The Impact of Language on Website Use and User Satisfaction

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The Impact of Language

on Website Use

and User Satisfaction

Anett Kralisch &

Veit Köppen

Institute of Information Systems

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Motivation:

the Tower of Babel on the Internet

ENGLISH PORTUGUESE URDU FRENCH THAI QUECHUA 2 Institut für Wirtschaftsinformatik

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Motivation:

the Tower of Babel on the Internet

• > 6000 languages spoken worldwide

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4

Institut für Wirtschaftsinformatik

Humboldt-Universität zu Berlin Kralisch & Köppen 2005

Motivation:

the Tower of Babel on the Internet

• > 6000 languages spoken by potential Internet users

• website translation / adaptations decisions often have significant financial ramificatiants

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Motivation:

the Tower of Babel on the Internet

• website translation / adaptations decisions often have significant financial ramifications

• language as a barrier to accessing information / participation on the Internet (digital divide)

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Motivation:

the Tower of Babel on the Internet

• website translation / adaptations decisions often have significant financial ramifications

• language as a barrier to accessing information / participation on the Internet (digital divide)

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Motivation:

the Tower of Babel on the Internet

• website translation / adaptations are often important investment decisions

• language as barrier to information access / citizen participation on the Internet (digital divide)

How does language affect website use ?

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Motivation:

the Tower of Babel on the Internet

• website translation / adaptations are often important investment decisions

• language as barrier to information access / citizen participation on the Internet (digital divide)

How does language affect website use ?

Which languages should be considered for translation ?

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Agenda

1. The model

2. The variables

4. Preliminary Results

3. Data & Measures

5. Outlook

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Agenda

1. The model

2. The variables

4. Preliminary Results

3. Data & Measures

5. Outlook

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1. The model

Internet

Language Offer

Language

Proficiency Level

A Website‘s

perceived

net value

Website Use

.

Satisfaction

.

+

-+

+

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Agenda

1. The model

2. The variables

4. Preliminary Results

3. Data & Measures

5. Outlook

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2. The variables

Internet

Language Offer

Language

Proficiency Level

A Website‘s

perceived

net value

Website Use

.

Satisfaction

.

+

-+

+

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2. The variables: net value

language-related

NET VALUE

of a website = of information gathering

VALUE

-

COSTS

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2. The variables: antecedents

Internet

Language Offer

Language

Proficiency Level

A Website‘s

perceived

net value

Website Use

.

Satisfaction

.

+

-+

+

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2. The variables: antecedents

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2. The variables: antecedents

NET VALUE = VALUE _- _COSTS

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2. The variables: antecedents

COGNITIVE EFFORT

• Revised-Hierarchy-Model (Dufour & Kroll 1995)

• higher cognitive effort required

for non-native language processing / at a lower language-proficiency level

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2. The variables: antecedents

• Revised-Hierarchy-Model (Dufour & Kroll 1995) • higher cognitive effort

TIME

• e.g. Hahne 2001

• slower language processing required in a non-native language / at a lower language-proficiency level

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2. The variables: antecedents

• Revised-Hierarchy-Model (Dufour & Kroll 1995) • higher cognitive effort

H1: A user‘s perception of a website‘s language-related net value increases with his/her language proficiency.

TIME

• e.g. Hahne 2001

• slower language processing

in a non-native language / at a lower language-proficiency level

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2. The variables: antecedents

NET VALUE = VALUE - COSTS

Internet Language Offer

• How much information is offered in the user‘s native language on the Internet?

Higher value

if few websites

are offered in that language

Lower value

if many websites

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2. The variables: antecedents

H2: A user‘s perception of a website‘s language-related net value

decreases with an increase in the perceived amount of information offered on the Internet in the site‘s language.

NET VALUE = VALUE - COSTS

Internet Language Offer

• How much information is offered on the Internet in the user‘s native language?

Higher value

if few websites

are offered in that language

Lower value

if many websites

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2. The variables

Internet

Language Offer

Language

Proficiency Level

A Website‘s

perceived

net value

Website Use

.

Satisfaction

.

+

-+

+

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2. The variables: outcomes

Information Foraging Theory (Pirolli, Card 1995): • Link is followed if: costs < expected value.

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2. The variables: outcomes

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2. The variables: outcomes

Website Use:

• How many pages are accessed?

(User decides about following the link before the page is visited.)

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2. The variables: outcomes

Information Foraging Theory (Pirolli, Card 1995): : • Link is followed if: costs < expected value.

Website Use:

• Which pages are accessed?

(User decides about the length of a page visit while the page is visited.)

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2. The variables: outcomes

H3: The number of pages accessed by a user on a site increases with the perceived language-related net value of that site.

Website Use:

(User decides about the lenght of a page visit while the page is visited.)

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2. The variables: outcomes

H3: The number of pages accessed by a user on a site increases with the perceived language-related net value of that site.

Website Use:

(User decides about the lenght of a page visit while the page is visited.)

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2. The variables: satisfaction

Technology Acceptance Model (Davis 1993): • Perceived usefulness positive attitude

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2. The variables: satisfaction

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2. The variables: outcomes

H5: User satisfaction increases with perceived net value.

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Agenda

1. The model

2. The variables

4. Preliminary Results

3. Data & Measures

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3. Data & Measures

1. Questionnaire: all perceptual & attitudinal variables

• Multilingual questionnaire

• Likert or semantic differential scales

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3. Data & Measures

1. Questionnaire: all perceptual & attitudinal variables • Multilingual questionnaire

• Likert or semantic differential scales:

2. Logfiles: extent of website use

• Linked to the questionnaire trough session-IDs

• IP-address ( geographical information)

• requested page, time of access, etc.

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3. Data & Measures

• Likert or semantic differential scales: 2. Logfiles: extent of website use

• Linked to the questionnaire trough session-IDs • IP-address ( geographical information)

3. Webpage analysis: simplified “depth“ of processing

• Self-developed software measures web page complexity

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3. Data & Measures

1. Internet statistics: cross-check with self-reports

• Information about language offer on the Web

• e.g. Cyber Census Report; Mikami & Suzuki 2004; DMOZ.org

World Statistics

3. Webpage analysis: simplified “depth“ of processing • Self-developed software measures web page complexity

WEBPAGE

OTHER

SOURCES

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3. Data & Measures

1. Internet statistics: cross-check with self-reports • Information about language offer on the Web

• e.g. Cyber Census Report; Mikami & Suzuki 2004; DMOZ.org World Statistics

3. Webpage analysis: simplified “depth“ of processing • Self-developed software measures web page complexity

2. Language Status: cross-check with self-reports

• Which official language(s) in which region?

• Self-developed database

WEBPAGE

OTHER

SOURCES

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Agenda

1. The model

2. The variables

4. Preliminary Results

3. Data & Measures

5. Outlook

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4. Preliminary Results

• data from a pretest-questionnaire • simplified data analysis

• patients only (due to significant correlations between language and patients/physicians) • N=83

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4. Preliminary Results

• data from a pretest-questionnaire • simplified data analysis

• patients only (due to significant correlations between language and patients/physicians) • N=83

Preliminary results: no significant impact

Website Use

.

Language Proficiency Level

H3 H1 A Website‘s perceived net value H5 H2

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4. Preliminary Results

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Tendencies:

Internet Language Offer Language Proficiency Level

A Website‘s

perceived net value

Website Use

.

Satisfaction .

β = 0.182 (p=0.163)

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4. Preliminary Results

A Website‘s

perceived net value

Website Use

.

Satisfaction .

β = 0.146 (p=0.462)

β = 0.162 (p=0.417) Tendencies:

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4. Preliminary Results

A Website‘s

perceived net value

Website Use

.

Satisfaction .

β = 0.286 (p=0.151) Tendencies:

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4. Preliminary Results

A Website‘s

perceived net value

Website Use

.

Satisfaction .

+

-Tendencies:

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4. Preliminary Results

A Website‘s

perceived net value

Website Use

.

Satisfaction .

+

-Website culturally adapted to the major language groups?

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Agenda

1. The model

2. The variables

4. Preliminary Results

3. Data & Measures

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Outlook

• Final questionnaire with revised questions is currently posted on the website. • Logfiles are registered at the same time.

• Validation of Internet statistics and language status data for predicting website use and satisfaction.

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Outlook

• Final questionnaire with revised questions is currently posted on the website. • Logfiles are registered at the same time.

• Validation of Internet statistics and language status data for predicting website use and satisfaction.

Future questions to answer:

• The role of language associated values (e.g. Dmoch, 1997)

e.g. French – elegance; English - modernity

• The role of the number of languages on one website. • Personal language aspects (language fear / motivation).