product & pricing standardization within the global mobile network

Product & Pricing Standardization within the Global Mobile Network Operator Industry Richard Laws, Ni Mo

Faculty of Education and Business Studies

Department of Business and Economic Studies

Product & Pricing Standardization within the Global Mobile Network

Operator Industry

Richard Laws

Ni Mo

Second Cycle

2015

Supervisor:

Maria Fregidou-Malama

Examiner:

Akmal Hyder


Abstract

Aim: This study focuses on the degree to which mobile network operators standardize or adapt

their product and pricing strategies amongst their foreign subsidiaries.

Method: 10 mobile network operators with large overseas business investments and 70 of their

foreign majority-owned subsidiaries are included in this empirical analysis. Variables related

to data, SMS, Voice, and other relevant variables, are selected to represent ‘product’ marketing

characteristics; and number of plans and specific price points across three ‘price baskets’ to

represent ‘price’ marketing.

Results & Conclusion: MNOs exhibited a moderate degree of standardization in terms of

product design, with a lesser degree of standardization for price. Standardization scores were

highly positively correlated to subsidiary operations in markets within the same region and

level of economic development as the domestic market. There is also a notable clustering of

marketing approaches in the Sub-Saharan African region.

Implications: Existing research on standardization is reinforced by these results. Future

research on the MNO industry, if global in nature, will need to account for the large degree of

differences between markets. If focused on specific regions, studies can proceed on the basis

of similarity in marketing strategies.

Contribution: This is the most recent quantitative study on standardization in the MNO

industry carried out in the last 10 years. Since that time the industry has also undergone

significant changes.

Keywords:

Adaptation, International Marketing, Mobile Network Operators, Pricing, Product,

Standardization, Telecommunication Services.


Glossary

MNO - Mobile Network Operator, eg. Telia Sonera, Vodafone, Telenor. Companies that own

their own mobile network infrastructure.

MVNO - Mobile Virtual Network Operator, eg. Halebop, Lycamobile. Companies that do not

own their own mobile network infrastructure and instead lease services on a wholesale basis

from existing operators whilst being independent of them organisationally.

Mobile Phone Service - Service provided to customers by a mobile network operator to allow

access to SMS, data traffic, and voice calls from a compatible mobile phone.

Wireless Broadband Service - Service provided to customers by a mobile network operator to

allow access to data traffic from a compatible tablet, computer, or wireless modem.

Subscriber - An individual user on a mobile network.

Postpaid - Services paid by customers in arrears on an ongoing basis.

Prepaid - Services paid by customers in advance.


Acknowledgements

Our thanks goes to our Supervisor, Assistant Professor Maria Fregidou-Malama for her

consistent support, advice and review of our work. Thanks also to our examiner, Akmal Hyder,

for his evaluation of our work. Additional thanks to our peers within the MBA programme at

the University of Gävle for their critique and support during the writing period.

About the Authors

Richard Laws has worked within the Australian Telecommunications industry from 2008, in

roles across sales, competitive intelligence, market intelligence, product management, category

management, and pricing. He holds a Bachelor of Commerce degree from the University of

Melbourne, Australia, and is presently a Master’s student of Business Administration at the

University of Gävle, Sweden.

Ni Mo holds a Bachelor of Industrial Management and Logistics degree and Master’s of

Innovation Logistics Management degree, both from the University of Gävle. She is presently

a Master’s student of Business Administration at the University of Gävle, Sweden.


Contents

1. Introduction Chapter ...................................................................................................... 1

1.1 Background .............................................................................................................. 1

1.2 Problem Discussion ................................................................................................... 1

1.3 Research Purpose ...................................................................................................... 2

1.4 Research Aim & Research Questions ........................................................................... 3

1.5 Delimitations ............................................................................................................ 4

1.6 Organization of the study ........................................................................................... 5

2. Literature Review ........................................................................................................... 6

2.1 Globalization ............................................................................................................ 6

2.2 Marketing Mix – ‘4 P’s’ ............................................................................................. 7

2.3 Mobile Network Operator Industry ............................................................................... 7

2.4 Standardization/Adaptation ....................................................................................... 11

2.5 Internationalization ................................................................................................... 13

2.6 Research Hypotheses ............................................................................................... 14

3. Methodology ................................................................................................................. 16

3.1 Research Design ..................................................................................................... 16

3.2 Sample Selection Criteria ......................................................................................... 17

3.3 Measurement .......................................................................................................... 18

3.4 Reliability and Validity ............................................................................................ 21

4. Empirical Results ......................................................................................................... 22

4.1 Demonstration of Methodology ................................................................................. 22

4.2 Industry-Level Standardization Results ...................................................................... 25

5. Analysis ........................................................................................................................ 28

5.1 Research Question 1: ............................................................................................... 28

5.2 Research Question 2: .............................................................................................. 28

5.3 Region and Income Levels ....................................................................................... 29

5.4 Customization ......................................................................................................... 30

5.5 Regionalization/Clusters .......................................................................................... 31

5.6 Comparison against Earlier Studies ........................................................................... 32

6. Conclusion .................................................................................................................... 34

6.1 Discussion of Results ............................................................................................... 34

6.2 Implications ............................................................................................................ 35

6.3 Limitations ............................................................................................................. 36

Appendix A - Raw Data ...................................................................................................... 38


List of References ................................................................................................................ 39

List of Figures:

Figure 1: A conceptualization of standardization vs adaptation factors. ................................... 8

Figure 2: Global Mobile Traffic by Type. ................................................................................. 9

Figure 3: Mobile subscriptions by country type. ..................................................................... 11

Figure 4: Typical OPEX Breakdown for European Mobile Network Operator %. ................. 13

Figure 5: Example of MNO Website. ...................................................................................... 22

Figure 6: Level of product and pricing standardization across 70 foreign subsidiaries of

internationalized mobile network operators in 2015. .............................................................. 26

Figure 7: Example of Customization from Bharti Airtel (India). ............................................ 31

List of Tables:

Table 1: Average Data, SMS, Voice usage per subscriber by region.. .................................... 10

Table 2: List of sample MNOs and subsidiary countries (domestic market in red). ............... 18

Table 3: Standardization variables and measurements for MNO groups ................................ 20

Table 4: Description and Example of Variables. ..................................................................... 23

Table 5: Correlation of company’s aggregate product and pricing standardization indexes to

their % of subsidiaries which operate in areas of the same region and income level. ............. 29

Table 6: Plan customization availability by market and operator............................................ 30

Table 7: Operations (after cut-off criteria) per region, by operator. ........................................ 32

Table 8: Availability of postpaid services by region. .............................................................. 32

Table 9: Raw Data. .................................................................................................................. 38


1

1. Introduction Chapter

In the first chapter the authors present the general background to the study, followed by the

specific problem discussion and research questions. The purpose of the research is discussed

as well as the delimitation of the study.

1.1 Background

Global marketing is an important area of study given the increasing internationalization of

companies and reduction in trade barriers across countries. A large challenge to companies

seeking to manage subsidiaries in multiple foreign markets is the degree to which the products

and services offered can be standardized and offered globally, or adapted for individual

markets. If a change to the offering is required, it falls within the four “Ps” (product, price,

place, promotion). Similarities in a foreign market’s economic development, customer

perceptions and desires, competition levels, and legal/political stability is likely to pull a

company towards standardization, and the reverse towards adaptation (Vrontis, Thrassou &

Lamprianou, 2009).

The study of standardization and adaptation within marketing had been evident within

academic media since the 1970s (Leonidou, 1996). Czinkota and Ronkainen (2004) identify

that companies have a choice of four options when bringing products to foreign markets:

1. Selling the same product everywhere;

2. Making changes and adjustments of existing products for different markets;

3. Creation of new products for foreign markets;

4. Merging all requirements from all new markets into one new product to be

introduced globally.

1.2 Problem Discussion

Despite the decades of study on standardization and adaptation, a meta-study by Schmid and

Kotulla (2011) on 330 articles related to international marketing standardization determined

that overall, the field is “more or less fragmentary, and, to some extent, even contradictory”,

despite the widespread use of empirical data and both quantitative and qualitative studies.


2

An earlier and more detailed meta-study of 36 articles in the field, conducted in 2003 by

Theodosiou & Leonidou, determined that the majority of research focused on firms located in

the United States; and that few studies focused on one specific industry. Additionally, none of

the 36 studies checked for key informant bias, where data could have been collected from more

than one respondent within companies and answers compared and assessed.

The motivation of the study is considering the fragmentary nature of international marketing

standardization studies, the lack of focus on specific industries, emphasis on companies based

in the United States, and the reliance on key informant data collection, the objective of this

study is to contribute knowledge to the field of standardization in a manner which addresses

the research gap: data collected from a specific industry, without reliance on key informant

procedures, in a clear quantitative manner, with emphasis on companies located outside the

United States.

The industry chosen is the Mobile Network Operator (MNO) industry, suitable as it is relatively

internationalised and conglomerated (Curwen & Whalley, 2006), meaning many companies

operate in foreign markets and thus need to consider standardization; yet an industry in which

is a relatively small sample of companies serves as representative of the entire industry. The

present authors also hold existing professional experience within the industry.

1.3 Research Purpose

Understanding whether or not the international product marketing of MNOs is standardized is

worthwhile for industry practitioners, regulators, and researchers. If the market is highly

standardised, companies’ product management divisions could be concentrated in one

geographical area, market entry becomes simpler, consistent regulations could be applied to

the industry at a global level, and research could be conducted using standardization as an

‘independent variable’ (Rosenbloom & Larsen, 1997). If market adaptation is evident however,

these approaches would all necessarily become different.

There has been limited research on the adaptation/standardization practices of MNOs. The most

comprehensive work to date has been carried out by Gerpott & Jakopin (2005a), who examined

the degree of internationalization of a number of MNOs, across product, price, promotion and


3

place (ie. the traditional ‘4 Ps’ of marketing), finding moderately high levels of standardisation

for product and price, and lower levels for promotion and place. However, this study examined

product attributes at a relatively high and abstract level, such as what method of transmission

(eg. 2G, 3G) was used and what type of phone manufacturers were sold (ibid). The specifics

of the mobile phone service constructs were not examined. Additionally, since 2005 there have

been changes to the industry, particularly the rise of smartphones, the rise of mobile data traffic,

and increasing numbers of users in emerging and frontier markets (Vodafone, 2014). As such,

the research is worth repeating with contemporary points of measurement.

To do so, a cross-sectional study of a sample of MNOs with substantial foreign operations is

used. Data is gathered in an unobtrusive manner proximate to that of a content analysis; with

primary data drawn from MNOs (including foreign subsidiaries) websites and press releases.

This methodology is highly similar to, and drawn from, the methodologies successfully used

by Gerpott & Jakopin (2005a) and Curwen & Whalley (2006) in their own studies of the

industry.

Due to the small number of large MNOs (ibid) it is also possible to conduct research on a large

portion of this market, as opposed to other industries which are more fragmented and would

require a larger sample size for the same level of accuracy, or a lower level of accuracy for the

same sample size.

1.4 Research Aim & Research Questions

The aim of this study is to focus on the degree to which mobile network operators standardize

or adapt their product and pricing strategies amongst their foreign subsidiaries:

1. Research Question 1: Are product and pricing components completely (100%)

standardized when comparing operations across MNOs’ domestic and foreign markets?

2. Research Question 2: Which individual components of MNOs’ product and pricing

designs are most, and least, standardized?


4

1.5 Delimitations

Due to the ambitious quantitative nature of this study, reliance on data gathering from

companies’ websites, and large sample of companies, the scope of the study must be such that

the utility and completeness of the data gathered is maximised in the first instance.

In order to gather quantitative data in a consistent manner, it is necessary to focus on the

‘product’ and ‘price’ aspects of the four “Ps” as part of this study, and to not include

‘promotion’ and ‘place’. Prior research on this subject conducted by Gerpott & Jacopin

(2005a), professional academic researchers with a focus on this field, relied on access to private

research and membership to international telecommunications unions to provide source

material for their research of ‘promotion’ and ‘place’ (whilst using content analysis of

publically available information for ‘product’ and ‘price’). It is our estimation that the material

necessary to complete an analysis on ‘promotion’ and ‘place’ (eg. Number of stores, number

of franchises, alliances, frequency of advertising, advertising spend per customer etc.) are

commercially sensitive in nature and not completely available to the public, instead only

available via industry-grade private research which we do not have access to for this study.

Business offers are excluded from the study, as these are usually not publically marketed and

are often privately modified for one business account to another (Gerpott & Jakopin, 2005a).

Prepaid offers are excluded, as the average revenue per user of these services is typically lower

than postpaid accounts (Klein & Jakopin, 2014), and so these services are likely to receive less

global scrutiny and investment than postpaid services. Finally mobile broadband services are

excluded, as these services are typically very simple in product and pricing construction

(García-Murillo, & Rendón (2009), leaving less to analyse and compare across markets. This

leaves consumer, postpaid mobile phone-services as the target offerings for this study.

An attempt is made at focusing on measuring the ‘core’ aspects of the MNO product set (Data,

SMS, Voice, and other closely related areas) (Peppard & Rylander, 2006) which can reasonably

be expected to be present to some extent across MNO groups. However, given the dynamic

and global nature of the industry, certain novel product innovations, marketing schemes, or

‘unique service propositions’ which are present in individual markets and individual MNOs

may not be captured.


5

The rollout of 4G services is a widely reported industry metric, and whilst it is relevant to

consumers, rollouts are often dependant on the participation of national governments and

regulators. As such, timeframes are often outside of the control of MNOs (Calandro & Moyo,

2012), and measurement is not featured in this work.

1.6 Organization of the study

This work contains six chapters, outlined as follows:

Chapter One identifies the research gap of the topic and broadly discusses the solution.

Chapter Two discusses the theoretical framework related to the topic and provides context

related to the MNO industry. Based on this, hypothesis for the research questions are created

and explained.

Chapter Three contains a detailed description of the methodology used to establish the sample

of MNO companies and explains why each variable has been selected for measurement.

Chapter Four presents the results of the research against the research questions and

hypotheses.

Chapter Five conducts broader analysis on the results based on relevant marketing concepts.

Chapter Six concludes the work, and identifies the implications of the work and its limitations.


6

2. Literature Review

This section will examine the most relevant theories across globalization and

internationalization, standardization and adaptation, and finally MNO industry specific

theories and market information. These are distilled to form hypotheses related to the research

questions.

2.1 Globalization

With the rapid growth of both global capital and labour forces, internationalization and

globalization are not only contemporary issues to be considered by western companies, but

also for companies founded in emerging markets that wish to expand (Woods, 1998; Gurgul &

Lack, 2014). Globalization is as a process in which both human and non-human activities

become increasingly integrated on an international basis (Milani & Park, 2014). However,

globalization is not a simple idea that can be defined clearly with a distinct beginning or ending

(Eakin & Lemos, 2006). Many processes are involved with globalization, such as: the

transmission of knowledge, cultural stability, the reproduction & discourse of power, market

entry methodologies, and sociopolitical controls (Kobrin, 2015). The rapid pace of

globalization from the 20th century onwards means that developing markets have achieved an

increasing share of world trade, leading to many established westerns companies entering new

markets in order to pursue sales growth (Al-Rodhan & Stoudmann, 2006).

In order to gain long-term benefits from globalization, three different perspectives should be

reviewed: market-cantered, people-cantered and state-cantered aspects (Luo, 2005). The

market-cantered perspective focuses on transactions processes in the worldwide economy, and

often examines ongoing and future changes to production and distribution of goods and

services across economies (Leidner, 2010). This perspective will be particularly examined in

this work.

Globalization of course not only applies to the quantity of goods and services in a global

economy, but also to the quality. As such entry to markets with substantially different standards

of infrastructure or governance (on the supply side), or consumer preferences (on the demand

side) compared to a company’s domestic market can present substantial challenges (Jackson,


7

2008).

2.2 Marketing Mix – ‘4 P’s’

The marketing mix is a tool to categorise the components of a firm’s or product’s offerings to

customers. It is divided into the ‘4 P’s’: product, price, promotion and place (Londhe, 2014).

Given that this work examines product and price-related variables in detail, and excludes

promotion and place, it is necessary to consider each aspect.

‘Product’ describes the tangible good or intangible service that actually fulfils the needs or

wants of customers (ibid). The product can be manipulated in order to emphasise a certain

feature or aspect in response to the demands of customers.

‘Price’ is the amount a customer pays for the product or service. Price must be formulated in a

manner which considers the competitive environment, consumer’s willingness to pay, and

growth strategies of the company (Azzadina, Huda & Sianipar, 2012).

‘Promotion’ is the means of communicating information about the good or service to

consumers (Lin, Chen & Tzeng, 2010). This may involve media advertising, sponsorship, or press

releases.

‘Place’ describes the manner in which the good or service is distributed. This may involve

centralised company-owned stores, e-commerce, franchises, or retail distribution.

Examples of variables related to the ‘4 P’s’ are examined in the methodology chapter of this

work.

2.3 Mobile Network Operator Industry

The global MNO industry is large, internationalized, and conglomerated. The industry saw

global services revenues of US$960 billion in 2013 (Vodafone, 2014), and is one in which 88%

of large MNOs operate outside of their core region (Curwen & Whalley, 2006). There are

approximately 35 large multi-national MNOs which dominate the industry globally, and


8

typically 3-4 operators per country (ibid). The industry is noted as one in which product and

pricing design is critical for revenues (Peppard & Rylander, 2006).

The industry has undergone a great deal of change in the past 10 years. This change has taken

the form of a shift away from voice and SMS services towards data (Ericsson, 2013), as show

in Figure 1, and driven by the increasing adoption of internet-enabled smartphones. Secondly,

the overtaking of developed countries by emerging economies in terms of number of mobile

service subscribers (Microsoft, 2014), as shown in Figure 2, linked to increasing incomes in

emerging markets. Thirdly, the dominance of the GSM standard in terms of wireless

transmission (Casey & Töyli, 2012), which allows customers to access multiple networks

without requiring different mobile phones.

Figure 1: Global Mobile Traffic by Type

Source: Ericsson (2013)


9

Figure 2: Mobile subscriptions by country type

Source: Microsoft (2014).

As such studies which have examined the industry in the past are likely to have focused

primarily on customers in developed countries, on SMS and voice services, and on differences

in technological standards. This is the case when examining the most notable study of

international marketing standardization in the MNO industry, carried out by Gerpott & Jakopin

in 2005.

In terms of average usage of data, SMS and voice, volumes differ greatly by region, with the

largest usage seen in the US & Canada, moderate usage in Western Europe, and lower usage

in the Central/Eastern Europe and rest of the world, as shown in Table 1. Despite the differences

in usage by region, trends are similar for each, with consistent yearly increases in data volumes

for all countries in particular (Cisco, 2013). It is also worth considering that with greater

average usage comes the possibility of greater total variance in usage across the customer base

as a whole, which MNOs will need to account for in terms of their pricing strategies.


10

Table 1: Average Data, SMS, Voice usage per subscriber by region.

Data (2013) SMS (2013) Voice (2011)

US & Canada 1384 MB 467 356

Western Europe 716 MB 203 126

Central/Eastern

Europe

339 MB 122 78

Rest of World 211 MB N/A N/A

Sources: Statista (2013); Cisco (2013).

In terms of the major operating costs to MNOs in offering services, Capgemini (2009) find that

subscriber acquisition and retention costs (predominantly the subsidiation of mobile phones for

use by customers) account for 27%; the costs of running the mobile network itself at 24%, and

the charges levied by other MNOs in order to connect calls to eachother’s networks (often

influenced by Government regulation) at 23%. The full values are shown in Figure 3. The

remaining % likely relate to back-office labour costs. MNOs also have large CAPEX costs in

terms of first establishing their mobile network, and purchasing the radio spectrum licenses

from national governments necessary to broadcast their wireless signals within a country

(GSMA, 2012). Overall, there are a number of costs which are likely to differ from one country

to another, such as labour, rent, electricity, and interconnect charges.


11

Figure 3: Typical OPEX Breakdown for European Mobile Network Operator.

Source: Capgemini (2009).

The impact of each market’s economic and legal development also has an enlarged impact

upon the MNO industry due to its reliance on the ability of customers to make consistent

monthly payments as part of postpaid contracts (Bar-Gill & Stone, 2009); and also due to the

prevalence of subsidising hardware (ie. Providing hardware at a price lower than the regular

retail price) with the expectation of recouping the subsidy and gaining a return over a longer

period, typically 24 months (ibid).

As such, countries without adequate banking infrastructure or where large segments of the

population do not have access to banking services will be unable to sustain markets for postpaid

MNO services. Additionally, markets with insufficient legal recourse for incidents of fraud will

place greater strain on the provision of subsidies hardware, if the total level of contractual

payments is not provided by customers.

2.4 Standardization/Adaptation

A company’s ‘global marketing strategy’, if predominantly focused on achieving cost benefits

through economies of scale, would typically see a centralisation of resources and


12

responsibilities to a central headquarters (Bustamante, 2011). However, the demands of the

globalized marketplace are such that a multinational corporation’s (MNCs) inputs, skills,

services, products, and technologies are supplied to and demanded from many groups of

customers in multiple countries (Lall, 2004). Companies servicing different markets face many

challenges, and it is very possible that strategies which satisfy one group of customers in one

market will not satisfy others in a different market (Bustamante, 2011). Due to this reason,

companies’ marketing strategies theoretically need to be adapted for each market, to some

degree. However, it is this degree of adaptation which is the focus of much of the literature on

the topic, particularly as an excess of adaptation may potentially diminish the core appeal of

the product (Hyder & Freigdou-Malama, 2009).

The vast majority of standardization/adaptation literature also focuses heavily on marketing

mix elements, whilst issues such as governance decisions are covered in relatively little detail

(Griffith, Lee, Seob Yeo & Calantone, 2014). Governance decisions include, for instance,

global marketing program implementation, and the appropriate distribution of product and

technological expertise across the global organisation (Griffith et.al. 2014).

As summarised in Figure 1, the primary reasons pulling towards adaptation of marketing

behaviours are differences between the domestic and foreign market in terms of customers

(including culture and customers perceptions), social environment (including the political and

legal environment), and market development (income levels, competition, physical and

marketing infrastructure) (Akgün, Keskin and Ayar, 2014; Antonsen, Skarholt & Ringstad,

2012; Vrontis et al., 2009). Notably these are all external factors related to the markets, rather

than internal factors related to the company.

Logically, an absence of differences in these areas would eliminate pulls towards adaptation,

and so standardization would prevail based on the superior economies of scale it allows

(Bustamante, 2011). As such, it is reasonable to state that when quantifying standardization

and adaptation on a linear scale, an absence of standardization implies an equal presence of

adaptation.


13

Figure 4: A conceptualization of standardization vs adaptation factors.

Within the MNO industry, a quantification of international marketing standardization has been

carried out by Gerpott & Jakopin (2005a). The study finds that product and pricing of the 15

international MNO groups examined were moderately standardized, with scores of 60% and

54% standardization respectively. Promotion and place were more towards adaptation, with

scores of 33% and 42% respectively.

2.5 Internationalization

Rapid global economic change has made a strong impact on the internationalization of many

companies worldwide over the last few decades (Laanti, Gabrielsson and Gabrielsson, 2007).

Companies have established new marketing strategies in order to changes in global markets,

and must increasingly consider their marketing strategies as part of this global landscape

(Laroche and Park, 2013).

Recent research has emphasized the abilities of MNCs to understand and service foreign

markets, with joint ventures and other forms of co-ownership identified as methods to relatively

quickly attain these abilities. (Bowen, Baker & Powell, 2015). However, these methods can

Source: Vrontis et al., (2009)


14

result in lessened control over the foreign entity, particularly when the host government holds

an interest in the foreign entity (Bowen et al., 2015).

Traditional theories regarding the internationalization of a company define the process as

incremental and gradual (Zahid, 2015). Furthermore it is argued that business in the markets

which dominated by company, then started to enter the ambient markets, and later entered to

other others to achieve globalization, but try to on the same continent at first thereafter

expanded to other markets (Pehrsson, 1995). Firm performance is also heavily rely on the

ability of managers to influence their regulatory contexts and exploit company’s economic

markets (Rajwani and Liedong, 2015).

An additional advantage of an internationalized company is the ability to test products in

individual markets and analyse the results, rather than committing to a more costly and riskier

international rollout. Given the internationalized nature of the MNO industry, it is possible that

individual product strategies may be visible in select markets only, and not in home markets or

other foreign markets. This can also be considered a form of reverse innovation, where the

results from a less-developed market can influence strategies in more developed markets

(Govindarajan and Ramamurti, 2011).

2.6 Research Hypotheses

The marketing standardization studies examined identified multiple factors which influence

whether adaptation or required. As the MNO industry is a service sector, and so has less

reliance on physical transport and provisioning of its offerings compared to goods-based

industries, the need to adapt product and pricing in light of physical differences in markets is

unnecessary or reduced. Additionally, though there are large differences in the volume of usage

of mobile phone services from market to market, overall trends in terms of the emphasis on

mobile data is consistent across all markets.

As such, it is likely that product design is highly standardized across markets due to the lack

of factors which would encourage product adaptation. Pricing is likely to be only moderately

standardized, as if we consider an MNOs costs to be an indicator of final pricing, we have seen

that input costs to the final service are likely to differ from one country to another. Therefore,


15

when comparing the actions within MNO’s home countries to their foreign markets we can

develop the following hypothesis in relation to research question 1:

Research Question 1: Are product and pricing components completely (100%) standardized

when comparing operations across MNOs’ domestic and foreign markets?

Hypothesis 1: MNO ‘product’ design is highly standardized across foreign subsidiaries and

‘pricing’ is moderately standardized.

Secondly, when considering the particularly consistent trends and emphasis on data usage

across all countries, and the large differences in average customer usage by region, we can

develop the following hypothesis in relation to research question 2:

Research Question 2: Which individual components of MNOs’ product and pricing designs

are most, and least, standardized?

Hypothesis 2: Within ‘product’, the data category is more standardized than SMS or voice

categories, and within ‘pricing’ the number of plans offered to consumers is least standardized.


16

3. Methodology

This chapter introduces the strategy and methodology used for the study, and examines and

explains the individual variables against which data is collected.

3.1 Research Design

In order to answer the two research questions, a quantitative cross-sectional study using an

unobtrusive data collection format is required. The rationale for this is examined below.

In many studies of standardization/adaptation of global marketing strategies, data has been

collected by using perceptual responses from an individual “key informant” from each

company or subsidiary, as a form of qualitative study (Li & Cavusgil, 1995). However,

empirical studies indicate that this methodology is prone to a “headquarters bias” whereby

respondents who are not directly involved with an area of business can typically only offer

relatively inaccurate information on that area (ibid). An accurate examination of the

standardization/adaptation strategies of these multiple subsidiaries using the “key informant”

qualitative method would have required data sourced from individual managers of each

subsidiary (ibid) - not feasible with the total of 80 MNOs listed in our sample. By contrast, a

quantitative study allows for empirical data to be recorded in a manner which can be

mathematically analysed and expressed, and which is also generalizable to a larger population

(Bryman & Bell, 2011).

The unobtrusive data collection format focuses on standardization/adaptation areas related to

consumer postpaid mobile phone service product characteristics, and is measured by sourcing

published information from MNOs (Annual Reports, Telecommunications Industry Databases,

Press Releases) and by content analysis (detailed in appendix A) of their websites, and carried

out in 2015. This format has been used in other studies of global marketing strategies, for

example in the advertising industry (Harris & Attour, 2003), MNO industry (Gerpott &

Jakopin, 2005a), and e-commerce industry (Singh, Kumar & Baack, 2005). The unobtrusive

method is appropriate as data from all of the sample MNOs can be gathered quickly and directly

by the researchers, whilst also eliminating the risk of ‘headquarters bias’.

A cross-sectional study focuses on the collection of data from multiple cases at one point in

time (Bryman & Bell, 2011). This allows for variables from each part of the sample to be


17

compared with time period as a consistent independent variable, simplifying some aspects of

analysis (ibid). However, this comes at the disadvantage of not being able to examine trends

over time.

3.2 Sample Selection Criteria

In order to conduct our study it is first necessary to establish the sample group of MNOs. In

order to select MNOs with ‘substantial foreign operations’, we will use a cut-off approach,

where an initial group of MNOs is gradually filtered until the remaining set are appropriate to

be researched. Firstly, the MNO must belong to the group of the 30 largest MNOs worldwide,

as measured by their number of subscribers from 2011 onwards. Secondly, the MNO must hold

at least 90% ownership of at least two foreign MNO subsidiaries which offer consumer

postpaid mobile phone services. This information is sourced from MNO’s annual reports.

The reason for this is to ensure that we are focusing our research on companies that are

sufficiently large and internationalised as to be facing the issues of standardization/adaptation

across their operations (Schilke, Reimann & Thomas, 2009). Foreign subsidiaries with greater

than 10% outside investment were excluded as the other shareholder’s interests would

inherently make global standardization more difficult (Ozsomer, Bodur & Tamer Cavusgil,

1991), particularly as holding stakes within competing MNOs is common within the industry

(Renda, 2010). The foreign subsidiary companies must also be MNOs in that country (ie. own

their own mobile network infrastructure in that country), not MVNOs, as it is conceivable that

subsidiary MVNOs which are forced to rent network services from third-party operators are

likely to need to modify their product designs in order to align with the services and packages

offered by the wholesaler, for billing or contractual reasons.

This criteria is met by 10 MNOs: Vodafone (UK), Airtel (India), America Movil (Mexico),

Telefonica (Spain), Orange (France), Telenor (Norway), Telia Sonera (Sweden), T-Mobile

(Germany), Etisalat (United Arab Emirates), Ooredoo (Qatar), (sorted in descending order of

subscribers) (ITU, 2014). These 10 companies subsequently yield 70 foreign subsidiaries for a

total of 80 companies. In addition there are 35 subsidiaries, and one additional MNO group

(MTN), which do not offer postpaid mobile phone services, but meet all other criteria, and so

are still of use for broader analysis. A full list of these sample MNOs is provided in


18

Table 2.

Table 2: List of sample MNOs and subsidiary countries (domestic market in red).

Source: Own.

Based on this approach some large and notable companies are excluded - China Mobile, China

Unicom, and China Telecom for example, as they only operate within China; and Singapore’s

large SingTel, which has some presence in foreign markets though only one fully owned

foreign subsidiary.

3.3 Measurement

Measurements of standardization have been designed to fit the specific marketing features of

the MNO industry. Standardization is measured firstly at the MNO group level, using

comparisons between each individual foreign subsidiary’s (n = 70) variables compared against

its parent, with higher values indicating higher standardization. Secondly, at the level of the 10

MNOs, standardization is measured by using an average of the standardization results for each

variable of each MNO group to derive an industry figure. Table 3 summarises the

standardization variable measurements used at the MNO group level, and the following

paragraph explains the product section in more detail.

Many aspects of the offerings which MNOs provide to customers are core components of the

service, such as the ability to make and receive calls, to send messages, and to access the

MNO Group: Airtel Am. Movil Etisalat MTN Ooredoo Orange Telef. Telenor Telia.S TMobile Vodafone

Bangladesh Argentina United Arab EmiratesAfghanistan Qatar Armenia Argentina Bulgaria Uzbekistan Albania Albania

Burkina Faso Brazil Afghanistan Congo, Rep. Kuwait Cameroon Chile Denmark Denmark Austria Czech Republic

Chad Chile Benin Ghana Maldives Central African RepublicCosta Rica Hungary Estonia Czech Republic Germany

Congo, Dem. Rep.Colombia Central African RepublicGuinea-Bissau Myanmar Congo, Rep. Ecuador Montenegro Finland Germany Greece

Congo, Rep. Costa Rica Cote d'Ivoire South Africa Dominica Mexico Norway Lithuania Netherlands Hungary

Gabon Dominican RepublicGabon Uganda Egypt, Arab Rep.Peru Pakistan Norway Poland India

Ghana Ecuador Niger Zambia France Spain Serbia Sweden Ireland

India El Salvador Sri Lanka Israel United Kingdom Sweden Italy

Kenya Guatemala Sudan Moldova Uruguay Malta

Madagascar Honduras Togo Romania Venezuela, RB Netherlands

Malawi Mexico Slovak Republic New Zealand

Niger Nicaragua Spain Portugal

Rwanda Panama Romania

Seychelles Paraguay Spain

Sierra Leone Peru Turkey

Sri Lanka Puerto Rico United Kingdom

Uganda Uruguay

Total: 17 17 10 7 4 13 10 8 7 6 16


19

internet via a data connection. As such, it is not meaningful to measure such fundamental

aspects in terms of standardization.

As examined in more detail in this work’s Introduction chapter, prior studies on standardization

of MNO products were carried out most recently in 2005(a) by Gerpott & Jacopin. The

variables used were highly abstract and are now largely outdated given the changes to the

industry in the proceeding 10 years. The following six ‘new’ aspects of MNO consumer

postpaid mobile phone services appear to be applicable across contemporary markets, and the

presence or absence of each accurately captures the overall product designs of individual

MNOs. This statement is based on our preliminary examination of the 10 MNO’s parent

operations and our application of the variables to them.

This section describes the variables listed in Table 3. The means with which MNOs charge for

(1) voice, (2) SMS and (3) data usage can be in the form of (sub-variables) (.1): charging the

customer for every individual unit of usage and giving them no pre-set inclusion or ‘no

inclusion’ (eg. each call is charged per minute); (.2) offering the customer a ‘limited inclusion’

accessible during the billing period (eg. 100 minutes of calls), with extra charges or limitations

being applied for use above the inclusion; (.3) ‘unlimited’ usage; (.4) for data access only,

charging the customer based on the speed/bandwidth, network type, or type of device they

wish to select when accessing the service, (eg. additional charges when using the service with

a smartphone, or when using the ‘4G’ network). These sub-variables can apply to the voice,

SMS & data variables each independently, eg. An MNO can offer ‘unlimited’ voice & SMS,

with a ‘limited inclusion’ of 1GB of data. Additionally, the values are not binary, as MNOs

often offer multiple plans with different characteristics.

(4) Customisation is whether customers are presented with the ability to personally modify

each individual component of their plan, eg. To reduce their SMS inclusion but to increase

their voice inclusion. (5) Handset financing/subsidies is whether customers are offered

assistance from the MNO in paying for their mobile handset, or are required to pay the full

amount upfront, eg. $0 phone available on a 24 month contract. (6) Intra-account sharing is

whether customers can pool their voice, SMS & data inclusions (if present) for use by all users

on the account eg. Two users on the same account with 100 minutes of voice calls associated

with their individual plans are able to access a combined pool of 200 minutes of voice calls.


20

From these six variables, the MNO group’s overall product standardization is derived by

averaging all variable values. As such, product standardization index values can vary from a

minimum of zero (total adaptation) to a maximum of 100% (total standardization).

Table 3: Standardization variables and measurements for MNO groups.

Variable Measurement

Product 1. Voice

2. SMS

3. Data

4. Customisation

5. Handset

financing/

subsidies

6. Intra-account

sharing

● Sub-variables for Variables 1,2,3: 1. No inclusion .2

Limited Inclusion; .3 Unlimited; .4

Speed/Network/Device-based charges (Data only)

● Values for each: (binary variable): 0 (=not available), 1

(=available).

● Measure: Percentage share of foreign subsidiaries with

value equal to the parent.

S_Product = 1

6 ∑𝑛

𝑡 = 1 (𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠 1,2,3,4,5,6)

Price 7. Number of plans

8. ‘Low usage’ price

basket

9. ‘Medium usage’

price basket

10. ‘High usage’ price

basket.

● Measure: variance from domestic market:

[1 − (1

𝑛. ∑ [

𝑉𝑓−𝑉𝑑

𝑉𝑑]𝑛

𝑖=1 ] . 100

(Where V is the variable examined, f is the foreign market

result, d is the domestic market result)

● Package with 200MB data, 50 voice minutes, 50 SMS per

month

● Package with 1GB data, 200 voice minutes, 120 SMS per

month

● Package with 3GB data, 400 voice minutes, 250 SMS per

month

● (Baskets adjusted for PPP)

● S_Pricing = 1

4 ∑𝑛

𝑡 = 1 (𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠 7,8,9,10)

Aggreg-

ate

Aggregated product

and pricing

standardization score.

● S_Aggregate = (S_Product + S_Pricing) / 2


21

Source: Own.

In terms of Price, four variables are examined. (7) Number of plans examines the number of

choices the customer has when selecting a postpaid mobile phone service and the degree of

variance from the domestic market. MNOs provide multiple tiers of services to customers,

usually unique to each market. As such it is reasonable to create a price ‘basket’ in order to

allow a relatively like-for-like comparison of the price of similar services in different markets.

Low, medium and high baskets are created by the authors, based upon the global average usage

levels examined in the Theory chapter, such that the tiers serve to represent reasonable choices

that customers are likely to be able to select from. Effort is made during content analysis to

select the cheapest offering which satisfies the given price basket. Pricing is converted to USD

based on 2013 World Bank and OECD PPP data to account for regional differences in

purchasing power.

When discussing degrees of standardization, the following scales will be used, based on those

used in Gerpott & Jacopin (2005a): 0-33%: low standardization/high adaptation; 34-66%:

moderate standardization/moderate adaptation; 66-100%: high standardization/low adaptation.

3.4 Reliability and Validity

Reliability describes the extent to which a data collection process will produce consistent data,

finding and observations if the process was carried out by a different researcher (Saunders,

Lewis & Thornhill, 2009). Reliability is high, as the data is collected with very little individual

interpretation, and is taken directly from MNO’s publically available websites and press

releases. However, these websites can change over time, and so the results specific to Q2 2015

cannot be re-collected with ease. The analysis can be repeated exactly, however, as a full table

of the collected data points is included in Appendix A.

Validity describes the extent to which data collection methods accurately measure the intended

and relevant variables (ibid). Validity is also high, as the data is collected directly from MNO’s

publically available information, with little scope for recording error. Many of the variables

used are binary in measurement, simplifying data collection.


22

4. Empirical Results

This chapter uses examples from specific MNOs to show how the methodology has been

applied. It then details the results of the study as directly related to the research questions.

4.1 Demonstration of Methodology

In order to demonstrate the methodology used, the example of Vodafone’s Maltese website is

presented. This subsidiary has been selected as they only offer a total of three consumer

postpaid mobile phone service plans, have a single webpage which holds all relevant

information, and are written natively in English. The original source material from their website

is shown on Figure 5.

Figure 5: Example of MNO Website

Source: Vodafone Malta (2015).


23

The data from each MNO, shown as an example in Figure 5 is then captured and quantified in

the following format shown in Table 4, second column. Comments are provided for each

variable to explain the result.

Table 4: Description and Example of Variables.

Product Variable Result (0=Not

Present,

1=Present)

Comment

1.0 Data No

Inclusion

0 Data is included on all plans.

1.1 Data Bucket 1 A limited amount of data is included in all plans.

1.2 Data

Speed/Network

0 Data speeds are identical for all plans.

1.3 Data Unlimited 0 Unlimited data is not offered.

2.0 SMS No

Inclusion

0 SMS is included on all plans.

2.1 SMS Bucket 1 SMS is limited on the €35 plan.

2.2 SMS Unlimited 1 SMS is unlimited on the €60 and €99.99 plans.

3.0 Voice No

Inclusion

0 Voice is included on all plans.

3.1 Voice Bucket 1 Voice is limited on the €35 plan.

3.2 Voice Unlimited 1 Voice is unlimited on the €60 and €99.99 plans.

4. Customisation 0 Plans inclusions cannot be altered.

5. Subsidisation 1 Subsidised devices are available.

6. Bucket sharing 1 Usage can be shared with other users.


24

Pricing Variable Result Comment

7. # of Plans 3 A total of three plans are available.

7.1 Low: 200mb, 50

min, 50 SMS

35 A plan with precisely this level of inclusion is not

available, so the next cheapest plan which satisfies

requirements, the €35 plan, is selected.

7.2 Med: 1GB, 200

min, 120 SMS

35 The €35 plan offers 1GB of data and unlimited SMS

and voice, satisfying requirements for this tier.

7.3 High: 3GB, 400

min, 250 SMS

70 (60+10) A plan with precisely this level of data inclusion is

not available, and the €99.99 plan is over twice the

price of the medium plan and contains many

inclusion (eg. international roaming) which are out

of scope. So, the €60 plan with an additional €10 data

pack is entered to give an effective 3GB worth of

data inclusion. Total price is 60+10 (70).

Source: Own.

When calculating the standardization scores for variables 1.0 through 6, the mathematics are

relatively simple – a subsidiary score of 1 (i.e. A product characteristic is present) would give

100% standardization if the domestic score is also 1, and 0% standardization if there is a

mismatch between the two scores between foreign and domestic market.

For the pricing variables, the variance from the domestic market is calculated. Using Variable

7.1 ‘Low Bucket’ as an example, and after adjusting for PPP, comparing Vodafone Malta

($59.43) against its domestic market ($13.67) the calculation is: (59.43/13.67)/13.67 = 32%

standardized. This gives a logical result given the scale difference between variables in each

market, and uses the same formula used by Gerpott & Jacopin (2005a) in their own quantitative

study of this market.

These calculations are carried out for each subsidiary within the MNO group in order to form

the standardization scores for each MNO as a whole. The results are then averaged,

unweighted, to form the total industry figure.


25

4.2 Industry-Level Standardization Results

To address the degree of international standardization of product and pricing mean

standardization levels were calculated for the industry as a whole, based on the 10

internationalized MNO corporations and their 70 foreign affiliates. Table 3 reports descriptive

statistics for the individual variables and sub-variables and provides an index for both product

and pricing standardization.

These results below are intended to showcase the study at its simplest form, as most relevant

to the research questions, variables being measured, and existing understanding of

standardization. Given the large amount of data collected, some method of computing the data

must carried out before the results can be displayed for viewing. A full extract of the entire

spreadsheet of all data collected is available on Appendix A.


26

Figure 6: Level of product and pricing standardization across 70 foreign subsidiaries of 10

internationalized mobile network operators in 2015.

Source: Own.

These results for the 10 MNO groups and 70 subsidiaries demonstrate the standardization score

recorded for each variable across the industry as a whole. As explained in the methodology

chapter, standardization scores of 0-33% show low standardization/high adaptation; 34-66%

show moderate standardization/moderate adaptation; and 66-100% show high

standardization/low adaptation.

Sections in green denote areas where sub-variables have been averaged to form an overall result

for that variable, specifically for voice, SMS, data, as these variables are more complex to

Categories Standardization % (1 = completely standardized)

Data No Inclusion 77%

Data Bucket 95%

Data Speed/Network 57%

Data Unlimited 98%

Data Average 82%

SMS No Inclusion 80%

SMS Bucket 54%

SMS Unlimited 71%

SMS Average 68%

Voice No Inclusion 67%

Voice Bucket 74%

Voice Unlimited 68%

Voice Average 69%

Customisation 81%

Subsidisation 78%

Bucket sharing 57%

Product Standardization 73%

# of plans 58%

Low usage price basket 43%

Medium usage price basket 42%

High usage price basket 39%

Pricing Standardization 46%


27

measure (due to a greater degree of global variation in their design) and require measurement

at the sub-variable level to form an overall result.

Orange sections represent the aggregate Product and Pricing measures, based on the Product

and Pricing variables. Please refer to Table 3 for the full weightings.

Particular attention should be drawn to the results of variables which show relatively high or

low standardization scores, and any areas of particular interest for the reader. Analysis of the

results is given in the following chapter.


28

5. Analysis

The results are analysed against the research questions, and against theories and concepts

identified in the theory chapter.

5.1 Research Question 1:

Are product and pricing components completely (100%) standardized when comparing

operations across MNOs’ domestic and foreign markets?

Hypothesis 1: MNO ‘product’ design is highly standardized across foreign subsidiaries and

‘pricing’ is moderately standardized.

Results: With standardization scores for product of 73% (highly standardized) and 46% for

pricing (neither standardized nor adapted) the results are supportive of the hypothesis that

product design would be highly standardized, and pricing moderately standardized.

5.2 Research Question 2:

Which individual components of MNOs’ product and pricing designs are most, and least,

standardized?

Hypothesis 2: Within ‘product’, the data category is more standardized than SMS or voice

categories, and within ‘pricing’ the number of plans offered to consumers is least standardized.

Results: With a standardization score of 82%, data is indeed the most standardized product

component, in line with the hypothesis. This may be in line with the growth in data volumes

identified within the industry, and a subsequently greater level of global scrutiny. The least

standardized component is SMS, with notable differences in whether SMS is completely (ie.

Across the entire portfolio of plans) ‘limited’ or completely ‘unlimited’ across different

markets contributing to the ‘SMS Bucket’ sub-variable being the least standardized of all

product variables at 54%.

For pricing, the number of plans is the most standardized pricing component at 58%, which is

not in line with the hypothesis. The least standardized component is in fact the high usage


29

basket, at only 39% standardized. This is predominantly due to the comparatively high prices

charged for the basket in some foreign markets and resulting high levels of variance in pricing.

A full breakdown of the collected data is available in Appendix A.

5.3 Region and Income Levels

As discussed similarities (or differences) in region and income level, when comparing

companies’ home markets to their foreign markets, serve to encourage (or discourage)

marketing standardization.

With the aggregate standardization results from each operator group available, it is possible to

test these theories against the data set. This is achieved by examining the 10 MNO groups and

noting what % of their foreign subsidiaries operate in the same areas, by region and income

level, as the parent company. The results, shown in Table 5, show a highly positive correlation

between standardization and similarity of region (0.73) and similarity of income levels (0.8).

Given that this result aligns strongly with the positions supported by multiple authors, this also

serves as a strong indicator that the methodology used to produce the aggregate standardization

measurement of these companies is appropriate.

Table 5: Correlation of company’s aggregate product and pricing standardization indexes to

their percentage of subsidiaries which operate in areas of the same region and income level.

Source: Own.


30

5.4 Customization

Interestingly, seven of the ten MNOs offered customers the ability to customise their plan (ie.

Add and remove data, SMS, voice components at will). However, only at Etistalat is this

functionality offered across all markets, and for the other MNOs only at a minority of foreign

markets (shown on Table 6). An example of this customization is show on Figure 7. These

results can be compared against theories on reverse innovation and test marketing from

Govindarajan and Ramamurti (2011) which proposes that unique product designs can be drawn

from foreign markets. However, without full data on the product offerings of local competitors

in each market, it is not possible to rule out whether offering customization is only a reaction

to local competition and therefore an attempt to meet consumers established expectations.

Table 6: Plan customization availability by market and operator

Source: Own.

Row Labels Airtel Am. Movil Etisalat Telenor Telia.S TMobile Vodafone Grand Total

Domestic 1.00 1.00 2.00

Foreign 2.00 1.00 1.00 1.00 1.00 3.00 9.00

Grand Total 1.00 2.00 2.00 1.00 1.00 1.00 3.00 11.00


31

Figure 7: Example of Customization from Bharti Airtel (India).

Source: Bharti Airtel (2015).

The ability of customers to modify a plan to suit their own requirements is also in line with

articles from Grönroos & Voima, P. (2013), which identifies the value customers can bring to

companies as ‘co-creators’. However, the fact that customization is only offered in a minority

markets may indicate offering the functionality is technically challenging for MNOs, may lead

to inferior revenue, or may be difficult for consumers to understand.

5.5 Regionalization/Clusters

Literature from Birnik & Bowman (2007) suggests that some companies promote

regionalization as part of their standardization strategies - that they adopt standardized

marketing procedures specifically for certain regions, for example across all of their operations

in Latin America or Sub-Saharan Africa.


32

This theory cannot be tested reliably against the MNO data set as the MNOs sampled hold

(after the cut-off criteria is applied) insufficient subsidiaries in multiple regions. As shown in

Table 7, only two companies, Telefonica and Orange, hold more than one subsidiary in a region

outside of their dominant region. (Region classification: World Bank, 2014)

Table 7: Operations (after cut-off criteria) per region, by operator.

Source: Own.

However, by expanding the dataset to include the 35 subsidiaries which did not offer postpaid

services but met all other cut-off criteria (ie. That they only offered prepaid services to

consumers) (Table 6), we can see in Table 8 second column that the majority of MNOs which

did not offer postpaid services were in the Sub-Saharan African region, where 31 out of 32

MNOs did not. This also aligns to the article by Beck, Deirguc-Kunt & Peria (2007) discussing

the lack of access to banking services of many customers in Sub-Saharan Africa.

Table 8: Availability of postpaid services by region.

Source: Own.

5.6 Comparison against Earlier Studies

When comparing against the results from Gerpott & Jacopin (2005a) from their own study of

standardization of the MNO industry, which showed 60% standardization for product and 54%

for price, we can see an increase in standardization of product, and decrease in standardization

Row Labels nopostpaid postpaid Grand Total

East Asia & Pacific 1 1 2

Europe & Central Asia 2 39 41

Latin America & Caribbean 1 26 27

Middle East & North Africa 6 6

South Asia 7 7

Sub-Saharan Africa 31 1 32

Grand Total 35 80 115


33

in price. However, the product variables used between the two studies are quite different, given

the changes in the industry, and can only be compared loosely. Still, the results may be

interpreted to a limited degree to represent the maturation of the industry (from a product

perspective) since 2005.

Pricing metrics however are highly similar (with an update to the composition of the ‘baskets’

used in this study, to account for contemporary customer usage), and so this more recent study

can more reliably indicate declining price standardization. Part of this may be due to the

expansion of the industry into emerging markets over recent years, which may necessitate

greater levels of pricing adaptation.


34

6. Conclusion

The research is summarised, and its implications and limitations discussed. Areas for future

research are examined.

6.1 Discussion of Results

This research examines 10 MNO groups and 70 of their foreign subsidiaries, across markets

diverse in terms of region and economic development, and analyses their degree of product and

pricing standardization.

MNOs were moderately standardized in terms of product, and neither standardized nor adapted

in terms of pricing. Regional and economic (income) differences when comparing each

MNO’s home market to their foreign markets are highly positively correlated to a tendency to

adapt marketing, and vice versa, in line with the identified theories on standardization and

adaptation. This result is significant as prior research on the MNO industry (Gerpott & Jakopin,

2005a) did not link the levels of standardization found to these variables, despite their centrality

to standardization theories.

MNOs were most standardized in their product design of mobile data, with product designs for

SMS and voice more adapted to each market. This is in line with research on the industry which

shows an emphasis on mobile data volumes and revenues, and a comparative plateauing of

SMS and voice volumes.

Pricing levels exhibited a great degree of variance across markets, despite the attempt to

compare like-for-like pricing baskets. As the industry continues to attract customers from

emerging markets, this pricing adaptation is likely to increase, and has done so in the 10 years

since 2005 when the Gerpott & Jacopin (2005a) study was carried out. Alternatively, if the

future sees the rise of MNO groups headquartered in emerging markets, pricing standardization

may rise.

There does not appear to be a company, region or product/pricing component available which

is highly standardized, with the exception of MNOs consistently not offering consumers


35

unlimited data. Also, standardization results for MNOs headquartered in the European and

Central Asian region were only moderately standardized, despite the benefits to international

commerce brought about by the establishment of the European Union, which might have

implied higher standardization.

6.2 Implications

The results of this study hold significance for MNOs, regulators, and MNO industry

professionals.

On the basis that marketing standardization implies lower costs (via better economies of scale),

MNOs seeking to enter new markets will face higher costs when entering markets different

from their home country in terms of region or income levels, due to the need to adapt marketing.

Due to the high degree of variance seen in pricing, and absence of widespread plan

customization availability, there generally is not a range of product/pricing options sufficiently

broad to satisfy the requirements of consumers in every market.

However, the higher incidence of standardization across regionally and economically similar

regions, particularly for product components, indicates that by researching an MNO’s home

market, many inferences can be made about their operations in regionally and economically

similar markets. For example, this might allow an MNO to monitor developments in a local

competitor’s domestic markets in order to predict future product changes coming to the foreign

market.

For regulators, the results imply that regulations enacted in one market may have impacts in

geographically and economically similar markets, if both of those markets are served by the

same MNO group. This potentially raises the importance of effective regulation in terms of

allowing for the commercial development of MNOs and fairness for consumers.

For MNO professionals, whom may seek to change jobs from one MNO to a competitor, or to

a different market within the same company, the results indicate that some degree of marketing

adaptation is carried out by MNOs in all markets, to varying degrees. As such, MNO


36

professionals can retain their existing skills by seeking roles in regionally or economically

similar markets.

6.3 Future Research

By repeating this analysis in approximately 10 years, trends can be drawn and changes to the

industry evaluated. However, changes to the nature of the industry (as had occurred for this

study, against prior studies 10 years ago) may make comparisons difficult.

The research can be broadened in scope to include all MNOs within particular markets,

allowing the analysis of whether marketing strategies are applied based on local conditions and

competition, test marketing, or global standardization. The marketing variables of ‘place’ and

‘promotion’ could also be included, to measure how they are standardized and to compare their

standardization scores against the ‘product’ and ‘price’ variables examined in this work.

Internal factors of organizations can be examined, perhaps using qualitative key-informant

based research, to understand the internal rather than purely market-based drivers of

standardization.

Given the large amount of data captured by this study, it is possible for additional analysis to

be carried out specific to each MNO group, such as creating an MNO group ‘snapshot’ which

details the average offerings from each brand. This may be useful when attempting to predict

the characteristics of an MNO’s product and pricing offerings when they enter into or make an

acquisition into a new market, for example.

Research on other industries could also be examined, to understand whether the correlations

between high standardization scores and similarities of region/economic development are as

distinct.

6.3 Limitations

Our study is unable to make a complete statement on the standardization/adaptation of MNOs,

as we are only examining the product and pricing design function. Promotion, and place are


37

not examined. Additionally, only the postpaid mobile phone product is examined, not prepaid

or wireless broadband products, or any other value-added services.

By using our research and comparing the results against Gerpott & Jakopin (2005a), some

degree of time series analysis is made possible, allowing us to examine whether the product

design of MNOs has changed since 2005. However, as the methodology and scope of this

earlier work differs from our own, only limited conclusions can be drawn. As such it is best to

consider this work a cross-sectional study, wherein concrete statements on trends cannot be

made.

Certain characteristics of MNO services which individual readers may be most familiar with

eg. The provisioning of ‘4G’ transmission-type services, the availability of promotional music

offers etc. are not present in this study. As the industry evolves, it is likely that future research

will differ in its selection of product variables in particular. As such, future research which

compares against this work for time-series analysis should denote differences in variables.

The weightings of individual product and pricing variables has an impact on the final

standardization scores. As such, if this research is repeated with different weightings, different

standardization scores will be produced. However, given that the standardization scores are

examined at a high level, weightings would have to change to a large degree in order to have a

large impact on the results.

Our reliance on operator’s websites allows the possibility that alternative product strategies are

carried out and visible only in other channels that we do not have access to, such as retail and

call centres. .We are also reliant on automatic translation tools to allow examination of content

in languages other than English. However, we anticipate these risks to be minimal given that

the companies and subsidiaries examined are not small operations.


38

Appendix A - Raw Data

This is the original data collected from the 115 MNOs in 2015, organised by MNO, across all

of the variables examined. Providing this data allows the analysis to be repeated, or for future

researchers to compare results for specific markets or MNOs over time.

Line

Comp

anyCountry

Mark

et

Data No

Inclusi

on

Data

Bucket

Data

Speed/

Networ

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sharing#Plans

Low:

200mbMed: 1GB High: 3GB PPP$ $Low $Med $High Region Income

Postp

aid?

1 Airtel Seychelles Foreign 1 0 0 0 1 1 0 0 1 0 0 0 0 6 350 725 1250 7.94 44.09 91.32 157.45 Sub-Saharan AfricaUpper middle incomepostpaid

2 Airtel India Domestic 1 1 1 0 1 1 0 1 1 0 1 0 1 7 199 599 799 16.76 11.88 35.75 47.68 South AsiaLow er middle incomepostpaid

3 Airtel Bangladesh Foreign 0 1 0 0 1 1 0 0 1 0 0 0 0 8 299 299 699 25.97 11.51 11.51 26.91 South AsiaLow incomepostpaid

4 Airtel Sri Lanka Foreign 1 1 0 0 1 0 0 1 0 0 0 0 0 8 350 499 999 43.49 8.05 11.48 22.97 South AsiaLow er middle incomepostpaid

5 Airtel Burkina FasoForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 223.15 prep prep prep Sub-Saharan AfricaLow incomeprep

6 Airtel Chad Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 249.24 prep prep prep Sub-Saharan AfricaLow incomeprep

7 Airtel Congo, Dem. Rep.Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 550.37 prep prep prep Sub-Saharan AfricaLow incomeprep

8 Airtel Gabon Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 296.74 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

9 Airtel Ghana Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 0.91 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

10 Airtel Kenya Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 38.38 prep prep prep Sub-Saharan AfricaLow incomeprep

11 Airtel Madagascar Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 722.59 prep prep prep Sub-Saharan AfricaLow incomeprep

12 Airtel Malaw i Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 105.80 prep prep prep Sub-Saharan AfricaLow incomeprep

13 Airtel Niger Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 224.00 prep prep prep Sub-Saharan AfricaLow incomeprep

14 Airtel Congo, Rep. Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 266.62 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

15 Airtel Rw anda Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 280.28 prep prep prep Sub-Saharan AfricaLow incomeprep

16 Airtel Sierra Leone Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 1,904.95 prep prep prep Sub-Saharan AfricaLow incomeprep

17 Airtel Uganda Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 1,047.02 prep prep prep Sub-Saharan AfricaLow incomeprep

18 Airtel Zambia Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 2.54 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

19 Am. MovilCosta Rica Foreign 0 0 1 1 0 1 0 1 1 0 1 1 0 3 7000 9500 12500 366.82 19.08 25.90 34.08 Latin America & CaribbeanUpper middle incomepostpaid

20 Am. MovilBrazil Foreign 0 1 0 1 0 1 1 0 1 0 1 1 0 4 70 213 294 1.61 43.53 132.46 182.84 Latin America & CaribbeanUpper middle incomepostpaid

21 Am. MovilArgentina Foreign 0 1 0 0 0 1 0 0 1 0 0 1 0 5 100 190 190 2.66 37.53 71.30 71.30 Latin America & CaribbeanUpper middle incomepostpaid

22 Am. MovilUruguay Foreign 0 1 0 0 0 1 0 0 1 0 0 0 0 5 350 500 700 17.09 20.48 29.25 40.96 Latin America & CaribbeanHigh incomepostpaid

23 Am. MovilEl Salvador Foreign 1 0 0 0 0 1 0 0 1 0 0 1 0 6 16.99 46.99 65 0.49 34.48 95.36 131.90 Latin America & CaribbeanLow er middle incomepostpaid

24 Am. MovilParaguay Foreign 0 1 0 1 0 1 0 0 1 0 0 1 0 8 60000 170000 250000 2,268.05 26.45 74.95 110.23 Latin America & CaribbeanLow er middle incomepostpaid

25 Am. MovilPanama Foreign 0 1 0 0 1 0 0 0 1 0 0 0 0 9 14.99 27.99 0.57 26.37 49.24 - Latin America & CaribbeanUpper middle incomepostpaid

26 Am. MovilGuatemala Foreign 0 1 0 0 0 1 1 0 1 1 0 1 0 13 262 340 595 3.74 69.96 90.79 158.88 Latin America & CaribbeanLow er middle incomepostpaid

27 Am. MovilMexico Domestic 0 1 0 0 0 1 0 0 1 0 0 1 0 21 349 399 999 8.00 43.65 49.90 124.93 Latin America & CaribbeanUpper middle incomepostpaid

28 Am. MovilPuerto Rico Foreign 0 1 0 0 0 1 1 0 1 1 0 1 1 21 19.99 49.99 59.98 0.82 24.35 60.89 73.06 Latin America & CaribbeanHigh incomepostpaid

29 Am. MovilDominican RepublicForeign 1 1 0 0 0 1 0 0 1 0 0 1 1 23 595 1365 2195 20.17 29.50 67.68 108.83 Latin America & CaribbeanUpper middle incomepostpaid

30 Am. MovilChile Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 26 10350 14450 26400 355.41 29.12 40.66 74.28 Latin America & CaribbeanHigh incomepostpaid

31 Am. MovilHonduras Foreign 1 0 0 0 1 0 0 1 0 0 0 1 0 26 40 55 80 10.15 3.94 5.42 7.88 Latin America & CaribbeanLow er middle incomepostpaid

32 Am. MovilPeru Foreign 0 1 0 0 0 1 0 0 1 0 0 1 1 37 100 120 155 1.53 65.39 78.47 101.36 Latin America & CaribbeanUpper middle incomepostpaid

33 Am. MovilEcuador Foreign 1 1 0 0 0 1 0 1 1 0 0 1 0 70 15 50 100 0.55 27.21 90.71 181.41 Latin America & CaribbeanUpper middle incomepostpaid

34 Am. MovilColombia Foreign 1 1 0 0 0 1 1 0 1 1 0 0 0 71 32900 59900 89900 1,177.96 27.93 50.85 76.32 Latin America & CaribbeanUpper middle incomepostpaid

35 Am. MovilNicaragua Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 9.86 prep prep prep Latin America & CaribbeanLow er middle incomeprep

36 Etisalat United Arab EmiratesDomestic 0 1 0 0 1 0 0 0 1 0 1 1 1 5 150 200 350 2.59 57.92 77.23 135.16 Middle East & North AfricaHigh incomepostpaid

37 Etisalat Sri Lanka Foreign 0 1 0 0 1 1 0 1 1 0 1 0 1 16 400 600 1000 43.49 9.20 13.80 23.00 South AsiaLow er middle incomepostpaid

38 Etisalat Afghanistan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 18.92 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

39 Etisalat Benin Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 222.00 prep prep prep Sub-Saharan AfricaLow incomeprep

40 Etisalat Central African RepublicForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 272.58 prep prep prep Sub-Saharan AfricaLow incomeprep

41 Etisalat Gabon Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 296.74 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

42 Etisalat Cote d'Ivoire Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 235.28 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

43 Etisalat Niger Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 224.00 prep prep prep Sub-Saharan AfricaLow incomeprep

44 Etisalat Togo Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 226.12 prep prep prep Sub-Saharan AfricaLow incomeprep

45 Etisalat Sudan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 2.47 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

46 MTN South Africa Domesticprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 5.11 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

47 MTN Afghanistan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 18.92 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

48 MTN Congo, Rep. Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 266.62 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

49 MTN Ghana Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 0.91 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

50 MTN Guinea-BissauForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 197.95 prep prep prep Sub-Saharan AfricaLow incomeprep

51 MTN Uganda Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 1,047.02 prep prep prep Sub-Saharan AfricaLow incomeprep

52 MTN Zambia Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 2.54 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

53 OoredooKuw ait Foreign 1 1 0 0 1 1 1 1 1 1 0 1 1 7 10 10 15 0.18 55.93 55.93 83.90 Middle East & North AfricaHigh incomepostpaid

54 OoredooQatar Domestic 0 1 0 0 0 1 1 0 1 1 0 0 0 8 35 100 450 2.49 14.08 40.24 181.07 Middle East & North AfricaHigh incomepostpaid

55 OoredooMaldives Foreign 0 1 0 0 0 1 0 0 1 0 0 0 0 9 149 499 749 8.79 16.96 56.79 85.24 South AsiaUpper middle incomepostpaid

56 OoredooMyanmar Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 234.97 prep prep prep East Asia & Pacif icLow incomeprep

57 Orange Spain Foreign 0 1 0 0 1 0 0 1 1 1 0 1 1 4 20.95 21.95 39.95 0.68 30.67 32.13 58.48 Europe & Central AsiaHigh incomepostpaid

58 Orange Israel Foreign 0 1 0 0 0 0 1 0 0 1 0 0 0 4 85 85 99 3.98 21.33 21.33 24.85 Middle East & North AfricaHigh incomepostpaid

59 Orange Egypt, Arab Rep.Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 6 100 100 300 1.93 51.90 51.90 155.70 Middle East & North AfricaLow er middle incomepostpaid

60 Orange France Domestic 0 1 1 0 0 0 1 0 1 1 0 1 1 9 9.99 29.99 32.99 0.85 11.82 35.48 39.03 Europe & Central AsiaHigh incomepostpaid

61 Orange Moldova Foreign 1 1 0 0 1 1 1 1 1 1 0 1 0 11 90 150 250 6.03 14.91 24.86 41.43 Europe & Central AsiaLow er middle incomepostpaid

62 Orange Slovak RepublicForeign 0 1 0 0 0 1 1 0 1 1 0 1 1 12 15 35 40 0.51 29.40 68.60 78.40 Europe & Central AsiaHigh incomepostpaid

63 Orange Armenia Foreign 0 1 0 0 0 1 0 0 1 0 0 1 1 14 3000 6000 10000 184.60 16.25 32.50 54.17 Europe & Central AsiaLow er middle incomepostpaid

64 Orange Dominica Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 16 650 1850 2650 1.87 34.00 98.00 141.00 Latin America & CaribbeanUpper middle incomepostpaid

65 Orange Romania Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 19 11 16 31 1.66 6.61 9.61 18.62 Europe & Central AsiaUpper middle incomepostpaid

66 Orange Cameroon Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 231.93 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

67 Orange Central African RepublicForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 272.58 prep prep prep Sub-Saharan AfricaLow incomeprep

68 Orange Congo, Rep. Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 266.62 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

69 Telef. Argentina Foreign 0 1 0 0 0 1 1 0 1 0 0 1 0 3 149 229 349 2.66 55.91 85.93 130.97 Latin America & CaribbeanUpper middle incomepostpaid

70 Telef. Costa Rica Foreign 0 1 0 0 0 1 0 0 1 0 0 1 0 5 9600 9600 17280 366.82 26.17 26.17 47.11 Latin America & CaribbeanUpper middle incomepostpaid

71 Telef. Uruguay Foreign 0 1 0 0 1 0 0 0 1 0 0 1 0 5 499 599 899 17.09 29.20 35.05 52.60 Latin America & CaribbeanHigh incomepostpaid

72 Telef. Venezuela, RBForeign 0 1 0 0 0 1 0 0 1 0 0 0 0 5 210 550 4.79 43.84 114.81 - Latin America & CaribbeanUpper middle incomepostpaid

73 Telef. Mexico Foreign 0 1 0 0 0 0 1 0 0 1 0 1 0 5 349 440 999 8.00 43.65 55.03 124.93 Latin America & CaribbeanUpper middle incomepostpaid

74 Telef. Peru Foreign 0 1 0 0 0 1 1 0 1 0 0 1 0 7 54.9 99.9 139.9 1.53 35.90 65.33 91.49 Latin America & CaribbeanUpper middle incomepostpaid

75 Telef. Spain Domestic 0 1 0 0 0 1 1 0 1 1 0 1 1 8 11 25 45 0.68 16.10 36.60 65.88 Europe & Central AsiaHigh incomepostpaid

76 Telef. Chile Foreign 0 1 0 0 1 0 1 0 1 0 0 1 0 8 14390 18890 31990 355.41 40.49 53.15 90.01 Latin America & CaribbeanHigh incomepostpaid

77 Telef. Ecuador Foreign 1 1 0 0 1 1 0 0 1 0 0 1 0 8 20 35 60 0.55 36.28 63.49 108.85 Latin America & CaribbeanUpper middle incomepostpaid

78 Telef. United KingdomForeign 0 1 0 0 0 0 1 0 1 1 0 1 1 14 10.5 16 22 0.70 15.10 23.02 31.65 Europe & Central AsiaHigh incomepostpaid

79 Telenor Hungary Foreign 0 1 0 0 1 1 1 0 1 1 1 1 1 5 2790 9490 14990 128.42 21.73 73.90 116.72 Europe & Central AsiaUpper middle incomepostpaid

80 Telenor Denmark Foreign 0 1 0 0 0 0 1 0 1 1 0 1 0 6 99 99 179 7.73 12.80 12.80 23.14 Europe & Central AsiaHigh incomepostpaid

81 Telenor Pakistan Foreign 0 1 0 0 0 1 0 0 1 0 0 0 0 6 300 1000 3000 26.83 11.18 37.27 111.81 South AsiaLow er middle incomepostpaid

82 Telenor Norw ay Domestic 0 1 1 0 0 0 1 0 0 1 0 1 0 7 199 249 349 9.05 21.99 27.52 38.57 Europe & Central AsiaHigh incomepostpaid

83 Telenor Montenegro Foreign 0 1 1 0 0 1 0 0 1 0 0 1 0 10 11.9 24.9 59.9 0.38 31.41 65.72 158.09 Europe & Central AsiaUpper middle incomepostpaid

84 Telenor Serbia Foreign 0 1 1 0 0 1 0 0 1 0 0 1 0 12 895 1995 6995 41.56 21.54 48.00 168.32 Europe & Central AsiaUpper middle incomepostpaid

85 Telenor Sw eden Foreign 0 1 0 0 0 0 1 0 0 1 0 1 1 12 199 299 299 8.72 22.82 34.29 34.29 Europe & Central AsiaHigh incomepostpaid

86 Telenor Bulgaria Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 20 14.99 25.99 0 0.70 21.34 37.00 - Europe & Central AsiaUpper middle incomepostpaid

87 Telia.S Norw ay Foreign 0 1 1 0 0 0 1 0 0 1 0 1 1 4 19 199 299 9.05 2.10 21.99 33.05 Europe & Central AsiaHigh incomepostpaid

88 Telia.S Denmark Foreign 0 1 0 0 0 1 1 0 1 0 0 1 1 5 129 129 129 7.73 16.68 16.68 16.68 Europe & Central AsiaHigh incomepostpaid

89 Telia.S Estonia Foreign 1 1 0 0 1 1 0 0 1 0 1 1 1 5 15 18 0.56 27.00 32.40 - Europe & Central AsiaHigh incomepostpaid

90 Telia.S Sw eden Domestic 0 1 0 0 0 1 1 0 1 1 0 1 1 6 199 299 299 8.72 22.82 34.29 34.29 Europe & Central AsiaHigh incomepostpaid

91 Telia.S Finland Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 7 9.9 14.9 19.9 0.93 10.65 16.03 21.40 Europe & Central AsiaHigh incomepostpaid

92 Telia.S Lithuania Foreign 0 1 0 0 0 1 1 0 1 1 0 1 0 9 8.11 9.56 14.19 1.59 5.11 6.02 8.94 Europe & Central AsiaHigh incomepostpaid

93 Telia.S Uzbekistan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 761.30 prep prep prep Europe & Central AsiaLow er middle incomeprep

94 TMobile Austria Foreign 0 1 1 0 0 0 1 0 0 1 0 1 0 3 19.95 29.99 39.99 0.84 23.84 35.84 47.79 Europe & Central AsiaHigh incomepostpaid

95 TMobile Germany Domestic 0 1 1 0 0 0 1 0 0 1 0 1 0 4 26.95 35.95 44.95 0.78 34.39 45.88 57.36 Europe & Central AsiaHigh incomepostpaid

96 TMobile Czech RepublicForeign 0 1 0 0 0 0 1 1 1 1 0 1 1 5 549 749 999 13.50 40.67 55.48 74.00 Europe & Central AsiaHigh incomepostpaid

97 TMobile Albania Foreign 0 1 0 0 0 1 0 0 1 0 0 1 0 5 1200 3600 7200 47.46 25.28 75.85 151.71 Europe & Central AsiaHigh incomepostpaid

98 TMobile Netherlands Foreign 0 1 1 0 0 0 1 1 1 1 1 1 0 6 18.5 21 33.5 0.83 22.39 25.42 40.54 Europe & Central AsiaHigh incomepostpaid

99 TMobile Poland Foreign 0 1 0 0 1 0 1 1 1 1 0 1 1 8 27 41 41.99 1.82 14.80 22.48 23.02 Europe & Central AsiaHigh incomepostpaid

100 VodafonePortugal Foreign 0 1 0 0 0 0 1 0 0 1 0 1 1 1 25.9 30.9 59.9 0.61 42.34 50.52 97.92 Europe & Central AsiaHigh incomepostpaid

101 VodafoneIreland Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 3 35 35 55 0.82 42.46 42.46 66.72 Europe & Central AsiaHigh incomepostpaid

102 VodafoneItaly Foreign 0 1 0 0 0 0 1 0 0 1 0 1 0 3 45 45 75 0.76 59.20 59.20 98.67 Europe & Central AsiaHigh incomepostpaid

103 VodafoneMalta Foreign 0 1 0 0 0 1 1 0 1 1 0 1 1 3 35 35 60 0.59 59.43 59.43 101.88 Middle East & North AfricaHigh incomepostpaid

104 VodafoneHungary Foreign 0 1 0 0 0 1 1 0 1 1 0 1 1 5 4990 11990 14990 128.42 38.86 93.36 116.72 Europe & Central AsiaUpper middle incomepostpaid

105 VodafoneNew ZealandForeign 0 1 0 0 0 1 1 0 1 1 0 1 1 5 39 39 69 1.46 26.80 26.80 47.42 East Asia & Pacif icHigh incomepostpaid

106 VodafoneUnited KingdomDomestic 0 1 1 0 0 0 1 0 1 1 0 1 1 7 9.5 15.3 19.8 0.70 13.67 22.01 28.48 Europe & Central AsiaHigh incomepostpaid

107 VodafoneGermany Foreign 0 1 1 0 0 1 1 0 1 1 0 1 0 7 12.99 34.99 39.99 0.78 16.58 44.65 51.03 Europe & Central AsiaHigh incomepostpaid

108 VodafoneRomania Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 7 7 15 39 1.66 4.21 9.01 23.43 Europe & Central AsiaUpper middle incomepostpaid

109 VodafoneSpain Foreign 1 1 0 0 1 1 1 1 1 1 1 1 0 7 10.5 12 39 0.68 15.37 17.57 57.09 Europe & Central AsiaHigh incomepostpaid

110 VodafoneCzech RepublicForeign 0 1 0 0 0 0 1 0 1 1 0 0 1 8 549 749 999 13.50 40.67 55.48 74.00 Europe & Central AsiaHigh incomepostpaid

111 VodafoneTurkey Foreign 0 1 0 0 1 1 0 0 1 0 1 1 1 8 19 29 65 1.10 17.30 26.41 59.19 Europe & Central AsiaUpper middle incomepostpaid

112 VodafoneNetherlands Foreign 1 1 1 0 0 1 1 0 1 1 1 1 0 9 14 18 39 0.83 16.94 21.78 47.20 Europe & Central AsiaHigh incomepostpaid

113 VodafoneGreece Foreign 0 1 1 0 1 1 0 0 1 0 0 1 1 15 31.5 55.35 76 0.64 48.96 86.04 118.14 Europe & Central AsiaHigh incomepostpaid

114 VodafoneIndia Foreign 1 1 0 0 1 1 0 0 1 0 0 0 1 16 499 699 1299 16.76 29.78 41.71 77.52 South AsiaLow er middle incomepostpaid

115 VodafoneAlbania Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 47.46 prep prep prep Europe & Central AsiaHigh incomeprep


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Low:

200mbMed: 1GB High: 3GB PPP$ $Low $Med $High Region Income

Postp

aid?

1 Airtel Seychelles Foreign 1 0 0 0 1 1 0 0 1 0 0 0 0 6 350 725 1250 7.94 44.09 91.32 157.45 Sub-Saharan AfricaUpper middle incomepostpaid

2 Airtel India Domestic 1 1 1 0 1 1 0 1 1 0 1 0 1 7 199 599 799 16.76 11.88 35.75 47.68 South AsiaLow er middle incomepostpaid

3 Airtel Bangladesh Foreign 0 1 0 0 1 1 0 0 1 0 0 0 0 8 299 299 699 25.97 11.51 11.51 26.91 South AsiaLow incomepostpaid

4 Airtel Sri Lanka Foreign 1 1 0 0 1 0 0 1 0 0 0 0 0 8 350 499 999 43.49 8.05 11.48 22.97 South AsiaLow er middle incomepostpaid

5 Airtel Burkina FasoForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 223.15 prep prep prep Sub-Saharan AfricaLow incomeprep

6 Airtel Chad Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 249.24 prep prep prep Sub-Saharan AfricaLow incomeprep

7 Airtel Congo, Dem. Rep.Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 550.37 prep prep prep Sub-Saharan AfricaLow incomeprep

8 Airtel Gabon Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 296.74 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

9 Airtel Ghana Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 0.91 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

10 Airtel Kenya Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 38.38 prep prep prep Sub-Saharan AfricaLow incomeprep

11 Airtel Madagascar Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 722.59 prep prep prep Sub-Saharan AfricaLow incomeprep

12 Airtel Malaw i Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 105.80 prep prep prep Sub-Saharan AfricaLow incomeprep

13 Airtel Niger Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 224.00 prep prep prep Sub-Saharan AfricaLow incomeprep

14 Airtel Congo, Rep. Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 266.62 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

15 Airtel Rw anda Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 280.28 prep prep prep Sub-Saharan AfricaLow incomeprep

16 Airtel Sierra Leone Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 1,904.95 prep prep prep Sub-Saharan AfricaLow incomeprep

17 Airtel Uganda Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 1,047.02 prep prep prep Sub-Saharan AfricaLow incomeprep

18 Airtel Zambia Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 2.54 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

19 Am. MovilCosta Rica Foreign 0 0 1 1 0 1 0 1 1 0 1 1 0 3 7000 9500 12500 366.82 19.08 25.90 34.08 Latin America & CaribbeanUpper middle incomepostpaid

20 Am. MovilBrazil Foreign 0 1 0 1 0 1 1 0 1 0 1 1 0 4 70 213 294 1.61 43.53 132.46 182.84 Latin America & CaribbeanUpper middle incomepostpaid

21 Am. MovilArgentina Foreign 0 1 0 0 0 1 0 0 1 0 0 1 0 5 100 190 190 2.66 37.53 71.30 71.30 Latin America & CaribbeanUpper middle incomepostpaid

22 Am. MovilUruguay Foreign 0 1 0 0 0 1 0 0 1 0 0 0 0 5 350 500 700 17.09 20.48 29.25 40.96 Latin America & CaribbeanHigh incomepostpaid

23 Am. MovilEl Salvador Foreign 1 0 0 0 0 1 0 0 1 0 0 1 0 6 16.99 46.99 65 0.49 34.48 95.36 131.90 Latin America & CaribbeanLow er middle incomepostpaid

24 Am. MovilParaguay Foreign 0 1 0 1 0 1 0 0 1 0 0 1 0 8 60000 170000 250000 2,268.05 26.45 74.95 110.23 Latin America & CaribbeanLow er middle incomepostpaid

25 Am. MovilPanama Foreign 0 1 0 0 1 0 0 0 1 0 0 0 0 9 14.99 27.99 0.57 26.37 49.24 - Latin America & CaribbeanUpper middle incomepostpaid

26 Am. MovilGuatemala Foreign 0 1 0 0 0 1 1 0 1 1 0 1 0 13 262 340 595 3.74 69.96 90.79 158.88 Latin America & CaribbeanLow er middle incomepostpaid

27 Am. MovilMexico Domestic 0 1 0 0 0 1 0 0 1 0 0 1 0 21 349 399 999 8.00 43.65 49.90 124.93 Latin America & CaribbeanUpper middle incomepostpaid

28 Am. MovilPuerto Rico Foreign 0 1 0 0 0 1 1 0 1 1 0 1 1 21 19.99 49.99 59.98 0.82 24.35 60.89 73.06 Latin America & CaribbeanHigh incomepostpaid

29 Am. MovilDominican RepublicForeign 1 1 0 0 0 1 0 0 1 0 0 1 1 23 595 1365 2195 20.17 29.50 67.68 108.83 Latin America & CaribbeanUpper middle incomepostpaid

30 Am. MovilChile Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 26 10350 14450 26400 355.41 29.12 40.66 74.28 Latin America & CaribbeanHigh incomepostpaid

31 Am. MovilHonduras Foreign 1 0 0 0 1 0 0 1 0 0 0 1 0 26 40 55 80 10.15 3.94 5.42 7.88 Latin America & CaribbeanLow er middle incomepostpaid

32 Am. MovilPeru Foreign 0 1 0 0 0 1 0 0 1 0 0 1 1 37 100 120 155 1.53 65.39 78.47 101.36 Latin America & CaribbeanUpper middle incomepostpaid

33 Am. MovilEcuador Foreign 1 1 0 0 0 1 0 1 1 0 0 1 0 70 15 50 100 0.55 27.21 90.71 181.41 Latin America & CaribbeanUpper middle incomepostpaid

34 Am. MovilColombia Foreign 1 1 0 0 0 1 1 0 1 1 0 0 0 71 32900 59900 89900 1,177.96 27.93 50.85 76.32 Latin America & CaribbeanUpper middle incomepostpaid

35 Am. MovilNicaragua Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 9.86 prep prep prep Latin America & CaribbeanLow er middle incomeprep

36 Etisalat United Arab EmiratesDomestic 0 1 0 0 1 0 0 0 1 0 1 1 1 5 150 200 350 2.59 57.92 77.23 135.16 Middle East & North AfricaHigh incomepostpaid

37 Etisalat Sri Lanka Foreign 0 1 0 0 1 1 0 1 1 0 1 0 1 16 400 600 1000 43.49 9.20 13.80 23.00 South AsiaLow er middle incomepostpaid

38 Etisalat Afghanistan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 18.92 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

39 Etisalat Benin Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 222.00 prep prep prep Sub-Saharan AfricaLow incomeprep

40 Etisalat Central African RepublicForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 272.58 prep prep prep Sub-Saharan AfricaLow incomeprep

41 Etisalat Gabon Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 296.74 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

42 Etisalat Cote d'Ivoire Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 235.28 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

43 Etisalat Niger Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 224.00 prep prep prep Sub-Saharan AfricaLow incomeprep

44 Etisalat Togo Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 226.12 prep prep prep Sub-Saharan AfricaLow incomeprep

45 Etisalat Sudan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 2.47 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

46 MTN South Africa Domesticprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 5.11 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

47 MTN Afghanistan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 18.92 prep prep prep Sub-Saharan AfricaUpper middle incomeprep

48 MTN Congo, Rep. Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 266.62 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

49 MTN Ghana Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 0.91 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

50 MTN Guinea-BissauForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 197.95 prep prep prep Sub-Saharan AfricaLow incomeprep

51 MTN Uganda Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 1,047.02 prep prep prep Sub-Saharan AfricaLow incomeprep

52 MTN Zambia Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 2.54 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

53 OoredooKuw ait Foreign 1 1 0 0 1 1 1 1 1 1 0 1 1 7 10 10 15 0.18 55.93 55.93 83.90 Middle East & North AfricaHigh incomepostpaid

54 OoredooQatar Domestic 0 1 0 0 0 1 1 0 1 1 0 0 0 8 35 100 450 2.49 14.08 40.24 181.07 Middle East & North AfricaHigh incomepostpaid

55 OoredooMaldives Foreign 0 1 0 0 0 1 0 0 1 0 0 0 0 9 149 499 749 8.79 16.96 56.79 85.24 South AsiaUpper middle incomepostpaid

56 OoredooMyanmar Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 234.97 prep prep prep East Asia & Pacif icLow incomeprep

57 Orange Spain Foreign 0 1 0 0 1 0 0 1 1 1 0 1 1 4 20.95 21.95 39.95 0.68 30.67 32.13 58.48 Europe & Central AsiaHigh incomepostpaid

58 Orange Israel Foreign 0 1 0 0 0 0 1 0 0 1 0 0 0 4 85 85 99 3.98 21.33 21.33 24.85 Middle East & North AfricaHigh incomepostpaid

59 Orange Egypt, Arab Rep.Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 6 100 100 300 1.93 51.90 51.90 155.70 Middle East & North AfricaLow er middle incomepostpaid

60 Orange France Domestic 0 1 1 0 0 0 1 0 1 1 0 1 1 9 9.99 29.99 32.99 0.85 11.82 35.48 39.03 Europe & Central AsiaHigh incomepostpaid

61 Orange Moldova Foreign 1 1 0 0 1 1 1 1 1 1 0 1 0 11 90 150 250 6.03 14.91 24.86 41.43 Europe & Central AsiaLow er middle incomepostpaid

62 Orange Slovak RepublicForeign 0 1 0 0 0 1 1 0 1 1 0 1 1 12 15 35 40 0.51 29.40 68.60 78.40 Europe & Central AsiaHigh incomepostpaid

63 Orange Armenia Foreign 0 1 0 0 0 1 0 0 1 0 0 1 1 14 3000 6000 10000 184.60 16.25 32.50 54.17 Europe & Central AsiaLow er middle incomepostpaid

64 Orange Dominica Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 16 650 1850 2650 1.87 34.00 98.00 141.00 Latin America & CaribbeanUpper middle incomepostpaid

65 Orange Romania Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 19 11 16 31 1.66 6.61 9.61 18.62 Europe & Central AsiaUpper middle incomepostpaid

66 Orange Cameroon Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 231.93 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

67 Orange Central African RepublicForeignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 272.58 prep prep prep Sub-Saharan AfricaLow incomeprep

68 Orange Congo, Rep. Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 266.62 prep prep prep Sub-Saharan AfricaLow er middle incomeprep

69 Telef. Argentina Foreign 0 1 0 0 0 1 1 0 1 0 0 1 0 3 149 229 349 2.66 55.91 85.93 130.97 Latin America & CaribbeanUpper middle incomepostpaid

70 Telef. Costa Rica Foreign 0 1 0 0 0 1 0 0 1 0 0 1 0 5 9600 9600 17280 366.82 26.17 26.17 47.11 Latin America & CaribbeanUpper middle incomepostpaid

71 Telef. Uruguay Foreign 0 1 0 0 1 0 0 0 1 0 0 1 0 5 499 599 899 17.09 29.20 35.05 52.60 Latin America & CaribbeanHigh incomepostpaid

72 Telef. Venezuela, RBForeign 0 1 0 0 0 1 0 0 1 0 0 0 0 5 210 550 4.79 43.84 114.81 - Latin America & CaribbeanUpper middle incomepostpaid

73 Telef. Mexico Foreign 0 1 0 0 0 0 1 0 0 1 0 1 0 5 349 440 999 8.00 43.65 55.03 124.93 Latin America & CaribbeanUpper middle incomepostpaid

74 Telef. Peru Foreign 0 1 0 0 0 1 1 0 1 0 0 1 0 7 54.9 99.9 139.9 1.53 35.90 65.33 91.49 Latin America & CaribbeanUpper middle incomepostpaid

75 Telef. Spain Domestic 0 1 0 0 0 1 1 0 1 1 0 1 1 8 11 25 45 0.68 16.10 36.60 65.88 Europe & Central AsiaHigh incomepostpaid

76 Telef. Chile Foreign 0 1 0 0 1 0 1 0 1 0 0 1 0 8 14390 18890 31990 355.41 40.49 53.15 90.01 Latin America & CaribbeanHigh incomepostpaid

77 Telef. Ecuador Foreign 1 1 0 0 1 1 0 0 1 0 0 1 0 8 20 35 60 0.55 36.28 63.49 108.85 Latin America & CaribbeanUpper middle incomepostpaid

78 Telef. United KingdomForeign 0 1 0 0 0 0 1 0 1 1 0 1 1 14 10.5 16 22 0.70 15.10 23.02 31.65 Europe & Central AsiaHigh incomepostpaid

79 Telenor Hungary Foreign 0 1 0 0 1 1 1 0 1 1 1 1 1 5 2790 9490 14990 128.42 21.73 73.90 116.72 Europe & Central AsiaUpper middle incomepostpaid

80 Telenor Denmark Foreign 0 1 0 0 0 0 1 0 1 1 0 1 0 6 99 99 179 7.73 12.80 12.80 23.14 Europe & Central AsiaHigh incomepostpaid

81 Telenor Pakistan Foreign 0 1 0 0 0 1 0 0 1 0 0 0 0 6 300 1000 3000 26.83 11.18 37.27 111.81 South AsiaLow er middle incomepostpaid

82 Telenor Norw ay Domestic 0 1 1 0 0 0 1 0 0 1 0 1 0 7 199 249 349 9.05 21.99 27.52 38.57 Europe & Central AsiaHigh incomepostpaid

83 Telenor Montenegro Foreign 0 1 1 0 0 1 0 0 1 0 0 1 0 10 11.9 24.9 59.9 0.38 31.41 65.72 158.09 Europe & Central AsiaUpper middle incomepostpaid

84 Telenor Serbia Foreign 0 1 1 0 0 1 0 0 1 0 0 1 0 12 895 1995 6995 41.56 21.54 48.00 168.32 Europe & Central AsiaUpper middle incomepostpaid

85 Telenor Sw eden Foreign 0 1 0 0 0 0 1 0 0 1 0 1 1 12 199 299 299 8.72 22.82 34.29 34.29 Europe & Central AsiaHigh incomepostpaid

86 Telenor Bulgaria Foreign 1 1 0 0 0 1 0 0 1 0 0 1 0 20 14.99 25.99 0 0.70 21.34 37.00 - Europe & Central AsiaUpper middle incomepostpaid

87 Telia.S Norw ay Foreign 0 1 1 0 0 0 1 0 0 1 0 1 1 4 19 199 299 9.05 2.10 21.99 33.05 Europe & Central AsiaHigh incomepostpaid

88 Telia.S Denmark Foreign 0 1 0 0 0 1 1 0 1 0 0 1 1 5 129 129 129 7.73 16.68 16.68 16.68 Europe & Central AsiaHigh incomepostpaid

89 Telia.S Estonia Foreign 1 1 0 0 1 1 0 0 1 0 1 1 1 5 15 18 0.56 27.00 32.40 - Europe & Central AsiaHigh incomepostpaid

90 Telia.S Sw eden Domestic 0 1 0 0 0 1 1 0 1 1 0 1 1 6 199 299 299 8.72 22.82 34.29 34.29 Europe & Central AsiaHigh incomepostpaid

91 Telia.S Finland Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 7 9.9 14.9 19.9 0.93 10.65 16.03 21.40 Europe & Central AsiaHigh incomepostpaid

92 Telia.S Lithuania Foreign 0 1 0 0 0 1 1 0 1 1 0 1 0 9 8.11 9.56 14.19 1.59 5.11 6.02 8.94 Europe & Central AsiaHigh incomepostpaid

93 Telia.S Uzbekistan Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 761.30 prep prep prep Europe & Central AsiaLow er middle incomeprep

94 TMobile Austria Foreign 0 1 1 0 0 0 1 0 0 1 0 1 0 3 19.95 29.99 39.99 0.84 23.84 35.84 47.79 Europe & Central AsiaHigh incomepostpaid

95 TMobile Germany Domestic 0 1 1 0 0 0 1 0 0 1 0 1 0 4 26.95 35.95 44.95 0.78 34.39 45.88 57.36 Europe & Central AsiaHigh incomepostpaid

96 TMobile Czech RepublicForeign 0 1 0 0 0 0 1 1 1 1 0 1 1 5 549 749 999 13.50 40.67 55.48 74.00 Europe & Central AsiaHigh incomepostpaid

97 TMobile Albania Foreign 0 1 0 0 0 1 0 0 1 0 0 1 0 5 1200 3600 7200 47.46 25.28 75.85 151.71 Europe & Central AsiaHigh incomepostpaid

98 TMobile Netherlands Foreign 0 1 1 0 0 0 1 1 1 1 1 1 0 6 18.5 21 33.5 0.83 22.39 25.42 40.54 Europe & Central AsiaHigh incomepostpaid

99 TMobile Poland Foreign 0 1 0 0 1 0 1 1 1 1 0 1 1 8 27 41 41.99 1.82 14.80 22.48 23.02 Europe & Central AsiaHigh incomepostpaid

100 VodafonePortugal Foreign 0 1 0 0 0 0 1 0 0 1 0 1 1 1 25.9 30.9 59.9 0.61 42.34 50.52 97.92 Europe & Central AsiaHigh incomepostpaid

101 VodafoneIreland Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 3 35 35 55 0.82 42.46 42.46 66.72 Europe & Central AsiaHigh incomepostpaid

102 VodafoneItaly Foreign 0 1 0 0 0 0 1 0 0 1 0 1 0 3 45 45 75 0.76 59.20 59.20 98.67 Europe & Central AsiaHigh incomepostpaid

103 VodafoneMalta Foreign 0 1 0 0 0 1 1 0 1 1 0 1 1 3 35 35 60 0.59 59.43 59.43 101.88 Middle East & North AfricaHigh incomepostpaid

104 VodafoneHungary Foreign 0 1 0 0 0 1 1 0 1 1 0 1 1 5 4990 11990 14990 128.42 38.86 93.36 116.72 Europe & Central AsiaUpper middle incomepostpaid

105 VodafoneNew ZealandForeign 0 1 0 0 0 1 1 0 1 1 0 1 1 5 39 39 69 1.46 26.80 26.80 47.42 East Asia & Pacif icHigh incomepostpaid

106 VodafoneUnited KingdomDomestic 0 1 1 0 0 0 1 0 1 1 0 1 1 7 9.5 15.3 19.8 0.70 13.67 22.01 28.48 Europe & Central AsiaHigh incomepostpaid

107 VodafoneGermany Foreign 0 1 1 0 0 1 1 0 1 1 0 1 0 7 12.99 34.99 39.99 0.78 16.58 44.65 51.03 Europe & Central AsiaHigh incomepostpaid

108 VodafoneRomania Foreign 0 1 1 0 0 1 1 0 1 1 0 1 1 7 7 15 39 1.66 4.21 9.01 23.43 Europe & Central AsiaUpper middle incomepostpaid

109 VodafoneSpain Foreign 1 1 0 0 1 1 1 1 1 1 1 1 0 7 10.5 12 39 0.68 15.37 17.57 57.09 Europe & Central AsiaHigh incomepostpaid

110 VodafoneCzech RepublicForeign 0 1 0 0 0 0 1 0 1 1 0 0 1 8 549 749 999 13.50 40.67 55.48 74.00 Europe & Central AsiaHigh incomepostpaid

111 VodafoneTurkey Foreign 0 1 0 0 1 1 0 0 1 0 1 1 1 8 19 29 65 1.10 17.30 26.41 59.19 Europe & Central AsiaUpper middle incomepostpaid

112 VodafoneNetherlands Foreign 1 1 1 0 0 1 1 0 1 1 1 1 0 9 14 18 39 0.83 16.94 21.78 47.20 Europe & Central AsiaHigh incomepostpaid

113 VodafoneGreece Foreign 0 1 1 0 1 1 0 0 1 0 0 1 1 15 31.5 55.35 76 0.64 48.96 86.04 118.14 Europe & Central AsiaHigh incomepostpaid

114 VodafoneIndia Foreign 1 1 0 0 1 1 0 0 1 0 0 0 1 16 499 699 1299 16.76 29.78 41.71 77.52 South AsiaLow er middle incomepostpaid

115 VodafoneAlbania Foreignprep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep prep 47.46 prep prep prep Europe & Central AsiaHigh incomeprep


40

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