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Virtual Atmosphere: The Effect ofPleasure, Arousal, and Delight on Word-of-MouthSandra Maria Correia Loureiroa & Lara Ribeirob

a Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugalb University of Aveiro, Aveiro, PortugalPublished online: 08 Aug 2014.

To cite this article: Sandra Maria Correia Loureiro & Lara Ribeiro (2014) Virtual Atmosphere: TheEffect of Pleasure, Arousal, and Delight on Word-of-Mouth, Journal of Promotion Management, 20:4,452-469, DOI: 10.1080/10496491.2014.930283

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Journal of Promotion Management, 20:452–469, 2014Copyright © Taylor & Francis Group, LLCISSN: 1049-6491 print / 1540-7594 onlineDOI: 10.1080/10496491.2014.930283

Virtual Atmosphere: The Effect of Pleasure,Arousal, and Delight on Word-of-Mouth

SANDRA MARIA CORREIA LOUREIROInstituto Universitario de Lisboa (ISCTE-IUL), Lisbon, Portugal

LARA RIBEIROUniversity of Aveiro, Aveiro, Portugal

This study investigates the effect of virtual atmospheric cues onemotions and word-of-mouth and also analyzes the differencesbetween the perceptions of male and female participants relative tothe online environment. Questionnaires were given to students inhigher education and senior university students. The main findingssuggest that pleasure is the most effective emotion to lead to a positiveword-of-mouth for both genders. Women are more willing to saypositive words to others than men. Women are also more influencedby the delight and pleasure, whereas men are influenced only bypleasure.

KEYWORDS online purchase, pleasure, arousal, delight, gender,word-of-mouth

INTRODUCTION

Nowadays, room design and layout (atmosphere) has been a major concernwith the attractiveness of environments, in workplaces and in commercialspaces. According to Kotler (1973–1974, p. 50), the atmosphere is the “silentlanguage” in communication and results of “the conscious designing ofspace to create certain effects in buyers.” The statement reflects the effortof creating commercial environments that are intended to produce certainemotional effects on the buyer and increase the likelihood of purchase.The mentioned effort can be defined as the collection of atmosphericcues, meaning any component in a commercial environment, designed

Address correspondence to Sandra Maria Correia Loureiro, Instituto Universitario deLisboa (ISCTE-IUL), Av. Forcas Armadas, 1649–026 Lisbon, Portugal. E-mail: sandramloureiro@netcabo.pt

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Virtual Atmosphere and Word of Mouth 453

consciously, and external to the individuals, that falls within their field ofperception and stimulates their senses, and affects the entire customer expe-rience of being in a particular space and in a particular time (e.g., Koo & Ju,2010).

In this study we explore the virtual environment or web atmospherics.According to Dailey (2004, p. 796) web atmospherics is “the conscious de-signing of web environments to create positive effects (e.g., positive affect,positive cognition, etc.) in users in order to increase favorable consumerresponses (e.g., site revisiting, browsing, etc.).” The atmospheric variables inthe virtual environment can be defined “as the sum total of all the cues thatare visible and audible to the online shopper” (Eroglu, Machleit, & Davis,2001, p. 179).

Despite numerous studies on the influence of the virtual environmenton consumer behavior intentions, these investigations have not analyzed thedifferences between the perceptions of female and male participants (e.g.,Menon & Kahn, 2002; Novak, Hoffman, & Yung, 2000; Eroglu, Machleit, &Davis, 2003; Koo & Ju, 2010). Moreover, these studies usually consider sam-ples of students and/or young participants, and they do not tend to analyzeconsumers above 50 years old. In what concerns emotions, as mediators inS-O-R model, previous studies usually consider arousal and pleasure. There-fore, the main objective is to analyze the effect of atmospheric cues on threeemotions (arousal, pleasure, and delight), how these three emotions con-tribute to a positive word-of-mouth, and compare the perceptions of maleand female participants in virtual environment.

The next section provides a theoretical foundation of the S-O-R modeland a review of previous research on atmospherics, customer emotionalresponses, and intentions. A research model is then presented as well as aset of hypotheses to be tested. Furthermore, the research methodology usedfor this study is described and the final part of this article presents the resultsof the study as well as the relative implications, limitations, and suggestionsfor future research.

LITERATURE REVIEW

Stimuli–Organism–Response (S-O-R) Framework

The current study is based on the model proposed by Mehrabian and Rus-sel, S-O-R (stimuli, organism, response), which was applied for the firsttime in a commercial context by Donovan and Rossiter (1982). This modelsuggests that the stimuli (such atmospheric cues) as online precede and af-fect the consumers’ emotional states, which influence their retail behaviorssuch as re-patronage, store search, and in-store behavior (Thang & Tan,2003).

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454 S. M. C. Loureiro and L. Ribeiro

Online Atmospheric Cues

In the current study the virtual atmospheric cues are grouped into threecategories: design factors, layout, and information. These three groups re-sult from the literature review, which analyzed several online and offlineatmospheric cues categories (e.g., Eroglu et al., 2001; Manganari, Siomkos,& Vrechopoulos, 2009; Turley and Milliman, 2000; Wakefield and Baker,1998).

The design factors are comprised of elements such as architecture, dec-oration, colors scheme and the overall design (Wakefield and Baker, 1998).The layout is the site configuration that can be analyzed through the easinessof finding products and services and its variety, through graphics and imagesand facility of navigation. This variable has a great importance in the virtualatmosphere as it defines the route of the consumer within the site (Manga-nari et al., 2009); therefore, the layout should not be too simple but clear,to have the chance of unpredictability and surprise (Spies, Hesse, & Loesch,1997). The presence of information on sites is reflected by the amount, im-portance, and availability of information about products and services andon the presence of information about the forms of payment. A website thatoffers full information has an important role in the decision-making processfor consumers (Novak et al., 2000).

Emotional Responses

In most retailing studies, the emotional states analyzed are pleasure, arousal,and dominance. However, Eroglu et al. (2001) suggest that arousal andpleasure adequately capture the range of appropriate emotional responses;therefore, the present study captures the emotional responses with pleasureand arousal.

Pleasure is defined as “the degree to which a person feels good, joyful,happy, or satisfied in a situation” (Menon & Kahn, 2002, p. 32). The arousalis defined as “the extent to which an individual who engages in an onlineshopping feels stimulated, active, or excited when he navigates web pagesof the online store” (Koo & Ju, 2010, p. 380). As a result, arousal reflects theaffective dimension that ranges from sleep to frantic excitement (Kaltcheva &Weitz, 2006). In this investigation, pleasure is the degree to which a personfeels happy and pleased to be in a specific website, and the arousal is thedegree to which an individual who visits a website feels stimulated andawake.

We also introduce delight as an emotion arising from pleasure andarousal. Indeed, the emotions theories in the social psychology field de-scribe delight as a second order emotion, characterized by a combinationof a number of first order emotions. According to Plutchik (1980), there

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Virtual Atmosphere and Word of Mouth 455

are eight basic emotions that may be collapsed into four dimensions withopposite poles (sadness – happiness; surprise – anticipation; acceptance– rejection; and anger – fear). By combining these basic emotions, morecomplex emotions would arise. According to this theory, a secondary dyadis defined as a combination of two basic emotions that generate a morecomplex emotion. Thereby, delight would be defined as a secondary dyadcomprised of joy and surprise.

Other emotion-based theories define delight as a combination of arousaland pleasure (Russell, 1980), or as a positive affect implying a high level ofactivation (Watson & Tellegen, 1985). Furthermore, Richins (1997) identifiedthe most outstanding emotions in marketing studies on consumption, andincluded delight in the category of “joy.” Oliver, Rust, and Varki (1997)highlight arousal and the positive affect (pleasure) as antecedents of delight.They also hypothesize that delight creates a desire for further pleasurableservice in future intentions.

Word-of-Mouth as Intention

Intention refers to an online consumer’s predisposition toward using a web-site store in the future (e.g., Zeithaml, Berry, & Parasuraman, 1996), measuredby the word-of-mouth (WOM). WOM happens after the purchase experi-ence, when the customers share with others their experience; it’s exchangedthrough oral communication in real time and in a limited geographical space(Amblee & Bui, 2007). According to several studies (e.g., Danaher & Rust,1996), customer interactions through word-of-mouth can have a major im-pact on the consumer’s response to a product. Rogers (1995) and Murray(1991) concluded that WOM is especially effective in disseminating newproducts, more risky or uncertain products and in decision making regardingservices.

Moderator

The current study introduces gender as a potential moderator. Gender hasbeen used in marketing as a segmentation variable because it is easily iden-tifiable, its information is accessible, and its segments are large enough(Meyers-Levy & Sternthal, 1991; Palanisamy, 2005). Traditionally, researchon retail shopping has indicated strong differences in shopping behaviorbased on gender (Grewal, Baker, Levy, & Voss, 2003).

Furthermore, recent studies, mostly in the North-American context, haverevealed evidence suggesting an increase in male participation in shopping-related activities. This is a reflection of the trend whereby men are increas-ingly sharing shopping duties (e.g., Dholakia, Pedersen, & Hikmet, 1995;

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456 S. M. C. Loureiro and L. Ribeiro

Lee, Ibrahim, & Hsueh-Shan, 2005). Researchers have explained importantdifferences in cognitive processes and behavior between male and femaleconsumers (e.g., Meyers-Levy & Sternthal, 1991; Park & Berger, 2010). Thereare studies showing that women are more loyal customers than men (e.g.,Blumstein & Schwartz, 1983; Hansen, 1987).

There are several theories that contributed to explain different percep-tions and behaviors between men and women. Cross and Madson (1997)suggest that women are more interdependent whereas men are more in-dependent. However, the theory of self-construal (Baumeister & Sommer,1997) states that a fundamental difference between men and women liesin the duality “relational vs. collective” interdependence. Thus, women aremore likely to establish and maintain relationship with friends, family, andsocial contexts and tend to focus more on bonds than men (Markovits,Benenson, & White, 2006). One the other hand, men tend to focus moreon a group, for example, to identify themselves with a social categorysuch as college student (Sedikides & Brewer, 2001). In this context, fe-male customers would be more emotional and loyal to individuals, whereasmale customers would be relatively more loyal to groups and group likeentities.

Eagly (1987) and Eagly and Wood (1991) view the differences betweenmen and women as a result of social roles and stereotyping. Brody (1999)highlights that gender differences exist in the experience and expressionof emotion due to stereotypes, the sense of emotional intensity, and self-concept. Thus, women are viewed as being more emotional than men (Cross& Madson, 1997). Women express emotions more extremely than men (e.g.,Hess, Blairy, & Kleck, 1997; Plant, Hyde, Keltner, & Devine, 2000), are moreaffectionate (Briton & Hall, 1995), and experience more intense joy andsadness (Fujita, Diener, & Sandvik, 1991). As an exception of this generalrule, men tend to experience and express anger and pride more frequentlyand with greater intensity (Plant et al.) than women.

RESEARCH MODEL

The model based on S–O–R from environmental psychology perspective ispresented in Figure 1. In this research, the stimuli are operationalized asatmospheric cues (design, layout, and information) present in the websites,the organism are the emotions that consumers feel, and the responses areoperationalized as the positive word-of-mouth to others. Delight is viewedas a function of arousal and pleasure based on emotion theory of Russell(1980) and on model proposed by Oliver et al. (1997).

Atmospheric cues has been seen as influencing positively on emotions,such as arousal and pleasure (e.g., Davis, Wang, & Lindridge, 2008; Koo &Ju, 2010). Therefore, we hypothesized:

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Virtual Atmosphere and Word of Mouth 457

Pleasure

Arousal

Delight W-o-m

H1

H2

H3

H4a

H4b

H5a

H5c

Online Atmospheric cues

H5b

FIGURE 1 Proposed model.

H1: Atmospheric cues have a positive effect on arousal.

H2: Atmospheric cues have a positive effect on pleasure.

Several studies have found a direct and positive effect between arousaland pleasure, especially when regarding a high arousal which operates as amechanism of activation (e.g., Mano & Oliver, 1993; Oliver et al., 1997).

H3: Arousal has a positive impact on pleasure.

Delight is viewed as one of the second level emotions, characterized bya combination of high pleasure and high activation (arousal) (Russell, 1980;Watson & Tellegen, 1985). In the studies of Mano and Oliver (1993) andOliver et al. (1997), delight appears as resulting from pleasure (or positiveaffect) and arousal. Thus, the following hypothesis is proposed:

H4: Delight is positively affected by (a function of) arousal (H4a) andpleasure (H4b).

In the S-O-R model, responses are the result of emotions, and empiricalstudies have shown such relationships (e.g., Eroglu et al., 2003, Koo & Ju,2010). Delight is also viewed as an emotion that impacts positively on futureintentions (Oliver et al., 1997; Loureiro & Kastenholz, 2011).

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458 S. M. C. Loureiro and L. Ribeiro

H5: WOM is a function of arousal (H5a), delight (H5b), and pleasure(H5c).

Finally, based on the last section of literature review we expectedwomen to be more inclined to use positive words to others when atmo-spheric cues of websites positively influence emotions. Therefore the fol-lowing hypothesis is formulated:

H6 : The effect of shopping-related emotions on WOM is higher forwomen than for men.

METHODOLOGY

The survey was carried out in two months (May and July, 2010), in majorregions located in the North and Centre regions of Portugal. The samplewas comprised of students of higher education schools and senior universitystudents that never used the website analyzed under study before. To avoiderrors in completion, given the specificity of the selected sample and thetype of questions, it was decided to apply the questionnaire individuallywith the aid of a laptop, for the respondents to have access to the website.More than four hundred (412) questionnaires were distributed, but only 365were considered valid. The sample is characterized especially by femaleparticipants with 61.2% and the remaining 38.8% per male participants. Mostof the sample consists of people between 20 and 30 years with 41.5%,followed by participants with over 60 years (20.2%).

The brands chosen for analysis have a high profile in Portugal, two arenational, Agencia Abreu and Pingo Doce and two are international, Zara andRenault. The choice of these brands takes into account the binomial utili-tarianism/hedonism to reach a balance. Regarding hedonic characteristics,the choice fell on clothing and travel (Zara and Agencia Abreu), with moreutilitarian features, and cars and groceries (Renault and Pingo Doce).

The questionnaire contains a section with the socio-demographic vari-ables and the items of the latent variables: three atmospheric factors (design,layout, and information), three emotional variables (arousal, pleasure, anddelight), and online intentions. The items used were formulated and adaptedfrom Koo and Ju (2010); Turley and Milliman (2000); and Wakefield andBaker (1998). Respondents rated all measures on a 5-point Likert-type scaleranging from 1 (completely disagree) to 5 (completely agree). A pilot test withten consumers personally interviewed (five under 30 and five over 50 yearsolder) was carried out to ensure that the wording of the questionnaire wasclear.

A structural equation model approach using PLS was employed to testthe hypotheses of this study. PLS is based on an iterative combination of

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Virtual Atmosphere and Word of Mouth 459

principal component analysis and regression; it aims to explain the varianceof the constructs in the model (Chin, 1998). In terms of analysis advantages,PLS simultaneously estimates path coefficients and individual item loadingsin the context of a specified model. As a result, it enables researchers toavoid biased and inconsistent parameter estimates. PLS has been found tobe an effective analytical tool to test interactions by reducing Type II errors.By creating a latent construct that represents an interaction term, a PLS ap-proach significantly reduces this problem by accounting for error related tothe measures (Echambadi, Campbell, & Agarwal, 2006). Tenenhaus, Vinzi,Chatelin, & Lauro (2005) propose the geometric mean of the average com-munality (outer mode) and the average R2 (inner model) as overall goodnessof fit (GoF) measures for the PLS (Cross validated PLS GoF), which rangefrom 0 to 1.

The model proposed in the current study has formative constructs andmoderating effects. Thus, in order to test the model we used the repeatedindicators method (Chin, Marcolin, & Newsted, 2003), and we choose thePLS approach because it avoids two problems: inadmissible solutions andfactor indeterminacy (Fornell & Bookstein, 1982).

RESULTS

The PLS model is analyzed and interpreted in two stages. First, suitability ofthe measurements is assessed by evaluating the reliability of the individualmeasures and the discriminant validity of the constructs (Hulland, 1999).Then, the structural model is appraised.

Item reliability is assessed by examining the loading of the measures ontheir corresponding construct. Items with loadings of 0.707 or more shouldbe accepted, which indicates that more than 50% of the variance in theobserved variable is explained by the construct (Carmines & Zeller, 1979). Inthis study, all the items (see Table 1) have item loading equal and over than0.712 and, therefore, they were not eliminated from the structural analysis.Composite reliability was used to analyze the reliability of the constructs asit has been considered a more accurate measurement than Cronbach’s alpha(Fornell & Larcker, 1981). Table 2 indicates that all constructs are reliable, asthe composite reliability values are over 0.7 (Nunnally, 1978).

The measures demonstrated that convergent validity as the average vari-ance of manifest variables extracted by constructs (AVE) was at least 0.5, in-dicating that more variance was explained than unexplained in the variablesassociated with a given construct. The criterion used to assess discriminantvalidity was proposed by Fornell and Larcker (1981), and suggests that thesquare root of AVE should be higher than the correlation between the twoconstructs in the model. Table 2 also shows that all latent variables havediscriminant validity.

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TABLE 1 Item Loading and Cross-Loading Full Sample

Items Design Layout Information Pleasure Arousal Delight WOM

1D: The website’sarchitecture givesit an attractivecharacter.

0.839 0.505 0.369 0.239 0.198 0.197 0.443

2D: The website isdecorated in anattractive fashion.

0.879 0.530 0.342 0.233 0.200 0.216 0.435

3D: The websitecolor schemes areattractive.

0.840 0.533 0.370 0.211 0.162 0.181 0.430

5D: The overalldesign of thewebsite isinteresting.

0.823 0.645 0.491 0.261 0.228 0.231 0.521

1L: The websitelayout makes iteasy to get to thegood/service Iwant.

0.440 0.788 0.644 0.297 0.217 0.231 0.587

2L: The website hasan excellent rangeof goods/services.

0.435 0.804 0.643 0.298 0.208 0.240 0.575

3L: The websitelooks goodbecause ofgraphics/images.

0.615 0.810 0.559 0.268 0.187 0.263 0.511

4L: The websitegraphics/imagesare visuallyattractive.

0.643 0.783 0.520 0.288 0.197 0.231 0.485

5L: The websiteallows us to easilynavigate.

0.417 0.712 0.530 0.236 0.204 0.156 0.475

1Inf: The websiteinformation aboutgoods/services issufficient.

0.311 0.579 0.826 0.195 0.164 0.203 0.538

2Inf: Theinformation insidethe website isrelevant.

0.453 0.644 0.828 0.278 0.189 0.210 0.541

3Inf: The site hasinformation aboutdifferent productsof the samecompany.

0.381 0.615 0.793 0.223 0.187 0.209 0.493

4Inf: The websiteinformation aboutforms of paymentis sufficient.

0.337 0.516 0.736 0.193 0.162 0.180 0.543

1P: Using website Ifeel contented.

0.217 0.296 0.217 0.867 0.630 0.371 0.349

(Continued on next page)

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Virtual Atmosphere and Word of Mouth 461

TABLE 1 Item Loading and Cross-Loading Full Sample (Continued)

Items Design Layout Information Pleasure Arousal Delight WOM

2P: Using website Ifeel happy.

0.251 0.307 0.258 0.845 0.631 0.480 0.370

3P: Using website Ifeel satisfied.

0.267 0.342 0.288 0.894 0.658 0.427 0.446

4P: Using website Ifeel pleased.

0.264 0.318 0.232 0.864 0.624 0.365 0.411

5P: Using website Ifeel free.

0.190 0.251 0.198 0.789 0.671 0.358 0.324

1E: Using website Ifeel aroused.

0.207 0.251 0.225 0.688 0.897 0.367 0.337

2E: Using website Ifeel wide awake.

0.214 0.217 0.174 0.669 0.903 0.477 0.321

1S: Using website Ifeel delighted.

0.245 0.290 0.252 0.471 0.470 1.000 0.352

1Int: I will speakwell about thewebsite to otherpeople.

0.496 0.629 0.644 0.378 0.306 0.306 0.914

2Int: I willrecommend thesite if someoneasks for myadvice.

0.522 0.650 0.610 0.455 0.343 0.325 0.933

3Int: I willencourage myfriends andrelatives to visitthe website.

0.481 0.584 0.579 0.396 0.358 0.341 0.913

The structural results (full sample) are presented in Figure 2. In thisstudy a nonparametric approach, known as Bootstrap, was used to estimatethe precision of the PLS estimates and supports the hypotheses (Chin, 1998;Fornell & Larcker, 1981). All path coefficients are found to be significant atthe 0.010, 0.025, or 0.050 levels, except three: atmospheric cues > pleasure,arousal > word of mouth and delight > word of mouth. Therefore, for thefull sample, H2 is not supported and H5 is partially supported.

However, as models yielding significant bootstrap statistics can still beinvalid in a predictive sense (Chin, 1998), measures of predictive validity(such as R2 and Q2) for focal endogenous constructs should be employed.All values of Q2 (chi-squared of the Stone-Geisser Criterion) are positive;therefore, the relations in the model have predictive relevance (Fornell andCha, 1994). The model also demonstrated a good level of predictive power(R2), especially for pleasure, as the modeled constructs explained 59% of thevariance in pleasure, 25% of the variance in delight, and 22% of the variancein WOM. In fact, the good value of GoF (see Figure 2), regarding the large ef-fect size, reveals a good overall fit of the structural model. Atmospheric cues

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Virtual Atmosphere and Word of Mouth 463

FIGURE 2 Structural results for full sample.

(β = 0.276∗∗) significantly influence arousal and this emotional state signif-icantly influences (β = 0.710∗∗∗) pleasure. In turn, pleasure (β = 0.350∗∗∗)exercises a significant effect on WOM. In what concerns atmospheric factors,design (β = 0.365∗∗∗), layout (β = 0.452∗∗∗), and information (β = 0.331∗∗∗)have a positive effect on atmospheric cues.

To test the moderating effect of gender, we estimated two more separatemodels in PLS, the women’s sub-sample (n = 222) and the men’s sub-sample (n = 141), using the test for differences suggested by Chin (2011).The measurement results for each of two sub-samples reveal reliability of theindividual measures, as well as, the convergent validity and the discriminantvalidity of the constructs. The structural results for full sample and the multi-group analysis are presented in Table 3. In order to compare the two groups(the women’s group and the men’s group) we used the procedures describedby Chin et al. (2003) and Chin (2011). A comparison of results suggests thatdifferences exist across sub-groups. The structural model predicted 17.2%more of the variations in word-of-mouth in the women’s sub-group thanin the men’s sub-group. The results seem to reveal that the women’s sub-sample fit the proposed model better. The t-test results suggest that there aresignificant differences in the causal order relationships related to hypothesesH5(a), H5(b), and H5(c). Therefore, the sixth hypothesis is supported.

CONCLUSIONS AND IMPLICATIONS

This study introduces for the first time the second order delight emotion intothe context of S-O-R model and compares two sub-groups: women and men.The findings suggest that the three factors of atmospheric elements analyzed

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TA

BLE

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gnifi

cant.

464

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Virtual Atmosphere and Word of Mouth 465

have significant influence on the arousal and do not have a significant in-fluence on the consumers’ pleasure. In turn, both emotional states directlyaffect the second order emotion delight. It seems that it is pleasure whichexerts a major influence to get people to speak well about the website store.

Globally, the design, layout, and info included in the website signifi-cantly influence the arousal that people feel, but do not show a significantimpact on pleasure. On the other hand, to be aroused and alert when visitingthe website strongly influences the pleasure feeling. The fact that people feelcontent, happy, satisfied, pleased, and free reflects on the way they speakwell about the online store and when recommending it to others. However,WOM is not directly influenced by the arousal or delight of the users.

When dividing the sample by gender, we can observe that for womenatmospheric cues have a stronger significant influence in the sense of arousaland pleasure when compared to the total sample. On the other hand,whereas in the total sample the arousal and pleasure significantly influencedelight, for the men sample only pleasure has a significant effect on delightand in the case of women only on arousal.

For women to praise the website and recommend it to other people theyhave to feel pleasure and even more delight during their online experience;Whereas, for men it is the sense of satisfaction, happiness, or pleasure thatmakes them favorably speak about the website store and brand. Hence, wecan conclude that emotions influence the women’s group in a stronger waythat makes them favorably speak about the websites than men. Thus it seemsthat the proposed model is more adjusted to women then to men.

This seems to be in sync with the investigations by Blumstein andSchwartz (1983) and Hansen (1987), although their study was aimed at prov-ing that women are more loyal then men. In the present study, women tendto speak more positively if the stimuli create strong positive emotions.

According to the total sample, this study corroborates that of Oliveret al. (1997) by confirming in the online context that delight is formedfrom the arousal and pleasure, having the pleasure the same meaning thatOliver et al. (1997) attributed to positive affect. Although the results wefound need further confirmation, in order to achieve delight, website andbrand managers should take care to differentiate the stimuli presented intheir websites according to gender. The findings suggest that brand websitemanagers, marketers, and designers should create websites that have acollection of activities that make them more dynamic, in order to stimulatemen more. It would also be relevant to segment the construction of websitesbased on women/men dichotomy and not just present a single websiteproposal for the whole population in general, especially if they want toattract the men’s attention for products such as groceries, which are not themost attractive for men. This is increasingly important since as Dholakiaet al. (1995) and Lee et al. (2005) mentioned, lifestyles are changing and menunder the current circumstances are more prone to life alone for longer and

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466 S. M. C. Loureiro and L. Ribeiro

to go the supermarket to do shopping or even buy more useful and dailyproducts.

As a limitation and opportunity for further research, we draw the atten-tion to some aspects: to study in the future other factors that can start thewhole emotional process either for men or women; to consider other outputwithout WOM; to bring in positive and negative emotions to the model; totry and understand that other variables can contribute for the S-O-R frame-work to adjust better to men, which can be related to the type of stimulusthat creates positive emotions; to use more product categories (useful andhedonic) that from the start will stimulate both genders alike, and also takeinto consideration products that are more “male” (e.g., gadgets).

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