Website design, trust and culture: An eight country investigation

Electronic Commerce Research and Applications xxx (2013) xxx–xxx

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Website design, trust and culture: An eight country investigation

Dianne Cyr ⇑Beedie School of Business, Simon Fraser University, Central City Tower, 250-13450 102nd Avenue, Surrey, BC, Canada V3T 0A3

a r t i c l e i n f o a b s t r a c t

Article history:Received 19 July 2012 Received in revised form 15 March 2013 Accepted 16 March 2013 Available online xxxx

Keywords:CultureWebsite design Website trust Transaction security Theory of trust and social capital Clustering theory

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Please cite this article in press as: Cyr, D. Webdx.d oi.org/10.1016/j.elerap.20 13.03.0 07

User perceptions of website design (for Information Content, Information Design, Navigation Desig n,Visual Design), Website Trust, and Transaction Security are examined for differences in an eight country sample. Motivation for the investigat ion includ es: (1) to test and comp are user reactions to website design in countries with different degrees of uncertainty avoidance, (2) to consider user reactions based on country economic and technological conditions related to the theory of institutional trust and social capital, and (3) to extend clustering theory and the GLOBE cultural cluster model to determine if culturally similar countries group regarding user perceptions of websites. Overall and as predicted, users in low uncertainty avoidance, high institut ional trust and social capital countries such as Canada and the USA have the most favorabl e perceptions of website design. An interesting finding is that while country economic and technological conditions may temper user perceptions in some instances, overall culture is astronger predictor. Clustering theory is a useful determina nt of user perceptions, and there is strong support that users within a given cultural cluster have similar requirements regarding website design.

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1. Introductio n value website trust and security over users from lower uncertainty

In the realm of e-business, vendors seek to provide positive online experiences for potential buyers. This includes the development of websites that are visually pleasing, easy to navigate, and rich in accessible informat ion content. In addition, online vendors aim to induce a sense of security or trust in the user. In an increas- ingly global online market space, effective website design must appeal to users from diverse cultures (Barber and Badre 1998, Gefen and Heart 2006, Hu et al. 2004, Vyncke and Brengman 2010 ).

Acceptance of website design features differs among countries and cultures (Barber and Badre 1998, Hu et al. 2004, Nielsen and del Galdo 1996, Simon 2001, Singh et al. 2003, Smith et al. 2004 ).Cyr (2008) found differenc es between countries regarding website design related to trust, satisfaction , and website loyalty. These previous studies indicate that users in different countries are likely to experience website design differently, including trust and security on the Web. More specifically, in countries where uncertainty is avoided (e.g. uncertainty avoidance) there is less trust in the IT artifact such as a website (Vance et al. 2008 ). While other studies have examine d various cultural dimensions related to website design, there are few that focus on uncertainty avoidance as the predictor for user reactions in this context. Further, uncertainty avoidance has relevance in the current investigation since website trust and security will be investiga ted. According to Dinev et al.(2006) online users high in uncertainty avoidance will especially

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site design, trust and culture:

avoidance cultures.It is expected that country factors such as economic wealth and

levels of technology (including the Internet) will also potentially influence user perceptions of website design and security. With respect to economic factors, Fukuyama’s (1995) theoretical framework for institutiona l trust and social capital suggests that in countries with economic prosperity, social capital as a form of good will on the part of individuals or groups toward the actions of organizations is more likely to be present. Evidence of social capital leads to trust (Fukuyama 1995 ). In the context of the current research,users in countries with greater prosperity would be more likely to have social capital and therefore trust institutions such as the Inter- net. Throughout this paper, this will be termed trust and social capital. Concerning technological variables, in countries where online connectiv ity and infrastructu re are good and when digital legal safeguards are in place, then consumer and business electroni c adoption is higher (Source: e-Readiness Rankings 2007 ). It would be expected that higher adoption rates are related to user perceptions of trust and security of the digital infrastructu re.

As noted above, some research has investigated user perceptions of websites in diverse national contexts. However, to our knowled ge there is no research that systemati cally examines the influence of economic and technological elements on user perceptions of website design. Further, there is no research that examines national culture in conjunction with social capital and technological parameters with respect to website design. It is expected that studying these variables together will provide a more nuanced view as to how users in a given country respond to website design features, including levels of perceived trust and security.

An eight count ry investigation . Electron. Comm. Res. Appl. (2013), http ://

http://dx.doi.org/10.1016/j.elerap.2013.03.007

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1 Throughout this paper design ‘‘element’’ refers to the four design categories investigated and represente d as constructs in Appendix C for Information Design,Information Content, Navigation Design, and Visual Design.

2 D. Cyr / Electronic Commerce Research and Applications xxx (2013) xxx–xxx

Of additional interest, and new to this investigation, is the degree to which different countries are clustered related to user perceptions of website design (i.e. Information Design, Information Content, Navigation Design, Visual Design), as well as Website Trust and Transaction Security. According to clustering theory (Hartigan 1975 ), members of a group will serve as predictors of expected behavior of the classified group. The application of clustering has previously been used concerning culture (e.g. House et al.2002, Ronen and Shenkar 1985 ) wherein countries are grouped based on similarities and differenc es concerning values and beliefs.Given the expense of website developmen t costs, there is practical value to determine if users in different countries ‘‘cluster’’ or exhibit similarity in website design perceptions . Should this be the case, then websites can be developed for country clusters as opposed to individual countries.

Based on the preceding, the motivation for the current investigation includes to:

(1) test and compare user reactions to website design in a range of countries with differing degrees of uncertainty avoidance;

(2) evaluate user reactions based on country economic and technolo gical conditions related to the theory of trust and social capital, and to determine if this approach coupled with uncertainty avoidance is a better predictor of user perceptions of website design;

(3) extend clustering theory to determine if culturally similar countries group together regarding user perceptions of websites .

To further elaborate the background and rationale driving this research, this paper begins with an introduction to culture including Hofstede’s dimensio n of uncertainty avoidance; country economic and technologic al factors; and clustering theory. This is followed by a discussion of culture and website design. Topics such as website trust and transaction security are then elaborated. The method, results, and discussion follow, with both theoretical and practical implication s outlined.

2. Underlying theoretica l framewo rks

2.1. Culture and uncertainty avoidanc e

Although one definition of culture is not possible, various researchers have used nation state as a loose categorization for culture (Doney et al. 1998 ). Hofstede defines culture as ‘‘the collective programmin g of the mind which distinguishes the members of one group from another’’ (1980, p. 21). It is expected that within a given national culture there is a dominant set of shared values, attributes, beliefs and behaviors – although within that culture subtle differences may also occur due to individual, team or organizational differences (Erumban and de Jong 2006, Karahanna et al.2005, Matsumoto 1994 ). Culture is ‘‘a system of values and norms that are shared among a group of people and that when taken together constitute a design for living’’ (Doney et al. 1998, p. 67 ).

Researchers have often used Hofstede’s (1980) classifications to study social psychological phenomena (Dawar et al. 1996, Gefen and Heart 2006, Jarvenpaa et al. 1999, Mazaheri et al. 2011, Simon 2001). Although there have been questions regarding the validity of using Hofstede’s cultural dimensions, results of his work have been supported quantitative ly and qualitatively by numerous studies in various disciplines (Sondergaard 1990, Straub 1994 )including information systems. In alignment with Yoon (2002), in the current research Hofstede’s classification for uncertainty avoidance has been selected for its relevance to website design, as well as to trust and security issues related to e-commerce . According to Hofstede, uncertainty avoidance (at the country level) implies the

Please cite this article in press as: Cyr, D. Website design, trust and culture:dx.doi .org/10.1016/ j.elerap.201 3.03.007

degree to which members of a given culture are uncomforta ble in unstructured , uncertain or ambiguous situations and thus prefer formal rules. Cultures high on uncertainty avoidance aim to minimize the possibility of uncertainty by ensuring safety and security.In a review of fifteen studies, in nine of them Leidner and Kayworth (2006) found evidence that uncertainty avoidance is risk based and related to trust. Considering uncertainty avoidance in an online environm ent, we might expect members of high uncertainty avoidance cultures to prefer full information (through informat ion, navigation, or visual design elements 1) to minimize ambiguit y when visiting a website. As previously mentioned, online users high in uncertaint y avoidance will especially value website trust and security over users from lower uncertaint y avoidance cultures (Dinevet al. 2006 ).

2.2. Social capital, economic, and technologica l considerations

Countries investigated in the current study vary on country paramete rs with respect to economic, Internet and other issues as outlined in Appendix A. As such, culture is determined not only by similarity among members of the collective based on psycho- logically based values and beliefs such as uncertainty avoidance,but also by ‘‘commonali ty of observed and reported practices of entities such as families, schools, work organizations , economic and legal systems, and political institutions’’ (House et al. 2002,p. 5). It would be expected that people living in the same country with the same economic and technolo gical conditions would share similar values – which in turn may apply to perceptions of a website. As one example, in a study of perceived value of websites Steenkamp and Geyskens (2006) examined a country characterist ic such as the ‘‘rule of law’’, and found that in countries where the rule of law is weak the effect of privacy and security protection on the Internet is more valued by users.

Tied to economic and technolo gical country parameters as outlined above, an additional theoretical framework useful in this study is Fukuyama’s theory of institutiona l trust and social capital (Fukuyama 1995 ). Also used by Dinev et al. (2006) to examine privacy issues and trust in e-commerce, the underlyin g assumption is that social capital leading to institutiona l trust is develope d when cooperati ve norms such as honesty, keeping commitmen ts, and reliability prevail. In this instance, in countries where there is honesty and reliability on the part of institutions, then citizens in that country have goodwill in the form of social capital, which further leads to trust of that country’s institutions. According to Fukuyama,a country’s economic prosperity is tied to the amount of social capital and trust present in the country. He identifies groups of high-trust countries (e.g. US, Germany, and Japan) and low-trust countries (China, Italy, France, Korea, and Taiwan). Based on the logic proposed by Fukuyama, and related to e-comme rce as in this research, we might expect that in countries with higher economic prosperity there is more likely to be a higher degree of technolo g- ical competency and thus trust. In fact, in countries such as Canada,the USA, Germany, or Japan there is evidence of more connectivity and infrastructure resulting in higher levels of consumer and business electroni c adoption. Refer to Appendix A.

In sum, it would be expected that both the level of uncertainty avoidance, as well as country economic and technologic al factors will contribute to user perceptions of website design, as well as to trust and security. Including both sets of parameters (e.g. cultural and economic) is expected to contribute a more compreh en- sive and nuanced approach for how users experience e-commerce.

An eight countr y investigation . Ele ctron. Comm. Res. Appl . (2013), http ://



D. Cyr / Electronic Commerce Research and Applications xxx (2013) xxx–xxx 3

2.3. Clustering theory

In addition to an examination of users who differ by country for uncertainty avoidance, another approach is to investiga te differences and similarities between countries based on Clustering Theory (Hartigan 1975 ). According to Clustering Theory, prediction occurs in two ways. First, if a group (country) is classifiedinto a given cluster (country cluster) then information about behaviors or values of other members of that cluster would serve as predictor s of expected behavior of the classified group.Second, measure s (such as those related to website design) that demonstrat e a cultural affinity would be predictive of other members of another given group as long as they belong to the same cluster (i.e. user perceptions of website design in Canada would be aligned to the USA since they are within the same cultural cluster). In other work, clustering has been applied to international compensation practices (Townsend et al. 1990 ) and to leadership and organizational effectiveness (House et al. 2002 ).This approach is also consistent with cultural researchers (i.e.Ronen and Shenkar 1985 ) who adhere to a ‘‘culture cluster’’model. However, such a model has not previousl y been applied to website design.

Of particular relevance to the current research, House et al.(2002) conducte d an extensive investigatio n in 61 nations called the GLOBE project.2 Country clustering was determ ined based on similarities and differences concerning societa l values and beliefs.Ten cultural clusters are identified in the GLOBE research, of which five are represente d in the current study: North America (Canada,the USA), South Asia (India), Germanic Europe (Germany), Confuc ian Asia (Japan, China), and Latin America (Mexico, Chile). While the GLOBE project focused on leadershi p rather than on website design,the clustering of count ries as noted above is useful for forming comparisons in the current investigat ion. More specifically, it is expected that users from count ries within a given cluster will be more similar regarding their perception s of website design compared to users outside the country cluster.

3. Literature review and hypothe ses development

3.1. Culture and website design

Some investigatio ns have examined website design across cultures and countries with differences detected between country sam- ples. For example, Cyr and Trevor-Smith (2004) assessed eight elements of website design for 30 websites in each of the USA,Germany, and Japan (90 websites total) and found significant differences between country differences in all but one category. In another study, Cyr et al. (2005) evaluated website characterist ics related to information design, visual design, and navigation design and trust in Canada, the USA, Germany and Japan and uncovered differences in preferenc es by country for design elements between a local and foreign version of the same website. Extending these studies,the current research examines Information Content, Information Design, Navigation Design, and Visual Design in an eight country sample differing in uncertainty avoidance and in which multiple parameters such as the inclusion of social capital are considered.

3.1.1. Information content and information design As defined in this study, Information Content refers to informa-

tion that is of high quality and assessed by the user to be complete ,sufficient, and effective (Egger 2001, Marcus and Gould 2000 ).Alternately, Information Design refers to the organization and

2 The results of the GLOBE project appear in a series of papers in the Journa l of World Business (2002).

Please cite this article in press as: Cyr, D. Website design, trust and culture:dx.d oi.org/10.1016/j.elerap.20 13.03.0 07

logical representat ion of information (Egger 2001, Marcus and Gould 2000 ). In one cross-cultural study (Cyr et al. 2005 ), user design preferences including perceived access and presentation of product informat ion were compared for Canada, the USA, Germany and Japan. Results indicated few significant differences between the USA, Canada, and Germany but significant differenc es between these countries and Japan. Japanese users had a less favorable impressi on of the local website related to these select information components.

It is expected that Information Content and Information De- sign enable users to access informat ion regarding online products or services. Further, and based on Hofstede’s (1980)research with reference to uncertainty avoidance, it is antici- pated that users from higher uncertainty avoidance cultures would find these two design elements more important as they seek to reduce uncertainty and ambiguity in the process of gath- ering information about prospective electronic purchase s. Conse- quently, it would also be expected that the higher the uncertainty avoidance of users, it is less likely the demand for Informati on Design and Information Content will satisfactoril ybe met. This then results in higher uncertainty avoidance users who have a less favorable assessment of each design element.

In addition, and based on Fukuyama’s (1995) theory of trust and social capital, users will be more receptive to website design elements in higher trust countries such as in the USA, Germany,Japan, and Canada where there are higher levels of social capital and enhanced connectivity and infrastructu re over countries where this is not the case such as in India, Mexico, Chile, and China. Alternately, when countries have moderate levels of uncertainty avoidance, or mixed levels of uncertainty avoidance with country conditions then user perceptions are expected to be mid-range. For instance, Japan has the highest level of uncertainty avoidance but also a high level of trust and social capital based on advanced technolo gy and infrastructure. Therefore, it is unlikely that user perceptions will be either high or low for website design features. India has a low level of uncertainty avoidance, but also a low level of institutionalized trust and social capital which is expected to place user perceptions mid- range. Finally, both Germany and China are moderate for uncertainty avoidance, with Germany high in institutiona lized trust and social capital and China low for trust and social capital.Although exploratory, it is expected that they will both score mid-rang e as well.

This leads to the first set of hypotheses:

H1. Low uncertainty avoidance users in high trust countries (e.g.Canada and the USA) will provide highest ratings for Information Content over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany , China, and Japan).

H2. Low uncertainty avoidance users in high trust countries (e.g.Canada and the USA) will provide highest ratings for Information Design over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany , China, and Japan).

3.1.2. Navigatio n design Navigation Design refers to the navigationa l scheme used to

help or hinder users as they access different sections of a website (De Wulf et al. 2006 ). For example, this could include whether text is horizontal or vertical, and the number of drop down menus or submenus . Preferences for the form of navigationa l scheme are





expected to vary by culture (Marcus and Gould 2000 ). Europeans and North Americans prefer navigation that facilitates easy search and makes the site simple to use. Asian/Latin and South Americans desire navigation aids to change the appearance of the site without particular concern for movement (Simon2001). While, the preference for navigation differs between cultures, it is speculated that users from high uncertainty avoidance countries are more concerned with clarity in how to navigate to find out about products or services than users from lower uncertainty avoidance countries.

If this is the case, then users from high uncertainty avoidance cultures will have a less positive assessment of Navigation Design than low uncertainty avoidance users. Further, as with Information Content and Information Design, it is expected that trust and social capital will temper user perceptions – with users in high trust countries providing higher ratings for Navigation design over users in low trust or mixed countries (for uncertainty avoidance with trust and social capital).

H3. Low uncertainty avoidance users in high trust countries (e.g.Canada and the USA) will provide highest ratings for Navigation Design over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan).

3.1.3. Visual Design Visual Design encompasse s design elements such as balance,

emotional appeal, aesthetics, and uniformity of a website’s overall graphical look. This may include colors, photographs , shapes,images, or font type (Bonnardel et al. 2011, Garrett 2003, Salinas 2002). More specifically, a user may gain knowled ge or an appreciation of a product through the image conveyed. Users from countries such as China have a strong preference for visuals (Sun2001). Hedonic elements of websites are important to Chinese,while Canadians prefer utilitaria n design elements (Mazaheriet al. 2011 ). Cultural differenc es were found concerning use of images (Cyr et al. 2009 ) and use of color (Cyr et al. 2010 ) in website design. In a study that compare s Canadian, American, German and Japanese users, Japanese favor a visual approach which they said appeals to the user’s ‘‘emotion’’ (Cyr et al. 2005 ). Once again, while the preceding supports the idea that users from different countries have difference website preferenc es for visual design, it is expected that users from high uncertainty avoidance countries will use visual design features to obtain additional informat ion and to reduce ambiguity about electronics products. As in the previously stated hypotheses, it is proposed that high uncertainty avoidance users in low trust countries will have the least positive reaction to Visual Design, while low uncertainty avoidance users in high trust countries will have the most positive perceptions concerning Visual Design.

H4. Low uncertainty avoidance users in high trust countries (e.g.Canada and the USA) will provide highest ratings for Visual Design over high uncertainty avoidance users in low trust countries (e.g.Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India,Germany, China, and Japan).

Based on the GLOBE studies, it is expected that in certain countries (e.g. Canada and the USA; Japan and China; Mexico and Chile) user perceptions will be similar concerning the four website design elements as outlined above. Of note, this pro- posal is in alignmen t with country expectations based on trust and social capital as outlined by Fukuyama (1995). This leads to the following hypothes is:


H5. Countries within the same GLOBE cluster will exhibit similar responses to website design elements (e.g. Information Content,Informati on Design, Navigation Design, and Visual Design) compared to users outside the cluster.

3.2. Website trust across cultures

According to Jarvenpaa et al. (1999) online trust refers to consumer confidence in the website and ‘‘willingness to rely on the seller and take actions in circumstanc es where such action makes the consumer vulnerable to the seller’’ (p. 4). Building on this definition, in the current research online trust refers to general trust of the website, and that the user can trust the transacti on process as well as information presented. In an e- commerc e setting, when there is no physical presence of a sales- person, exchange relationship s are more comfortable and likely when institutiona l safeguards such as security symbols are present. Further, online business environments can result in ‘‘problems associate d with insecurity and privacy among transaction counterpar ts, which put pressure on Internet marketers to create a trust that is much stronger and more persisten t than what is normally demanded offline’’ (Yoon 2002, p. 51 ). Consumer trust in the website is fundamental to loyalty including online purchase intentions (Belanche et al. 2012, Flavián et al. 2006, Gefen 2000, McKnigh t et al. 2004 ), usage intentions (Kim et al. 2009 ),and willingness by consumers to buy from an online vendor (Flavián et al. 2006, Laurn and Lin 2003, Ou and Sia 2010, Pavlou 2003). Website quality is known to result in website trust (Cor-bitt et al. 2003 ).

Trust is influenced by culture (Jarvenpaa et al. 1999, Weber and Hsee 1998 ). Cyr et al. (2005) conducted a study to investigate whether or not local websites engender higher levels of trust for Web users than a foreign website of the same online vendor (whenlanguage is not an issue). The findings indicate large differenc es in ability to trust between Japanese and Americans and between Canadians or Germans . Japanese users trust their local website least while Germans trust their local site most. Based on interview data, all four cultural groups identified vendor familiarity and vis- ibility of security signs as important factors influencing trust in online purchasing. In further work (Cyr 2008 ), Information Design,Navigatio n Design, and Visual Design were modeled to trust for users in Canada, Germany and China with differing outcome s. Nav- igation Design results in trust for Canada and China, Visual Design results in trust for China only, and Information Design resulted in trust for Canada only.

In other research, it was expected and confirmed that individuals from high uncertainty avoidance cultures would place less trust in the IT artifact (a mobile device) than individuals from low uncertainty avoidance culture (Vance et al. 2008 ). Based on this and the previous findings, it is established that high uncertainty avoidance users will be less comfortable shopping online than users lower in uncertainty avoidance. As a result, users who are higher in uncertainty avoidance will also rate the website lower, even when it is the same website vendor. However, new to the current investiga -tion we now examine whether these results apply in a larger number of countries and when the institutional context such as online infrastructu re and connectivity (e.g. related to trust and social capital) are also considered.

H6. Low uncertainty avoidance users in high trust countries (e.g.Canada and the USA) will provide highest ratings for Website Trust over high uncertainty avoidance users in low trust countries (e.g.Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India,Germany , China, and Japan).




Table 1Country classifications.

Country and cluster Uncertainty avoidance Trust and social capital Sources: Hofstede(1980, 1993) and House et al. (2002)

Source: Fukuyama(1995)

North America Canada 48 (L) HUSA 46 (L) H

South Asia India 40 (L) L

Germanic Europe Germany 65 (M) H

Confucian Asia China 60 (M) LJapan 92 (H) H

Latin America Mexico 82 (H) LChile 80 (H) L

Notes: L = Low. M = Medium. H = High.


3.3. Transaction security across countries

Closely related to online trust, shopping online is influenced by transaction security and as such users are deterred by absence of payment security, payment -clearing structures, or privacy policies (Becerra and Korgaonkar 2011, Jarvenpaa et al. 1999 ). Use of trusted third parties as intermediaries such as VeriSign (Palmeret al. 2000 ) help to reduce buyer’s perceived risk, as do websites that are authentic (Featherman et al. 2006 ). In a study of online consumer behavior in which American, Brazilian, and Latin Amer- ican consumers are compared, Latin Americans and Brazilians (both from high uncertainty avoidance cultures) indicate the presence of credit card symbols on websites is more important than indicated by Americans who are low on uncertainty avoidance (Cheskin 2000 ).

In other research on website design across cultures (for Canada,USA, Germany and Japan), Germans, Americans and Canadians are less concerne d with security when buying online than Japanese users (Cyr 2011 ). In that research, Canadians noted they are aware of security problems when using the Internet, but felt the benefitsoutweigh the risks. In contrast, Japanese were extremely concerned about online risk and using credit cards for online purchasing. Related to the preceding, and with the vendor held constant, it is expected users from high uncertainty avoidance countries will perceive greater risk and less certainty in conducting transactions online than users from lower uncertainty avoidance countries.Subsequentl y the higher uncertainty avoidance users will also rate the website lower. This established finding is now coupled with the institutiona l perspective as prescribed by the theory of trust and social capital (Fukuyama 1995 ).

H7. Low uncertainty avoidance users in high trust countries (e.g.Canada and the USA) will provide highest ratings for Transacti on Security over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan).

Finally, and with reference to the GLOBE project, it is expected user perceptions in certain countries (e.g. Canada and the USA; Ja- pan and China; Mexico and Chile) will be similar concerning Trust and Transaction Security. This results in the final two hypotheses.

H8. Countries within the same GLOBE cluster will exhibit similar responses for Website Trust and Transacti on Security compared to users outside the cluster.

4 Using a localized website of a reputable company is the most viable option for the research despite certain trade-offs (as noted in Section 6). Alternately, if researchers

4. Methodology

4.1. Participants

A total of 1156 participants located in Canada (312),3 the USA (197), India (106), German y (122), Japan (78), Mexico (71), Chile (48), and China (222). These countries were selected due to differences in uncertaint y avoidance as well as economic and technologi -cal paramet ers. Refer to Table 1. Uncertainty avoidance designations of low, medium, or high are adapted from Hofstede (1993) as they appear in Francesco and Gold (1998, p. 27), as well as from Houseet al. (2002). Levels of Trust and Social Capital are from Fukuya ma (1995). As indicated in the introduc tory sections of this paper, acountry’s econom ic prosperity is tied to the amount of social capital and trust present in the country. Relevant to the countries selected

3 Data was collected se parately in French and English Canada but since there were no significant differences between the groups for any of the constructs tested in this investigation the two groups were combined.


for this study, Fukuyama identified the USA, Germany, and Japan as high-trust countries, while China is a low-trust country. Based on the logic proposed by Fukuyama, it is expected that in countries with higher econom ic prosperity there is more likely to be a higher degree of technologica l compet ency manifest in connecti vity and infrastru cture as indicated in Appendix A. Canada is very similar to the USA in terms of overall prosperity and connecti vity and infrastructure (7.9), and thus is designated high on trust and social capital. Alternately, India, Mexico and Chile score much lower for connecti vity and infrastru cture (2.9; 3.5; and 4.6 respectively ), and therefor e are designat ed as low in trust and social capital. It may be noted that these three countries are also similar to China (3.5)for connectivity and infrastructu re which is designated by Fukuyama as low in trust and social capital.

Participants living in each country were recruited from a wide range of sources including universities , institutes, and companies by scholars living in the country. To ensure participants are ‘‘of the culture’’ it was determined each had lived in the country the majority of their lives and spoke the native language as their pri- mary language . Average age across countries is similar with an overall average of 27.4 years. Participants are experienced online shoppers and well educated. Most had completed either a university degree or post-graduate education. To determine if significantdifferenc es existed across countries based on demograph ics, ANO- VA tests were run for age, education, and Internet and online shopping experience. Overall, no differences occurred between the countries that would influence the constructs tested in this research. Participant demographics appear in Appendix B.

4.2. Task and website design

This research targets user perceptions of B2C Web pages. For the research treatment participants responded to the localized version of the SonyStyl e website represented in their native language.The SonyStyle website was chosen after an extensive search for awell localized vendor website in which the design of the website was adapted to be appropriate to the culture of each user as determined by a design expert who rated each country website.4

aim to experim entally manipulate websites, localization preferences for users such as language, color, images, icons etc. must be taken into account. Such localization is very costly and reliability is not guaranteed. Further, using the same website to control for website differences with only language altered in not a viable solution, as users will find it unsatisfying and will judge the website negatively for that reason.




Table 2Factor analysis loadings matrix.

Sec InfoCont InfoDes NavDes VisDes Trust

Sec2 .675 .175 �.012 .059 .163 .399 Sec3 .824 .085 .157 .006 .046 .028 Sec4 .765 .218 .067 .151 .049 .188

InfoCont1 .335 .671 .206 .093 .000 .148 InfoCont2 .062 .814 .088 .184 .105 .141 InfoCont3 .150 .645 .303 .168 .110 .193 InfoCont4 .099 .791 .112 .129 .157 .018

InfoDes1 .152 .204 .748 .252 .148 .192 InfoDes2 .093 .225 .668 .367 .220 .134 InfoDes3 .076 .327 .617 .278 .107 .100

NavDes1 .095 .156 .253 .796 .137 .124 NavDes2 .076 .179 .197 .816 .120 .196 NavDes3 .066 .214 .229 .696 .163 .200

VisDes3 .104 .215 .203 .270 .709 .215 VisDes4 .108 .114 .147 .130 .818 .109

Trust1 .295 .171 .107 .211 .195 .664Trust2 .060 .143 .211 .170 .084 .781Trust3 .292 .135 .095 .191 .111 .714

NB: Sec = Transaction Security; InfoCont = Information Content; InfoDes = Infor- mation Design; NavDes = Navigation Design; VisDes = Visual Design


Users were requested to initially view the home page of the local website, followed by navigation of the website to choose a cell phone they would hypothetical ly purchase. This methodology is consistent with Cyr et al. (2005) and Cyr (2008). Once participants concluded this task, each completed an online questionnair e. Back- ground information to the study, and all other written content including the questionnair e were translated and back-tran slated into each required language . As an incentive to participate in the study, participa nts could optionally enter their name in a draw for a US$ 250 gift certificate for Amazon.com.

4.3. Instrument validity and reliability

Content validity ensures construct items are representat ive and drawn from a universal pool (Cronbach 1971 ). With the exception of Information Content, the constructs used in the investigatio n(for Transaction Security, Informati on Design, Navigation Design,Visual Design, Website Trust) are based on earlier research and had previously been validated from a variety of sources and exhibit content validity. Items for Informati on Content were derived from existing literature including Garrett’s (2003) website classifica-tions, and this construct was successfully validated in this investigation. Questionnaire items and sources appear in Appendix C. All items were assessed on a 7-point Likert scale from strongly disagree to strongly agree. The questionnaire was pre-tested with 62 undergraduate students in English Canada. Categories were evaluated for item validity and reliability and several items were revised for better fit.

Table 3Reliability and validity indices.

Average Variance Extracted (AVE)

Composite Reliability

Cronbach’s Alpha

InformConten

Information Content

0.675 0.893 0.841 0.822

Information Design

0.733 0.892 0.818 0.613

Navigation Design

0.791 0.919 0.868 0.519

Transaction Security

0.690 0.869 0.777 0.467

Trust 0.748 0.899 0.832 0.501 Visual Design 0.778 0.875 0.715 0.461


Construct validity is demonstrated when there are relatively high correlations between measures of the same construct (con-vergent validity) and low correlations between measures of constructs that are expected to be different (discriminant validity)(Straub 1989 ). To assess converge nt validity of the measureme nts Fornell and Larcker (1981) proposed examining: (i) the item reliability of each measure, (ii) the composite (construct) reliability of each construct, and (iii) the average variance extracted for each construct. Item reliability of each measure was assessed through aprincipal component factor analysis as recomme nded by Straub(1989). Table 2 shows the results of the principal component analysis with Varimax rotation for the constructs. As a rule, items in aconstruct load highly if the loading coefficient is above 0.6, and do not load highly if the coefficient is below 0.4 (Hair et al. 1995 ). The constructs in the questionnair e demonst rate discriminant validity.

Internal consisten cy was assessed using Cronbach’s a-valuesand composite reliability . In Table 3 a-values ranged from 0.715 (for Visual Design) to 0.868 (for Navigation Design). The Cronbach a of a scale should be greater than 0.5 for items used together and ideally higher than 0.7 (Rivard and Huff 1988 ). Similarly , the composite reliability of each construct exceeded the recommend ed threshold of .7 (Straub et al. 2004 ). Therefore all constructs possess construct reliability. Convergent validity is demonstrat ed as the average variance extracted (AVE) of all constructs exceeded 0.5 (Fornell and Larcker 1981 ).

As per Fornell and Larcker (1981) the correlations between items in any two constructs should be lower than the square root of the average variance shared by items within a construct.As shown in Table 3, the square root of the variance shared between a construct and its items was greater than the correlations between the construct and any other construct in the model, satisfying Fornell and Larcker’s (1981) criteria for discriminant validity.

4.4. Testing common method variance

To test for common method variance (CMV), Harman’s single- factor test was applied, which is the most widely known approach for assessing CMV (Podsakoff et al. 2003 ). As per Vanceet al. (2008), an explorator y factor analysis was run which included all first-order constructs. The unrotated factor solution was examined against Podsakoff et al.’s (2003) assertion that common method variance exists if (a) a single factor emerges from the factor analysis or (b) one general factor will account for the majority of the covariance among the measures (p.889). More than one factor emerged to explain the variance in the analysis, with the first factor explainin g 43.45% of the variance, indicating that common method bias is not a likely con- taminant of the results.

In an additional test for CMV, LISREL (i.e., a covariance-bas ed structura l equation modeling technique) was used rather than PLS to conduct /Confirmatory Factor Analysis/ (CFA). This test not

ation t

Information Design

Navigation Design

Transaction Security

Trust Visual Design

0.856

0.695 0.889

0.374 0.323 0.830

0.525 0.553 0.576 0.8650.554 0.531 0.363 0.508 0.882




Table 4Test of common methods variance [LISREL analysis].

Model v2df [smaller] v2/df [<3.0] GFI [>0.9] AGFI [>0.8] RMR [<0.05] RMSEA [<0.06] NFI [>0.9] CFI [>0.9]

Original model v2120 ¼ 557:85 4.65 0.95 0.93 0.039 0.056 0.95 0.96

Original model with method v296 ¼ 397:26 4.14 0.96 0.93 0.029 0.052 0.96 0.97


only includes the six cognitive constructs of interest (i.e., information content, information design, navigation design, visual design,transaction security and trust), but also incorporate s an extra latent method construct which is connected reflectively to all measurement items. As can be seen from Table 4, the addition of this latent method construct causes a drop in chi-square value from 557.85 to 397.26 with a correspondi ng decrease in degrees of freedom from 120 to 96. The change in chi-squa re value of 160.59 with 24 degrees of freedom implies that there is a difference in the fit of the CFA model when the latent method construct is added.

In this sense, the possibility of CMB cannot be ruled out en- tirely for the data sample. Neverthel ess, as pointed out by Richardson et al. (2009), covariance- based structural equation modeling techniqu es, when applied to the ULMC approach, can only correctly identify CMB ‘‘about 41% of the time’’ (p. 794).Further, it can be inferred from Table 3 that all fit indices exceed recommend ed thresholds for the CFA model with the original six cognitive constructs. The addition of the latent method construct does not lead to substantial improvement in fit indices. This in turn testifies to the convergent and discriminant validity of the six cognitive constructs, and as alleged by Conway and Lance (2010), evidence of construct validity should be prioritized over post hoc statistical control strategies for CMB since each of these latter strategies suffer from significant drawbacks. In sum, based on the two tests of CMV and related to the tested validity of the constructs, CMV does not appear to be a significant issue in this study.

Table 5Descriptive statistics [samp le N = 1156].

Country Construct

Sec InfoCont InfoDes Mean (S.D.) Mean (S.D.) Mean (S.D.)

CAN 5.256 (1.113) 5.191 (1.164) 5.477 (1.022USA 5.276 (0.974) 5.396 (1.034) 5.721 (0.877IND 4.966 (1.185) 4.781 (1.244) 5.145 (1.258GER 4.405 (1.205) 4.525 (1.244) 4.790 (1.170JAP 5.471 (1.191) 4.808 (0.936) 4.368 (0.940MEX 4.968 (1.294) 4.919 (1.206) 5.442 (1.167CHI 4.938 (1.089) 5.021 (1.415) 5.223 (1.260CHN 4.548 (1.049) 4.606 (1.049) 4.490 (1.153Total 4.975 (1.159) 4.944 (1.169) 5.120 (1.182

NB: CAN = Canada; USA = United States of America; IND = India; GER = Germany; JAP = JSe = Transaction Security; IC = Information Content; ID = Information Design; ND = Navig

Table 6Summary of dependen t variable significance between countr ies.

CAN USA IND

CAN USA (–)IND (–) (IC | ID | ND)GER (Se | IC | ID | ND l VD | T) (Se | IC | ID | ND | VD | T) (Se | VD)JAP (ID | ND | VD l T) (IC | ID | ND | VD | T) (ID | ND | T)MEX (–) (–) (–)CHI (VD) (VD) (–)CHN (Se | IC | ID | ND | VD | T) (Se | IC | ID | ND | VD | T) (Se | ID | ND | VD |

NB: Se = Transaction Security; IC = Information Content; ID = Information Design; ND = NThis table represents where significant differences exist for the two intersected countrie


5. Results

One goal of the investigation is to determine between country similarities and differences for eight countries related to value considerations of uncertainty avoidance, as well as institutiona lparamete rs such as social capital, economic, and technologic al condition s. A second goal is to determine if countries within the same country cluster are more similar compared to countries outside their cluster. Tukey HSD testing (N = 1156) was used to determine between group differenc es. Information used for between country comparisons is derived from the following sources: (1) Table 5 provides descriptive statistics including means and standard deviations for each country and combined country totals; (2) Table 6 offers a summary of significant differences that occurred for between country comparisons for each depende nt variable as derived from Tukey comparisons (whichtests for significant differences). Due to the large number of comparis ons and space requiremen ts a table with full results of Tukey comparisons is not provided. Therefore this table sum- marizes only results in which significant differences occur between countries.

As expected, in Table 6 no significant differences occur across all dependent variables between Canada with the USA No differences exist between Mexico and Chile. A number of significantdifferenc es exist between India, Germany, Japan, and China with the other countries in the sample. In terms of statistical ly significant differences for the various dependent variables in this study (as tallied based on the results in Table 6), a large number

NavDes VisDes Trust Mean (S.D.) Mean (S.D.) Mean (S.D.)

) 5.590 (1.072) 5.720 (1.133) 5.516 (1.030)) 5.779 (1.000) 5.833 (1.045) 5.611 (0.923)) 5.117 (1.341) 5.524 (1.339) 5.239 (1.127)) 5.148 (1.396) 4.615 (1.386) 4.905 (1.011)) 4.009 (1.277) 4.988 (1.307) 4.342 (1.191)) 5.559 (1.096) 5.479 (1.218) 5.343 (1.194)) 5.487 (1.113) 4.980 (1.595) 5.619 (0.968)) 4.597 (1.278) 4.669 (1.268) 4.428 (1.135)) 5.214 (1.292) 5.279 (1.341) 5.140 (1.163)

apan; MEX = Mexico; CHI = Chile; CHN = China ation Design; VD = Visual Design; T = Trust

GER JAP MEX CHI CHN

(Se | ND | T)(Se | ID | VD) (ID | ND | T)(T) (ID | ND | T) (–)

T) (ND | T) (Se | ND) (ID | ND | VD | T) (ID | ND | T)

avigation Design; VD = Visual Design; T = Trust s based on Tukey HSD testing. (–) indicates no significant difference.




Table 7Hypotheses and outcomes.

Hypothesis Outcome

H1: Low uncertainty avoidance users in high trust countries (e.g. Canada and the USA) will provide highest ratings for Information Content over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan)

Partial support. Users in low uncertainty avoidance high trust countries (e.g.Canada and the USA) score higher than other countries. Users in high uncertainty avoidance low trust countries (e.g. Mexico and Chile) are not significantly different to several other countries. Significant between country differences between CAN (mean 5.3) and USA (5.4) with Germany (4.5) and China (4.6) (p = .000). India (4.8)with no significant differences with Japan (4.8), Mexico (4.9) and Chile (5.0). USA has the highest score for Information Content and Germany has the lowest

H2: Low uncertainty avoidance users in high trust countries (e.g. Canada and the USA) will provide highest ratings for Information Design over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan)

Overall support. Users in low uncertainty avoidance high trust countries (e.g. USA)score higher (5.7) than other countries. Significant differences (p = .000) between CAN and USA with Japan (4.4), China (4.5) and Germany (4.8). Chile (5.2) and India (5.1) score lower than Mexico (5.4), but no significant differences. USA has the highest score for Information Design while Japan has the lowest

H3: Low uncertainty avoidance users in high trust countries (e.g. Canada and the USA) will provide highest ratings for Navigation Design over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan)

Partial support. USA (5.8) with highest score. CAN (5.6) same as Mexico (5.6) and India (5.1) is lower than Mexico (5.6). Germany (5.1) significantly different from CAN (p = .034) and USA with Germany (p = .000). Significant differences for CAN and USA with Japan (4.0) and China (4.6) (p=.000). USA has the highest score for Navigation Design and Japan has the lowest

H4: Low uncertainty avoidance users in high trust countries (e.g. Canada and the USA) will provide highest ratings for Visual Design over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan)

Partial support. CAN (5.7) and USA (5.8) have the highest scores. Significantdifferences (p = .000) for CAN and USA with Germany (4.6), China (4.7) and Japan (5.0). USA has highest score for Visual Design while China and Germany have the lowest

H5: Countries within the same GLOBE cluster will exhibit similar responses to website design elements compared to users outside the cluster

Overall support. Based on 12 comparisons in EACH cluster, in North America there are no significant differences; in the Asian cluster only one significant difference for Navigation Design for Japan and China; for Latin America no differences

H6: Low uncertainty avoidance users in high trust countries (e.g. Canada and the USA) will provide highest ratings for Website Trust over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan)

Partial support. CAN (5.5) and USA (5.6) have highest scores. India (5.2) is lower than Chile (5.6) and Mexico (5.3). Significant differences (p = .000) for CAN, USA,and India with Germany (4.9), China (4.4) and Japan (4.3). CAN, USA and Chile have the highest scores and Japan the lowest

H7: Low uncertainty avoidance users in high trust countries (e.g. Canada and the USA) will provide highest ratings for Transaction Security over high uncertainty avoidance users in low trust countries (e.g. Chile and Mexico); with countries that are mixed in uncertainty avoidance and high/low trust scoring in the middle (e.g. India, Germany, China, and Japan)

Limited support. CAN (5.3) and USA (5.3) have the highest scores, with the exception of Japan (5.5). CAN and USA are not significantly different to Mexico (5.0), India (5.0), and Chile (4.9). Significant differences (p = .000) between CAN and USA with China (4.5) and Germany (4.4). India is significantly different from China (p = .040) and Germany (p = .005). Japan has the highest score for Transaction Security and Germany the lowest score

H8: Countries within the same GLOBE cluster will exhibit similar responses for Website Trust and Transaction Security compared to users outside the cluster

Overall support. No significant differences for North American and Latin American clusters. For the Asian cluster there are differences for Transaction Security


of between country differences occur for three of the four design constructs (Navigation Design = 16; Information Design = 14; Vi- sual Design = 12; Information Content = 6). Website Trust was significantly different in 15 instances , and as well 15 between country differences occurred for Transaction Security.

5.1. Results of hypothesis testing

Overall, the results of this investigation are in general alignmen twith the hypotheses as stated. As such, expected user reactions relate to uncertainty avoidance, as well as to predictio ns based on trust and social capital with respect to institutiona l conditions affecting the Internet in the eight countries in this investigation.More specifically, this includes:

(1) Overall, lower uncertainty avoidance groups in high trust countries as in Canada and the USA have the highest scores on the various constructs over those in other countries,although there are some exception s. In fact, for mean scores for all constructs across all countries , participa nts in the USA and Canada have the highest scores with only 2 exceptions (for Security in Japan and Trust in Chile). Please refer to Table 7 for an elaboration of each hypothesis and the level of support received by each. Data is used from Tables 5and 6 to provide an elaboration as to the level of support for each hypothesis.

(2) Of the countries mixed in uncertainty avoidance and high/ low trust scores (India, Japan, Germany , and China), India has surprisingly few differences with the USA and Canada.


In comparison, there are numerous differences between Ger- many, Japan, and China with the other countries and they all tend to score in the lowest ranges.

(3) Clustering theory is overwhelmingl y supported. Of a total of 60 comparisons there were only two differences that occurred within the Asian cultural cluster (for Japan and China). Support is thus provided for Hypotheses 5 and 8.

6. Discussion and conclusion s

The current investiga tion offers a comprehensive insight into website perceptions of 1156 participants located in eight countries.Wide sampling of users in a number of countries offers an oppor- tunity to derive insights about cultural similarities and differenc es as they relate to website design. In addition, we learn more about how institutiona l perspectives and country clustering operate related to user perceptions of websites.

As outlined in this paper, the goals for this project are achieved including:

(1) Hypothesized comparisons for eight countries were based on levels of uncertainty avoidance (Hofstede 1980 ), and overall the prediction that lower uncertainty avoidance cultures score higher for perceptions of website design is supported. Alternate ly, in higher uncertainty avoidance cultures such as in Japan, there is a tendency to score lower on trust. The large number of comparisons as graphica lly depicted in Tables 5 and 6 can be utilized by other researchers as a baseline for how users react in each of the countries





studied concerning website design elements and outcome s.(2) In addition, the research is aimed to consider how country

economic and technolo gical variables might potentially affect user perceptions of an e-commerce website, including website trust and security. It would appear that this is a useful addition to understand ing user website perceptions . Low uncertainty avoidance users in high trust countries do have the highest scores, although high uncertainty avoidance users in low trust countries did not systematically have the lowest scores as predicted. Of interest are the results of countries mixed in uncertainty avoidance and high/low trust (e.g. India, Japan, Germany , and China). As one example, Germany and China are both moderate in uncertainty avoidance but differ substanti ally on social capital and technology-related infrastructure. However, overall they score similarly on most constructs. This would indicate that while the country conditions are very different , overall cultural values tend to determine user perceptions of website design.

(3) This research contributes to understanding how country clustering occurs in the unique context of website design,and the relevance of this for website localization practices.The results are quite remarkable in terms of how countries fall with others in their cultural cluster, given the large number of comparisons .

6.1. Theoretical contribut ions

In recent years, researche rs have explored website design in asingle country context (Flavián et al. 2006, Garrett 2003, Palmer 2002). In some cases user perceptions of website elements have been investiga ted across cultures (Barber and Badre 1998, Cyr et al. 2005, Cyr 2008, Gefen and Heart 2006, Hu et al. 2004, Jar- venpaa et al. 1999 ), although not with a focus on website design and uncertainty avoidance as in the current research. With respect to the four design elements studied in the current investigatio n,lower uncertainty avoidance countries such as Canada and the USA score highest for Informati on Content, Information Design,Navigation Design, and Visual Design. This signifies that users in these countries are more favorable toward each design element for their country website. Hence, users who find website visits less risky and who are less concerned with ambiguit y tend to rate website design elements higher. Overall, results for Canada and the USA are significantly different from Germany and China (moderatein uncertainty avoidance) and Japan (high in uncertainty avoidance). As such, Germany, Japan and China are more concerned about the various design elements as presented. An unexpected result of this research is that no differences in user perceptions were detected between Canada (low uncertainty avoidance, high trust and social capital) with Mexico (high uncertainty avoidance,low trust and social capital) and this finding merits further investigatio n.

Consideri ng both uncertainty avoidance and levels of country institutiona l trust and social capital, there is considerable varia- tion of user perceptions for design elements across countries,thus supportin g the notion that websites require localization of design content for unique cultural groups (Cyr and Trevor-Smi th 2004). These results represent an extension of Cyr et al. (2005)in which design elements were studied and comparisons made between a localized and foreign website of the same vendor. If websites are congruent with user expectati ons, then they are also judged to be more effective (Vyncke and Brengman 2010).

With respect to institutiona lized trust and social capital (Fukuyama 1995 ), as well as related to economic barriers


concerning technology and infrastructu re (Kshetri 2007 ), it would appear these parameters are useful to consider, but may not be as strong a predictor of user perceptions as is culture.To elaborate, in countries that are mixed such as India with low uncertainty avoidance but low connectivity and infrastructure (2.9/10), overall the results are similar to Canada or the USA which are also low in uncertainty avoidance. However, levels of connectivity and infrastructu re are higher for these countries (Canada 7.9/10; USA 8.1/10). This suggests that even though the economics and technolo gical infrastructu re are very different in India from Canada or the USA, this is not enough to instill lower perceptions of website design for users in India.Further, Japan is the country with the highest score for uncertainty avoidance and is high in connectiv ity and infrastructu re (7.5/10). However, for all four design constructs Japan scores lower than Mexico and Chile who are also high in uncertainty avoidance, but lower in connectiv ity and infrastructu re (Mexico3.6/10; Chile 4.6/10). Despite the higher levels of technology in Japan, this is not sufficient to elevate user design perceptions,and we may therefore deduce this is related to the high level of uncertainty avoidance in that country.

Users were also evaluated for their perceptions of Website Trust and Transaction Security, and overall the results are paral- lel to expectati ons for both constructs . That is, Canadians and Americans had the highest user perceptions for Website Trust and Transaction Security. Japan has the lowest score for Website Trust which is in alignmen t with expectations of a country high on uncertainty avoidance, and supports earlier research by Cyret al. (2005) who found Japanese to be least trusting over Cana- dians, Americans or Germans. However, one unexpected outcome is that Japanese users score highest for Transaction Security. In this particular instance, it may be that although users do not trust the website, the higher level of connectivity and infrastructu re is a signal to users in Japan that website transacti ons are relatively secure.

While the cultural classifications from Hofstede (1980) havebeen used by a variety of researchers including those who study website design, a fruitful addition to the current research is the evaluation of country responses based on Clustering Theory and the GLOBE study. Based on the GLOBE cultural clusters predicted results were obtained – now in a new context of website design.That is, across all six constructs investigated, for the North American and Latin American clusters there are no significantdifferenc es. These are remarkabl e findings, given the number of cross-count ry comparisons involved . In the Confusion Asian cluster, Japan and China are likewise similar although there are differences for Transaction Security and Navigation Design. These differenc es may be related to the variances in country connectivity,infrastructu re and the digital environment as speculate d earlier.Based on these results, it would appear the GLOBE clusters afford a useful conceptual classification system for use in future research for assessing between country differences related to website design or other topics.

To summari ze, to my knowledge this is the first research study to investigate user perceptions of website design in the context of both cultural differenc es for uncertainty avoidance,as well as related to institutional paramete rs such as institutional trust and social capital stemming from rankings that include country connectivity and infrastructu re. One important theoretical implication that emanate s from this research is that culture is a more important predictor of user perceptions than institutiona lized parameters (i.e. connectiv ity and infrastructure).More specifically, if we consider the cultural clusters as intro- duced by House et al. (2002), of 60 comparis ons, 58 conform





to cultural predictio ns. Likewise, referring to mean scores for each construct, Canada and the USA (both highest in uncertainty avoidance) have the highest scores for all constructs across all countries with only two exceptions (Japan for Security and Chile for trust) as outlined in Table 5. Alternate ly, for the two countries both moderate in uncertainty avoidance (Germany and Chi- na) but with widely different institutiona l parameters – they score similarly – indicating culture to be the stronger predictor of user perceptions .

Regardless of the preceding, it is also possible these institutionalized parameters do have some impact such as is the case with transaction security. This notion is supported by Steenkamp and Geyskens (2006) who implied that country characterist ics can affect perceived website value. So while there are some indications that social capital and institutiona lized country characterist ics may affect user perceptions of website design – there is much scope for other researchers to investigate this further – not only in the context of website design, but in other areas as well. A second important development from this research is the strong clustering of countries with respect to website design. This has important implication s for compani es who wish to provide users with culturally appropriate Web content based on country clusters,as opposed to individual country specifications.

6.2. Practical contribution s

The current research reinforces that attention is paid by Web designers and strategists to different user perceptions in different countries (as per Barber and Badre 1998, Singh et al. 2003, Vyncke and Brengman 2010 ) – especiall y in higher uncertainty avoidance countries where perceptions of website design are lower than in lower uncertainty avoidance cultures. Concerning the design features investigated in this research, for Information Content and Information Design, online product information should be accu- rate, complete, detailed, and logically presented and organized.More specifically, in high uncertainty avoidance cultures, local ter- minology, customer testimonials, company information , and toll- free numbers to access additional information are important (Singh et al. 2003 ). In addition, using headers and sub-headers on webpages to break up text and product information assists the user to find relevant information.

Regarding Navigatio n Design, consistency of page layout and quick access to navigationa l features are universa lly desirable. In the current study, Japanese users had the lowest perceptions for Navigation Design, indicating effective and efficient navigation would be very important for this group. Navigation is highly related to trust for Chinese (Cyr 2008 ), which suggests users from this country expect websites that are transparent and clear. In Chi- na, links to local websites and guided navigation are desirable (Singh et al. 2003 ). To encourag e ease of navigation the search bar should be obvious. In addition, browsing refinements can be of- fered by category or subcateg ory. For instance, filters of a product line will allow the user to compare products, and quickly generate pages of relevant items. More specifically, if an online vendor is selling shoes, then navigation can lead to attribute refinementssuch as color, shoe size, etc.

Visual Design preferenc es likewise vary across countries, and visual components and aesthetics of the website are especiall yimportant for Chinese and Japanese (Cyr et al. 2005, Cyr 2008 ).Hence in higher uncertainty avoidance countries, website designers should pay particular attention to colors, images, shapes and overall graphical look of websites. Color is important and con- veys meaning to users. For example, on banking websites in In- dia colors often used are red and saffron (Smith et al. 2004 ). The


State Bank of India uses Gandhi’s image and the map of India to elicit patriotic feeling and to signify that the bank serves all Indi- ans whether in India or abroad (Smith et al. 2004 ). High quality images are important, and for products it is useful to include product shots from multiple angles. Provide photos with different color combinations . Show clothing on models to create image appeal.

Website localization carries a substantial cost to companies,particular ly those companies which operate in multiple locations (i.e. in 2012 Coca-Cola had as many as 157 websites ). Based on the current data, and with respect to the GLOBE clusters, there are certain countries where user perceptions are the same as within the North American or the Latin American clusters. Coca Cola segments its markets into six geographi cal regions with multiple websites in each: North America (4), Latin America (22), Europe (35), Eurasia (32), Africa (52), and Asia Pacific(12). While some adaptation within a cluster is necessar ysuch as language, other elements may be common such as color preferenc es and only require minimal modification. Hence,‘‘cluster localization ’’ serves the purpose of providing some degree of cultural adaptation to user groups, but with a substantial cost savings to online vendors over deep localization procedures .

6.3. Limitations and directions for future research

A large and diverse sample population is a positive feature of this investigation. Data was collected in eight countries with atotal of 1156 participants . While data might have been collected on espoused cultural values of each respondent, the countries in this sample are chosen for their diversity. Further, the methodol -ogy of using pre-determ ined countries as a proxy for culture is consisten t with previous research, including research on website design (e.g. Gefen and Heart 2006, Jarvenpaa et al. 1999, Simon 2001). As outlined in Appendix A, countries included in this research are representative of both higher and lower levels of connectivity and infrastructure as well as e-business adoption .Rather than a student only population, participa nts are from avariety of sources including companies, universities, and institutes which offers generalizabi lity of the findings. However, alimitatio n of the sample is that some of the countries had relatively small sample sizes with the smallest number of participants being 48 in Chile. Additionally, the sample is not truly random since an online survey was circulated through various avenues with no possibilit y to determine the number of respon- dents compared to the number of non-respon dents. Finally, asingle-m ethod survey was used to collect data, rather than amultiple methods approach. In the future, similar research would benefit from the use of multiple methodologies including questionnaire s, eye-tracking, and interviews.

In terms of limitations to the research, a single vendor website (SonyStyle) was used. In addition, a single task was used (i.e.searching for a cell phone for hypothetical purchase on a product-based website). No actual purchase was required. While this procedure is consisten t with other e-commerce research, this may limit transferabili ty of the findings to actual e-comme rce situations. In the future, similar research could be expanded to include a greater variety of tasks on both service and product websites , and a larger sample of websites.

Based on the successfu l use of the GLOBE clusters for country comparis ons in this study, it is recommend ed that additional studies concerned with culture likewise adopt this framework. Further,it would be interesting to utilize the country indicators (inAppendix A) to further explore similarities and differences





between countries score highly on Internet use, connectivity and infrastructu re, digital legal environm ent, and consumer and business electronic adoption with those countries with less favorable scores. Since this is the first study to examine Hofstede’s cultural dimensions in conjunction with institutiona lized country conditions, it is suggested that future research examine additional topics using this dual framework.

Appendi x A. Country indicators

Country Indicators

Population a

(Millions)Surface area a (sq.km)

GDP a

(Billions)Internet users b (per1000 people)

Conninfra(rati

CAN 32.6 9984.7 1251.5 520 7.90USA 299.0 9632.0 13201.8 630 8.10IND 1109.8 3287.3 906.3 55 2.90GER 82.4 357.0 2906.7 455 7.10JAP 127.6 377.9 4340.1 668 7.50MEX 104.2 1958.2 839.2 181 3.55CHI 16.5 756.6 145.8 172 4.60CHN 1311.8 9598.1 2668.1 85 3.50

NB: CAN = Canada; USA = United States of America; IND = India; GER = Germany; JAP = J[http://www.eiu.com/site_info.asp?info_name=eiu_2007_e_readiness _rankings&rf=0 ]

a Year 2006 Figures – From the World Bank.b Year 2005 Figures – From the World Bank.c Year 2007 Figures – From the 2007 e-Readiness Rankings: Raising the Bar.d Connectivity and Infrastructure, Legal Environment as well as Consumer and Busine

Appendi x B. Participant demographi cs

Demograph ic Canada n = 312

USA n = 197

Indn =

Mean age 30.25 29.1 30.Gender M: 149 M: 81 M:

F: 163 F: 116 F: 9Mean number of years shopping online 3.15 5.8 3.1Mean number of online purchase s last year 7.7 15.6 7.7Education level a HS: 119 HS: 87 HS

U: 126 U: 64 U:G: 47 G: 39 G:T: 18 T:7 T:

Has previously shopped at Sony website Yes: 23 Yes: 29 YesNo: 287 No:

168 No

Prefer to buy known brands from arecognized company when shopping online

Yes:278

Yes:178

Yes

No: 32 No: 19 No

a HS = High School; U = Undergraduate; G = Graduate; T = Technical.


Acknowledgeme nts

This research was funded by the Social Sciences and Humanities Research Council of Canada. Sincere appreciation is extended to Milena Head, who provided insight and assistance related to analysis of the data. Additional research assistance was provided by Eric Lim and Alex Ivanov.

ectivity &structure c

ng of 1–10) d

Digital legal environment c

(rating of 1–10) d

Consumer & business electroni c adoption c

(rating of 1–10)d

8.95 8.60 9.00 9.50 5.50 4.50 8.25 8.45 8.00 8.30 7.40 6.20 8.00 6.40 3.60 4.55

apan; MEX = Mexico; CHI = Chile; CHN = China

ss Adoption are rated on a scale of 1–10 in ascending order of maturity.

ia 106

Germany n = 122

Japan n = 78

Mexico n = 71

Chile n = 48

China n = 222

Total n = 1156

5 26.2 27.3 23.9 29.6 25.2 27.4 16 M: 57 M: 47 M: 30 M: 11 M: 114 M: 456 0 F: 61 F: 31 F: 41 F: 37 F: 109 F: 622

4.1 3.5 2.6 3.6 2.7 3.8 10.2 7.9 6.0 4.9 8.4 9.2 : 3 HS: 4 HS: 6 HS: 5 HS:

10 HS: 35 HS: 263

33 U: 90 U: 47 U: 51 U: 24 U: 99 U: 487 62 G: 21 G: 20 G: 15 G: 11 G: 78 G: 273 8 T: 3 T: 5 T: 0 T: 3 T: 11 T: 50 : 9 Yes: 5 Yes: 9 Yes: 3 Yes: 0 Yes: 39 Yes: 98

: 97 No: 113 No: 69 No: 68 No:48

No:184

No: 980

: 97 Yes: 86 Yes:66

Yes: 66 Yes:44

Yes:121

Yes: 875

: 9 No: 32 No: 12 No: 5 No: 4 No:102

No: 203


http://www.zing.ncsl.nist.gov/hfweb/att4/proceedings/barber/



Appendix C. Questionnaire items and sources

Information Content (Source: Egger 2001; Marcus and Gould 2000; Cheskin 1999, 2000 )InfoCont-1. The information provided at this site is complete .InfoCont-2. The information provided at this site is sufficient.InfoCont-3. The information provided at this site is effective.InfoCont-4. The website adequately meets my informat ion needs.

Information Design (Source: Cyr 2008; Egger 2001; Cheskin 1999, 2000 )InfoDes-1. I find the information logically presented.InfoDes-2. I find the information on this site to be well organized.InfoDes-3. All product options, product attributes and product information are well presented.

Navigation Design (Source: Cyr 2008; Egger 2001; Cheskin 1999, 2000 )NavDes-1. I can easily navigate this site.NavDes-2. I find this website easy to use.NavDes-3. This site provides good navigation facilities to information content.

Visual Design (Source: Cyr 2008; Egger 2001; Marcus and Gould 2000; Cheskin 1999, 2000 )VisDes-1. The screen design (i.e. colors, images, layout etc.) is attractive.VisDes-2. The website animations are meaningful .

Website Trust (Source: Cyr et al. 2008, 2007; Gefen 2000; Yoon 2002 )Trust-1. I can trust this website.Trust-2. I trust the information presented on this website.Trust-3. I trust the transaction process on this website.

Transaction Security (Source: Yoon 2002, Torkzadeh and Dhillon 2002 , McKnight et al. 2002 )Sec-1. If I buy a product from this website, I believe it would be a secure transaction.Sec-2. The third party assurance seals on this website make me feel this website is secure.Sec-3. The level of security for personal information on this site is good.

Note: The questionnaire consisted of the following statements that were rated on a 7-point Likert scale from ‘very strongly disagree’ to ‘very strongly agree’.


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Website design, trust and culture: An eight country investigation

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