This article was downloaded by: [ECU Libraries]On: 10 October 2014, At: 03:55Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

International Journal of Human-Computer InteractionPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/hihc20

Visualizing E-Brand Personality:Exploratory Studies on Visual Attributesand E-Brand Personalities in KoreaSu-e Park , Dongsung Choi & Jinwoo KimPublished online: 09 Jun 2010.

To cite this article: Su-e Park , Dongsung Choi & Jinwoo Kim (2005) Visualizing E-Brand Personality:Exploratory Studies on Visual Attributes and E-Brand Personalities in Korea, International Journal ofHuman-Computer Interaction, 19:1, 7-34, DOI: 10.1207/s15327590ijhc1901_3

To link to this article: http://dx.doi.org/10.1207/s15327590ijhc1901_3

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever orhowsoever caused arising directly or indirectly in connection with, in relation to or arisingout of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Visualizing E-Brand Personality: ExploratoryStudies on Visual Attributes and E-Brand

Personalities in Korea

Su-e ParkDongsung Choi

Jinwoo KimHCI Lab, Yonsei University, Seoul, Korea

The brand personality of an online product and service, usually represented by a Website, is known as its e-brand personality. In the competitive conditions of online mar-kets, e-brand personality is agreed to be an important factor in securing distinctiveidentity; however, few studies have suggested how to establish e-brand personalitythrough the visual design of Web sites. This study explores the feasibility of construct-ing target e-brand personalities for online services by using visual attributes. It con-sists of 3 consecutive studies. The 1st study identified four major dimensions ofe-brand personality on diverse Web sites. The 2nd study used 52 experimental homepages to identify key visual attributes associated with those 4 personality dimensions.The 3rd study explored whether those findings from the 2nd study can be applied inconstructing Web sites for online services. The results showed that 2 visual attrib-utes—simplicity and cohesion—are closely related to a bold personality. Three attrib-utes—contrast, density, and regularity—can be used to create a Web site that has ananalytical personality. Contrast, cohesion, density, and regularity are closely related toa Web site that is perceived to have a friendly personality. Regularity and balance wereexpected to be related to the sophisticated personality dimension, but no such relationwas identified in the 3rd study. The article concludes with a discussion of implications,limitations, and future research directions.

1. INTRODUCTION

The online business environment is becoming more and more complicated andcompetitive. To survive in this environment, online companies have adopted elab-orate strategies to build distinctive brand identities for their Web sites (Keller, 2002;

INTERNATIONAL JOURNAL OF HUMAN–COMPUTER INTERACTION, 19(1), 7–34Copyright © 2005, Lawrence Erlbaum Associates, Inc.

Su-e Park is now at the Contents Design Department, Seoul Women’s University, Seoul, Korea.This research was supported by a Korea Research Foundation Grant (KRF–2002–005–H20002).Requests for reprints should be sent to Su-e Park, Sang Dae Shin Kwan, #613, Yonsei University, Se-

oul, 120–749, Korea. E-mail: spark44@hanmail.net; spark44@yonsei.ac.kr

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

Lindstrom & Anderson, 2000) and, thus, to assert the uniqueness of their productor service (Breakenridge, 2001). The concept of e-brand personality has been pro-posed as a way to understand how these strategies can bestow a compelling iden-tity on an online product or service (Lindstrom, 2001) as they have done for prod-ucts and services in the real world (D. A. Aaker, 1996; J. Aaker, 1997; Plummer,1985; Rust, Ambler, Carpenter, Kumar, & Srivastava, 2004). E-brand personality is amodel in which human personality traits such as “sincerity” and “sophistication”are applied to online products and services.

Studies of brand have been conducted primarily in two areas: marketing and de-sign. Marketing research has focused mainly on the basic concepts (D. A. Aaker,1996, 1997; Davis, 2000; Schmitt, Simonson, & Marcus, 1995; Yeo, 2000), generalstrategies (Campbell, Keller, Mick, & Hoyer, 2003; Keller & Lehmann, 2003;Moorthi, 2004), brand personality dimensions (J. Aaker 1997; Davies, Chun, Silva,Vinhas, & Roper, 2004; Keller, 2003; Y. K. Kim, 2000; Rust et al., 2004), case studies(Breakenridge, 2001; Joachimsthaler, 1999), and cross-cultural influences (J. Aaker,Benet-Martinez, & Garolera, 2001) of brand in general. The few researchers whohave studied brand personalities specifically have generally focused on theoreticalquestions, that is, on working out basic definitions and framing conceptual models(J. Aaker, 1997; Hoeffler & Keller, 2003). Thus, although research in marketingfields has generally presented solid and reliable models of brand personality froma macroscopic perspective, it has not provided specific, concrete guidance on howto build e-brand personalities. In particular, practical research on the visual factorscontributing to e-brand personality is conspicuously thin, considering that Internetusers receive most of their information from visual stimuli (J. W. Kim, 2002). Inother words, there is a large gap between the existing marketing literature on brandpersonality, which is largely theoretical, and the actual needs of Web site designersfor concrete visual design guidelines to build brand personality.

By contrast, research in the design field has taken a microscopic perspective, fo-cusing on the use of individual visual elements in building brand personalities. Forexample, such research for traditional media has generally suggested color, symbolor logo, shape, and layout as important visual elements in printed materials (Bed-ford, 2003; Bevlin, 1997; No & Lim, 1999; Schmitt et al., 1995), television (Hwang,2000), and products themselves (Gardne & Burlegh, 1955; Heskett, 1980;McCormack, Cagan, & Vogel, 2004). Similarly, several studies on the Internet haveemphasized important visual factors from the usability perspective (Hong, Thong,& Tam, 2004; Hoque & Lohse, 1999; Pearson & Schail, 2003; Scott, 1993), the emo-tional perspective (J. Kim, Lee, & Choi, 2003), and the advertising perspective(Dreze & Hussherr, 2003). However, it is hard to find empirical research that sug-gests the importance of visual elements and their attributes for building e-brandpersonality. Only a few books and research papers (Breakenridge, 2001; J. S. Kim,2002; Lindstrom & Andersen, 2000) suggest graphic expressions (e.g., color, icons)as primary elements for embodying e-brand personality on Web sites, but they relyon subjective data and anecdotal experience, rather than on empirical results. Forexample, J. S. Kim’s (2002) study of the role of color in branding suggested using aspecific color for the target brand personality. However, the article, for the mostpart, described the researcher’s subjective impressions, without the support of a

8 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

theoretical framework or empirical data. This omission makes it hard to explainwhy a particular visual element is effective in establishing e-brand personality or,for that matter, how its effectiveness can be applied to other products and services.

To provide practical guidelines for building e-brand personalities, research thatbridges the gap between the macroscopic perspective of marketing and the micro-scopic perspective of design is required. This need was the main rationale for ourresearch, which focuses on the relationship between visual design factors of Websites and e-brand personalities.

In a narrow sense, an e-brand means an online-based brand for companies origi-nally born in cyberspace, such as Yahoo or Amazon (Hue, 2001). E-brand can beconstructed in numerous ways, including electronic mailings, mass-media adver-tisements, and Web sites (Ansari & Mela, 2004; Dayal, Landesberg, & Zeisser, 2000;Lindstrom & Andersen, 2000). Of these diverse methods, this study focuses on Websites for three reasons. First, people tend to spend more time in cyberspace surfingvarious Web sites than engaged in other media-based pastimes. An industry reportindicated that the growth rate of using the Internet is around 23%, which is muchbigger than that in using traditional media such as television and newspapers(Morgan Stanley Dean Witter & Co., 2002). In particular, younger people spend ap-proximately 17 hr a week on the Internet, which is much longer than the time theyspend watching television and listening to radios. Web sites, therefore, are not justa minor medium but have become significant competitors to traditional mass me-dia (Dayal et al., 2000; Lindstrom & Andersen, 2000). Second, Web sites are espe-cially important for the brand personalities of online-based products and services,such as Ebay and WoW. In these instances, consumers conduct their entire con-sumption process on the Web sites, getting information on products, selecting andpurchasing products, and even getting after-sales services. Therefore, for pure on-line companies, Web sites themselves are products and services. Further, the char-acteristics of products and services were found to have substantial impacts onbuilding brand personality (D. A. Aaker, 1996; J. Aaker, 1997; Dayal et al., 2000).Third, two-way communications have been found to be effective in building brandpersonality by allowing customers to actively participate in the brand creation pro-cess (D. A. Aaker, 1996; Holland & Baker, 2001). Web sites have been used to pro-vide individualized two-way communication on the basis of their interactivity andselectivity (Ansari & Mela, 2004; Duncan & Moriarty, 1998; Lindstrom &Andersenm, 2000). Therefore, a Web site is becoming an important tool for buildinge-brand personalities, especially for pure online companies.

Web sites consist of several different components such as content, structure, nav-igation, and representation (J. W. Kim, 2002; Rosenfeld & Morville, 2002). Eventhough all of them may have substantial impacts on the formation of e-brand per-sonalities, this study focuses on visual representation factors for two reasons. First,representational factors have been found to have a more direct and instant effect onuser impressions than navigational or structural factors. Navigational or structuralfactors need to be cognitively processed for a certain time before they are recog-nized by users, whereas representational factors affect users’ impressions almostinstantly (D. A. Norman, 2004; J. Kim et al., 2003). For example, Schenkamn andJonsson (2000) empirically emphasized that the first impression users get from vi-

Visualizing E-Brand Personality 9

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

sual factors of homepages largely determines their image of the owner or company.Second, visual representation is particularly important for Web sites because mostof the content and interactivities are eventually conveyed to the users through vi-sual stimuli. Of course, other modalities, such as sound, touch, and smell are tech-nically feasible for conveying content and functions, but visual representation con-stitutes the vast majority of them for practical and technological reasons. Therefore,the information content and interactive facilities provided to users need to be rep-resented visually on the Web sites, which limits this study to the visual aspects ofWeb sites.

This investigation breaks up the main research question into three smaller ques-tions and undertakes a study for each question in turn. First, there is a need to iden-tify the important dimensions of e-brand personality for diverse Web sites. Eventhough several well-established brand personality frameworks exist for real-worldproducts and services (J. Aaker, 1997; Y. K. Kim, 2000), few dimensions have beenidentified specifically for online products and services. To identify such dimen-sions, the authors collected personality-related adjectives and conducted a prelimi-nary survey study that identified four major dimensions of e-brand personality.The adjectives will be used in the second and third study to link e-brand personal-ity to visual attributes.

Second, there is a need to identify visual design factors associated with thepersonality dimensions identified in the first study. Visual design factors can beanalyzed at several different levels of abstraction. A fairly concrete level analyzesindividual visual elements, such as icons and buttons; a more abstract level fo-cuses on the relationships between individual elements, considering such traitsas balance and contrast. This study analyzes Web sites at the level of “visual at-tributes,” that is, visual composition among elementary visual objects (Bevlin,1997; C. L. Kim, 1996; Lauer, 1985). A more abstract level of analysis was selectedbased on prior studies in Gestalt psychology (Arnheim, 1983; Koffka, 1955) andExploratory Approach theory in perceptual psychology (Pickford, 1972; Scott,1993). Recent studies that applied those theories in the Internet area (Lavie &Tractinsky, 2004; Park, Choi, & Kim, 2004; Pearson et al., 2003) indicate that usersperceive a screen-sized portion of a Web page as a whole, not as a group of indi-vidual elements. To identify visual attributes related to e-brand personality traits,the authors analyzed the visual attributes of 52 diverse home pages and thenconducted an online survey in which participants looked at these pages and re-ported on their perceived personalities.

Finally, the third study was conducted to explore the feasibility of constructingWeb sites for online services that have a relatively strong personality this study istargeting. Four different versions of Web sites were built, one for each of the per-sonality traits identified in the first study. The cascading style sheet (CSS) for eachversion was based on the visual attributes identified in the second study.

All three studies were conducted in Korea with Korean participants. All thestudy materials were written in Korean and were translated into English for this ar-ticle. Korea provided an excellent environment for this study because of its leadingposition in broadband and Internet use. Taken together, these three studies offer aset of detailed empirical results regarding visual-design factors and e-brand per-

10 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

sonalities that have been theoretically grounded. Figure 1 summarizes the overallorganization of the three studies presented in this article.

2. THEORETICAL BACKGROUND

2.1. Brand Personality

Although researchers have studied human personality for almost 100 years, theydo not entirely agree on the definition of personality. One popular definition is“individual differences among various people” (Mischel, 1993, p. 8); many re-searchers have in turn tried to explain the various dimensions of the individualdifference. The dimensions of human personality have been classified differentlyin different models, such as the Big-Five model (W. T. Norman, 1963), theNeuroticism, Extroversion, Openness to Experience Personality Inventory (NEO)model (McCrae & Costa, 1989) and the Adjective Check-List (John, 1990). Thesemodels identify principal attributes of human personality and suggest methodsof measuring them through the use of descriptive adjectives such as “friendly”and “calm” (Lievens, Fruyt, & Dam, 2001; W. T. Norman, 1963). Personality-re-lated adjectives are generally accepted as an effective means of measuring anddescribing human personality (McCrae & Costa, 1997; Piedmont, McCrae, &Costa, 1991).

The attribution of human personality traits to products and services leads to theconstruct of brand personality (D. A. Aaker, 1996; Plummer, 1985). Brand personal-ity is defined as “the set of human characteristics associated with a brand” (J.Aaker, 1997, p. 347). Brand personality cannot be easily imitated, and the unique-ness it projects gives the holding company an economic advantage over its compet-itors (Carpenter, 2000; Y. K. Kim, 2001). Consequently, developing and using brandpersonality is an effective, economical business strategy (D. A. Aaker, 1996; Hue,2001; Hoeffler & Keller, 2003; Keller & Lehmann, 2003).

Visualizing E-Brand Personality 11

FIGURE 1 Overall organization of this article.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

Studies of brand personality have focused on defining, measuring, and con-structing brand personality traits. J. Aaker (1997) identified five dimensions ofbrand personality perceived by Americans: sincerity, excitement, competence, so-phistication, and ruggedness. In further studies, she found some brand personalitytraits that were common across cultures and others that were culturally specific.For instance, a study conducted in Japan has found that Japanese identify “peace-fulness” as a brand-personality dimension but not the “ruggedness” perceived byAmericans (J. Aaker et al., 2001).

A Web site establishes personality through its interactions with users(Breakenrige, 2001; Y. K. Kim, 2000; Lindstrom, 2001). For these interactions, it reliesprimarily on visual components, and so any discussion of a Web site’s “style,” whichSchmitt (1999) suggests is a key to pinpointing a site’s personality, will generally fo-cus on its visual environment and stimuli, as explained in the introduction. Astrongvisual style can exert a strong stimulus on a user’s perceptions. For instance, it hasbeen established that visual images can be key factors in memory and recall mecha-nisms (Kleinbard & Erdelyi, 1978). The predominance of visual stimuli in the onlineenvironment and the demonstrated role of visual stimuli in memory and recall to-gether suggest that an integrated management of visual elements, such as figuresandoverall layout, isessential totheeffectivemanagementofe-brandpersonality.

2.2. Visual Attributes

The concept of visual attributes is drawn from Gestalt theory (Arnheim, 1983;Lupton, 1999). Gestalt means “shape” or “form” in German, and Gestalt theory canbe summarized in the maxim that the whole is greater than the sum of its parts(Arnheim, 1983; Koffka, 1955). In other words, the whole is not merely the sum ofits elements, but an entity with unique characteristics that derive from how thoseelements are arranged. For Gestalt psychologists, the manner in which objects areconstituted is more important than what they consist of (Behrens, 1984; Ellis, 1938;Koffka, 1955).

Gestalt theory is, among other things, a theory of perception (Arnheim, 1983).Gestalt psychologists conceive of visual perception in terms of the composition ofan object—the relationships between its constituent elements—rather than interms of individual characteristics, such as shape or color (Arnheim, 1988). Whenpeople perceive something, say Gestalt psychologists, they perceive a whole, not anumber of individual elements (Arnheim, 1983). In other words, people tend toperceive objects as integrative and compositional objects (Arnheim, 1983; Koffka,1955), and the important factors are in the composition of the visual elements, notin the individual elements themselves. Composition, the manner in which the ele-ments are arranged, is influenced by the qualities of each element; however, differ-ent arrangements of visual elements are possible, and two different arrangementsof identical elements will induce substantially different perceptions in viewers(Arnheim, 1988).

Studies have already proposed various visual elements as factors in e-brandpersonality (Ansari & Mela, 2004; Dayal et al., 2000; Y. K. Kim, 2000, 2001;

12 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

Lindstrom & Andersen, 2000). Most studies, however, have been conducted onthe basis of individual elements, such as color, shape, layout, and Web site logos(J. S. Kim, 2002; Y. K. Kim, 2001). Gestalt theory suggests, instead, that visualstimuli should be analyzed as unified wholes, focusing on the compositional re-lationships among individual elements. A similar argument can be made basedon the Exploratory Approach theory in perceptual psychology (Pickford, 1972),which is later applied to Web environments (Lavie & Tractinsky, 2004; Pearson &Schail, 2003). According to the studies, before people experience the interactivityof Web sites by clicking certain objects, they conduct a visual search process thatincludes two subphases (Pearson & Schail, 2003). In the first subphase, all visualelements of the entire page are processed in a parallel pattern without paying at-tention to any specific items. Only when conspicuous items are found in the firstsubphase, will enough attention be focused on the items in the second phase.Therefore, people perceive the overall composition of interactive Web pages. Thisis why several studies have focused on the overall visual impression in Web en-vironments. For example, Schenkamn and Jonsson (2000) found that Web usersconstructed their first impression based on the overall visual composition ofhomepages. Similarly, Lavie and Tractinsky (2004) developed a scale to measurethe overall aesthetic quality of Web pages based on visual factors. Therefore, thisstudy analyzed Web pages on the basis of visual attributes; that is, the overallcomposition of individual elements. A further advantage is that related studies(Ngo & Byrne, 2001; Park et al., 2004) have developed algorithms that allow nu-merical measurement of the visual attributes. Finally, this approach has practicalmerits in that the results will be easy for designers to understand and to apply toWeb page design. Most designers invoke the same visual attributes, for instance,balance, rhythm, unity, and contrast, to explain or evaluate their design work(Kim, 1996; Ngo & Byrne, 2000).

The visual attributes model also has been described in terms of visual composi-tion and design formation, (C. L. Kim, 1996; Ngo & Byrne, 2000), but the basic con-cepts are similar in that they all focus on the compositional relationships among in-dividual elements (J. S. Kim, 2002; Lauer, 1985). A review of relevant studies in thefield of visual design yields 11 distinct visual attributes (Arnheim, 1983;Constaintine, 1999; C. L. Kim, 1996; Lauer, 1985; Ngo & Byrne, 2000, 2001; Wong,1987). Table 1 describes each visual attribute in detail. The first column indicatesthe name of the attribute. The second column provides a schematic example of theattribute, depicting a graphic layout that has a high numeric value for the attribute.The third column defines the attribute and describes its determining factors. Forexample, balance is defined as the distribution of visual weight across the wholepicture; it is maximized when the visual weights of elements on the right and leftside, or in the upper and lower regions, are equal.

3. STUDY 1: IDENTIFYING E-BRAND PERSONALITY DIMENSIONS

The main goal of the first study was to identify e-brand personality dimensions rel-evant to Web sites. This goal was achieved in three consecutive stages.

Visualizing E-Brand Personality 13

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

14

Table 1: Definitions of Visual Attributes

Visual Attribute

Schematic Depiction ofAttribute at a High

Numeric ValueDescription

(A. Definition, B. Determining Factors)

1. Balance A. Balance is the distribution of visualweight across the whole picture (Behrens,1984; C. L. Kim, 1996; Lauer, 1985; Ngo &Byrne, 2001). Visual weight is influencedmainly by the sizes, colors, and locationsof objects (Ngo & Byrne, 2001; Wong,1987).B. The numeric value of balance ismaximized when the visual weights ofelements on the right and left sides or inthe upper and lower regions on a screenare equal.

2. Symmetry A. Symmetry is the mirroring of the visualcomposition across a vertical or horizontalpivot line (Ngo & Byrne, 2001).B. The numeric value of symmetry is higherwhen objects of the same color and size aremirrored across a vertical or horizontal axis(Lauer, 1985; Ngo & Byrne, 2001).

3. Movement A. Movement is the tendency of the eyes tomove from the upper left to the lower rightof the picture (Ngo & Byrne, 2000; Dillon,1992).B. The numeric value of movement isaffected by visual contrast in the sizes,colors, and shapes of objects (Constaintine,1999).

4. Rhythm A. Rhythm is the flow of the compositionthrough a pattern of identical or similarobjects (Lauer, 1985; Wong, 1987).B. The numeric value of rhythm isdetermined by repetition of, or regularityin, the sizes, colors, or locations of objects(Bevlin, 1997; C. L. Kim, 1996; Ngo & Byrne,2001).

5. Contrast A. Contrast is the degree of differencebetween elements (Wong, 1987).B. The numeric value of contrast isdetermined by the degree of differenceamong objects in size, color, and location(Wong, 1987).

(Continued on next page)

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

15

Table 1 (Continued)

Visual Attribute

Schematic Depiction ofAttribute at a High

Numeric ValueDescription

(A. Definition, B. Determining Factors)

6. Proportion A. Proportion is the ratio of an object’sheight to its width (Bevlin, 1997; Ngo &Byrne, 2001).B. The numeric value of proportionincreases as the ratio of width to heightapproaches 1:1 (square), 1:1.414 (square rootof two), 1:1.618 (golden rectangle), or 1:2(double square).

7. Unity A. Unity is a visual association of objectsthat leads them to be perceived as a singleentity (Lauer, 1985).B. The numeric value of unity is determinedby the repetition of objects identical orsimilar in size or color, as well as by theproximity between objects (C. L. Kim, 1996;Ngo & Byrne, 2001).

8. Simplicity A. Simplicity is the clarity projected by apicture (Arnheim, 1983; Ngo & Byrne, 2000).B. The numeric value of simplicity is affectedby the number of objects in the compositionand by the variety in their sizes, colors, andshapes (Ngo & Byrne, 2001).

9. Density A. Density is the ratio between the area ofthe background (i.e. the area not covered byobjects) and the area covered by objects(Behrens, 1984; Koffka, 1955; Ngo & Byrne,2001).B. The numeric value of density increases asthe sum of the areas of the objects rises andthe area of the background diminishes (Ngo& Byrne, 2001).

10. Regularity A. Regularity is the visual consistencyamong objects (Ngo &Byrne, 2001).B. The numeric value of regularity isaffected by the consistency objects show inlocation, size, and color (Ngo & Byrne,2001).

11. Cohesion A. Cohesion is the degree to which objectshave the same width-to-height ratio (Ngo &Byrne, 2001).B. The numeric value of cohesion rises asthe width-to-height ratios of objects becomecloser (Ngo & Byrne, 2001).

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

3.1. Collection of Personality Adjectives

In the first stage of Study 1, basic personality adjectives were collected from thepsychology, design, and marketing literatures, as well as from a small-scale sur-vey. Two hundred and four adjectives were collected from personality modelsused by psychologists, including the original Big-Five Model (W. T. Norman,1963), the NEO model (McCrae & Costa, 1989), the Big-Five Prototypes (John,1990), the Adjective Check List model (Piedmont et al., 1991) and theInter-Circumplex Model (McCrae & Costa, 1989). An additional 30 adjectiveswere drawn from recent research (J. Kim et al., 2003) that studied aesthetic evalu-ation of various homepages. Finally, to derive further personality adjectives, asmall-scale survey was conducted that used a free-association process. Sixty-twoparticipants in their 20s and 30s were asked what personality traits came to mindwhen they viewed several homepages; 645 personality adjectives were collectedthis way. Pooling results from the three sources produced a total of 879 personal-ity adjectives. Once identical adjectives were eliminated, 747 personality adjec-tives remained.

3.2. Evaluation of Appropriateness

In the second stage, the relevance of adjectives was evaluated in six steps. First, theauthors established general criteria (e.g., delete any adjective whose meaning isambiguous). Second, 11 experts—three psychologists, three cognitive scientists,two linguists, one professional Web designer, and two Web planners—gathered todiscuss and define the scope of the proposed criteria. For example, for the criteriondelete adjectives whose meaning is ambiguous, they defined the scope of ambiguousadjectives as those for which the primary dictionary definitions differed from thecommon definitions in daily use. Third, each expert individually responded to asurvey on the relevance of e-brand personalities based on the established criteria.The survey consisted of the 747 adjectives on a 7-point Likert scale. Fourth, the ex-pert group gathered together and evaluated the 747 adjectives one by one, based onthe result of the surveys. Group members evaluated each adjective for its linguisticrelevance as a personality adjective. In cases in which experts did not agree on thelinguistic relevance of adjectives, the results were reconciled through group discus-sions among the linguists, psychologists, and cognitive scientists. Fifth, the expertgroup evaluated the adjectives that fulfilled the linguistic criteria again in terms oftheir relevance in describing e-brand personalities of Web sites. For example, emo-tional adjectives (e.g., sad) not appropriate for describing Web site characteristicswere deleted. When experts did not agree on the relevance of adjectives, the resultswere reconciled by group discussion between the Web designer and Web planners.Finally, after evaluating all 747 adjectives and modifying the criteria, experts veri-fied each of the adjectives again, one by one, based on the criteria that had beenmodified throughout the discussion, which are shown in Table 2. In the end, 190personality adjectives were selected. The entire study was conducted in the Koreanlanguage.

16 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

3.3. Survey

In the third stage, a survey was conducted to identify major dimensions of e-brandpersonality. A total of 470 respondents participated in the survey; 399 of them werein their 20s, the rest were in their 30s. There were equal numbers of men andwomen. Each participant was asked to choose a Web site that came instantly tomind and to describe the e-brand personality of that site in terms of 190 adjectivesset up on 7-point Likert scales.

To analyze associations among adjectives, a hierarchical cluster analysis and ex-ploratory factor analysis with varimax rotation was conducted. Factors consistingof only one adjective were deleted because they could not meet the reliability andvalidity criteria of factor analysis. Those adjectives that have a factor loading lowerthan other similar adjectives were deleted to increase reliability and to facilitate thesurvey process. These practices are consistent with a common procedure that hasbeen exploited to select important features in related studies (J. Aaker, 1997; Y. K.Kim, 2001). Analysis yielded four e-brand personality factors and 19 personalityadjectives (Table 3). The first personality dimension, bold, consisted of the adjec-tives gaudy, sexy, frivolous, arbitrary, bold, and show-offy. The second dimension,analytical, consisted of analytical, objective, accurate, detailed, and realistic. Thethird dimension, friendly, consisted of ingenuous, warm, gentle, and friendly. Thefourth dimension, sophisticated, consisted of sophisticated, liberal, luxurious, andfuturistic. Eigen values of each of the four dimensions exceed 1.00, and the cumula-tive percentage of explained variance reached 52.67. The Cronbach alpha coeffi-cients of all dimensions were higher than 0.7 (i.e., within acceptable ranges).

In summary, the first study identified four dimensions of e-brand personality,with 19 personality adjectives, and found them to be valid and reliable. Thus, theywere ready for use in the second study, which attempted to identify important vi-sual attributes for the four personality dimensions.

4. STUDY 2: IDENTIFYING KEY VISUAL ATTRIBUTES

In the second phase, an exploratory study was conducted to identify visual attrib-utes associated with the four dimensions of e-brand personality.

Visualizing E-Brand Personality 17

Table 2: Criteria for Evaluating Personality Adjectives

Criterion Examples

Deletion Delete adjectives inappropriate for representing e-brandpersonalities.

beautiful, practical

Delete negative adjectives, when positive adjectiveswith the same meaning are available.

not diligent → diligent

Delete any adjective whose meaning is ambiguous. like guidesDelete adjectives when more frequently used synonyms

are available.mild, gentle → gentle

Alteration Change negative words to positive words. unstable → stableReframe subjective adjectives in objective terms. seems intelligent → intelligent

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

4.1. Measurement of Visual Attributes

This study used 52 homepages produced by 32 professional Web designers in ex-perimental environments (see Figure 2). Request forms for Web-page developmentwere given to the professional designers. All request forms had exactly the samecontents written in Korean. These included personal profiles, menu structures, andnavigations, except for adjectives expressing the visual appearance (e.g., calm,tidy). Each of the designers produced two or three homepages with different visualappearances according to their graphic design style and expertise. Therefore, the 52homepages had the same content, with a wide variety of visual appearances, which

18 Park, Choi, Kim

Table 3: Results of Exploratory Factor Analysis (EFA)

Personality Dimension Adjectives Factor 1 Factor 2 Factor 3 Factor 4

Bold Gaudy 0.80Sexy 0.79Frivolous 0.75Arbitrary 0.66Bold 0.65Show-offy 0.55

Analytical Analytical 0.78Objective 0.70Accurate 0.68Detailed 0.62Realistic 0.53

Friendly Ingenuous 0.81Warm 0.79Gentle 0.66Friendly 0.65

Sophisticated Sophisticated 0.72Liberal 0.67Luxurious 0.67Futuristic 0.61

% of Variance 29.63 29.63 13.37 8.87Cumulative % 29.63 29.60 43.33 52.67Eigen values 5.63 5.33 2.47 1.68Cronbach Alpha 0.82 0.82 0.77 0.77

FIGURE 2 Examples of home pages produced for study purposes.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

provided a good stimulus to explore the visual appearances of Web sites while con-trolling for other design factors, such as content and interactivities.

Arriving at numerical values for the 11 visual attributes for each of the 52homepages took three complex phases. In the first phase, following the principlesof Gestalt psychology (Arnheim, 1983; Behrens, 1984; Ellis, 1938; Koffka, 1955), ac-cording to which the obvious area in a visual field is the “figure,” the ambiguousarea is the “ground” (Koffka, 1955), each homepage was divided into figure andbackground. Areas without specificity were defined as background, and all othercomponents were defined as the figure. Next, all figures were organized into clus-ters, according to the four principles of visual organization described by Gestaltpsychologists (Arnheim, 1983; Bevlin, 1997; Ellis, 1938; Koffka, 1955; Lupton, 1999):proximity, similarity, continuity, and closure (Arnheim, 1983; Koffka, 1955; Lupton,1999). The principle of proximity means that elements close to each other are per-ceived to associate together. The principle of similarity means that elements that re-semble each other in terms of color, size, or texture are perceived to associate to-gether (Koffka, 1955). For example, on the basis of similarity, most menus on Webpages were organized as single objects, because each menu element was of similarshape and color. The principle of continuity is based on the idea that people preferto perceive smooth, continuous contours, rather than sudden changes in direction(Koffka, 1955; Lupton, 1999). According to the principle of closure, people tend tointerpret elements as being complete rather than incomplete (Ellis, 1938). There-fore, incomplete figures are considered as complete in people’s minds.

Figure 3 shows the process of identifying figures and background for 1 of the 52homepages using the four Gestalt principles described here. The homepage wasfoundtohavefourfiguresandalargebackground.Thissameprocesswasconductedfor each of the 52 homepages, during which 1,572 visual objects were identified.

In the second phase, numeric values were given to the color, size, and location ofeach of the 1,572 objects (C. L. Kim, 1996). For color, using PhotoShop 7.0, the red,green, and blue values of each object were measured and then the values were recastin terms of brightness, saturation, and hue, normalizing the three values between 0and 1. The size of each object was measured in pixel units. The location of each objectwas measured as the x point and y point of the pixel in the upper-left corner. Table 4shows the measured values of color, size, and location for the sample in Figure 3.

Visualizing E-Brand Personality 19

FIGURE 3 Example of the measurement process.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

In the third phase, the 11 visual attributes of the 52 homepages were calculatedusing algorithms proposed by Ngo and Byrne (2000) and extended by Park et al.(2004). The input values were the numeric measures for color, size, and location foreach object. These 11 visual attributes are affected by the consistency, variation, andregularity of the numeric values for color, size, and location. For example, the nu-meric value of balance is calculated as the distribution of visual weight, which isdetermined by the sizes and colors of the objects in the visual field. Thus, to arriveat a measure for balance, the visual weight of objects was first calculated in eachquadrant of the screen—upper-right, upper-left, lower-right, and lower-left—andthen the distribution of visual weight was determined on the basis of these four nu-meric values. Table 5 shows the numeric values of the 11 visual attributes of thehomepage depicted in Figure 3.

4.2. Survey and Analysis

An online survey was conducted to analyze the relation between visual attributesand e-brand personality. A total of 8,184 Web users participated. They were in their20s and 30s; 60% were men and 40% were women. They were asked how they per-ceived the personalities of the 52 homepages in terms of the 19 e-brand personalityadjectives identified in the first study.

20 Park, Choi, Kim

Table 4: Numeric Values of Color, Size, And Location For The Sample inFigure 3

Location Size Color

Object X Point Y Point Width Height Size Hue Saturation Brightness

O1 152 32 192 75 3208 0.15 0.30 0.92O2 0 0 571 33 18272 0.60 0.58 0.41O3 568 32 4 403 1208 0.23 0.08 0.68O4 0 402 569 33 18379 0.16 0.01 0.84

Table 5: Numerical Values of Visual Attributesfor the Home Page Shown in Figure 3

Visual Attribute Numerical Value

Balance 0.35Symmetry 0.49Movement 0.00Contrast 0.48Unity 0.33Proportion 0.92Simplicity 0.05Density 0.04Regularity 0.50Rhythm 0.18Cohesion 0.70

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

A factor analysis was conducted on the survey results to confirm the e-brandpersonality dimensions identified in the first study. The 19 adjectives were groupedinto their four personality dimensions. Eigen values of each of the four dimensionsexceeded 1.00 (bold = 6.55, analytical = 1.59, friendly = 2.40, sophisticated = 1.11)and the cumulative percentage of explained variance reached 61.29. Cronbachalphas for all dimensions were within an acceptable range (bold = 0.85, analytical =0.78, friendly = 0.80, sophisticated = 0.76). The analysis showed that the personalitydimensions in the second study were identical with those found in the first study.

Finally, a stepwise multiple regression analysis was conducted for each of thefour personality dimensions. The dependent variables were the factor scores forthe four personality dimensions in the survey, and the independent variables foreach personality dimension were the 11 visual attributes.

4.3. Results

Results fromthefourregressionanalysesaresummarizedinTable6.All fourperson-alitydimensionswerefoundtocorrelatecloselywithat least twovisualattributes.

Regression analysis indicated that 2 of the 11 visual attributes, simplicity and co-hesion, were closely related to the bold personality type. Simplicity correlated neg-atively with the bold type; cohesion correlated positively. The implication is thatusers will find a Web page exhibiting a bold personality if it has a high number ofobjects irregularly placed (lacking simplicity) but proportionate in terms of widthand height (showing cohesion).

Visualizing E-Brand Personality 21

Table 6: Results of Regression Analysis

PersonalityDimension

StandardizedCoefficients Beta t Sig.

AdjustedR2 F

P1: Bold (Constant) –4.05 0.000 0.345 9.79 (p < .05)Simplicity –0.340 –2.97 0.005Cohesion 0.484 4.23 0.000

P2: Analytical (Constant) –5.19 0.000 0.440 12.30 (p < .05)Contrast 0.443 3.99 0.000Simplicity 0.359 3.24 0.002Density 0.302 2.71 0.009

P3: Friendly (Constant) 4.32 0.000 0.370 6.87 (p < .05)Contrast –0.307 –2.64 0.011Density –0.268 –2.31 0.026Regularity –0.351 –3.01 0.004Cohesion –0.455 –3.83 0.000

P4: Sophisticated (Constant) –3.21 0.002 0.321 6.92 (p < .05)Balance 0.524 3.52 0.001Regularity 0.388 3.26 0.002

Note. Regression equations: Bold = –0.34 * simplicity + 0.484 * cohesion. Analytical = 0.443 * contrast +0.302 * density + 0.359 * simplicity. Friendly = –0.307 * contrast –0.268 * density –0.351 * regularity –0.455 * co-hesion. Sophisticated = 0.542 * balance + 0.388 * regularity.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

Three visual attributes, density, simplicity, and contrast, correlate positivelywith the analytical personality type. In other words, users tend to find a Web siteanalytical when there is relatively little empty background, when there are rela-tively few distinct objects, and when those objects contrast sharply in size andcolor.

The friendly personality dimension correlates negatively with contrast, density,regularity, and cohesion. Thus, a friendly personality type is established by a simi-larity of size, color, and location among objects; by a relatively large amount ofbackground space; by a relative lack of proportion between objects in terms ofwidth and height; and by a generally irregular placement of objects.

Finally, the sophisticated personality dimension correlates positively with thevisual attributes of regularity and balance. Users will find a Web site sophisticatedwhen figures are placed on the screen in a consistent manner and when the visualweights of objects are distributed evenly across the screen.

In sum, all four regression equations were found to be statistically significant.For each personality dimension, at least two visual attributes were found to beclosely related. However, although this second study found clear correlations be-tween visual attributes and personality dimensions for homepages, it had not yetbeen established whether the identified visual attributes could actually increasethe personality dimensions of Web sites.

5. STUDY 3: FEASIBILITY OF CONSTRUCTING TARGET PERSONALITIESFOR ONLINE SERVICE WEB SITES

The second study found four regression equations that related between the fourpersonality dimensions and 11 visual attributes. However, there are two importantlimitations in the second study. First, the second study exploited personalhomepages as stimuli because this research focused on visual aspects and not onthe informative nature of content. However, human personality, as mediated by apersonal homepage, might be different from e-brand personality of online prod-ucts and services. Therefore, we should explore whether the relations that wereidentified with a single page of personal homepages in the second study can be ap-plied to Web sites for online products and services. To do this, Web sites were con-structed for four different online services in the third study. Second, prior studies inindividual differences of human personalities clearly indicate that people perceivepersonalities from a relative perspective, rather than from an absolute perspective(Buss, 1999; MacIntyre, 1984; McAdams, 1995, 1994). For example, McAdams(1995) argued that human beings can be characterized not only by their absolutevalues on personality traits but also by their relative contextual characteristics (e.g.,standing compared to other persons), wherein the latter factor is more important indetermining human personality. In other words, for a person to be perceived asbold, he or she needs to be bolder than other people around him or her. The sameprinciple of relativity should be applied to e-brand personality because it was orig-inally based on human personality in theory (J. Aaker, 1997). Therefore, for a Website to be considered analytical, its analytical personality should be stronger thanother Web sites’ analytical personality, and its other personalities (e.g., bold)

22 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

should be weaker than other Web sites’ target personalities. However, the resultsfrom the second study focused on the absolute value of four e-brand personalitiestreating each personality independently. This would have been acceptable if eachpersonality was completely independent from others. However, the results in thesecond study showed that a visual attribute is related to more than one personality(e.g., the simplicity attribute to both bold and analytical personalities). Therefore,the second study cannot establish whether a Web site can be constructed to have atarget personality from the relative comparison perspective.

In summary, the third study was conducted to explore the feasibility of con-structing Web sites with relative target personalities for online services based onthe regression equations from the second study.

5.1. Study Materials

In the first study, the research results identified four dimensions of e-brand personal-ity. In the second study, research results found visual attributes that were closely as-sociated with each personality dimension. Drawing from the results of the first twostudies, fourWebsitestylesweredeveloped,oneforeachpersonalitydimension.Be-cause the relationships between personalities and visual attributes might be affectedby the nature of the Web site domain, Web sites in four different domains were builtfor each personality type: a search portal site, an online game site, a matchmakingsite, and a photo gallery site. The four kinds of online services were selected becausetheywerepopular inKoreaat thetimeofthestudy.Theyalsoprovidedawidevarietyof Web sites: an online games site and a matchmaking site for hedonistic Web sites,andasearchportal siteandaphotogallerysite forutilitarianWebsites (Hirschman&Holbrook, 1982; Hofacker, 2000; Vogt & Fesenmaier, 1998). Therefore, a total of 16Web sites (four personality dimensions for each of four site domains) were con-structedasstudystimuli.AsamplepagefromeachWebsite ispresentedinFigure4.

Constructing the 16 Web sites involved several complex steps. First, for each ofthe four personality dimensions, a prototype CSS was designed. These style sheetswere based on the regression equations in Table 6. CSS1 (bold) minimized simplic-ity by incorporating as many objects of different color and size as possible and byplacing them at irregular locations; to achieve a high cohesion, this style sheet alsoused objects with similar width-to-height ratios. CSS2 (analytical) used objects thatcontrasted sharply in colors and size, and devoted relatively little space to back-ground. At the same time, it used relatively few figures to maximize simplicity.CSS3 (friendly) minimized the contrast between figures in terms of size and colorand varied the objects’ width-height ratios; the area devoted to objects was mini-mized compared with the area of the remaining background, and objects wereplaced in random and irregular locations. CSS4 (sophisticated) maximized balanceby making objects similar in terms of location, size, color, and regularity by placingthe objects in consistent locations.

Second, for the purpose of verification, the numerical values of the expected tar-get personalities for each CSS was calculated using the same algorithm used in thesecond study. If the target personalities for a given CSS were lower than those forother CSSs, the visual attributes were adjusted and the target personality was mea-

Visualizing E-Brand Personality 23

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

sured again. At the end of the procedure, there were four algorithmically verifiedcascading style sheets, one for each of the four dimensions. A sample page fromeach Web site is shown in Figure 4.

The following is an explanation of the four CSSs in terms of their target personal-ities. First, according to the regression equations in Table 6, the value for the boldpersonality will be maximized (0.484) when simplicity is 0 and cohesion is 1. CSS1showed a simplicity score of 0.46 and cohesion score of 0.704, yielding a bold per-sonality value of 0.325. This value is higher than the bold personality values forCSS2 (0.188), CSS3 (0.314), and CSS4 (0.319). Second, the analytical dimension willbe maximized (1.104) when contrast, density, and simplicity are all 1. Contrast,density, and simplicity scores for CSS2 are 0.610, 0.923, and 0.46, respectively, yield-ing an analytical personality value of 0.715. This value is higher than the analyticalvalues for CSS1 (0.591), CSS3 (0.442), and CSS4 (0.555). Third, the friendly person-ality will be maximized (0.00) when contrast, density, regularity, and cohesion areall 0. (Note that the coefficients of the regression equation for the friendly personal-ity are all negatives.) Contrast, cohesion, density, and regularity scores for CSS3 are0.722, 0.695, 0.328, and 0.30 respectively, yielding a friendly personality value of–0.731. This value is higher than the friendly personality values for CSS1 (–0.910),CSS2 (–0.949), and CSS4 (–0.896). Finally, the sophisticated dimension is maxi-mized (0.930) when regularity and balance are 1. The regularity and balance scoresfor CSS4 were 0.466 and 0.753, yielding a sophisticated value of 0.589. This value ishigher than the sophisticated values for CSS1 (0.551), CSS2 (0.210), and CSS3(0.561).

Table 7 shows the numerical values for the visual attributes and expected targetpersonalities of each CSS. In each case, the CSS scores are higher for its targetedpersonality dimension than any other CSS. However, because each CSS had to notonly maximize the targeted dimension but also minimize the other dimensions, thefour personality dimensions could not be actually maximized.

Finally, each CSS was applied to the four aforementioned Web sites in four do-mains. Thus, for each personality dimension, four Web sites were developed, usinga single CSS: one for the search portal site, one for the online game site, one for thematchmaking site, and finally one for the photo gallery site. As evident from Figure4, the four sites for a given target personality look almost the same, because thesame CSS was applied to them. Each Web site consisted of approximately 20 sam-ple Web pages—enough for participants to conduct simple tasks.

5.2. Procedure

An online study was conducted to explore the feasibility of constructing Web siteswith relatively high target personalities for online service Web sites. Participantswere recruited by means of banner advertisements at major Internet portals in Ko-rea and were offered monetary compensation. A total of 740 people participated inthe study. Seventy percent were men, and 30% were women; all were in their 20sand 30s. They were randomly distributed among the 16 Web sites. Table 8 presentsthe numbers of people allocated to each site.

24 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

25 FIGURE 4 Final designs of Web pages for the 16 experimental sites.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

In the third study, participants were asked to visit their assigned Web site andcomplete a simple task. For example, one task on the search portal site was to findthe score of an Olympic soccer game. Afterward, participants answered questionsabout the e-brand personalities of their assigned Web sites, rating the 19 personal-ity adjectives drawn from the first study on a 7-point Likert scale.

26 Park, Choi, Kim

Table 8: Numbers of Participants for Each Web Site

Stimulus

Site Category CSS1 CSS2 CSS3 CSS4

Search portal site 56 48 44 40Online game site 52 44 52 43Match-making site 51 39 48 45Photo gallery site 51 47 41 39Total 210 178 185 167

Note. CSS = cascading style sheet.

Table 7: Numerical Values of Experimental Stimuli

TP Stimulus Significant Visual AttributesNumericalValue of TP Max Min

Bold Simplicity Cohesion 0.484 –0.340

CSS1 0.046 0.704 0.325CSS4 0.067 0.706 0.319CSS3 0.065 0.695 0.314CSS2 0.462 0.712 0.188

Analytical Contrast Density Simplicity 1.104 0.00

CSS2 0.610 0.923 0.462 0.715CSS1 0.696 0.881 0.046 0.591CSS4 0.696 0.739 0.067 0.555CSS3 0.722 0.328 0.065 0.442

Friendly Contrast Cohesion Density Regularity 0.00 –1.381

CSS3 0.722 0.695 0.328 0.301 –0.731CSS4 0.696 0.706 0.739 0.466 –0.896CSS1 0.696 0.704 0.881 0.399 –0.910CSS2 0.610 0.712 0.923 0.542 –0.949

Sophisticated Regularity Balance 0.93 0.00

CSS4 0.466 0.753 0.589CSS3 0.301 0.821 0.561CSS1 0.399 0.731 0.551CSS2 0.542 0.000 0.210

Note. TP = target personality; CSS = cascading style sheet. Regression equations: Bold = –0.34 * simplicity+ 0.484 * cohesion. Analytical = 0.443 * contrast + 0.302 * density + 0.359 * simplicity. Friendly = –0.307 * contrast–0.268 * density –0.351 * regularity –0.455 * cohesion. Sophisticated = 0.542 * balance + 0.388 * regularity.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

5.3. Data Analysis

Data analysis for the third study was conducted in two stages. First, a confirmatoryfactor analysis was conducted to test the reliability and validity of the personalitydimensions. Second, an analysis of variance (ANOVA) with contrast among thefour groups of CSSs was conducted to find whether the Web sites were perceived tohave relatively high target personalities.

Table 9 presents the results of the confirmatory factor analysis. The 19 personalityadjectives are found to converge nicely into the four personality dimensions. More-over, Goodness of Fit Index, Adjusted Goodness of Fit Index, and Normed Fit Indexare all higher than the cutoff point of 0.9. Root Mean Square Residual and Root MeanSquare Error of Approximation are also around 0.05, which is within the acceptablerange. These results confirm that the measurement model—four personality dimen-sions with 19 questions—was valid. Finally, Cronbach’s alpha coefficients for thefour factors were also higher than 0.7, implying that the four personality dimensionsare reliable constructs.

Before combining data from the four different types of online services, the datawere tested to determine whether there were any differences in terms of person-ality dimensions among the different service types. It was found that none of thefour e-brand personalities was statistically significantly different among the four

Visualizing E-Brand Personality 27

Table 9: Results of Confirmatory Factor Analysis

Factor Adjective Factor 1 Factor 2 Factor 3 Factor 4

P1 Bold Show-offy 16.16**Arbitrary 9.72**Sexy 28.91**Gaudy 30.82**Frivolous 15.86**Bold 27.15**

P2 Analytical Objective 11.38**Detailed 17.42**Analytical 16.65**Accurate 18.91**Realistic 21.04**

P3 Friendly Ingenuous 14.11**Warm 18.65**Gentle 20.59**Friendly 22.84**

P4 Sophisticated Luxurious 21.38**Futuristic 21.62**Sophisticated 25.61**Liberal 15.50**

Cronbach alpha 0.79 0.81 0.77 0.72

Model χ2 df GFI AGFI NFI NNFI RMR RMSEA163.43 56 0.98 0.92 0.99 0.98 0.05 0.051

Note. **p < .01. GFI = goodness of fit index; AGFI = adjusted GFI; NFI = normed fit index; RMR = rootmean square residual; RMSEA = root mean square error of approximation.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

types of online services. This might be because the CSS had been applied ratherstrictly for the Web sites, as shown in Figure 4, which minimizes the possible dif-ferentiation from the four types of online services. Therefore, survey data fromthe four different types of online services were combined for further analysis bycalculating the average personality values for the four Web sites that used thesame cascading style sheet. For example, the mean value of CSS1, which was de-signed to maximize the bold personality, was calculated by averaging the re-sponses of the 56 participants assigned to the search portal version of CSS1, the52 participants assigned to the online game version of CSS1, the 51 participantsassigned to the matchmaking version, and the 51 participants assigned to thephoto gallery version. The same calculation was made for the other three stylesheets.

For each style sheet, the mean value of the target personality dimension wascompared with the mean values the other three style sheets showed for that samedimension. For example, we compared the bold personality value of CSS1 with theaverage of the bold personality values of CSS2, CSS3, and CSS4. The same calcula-tion was made for the personality values of the analytical, friendly, and sophisti-cated style sheets.

5.4. Results

Table 10 shows the results of ANOVA tests with contrast for each of the four per-sonality dimensions. The second column presents the mean values of personalityaccording to the study stimuli (CSS1, CSS2, CSS3, CSS4), and the following col-umns show the value of contrast, degrees of freedom, and statistical significance.

The results indicate that Web sites could actually be built with relatively high tar-get personalities for bold, analytical, and friendly. In these three cases, the CSS thatwas designed to increase the target personality dimension did, in fact, provide a rela-tively high target personality value. In other words, the mean value of the bold per-sonality of CSS1 (2.84) is statistically higher than the average of the bold personalityof CSS2, CSS3, and CSS4 (χ2 = 0.529, df = 650, p = 0.032 < 0.05). The same was found forthe analytical personality of CSS2 (3.68) and the friendly personality of CSS3 (3.68).However, contrary to expectation, the mean value of the sophisticated personality

28 Park, Choi, Kim

Table 10: Results of Contrast Test (ANOVA)

PersonalityDimension

MeanValue ofContrast

StatisticalSignifigance

(2-Tailed)CSS1 CSS2 CSS3 CSS4 df

Bold 2.84 2.57 2.71 2.70 0.529 650 0.032Analytical 3.53 3.79 3.74 3.44 0.655 650 0.011Friendly 3.53 3.65 3.68 3.28 0.576 650 0.040Sophisticated 2.89 2.96 3.14 2.78 –0.631 650 0.028

Note. ANOVA = analysis of variance; CSS = cascading style sheet. Boldface = M value of targetstimulus, which was designed to maximize each personality dimension.

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

dimension of CSS4 (2.78) was lower than those of the other stimuli (CSS1 = 2.89, CSS2= 2.96, CSS3 = 3.14). These results are all statistically significant (p < 0.05).

6. CONCLUSIONS AND DISCUSSION

The main goals of this research were to explore the relationship between the visualattributes of Web sites and their e-brand personalities and to offer concrete guide-lines for shaping e-brand personalities in Web site design. The research consisted ofthree consecutive studies: the first study to define basic e-brand personality dimen-sions; the second study to identify important visual attributes associated with eachof the e-brand personality dimensions found in the first; and, finally, the thirdstudy to explore the feasibility of constructing Web sites with relatively high targetpersonalities.

In the first study, four e-brand personality dimensions were identified, namely,bold, analytical, friendly, and sophisticated. In the second study, numeric valuesfor 11 visual attributes were determined in 52 representative Web pages, and a sur-vey in which respondents assessed the personalities of those Web pages was con-ducted. Regression analysis using visual attributes as independent variables andpersonality traits as dependent variables found the following correlations:

• theboldpersonality isrelatedtothevisualattributesofsimplicityandcohesion• the analytical personality is associated with the attributes of contrast, density,

and simplicity• the friendly personality is related to contrast, cohesion, density, and regularity• the sophisticated personality is associated with regularity and balance.

The third study was conducted to explore the feasibility of constructing Web sitesfor online services with relatively high target personalities. On the basis of the re-gression equations from the second study, four styles of Web site (CSS1, CSS2,CSS3, and CSS4) were constructed as study stimuli. An online survey was con-ducted to determine how people perceived the e-brand personalities of the devel-oped sites. The Web sites that had been designed to assert bold, analytical, andfriendly personalities were successful in making the participants perceive the tar-get personalities higher than those from other Web sites that were expected to havedifferent target personalities. However, the Web sites that had been designed to as-sert the sophisticated personality did not achieve that goal.

Why did the sophisticated Web sites fail to strike participants as sophisticated?Onepossiblereasonis thesmalldifferencebetweenCSS4andtheotherstylesheets interms of sophistication measures. As shown in Table 7, the numeric value for sophis-ticatedpersonalitydimensionforCSS4(0.589) is thehighestof thefour.However, thevalues for sophisticated personality dimension for CSS2 and CSS3 are also high(0.561 and 0.551, respectively). A broader difference could not be achieved in thisstudy because of the requirement that within each style sheet, the target personalityshould be maximized and the other personalities simultaneously minimized.

Visualizing E-Brand Personality 29

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

This requirement is one limitation of this study. This research cannot verify thecausal relations between individual visual attributes and personality dimensions.Given that this research has explored the overall feasibility of manipulating visualattributes in online service Web sites, a future study should be conducted to test thecausal relations in more detail. To do this, experimental Web sites need to be con-structed that manipulate only one visual attribute at a time, and a series of experi-ments to identify the impact of the visual attribute to the four personality dimen-sions should be conducted.

The second limitation is that the Web sites in the third study differed from actualWeb sites, not only in terms of the total number of Web pages but also in terms ofusability and aesthetic factors. Because this research focused on exploring person-ality dimensions, other important aspects of Web design, such as usability or aes-thetics, were overlooked. In a further study, Web sites that are more realistic shouldbe constructed to provide a higher level of external validity.

The third limitation of this study is that the focus was only on the visual aspectsof Web sites for e-brand personalities. However, there might be more effective fac-tors other than visual aspects of Web sites, such as advertisements and e-mailing. Afuture study on e-brand personality should broaden its scope to account for theseimportant aspects of e-brand facilitators.

The fourth limitation is that the number of basic elements used was restricted incalculating visual attributes. For example, the 11 visual attributes for homepages inthe second study and for the style sheets in the third study were measured and de-signed mainly on the basis of color, size, and location of visual elements. This studycould not deal with other important design factors such as space, typography, andimages. A future study should include additional design factors to provide morecomplete coverage of visual design aspects.

A further limitation is that the 52 homepages used in the second study were pro-duced under experimental circumstances. The experimental characteristics ofthese homepages may have caused several visual attributes, for instance move-ment, rhythm, unity, and proportion, to be less significant in the four personalitydimensions than they would be under real-world conditions. Therefore, in the nextstudy, more diverse Web pages will be used in the real world to secure more vari-ous visual designs.

Another limitation of the research is that participants were asked to state adjec-tives for the Web site that came to their mind. By doing that, the first study, espe-cially in the third phase, might have asked participants about their memorizedbrand rather than their perceived brand personality. A future study should be con-ducted to compare memorized brand and perceived brand in terms of personalityadjectives.

Finally, this research was conducted in Korea, with Korean participants, entirelyin the Korean language. It would be difficult to apply the study results to othercountries without additional verification in those countries.

In spite of these limitations, this study has several important implications. First,the study empirically identifies significant visual attributes that affect e-band per-sonality. Although most studies in the marketing area have worked on the concep-tual level, suggesting abstract principles and strategies, this study actually sug-

30 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

gests specific visual factors that designers can emphasize as they shape the e-brandpersonality of their sites.

Second, this research suggests a multiphase methodology with three consecu-tive studies. In the first phase, preliminary surveys and interviews were conductedto identify the major personality dimensions of e-brands. Drawing from the resultsof the first study, an exploratory survey was conducted in the second phase to iden-tify important visual attributes associated with e-brand personality. Finally, in thethird phase, a study was conducted to explore the feasibility of actually construct-ing Web sites for online services with relatively high target personalities. Eachstudy was established on the results of previous studies and extended those stud-ies’ results. The research sequence as a whole successfully provided empirical evi-dence that Web sites can be built with relatively high target personalities by usingvisual attributes.

Third, drawing from research in the Gestalt psychology and Exploratory Ap-proach theory, this study discusses visual attributes at a compositional level, ad-dressing not only visual elements in themselves but also the broader relationshipsbetween them. Thus, from a design standpoint, the study offers guidelines on howto use visual composition to shape a Web site’s e-brand personality. For example, ifdesigners want to achieve a bold personality on their Web pages, they may focus onsimplicity and cohesion. To do so, they can design objects with contrasting colors,sizes, or locations and can keep consistent ratios between the heights and widths ofobjects.

The authors, in closing, address a possible concern about this sort of research. Intrying to quantify and analyze a design process that is first and foremost creative, astudy like this one may risk suffocating the creativity of designers, and thus defeat-ing its own purpose. This kind of criticism may indeed be appropriate for priorstudies in this area (e.g., J. Kim et al. 2003), which focused on the basic elements ofvisual design. These studies linked conceptual factors, such as aesthetic impres-sions, directly to individual design elements such as icons and buttons, leaving lit-tle room for a designer’s creativity. However, the results of our study provide farmore room for the designer’s creativity, because visual attributes—as distinct fromindividual design elements—can be minimized or maximized in a wide variety ofways. Thus, designers can express their creativity through different combinationsof visual elements—color, size, location, and the like—while still maximizing thesame visual attributes. For example, although two Web pages may have the samenumeric value for balance, the pages themselves may differ greatly, using very dif-ferent combinations of color, size, shape, and layout to achieve their balance.

Offering specific guidelines on how to use visual attributes, at the same timeleaving plenty of latitude for creative expression, this research will help designersgive their Web sites effective, appropriate, clearly articulated e-brand personalities.

REFERENCES

Aaker, D. A. (1996). Building strong brands. New York: Free Press.

Visualizing E-Brand Personality 31

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

Aaker, D. A. (1997). Should you take your brand to where the action is? Harvard Business Re-view, 75, 135–42.

Aaker, J. (1997). Dimensions of brand personality. Journal of Marketing Research, 34, 347–356.Aaker, J., Benet-Martinez, V., & Garolera, J. (2001). Consumption symbols as carriers of cul-

ture: A study of Japanese and Spanish brand personality constructs. Journal of Personalityand Social Psychology, 81, 492–508.

Ansari, A., & Mela, C. F. (2004). E-customization. Journal of Marketing Research, 41, 131–146.Arnheim, R. (1983). Art and visual perception: A psychology of the creative eye. Los Angeles: Uni-

versity of California Press.Arnheim, R. (1988). The power of the center: A study of composition in the visual arts. Los Angeles:

University of California Press.Bedford, C. (2003). Atool for managing brand assets. Design Management Journal, 14, 81–88.Behrens, R. R. (1984). Design in the visual arts. Upper Saddle River, NJ: Pearson Prentice Hall.Bevlin, M. E. (1997). Design through discovery: The elements and principles. Belmont, CA:

Wadsworth.Breakenridge, D. (2001). Cyberbranding. Upper Saddle River, NJ: Pearson Prentice Hall.Buss, D. M. (1999). Human nature and individual differences: The evolution of human per-

sonality. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (pp.31–56). New York: Guilford Press.

Campbell, M. C., Keller, K. L., Mick, D. G., & Hoyer, W. D. (2003). Brand familiarity and ad-vertising repetition effects. Journal of Consumer Research, 30, 292–305.

Carpenter, P. (2000). eBrands: Building an internet business at breakneck speed. Boston: HarvardBusiness School Press.

Davies, G., Chun, R., Silva, D., Vinhas, R., & Roper, S. (2004). A corporate character scale toassess employee and customer views of organization reputation. Corporate Reputation Re-view, 7, 125–147.

Davis, S. M. (2000). Brand asset management: Driving profitable growth through your brands. SanFrancisco: Jossey-Bass.

Dayal, S., Landesberg, H., & Zeisser, M. (2000). Building digital brands. McKinsey Quarterly,2, 42–52.

Dillon, A. (1992). Reading from paper versus screens: A critical review of the empirical litera-ture. Ergonomics, 35, 1297–1326.

Dreze, X., & Hussherr, F. (2003). Internet advertising: Is anybody watching? Journal of Interac-tive Marketing, 17, 8–23.

Duncan, T., & Moriarty, S.E. (1998). A communication-based marketing model for managingrelationships. Journal of Marketing, 62, 1–13.

Ellis, W. D. (1938). A source book of Gestalt psychology. New York: Harcourt, Brace, & Co.Gardne, S. J., & Burlegh, L. (1955). The product and the brand. Harvard Business Review, 33,

33–39.Heskett, J. (1980). Industrial design. London: Thames and Hudson.Hirschman, E., & Holbrook, M. B. (1982). Hedonic consumption: Emerging concepts, meth-

ods and propositions. Journal of Marketing, 46, 92–101.Hoeffler, S., & Keller, K. L. (2003). The marketing advantages of strong brands. Journal of

Brand Management, 10, 421–446.Hofacker, C. F. (2000). Internet marketing. Indianapolis,IN: Wiley.Holland, J., & Baker, S. M. (2001). Customer participation in creating site brand loyalty. Jour-

nal of Interactive Marketing, 15, 34–45.Hong, W., Thong, J. Y. L., & Tam, K. Y. (2004). Designing product listing pages on e-com-

merce Web sites: An examination of presentation mode and information format. Interna-tional Journal of Human-Computer Studies, 61, 481–503.

32 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

Hoque, A. Y., & Lohse, G. L. (1999). An information search cost perspective for designing in-terfaces for electronic commerce. Journal of Marketing Research, 36, 387–394.

Hue, U. (2001). The study of the formation of brand personality and the application of posi-tioning strategies. The Journal of Korea Association for Advertising, 3, 7–20.

Hwang, I. S. (2000). Effects of visual and auditory components in advertisement on the per-ception of brand personality. The Korean Journal of Advertising, 11, 255–268.

Joachimsthaler, E. (1999). Harvard Business Review on Brand Management. Boston: HarvardBusiness School Press.

John, O. P. (1990). The big five factor taxonomy: Dimensions of personality in the natural lan-guage and in questionnaires. In L. A. Pervin & O. P. John (Eds.), Handbook of personality:Theory and research (pp. 102–138). New York: Guilford.

Keller,K.L. (2002).Strategicbrandmanagement.UpperSaddleRiver,NJ:PearsonPrenticeHall.Keller, K. L. (2003). Brand synthesis: The multidimensionality of brand knowledge. Journal of

Consumer Research, 29, 595–601.Keller, K. L., & Lehmann, D. R. (2003). How do brands create value? Marketing Management,

12, 26–32.Kim, C. L. (1996). Bases and analysis of visual compositions. Seoul, Korea: Mijinsa.Kim, J., Lee, J., & Choi, D. (2003). Designing emotionally evocative homepages: An empirical

study of the quantitative relations between design factors and emotional dimensions. In-ternational Journal of Human-Computer Studies, 59, 899–940.

Kim, J. S. (2002). A study on the style and theme for visual identity of branding in focusedcolor. Journal of Package Design Research, 12, 1–16.

Kim, J. W. (2002). Digital content @ HCI Lab. Seoul, Korea: Yonjin.Kim, Y. K. (2000). The study on construction of eBrand personality and effective factors. Ad-

vertising Study, 49, 29–53.Kim, Y. K. (2001). The study on the dimensions of eBrand personality and its determinants.

Journal of Korean Society for Journalism and Communication Study, 45, 229–426.Kleinbard, J., & Erdelyi, M. H. (1978). Has Ebbinghaus decayed with time? The growth of re-

call (hypermnesia) over days. Journal of Experimental Psychology: Human Learning andMemory, 4, 275–289.

Koffka, K. (1955). Principles of Gestalt psychology. London: Routledge & Kegan.Lauer, D. A. (1985). Design basics (4th ed.). Belmont, CA: Wadsworth.Lavie, T., & Tractinsky, N. (2004). Assessing dimensions of perceived visual aesthetics of Web

sites. International Journal of Human-Computer Studies, 60, 269–298.Lievens, F., Fruyt, F. D., & Dam, K. V. (2001). Assessors’ use of personality traits in descrip-

tions of assessment centre candidates: A five-factor model perspective. Journal of Occupa-tional and Organizational Psychology, 74, 623–637.

Lindstrom, M. (2001). Clicks, bricks, and brands. London: Kogan Page.Lindstrom, M., & Andersen, T. F. (2000). Brand building in the internet. London: Kogan Page.Lupton, E. (1999). Design writing research: Writing on graphic design. London: Phaidon Press.MacIntyre, A. (1984). After virtue. Chicago: University of Notre Dame Press.McAdams, D. P. (1994). Can personality change? Levels of stability and growth in personal-

ity across the life span. In T. F. Heatherton & J. L. Weinberger (Eds.), Can personalitychange? (pp. 299–314). Washington, D.C.: American Psychological Association.

McAdams, D. P. (1995). What do we know when we know a person? Journal of Personality, 63,365–396.

McCormack, J. P., Cagan J., & Vogel, C. M. (2004). Speaking the Buick language: Capturing, un-derstanding,andexploringbrandidentitywithshapegrammars.DesignStudies,25,1–29.

McCrae, R. R., & Costa, R. T. (1989). The structure of interpersonal traits: Wiggins’scircumplex and five-factor model. Journal of Personality and Social Psychology, 56, 586–595.

Visualizing E-Brand Personality 33

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014

McCrae, R. R., & Costa, R. T. (1997). Personality trait structure as a human universal. Ameri-can Psychologist, 52, 509–516.

Mischel, W. (1993). Introduction to personality (5th ed). Fort Worth, TX: Harcourt Brace .Moorthi, Y. L. R. (2004). Branding principles—Application to business-to-business brand-

ing. Business Marketing, 11, 79–103.Morgan Stanley Dean Witter & Co. (2002). Internet, technology, telecommunications. Retrieved

December 30, 2004, from http://www.morganstanley.com/institutional/techresearch.Nelson, S. J. V. (2002). Corporate brand and packaging design. Design Management Journal,

13, 32–38.Ngo, D. C. L., & Byrne, J. G. (2000). Aesthetic measures for assessing graphic screens. Journal

of Information Science and Engineering, 16, 97–116.Ngo, D. C. L., & Byrne, J. G. (2001). Application of an aesthetic evaluation model to data en-

try screens. Computers in Human Behavior, 17, 149–185.No, J. H., & Lim, H. H. (1999). Reconsideration of psychological differentiation methods of

building up the visual image of brand identity. The Journal of Korea Design, 5, 71–81.Norman, D. A. (2004). Emotional design. New York: Basic Books.Norman, W. T. (1963). Toward an adequate taxonomy of personality attribute. Journal of Ab-

normal and Social Psychology, 66, 574–583.Park, S., Choi, D., & Kim, J. (2004). The measurement of visual compositions focused on Web

pages. Korea Information Science Society, 13, 198–212.Pearson, R., & Schail, P. V. (2003). The effect of spatial layout of and link colour in Web pages

on performance in a visual search task and an interactive search task. International Journalof Human-Computer Studies, 59, 327–353.

Pickford, R. W. (1972). Psychology and visual aesthetics. London: Hutchinson Educational Ltd.Piedmont, R. L., McCrae, R. R., & Costa, P. T. (1991). Adjective check list scale and the

five-factor model. Journal of Personality and Social Psychology, 60, 630–637.Plummer, J. T. (1985). How personality makes a difference. Journal of Advertising Research, 24,

27–31.Rosenfeld, L., & Morville, P. (2002). Information architecture for the World Wide Web: Designing

large-scale Web sites (2nd ed). Sebastopol, CA: O’Reilly & Associates.Rust, R. T., Ambler, T., Carpenter, G. S., Kumar, V., & Srivastava, R. K. (2004). Measuring mar-

keting productivity: Current knowledge and future directions. Journal of Marketing, 68,76–90.

Schenkamn, B. N., & Jonsson, F. U. (2002). Aesthetics and preferences of Web pages. Behaviorand Information Technology, 19, 367–377.

Schmitt, B. H. (1999). Experiential marketing: How to get customers to sense, feel, think, act and re-late to your company and brand. New York: Free Press.

Schmitt, B. H., Simonson, A., & Marcus, J. (1995). Managing corporate image and identity.Long Range Planning, 28, 82–92.

Scott, D. (1993). Visual search in modern human-computer interfaces. Behavior and informa-tion technology, 12, 174–189.

Vogt, C. A., & Fesenmaier, D. R. (1998). Expanding the functional information search model.Annals of Tourism Research, 25, 551–578.

Wong, W. (1987). Principles of color design. New York: Van Nostrand Reinhold.Yeo, J. Y. (2000). Check points for constructing successful eBrand. Seoul, Korea: LG Economic Re-

search Institute.

34 Park, Choi, Kim

Dow

nloa

ded

by [

EC

U L

ibra

ries

] at

03:

55 1

0 O

ctob

er 2

014