Role of Website Design Quality in Satisfaction and WOM Generation_10

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Role of website design quality in satisfaction and word of mouth generation

Abstract

Purpose The purpose of this study is to examine a comprehensive model explaining how

website design influences consumers emotional and cognitive responses and contributes to

satisfaction and WOM communication in an online shopping context.

Design/methodology/approach A total of 804 female college students completed an online

survey after browsing one of two mock websites developed to manipulate website design quality.

Findings Website design quality showed positive direct effects on pleasure, arousal, and

perceived information quality and indirect effects on satisfaction and WOM intention. Pleasant

shopping experience increased positive perceptions and satisfaction. The results also showed that

satisfaction mediated the relationship between emotional and cognitive responses and positive

WOM intention.

Research limitations/implications Although an online survey was used to increase the reality

of an online shopping experience, uncontrolled conditions may have influenced the results of the

study. Further Research needs to be conducted in a lab setting to control these factors.

Originality/value This study theoretically extends the applicability of the Stimulus-Organism-

Response paradigm to satisfaction and electronic WOM intention research and fills the gap in the

current online shopping literature. This study also offers valuable information to online retailers

to maximize consumer satisfaction and generate positive WOM using website design.

Keywords eWOM, Website Design, Emotions, Satisfaction

Paper type Research Paper


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1. Introduction

Word of mouth (WOM) refers to informal interpersonal communication regarding the

evaluation of a store, its product and service, and related experience (Dichter, 1966; Gupta and

Harris, 2010). Initiating positive WOM among consumers becomes an important marketing

strategy (Smith et al., 2007) because of its significant impact on the consumers purchase

decision (Michelle, 2006). In general, WOM is seen as a significant and trustworthy source of

information in the formation of a positive image of a company (Allsop et al., 2007). The effect of

WOM activity on consumer trust and behavioral intention is particularly prominent on the

Internet (Award and Ragowsky, 2008). In a traditional store setting, consumers examine

products using visual and tangible cues. However, online shoppers can count only on visual cues

presented on the screen. Due to lack of direct interaction with the product in an online shopping

context, the impact of WOM on consumer purchase decisions could be more powerful (Smith et

al., 2007).

Researchers and practitioners have highlighted the role of electronic WOM (eWOM) in

marketing practice as the extensive use of the Internet, smartphones, and PDAs has made

information sharing easier than ever before (Allsop et al., 2007). Previous research investigated

antecedents of eWOM communication and identified factors contributing to WOM activities.

Evidence shows that satisfaction (Casalo et al., 2008; Finn et al., 2009) and customer loyalty

(Casalo et al., 2008) are key determinants of positive eWOM. Various personal factors (e.g.,

prior internet experience, need for uniqueness) are also related to eWOM engagement (Cheema

and Kaikati, 2010; Ho and Dempsey, 2010; Jones et al., 2009). Additionally, researchers have

investigated the impact of eWOM and identified outcomes. It was found that the quality and type

(e.g., positive vs. negative customer reviews) of eWOM have a significant influence on


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consumer trust (Award and Ragowsky, 2008), purchase decisions (Award and Ragowsky, 2008;

Gupta and Harris, 2010), and behavioral intentions (Jones et al., 2009; Park and Kim, 2008).

As indicated above, numerous studies have tested the antecedents and effects of eWOM

activity. However, no research has focused on how website design contributes to generating

consumers WOM communication, although it has been well documented that website design

affects online shoppers in many ways. For example, website design plays a significant role in

shaping store image and creating the first impression of a store (Oh et al., 2008). Previous

research underlined the effectiveness of website design on consumer responses, such as emotions,

cognitions, and various consumer behavioral intentions (e.g., Eroglu et al., 2003; Ha and Lennon,

2010a; Richard, 2005). Wu et al. (2008) found that website design elements such as color and

music have a significant impact on the level of pleasure and arousal. Previous research also

confirmed that website design elicits positive perceptions about the store and its products (Oh et

al., 2008). Both emotional and cognitive responses induced by website design have been found

to increase consumer satisfaction (Eroglu et al., 2003) and positive behavioral intentions (Eroglu

et al., 2003; Richard, 2005). Whereas there has been extensive research on the effect of website

atmosphere on consumer response behaviors, little research has examined how website design

affects online consumers WOM activity. Thus it is timely to investigate how website design

influences WOM communication in an online shopping context.

The current study is designed to fill this void in the literature of website

design/atmosphere and WOM. A comprehensive model was developed and empirically tested to

explain the effect of website design on consumers emotional and cognitive responses that, in

turn, affect satisfaction and WOM intention.

2. Theoretical Background and Hypotheses Development


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2.1 S-O-R Paradigm and Its Extension

Mehrabian and Russell (1974) proposed the Stimulus (S) Organism (O) Response (R)

paradigm that describes the effects of environmental stimuli on emotions and behavioral

responses. According to the paradigm, various environmental stimuli (e.g., color, music, light,

and scent) induce emotions (e.g., pleasure, arousal, and dominance) which in turn influence

approach-avoidance behaviors (Mehrabian and Russell, 1974). By applying the S-O-R paradigm

to traditional and online store settings, previous researchers empirically demonstrated that

traditional or online store environmental stimuli affect emotional reactions that in turn influence

response behaviors such as purchase and revisit (Babin and Babin, 2001; Eroglu et al., 2003;

Fiore et al., 2005; Ha and Lennon, 2010a, 2010b; Hu and Jasper, 2006; Menon and Kahn, 2002).

In addition to emotional reactions, researchers have extended the paradigm by

incorporating consumers cognitive responses toward the store environment. These include the

perceptions, thoughts, and beliefs structured in consumers minds while interacting with various

cues. Researchers found that store stimuli (e.g., color, light) elicit not only emotional but also

cognitive responses within organisms and that cognitive responses also affect

approach/avoidance behaviors (Babin et al., 2003). In an online store setting, both emotional and

cognitive responses are also found to play an important role in the relationship between online

store atmosphere and behavioral responses (Eroglu et al., 2003; Park et al., 2008; Richard, 2005).

In the S-O-R paradigm, approach or avoidance behaviors are generally operationalized as

the response behavior or behavioral intention and measured with behavioral outcome variables

such as desire to explore the store (Ha and Lennon, 2010a; Wu et al., 2008) and time/money

spent (Smith and Sherman, 1993).


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Recent studies have extended the S-O-R paradigm by exploring new variables in the

response pool, widening the scope of response (R) induced from emotional and cognitive

reactions that occur in the organism (O). Researchers proposed satisfaction (Eroglu et al., 2003;

Ha and Lennon, 2010a; Im and Ha, 2011) and purchase/patronage intentions (Babin et al., 2003;

Fiore et al., 2005; Ha and Lennon, 2010a, 2010b) as important positive response behaviors.

Studies confirmed that emotions and cognitions induced by store or non-store environment

influence satisfaction (Eroglu et al., 2003; Im and Ha, 2011) and behavioral intention (Kim et al.,

2009; Kim and Niehm, 2009; Oh et al., 2008).

In addition to satisfaction, Ladhari, 2007 examined WOM intention as a response

behavior in a movie consumption context which demonstrated a positive relation to emotion and

satisfaction. This present study extends the applicability of the S-O-R paradigm into eWOM

research by examining the role of emotional and cognitive responses to site design in explaining

satisfaction and WOM intention in an online shopping context.

2.2 Website Design, Emotions, and Cognition

Store environmental cues affect consumer emotions both in traditional (Babin et al.,

2003; Baker et al., 1992; Crowley, 1993; Donovan et al., 1994) and online (Eroglu et al., 2003;

Fiore et al., 2005; Ha and Lennon, 2010a, 2010b; Menon and Kahn, 2002) settings. In brick-and-

mortar stores, atmospheric cues such as music (Baker et al., 1992; Donovan et al., 1994) and

color (Babin et al., 2003; Crowley, 1993) increase consumer pleasure and arousal while shopping.

Online shopping researchers also demonstrated the effects of various website design factors (e.g.,

color) on consumer pleasure and arousal (Eroglu et al., 2003; Ha and Lennon, 2010a; Menon and

Kahn, 2002). Website cues such as font color, background color, animated images, and


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interactivity features positively influence the emotions or moods felt by online shoppers (Eroglu

et al., 2003; Fiore et al., 2005; Park et al., 2008; Wu et al., 2008).

According to the extended S-O-R paradigm (Eroglu et al., 2001), website atmosphere

also influences cognitive responses (e.g., attitude, perception). Previous research found that

various website design cues influence consumers cognitive judgment such as attitude and

perceived information (Eroglu et al., 2003; Oh et al., 2008; Park et al., 2008). Oh et al., (2008)

found that website design affects the perceived quality of the online store. Online shoppers

exposed to a picture-based website design were more likely to perceive the online store as a safe,

convenient, and enjoyable place to shop than those exposed to the site with a text-based website

design (Oh et al., 2008). More closely related to the current research, Kim and Niehm (2009)

revealed that website design quality positively influences perception regarding the quality of

information shown on the website. Therefore, the following hypotheses were proposed.

H1. Website design will influence consumer emotional and cognitive responses.

H 1a. Website design will influence pleasure.

H 1b. Website design will influence arousal.

H 1c. Website design will influence perceived quality of information.

Previous research emphasized the significant role of emotions in the formation of

cognitive responses (Eroglu et al., 2001, 2003; Olney et al.,1991; Zajonc and Markus, 1982). It

was found that positive emotions generate a positive attitude toward an online store (Eroglu et al.,

2003) and enhance perceived store image (Sherman and Smith, 1987). Consumer mood also

influences perceptions about the website and its service (Park et al., 2005; Park et al., 2008).

Positive mood induced by a moving image decreases perceived risk (Park et al., 2005) and

results in a positive evaluation of the website and its content, such as product information (Park


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et al., 2008). Therefore, it is possible that people who experience more pleasure and arousal by

the website design may evaluate the website and product information more favorably. Based on

the rationale from previous research, the following hypotheses were developed.H2. Emotions will influence cognitive response.

H2a. Pleasure will influence perceived quality of information.

H2b. Arousal will influence perceived quality of information.

2.3 Antecedents of Satisfaction and Word of Mouth Intention

Satisfaction research has emphasized that both emotional response and cognitive

judgment are required to create satisfaction (e.g., Im and Ha, 2011; Oliver, 1993). Oliver et al.

(1997) found that positive emotion increases satisfaction. Im and Ha (2011) confirmed that

consumer emotions (i.e., pleasure and arousal) and cognition (i.e., perception of retail

environment) are strong antecedents of satisfaction. The online atmospheric literature has also

highlighted the importance of both emotional and cognitive variables in predicting satisfaction as

well as various behavioral intentions (Eroglu et al., 2001; Fiore and Kim, 2007; Park et al., 2008).

Eroglu et al. (2003) found that in the online shopping setting, both emotion and cognition are

positively related to satisfaction and approach behaviors. However, the majority of previous

research in relation to retail or online store environments has empirically examined either

emotion (e.g., pleasure and arousal) or cognitive judgment (e.g., perceived quality of website) as

an antecedent of satisfaction and behavioral intention.

Drawn from the S-O-R paradigm, researchers empirically demonstrated the significant

effects of pleasure and arousal on satisfaction (Eroglu et al., 2003; Ha and Lennon, 2010a; Spies

et al., 1997) and behavioral intentions (Babin and Babin, 2001; Fiore et al., 2005; Ha and Lennon,

2010a). Positive perceptions about the website and its content increase satisfaction (Rodgers et


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al., 2005) and loyalty intention (Kim et al., 2009; Kim and Niehm, 2009). Perceived information

quality is positively related to consumers behavioral intention (e.g., recommending the site to

others) (Kim and Niehm, 2009). Therefore, online shoppers who perceive the information

provided to be of high quality are likely to be satisfied with the website and consequently

generate positive WOM.

Due to the recognizable power of eWOM (Award and Ragowsky, 2008), the importance

of emotional and cognitive dimensions in relation to eWOM communication has been noted by

researchers (Allsop et al., 2007; Jones et al., 2006). Closely related to the current study, Ladhari

(2007) examined the role of emotions in anticipating satisfaction and WOM communication and

found that pleasure and arousal were significant predictors of satisfaction and the likelihood of

generating WOM. Both emotional (e.g., pleasure, joy) and cognitive (e.g., acquisition of

products or information) aspects of the shopping experience can contribute to generating positive

WOM (Jones et al., 2006). Based on previous research, it is likely that positive emotions and

perceptions about the website will increase online shoppers satisfaction and positive WOM.

Given the rationale above, the following hypotheses were developed.

H3. Emotional and cognitive responses will influence satisfaction.

H3a. Pleasure will influence satisfaction.

H3b. Arousal will influence satisfaction.

H3c. Perceived quality of information will influence satisfaction.

H4. Emotional and cognitive responses will influence word-of-mouth intention.

H4a. Pleasure will influence word-of-mouth intention.

H4b. Arousal will influence word-of-mouth intention.

H4c. Perceived quality of information will influence word-of-mouth intention.


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2.4 Effect of Satisfaction on Word of Mouth Intention

It is established that satisfaction is positively related to positive WOM. Previous

marketing and satisfaction research highlighted the important role of satisfaction in predicting

various outcome behaviors such as WOM (Jones et al., 2006; Ladhari, 2007; Swan and Oliver,

1989) and loyalty intention (Kim et al., 2009; Rodgers et al., 2005). The likelihood of consumers

engaging in WOM communication is strongly linked to their level of satisfaction (Bearden and

Teel, 1983; Ladhari, 2007; Matos and Rossi, 2008; Ranaweera and Prabhu, 2003). In a retail

shopping context, satisfaction is a significant antecedent of positive WOM (Jones et al., 2006).

Satisfied consumers are more likely to recommend the store or its product to others (Swan and

Oliver, 1989). Ladhari (2007) demonstrated the positive effect of satisfaction on the likelihood of

generating WOM in a movie consumption context.

Although many researchers have proposed satisfaction as a direct predictor of WOM, a

comprehensive WOM model that incorporates antecedents of satisfaction has not been

extensively explored. Some researchers investigated the mediating role of satisfaction between

emotions/cognitions and behaviors. Satisfaction was found to partially mediate the relationship

between emotions (i.e., pleasure and arousal) and WOM (Ladhari, 2007). Previous research

(Finn et al., 2009) also confirmed that satisfaction mediates the effect of cognitive judgment (e.g.,

disconfirmation) on positive WOM intention (Finn et al., 2009). Satisfaction literature suggests

that both cognitive and emotional antecedents need to be examined to explain satisfaction.

Therefore, understanding how consumer emotional and cognitive responses toward website

design produce satisfaction and how satisfaction contributes to positive WOM is deemed

important. Consistent with previous research, the following hypotheses were proposed.

H5. Satisfaction will influence word of mouth intention.


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H6. Satisfaction will partially mediate the effects of pleasure, arousal, and perceived information

quality on word of mouth intention.

3. Methodology

3.1 Research Design and Procedure

In this study, two mock apparel websites that differed in atmospheric design were

developed to target young female consumers. It has already been determined that young female

consumers are the key drivers of online purchasing (Abraham et al., 2010). Female consumers

spend more time and dollars online than male consumers (Abraham et al., 2010) and spend 41%

more time on social networking sites than their male counterparts (ComScore, 2010). More

importantly, their purchases are strongly influenced by eWOM such as online product reviews

and recommendations (InternetRetailer, 2010). Therefore, understanding female online

consumers perceptions and their influence on eWOM behavior is very important. Apparel

products were selected because they are one of the most popular merchandise categories

purchased online (Corcoran, 2007). Among the top 500 online retailers, online sales of apparel

and related products reached $12.4 billion, which accounted for 12.2% of total sales in 2007

(Brohan, 2008).

This study adopted various web stimuli (e.g., background colors, fonts, and icon types) to

manipulate website design, as has been reflected in previous research (Davis et al., 2008; Eroglu

et al., 2003; Ha and Lennon, 2010b). In this study, the website with high (vs. low) quality design

contained blue text (vs. black), colorful icons (vs. underlined hyperlinks), and a background with

a brand logo pattern (vs. a white background). The effectiveness of this manipulation was

checked using perceived quality of website design items and found to be successful (Check the


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measures section below for detail). Identical product information was provided in both

websites to observe whether perceived information quality differs as a function of website design.

Since the website was designed to target young female consumers, a random sample of

female students was recruited at a large Midwestern university. Potential participants received an

invitation email with a URL link and a description of the study. By clicking the link, participants

were randomly assigned to one of the two websites and asked to browse the site for a while.

After browsing, participants completed the survey.

3.2 Measures

The questionnaire consisted of six parts:

1) quality of website design (WD);

2) Pleasure (PL) and Arousal (AR);

3) perceived quality of information (PQI);

4) satisfaction (SAT);

5) word of mouth intention (WOM);

6) demographic information. Multiple items were used to measure six latent variables in

the analyses.

Perceived quality of website design was assessed using five 5-point Likert scales (1-

strongly disagree to 5-strongly agree) developed and validated through a two-stage study by

Aladwani and Palvia (2002). The result of univariate analysis of variance (ANOVA) revealed a

significant main effect for high or low quality site design manipulation on perceived quality of

website design, F(1, 802) = 7.494,p < .005. Mean scores for high or low quality website design

were 18.49 (SD=4.13) and 17.70 (SD=4.08), respectively. Participants who browsed the website

with the high quality design tended to perceive the web design to be higher quality than those


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who browsed the website with low quality design. Thus, five website design quality items were

used to measure the website design latent construct in the main model.

Information quality was extensively studied in data management research. Wang and

Strong (1996) proposed and empirically tested a hierarchical framework for the dimensions of

data quality. The framework identified four major dimensions of data quality: Intrinsic (e.g.,

accuracy), contextual (e.g., relevancy, completeness, appropriateness of amount),

representational (e.g., ease of understanding), and accessibility. In this study, information quality

focuses on contextual data quality which needs to take into account the situation in which the

information is used (Wang and Strong, 1996). Contextual data quality emphasizes the

importance of value-added, relevancy, timeliness, completeness, and amount of information

(Wang and Strong, 1996). The focus of the current study is not on data quality management but

the impact of website appearance factors on perception of information quality and other outcome

variables. The contextual dimension provides a more meaningful understanding of consumers'

needs within a particular shopping situation (i.e., online apparel shopping). Therefore, perceived

quality of information was measured using five Likert scales representing contextual data quality.

For example, as shown in Table 1, PQI1 and PQ3 measure perceived amount of information,

PQI2 represents completeness (scope of information) and relevancy of information, and PQI4

assesses whether the product information available in the website adds value to the shopping

process (i.e., assists with the purchase decision).

Emotions were measured by pleasure (e.g., pleased-annoyed) and arousal (e.g., frenzied-

sluggish) with 12 items using 7-point semantic differential scales (Mehrabian and Russell, 1974).

Three 5-point Likert scales were used to assess satisfaction (e.g., I was satisfied with my

shopping experience at the website) (Eroglu et al., 2003). Word of mouth was measured by two


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items (e.g., I would recommend this website to other people) using 5-point Likert-type scales

ranging from 1 (unlikely) to 5 (likely). Demographic information such as age, academic standing,

and ethnicity was also gathered.

4. Results

4.1 Description of Participants

A total of 804 usable responses were collected. The mean age was 21 years, with a range

of 18 to 48 years. Respondents varied in terms of academic background and were mostly

Caucasian Americans (74%), with small percentages from other ethnic groups: Asian Americans

(6.5%), African Americans (6.3%), and Hispanic Americans (2.6%).

4.2 Model Assessment

A confirmatory factor analysis (CFA) using Amos 16 was performed to assess the initial

measurement model. Based on the result, the initial model was respecified (Anderson and

Gerbing, 1988). Three arousal measures, one pleasure measure, one perceived quality of

information measure, and one satisfaction measure were eliminated due to their low squared

multiple correlations (lower than .5) (Bagozzi and Yi, 1991). One website design indicator was

removed because of unexplainable error variances with other indicators posited to measure other

latent variables. Table 1 shows the measurement items included in the final model.

Convergent and discriminant validity and unidimensionality were checked for the

respecified model. Significant path coefficients (s=.65-.92,p


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unidimensionality (Grefen, 2003). Discriminant validity was also achieved by higher average

variance extracted (AVE) for each latent variable than the squared correlation between constructs

(Fornell and Larker, 1981) (See Table 2). The reliability of the measurement model was assessed

by composite reliability and AVE (Fornell and Larcker, 1981). The composite reliability of all

latent variables was within the acceptable range and the AVE estimates for latent constructs

exceeded the .50 critical value (Fornell and Larcker, 1981), providing evidence of reliability (See

Table 2).

Table 1. Final measurement items used in the main study.

Latent Constructs Indicators Measurement Items

WD1 The website looks attractive

WD2 The website uses fonts properly

WD3 The website uses colors properly

Website Design

WD4 The website uses multimedia features properly

PL1 Happy UnhappyPL2 Pleased AnnoyedPL3 Satisfied -- UnsatisfiedPL4 Contented MelancholicPL5 Hopeful Despairing

Pleasure

AR1 Frenzied SluggishAR2 Excited Calm

Arousal

AR3 Wide-awake Sleepy

PQI1 The website you browsed today contained very much

informationPQI2 From browsing the website, I learned a great deal about

the productPQI3 The website was very informative

Perceived Quality

of Information

PQI4 After browsing the website, I know enough to make aninformed purchase decision

SAT1 I enjoyed visiting this website.Satisfaction

SAT2 I was satisfied with my shopping experience at this website.

WOM1 I would recommend this website to other people.Word of Mouth

Intention WOM2 I would recommend this website to my friend.


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Table 2. Composite reliabilities, Squared correlations, and AVEs of latent constructs.

Latent ConstructsWebsiteDesign

Pleasure Arousal Perceivedquality of

Information

Satisfaction Word ofMouth

Website Design.73a, .91b

Pleasure .16c .52, .84

Arousal .06 .20 .52, .76

Perceived qualityof Information

.34 .12 .05 .74, .92

Satisfaction .30 .43 .11 .24 .81, .90

Word of mouth .25 .32 .09 .23 .64 .66, .79

Note. a Average variance extracted, b Composite reliability, c Squared Correlation.

To confirm that the measures used in the study are generalizable beyond the given sample,

the validity of the proposed model was cross-validated using two sub-samples, calibration and

validation samples, as suggested by previous researchers (MacCallum, 1995; Schumacker and

Lomax, 2004). Fit indices for two sub-samples were within acceptable ranges (RMSEA1=.064,

RMSEA2=.052, NFI1=.93, NFI2=.95, GFI1=.91, GFI2=.93, CFI1=.96, CFI2=.97). The results

confirm the validity and generalizability of the measures used in the study.

4.3 Hypotheses Testing

Structural equation modeling (SEM) using Amos 16 was performed to test hypotheses.

The model consisted of six latent constructs (one exogenous latent variable website design

quality and five endogenous latent variables pleasure, arousal, perceived quality of

information, satisfaction, and word of mouth intention) and 20 manifest variables. Since the chi-

square statistic is sensitive to a large sample size and a large number of indicators, the significant


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value for the model was not unexpected (2=550.507 with df=157,p


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Table 3. Measurement and structural model parameters and model fit.

Parameters Standardizedestimates

t-values

Structural ModelWebsite Design (1) Pleasure (1) 11 .40 10.22***Website Design (1) Arousal (2) 21 .32 07.12***Website Design (1) Information Quality (3) 31 .53 13.29***Pleasure (1) Information Quality (3) 31 .12 02.83**Pleasure (1) Satisfaction (4) 41 .50 12.12***Pleasure (1)Word of Mouth (5) 51 -.01 00.28Arousal (2) Information Quality (3) 32 .04 00.81

Arousal (2) Satisfaction (4) 42 .11 02.72**Arousal (2)Word of Mouth (5) 51 .08 02.06*Information Quality (3) Satisfaction (4) 43 .30 09.07***Information Quality (3)Word of Mouth (5) 53 .08 02.57**Satisfaction (4)Word of Mouth (5) 54 .79 15.00***

Measurement ModelWebsite Design (1)WA1 x11 .79 --Website Design (1)WA2 x21 .85 26.89***Website Design (1)WA3 x31 .90 32.46***Website Design (1)WA4 x41 .84 29.58***Pleasure (1) PL1 y11 .74 --

Pleasure (1) PL2 y21 .83 23.74***Pleasure (1) PL3 y31 .86 24.65***Pleasure (1) PL4 y41 .84 24.08***Pleasure (1) PL5 y51 .73 20.70***Arousal (2) AR1 y62 .84 --Arousal (2) AR2 y72 .81 20.52***Arousal (2)AR3 y82 .66 17.83***Information Quality (3) PIQ1 y93 .84 --Information Quality (3) PIQ2 y103 .92 27.30***Information Quality (3) PIQ3 y113 .92 30.93***Information Quality (3) PIQ4 y123 .79 30.82***Satisfaction (

4) SAT1

y134.90 --

Satisfaction (4) SAT2 y144 .91 35.67***Word of Mouth (5)WOM1 y155 .74 --Word of Mouth (5)WOM2 y165 .92 23.00***

Model fitChi-square (2) 550.507 df= 157, p < .0001RMSEA .056 C.I. (.051; .061)GFI .94AGFI .91NFI .95CFI .97

Note. *p


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To test Hypothesis 6, the bootstrapping method was employed because it provides the

most powerful method of testing mediating effects and obtaining confidence intervals (Preacher

and Hayes, 2008; Williams and MacKinnon, 2008). If confidence intervals do not include zero, it

can be claimed that the effect is significantly different from zero with 90% confidence (Hayes,

2009). Results confirmed that the indirect effect of pleasure on WOM intention was significant

and strong (indirect effect=.426) while the direct effect was not significant (H4a). Although both

direct and indirect effects of perceived information quality on WOM were statistically significant,

the indirect effect (.227) was deemed greater than the direct effect (.080). Arousal was also found

to have significant and positive direct and indirect effects on WOM. The results indicated that

satisfaction partially mediated the effects of pleasure, arousal, and perceived quality of

information on WOM intention. Therefore, H6 was supported. Bootstrapping results appear in

Table 4.

Table 4. Standardized direct and indirect effects and 90% confidence intervals.

Direct effect Indirect effect Total effect

Path 90% CI 90% CI

Website Design Pleasure .399*** .335 .468 .399***

Website Design Arousal .322*** .242 .405 .322***

Website Design PQI .528*** .468 .593 .059*** .036 .091 .587***

Website Design Satisfaction .408*** .364 .467 .408***

Website Design WOM .383*** .333 .441 .383***

Pleasure PQI .118** .059 .219.118**

Pleasure Satisfaction .504** .433 .577 .034** .018 .064 .539***

Pleasure WOM -.012 -.084 .058 .426*** .364 .498 .414***

Arousal PQI .036 -.040 .117 .036

Arousal Satisfaction .110* .036 .199 .010 -.011 .035 .121***

Arousal WOM .076* .016 .150 .096** .036 .158 .173**

PQI Satisfaction .293** .230 .346 .293**

PQI WOM .080* .022 .137 .227*** .179 .273 .306***

Satisfaction WOM .774** .699 .831 .774**

Note. CI denotes a confidence interval, *p


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4.4 Post-hoc Model Test

As shown in Table 4, no direct effect of pleasure on WOM intention was found while the

indirect effect was strong. To confirm the complete indirect effect of pleasure on WOM intention,

the original structural model was compared with the nested model (no causal relation between

pleasure and WOM intention). Results showed that there were no significant differences in terms

of fit indices (the nested model: 2=550.587 with df=158,p


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shows a significant direct effect on perceived quality of product information. Indications are that

colors, fonts, and background images used in the online retail website induce pleasure and

arousal and increase positive perception about the information provided in the website. In

general, the website front page plays a vital role in enhancing store image and generating

positive impression about the online store and its products (Oh et al. 2008). Therefore,

developing a better quality front page design using appropriate design elements (e.g., colors,

icons, fonts, images) is crucial to a pleasant and exciting shopping experience with the website,

and to increase positive perceptions about the store and its content (e.g., product information

quality).

The result shows a significant direct effect of pleasure on perceived information quality.

A pleasant experience leads consumers to a positive cognitive evaluation (i.e., perceived quality)

of the product information provided on the website. However, the effect of arousal on perceived

quality of information was not significant. These results are similar to Eroglu et als (2003) study

that found a positive effect of pleasure on attitude (i.e., cognitive response) toward the online

store but no effect of arousal on attitude. Rather than arousal, pleasure induced by the website

atmosphere seems to be a stronger antecedent of cognitive response.

According to Mano and Oliver (1993), arousal is strongly related to hedonic evaluations

(e.g., pleasantness) rather than utilitarian evaluations (e.g., need or value) of the store or its

products. Although a mediating effect of pleasure in the relationship between arousal and

perceived information quality was not examined in this study, it is possible that arousal has an

indirect effect on perceived quality of information through pleasure (i.e., hedonic evaluation of

the site).


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As hypothesized, direct effects of pleasure and arousal on consumer satisfaction were

significant and positive. The results are consistent with previous research that found the positive

relationship between emotional responses and satisfaction (Eroglu et al., 2003; Im and Ha, 2011;

Ladhari, 2007). Similar to previous findings (Kim et al., 2009; Rodgers et al., 2005), this study

also confirms that perceived quality of product information has a positive impact on satisfaction.

Thus, both emotional and cognitive responses to the website design are found to be significant

antecedents of satisfaction. Additionally, this study shows that pleasure affects satisfaction both

directly and indirectly, and the effect of pleasure on satisfaction is stronger than the effects of

arousal and perceived information quality on satisfaction (See Table 4). This highlights an

essential role of a pleasant shopping experience in consumer satisfaction.

This study confirms that arousal and perceived information quality positively influence

WOM intention. Although arousal has significant direct and indirect effects on positive WOM

intention, the impact of arousal on WOM intention is rather weak and partially mediated by

satisfaction. This finding is consistent with Ladharis (2007) results. Perceived information

quality appears to influence WOM intention both directly and indirectly (through satisfaction).

This suggests that online shoppers who perceive information as high quality are more likely to

recommend the site to others than those who perceive information as low quality.

The effect of emotions and cognitions on WOM seems to become even stronger

following a satisfying shopping experience. As expected, satisfaction shows a positive impact on

WOM generation. Satisfied online shoppers are more likely to recommend the website to others

than dissatisfied shoppers. Furthermore, significant indirect effects of arousal, pleasure, and

perceived information quality on WOM intention support the mediating impact of satisfaction on

positive WOM intention. Interestingly, pleasure shows no direct effect on WOM intention


24/34

whereas the indirect effect of pleasure on WOM intention is strong and significant. This

suggests a significant mediating role of satisfaction between pleasure and WOM intention and

also indicates that pleasure is not likely to generate WOM unless shoppers are satisfied with their

experience at the online store. This is consistent with previous research (Finn et al., 2009;

Ladhari, 2007) that reported a significant mediating role of satisfaction in WOM intention.

The key conclusion from this study is that website design does make a difference in

consumer emotions and perception about the website content (product information). Overall, the

results suggest that online retailers need to develop websites that induce pleasure rather than

arousal if they want to improve consumers cognitive evaluation of the website content and their

satisfaction. This may be more important for online retailers who sell experience goods (e.g.,

clothing, movies, music) rather than search goods (e.g., digital camera, printer) because in

general, consumers are likely to value a hedonic experience (i.e., pleasure) while shopping for

experience goods. In addition, since attributes of experience goods are hard to compare and

evaluate (Mudambi and Schuff, 2010), perceived information quality may play a more important

role in satisfaction and WOM generation for experience goods than for search goods. Online

retailers are advised to provide quick links to social networking sites such as Facebook, Twitter,

and YouTube in their website so that the increased WOM intention can be more easily actualized.

Website design shows significant indirect effects on satisfaction and positive WOM

generation as well (see Table 4). This study emphasizes the important role of consumers

shopping experience while browsing the website and its impact on satisfaction and WOM

generation. Both emotional and cognitive evaluations about the website influence satisfaction

and WOM generation. To maximize satisfaction and generate positive WOM, it is important for

online retailers to develop a site design with appropriate design cues targeting its potential


25/34

consumers. Website personalization may help online retailers improve consumers hedonic

shopping experience (i.e., pleasure) that in turn influences cognitive evaluation of site contents

(product information), satisfaction, and WOM generation. In the front page of the online store,

retailers can provide options for shoppers to view different colors, fonts, icons, and/or

background image/color. Personalization may increase shopping enjoyment and satisfaction level

for consumers with different needs and tastes.

Although an online survey was used to increase the reality of an online shopping

experience, uncontrolled conditions (e.g., different monitor resolution, the speed of the Internet)

may have influenced the results of the study. Further research needs to be conducted in a lab

setting to control these factors along with an examination of how different types of design cues

(e.g., flash images, video clips, music, etc.) and their characteristics (e.g., tangibility,

interactivity) affect consumer satisfaction and WOM intention.


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Stimulus Organism Response

Direct effect

Indirect effect

Note. *p

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