Dimensions and basic emotions

Abstract

Emotions are crucial to explaining consumer behavior. Following an in-depth review of the literature, we identified three types of emotional stimuli affecting consumers: emotions produced by the item being purchased, emotions related to various aspects of the evaluation process, and emotions stemming from factors unrelated to the purchase itself. Previous studies have identified two approaches to analyzing emotions, namely, a categorical approach, which looks at basic emotions, and a dimensional one, which studies the dimensions of the emotions. Although these approaches are thought to be complementary, very few studies have been conducted on the subject, and none have specifically examined it in the context of the tourism industry. We have thus conducted a detailed and empirical study measuring the basic emotions and emotional dimensions elicited by hotels in 841 tourists. We demonstrate the existence of differences in both basic emotions and emotional dimensions among tourists and the additional benefit of using both approaches to study them. The results of this research will facilitate the design of appropriate marketing strategies, thereby helping hospitality managers adapt to the different established tourism segments defined by emotions.

Keywords

Hotel emotions consumer behavior basic emotions emotional dimensions

Introduction

Over the past few decades, a number of studies on consumer behavior have shown that both cognitive and affective factors have a strong impact on people’s evaluations and behavior(Bagozzi, 1982; Campbell, 2007; Dean et al., 2008; Hirschman and Holbrook, 1982). Specifically in relation to the tourism industry, various authors have shown the importance of emotions and the strong influence they can have on consumers’ assessments of the tourism offer (Decrop and Snelders, Gnoth, 1997, 2004; Kim et al., 2011). In this regard, it has been shown that the formation of a destination’s image in tourists’ minds is affected by both cognitive and affective factors (Baloglu and McCleary, 1999; Bigné et al., 2001; Chen and Uysal, 2002; Moutinho, 1987; Pike and Ryan, 2004; San Martín and Rodríguez, 2008).

Indeed, emotions have been found to explain consumer behaviors in the evaluation of hotel chains that cannot be predicted from the study of just cognitive factors (Mattila, 2006). Thus within the context of consumer evaluations of tourism products, emotions are thought to play an important and essential role in the choice of supplier (Barsky and Nash, 2002; Decrop and Snelders, 2004; Gnoth, 1997; Goossens, 2000; Gountas and Gountas, 2007; Pike and Ryan, 2004). The motivation to purchase tourism services and choose a given destination is influenced by the tourist’s perceived affective feelings (Gnoth, 1997; Goossens, 2000; Jang et al., 2009; Pomfret, 2006). Likewise, in the context of leisure tourism, the highest motivation has been found to come from exciting emotions (Decrop and Snelders, 2004). Galloway et al. (2008) have determined that one of the most important dimensions in the choice of a wine tourism destination is the ability to have experiences and feel emotions.

Previous studies have identified two approaches to determining how people experience emotions (Esses and Maio, 2002; Mano, 1991; Richins, 1997; Russell, 2003; Russell and Barrett, 1999; Wirtz and Bateson, 1999; ): a categorical approach, which studies basic emotions, and a dimensional one, which examines the different dimensions of emotions and the degree to which the customer feels them. While these two approaches are currently widely believed to be complementary (Dean et al., 2008; Esses and Maio, 2002; Russell, 2003), there is a dearth of research on how they might apply to service evaluation. Likewise, to date, no studies have been conducted on tourism that not only use both approaches but also evaluate the pros and cons of doing so.

This study aims to examine the complementarity of these approaches in relation to the tourism industry. To this end, we conducted an empirical study measuring, in a complementary manner, both the basic emotions and the emotional dimensions evoked in tourists by hotels.

The concept of emotion

The concept of emotion has been widely discussed in the scientific literature. Kleinginna and Kleinginna (1981) identified 101 definitions, while Cohen et al. (2006) established the use of 175 different terms referring to emotions felt by consumers in the product evaluation research. However, despite such research in the field, there is no single clear definition accepted by the majority of the scientific community (Scherer, 2005).

Although emotion has been defined in many ways (Kleinginna and Kleinginna, 1981;Richins, 1997; Scherer, 2005), these definitions share certain similarities, which make it possible to establish minimum prototypical components that can be used to establish a general definition of the concept (Richins, 1997).

The componential theory of emotion is based on the idea that emotions are not exclusively cognitive, but rather consist of multiple components, which collectively support the definition of emotion as a whole (Ortony and Turner, 1990; Russell, 2003; Scherer, 2001, 2005). According to this theory, the following minimum prototypical factors can be considered emotional components:

Stimulus: This refers to the need for there to be an intentional object or stimulus.

Cognitive assessment: The literature has described the need for there to be a cognitive assessment in order to have emotions. Our definition includes cognitive assessment as a component of emotions in order to distinguish them from visceral responses that do not require such an assessment.

Attribution: This component refers to the identification of the emotional object or stimulus generating the emotion.

Physiological expressions: The triggering of physiological reactions is an essential feature of emotions.

Feeling of pleasure–displeasure: This feature refers to an individual’s perception of an emotional experience as being pleasant or unpleasant.

Qualitative sense: Humans experience emotions as being qualitatively unique, as if each were a different hue.

Action tendency: Emotions generate a tendency or willingness to perform an action.

Short-term process: Emotions are felt for a short period of time.

We will now use this definition of emotion to narrow down the types of emotions to be studied.

Influence of emotions on consumer evaluations of competing offers

The importance of studying emotions is due to the direct influence they have on consumers’ evaluations of offers (Bagozzi, 1997; Han et al., 2007; Hirschman and Stern, 1999). To understand how emotions influence consumer assessments, it is necessary to consider three different types of emotional influences (Garg et al., 2005; Han et al., 2007; Penz and Hogg, 2011). These three types of emotional influences are discussed in detail below.

Emotional influence produced by the product being evaluated

A product’s influence is grounded in its ability to create a symbolic representation in the mind, which then generates an emotional influence on the product evaluation strategy (Elliott, 1998; Laverie et al., 2002; Mittal, 1994).

From the perspective of evaluating purchase alternatives, it has been demonstrated that positive emotions toward a product usually increase the likelihood of a positive evaluation (Bagozzi, 1997; Oliver et al., 1997; Shiv and Fedorikhin, 1999).

Product symbolism is related to the cognitive–affective selection process (Laverie et al., 2002). It has been observed that the more important the symbolic component of a brand, the more likely customers are to choose an affective selection strategy, rather than a purely rational or cognitive one (Mittal, 1994). Moreover, product appreciation based on symbolic meaning has been shown to be the main reason for emotion-driven consumer choice (Elliott, 1998).

A distinction has been drawn in the literature between hedonic and utilitarian products (Hirschman and Holbrook, 1982; Moe and Fader, 2001). Affective components have been proven to have a greater influence in the purchase of hedonic products (Yeung and Wyer, 2004).

Separately, it has been observed that the quality–price ratio (Zielke, 2011) and the perception of the price paid (Gelbrich, 2011) lead to the formation of emotions toward a product. The influence of emotions on the perception of price has likewise been established (Gupta and Kim, 2010; Zielke, 2011).

The level of pleasure produced by the purchase of material products as opposed to experiential ones has also been compared, with experiences, such as going on a trip, outstripping the material. In this regard, Nicolao et al. (2009) showed that products involving significant experiences tend to produce more pleasure and displeasure than material ones.

With regard to tourism, it has been shown that, in order to effectively evaluate a destination, tourists must experience positive, negative, and neutral emotional associations (Pike and Ryan, 2004; Woodside and Lysonski, 1989; Yüksel and Yüksel, 2007) and that they use these affective associations to classify the destinations (Woodside and Lysonski, 1989). Destinations considered to be possibilities are affectively associated in a positive manner, while rejected destinations have negative affective associations (Jang et al., 2009; Woodside and Lysonski, 1989; Yüksel and Yüksel, 2007).

Several studies have looked at the influence of emotions on tourist satisfaction and loyalty. The degree of pleasure tourists feel as a result of a tourism service positively affects their loyalty to it (Bigné and Andreu, 2004; Bigné et al., 2005, 2008; De Rojas and Camarero, 2008; San Martín and Rodríguez, 2008). In the same vein, Yuan et al. (2008) found that the positive feelings generated in tourists by wine tourism services affect their satisfaction and that, in turn, this mix of satisfaction and positive feelings positively affects their intention to visit wineries, purchase wine, and return to the same destination. Charters et al. (2009) studied trips to wineries and found that the type of satisfying or unsatisfying experience can generate positive emotions that mitigate or completely offset the impact of negative emotions caused by the feeling that they must purchase wine.

Specifically with regard to tourism accommodations, Barsky and Nash (2002) showed that the emotions generated in tourists by hotels affect both their propensity to pay more and their loyalty to the establishment. Similarly, Mattila (2006) described how customers’ affective commitment to a hotel positively influences their loyalty to it. Han and Back (2006, 2008) conducted several studies establishing that positive emotions generated in tourists during their stay at a hotel positively affect customer loyalty. Ladhari (2009) described how emotions generated by satisfaction with a hotel significantly influence loyalty to the hotel. Likewise, in their investigation of hotel guests’ behavior, Han et al. (2011) found that service quality and perceived value affect the generation of positive and negative emotions in tourists, which, in turn, impact tourist satisfaction, while positive emotions have a positive effect on tourists’ loyalty. Additionally, Brunner-Sperdin and Peters (2009) demonstrated that tourists’ emotional state when staying at a hotel depends on their assessment of it, and Ladhari (2009) found that tourists’ perceptions of the quality of service provided by a hotel generate emotions.

Emotional influence produced by the evaluation process

The stress of choosing between products generates emotions that are not directly related to the item being purchased (Novemsky et al., 2007). In this regard, various factors have been shown to influence the importance of different attributes in purchase decision making, and consumers will sometimes trade a given amount of one attribute for a bit more of another (Drolet and Luce, 2004; Luce et al., 1999).

In relation to the above, some customers experience mixed (a blend of basic emotions) and opposing (both pleasant and unpleasant) emotions, when evaluating competing products (Chitturi et al., 2007; White and Yu, 2005) or when indulging in the consumption of products considered inappropriate but nevertheless consumed (Ramanathan and Williams, 2007; Xu and Schwarz, 2009).

It has been established that consumers avoid attribute trade-offs when the trade-off produces negative emotions (Drolet and Luce, 2004; Luce et al., 1999) and that difficulty in the decision-making stage generates negative emotions for consumers, affecting their product evaluation (Garbarino and Edell, 1997; Garg et al., 2005; Novemsky et al., 2007).

Other external aspects (i.e. unrelated to the product or purchasing process) influencing product evaluation include the environment and the purchasing situation (Mattila and Wirtz, 2000; Penz and Hogg, 2011; Wang et al., 2011). In addition, negative emotions due to a lack of stock have been shown to damage brand image (Kim and Lennon, 2011).

Emotions produced by stimuli other than the tourism product itself have also been shown to affect purchase option appraisals. Gnoth et al. (2000) found that emotions caused by problems at work can influence decisions to engage in tourism as an escape mechanism. Similarly, Labroo and Rucker (2010) induced emotions by having potential tourists recall sad events, generating anxiety and embarrassment in them, and showing how emotions unrelated to the product affect how people evaluate their feelings toward an advertisement for a tourist destination. Miao et al. (2011) found that customers’ emotional response to the behavior of other customers in a restaurant affected their evaluation of its service.

With regard to hotels, Mattila (1999) showed that ads developed by hotel chains generate emotions that influence the generation of a positive attitude and purchase intent.

Emotional influence generated by factors unrelated to product evaluation

A number of emotions unrelated to product evaluation, but that nevertheless affect it, have been described in the literature. For example, emotions caused by the weather have been shown to affect the purchasing process (Han et al., 2007).

People’s state of mind and emotions prior to the purchasing action can also impact their decision (Garg et al., 2005; Mano, 1999). Likewise, unrelated induced emotions have also been shown to affect customers’ evaluation process (Griskevicius et al., 2010; Kahn and Isen, 1993).

Another main aspect of offer evaluation is emotions produced by personal issues unrelated to the purchase, such as a divorce or the birth of a child (Hirschman and Stern, 1999; Noble and Walker, 1997).

Similarly, personality affects emotions and, thus, evaluation (Baker and Meyer, 2011; Faullant et al., 2011; Shiv and Fedorikhin, 1999).

Finally, certain demographic characteristics have been found to have a moderating influence on how emotions affect the evaluation process (Aaker and Williams, 1998; Albers-Miller and Stafford, 1999; Valenzuela et al., 2010).

Specifically with regard to tourism, in their study of airline customers, Gountas and Gountas (2007) demonstrated how personality is related to emotional mood states and how these, in turn, influence customer loyalty.

In our study, we will focus on emotions produced by the item being purchased, specifically, on emotions evoked in tourists by hotels.

Empirical study of basic emotions and emotional dimensions evoked in tourists by hotels

There are two main theoretical approaches to measuring emotional subjective experience (Richins, 1997; Russell and Barrett, 1999; Wirtz and Bateson, 1999): the categorical approach, which studies basic emotions, and the dimensional one, which looks at emotional dimensions and the degree to which these dimensions are perceived. ‘One approach views emotions in terms of continuous underlying dimensions that distinguish among emotional states, while the other views all emotions as stemming from a relatively small number of basic emotional categories’ (Havlena and Holbrook, 1986: 395). Thus, within the dimensional approach, some researchers believe that the emotional state can be determined exclusively based on the levels of arousal and pleasure. In contrast, researchers who use a categorical approach seek to determine which of a given set of basic emotions (e.g. fear, anger, joy, sadness, acceptance, disgust, expectancy, and surprise) a subject is feeling.

Each of these approaches has led to a different way of measuring emotions (Scherer, 2001). While the categorical approach measures the basic emotions within the emotional event, the dimensional approach measures the degree to which the emotional dimensions are felt.

Several studies have attempted to compare these two ways of measuring emotions from both a theoretical (Wirtz and Bateson, 1999) and an empirical (Havlena and Holbrook, 1986) viewpoint, but a clear conclusion has yet to be reached on which of the two approaches is preferable.

In this regard, Russell (2003) holds that the ‘dimensional perspective must be integrated with the categorical perspective’. Indeed, several studies on goods have used both models – categorical and dimensional – at the same time (Dean et al., 2008; Esses and Maio2002;). This idea of complementarity and the resulting joint use of the two methodologies has the advantage of enhancing the information obtained on emotions (Scherer, 2005). ‘For example, one can infer more about an experience when one knows that the consumer felt angry or ashamed than when one only has information on his level of arousal and displeasure’ (Wirtz and Bateson, 1999: 56).

In contrast, the use of just one methodology to measure emotions has the following drawbacks:

If only the emotional dimensions are measured, we might mistakenly consider two people to be feeling different emotions when they are actually feeling the same one (Russell and Barrett, 1999) or believe that they are feeling the same emotion when they are in fact feeling different ones (Russell and Barrett, 1999; Scherer, 2005) with different effects (Han et al., 2007). For example, sadness can generate different levels of activation and pleasure depending on the person and the moment in which it is taking place, while two different emotions, such as sadness and disgust, can cause the same level of activation and pleasure in two different people, yet result in different behaviors; for example, sadness might make consumers feel a need to buy to mitigate the negative emotion, while disgust is associated with the rejection of purchases.

If only a categorical approach is used, the distinctions that make two emotions with similar verbal labels (e.g. grief and sadness) different in each person may be missed. Measuring the levels of pleasure and activation generated allows us to appreciate the differences between them (Russell, 1980; Russell and Barrett, 1999; Wirtz and Bateson, 1999). Including emotional dimensions in basic emotions enables the identification of both similarities and differences (Wirtz and Bateson, 1999) and the level of intensity (Russell and Barrett, 1999) with which the emotions are felt.

Once the decision was made to use both the dimensional and categorical approach, it was necessary to decide on the scale of basic emotions to be used and the appropriate emotional dimensions.

Our argument took into account Richins’s (1997) recommendations, namely:

The statistical mean must include the range of emotions experienced most often in the various specific consumption situations.

In order to be used in surveys, the scale should be brief.

The scale must include words that are familiar and easy for consumers to understand.

Although, in contrast to these recommendations, some investigators recommend the use of open-ended questions to determine the range of emotions frequently experienced in a specific consumption situation (Esses and Maio, 2002), we ruled this option out due to the difficulty people have finding verbal labels to describe emotional situations. Moreover, people might use such a wide range of labels, or the frequency with which each one was used might be so low, as to render statistical treatment impossible (Scherer, 2005). We therefore applied Richins’s recommendations.

We then decided to use an existing scale of basic emotions used in science.

The decision to use the Positive and Negative Affect Schedule (PANAS) scale, developed by Watson et al. (1988), was based on the study of the most commonly used scales of basic emotions. The PANAS scale was used 19 times in 2010 and 2011 in the following journals dedicated to study of the role of emotions in consumer behavior: the Journal of Consumer Research, the Journal of Marketing Research, Marketing Science, Marketing Letters, Psychology and Marketing, Motivation and Emotion, and the Journal of the Academy of Marketing Science. In contrast, the Consumption Emotion Set (CES) scale (Richins, 1997) was used five times, and the Differential Emotions Scale (DES) (Izard, 1977) was used twice.

We then qualitatively adapted the PANAS scale to ensure that completion of the questionnaire would comply with Richins’s (1997) recommendations. To this end, we translated the emotions to Spanish, seeking equivalences that were both as faithful as possible to the original English and well suited to the context of hotel services. The emotions we included were interest, anguish, excitement (impatience), disgust, self-confidence, guilt, scared, antipathy, enthusiasm, pride, irritation, attentiveness, shame, creativity, inspiration, nervousness, decisiveness, affection, restlessness, activeness, liveliness, and afraid. Each emotion was measured with one item within a sentence designed to facilitate comprehension (e.g. ‘I felt enthusiastic about the chosen hotel’).

With regard to the emotional dimensions, an analysis of the various scales used by investigators and the different numbers of emotional dimensions they included revealed a broad consensus on the use of two dimensions (Chhetri et al., 2004; Fontaine et al., 2007), most often, the level of pleasure and the level of activation or excitement (Bigné et al., 2008; Oliver et al., 1997; Russell, 1980, 2003, 2005; Russell and Barrett, 1999; Scherer, 2001). In this regard, Bigné and Andreu (2004, 2005) have demonstrated the influence of the degree of pleasure and the degree of activation as segmentation criteria for tourists’ emotional dimensions. Likewise, Bigné and Andreu (2004) and Yüksel and Yüksel (2007) have shown that the degree of pleasure and activation felt by tourists positively affects their loyalty.

Drawing on these findings, we looked for a scale that had been used in tourism studies. Ultimately, we selected the scale developed and tested by Bigné et al. (2005, 2008). We chose this scale because the authors based it on Russell’s (1980) work on emotional dimensions and validated it in the context of tourism. The scale consisted of 12 items, representing the dimensions of arousal and pleasure. Arousal was measured on a 10-point semantic differential scale with 6 items, namely, depressed–cheerful, quiet–anxious, calm–enthusiastic, relaxed–nervous, passive–active, and indifferent–surprised. Six items were likewise used to measure pleasure, namely, angry–content, unhappy–happy, dissatisfied–very pleased, sad–joyful, disappointed–delighted, and bored–entertained.

Data collection

In the first stage, we identified and characterized the different competitive groups of hotels in the wine tourism destination of the Spanish wine region DOC Rioja (Rioja Designation of Origin). We then measured the emotions felt by tourists staying at these hotels.

Competitive groups were defined as groups of companies that are direct rivals for different target audiences (Bigné and Vila, 2001). From a demand perspective, they are the selection of providers perceived as similar by the customer.

To identify the competitive groups of hotels in the analysis, we developed a database by administering a questionnaire, via a telephone interview, to all hotel managers at establishments located at the destination. In order to obtain reliable data, all data would refer to the same ordinary 2-day weekend (i.e. with no bank holiday) of the 2011–2012 winter season and to the rate for a standard double room, including tax.

Because the formation of competitive groups in the customer’s mind is conditioned by the information the customer receives (Shapiro et al., 1997), we decided to include information easily available to customers on three different aspects, namely, the basic benefits customers seek in a hotel, in this case defined by the wine tourism services offered; the quality of the hotel’s service, using the hotel’s star rating and size as quality cues; and the price of an overnight stay at each establishment.

The decision to use a hotel’s star rating and size as proxy measures for the quality of its services was based on Zeithaml’s (1988) consideration of size as an intrinsic indicator of service quality. Likewise, Fernández Barcala et al. (2009) found that star ratings influence quality expectations and, thus, are indicators of quality. Similarly, López and Serrano (2004) showed that, while a hotel’s star rating is not an exact proxy for consumers’ expectations of it, there are nevertheless statistically significant differences in the quality offered by hotels with different numbers of stars.

Through the telephone interviews, we obtained 74 census sheets for statistical analysis. To create the competitive groups of hotels, we applied a sequential cluster analysis, followed by a discriminant analysis to classify and reassign the solution. Specifically, to classify the hotels into groups, we first applied a hierarchical cluster analysis, defining each element or object to be classified (i.e. the hotels) by means of the four aforementioned variables.

As a proximity measure, we used the squared Euclidean distance, and as a classifying algorithm, we used Ward’s method. We thus obtained a dendrogram, which allowed us to establish clusters and centroids in order to apply the K-means method. The resulting six clusters were validated using the following two methods: analysis of variance (ANOVA) and discriminant analysis. The ANOVA¹ results reflected the existence of inequality of means between the competitive groups for all included variables. The multiple discriminant analysis showed, through the test of equality of means (F), the existence of inequality of means within the competitive groups of hotels (see Table 1); we moreover observed low values on Wilks’s λ and significant χ ² values associated with Wilks’s λ, which allowed us to accept the hypothesis of differences in the ratings given to the independent variables within the established competitive group of hotels (see Table 2). Box’s M test revealed an F-statistic of 90.961, with a level of significance of 0.001, allowing us to reject the null hypothesis of a variance–covariance matrix, not presenting significant statistical difference within the competitive group of hotels. Finally, the confusion matrix showed that 98.6% of the original group of cases had been classified correctly. All of the above confirmed that the clusters obtained were distinct and properly identified.

Table 1.

Equality of means test of the groups.

Variables	Wilks’s λ	F
Wine tourism services	0.205	52.884
Stars	0.195	56.268
Size of hotel	0.286	33.920
Price	0.414	19.250

Table 2.

Wilks’s λ.

Contrast function	Wilks’s λ	Chi- squared	Degrees of freedom
1–4	0.010	312.411	20
2–4	0.065	185.349	12
3–4	0.372	67.320	6
4	0.701	24.192	2

Having confirmed the sustainability of the statistical instrument, we will now proceed to discuss the results. We assigned names to the six clusters obtained according to their characteristics:

Group 1. Prestigious wine tourism hotels: This group includes 3- and 4-star hotels in Spain, mostly located at or near wineries, with the highest nightly rate (€134.68). Their main competitive advantage is their focus on wine tourism (they offer an average of 5.3 wine tourism services of the 7 analyzed) and their status. Because they are smaller (36.5 rooms on average), they are able to offer personalized service.

Group 2. Mid-to-low-end wine tourism hotels: The hotels in this group are similar to those in the previous group, but have only 1 or 2 stars and charge an average nightly rate of €85.35). They are also located at or near wineries. Their competitive advantage lies in their wine tourism services (4.7 services on average) and smaller size (24.87 rooms), which allows them to offer a more personalized service.

Group 3. Charming, non-wine tourism hotels: This group basically includes a mix of hotels whose main competitive advantage is their charm (housed in a unique or historic building, innovative decor, own spa, etc.) rather than the offer of wine tourism services (0.33 services). They charge the second highest nightly rate (€106.66).

Group 4. 4-Star urban hotels: This group is composed of large hotels whose competitive advantages are their central location in the city and prestigious brand reputation (usually 4 stars). They may also further enhance their image by offering wine tourism services. Their size (117.35 rooms) allows them to offer reasonable rates (€86.28) in relation to their star rating.

Group 5. Midrange budget hotels: These are medium-sized, 3-star hotels charging modest nightly rates (€68.40) and offering virtually no wine tourism services (0.62 services). Their advantage is their low rate for a 3-star hotel.

Group 6. Low-end budget hotels: Small 1-star hotels charging the lowest nightly rates (€57.93). They barely offer any wine tourism services (0.42).

In the second phase, which lasted approximately 4 months, we surveyed tourists staying at six different hotels, one from each of the six competitive groups. We chose to use one hotel per group to prevent the peculiarities of any one hotel from affecting the overall results for its competitive group. The chosen hotels largely conformed to the average characteristics of their competitive group. A stratified random sampling based on the size of the hotel was applied, yielding l00 valid surveys for the smallest hotel. Tourists were surveyed near the hotel’s reception upon their arrival at the hotel.

We thus obtained 841 valid surveys of a total of 865. Due to the presence of a group of tourists on a business trip, 61.47% of the respondents were men. This fact masks a certain equality among leisure tourists, among whom the percentage of men (48%) and women (52%) is generally very similar. In terms of age, a small percentage of the respondents were under 25 (1.55%) or over 64 (6.06%), while the brunt were between the ages of 25 and 54 years (78.48%). The majority of the respondents held a college degree (54.85%) and had a household income of over €2400 a month (40.78%). This may be because people with higher incomes have more disposable income for leisure and are thus more likely to be able to afford to stay in hotels.

Results

Once we had this information, we compared the emotional dimensions the tourists felt toward the hotel they had chosen for their overnight stay. We then used the categorical approach to analyze the basic emotions evoked by these hotels.

The analysis of the emotional dimensions consisted of several stages. First, we performed an exploratory factor analysis to check for the existence of two emotional dimensions, one related to the level of pleasure and the other to the level of activation. Second, we performed a confirmatory factor analysis to examine the underlying structure and to study the reliability and validity of the scale. Third, and finally, we used structural equations to create the level-of-pleasure and level-of-activation emotional dimensions as well as a variable to integrate the two related to the degree of emotion produced by the hotel in the customer.

The results of the exploratory factor analysis demonstrated the existence of two dimensions that, together, accounted for 80.794% of the variance. The first dimension encompasses variables associated with the level of activation or excitement felt by the tourist as a result of the particular hotel, while the second dimension includes variables related to the level of pleasure evoked in the tourist by spending the night in the hotel. The loading factor for all observed variables was over 0.4. The statistical instrument was found to work correctly; that is, the determinant was very small (1.62 × 10⁻⁶), the Kaiser–Meyer–Olkin measure showed good results (0.935), and Bartlett’s test for sphericity reflected a level of significance lower than 0.001. Finally, Cronbach’s α was 0.949.

We then performed a partially amended confirmatory factor analysis, allowing us to apply the Lagrange multiplier test and the Wald statistical test, which evaluates the effect of releasing (or not) a set of parameters simultaneously. Parametric convergence of the factors was also taken into account in the re-specification of the model. In this case, it was deemed sufficient to remove the parameters with a λ < 0.6, as they contributed little to their respective factors (indifferent–surprised, dissatisfied–very pleased, and bored–entertained).

The results of the convergent validity analysis, shown in Table 3, allowed us to confirm that the indicators converge with the assigned factors, as the λ parameters were greater than 0.5 and significant. Furthermore, the average variance extracted was found to be greater than 0.5 for all factors, and the compound coefficient of reliability showed values well above 0.7 with very good results (equal to or greater than 0.8).

Table 3.

Convergent validity and reliability analysis.

	Standardized parameters >0.5 and t value >1.96	Compound reliability coefficient >0.7	AVE > 0.5
F1. Activation		0.95	0.80
Calm–enthusiastic	0.93 (35.6)
Depressed–cheerful	0.96 (37.4)
Quiet–anxious	0.86 (30.9)
Passive–active	0.89 (33.0)
Relaxed–nervous	0.83 (29.4)
F2. Pleasure		0.91	0.71
Disappointed–delighted	0.90 (32.6)
Unhappy–happy	0.82 (28.0)
Angry–content	0.81 (27.6)
Sad–joyful	0.85 (29.6)

AVE: average variance extracted.

As for the discriminant validity, Table 4 shows the differences found between the factors. Thus, we demonstrated that the confidence interval near the covariance value did not include value 1 and, therefore, there was no issue in the covariance of the factors involved and, moreover, we had complied with the discriminant validity requirements.

Table 4.

Discriminant validity analysis.

Factors involved	Covariance	Standard error	Correlation confidence interval		Value outside the interval
F1–F2	0.601	0.026	0.549	0.653	1

Tables 5 and 6 below show the results of our factor analysis of the level of emotion generated by the hotel and the goodness of fit.

Table 5.

Factor analysis of the level of emotion generated by the hotel.

	Standardized parameters	p Value
Activation => Level of emotion generated by the hotel	0.80	0.00
Pleasure => Level of emotion generated by the hotel	0.75	0.00

Table 6.

Goodness of fit indices.

Index	Considered good value	Model
BBNFI	>0.9	0.99
BBNNFI	>0.9	0.99
CFI	>0.95	0.99
Robust CFI	>0.95	0.99
GFI	>0.9	0.98
AGFI	>0.9	0.97
RMSEA	<0.08	0.05

Note: BBNFI = Bentler–Bonett normed fit index; BBNNFI = Bentler–Bonett non-normed fit index; CFI = comparative fit index; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; RMSEA = root mean square error of approximation.

The results reported in Table 7 show the differences in the emotional dimensions.

Table 7.

Differences in the emotional dimensions.

		Average factor value by hotel type
Emotional dimensions	ANOVA and Kruskal–Wallis H	Prestigious wine	Mid-to-low- end wine	Charming non-wine	4-Star urban	Midrange budget	Low-end budget
Level of pleasure	p Value <0.00 p Value <0.00	1.54	0.69	1.99	0.06	−2.08	−0.12
Level of activation	p Value <0.00 p Value <0.00	1.63	0.59	2.33	0.24	−2.40	−0.14

ANOVA: analysis of variance.

Although this information is useful for understanding the intensity of the emotions generated by the hotels, it does not tell us which emotions are responsible for that intensity. To determine that, an analysis of basic emotions must be conducted.

To this end, we next examined the existence of significant statistical differences between the basic emotions generated by the hotels. The results reported in Table 8 reveal the existence of profound differences among the customers of the different competitive groups for all the basic emotions analyzed.

Table 8.

Differences in customers’ basic emotions by competitive group of hotels.

		Average values by hotel type
Basic emotion	ANOVA and Kruskal–Wallis H	Prestigious wine	Mid-to-low- end wine	Charming non-wine	4-Star urban	Midrange budget	Low-end budget
Interest	p Value <0.00 p Value <0.00	8.03	7.21	7.45	6.15	5.88	6.47
Anguish	p Value <0.00 p Value <0.00	2.43	3.33	2.37	3.01	4.02	3.17
Excitement and impatience	p Value <0.00 p Value <0.00	7.68	6.74	7.35	5.89	5.03	5.49
Disgust	p Value <0.00 p Value <0.00	1.98	2.81	1.55	2.62	3.22	2.53
Self-confidence	p Value <0.00 p Value <0.00	6.93	6.16	7.05	6.50	5.60	6.04
Guilt	p Value <0.00 p Value <0.00	2.58	3.17	1.80	2.60	3.27	2.72
Scared	p Value <0.00 p Value <0.00	2.68	3.29	1.49	2.44	3.35	2.69
Antipathy	p Value <0.00 p Value <0.00	2.56	3.01	1.48	2.13	3.07	2.04
Enthusiasm	p Value <0.00 p Value <0.00	7.48	6.61	8.04	6.71	5.62	6.06
Pride	p Value <0.00 p Value <0.00	7.07	6.39	7.33	6.57	5.36	5.60
Irritation	p Value <0.00 p Value <0.00	3.55	3.96	2.44	3.37	4.86	3.47
Attentiveness	p Value <0.00 p Value <0.00	6.03	5.37	5.90	5.29	3.50	4.50
Shame	p Value <0.00 p Value <0.00	4.41	4.71	4.61	4.64	6.69	5.18
Creativity and inspiration	p Value <0.00 p Value <0.00	5.47	5.47	5.85	5.38	3.43	4.62
Nervousness	p Value <0.00 p Value <0.00	3.99	4.03	2.21	3.25	4.58	2.79
Decisiveness	p Value <0.00 p Value <0.00	5.95	5.98	6.30	6.04	4.51	5.46
Affection	p Value <0.00 p Value <0.00	6.48	6.50	7.75	7.34	5.94	7.34
Restlessness	p Value <0.00 p Value <0.00	3.39	3.53	1.86	3.06	4.38	3.18
Activeness and liveliness	p Value <0.00 p Value <0.00	7.05	6.49	7.73	6.86	5.70	6.42
Afraid	p Value <0.00 p Value <0.00	2.56	2.91	1.62	2.20	2.89	1.95

Note: ANOVA = analysis of variance. Scale of 0 to 10.

Conclusions

This study analyzes the emotions evoked in tourists by hotels. There are two theoretical approaches for measuring this: the categorical approach, which studies basic emotions, and the dimensional one, which studies the emotional dimensions.

We have shown that in the hotel sector, both the dimensional and categorical approach should be used, as Russell (2003) has proposed. The use of both approaches enhances the information obtained, as other researchers have described (Scherer, 2005; Wirtz and Bateson, 1999).

The emotional dimensions approach allowed us to observe the intensity of the pleasure and activation triggered by hotels. The basic emotions approach complemented this measurement and allowed us to identify which emotions were responsible for the varying degrees of the emotional dimensions. Specifically, we found that the highest degree of pleasure and emotional activation was generated in tourists by the charming, non-wine tourism hotel. We also found that the basic emotions these tourists felt most intensely were excitement, impatience, enthusiasm, pride, attentiveness, creativity, inspiration, decisiveness, affection, and activeness. This finding is in keeping with Wirtz and Bateson’s (1999) observation that knowing the type of emotion makes it possible to understand the emotional experience much more thoroughly than knowing only the emotional dimensions’ levels of activation and pleasure.

In keeping with the findings of Russell and Barrett (1999) and Scherer (2005), the use of both approaches enabled us to determine whether tourists feeling a similar degree of pleasure or activation were also feeling the same basic emotions (categories of emotions). Our research showed that tourists staying at both 4-star urban and medium-to-low-end wine tourism hotels felt similar levels of arousal. However, it also showed, with regard to basic emotions, that, tourists at medium-to-low-end wine tourism hotels felt more interested, excited, impatient, and nervous than tourists staying at 4-star urban hotels. Despite these difference, tourists at both types of hotels felt similar levels of enthusiasm. Thus, although they experienced similar levels of arousal, some of the basic emotions they felt were different.

Likewise, we observed that tourists who feel similar basic emotions, for example tourists at medium-to-low-end wine tourism hotels and midrange budget hotels who feel scared or afraid, feel different levels of pleasure and activation, in keeping with the findings of Russell (1980), Russell and Barrett (1999), and Wirtz and Bateson (1999). This finding shows that these same feelings of being scared or afraid can generate different levels of pleasure and arousal.

Considerable differences were found among tourists with regard to both emotional dimensions and basic emotions. This conclusion testifies to the power of these affective variables in tourism market segmentation.

Emotional dimensions: The tourists whose hotels evoked the highest levels of emotion with regard to both the pleasure and activation dimensions were those staying at charming non-wine tourism hotels and prestigious wine tourism hotels. Tourists staying at midrange budget hotels and low-end budget hotels showed the lowest levels of intensity with regard to these emotions.

Basic emotions: Certain emotions occur with greater intensity at certain types of establishments. In general, customers at more prestigious establishments (prestigious wine tourism hotels and charming non-wine hotels) feel positive emotions more intensely, while customers at lower end establishments (midrange budget hotels and low-end budget hotels) feel negative emotions more intensely. However, some basic emotions are subject to specific considerations, which we discuss below.

Customers at prestigious wine tourism hotels and charming non-wine hotels are the most impatient and eager to enjoy the hotel; in addition, these customers are usually more attentive, take greater emotional pride, and have higher self-esteem. Conversely, customers at budget hotels feel these emotions less intensely.

With regard to guilt, antipathy, and afraid, our results show that customers at midrange hotels (medium-to-low-end wine tourism hotels and midrange budget hotels) feel these emotions most intensely. This may be because customers at these intermediate-category hotels are unsure of their choice. It is worth noting that customers at charming non-wine tourism hotels, the most expensive ones, feel these emotions least intensely of all, indicating that paying more is not associated with feelings of guilt or afraid of the selected hotel.

The most inspired, determined, active, and affectionate customers were those at charming, non-wine tourism hotels, while the customers who felt these emotions least intensely were usually those staying at mid-to-low-range budget hotels.

In contrast, customers at midrange budget hotels felt anguish, disgust, and irritation most intensely, while customers at charming, non-wine tourism hotels felt these emotions least intensely.

Finally, customers at prestigious wine tourism hotels showed greater interest in the hotel itself than those at midrange budget hotels, whereas customers at midrange budget hotels felt shame more intensely than those at prestigious wine tourism hotels.

In short, compared to customers at charming, non-wine tourism hotels, and prestigious wine tourism hotels, the emotions of customers at midrange budget hotels showed that, although they had chosen the hotel they were staying at, they were not happy with their choice and would have preferred to be staying elsewhere. Their ability to do so, that is, to stay at a more prestigious hotel, may have been limited by financial constraints.

As a future line of investigation, the applicability of these conclusions to different markets and tourism products should be considered in order to determine the generalizability of our conclusions.

Business involvement

The conclusions drawn from this study are particularly relevant for managers in the hospitality industry. They show that higher priced, more prestigious establishments with distinguishing features (wine tourism services or charming hotels) produce both more intense emotions in terms of their level of pleasure and activation and more positive basic emotions. In contrast, lower end hotels produce the most negative emotions. Also certain basic emotions occur with greater intensity at certain types of hotels. For instance, feelings of guilt, afraid, or distaste occur more frequently in customers at midrange hotels.

In keeping with these findings, hotels can generate more positive emotions by offering distinguishing features. Managers should thus design their offers to highlight these notable features. Managers at lower end hotels should take special care with regard to the negative emotions their hotel can elicit in their customers, while managers at midrange hotels should try to generate confidence in their customers with regard to the adequacy of their decision. To this end, they could design advertising or loyalty campaigns, among other commercial activities. Managers seeking to use the influence of emotions to draw potential tourists to their hotel must analyze the level-of-pleasure and level-of-activation dimensions as well as the basic emotions the establishment evokes. Analyses using just one approach could lead to a myopic view of the reality of what customers feel and, thus, to policies that could result in poor communication and product design or misleading offers.

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Note

References

Aaker

Williams

(1998) Empathy versus pride: the influence of emotional appeals across cultures. Journal of Consumer Research 25(3): 241–261.

Albers-Miller

Stafford

(1999) An international analysis of emotional and rational appeals in service vs goods advertising. Journal of Consumer Marketing 16(1): 42–57.

Bagozzi

(1982) A field investigation of causal relations among cognitions, affect, intentions, and behaviour. Journal of Marketing Research 19(4): 562–584.

Bagozzi

(1997) Goal-directed behaviors in marketing: the role of emotion, volition and motivation. Psychology and Marketing 14(3): 309–313.

Baker

Meyer

(2011) White response to potentially discriminatory actions in a services setting. Psychology & Marketing 28(2): 188–204.

Baloglu

McCleary

(1999) A model of destination image formation. Annals of Tourism Research 26(4): 868–897.

Barsky

Nash

(2002) Evoking emotion. Affective keys to hotel loyalty. Cornell Hotel and Restaurant Administration Quarterly 43(1): 39–46.

Bigné

Andreu

(2004) Emotions in segmentation. An empirical study. Annals of Tourism Research 31(3): 682–696.

Bigné

Andreu

(2005) Emociones del consumidor. Aplicación de la escala agrado-activación en la segmentación de visitantes de servicios de ocio y turismo. Revista Española de Investigación de Marketing ESIC 9(1): 11–36.

10.

Bigné

Andreu

Gnoth

(2005) The theme park experience: an analysis of pleasure, arousal and satisfaction. Tourism Management 26(6): 833–844.

11.

Bigné

Mattila

Andreu

(2008) The impact of experiential consumption cognition and emotion on behavioural intentions. Journal of Service Marketing 22(4): 303–315.

12.

Bigné

Vila

(2001) Alternative ways in competitive groups definition: a managers approach. Journal of Marketing Management 17(7-8): 671–693.

13.

Bigné

Sánchez

MI,

Sánchez

(2001) Tourism image, evaluation variables and after purchase behaviour: inter-relationship. Tourism Management 22(6): 607–616.

14.

Brunner-Sperdin

Peters

(2009) What influence guests’ emotions? The case of high-quality hotels. International Journal of Tourism Research 11(2): 171–183.

15.

Campbell

(2007) Says who? How the source of price information and affect influence perceived price (un)fairness? Journal of Marketing Research 44(2): 261–271.

16.

Charters

Fountain

Fish

(2009) You felt like lingering.… Journal of Travel Research 48(1): 122–134.

17.

Chen

Uysal

(2002) Market positioning analysis. A hybrid approach. Annals of Tourism Research 29(4): 987–1003.

18.

Chhetri

Arrowsmith

Jackson

(2004) Determining hiking experiences in nature-based tourist destinations. Tourism Management 25(1): 31–43.

19.

Chitturi

Raghunathan

Mahajan

(2007) Form versus function: How the intensities of specific emotions evoked in functional versus hedonic trade-offs mediate product preferences. Journal of Marketing Research 44(4): 702–714.

20.

Cohen

Pham

MT,

Andrade

(2006) The nature and role of affect in consumer behavior. In: Haugtvedt

Herr

Kardes

(eds) Handbook of Consumer Psychology. Mahwah: Lawrence Erlbaum, pp. 297–348.

21.

De Rojas

Camarero

(2008) Visitors’ experience, mood and satisfaction in a heritage context: evidence from an interpretation center. Tourism Management 29(3): 252–537.

22.

Dean

Raats

Shepherd

(2008) Moral concerns and consumer choice of fresh and processed organic foods. Journal of Applied Social Psychology 38(8): 2088–2107.

23.

Decrop

Snelders

(2004) Planning the summer vacation. An adaptable process. Annals of Tourism Research 31(4): 1008–1030.

24.

Drolet

Luce

(2004) The rationalizing effects of cognitive load on emotion-based trade-off avoidance. Journal of Consumer Research 31(1): 63–77.

25.

Elliott

(1998) A model of emotion-driven choice. Journal of Marketing Management 14(1-3): 95–108.

26.

Esses

Maio

(2002) Expanding the assessment of attitude components and structure: the benefits of open-ended measures. European Review of Social Psychology 12: 71–701.

27.

Faullant

Matzler

Mooradian

(2011) Personality, basic emotions, and satisfaction: primary emotions in the mountaineering experience. Tourism Management 32(6): 1423–1430.

28.

Fernández Barcala

González Díaz

Prieto Rodríguez

(2009) Factors influencing guests hotel quality appraisals. European Journal of Tourism Research 2(1): 25–40.

29.

Fontaine

Scherer

Roesch

. (2007) The world of emotions is not two-dimensional. Psychological Science 18(12): 1050–1057.

30.

Galloway

Mitchell

Getz

. (2008) Sensation seeking and the prediction of attitudes and behaviours of wine tourists. Tourism Management 29(5): 950–966.

31.

Garbarino

Edell

(1997) Cognitive effort, affect, and choice. Journal of Consumer Research 24(2): 147–158.

32.

Garg

Inman

Mittal

(2005) Incidental and task-related affect: a re-inquiry and extension of influence of affect on choice. Journal of Consumer Research 32(1): 154–159.

33.

Gelbrich

(2011) I have paid less than you! The emotional and behavioural consequences of advantaged price inequality. Journal of Retailing 87(2): 207–224.

34.

Gnoth

(1997) Tourism motivation and expectation formation. Annals of Tourism Research 24(2): 283–304.

35.

Gnoth

Zins

Lengmueller

Boshoff

(2000) Emotions, mood, flow and motivation to travel. Journal of Travel and Tourism Marketing 9(3): 23–34.

36.

Goossens

(2000) Tourism information and pleasure motivation. Annals of Tourism Research 27(2): 301–321.

37.

Gountas

(2007) Personality orientations, emotional states, customer satisfaction, and intention to repurchase. Journal of Business Research 60(1): 72–75.

38.

Griskevicius

Shiota

Nowlis

(2010) The many shades of rose-colored glasses: an evolutionary approach to the influence of different positive emotions. Journal of Consumer Research 37(2): 238–250.

39.

Gupta

Kim

(2010) Value-driven internet shopping: the mental accounting theory perspective. Psychology & Marketing 27(1): 13–35.

40.

Han

Lerner

Keltner

(2007) Feeling and consumer decision making: the appraisal–tendency framework. Journal of Consumer Psychology 17(3): 158–168.

41.

Han

Back

(2006) Investigating the effects of consumption emotions on customer satisfaction and repeat visit intentions in the lodging industry. Journal of Hospitality and Leisure Marketing 15(3): 5–30.

42.

Han

Back

(2008) Relationships among image congruence, consumption emotions, and customer loyalty in the lodging industry. Journal of Hospitality and Tourism Research 32(4): 467–490.

43.

Han

Kim

(2011) Cognitive, affective, conative y action loyalty: Testing the impact of inertia. International Journal of Hospitality Management 30(4): 1008–1019.

44.

Havlena

Holbrook

(1986) The varieties of consumption experience: comparing two typologies of emotion in consumer behavior. Journal of Consumer Research 13(3): 394–404.

45.

Hirschman

Holbrook

(1982) Hedonic consumption: emerging concepts, methods and propositions. Journal of Marketing 43(3): 92–101.

46.

Hirschman

Stern

(1999) The roles of emotion in consumer research. Advances in Consumer Research 26: 4–11.

47.

Izard

(1977) Human Emotions. New York: Plenum Press.

48.

Jang

SCS

Bai

. (2009) Affect, travel motivation, and travel intention: a senior market. Journal of Hospitality and Tourism Research 33(1): 51–73.

49.

Kahn

Isen

(1993) The influence of positive affect on variety seeking among safe, enjoyable products. Journal of Consumer Research 20(2): 257–270.

50.

Kim

Lennon

(2011) Consumer response to online apparel stockouts. Psychology & Marketing 28(2): 115–144.

51.

Kim

Goh

(2011) An examination of food tourist’s behavior: using the modified theory of reasoned action. Tourism Management 32(5): 1159–1165.

52.

Kleinginna

(1981) A categorized list of emotion definitions, with suggestions for a consensual definition. Motivation and Emotion 5(4): 345–379.

53.

Labroo

Rucker

(2010) The orientation-matching hypothesis: an emotion-specificity approach to affect regulation. Journal of Marketing Research 47(5): 955–966.

54.

Ladhari

(2009) Service quality, emotional satisfaction, and behavioural intentions. A study in the industry. Managing Service Quality 19(3): 308–331.

55.

Laverie

Kleine

(2002) Reexamination and extension of Kleine, Kleine and Kerman’s social identity model of mundane consumption: the mediating role of appraisal process. Journal of Consumer Research 28(4): 659–669.

56.

López Fernández

Serrano Bedia

(2004) Is the hotel classification system a good indicator of hotel quality? An application in Spain. Tourism Management 25(6): 771–775.

57.

Luce

Payne

Bettman

(1999) Emotional trade-off difficulty and choice. Journal of Marketing Research 36(2): 143–159.

58.

Mano

(1991) The structure and intensity of emotional experiences: method and context convergence. Multivariate Behavioral Research 26(3): 389–411.

59.

Mano

(1999) The influence of pre-existing negative affect on store purchase intentions. Journal of Retailing 75(2): 149–172.

60.

Mattila

(1999) Do emotional appeals work for services? International Journal of Services Industry Management 10(3): 292–306.

61.

Mattila

(2006) The impact of affective commitment and hotel type in influencing guests’ share of wallet. Journal of Hospitality and Leisure Marketing 15(4): 55–68.

62.

Mattila

Wirtz

(2000) The role of preconsumption affect in postpurchase evaluation and behavior. Psychology and Marketing 17(7): 587–605.

63.

Miao

Mattila

Mount

(2011) Other consumers in service encounters: a script theoretical perspective. International Journal of Hospitality Management 30(4): 933–941.

64.

Mittal

(1994) A study of the concept of affective choice mode for consumer decisions. Advances in Consumer Research 21(1): 256–263.

65.

Moe

Fader

(2001) Modeling hedonic portfolio products: a joint segmentation analysis of music compact disc sales. Journal of Marketing Research 38(3): 376–385.

66.

Moutinho

(1987) Consumer behaviour in tourism. European Journal of Marketing 21(10): 5–44.

67.

Nicolao

Irwin

Goodman

(2009) Happiness for sale: do experiential purchases make consumer happier than material purchase? Journal of Consumer Research 36(2): 188–198.

68.

Noble

Walker

(1997) Exploring the relationships among liminal transitions, symbolic consumption, and extended self. Psychology and Marketing 14(1): 29–47.

69.

Novemsky

Dhar

Schwarz

. (2007) Preference fluency in choice. Journal of Marketing Research 44(3): 347–356.

70.

Oliver

Rust

RT,

Varki

(1997) Customer delight: foundations, findings, and managerial insight. Journal of Retailing 73(3): 311–336.

71.

Ortony

Turner

(1990) What’s basic about basic emotions? Psychological Review 97(3): 315–331.

72.

Penz

Hogg

(2011) The role of mixed emotions in consumer behavior. European Journal of Marketing 45(1/2): 104–132.

73.

Pike

Ryan

(2004) Destination positioning analysis through a comparison of cognitive, affective and conative perceptions. Journal of Travel Research 42(4): 333–342.

74.

Pomfret

(2006) Mountaineering adventure tourists: a conceptual framework for research. Tourism Management 27(1): 113–123.

75.

Ramanathan

Williams

(2007) Immediate and delayed emotional consequences of indulgence: the moderating influence of personality type on mixed emotions. Journal of Consumer Research 34(2): 212–223.

76.

Richins

(1997) Measuring emotions in the consumption experience. Journal of Consumer Research 24(2): 127–146.

77.

Russell

(1980) A circumplex model of affect. Journal of Personality and Social Psychology 39: 1161–1178.

78.

Russell

(2003) Core affect and the psychological construction of emotion. Psychological Review 110(1): 145–172.

79.

Russell

(2005) Emotion in human consciousness is built on core affect. Journal of Consciousness Studies 12(8/10): 26–42.

80.

Russell

Barrett

(1999) Core affect, prototypical emotional episodes, and other things called emotion: dissecting the elephant. Journal of Personality and Social Psychology 76(5): 805–819.

81.

San Martín

Rodríguez

(2008) Exploring the cognitive-affective nature of destination image and the role of psychological factors in its formation. Tourism Management 29(2): 263–277.

82.

Scherer

(2001) Emotions, psychological structure of. In: Smelser

Baltes

(eds) International Encyclopedia of the Social and Behavioral Sciences. Oxford: Pergamon, pp. 4472–477.

83.

Scherer

(2005) What are emotions? And how can they be measured? Social Science Information 44(4): 695–729.

84.

Shapiro

MacInnis

DJ,

Heckler

(1997) The effects of incidental ad exposure on formation of consideration sets. Journal of Consumer Research 24(1): 94–104.

85.

Shiv

Fedorikhin

(1999) Heart and mind in conflict: the interplay of affect and cognition in consumer decision making. Journal of Consumer Research 26(3): 278–292.

86.

Valenzuela

Mellers

Strebel

(2010) Pleasurable surprises: a cross-cultural study of consumer responses to unexpected incentives. Journal of Consumer Research 36(5): 792–805.

87.

Wang

Minor

Wei

(2011) Aesthetics and the online shopping environment: understanding consumer responses. Journal of Retailing 87(1): 46–58.

88.

Watson

Clark

LA,

Tellegen

(1988) Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology 54(6): 1063–1070.

89.

White

(2005) Satisfaction emotions and consumer behavioral intentions. Journal of Services Marketing 19(6): 411–420.

90.

Wirtz

Bateson

(1999) Consumer satisfaction with services: integrating the environment perspective in services marketing into the traditional disconfirmation paradigm. Journal of Business Research 44(1): 55–66.

91.

Woodside

Lysonski

(1989) A general model of travel destination choice. Journal of Travel Research 27(4): 8–14

92.

Schwarz

(2009) Do we really need a reason to indulge? Journal of Marketing Research 46(1): 25–36.

93.

Yuan

Morrison

Cai

Linton

(2008) A model of wine tourist behaviour: A festival approach. International Journal of Tourism Research 10(3): 207–219.

94.

Yeung

Wyer

(2004) Affect, appraisal, and consumer judgment. Journal of Consumer Research 31(2): 412–424.

95.

Yüksel

(2007) Shopping risk perceptions: Effects on tourists’ emotions, satisfaction and expressed loyalty intentions. Tourism Management 28(3): 703–713.

96.

Zeithaml

(1988) Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing 52(3): 2–22.

97.

Zielke

(2011) Integrating emotions in the analysis of retail price images. Psychology & Marketing 28(4): 330–359.