfactory, it is highly likely that users will switch to another source of information or even change their travel destination. In contrast, a satisfactory browsing experience will elicit continuous website use intention and enhance positive emotional assessment of a travel destination. Therefore, there is likely to be a positive relationship between satisfaction with browsing a website promoting products or services, and an affective association with said products or services. Jalilvand et al. (2012) evidenced that overall satisfaction with the web experience has a direct influence on the formation of user perception towards a specific entity conveyed on a website. Perception predisposes a person to act or perform in a certain manner, as shown in studies on traveler behavior (Hrubes, Ajzen, & Daigle, 2001; Lee, 2007; Sparks, 2007). Along these same lines, Lu, Lu, and Zhang (2002) also argue that consumers’ satisfaction with their online browsing experience, alongside website usability and perceived security, is fundamental in determining their affective associations. Similarly, Chung et al. (2015) assert that website quality is positively related to the user's perception of website usefulness and feelings of satisfaction with the browsing experience. Positive affect towards the destination website and the destination itself is derived only when potential users perceive the website to be useful and feel satisfied with their browsing experience. Although the literature on tourism has broadly examined the role of consumer satisfaction, there is still insufficient evidence of the specific relationship between satisfaction with the browsing experience and affect towards the travel destination itself in the web environment. Thus, the following hypothesis is proposed: H1. Online satisfaction has a positive impact on the affect towards a travel destination. 2.3. Perceived risk in the online environment and affect towards a travel destination Perceived risk online can be defined as the feeling of insecurity and vulnerability experienced while browsing a website (Alcántara-Pilar et al., 2015). Many researchers acknowledge perceived risk in the online environment to be a key element in the first user–website interaction, on which the individual's overall assessment of that site is based (Chung et al., 2015; Syafiah, Razak, Marimuthu, Omar, & Mamat, 2014). Moreover, a large number of studies have reported perceived risk to be an essential determinant of the purchase intention in decisionmaking processes, as well as a fundamental ingredient for successful long-term business–customer relationships (Vainikka, 2013). The impact of uncertainty on purchasing decisions is even more strongly emphasized in the tourism and hospitality sector, because travel services are intangible, heteronomous, perishable, and simultaneously produced and consumed. As such, service users assume greater risks in online purchasing than consumers of tangible goods (Murray & Schlacter, 1990). Moreover, perceived risk in the case of online transactions is even greater than in traditional channels, for several reasons: there is no assurance that the user who is browsing a website will receive the products presented on the website; there is no sales person physically present; and there is a great distance between buyer and seller (Wang & Emurian, 2005). As websites remain the predominant medium in tourism for online

H2. The perceived risk online has a negative impact on affect towards a travel destination. 2.4. Perceived website usability and affect towards a travel destination Perceived usability refers to the value users attach to products and services with regard to the level of expected performance received during consumption (Chung et al., 2015). In the website context, usability refers to the website design and specific functional features that make a site easier to use (Alcántara-Pilar et al., 2015). Wang and Emurian (2005) identified four components of a website having good usability. The first component, that of helpful graphic elements, includes overall visual design, layout, appealing typography, appropriate font size, and quality of photography. The second component, namely

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good structural design, refers to usability in general, clear navigation hierarchy, ease of access to desired information, well-chosen text links within the page, and so on. The third component is clear content design, which refers to comprehensive and relevant website content, either textual or graphic, security and privacy policies, relevant domain name, secure payment guarantees, and the like (Seckler, Heinz, Forde, Tuch, & Opwis, 2015). Finally, the fourth component corresponds to social cues, such as information on the contact details of the company and complaints/suggestions options. Elsewhere, Suárez, Martínez, Álvarez, and Alva (2013) reported learnability, efficiency, memorability, and errors to be important aspects in the evaluation of website usability. In short, a website with good usability will have some of the following qualities: easy to navigate and use, good organization of the site, shows and explains products and services clearly and concisely, quick download, simple registration process, and positive browsing experience for users (Chung et al., 2015; Golja, Paulišić, & Slivar, 2015). Chung et al. (2015) demonstrated that a consumer's perception of website usefulness influences the formation of their attitude towards it, which consequently affects actual consumer behavior or future intention. It has also been demonstrated by multiple studies that perception of website usefulness and satisfaction with the browsing experience greatly contribute to consumers’ positive affect towards a travel website (Chung et al., 2015; Romanazzi, Petruzzellis, & Iannuzzi, 2011). Similarly, Green and Pearson (2011) found website usability to influence levels of consumer trust, decrease the perceived risk online, and enhance the intention to continue using the website, as well as fostering a positive emotional assessment of the travel destination. The same authors demonstrated that website usability influences several outcomes that are important for businesses that struggle to attract, emotionally engage – and hence, retain – customers. However, while the majority of previous studies examine the indirect relationship between website usability and affect towards a travel destination, little work has been done so far to explore the nature of the direct relationship between these two constructs. Moreover, while the field of usability has been traditionally focused on ease of use and functionality, based on observable cognitive activity, only recently have marketing practitioners and web designers begun to pay closer attention to the affective aspects of users’ interaction with the product when evaluating usability (Norman, 2003). New avenues in affective research have been opened up by the work conducted by Spillers (2003), Jordan (2002), and Desmet (2002), who have advocated a broader focus on pleasure and emotion in the usability and design of a product and the user experience. However, those studies explore the affective aspects of user experience, specifically in the context of mobile handsets and communication devices (Lindholm, Keinonen, & Kiljander, 2003). In tourism, the nature of this direct link between website usability and users’ emotional responses to the online experience remains under-researched. To contribute to bridging the tourism literature gap, the present research examines the direct link between users’ evaluation of website usability and their feelings towards the travel destination, as a product purposively designed and communicated on the site. Thus, the following hypothesis is proposed:

Fig. 1. Research model and hypotheses.

AFFi = β0 + β1 SATi – β2 RISKi + β3 USABi + ui

(1)

where AFFi is the affect towards the travel destination, SATi is the online satisfaction, RISKi is the perceived risk online, and USABi is the perceived usability of the website. According to the proposed hypotheses, it is expected that β1 and β3 will present positive values and β2 a negative one. 3.2. Research procedure and data collection In order to fulfill the research objectives, a website was created for a fictitious tourist destination called Buyuada (see Appendix 1). This required a professional website to be purpose-built, with its own domain name, providing information on the destination. The site was hosted via a domain belonging to the researchers, enabling them to simulate natural browsing conditions at all times for the subjects. With regard to the site design, the works conducted by Moss (2004) and Nielsen (2009, 2011) were followed as a guide (see Table 1). As shown in Appendix 1, following the recommendations made by Nielsen (2009, 2011) on menu options and consistent browsing, the website menu was located on the left, to make browsing easier for the user. The site also included high-quality images in all the sections, and detailed information on the different options available in terms of hotels and restaurants. The font selected was Verdana, widely recommended for its readability on the Internet (Nielsen & Loranger, 2006) and often used on other destination websites. A section was also included for flight reservation in the main menu, structured in tables as recommended by Nielsen (2011). All the services available (flight selection, hotels, and restaurants) provided a reservation option, so that users could add items to their cart while browsing the website. The decision to use a fictitious destination was made with the Table 1 Design factors for the website. Source: Own elaboration, based on Moss (2004) and Nielsen (2009, 2011)

H3. Perceived website usability has a positive impact on affect towards a travel destination.

Browsing Menu option style Page length Pop-ups Product information Scroll bar

3. Research methodology 3.1. Theoretical model The model defined to analyze the relationship between online satisfaction, perceived risk online, perceived website usability, and affect towards a travel destination is shown in Fig. 1. A regression model was used to test the research hypotheses. The model was estimated using the following equation:

Design of the structure

4

The information conveyed to users via icons, links, and images will be easy to use. The main options, icons, and symbols will be those commonly found on the Internet. The length of each page will not be excessive. There will be no pop-ups on the site. The product information will be organized in tabular form. The pages will be separated by category and adjusted so as to avoid the user having to use the scroll bar. Recommended guidelines for designing the site will be applied, with information structured around where the user finds themselves. The site will be divided into categories, but not overly so.

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3.4. Measurements

intention of avoiding a scenario in which the subjects’ previous awareness of, or attitude towards, the destination might affect the results. In this same regard, Dahlén, Friberg, and Nilsson (2009) used fictitious brands to minimize the possibility of differences between subjects, as using real brands could have meant that some individuals had preconceived representations and associations. Similarly, Nelson, Yaros, and Kerum (2006) recommend using fictitious brands as this gives the researcher greater control over the possible effects of the subjects’ past experiences. The subjects were selected by an external company commissioned to establish an online survey panel for the research. The company contacted each panel member by email, according to the gender and age quotas that had been pre-established. The subjects who agreed to participate in the research were then guided to an initial webpage displaying an introductory text. The purpose of this introduction was to thank them for their contribution and reassure them that the datagathering and analyses were entirely anonymous (see Appendix, Table A1). Subjects were then invited to browse the website and put together their own tourism package composed of an outward flight, a return flight, hotel accommodation, and a restaurant, from the multiple options available (see Appendix, Table B1). The aim of this task was to ensure that subjects were fully engaged in the browsing process from the outset, by capturing their attention and concentration for the entire browsing period. In line with the recommendations of several authors (Crespo-Almendros, Del Barrio-García, & Alcántara-Pilar, 2015), subjects were also offered an incentive to achieve the optimum result for the task and complete the subsequent questionnaire, in the form of a free prize draw to win an iPod Touch. Once they had completed the task and browsing was complete, subjects were redirected to a questionnaire.

In line with the proposed hypotheses, the variables used in the present study were: affect towards the travel destination, online satisfaction, perceived risk online, and perceived website usability. The most commonly-used scale for measuring emotional states is that developed by Russell (Kim & Richardson, 2003). Russell (1980) explored the multidimensionality and psychometric characteristics of affect and identified four polar pairs of affects that were positioned in the coordinate system as follows: pleasant (0°), exciting (45°), awakened (90°), worried (135°), unpleasant (180°), depressed (225°), dormant (270°), and relaxed (315°). Eight interval positions were used for circular ordering of emotional expressions related to the object of interest. In other words, instead of a circular ranking of the original pairs of affects, bipolar categories are modified and typically assessed by placing them on the semantic differential scales (Jenkins, 1999). Russell's technique has acquired great popularity, albeit in a somewhat simplified form, in a wide range of behavioral sciences. Following the work of Artigas, Vilches-Montero, and Yrigoyen (2015) and Baloglu and Brinberg (1997), in the present study a seven-point semantic differential scale with 4 items was proposed to capture the affect towards the travel destination (see Table 3). Online satisfaction was also measured using two items on a sevenpoint semantic differential scale adapted from Hao, Yu, Law, and Fong (2015). Perceived risk online was measured by means of a three-item, three-point Likert scale from Wakefield and Whitten (2006). Finally, perceived usability was measured using a seven-item, seven-point Likert scale from Kirakowski, Claridge, and Whitehand (1998), also used by other authors such as Flavián, Guinalíu, and Gurrea (2006) and Alcántara-Pilar et al. (2015) (see Table 3). 4. Data analysis

3.3. Sample

4.1. Analysis of the psychometric properties of the scales

The final sample comprised 228 Spanish Internet users. The sample was well balanced in gender terms, with 68.28% men (155) and 31.72% women (73). The minimum age was 18 and the maximum was 64, giving an average age of 38.7 years. The sample was quite similar to the proportion of Internet users in the Spanish population at that time in terms of gender balance, according to data from the Spanish Association for Research Media (AIMC, 2012). Slightly larger differences were identified between age groups, particularly in the ‘25–35 years’ and ‘over 35’ categories (see Table 2). The subjects were also highly experienced in using the Internet, with 66.08% of them browsing online for over 10 hours a week. As regards educational level, the sample was divided into three subgroups: primary education only/no qualifications; secondary-education qualifications; and university-level qualifications. The highest percentage was for university-level qualifications (56.58% of the sample), followed by secondary-education qualifications (40.35%), and no qualifications (3.07%). In Spain, over 95% of Internet users have secondary-level qualifications or university-level qualifications (AIMC, 2012).

Prior to testing the hypotheses it was necessary to examine the validity and reliability of the multi-item scales used in the present study. For this purpose, a confirmatory factorial analysis (CFA) was used. The CFA demonstrated that all the different scales presented sound psychometric properties, as all the standardized coefficients were significant and very close to one, while the individual reliability of each indicator was above the recommended limit of 0.50. The overall goodness-of-fit indices and the composite reliability (CR) and average variance extracted (AVE) indices were also, in all cases, well over the recommended values (Kline, 2011) (see Table 4). The discriminant validity of the four constructs was tested following the procedure proposed by Fornell and Larcker (1981), according to which the square root of the extracted variances and the correlations between constructs are compared (see Table 5). It can be seen that the average variance extracted value for each construct is above 0.50 and the square roots of these variances are greater than the correlations between constructs, so the results confirm a good level of discriminant validity for multi-item scales. Once the psychometric properties of the measurement scales had been examined, the values of the variables were determined by the average of the items considered within each of them – that is, four for affect towards the destination, two for online satisfaction, three for perceived risk online, and seven for perceived usability.

Table 2 Sample divided by gender and age groups.

18–25 26–35 > 35 % Total Spanish Users (AIMC, 2012)

Men

Women

% Total

Spanish Users (AIMC, 2012)

23 88 44 155 (68.28%) 56.1%

10 36 27 73 (31.72%) 43.9%

33 (14.5%) 124 (54.4%) 71 (31.1%) 228 (100%)

19.2% 28.2% 52.6%

4.2. Regression results Table 6 shows the results of the regression analysis. Affect towards the travel destination is influenced by online satisfaction, perceived risk online, and perceived usability. All the independent variables are statistically significant at the 0.01 or 0.05 level. The positive coefficient of SAT and USAB (βSAT– 5

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Table 3 Measurements. Description

Mean

Affect towards the travel destination (AFF) The image of the destination that this website has generated is … AFF1. Bad/Good AFF2. Negative/Positive AFF3. Unfavorable/Favorable AFF4. I don´t like/I like Online satisfaction (SAT) Overall, how do you feel about your Internet experience? SAT1. Very dissatisfied/Very satisfied SAT2. Very displeased/Very pleased Perceived risk online (RISK) Whilst I was browsing this website, and due to its characteristics, I felt that … RISK1. There is a high risk of loss if I make a reservation via this site RISK2. There is a major risk involved in making a reservation via this site RISK3. Making tourism reservations via this site is risky Perceived usability (USAB) Please assess the website you have just browsed … USAB1. Everything on this website is easy to understand USAB2. This website is simple to use even for the first time USAB3. Finding the information I need on this website is simple USAB4. The content structure on this website is easy to understand USAB5. It is easy to find your way around this website USAB6. The way in which the content on this site is organized enables me to know where I am when I browse through the different pages USAB7. When I am browsing this site I feel in control of what I can do

S.D.

Percentage 1

2

3

4

5

6

7

5.50 5.50 5.45 5.42

1.56 1.55 1.58 1.64

2.7 2.9 3.3 4.1

4.3 3.9 4.3 4.5

5.7 5.5 5.7 5.3

8.8 8.8 7.8 9.0

15.7 16.3 17.1 16.1

32.0 32.7 33.1 31.0

30.8 30.0 28.8 30.0

5.18 4.90

1.60 1.78

3.3 5.9

5.3 9.0

6.7 4.9

13.9 16.3

18.0 16.7

31.2 28.0

21.6 19.2

3.43 3.39 3.39

1.79 1.78 1.84

18.2 18.3 19.0

17.5 19.2 20.0

17.1 15.7 15.7

18.2 18.8 15.7

13.9 13.5 13.3

9.4 9.4 10.2

5.7 5.1 6.1

5.31 5.41 5.39 5.42 5.46 5.34

1.58 1.64 1.58 1.58 1.63 1.65

3.3 4.7 4.5 3.5 3.5 5.3

4.9 4.3 2.9 4.1 5.1 3.7

6.5 4.5 4.7 5.5 5.5 4.9

7.8 8.0 9.6 9.0 7.3 9.4

21.8 16.5 20.4 16.9 15.5 16.7

31.4 34.7 31.0 34.1 32.5 34.3

24.3 27.3 26.9 26.9 30.6 25.7

5.34

1.57

3.9

3.5

5.7

10.2

19.4

32.8

24.5

Table 6 Estimation of the regression model.

Table 4 Analysis of the psychometric properties of the scales (standardized coefficients) and goodness-of-fit índices.

Coefficient Items

R2

Coef. (t-value)

CR

AVE

Intercept 1.395 SAT 0.415 RISK −0.066 USAB 0.403 Sample size = 228 2 Adjusted R = 0.61 Model F-statistic = 245.41***

a

0.91 0.97 0.86 AFF1 0.96 AFF2 0.96 (37.23) 0.92 AFF3 0.94 (32.79) 0.89 AFF4 0.91(33.10) 0.84 SAT1 0.97a 0.94 0.87 0.78 SAT2 0.79 (30.48) 0.62 RISK1 0.90a 0.82 0.95 0.86 RISK2 0.94 (35.15) 0.87 RISK3 0.94 (34.50) 0.88 USAB1 0.88a 0.77 0.97 0.83 USAB2 0.92 (32.33) 0.84 USAB3 0.91 (27.88) 0.82 USAB4 0.93 (26.88) 0.86 USAB5 0.92 (26.91) 0.85 USAB6 0.91(25.85) 0.82 USAB7 0.91(26.80) 0.83 SB- χ2 (d.f.)=206.05 (98); χ2 normed=2.10; RMSEA=0.047; NFI=0.99; CFI=1.00; IFI=1.00; CN=318.42; GFI=0.90

t-statistic

p-value

5.963 10.720 −2.426 9.226

0.000 0.000 0.015 0.000

*** *** ** ***

Note: Affect towards the destination is the dependent variable. ** Significance level: p < 0.05. *** Significance level: p < 0.01.

R2: Reliability; CR: Composite Reliability; AVE: Average Variance Extracted. a Note: Fixed parameter. Value not calculated since the parameter was established at 1 in order to set the scale for the latent variable.

Table 5 Discriminant validity.

AFF SAT RISK USAB

AFF

SAT

RISK

USAB

0.93 0.78 −0.33 0.74

0.88 −0.32 0.78

0.93 −0.41

0.91

Note: Diagonal elements in bold are the square root of the average variance extracted (AVE) between the constructs and their indicators. Off-diagonal elements are correlations between the constructs.

Fig. 2. Influence of satisfaction, perceived risk, and perceived usability on affect towards the travel destination.

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J.M. Alcántara-Pilar et al. > AFF=0.415, p < 0.01; βUSAB– > AFF=0.403, p < 0.01) indicates that online satisfaction and perceived usability are positively associated with affect towards the travel destination, hence H1 and H3 were supported. The negative coefficient of RISK (βRISK– > AFF=−0.066, p < 0.01) suggests that the higher the perceived risk online, the lower the affect towards the travel destination. This result therefore supports H2. The effect of satisfaction, perceived risk, and perceived usability on affect towards the travel destination is represented in Fig. 2, which was generated from a simple slope analysis. Using this analysis, it can be determined whether the three independent variables influence the dependent one in accordance with the directions proposed in the hypotheses. As shown in Fig. 2, the effects of perceived usability and satisfaction on affect towards the travel destination are similar, especially for the higher values indicated by the respondents. Moreover, the model explains a significant percentage of the observed variance (above 0.60). This value is sufficient when using cross-sectional data (Gujarati & Porter, 2009; Wooldridge, 2006). Finally, the value of the Fstatistic indicates that the regression equation correctly maps the relationship between the dependent and independent variables. Having tested the proposed hypotheses, an additional moderation analysis was also performed. Belanche, Casaló, and Guinalíu (2012) found that perceived risk online exerted a moderating effect on the relationship between perceived usability and online satisfaction. This result led us to assess the possible moderating effect of perceived risk online on (a) the relationship between online satisfaction and affect towards the destination and (b) the relationship between perceived usability and affect towards the destination. As far as the authors know, no other study in the tourism sector has examined this moderating effect. The method proposed by Preacher, Rucker, and Hayes (2007) was applied to estimate two moderated regression models, using the PROCESS statistics tool (Hayes, 2013). This method does not make any baseline assumptions regarding the shape of the sample distribution, and uses bootstrapping. For the first model a moderated regression was used, where the dependent variable was ‘affect towards destination’ (AFF) and the independent variables were ‘perceived usability’ (USAB) and the interaction effect (USAB x RISK). The results showed that perceived risk exerted no moderating effect in the relationship between usability and affect towards the destination, since the interaction effect was found to be non-significant (βUSABXRISK– > AFF=0.002, p > 0.10) (see Table 7). A second moderated regression model was conducted to examine the possible moderating effect of perceived risk online in the relationship between satisfaction and affect towards the destination. The results showed perceived risk to have a significant moderating effect, since the interaction effect between satisfaction and perceived risk (SAT x RISK) was found to be significant in this case, albeit low in magnitude (βSATXRISK– > AFF=0.037, p < 0.05). As shown in Table 8, identifying three levels of perceived risk (low risk: −1.721; moderate risk: 0.000; high risk: +1.721), satisfaction during browsing will be a more important antecedent of affect among those subjects who present a higher

Table 8 Moderated regression model. Online satisfaction on affect towards the destination moderated by perceived risk online. Coefficient

Intercept 5.495 115.720 RISK −0.111 −3.997 SAT 0.648 20.756 SAT x RISK 0.037 2.392 Sample size = 228 2 Adjusted R = 0.554 Model F-statistic = 201.606*** Conditional effect of X on Y at values of the moderator(s): RISK Effect t-statistic −1.721 0.583 12.420 0.000 0.648 20.756 1.721 0.713 20.319

Intercept 5.471 RISK −0.029 USAB 0.726 USAB x RISK 0.002 Sample size = 228 Adjusted R2 = 0.53 Model F-statistic = 178.647***

t-statistic

p-value

108.186 −0.976 19.643 0.162

0.000 0.329 0.000 0.870

p-value 0.000 0.001 0.000 0.017

p-value 0.000 0.000 0.000

*** *** *** **

*** *** ***

Note: Affect towards the destination is the dependent variable. ** Significance level: p < 0.05. *** Significance level: p < 0.01.

level of perceived risk (βSATK– > AFF=0.713) than among those presenting a lower level of perceived risk (βSAT– > AFF=0.583). In other words, for those with a higher level of perceived risk, the benefits in terms of affect towards the website of a tourism destination will be greater (compared to those who present a lower level of perceived risk), if their browsing process successfully leaves them feeling satisfied. 5. Discussion In the tourism sector, the elements that help create user affect towards a travel destination have special relevance for travel-related businesses. To date, several works have addressed the antecedent effect of perceived website usability (Pereira & Baranauskas, 2015; Romanazzi et al., 2011), online satisfaction (Sabiote, Frías, & Castañeda, 2012), and perceived risk online (Kim et al., 2009; Yang & Nair, 2014) on the formation of affect towards a travel destination. The present work proposes an integrative model that explains users’ online behavior and provides a relevant contribution, with respect to the research to date, from both theoretical and practical perspectives. As one of the most widely-explored constructs in the field of tourism research, destination image has predominantly been studied from a cognitive or/and a cognitive–affective approach. The cognitive component of the image refers to beliefs and knowledge about an object, in this case the tourism destination, while affective refers to feelings about it (Baloglu & Brinberg, 1997; Baloglu & McCleary, 1999; Golden & Zimmer, 1988; Holbrook, 1978; Walmsley & Jenkins, 1993; Ward & Russell, 1981). In marketing and consumer behavior those two components are treated under the labels of ‘beliefs’ versus ‘affect’. In other words, the cognitive component is the knowledge about the destination's objective attributes and refers to the appraisal of physical features of environments (Genereux, Ward, & Russell, 1983). In this paper, since the research focus is a fictitious destination created ad hoc (Buyuada), it is expected that the subjects have no previous knowledge or beliefs regarding the target destination. For this reason, the study only considered the affective component of the image – ‘affect towards the destination’ – which the subjects would indeed form after visiting the destination website. Hence, this study aimed to explore whether the consumer's satisfaction while browsing, their perception of risk online, and the perceived usability of the travel website can influence their affect towards a travel destination. In order to develop a framework that enables academics and practitioners to identify the antecedents that can contribute to affect towards a travel destination, the work explored the literature on tourist online satisfaction, perceived website usability, and perceived risk online. It was found that there is still insufficient

Table 7 Moderated regression model. The relationship between perceived usability and affect towards the destination, moderated by perceived risk online. Coefficient

t-statistic

***

***

Note: Affect towards the destination is the dependent variable (Y). *** Significance level: p < 0.01.

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Marketing practitioners can manipulate this emotional response to tourism destination websites so as to enhance revisit intention. Since the image of a destination conveyed by the destination website has a substantial impact on tourists’ purchasing behavior, managers should be more concerned with the features of the website and its functional characteristics (Alcántara-Pilar & Del Barrio-García, 2015). Thus, they should promote their destinations using a website that ensures a high level of tourist satisfaction during browsing, a strong perception of website usability, and a low perceived risk online, in order to elicit positive affect towards the travel destination and, therefore, to encourage more visits to that destination. In this way, destinations can develop a more competitive position in the markets where they operate. Moreover, investing in a good website design is shown to be a prerequisite for improving affect towards a travel destination during browsing. This issue needs to be taken into account by those firms and institutions offering e-commerce services (particularly those operating in the tourism-related field, such as hotels, tour operators, travel agencies, and public bodies), as consumers often conduct online research to compare destinations and services. As also demonstrated by Wood (2004), it is important to remember that website design is not an end in itself, but is rather a means of facilitating purchase and information-search on the part of the user. In this regard, when designing a website it is not sufficient to follow the recommendations of Nielsen and Loranger (2006), for example, by simply drawing on heuristic lists of features for usability. It is also essential to have a user-friendly site design, for example by seeking their views on its usability via different questionnaires. There are numerous examples of firms that have improved profits by investing in usercentered website design. For example, in the late 1990s IBM increased its e-commerce sales by 400% thanks to improvements made to the usability of ibm.com, while Dell achieved an increase of $33 million in its daily online sales following an initiative to enhance the usability of dell.com (Black, 2002). Finally, it is essential that firms create positive affect towards the travel destination they offer via their websites, as a way to achieve a conative response among consumers (Alcántara-Pilar et al., 2015). Firms have to transfer positive experiences to users, to enable them to enjoy their browsing time. It is also crucial to develop a website design that helps users to feel secure when browsing, searching for destination information, or booking a tourism package. Usability can provide those elements that make the browsing experience more pleasurable and secure. This will also develop more affect towards the travel destination, as the present results reveal.

evidence of the specific relationships between these three variables and the affect towards a travel destination in an online environment. The results of the regression model revealed that tourists’ online satisfaction, perceived website usability, and perceived risk online are significant antecedents that influence the affect towards a travel destination generated online. The statistically significant and positive relationship between ‘destination affect’ and ‘online satisfaction’ confirms previous research, which identified that the greater the tourist satisfaction during browsing, the more positive their affect towards a destination will be (Chung et al., 2015; Lu et al., 2002). Furthermore, the statistically significant and negative relationship between ‘destination affect’ and ‘perceived risk online’ suggests that the higher the perceived risk online, the lower the affect towards a travel destination. Since in the tourist literature there are no sound theoretical arguments in this regard, these findings, supporting the assumption made in this study, make a particularly relevant contribution of the paper. From the statistically significant and positive relationship between ‘destination affect’ and ‘website usability’, the perception of website usability is found to be a direct determinant of the tourist's affect towards a travel destination. This is consistent with the thrust of numerous studies (Bai et al., 2008; Belanche et al., 2012), namely that the perceived usability of a destination website greatly contributes to the positive affect towards that site and, indirectly, towards the destination itself. From the perspective of consumer behavior theory, this research helps in understanding the influence of satisfaction during browsing on users´ affect towards a travel destination. The results confirm that users who experience a high level of satisfaction and perceive the website to be highly usable will generate positive affect towards the travel destination promoted on that site. On the other hand, it is confirmed that perceived risk online negatively affects perceptions of the travel destination and users’ intention to engage in an online transaction. This can lead users to look for a different website as a source of information about the desired destination or even change the destination. A moderating effect of the perceived risk has also been identified in the relationship between online satisfaction and affect towards the destination, this relationship being more important for the subjects who perceive a higher risk during browsing. The explanation for this result might be that in situations of high perceived risk, users are more likely to analyze in detail the information displayed on the website (Belanche et al., 2012); as a result, high satisfaction during browsing can help them overcome those fears and form a more favorable opinion about the website and the tourist destination itself. On the contrary, in situations of low perceived risk, users may pay less attention to the information displayed on the website, which could partly reduce the effect of online satisfaction on the formation of the affect towards the destination. Therefore, destination marketers and managers must pay more attention to consumer satisfaction with their websites and continuously strive to develop their websites’ characteristics to match consumers’ needs and expectations.

7. Limitations and future research As with all research, the present study has certain limitations that are important to note and that may point to potential research topics for the future. The first limitation is related to the experimental design, which required users to browse a website promoting a fictitious tourist destination and put together a tourism package from the options available. Although the site was professionally designed, the fact that the destination was fictitious may have influenced the attention paid by respondents while processing the information and/or their emotional response towards the destination. Future studies could employ a more real-life approach to examine perceived usability, online satisfaction, and perceived risk in the formation of affect towards a tourist destination – by using a replica of the website of a real destination, for instance. A second limitation of the present work is its use of an Internet user panel as a sample. This entails the risk of subjects’ responses being affected by the incentive offered. During the database-purging process, atypical cases were identified and removed to mitigate this possible bias. That said, other researchers may wish to use different informationgathering methods compatible with the aims of this work, such as a hall

6. Managerial implications A number of interesting implications for management arise from the present work. Firstly, while previous studies explore affective image in the context of traditional media, it has not been sufficiently examined in the online context. In this respect, the present research is framed within a virtual environment since the Internet is the predominant source of information used by tourists for planning and choosing a travel destination. Furthermore, although online satisfaction, perceived website usability, and perceived risk online have been analyzed in the general tourist literature, this paper provides a new perspective, considering them as antecedents of affect towards a travel destination.

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research would need to be replicated in different national subsets. Finally, it would also be interesting to make a comparison between other cultures, focusing particularly on the degree of bilingualism of the subjects and analyzing other dependent variables such as destination loyalty.

test. This would involve stopping tourists in the street and inviting them to use the website in a room specially prepared for the purpose, where the browsing process can be monitored by the researchers at all times. A further limitation was the measurement of perceived risk during browsing and compiling the tourism package. This being an experimental setting in which users faced no monetary risk, their perception of risk differed from that arising in a real-life situation. However, Al Kailani and Kumar (2011) note that when users browse a website they perceive different levels of risk, depending on their personal characteristics – not only financial risk. Looking to the future, it would be valuable for further studies to take the cultural factor into account when analyzing the affect towards a travel destination generated through websites. It is highly likely that cultural values significantly mitigate the power of satisfaction, perception of online risk, and perceived usability of a travel website to influence the tourist's affect towards a destination. To this end, the

Acknowledgements The authors appreciate the financial help provided via a research project of the ADEMAR group (University of Granada) under the auspices of the Andalusian Program for R & D, number P12-SEJ2592, and a Research Program from the Faculty of Education, Economy and Technology of Ceuta. The research work of our Serbian collaborator is supported by the Ministry of Education, Science and Technological Development, Republic of Serbia (project number 176020).

Appendix 1. Experimental design diagram

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(See Figs. A1–D1). Fig. A1. The Buyuada website homepage.

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Fig. B1. Information about hotels.

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Fig. C1. Information about restaurants.

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Fig. D1. Information about flights.

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(See Tables A1 and B1).

Table A1 Introductory text (text translated from Spanish into English). Good morning/good afternoon. We would like to ask you for your help in this study, and we are grateful for your collaboration. Next you will see a series of questions which we would like you to answer. Your responses need to be as honest as possible so that our research is based on reliable results. There are no ‘correct’ answers – it is simply a question of expressing your opinion. Your responses will be analyzed anonymously, and complete confidentiality is guaranteed. Once you have answered these questions, you will be invited to visit a website about a tourist destination. Following your visit, you will be asked to complete a further questionnaire based specifically on the website you have just consulted. Thank you very much, once again, for your collaboration.

Table B1 Instructions given to the user (text translated from Spanish into English). Buyuada: Next, you will visit a website about a tourist destination – the island of Buyuada in the Mediterranean. The visit will last a minimum of 2 min. Buyuada is becoming increasingly popular as a tourist destination. Your task is to imagine a situation in which you are thinking of going on holiday in the next few months, during mid-season. To this end, you need to design a tourism package on Buyuada that includes the following: – An outward flight – A return flight – A hotel for your stay – A restaurant – An activity or excursion To book these services you must select the options of your choice, press the button ‘add to basket’ and confirm your bookings using the shopping trolley icon. Please bear in mind that, among all the alternatives you will find, there is one option that is superior to the others in terms of quality/price. All those participating in the study who have responded to the questionnaire and who have chosen the best option in terms of quality/price will be entered into a draw to win an iPod-Touch. As a global leader in domain names and Internet security, Verisign ensures the security, stability and resiliency of this website. Thank you very much for your collaboration. Enter the website

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