Cultural Preference Identification for Cross-cultural Website Design

Gatis Vitols

, Irina Arhipova

and Yukako Hirata

Faculty of Information Technologies, Latvia University of Agriculture, Liela 2, Jelgava, Latvia

Hewlett-Packard Japan, Ltd., 2-2-1, Ojima, Koto-Ku, Tokyo, Japan

Keywords: Cross-cultural design, Website, Usability.

Abstract: In this article analysis of available cross-cultural website design model methods for cultural preference

identification is performed. Users from various cultures not only speak different languages, but also think

and act differently. These differences impact process of how users perceive and use information systems,

including websites. Therefore there is emerging need for models, methods and technologies for design of

usable cross-cultural websites. One of the main tasks relating to usable cross-cultural website design is to

gather data about cultural preferences for a selected culture. We propose to extend the existing methods for

cultural preference identification with additional cultural dimension theories and methods for extraction of

data from culture preferred products.

1 CROSS-CULTURAL WEBSITE

DESIGN

Since the introduction of the Internet, various

services have been created and become available for

users around the world. World Wide Web and

websites became a widespread communication tool.

Initially, Internet services, including websites,

were developed mainly in English language

typically for users from western countries. However

only 8-10% of world population and 35% of website

users use English as their primary communication

language (Takasaki & Mori, 2007).

It is concluded by various authors that such

cultural differences as language, thinking patterns

and communication style can significantly impact

website usability (Rau et al., 2011). Because of such

conclusions there are increased demands for

research about cross-culturally usable website design

models, methods and technologies.

Though, as Jasem Alostath with co-authors

(Alostath et al., 2009) admit, for website designers

there is almost no unified models, methods and

tools, that would support cross-cultural website

design. Alostath also admits that there are no sets of

published guidelines that would gurantee cross-

cultural usability.

One of main challanges for website designers is

to aquire detailed data about cultural preferences of

certain culture in a website design requirements

stage (Kondratova et al., 2007; Rau et al., 2011).

Such cultural preferences include for example

websites colour, layout and information density

preferences.

The aim of this article is to summarize and

analyse the existing methods for cultural preference

identification for cross-cultural website design and

develop an improved methods. To reach this aim the

following tasks are brought forward:

1. Analyse previous researches that relate to

cross-cultural website design and summarize

methods for cultural preference identification.

2. Based on analysis and synthesis of

literature propose improved methods for cultural

preference identification for cross-cultural website

design.

2 CULTURAL PREFERENCE

IDENTIFICATION METHODS

From analysis of literature (Hsieh et al., 2009;

Kondratova et al., 2007; Rau et al., 2011), it can be

concluded that there are two main approaches which

can be used for usable cross-cultural website design.

One is to use existing theoretical studies about

cultures and the other is to involve directly into life

of culture with testing and observing users. The

latter approach usually requires long-term

involvement, which is often not affordable for

Vitols G., Arhipova I. and Hirata Y..

Cultural Preference Identiﬁcation for Cross-cultural Website Design.

DOI: 10.5220/0003968600990102

In Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS-2012), pages 99-102

ISBN: 978-989-8565-12-9

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

website designers.

Instead, most cross-cultural design methods

recommend using data from cultural theories

combined with published empirical studies.

Some authors, including Gevorgyan and

Manucharova (Gevorgyan & Manucharova, 2009)

successfully applied cultural dimension theories

from psychology, sociology and communication

science for cultural preference identification in

process of cross-cultural website design.

Well known studies that are used for cross-

cultural information system design are published by

authors Geert Hofstede (Hofstede et al., 2010) and

Edward Hall (Hall, 1976; Hall & Hall, 1990). These

authors propose certain dimensions for culture

examination and classification, such as time

perception, power distance, uncertainty avoidance

and other.

Zahedi with co-authors (Zahedi et al., 2001) in

their web design conceptual model for cultural

preference identification recommend to use

theoretical studies such as Hall's time orientation

dimension and all Hofstede's dimensions.

Jagne with co-authors (Jagne et al., 2004) in their

cross-cultural interface design strategy for cultural

preference identification recommend designers to

involve into target cultures with website audits and

interviews with usability experts from those target

cultures. Some authors also propose to investigate

existing empirical researches, such as published by

Barber and Badre (Barber & Badre, 1998).

Smith with co-authors (Smith et al., 2004) in

their process model for usable cross-cultural website

development, propose to audit target culture

websites, investigate Hofstede's culture dimensions

and observe local users.

Hsieh et al., (2009) in their theoretical model for

cross-cultural website design, for cultural preference

identification propose to audit target culture

websites, investigate existing empirical studies and

use Hall's context dimension and all Hofstede's

dimensions.

Many similarities can be seen in methods for

cultural preference identification by previously

mentioned authors.

Most of published methods agree on such steps

as target culture website audit and use of cultural

dimensions by either Hofstede or Hall or combined.

3 IMPROVED CULTURAL

PREFERENCE

IDENTIFICATION PROCESS

We would like to offer expand existing cultural

preference identification process by adding a few

factors that emerge from literature reviews.

First of all, agreement can be found that Hall and

Hofstede cultural dimensions are successfully used

in cross cultural website design. However, recent

studies, such as performed by Ying and Lee (Ying &

Lee, 2008) show that there is one more culture

dimension that should be considered as important for

website designers. Ying and Lee empirical study

showed that Nishbett's (Nishbett, 2003) proposed

culture division based on style of thinking have an

impact on how users from various cultures scan

information on websites. Based on whether thinking

style in culture is holistic or analytic, website

designers should consider how to organize website

layout.

Therefore we suggest using Hofstede, Hall and

Nishbett dimensions for cultural preference

identification. In addition to target culture website

audit, we would like to suggest methods for target

cultural preference identification. Based on culture

preference identification results of previous studies

(Braun & Rose, 2007), we would like to suggest

applying methods from Quick and Dirty User

Profiling Technique (QDUPT) introduced by

Chavan (Chavan, 1999).

Most cultural dimensions can be divided in two

groups: subjective and objective. This division is

well known and used in cross-cultural researches

(Gould, 2005). Objective dimensions are those that

can be easily identified, such as language in which

target culture speaks. Subjective dimensions are

more complicated to identify and include, for

example, target culture information scanning

preferences.

As a result, in order to identify cultural

preferences we propose to execute following

methods:

• Culture life style data collection.

• Identification of objective dimensions.

• Identification of subjective dimensions.

• Target culture website examination.

3.1 Culture Life Style Data Collection

To gather data about target culture life style and

certain cultural preferences, there is a need to

analyse data about target culture success products,

ICEIS2012-14thInternationalConferenceonEnterpriseInformationSystems

100

movies and music videos from past 5 years (Braun

& Rose, 2007; Chavan, 1999). Analysis of collected

data need to be performed to extract attributes that

relate to website design. For example, find anwers

about mobile device success or what are the colour

preferences.

We suggest to perform manual content analysis

of gathered data with combination of tool that allow

to extract colour preferences from videos. Such tool

prototype has been developed for this research in

programming language Processing.

3.2 Identification of Objective

Dimensions

After reviewing literature on objective dimensions

(Gould, 2005; Kondratova et al., 2007; Rau et al.,

2011), we found that most common objective

dimension classification for website design is:

language, format, graphics, colour and layout.

Partly data about objective dimensions can be

acquired when performing culture life style data

collection and analyse literature about target culture.

For example Marcus and Baumgartner (Marcus &

Baumgartner, 2004) advice for this purpose to use

The World Fact Book published and maintained by

the Central Intelligence Agency.

3.3 Identification of Subjective

Dimensions

To identify subjective culture dimensions we

propose to analyse Hofstede's, Nishbett's and Hall's

published researches. Also, other author theoretical

and empirical studies can be used to confirm target

culture subjective dimensions. For example, if we

analyse Japanese culture subjective dimensions, we

find that Japanese culture, for example, is high

power distance, high context, holistic thinking and

masculine culture.

After investigating characterictics gathered from

analysis of subjective dimensions, guidelines for

website designers can be determined. Certain such

guidelines exist and are published (Ahmed et al.,

2009). However, there is no central repository for

such guidelines available.

3.4 Target Culture Website

Examination

Tipically target culture website examination or audit

is performed by or with expert from target culture

(A. Smith et al., 2004). For this process usually

certain group of websites is selected. Usually those

websites are most popular in target culture or

popular in certain field, such as, for example, most

popular target culture restaurant websites. For data

gathering we suggest using website statistics

services provided by companies such as Google or

Amazon, which has been succesfully applied in

previous researches (Kondratova et al., 2007; Vitols

et al., 2011). Content analysis usually is chosen as a

method for evaluation and extraction of data.

Extracted data usually help to identify target culture

objective dimensions, such as website font or

character encoding preferences.

Kondratova and Goldfarb (Kondratova et al.,

2007) for extraction of colour and font preferences

advise to use a tool allowing to scan target culture

websites based on website country domain and

analyse HTML and CSS codes for colour codes and

fonts. However, as those authors admit, this tool

cannot read colour from images and only

approximately can determine colour distribution in

websites. For example, if the website background is

white and there is one letter in black, that tool will

output same colour distribution in ratio 50% black

and 50% white. So for our method we suggest to use

such tool only as a reference information, but main

evaluation has to be performed manually. More

detailed target culture website examination process

is described in our previous paper (Vitols et al.,

2011).

4 CONCLUSIONS

From summarization of methods for cultural

preference identification, there is a seen similarity

that most authors propose to use cultural theories by

researchers such as Hofstede and Hall, combined

with target culture website examination.

Our method, besides evaluation of Hofstede and

Hall dimensions, include additional analysis of

research results by Nishbett on culture thinking

style, which is proven to be an important cultural

dimension that relates to how users scan information

in websites.

Our added method from Chavan's QDAPT

technique can help website developers to gather

additional data such as colour preferences.

As further steps we suggest evaluating those

collected data with usability experts from a target

culture.

Developed method will be applied for Japanese

cultural preference identification. To execute the

method, we will gather data about Japanese success

products from Japan's main advertisement company

CulturalPreferenceIdentificationforCross-culturalWebsiteDesign

101

Dentsu and magazine's Nikkey Trendy annual

reports. To gather data about successful movies, and

top target culture websites, we will use statistics

provided by company Amazon.

ACKNOWLEDGEMENTS

Funding support for this research provided by

Europe Social Fund program “Support for doctoral

studies in LUA”, agreement 2009/0180/1DP/

1.1.2.1.2/09/IPIA/VIAA/017.

REFERENCES

Ahmed, T., Mouratidis, H., & Preston, D. (2009). Website

Design Guidelines: High Power Distance and High-

Context Culture. International Journal of Cyber

Society and Education, 2(1), 47-60.

Alostath, J., Almoumen, S., & Alostath, A. (2009).

Identifying and Measuring Cultural Differences in

Cross-Cultural User-Interface Design. In Aykin, N.

(Ed.), Proceedings of Third International Conference

on Internationalization, Design and Global

Development, IDGD 2009 (pp. 3-12). San Diego:

Springer-Verlag Berlin Heidelberg.

Barber, W., & Badre, A. (1998). Culturability: The

Merging of Culture and Usability. Proceedings of the

4th Conference on Human Factors and the Web.

Basking Ridge: AT&T Labs.

Braun, B., & Rose, K. (2007). Localization Issues: A

Glimpse at the Korean User (From the Western

Perspective). In Aykin, N. (Ed.), UI-HCII’07

Proceedings of the 2nd International Conference on

Usability and Internationalization (pp. 3-12). Beijing:

Springer-Verlag Berlin Heidelberg.

Chavan, A. L. (1999). A Quick and Dirty User Profiling

Technique. In Prabhu, G. & De Galdo, E. (Eds.),

Designing for Global Markets 1, IWIPS 1999, First

International Workshop on Internationalisation of

Products and Systems (pp. 79-93). New York:

Backhouse Press.

Gevorgyan, G., & Manucharova, N. (2009). Does

Culturally Adapted Online Communication Work? A

Study of American and Chinese Internet Users’

Attitudes and Preferences Toward Culturally

Customized Web Design Elements. Journal of

Computer Mediated Communication, 14(2), 393-413.

Gould, E. W. (2005). Synthesizing the Literature on

Cultural Values. In Aykin, N. (Ed.), Usability and

Internationalization of Information Technology (pp.

79-120). New Jersey: Lawrence Erlbaum Associates,

Inc.

Hall, E. T. (1976). Beyond Culture (p. 320). New York:

Anchor Books.

Hall, E. T., & Hall, M. R. (1990). Understanding Cultural

Differences. Yarmouth: Intercultural Press Inc.

Hofstede, G., Hofstede, G. J., & Minkov, M. (2010).

Cultures and Organizations: Software for the Mind

(3rd ed., p. 576). New York: McGraw-Hill.

Hsieh, H. C., Holland, R., & Young, M. (2009). A

Theoretical Model for Cross-Cultural Web Design. In

Kurosu, M. (Ed.), Proceedings of the First

International Conference on Human Centered Design

HCD09 (pp. 712-721). San Diego: Springer-Verlag

Berlin Heidelberg.

Jagne, J., Smith, S. G., Duncker, E., & Curzon, P. (2004).

Cross-Cultural Interface Design Strategy (p. 8).

London.

Kondratova, I., Goldfarb, I., & Aykin, N. (2007). Color

Your Website: Use of Colors on the Web. In Aykin,

N. (Ed.), Usability and Internationalization. Global

and Local User Interfaces (Vol. 4560, pp. 123-132).

Berlin: Springer Berlin Heidelberg

Marcus, A., & Baumgartner, V.-J. (2004). A Practical Set

of Culture Dimensions for Global User-Interface

Development. In Masoodian, M., Jones, S., & Rogers,

B. (Eds.), Proceedings of 6th Asia Pacific Conference,

APCHI 2004 (pp. 252-261). Rotorua: Springer-Verlag

Berlin Heidelberg.

Nishbett, R. (2003).

The Geography of Thought: How

Asians and Westerners Think Differently...and Why (p.

275). New York: The Free Press.

Rau, P.-L. P., Plocher, T., & Choong, Y.-Y. (2011). Cross-

Cultural Web Design. In Proctor, R. & Vu, K.-P.

(Eds.), Handbook of Human Factors in Web Design

(pp. 677-698). Boca Raton: CRC Press.

Smith, A., Dunckley, L., French, T., Minocha, S., &

Chang, Y. (2004). A Process Model for Developing

Usable Cross-Cultural Websites. Interacting with

Computers, 16(1), 63-91.

Takasaki, T., & Mori, Y. (2007). Design and Development

of a Pictogram Communication System for Children

Around the World. IWIC’07 Proceedings of the 1st

International Conference on Intercultural

Collaboration (pp. 193-206). Kyoto: Springer-Verlag

Berlin Heidelberg.

Vitols, G., Arhipova, I., & Hirata, Y. (2011). Evaluation of

Cross-Cultural Web Information System Design

Guidelines. In Zhang, R., Cordeiro, J., Li, X., Zhang,

Z., & Zhang, J. (Eds.), Proceedings of the 13th

International Conference on Enterprise Information

Systems, ICEIS 2011 (pp. 275-280). Beijing:

SciTePress.

Ying, D., & Lee, K.-P. (2008). A Cross-Cultural

Comparative Study of Users’ Perceptions of a

Webpage: With a Focus on the Cognitive Styles of

Chinese, Koreans and Americans. International

Journal of Design, 2(2), 19-30.

Zahedi, F. “Mariam,” Van Pelt, W., & Song, J. (2001). A

Conceptual Framework for International Web Design.

IEEE Transactions on Professional Communication,

44(2), 83-103.

ICEIS2012-14thInternationalConferenceonEnterpriseInformationSystems

102