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Measuring the global readiness of airline websites:

Are they speaking the world’s languages?

Peter O'Connor & Zaheer A. Shaik

ESSEC Business SchoolParis, France

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Agenda• Introduction

– Inspiration for GRI, Glocalization, History of GRI, Limitation of previous studies, Language weights

• Parameters– Language & Content, Means of payment, Bookings engine, Address

elements, Currency, Email support, Social media, Alliances

• Research method– Criteria used for evaluation

• Results

• Contribution & Conclusion

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INTRODUCTION

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Inspiration for GRI

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Glocalization

• Dochakuka (meaning indigenization)• Relevance to tourism • Airlines

– try to be global to achieve economies of scale

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History of GRI

• Augustine, Surynt, and Jens (2008)

• O'Connor (2011)

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Why?

• Measures & Indices aid stakeholders in understanding the environment

• CPI & GDI

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Limitation of previous GRI studies

• Language given equal weight

Parameters Original GRI GRI of hotel websites GRI of airline websites

Language Yes Yes Yes (modified)

Content No Yes Yes

Payment option Yes Yes Yes

Bookings option No Yes Yes

Address elements Yes Yes Yes

Logistics/shipping Yes Yes No

Currency Yes Yes Yes

Email support No No Yes

Social media links on the website No No Yes

Part of alliances No No Yes

Website with English and Korean versions is typically rated globally ready on a par

with another website with English and Mandarin versions (other parameters being equal)

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Language WeightsLanguage Internet users

English 27%

Chinese 24%

Spanish 8%

Japanese 5%

Portuguese 4%

German 4%

Arabic 3%

French 3%

Russian 3%

Korean 2%

Rest 17%

http://www.internetworldstats.com/stats7.htm

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PARAMETERS

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Language & Content

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Means of payment

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Bookings Engine

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Address Elements

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Currency

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Email Support

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Social Media Links on the website

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Part of Alliances

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Why logistics/shipping was removed?

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RESEARCH METHOD

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Case of two airlines

Airline 1Parameter English Mandarin

Language 1 1

Content 1 1

Payment 0 1

Bookings 1 1

Address 1 1

Currency 1 0

Email 0 1

Social Media 0 0

Alliances 1 1

Airline 2Parameter English Korean

Language 1 1

Content 1 1

Payment 0 1

Bookings 1 1

Address 1 1

Currency 1 0

Email 0 1

Social Media 0 0

Alliances 1 1

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Effect of weighting language

• Previous studies– GRI 1 = (6+7)/2 = 65%– GRI 2 = (6+7)/2 = 65%

• Weighed approach– GRI 1 = (6*0.27)+(7*0.25)/8 = 42.1%– GRI 2 = (6*0.27)+(7*0.002)/8 = 20.4%

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Criteria used for Evaluation

Parameter Criteria used to evaluate the website elements

Content Same language as language version = 1, else = 0

Payment option Credit card only = 0, else = 1

Bookings engine Bookings engine in the same language = 1, else = 0

Address elements US specific address elements only = 0, else = 1

Currency Currency conversion available = 1, else = 0

Email support Email reply in same language = 1, else = 0Social media link on

the websiteLink to Facebook (Weibo) in same language = 1No link or a link to a different language page = 0

Part of an alliance Part of any alliance = 1, else = 0

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Data98 airlines with 293 language

versionsLanguage versions Number of websites

10 1

9 4

8 3

7 4

6 2

5 7

4 11

3 10

2 18

1 38

Total 98

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RESULTS

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Content – 93%

• Others had parts of their home pages (images, text, or text in images) in a different language than intended

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Alternate payment methods – 27%

• 73% of websites accepted only Visa or MasterCard

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Bookings engine – 87%

• Most are paying attention to the importance of language throughout the entire customer experience

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Non-US address – 81% (49% did not ask for an address)

• Widespread adoption of electronic ticketing

• Airlines aware of diverse physical location of users

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Currency converter – 26%• Airlines do not realise the importance of

allowing users to see prices in different currencies

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Emails• 96 / 293 emails replied• 77% (74) in the same language (74/293 =

25.3%)• Average email turnaround time was 37

hours and 17 minutes

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Social media – 27%

• Chinese social media links like Weibo also gaining traction

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Airline alliance – 36%

• Star Alliance - 8 airlines • SkyTeam - 6 airlines• OneWorld - 5 airlines

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GRI

Highest – 59%Lowest – 1%

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CONTRIBUTION & CONCLUSION

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Contribution• Language parameter given weight according

to the online usage of each particular language– Website with Mandarin and English versions rated

differently than one with English and Korean versions

• Without weighting – GRI = 65%• With language weighting – GRI = 42.1% & 20.4%

• Moving towards weighted GRI where all parameters are weighted according to importance

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Conclusions• GRI improved by attributing weights to language –

to be done the same with other parameters • GRI at 21% lower than previous studies

– Airline may be less globally ready than hotel and ecommerce websites

– Weighted approach may have significantly reduced the value

• Improvements in social media (27%) and alliances (36%)

• Future correlation with other parameters such as profit, sales, human index etc.

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Thank youPeter O'Connor & Zaheer A. Shaikzaheer.shaik@essec.edu