Conference PaperPDF Available

OTT -threat or opportunity for African Telcos?

Authors:
  • Research ICT Solutions
  • Research ICT Solutions
OTT - threat or opportunity for African Telcos?
Authors: Christoph Stork, Steve Esselaar, Chenai Chair and Safia Kahn
Keywords: Telecommunication Regulation, Mobile Broadband, Over The Top services, Mobile
operators
Abstract:
The paper shows that embracing OTTs and providing prepaid products that resemble flat rate
pricing is the most successful strategy to retain revenues. The paper also shows how zero rated OTTs
can be used to gain market share for new entrants.
Introduction
Mobile broadband and declining smart phone prices have lead to a rapid increase in Internet use.
Computer based Internet access was and still is the privilege of the few in Africa, mostly those with
formal jobs, students and those that access it in Internet cafes (Stork et al 2013). Mobile Internet
requires less skills than computer based access, it does not require electricity at home and is
prepaid, all important conditions for use by low income groups in Africa. Mobile Internet is
expensive for the poor at the same time as it is a cost saving tool. It is expensive when using the full
Internet including media streaming. It is cheap when Over The Top (OTT) services are used instead
of voice and text messages.
African operators have adopted various strategies to defend their revenues against OTT services
such as Facebook, WhatsApp and Skype. One strategy is bundling voice, text and data together in
top-up products.
The operator sets the price of the top-up so that it receives the desired ARPU and in exchange
provides close to unlimited voice call and text messages. Another strategy is a regulatory one to
prevent customers using OTTs in the first place. Some countries have banned Skype, for example, to
protect international voice revenues. A third strategy is to use OTTs to gain market share. In markets
with entrenched incumbents and high mobile termination charges, zero rated Facebook and
WhatsApp may sway users to switch to a smaller operator.
This paper analyses quarterly prices for prepaid user baskets across 44 African countries and
introduces alternative approaches to user baskets in order to measure and compare top-up bundles.
Prepaid voice, prepaid data and top-ups are analysed together with postpaid offerings to
demonstrate the various strategies operators in Africa have adopted and uses case studies to
highlight which strategies have successfully defended or increased their revenues.
Dominant operators and new entrants from South Africa, Kenya and Namibia will be analysed in
more detail including key performance indicators as well as pricing strategies and response to OTTs.
Background
Research ICT Africa conducted nationally representative household surveys in 2012 in 12 African
countries and identified a trend towards mobile Internet as either complementary to fixed Internet or
!1
as the primary or only form of Internet access (Stork et al, 2013). The Internet was first used on a
mobile phone by half the Internet users in Nigeria, Namibia, Uganda, Tanzania and Ethiopia. In
Namibia, Nigeria, Kenya, Uganda, Tanzania, and Ethiopia three fourths of Internet users used it on a
mobile phone in 2012.
Since the surveys were conducted in 2012 the trend towards mobile broadband has accelerated due
to faster mobile networks (4G rollout), more affordable and more capable smartphones and
explosive increase in social media use. Social media in particular has driven Internet uptake with
Facebook reaching the one billion daily users mark (Zuckerberg, 2015). VoIP services have also
gained in popularity in their use with WhatsApp reaching the 1 billion user milestone (Whatsapp,
2016).
Mobile Internet is expensive for the poor at the same time as it is a cost saving tool. It is expensive
when using the full Internet including media streaming. Using Over The Top (OTT) services instead of
voice and text messages is more affordable for consumers. A voice call for many minutes may not
use up a single MB of data. Also, thousands of text messages can be sent for a MB.
Prices in Africa do not yet reflect this. A voice minute or SMS frequently costs more than a MB of data
when topping up using a data bundle. A MB data is of much more use for voice and texting when
using for VoIP and instant messaging and other OTTs.
Table 2 displays the prices for a voice minute a SMS and 1 MB data (topped up) in US cents for
selected African countries. Even plain SMS cost often a multiple of 1 MB data. This imbalance
between value for an end user and actual cost will mean a strong push towards OTTs with the result
that mobile operators will turn into mere Internet access providers charging flat fees for connectivity
and leaving communication services to OTTs.
Table 1: Individual Internet use (RIA 2012 survey)
15+ that use the Internet
Where the Internet
was first used
Where did you use the Internet in the last 12 months?
2008
2012
Computer
Mobile
phone
Mobile
phone
Work
Place of
education
Another
persons
home
Internet
Cafe
South Africa
15%
33.7%
65.1%
34.9%
70.6%
35.8%
20.9%
14.3%
32.4%
Botswana
5.8%
29%
70.6%
29.4%
64.1%
51.1%
32.2%
43.7%
58.3%
Kenya
15%
26.3%
68.9%
31.1%
77.8%
31.4%
38.8%
38.9%
72.4%
Nigeria
18.4%
45.2%
54.8%
74.9%
29.3%
19.6%
30.3%
45.1%
Namibia*
8.8%
16.2%
50.1%
49.9%
87.3%
48.4%
36%
32.6%
22.5%
Cameroon
13%
14.1%
82.1%
17.9%
29.7%
9.8%
20.1%
18.7%
80%
Ghana
5.6%
12.7%
70.5%
29.5%
61.2%
34.6%
50.9%
34.5%
84.7%
Uganda
2.4%
7.9%
28.2%
71.8%
81.3%
55%
51.2%
54%
74%
Rwanda
2%
6%
70.8%
29.2%
70.9%
52.1%
30.7%
24.9%
50.2%
Tanzania
2.2%
3.5%
45.8%
54.2%
74.7%
44.6%
24.4%
23.9%
62.8%
Ethiopia
0.7%
2.7%
33.3%
66.7%
80.9%
17.4%
20.9%
3.5%
42.2%
* The surveys in Namibia were conducted in 2007 and 2011 respectively
!2
Traditional voices and sms revenues are shrinking already while there is strong growth in data
revenue across Africa. Figure 1 shows the revenue trends for four dominant operators in Kenya,
South Africa and Namibia.
Data revenues as share of total revenues in each case is on the increase and passed 20% in Namibia
and South Africa. Safaricom’s data revenue as share of total revenue patly does not increase at the
same speed due to a wider revenue base in the form of substantial MPESA revenues.
Table 2: Lowest average prices for a 1 minute voice call, 1 SMS and 1 MB data in US cents for Q1 2016
1 Mb out of
bundle
1 SMS
1 Minute
1 Mb based
on 1 GB top
up
1 Mb Top up
as % of 1 MB
out of bundle
1 Mb Top up
as % of 1
SMS
1 Mb Top up
as % of 1
voice minute
Malawi
0.89
3.78
9.30
0.67
75%
18%
7%
Sudan
1.08
0.71
0.71
0.43
40%
61%
61%
Ethiopia
1.76
1.76
3.37
0.96
55%
55%
28%
Tanzania
1.88
1.47
5.29
0.60
32%
41%
11%
Egypt
1.97
1.97
1.97
0.32
16%
16%
16%
South Africa
2.50
2.50
5.14
0.70
28%
28%
14%
Botswana
2.65
2.12
7.04
1.79
68%
84%
25%
Tunisia
2.74
1.37
1.70
0.50
18%
36%
29%
Cote d'Ivoire
3.81
3.81
8.95
0.82
22%
22%
9%
Kenya
5.65
1.13
3.01
0.50
9%
44%
17%
Namibia
7.76
3.02
12.50
0.55
7%
18%
4%
Mozambique
7.93
3.81
10.84
0.36
5%
9%
3%
D.R Congo
9.00
4.00
8.44
1.30
14%
33%
15%
Angola
9.01
9.01
20.03
1.86
21%
21%
9%
Lesotho
11.15
4.46
10.70
0.84
8%
19%
8%
Zambia
16.66
3.28
13.54
0.90
5%
27%
7%
!3
Figure 1: Data revenues as share of total revenues (MTC as share of service revenue)
Regulatory interventions such as cost based termination rates have impacted positively in driving
down retail prices as in the case of South Africa, Kenya and Namibia (Stork & Chair, 2015) and
consumers now expect continued declines in prices. Thus operators cannot resort to raising prepaid
prices to increase voice and SMS revenues but have to find other ways to generate the Average
Revenue Per User (APRU) to maintain or expand its network operation profitably. One such approach
is bundling data, voice and SMS together as a product and include even dedicated social media
(OTT) use.
Operator Responses to OTTs
OTTs present a threat to mobile network operator’s (MNO) traditional sources of revenue - voice and
SMS. As OTT services evolve from instant messaging to all forms of communication, some mobile
operators feel increasingly threatened while others use it as an opportunity to gain market share.
Operators have responded by offering vertically bundled services; developing their own
applications that compete directly with OTT services; blocking or throttling competitive services or
applying a fair use policy that imposes data limits (RIA, 2015; Seixas, 2015).
An operator launching their own OTT application is probably the least successful strategy unless it is
part of a data access only strategy. This approach has not yet been encountered in Africa. The other
responses to OTTS are discussed in the following sections.
2011
2012
2013
2014
2015
20%
20%
25%
30%
11.7%
9.1%
21.2%
23.8%
4.8%
4.9%
5.3%
6.4%
9.1%
11.6%
13.4%
15.2%
17.8%
21.8%
Vodacom SA Safaricom
MTN SA MTC Namibia
!4
Blocking OTTs
In Europe, the initial response by mobile operators had been to block or throttle peer-to-peer traffic
or VoIP (BEREC, 2012). The study found that blocking or throttling was a practice that occurred more
in mobile network traffic than in fixed line networks. At least 21% of mobile Internet users in Europe
has experience of some form of blocking or throttling of service (BEREC, 2012). Blocking, however,
directly violates the idea of net neutrality, an open Internet accessible to all.
Consumers and regulators have scrutinised the practice of blocking, even if not on grounds of net
neutrality. The European Commission in 2013 raided telecom operators on grounds of throttling
concerns (Seixas, 2015). The commission conducted inspections of Deutsche Telekom, Orange and
Telefonica over concerns they abused their dominant position in the market by throttling data heavy
services such as Youtube and Skype (Fontanella-Khan). AT&T blocked mobile VoIP following the
release of the iPhone but soon faced consumer and regulatory pressure and backed down, allowing
users to make Skype calls using its mobile data network (Singel, 2009).
Regulating OTTs
Regulatory intervention has been sought to either to prevent customers using OTTs in the first place
or to protect operators from market erosion. The regulation of OTT services has been argued from
different perspectives including the net neutrality principle by open Internet activists as well as by
regulators.
The regulatory agency in India banned zero rated services under the “Prohibition of discriminatory
tariffs for data services regulations” (Vincent, 2016). The argument was based on the net neutrality
principle arguing that there shall be no discriminatory pricing of data services which would limit what
people could access. In Morocco, the operators blocked Voice over IP services - Viber, WhatsApp
and Skype without subscribers knowledge (Southwood, 2016). The regulator supported this on the
grounds of protecting revenue streams of operators and the need for public communication service
providers to meet legal and regulatory obligations covering the sector and the terms of their
licensing agreements (Southwood, 2016). While in Egypt, the zero rated OTT service Free Basics was
banned without formal explanation by the regulator (Lelinwalla, 2016).
In South Africa, operators have been seeking regulatory intervention on the grounds of creating an
equal play field and have argued that OTTs have no licence or tax obligations (Alfreds, 2016).
Dominant operators (Vodacom and MTN) as well as the smallest operator in the market (Telkom
Mobile) have been publicly campaigning for government to address the issue of OTT services (van
Zyl, 2016). In a recent parliamentary discussion on whether there is a need to deal with OTTs,
operators argued for the need for regulatory intervention on the grounds of national security,
anonymity for consumers, lack of taxation of big corporates and investment within the country
(Claasen, 2016; McCloud, 2016). Cell C has been the only operator to use and defend the presence
of OTTs. Cell C offers a ZAR 5 WhatsApp bundle for the month for all its consumers as well as zero
rated WhatsApp for those who are subscribed to its Trace mobile package (Cell C, 2015).
Embracing OTTs
A number of African operators have opted to use OTT services to increase or defend their market
share. Operators that embrace OTTs offer it without charging for data services either by bundling
!5
dedicated data for social media (MTC in Namibia) or by offering the Free Basics package from
internet.org (Cell C in South Africa and Airtel in Kenya).
1
OTTs provide a competitive opportunity through various mechanisms:
In markets with entrenched incumbents and high mobile termination charges, zero rated or
discounted Facebook and WhatsApp services may sway users to switch to a smaller operator.
On-net / Off-net discrimination does not apply to OTT services and the size of the subscriber
base doesn't provide a competitive advantage.
2
Dominant operators may embrace OTTs to defend their market share and discourage market
entry. A new operator would need several years to break even while building a network. A
new operator would have to build a business case around flat access pricing rather than
traditional mobile business model in a market with wide spread OTT use.
OTTs stimulate data use through social networks in exponential form. An operator may seek
to boost its market share in data revenues rather then mobile subscribers as a niche strategy.
Operators in 21 African countries have partnered with Facebook to offer zero rated Free Basics on
their platforms (Internet.org, 2016). Interestingly, in nine of the African countries it is being driven by
Airtel despite despite the head of Airtel Africa calling for regulation of OTT services
(www.itnewsafrica.com (b)). Malawi and the Democratic republic of Congo are the only countries in
which the service is being offered by two operators.
Simulate OTTs through bundling
The third strategy in which operators have responded to OTT services is to bundle voice, SMS and
data into packages that provides OTT like services. The number of SMS’s included in the bundles is
high enough to be unlimited for most users and thus resembles free OTT texting. MTC Namibia is
offering these types of bundles for several years in an effort to defend market share and keep new
competition out. MTC’s aim for constant ARPU and competitive pressure leads not to lower ARPUs
but to more bundled value. This strategy is simulating flat rate pricing for unlimited voice and SMS.
Operators in 24 African countries offered bundling voice, text and data together in 2015 (RIA, 2015).
The operator sets the price of the top-up so that it receives the desired ARPU and in exchange
provides close to unlimited voice call and text messages. In Namibia and South Africa dominant and
smaller operators adopted bundling as part of their pricing strategies - MTN and Cell C in South
Africa and MTC and TN Mobile in Namibia. In Kenya, it is only smaller operators Airtel and Orange
that have adopted bundling as part of their pricing strategies. Safaricom has a very strong market
position as well as the MPESA mobile money service to ward off competition.
For dominant or effective monopoly operators facing limited competition in their domestic markets,
bundled packages provides a stable income stream and is a defensive strategy against OTT players.
Offering Non Telco OTT
Operators in Europe were also seen to partner with OTTs to enhance their product offering with the
most popular being streaming music and videos (Seixas, 2015). Revenue stream arrangements are
https://en.wikipedia.org/wiki/Internet.org
1
Mobile network coverage still does.
2
!6
negotiated with OTT streaming music services which help to differentiate their services while
enabling increased uptake of the OTT service (Seixas, 2015). T-Mobile (US) partnered with iHeart
radio and iTunes, Telefonica South America partnered with Napster based on an equity stake. In
South Africa, Vodacom partnered with Deezer, a music streaming service, offering first two months
free and then consumers pay ZAR59 for unlimited music access with online and offline listening
options. MTN offered its own video streaming service - MTN Vu formerly known as MTN Front Row.
3
MTN customers on prepaid or contract SIM on a supported device receive free streaming data when
using Max Vu and subscribers cannot use free data for any other service such as Facebook. Offering
of Video on Demand (VoD) services shows MTN seeking to diversify its products offering while
tapping into the growing video streaming market that moves away from traditional satellite
broadcasters. MTN offered the service as “part of…strategic intent of offering distinct customer
experience and enhancing…current VOD services” (McLeod, 2015).
Offering own OTT
An operator could develop a own OTT service. Deutsche Telekom offers a WhatsApp alternative with
its immmr service. Such a strategy would facilitate the transition to a flat rate access model.
4
Price Analysis
Due to the wider use of OTTs and other platforms entering the competition space products are
designed differently to adjust to consumer demands. One such change is to focus on competing
with bundled top-ups.
Bundled top-ups are being used by new entrants and dominant operators to increase market share,
retain customers or to defend against losing revenues to OTTs. Bundles exist in various forms
combining voice, SMS and data in varies denominations and validity periods.
Research ICT Africa used OECD (OECD, 2010) user baskets to track mobile prices across Africa since
2011. The basket methodology sets rules for use of calls and text messages (SMS) across networks
(on-net, off-net and fixed-lines) and times (peak, off-peak, weekends). The distribution across time
and call distribution as well as call duration is somewhat arbitrary. The OECD baskets are outdated
for several reasons:
In an OTT environment off-net and on-net and also peak and off-peak no longer plays a role
since calls and SMS are free.
The OECD baskets do not take mobile data into account.
The basket approach cannot accommodate bundles, top up products and promotions
We developed two measurement tools to complement the OECD basket that allows comparisons
between bundled top-ups and mobile broadband: the Bundled Value Index (BVI) and the 1 GB Data
Basket. The BVI captures the value of bundles that combine data, SMS and voice as a top-up
package. The 1GB Data Basket is the value of 1GB of prepaid mobile broadband data based on top
ups. These measures do not replace the OECD basket but rather complement it and provide unique
(www.mtnfrontrow.discoverdigital.co.za)
3
http://www.telekom.com/medien/konzern/302092
4
!7
insight into the transition towards new business models - especially as the transition means that
business models will incorporate varying degrees of the old and new approaches.
!8
OECD 30 calls and 100 SMS Prepaid Basket
The OECD user basket is used to track mobile prices across Africa. In Figure 3, the lowest price of a
30 call and 100 SMS basket is provided for each country. The three countries that are the subject of
the case studies - Kenya, Namibia and South Africa - are 4, 21 and 13th place respectively.
Figure 3: Lowest cost in USD for OECD 30 call and 100 SMS basket, Q1 2016
Uganda
Sudan
Tunisia
Kenya
Egypt
Ghana
Cameroon
Mauritius
Nigeria
Tanzania
Ethiopia
Guinea
South Africa
Madagascar
Mauritania
Rwanda
Algeria
Gambia
Burundi
Zambia
Namibia
Libya
Botswana
Mozambique
Benin
Cote d'Ivoire
D.R Congo
Senegal
Congo Brazzaville
Niger
Bukina Faso
Malawi
Morocco
Mali
Liberia
Gabon
Central African Republic
Swaziland
Guinea-Bissau
Zimbabwe
Chad
Togo
Angola
Sierra Leone
Lesotho
Seychelles
Cape Verde
23.21
17.13
13.66
13.37
12.99
12.99
12.86
12.80
12.74
12.56
11.19
10.58
10.48
10.47
10.20
9.93
9.25
8.84
8.65
8.34
8.14
8.11
7.63
7.31
6.94
6.45
6.13
5.92
5.83
4.88
4.70
4.59
4.56
4.31
3.82
3.57
3.40
3.36
3.28
3.10
2.93
2.49
2.26
2.23
2.03
1.58
1.45
!9
A simple example illustrates the shortcomings of the OECD user basket approach: In Namibia, the
cheapest product is Aweh Gig and it offers not only the 100 SMS and 30 calls that make up the
OECD user basket but an additional 2800 SMS, 400 minutes and 4 GB data. The Aweh Gig top-up
qualifies for the OECD user basket but offers so much more that is not captured and therefore the
need for a new methodology to capture the value of these sorts of top-ups.
Bundled Value Index (BVI)
The Bundled Value Index (BVI) captures the value of bundles that combine data, SMS and voice as a
top-up package. It does not make any assumptions about the average usage pattern as user baskets
do. It simply expresses what a consumer gets in terms what the consumer has to pay. The BVI
complements the basket approach allowing a different view on affordability and allows comparison
between top-up bundles across any validity.
The BVI adds the value of bundled voice minutes, SMSs and data and divides it by the price. The
value of bundled minutes is derived by multiplying the number of minutes with a fixed USD value
inclusive of tax. The BMI is constructed from the perspective of a smartphone / OTT user. One MB of
data is more valuable than 1 minute voice call or a single SMS. One minute is valued at 0.2 US cents,
1 SMS at 0.1 US cent, and 1 MB data at 1 US cents and 1 MB dedicated to Social Media at 0.5 US
cents. An offering with 50 minutes, 500 SMSs and 1000MB data bundled, with a price of 10 US$ will
then have the following BVI:
BVI =(50*0.002+500*0.001+1000*0.01)/10 = 1.06
This means that the consumer gets 1.06 times the value of the bundle offering. The higher the score
in the index, the higher the value. We used the same USD values across all operators and countries
for comparative purposes. Unlimited calls, SMSs or data contracts were made comparable to capped
packages by applying the following rules:
Unlimited minutes = 240 minutes per day or 7200 minutes per month
Uncapped SMS = 240 SMSs a day or 7200 per month.
Uncapped data = the smaller value out of the fair terms of use policy limit and 30 GB.
Figure 4 displays the BVI for Africa countries with operators that offered bundles including voice,
SMS and data. Below some observations from this data:
Operators in Ghana are at the bottom of this list since their bundles only include very low data
amounts (20MB e.g.).
MTN Cameroon bundles 200 MB regular data with 30 days of free browsing on Google,
Facebook, Twitter, and WhatsApp and unlimited SMS. The 30 days free OTTs were translated
as 2 GB of data use.
The product with the highest BVI is Telecom Namibia’s Jiva Plus. N$30 (US$ 2.1) per week
gives the user 1.3 GB data, 500 MB social media data, 100 minutes of airtime and 700 SMS.
The second highest BVI is a very different type of top-up. Uganda Telecom offers a daily top-
up with 100 MB data and 20 SMS for a very low price of 500 Uganda Shilling, which is about
US cents 14.3.
The most expensive top-up is from MTN South Africa and costs US$ 120.5 for 12,000 SMS and
4500 minutes and 1 GB data.
!10
The cheapest top-up is from Orange Kenya and costs US cents 10 and offers nearly twice the
value of the most expensive product from MTN South Africa (BVI of 1.92 compared to 1.1). It
is a daily top-up that includes free on-net calls and SMS, 20 off-net SMS and 10 MB data.
The BVI compares the value that a user gets for the money he or she pays independent of validity or
type of top-up. Case studies of OTT bundles in Namibia, Kenya and South Africa provide more
insight into the pricing strategies of operators.
Figure 4: Highest BVI per country for prepaid Top up product, Q1 2016
Mobile Broadband 1GB basket
As Figure 2 showed, data represents an increasing percentage of overall revenues. Mobile data is
also the basis for OTT services: subscribers usually have a data package to make use of OTT services
such as Skype or WhatsApp. In order to compare data packages between operators and countries,
the prices of 1GB prepaid data was collected.
The price of 1GB data was based on prepaid data top-ups or bundled top-ups. The out of bundle
prices of regular prepaid packages can be an order of magnitude more expensive compared to the
top-up prices.
An alternative approach is to capture data prices for 1MB of data (instead of 1GB of data) by dividing
the price of top-ups of different nomination by the nomination. 1 GB at US$10 would then result in a
MB price of 10/1000= US$0.01. However, the validity of the data package impacts on the price: the
shorter the validity period, such as 1 day, the lower the data volume and the higher the per MB price.
Uganda
Namibia
Cameroon
Tanzania
Mauritius
Sudan
Morocco
Madagascar
Cote d'Ivoire
Kenya
Senegal
South Africa
D.R Congo
Egypt
Rwanda
Angola
Botswana
Mozambique
Mauritania
Chad
Algeria
Gabon
Ethiopia
Ghana
0.00
0.13
0.24
0.33
0.35
0.57
0.59
0.61
0.67
0.67
0.90
1.03
1.10
1.80
1.92
2.00
2.30
3.11
3.33
3.68
4.16
5.83
7.79
8.59
!11
The longer the validity period, such as 30 days, the higher the data volume and the lower the per MB
price. Prices for 1MB of data have a bias towards short validities and purchasing multiple top-ups
which may not be a fair representation of user preferences.
Figure 5: Lowest prepaid data top up for 1 GB per month, Q1 2016
Data packages enable a user to bypass SMS or mobile voice calls altogether, and users are likely to
choose higher volume data packages that are valid for longer periods. As a result, we chose data
packages that were valid for at least a month and for at least 1GB - in those instances where an
Egypt
Mozambique
Rwanda
Sudan
Uganda
Ghana
Kenya
Cape Verde
Tunisia
Nigeria
Morocco
Namibia
Burundi
Tanzania
Mauritius
Malawi
Guinea
Cameroon
South Africa
Madagascar
Cote d'Ivoire
Benin
Bukina Faso
Senegal
Niger
Togo
Lesotho
Zambia
Gabon
Algeria
Ethiopia
Liberia
Mali
D.R Congo
Chad
Congo Brazzaville
Botswana
Angola
Zimbabwe
Sierra Leone
Mauritania
Swaziland
Seychelles
47.39
32.00
27.08
25.19
20.00
18.57
17.91
16.69
16.69
13.00
12.52
12.00
9.60
9.39
9.18
8.97
8.44
8.34
8.34
8.34
8.34
8.34
8.18
7.10
6.97
6.68
6.66
6.65
6.46
6.03
5.85
5.32
5.10
5.06
4.99
4.98
4.97
4.89
4.35
4.32
4.13
3.62
3.18
!12
operator didn’t provide data packages for a month, data packages with shorter validities were
combined to reach a month’s validity. Figure 4 shows the cheapest 1GB data package available in a
country in Africa in USD for the first quarter of 2016.
In the Bundled Value Index, RIA tracks the data included as part of a bundled top-up. Of the 43
countries, a 1GB prepaid data package is generally cheaper than the data that is part of a bundled
top-up (i.e. including data and SMS or data and voice). But in Uganda, Namibia and Madagascar,
bundle top-ups were cheaper than data top-ups. This means that it’s cheaper to buy top-up
including SMS and voice minutes along with data rather than just a 1GB prepaid data package. For
example, in Madagascar, the Kozy Kozy product from Airtel Madagascar gives 45 SMS and 50 MB of
data for USD 0.24 and is valid for one day. Multiplying by 30 to get 1 month validity, provides the
consumer with 1,5 GB of data and 1,350 SMS per month for a price of USD 7.2. The cheapest 1GB
data package in Madagascar is USD 7.9 and doesn’t offer any SMS.
The case in Namibia is more extreme. The Aweh Gig top up is valid for 7 days and includes 100
minutes, 700 SMS and 1 GB of data for 30N$. Multiplying by 4 to get 1 month’s validity, provides
400 minutes, 2800 SMS and 4 GB of data for N$120 compared to 800 MB top up for N$129 or a
1.5GB for N$219. The Aweh Gig bundle offers more data and additionally vertically unlimited SMS
and 400 minutes for the same price.
Summary
In the case studies that follow, we explain how flat rate pricing is the most successful strategy to
retain revenues and how zero rated OTTs have been used to gain market share for new entrants
using the three measurement tools explained in the previous sections: the Bundled Value Index, the
Mobile Broadband 1GB basket and the OECD user basket.
!13
Case Study - Kenya
The Kenyan market is currently made up of one dominant operator - Safaricom - and two smaller
operators, Airtel and Orange Kenya. Kenya also has a mobile virtual network operator (MVNO)
named Equitel. Airtel and Orange are the two smaller operators in Kenya. The fourth entrant, Essar
Telecom (Yu) exited the market in 2014 through an acquisition split between Airtel and Safaricom.
Despite the exit of Essar (Yu) total mobile subscriptions on the market increased for the year ending
2014 to 33.6 million subscribers. By September 2015 the market was still growing and had increased
to 36.1 million subscribers (7.4% growth over the previous three quarters). Of this larger market
Airtel holds 19% (7 million subscribers) and Orange holds 11% (4 million subscribers) and Safaricom
has a market share of 67% (24 million subscribers).
Figure 6: Market share by subscribers September 2015 (Source: CAK, 2015)
Analysing market share by voice traffic, which is a more robust measure of actual activity, Figure 7
shows that Airtel has 16% of the voice market, Orange has 8% of the market and Safaricom has 76%.
Figure 7: Market share by voice traffic July to September 2015 (Source: CAK, 2015)
66%
12%
19%
3%
Equitel
Airtel
Orange
Safaricom
76%
8%
16%
Equitel
Airtel
Orange
Safaricom
!14
Safaricom has long been the market leader in Kenya with an average market share of 66% as
measured by subscribers and 76% as measured by voice traffic over the last five financial years.
Safari com is in a unique situation in that it has growing revenues from a non telco service, i.e. Mpesa.
Mpesa makes up about 20% of Safaricom’s total revenue in the financial year ending in 2015, while
data only accounted for 9%. Surprisingly Safricom also managed to grow its voice revenue over time
and even SMS revenues increased each year since 2011.
Safari com may thus not be too concerned about OTTs since the market is still expanding and
Safaricom can wait until its voice revenues start to decrease before and makes strategic changes.
OECD user basket
The OECD basket ranks all the prepaid products based on 30 calls and 100 SMS’s. Both Orange and
Airtel offer cheaper basket prices than Safaricom. Safaricom’s prepaid product is in the middle of the
pack and scores USD 2.9. Orange Kenya offers a prepaid product for USD 2.2 and Airtel Kenya offers
a prepaid product for USD 2.5. But with 66% market share, Safaricom doesn’t need to offer
significantly cheaper products than the competitors because most calls will be on-net.
Table 2: Safaricom 5 YEAR PERFORMANCE SUMMARY in billion Kshs (source: Safaricom, 2016)
FY11
FY12
FY13
FY14
FY15
Voice service revenue
63.5
68.12
75.84
84.32
87.41
M-Pesa revenue
11.78
16.87
21.84
26.56
32.63
Mobile data revenue
4.54
5.22
6.62
9.31
14.82
Fixed service revenue
0.84
1.37
2.11
2.57
3.13
SMS revenue
7.54
7.77
10.15
13.62
15.63
Other service Revenue
0.84
1.49
1.98
2.63
Service revenue
88.2
100.19
118.05
138.36
156.25
Handset revenue
5.75
5.94
4.93
4.95
5.67
Connection and other revenue
0.88
0.87
1.31
1.36
1.45
Total revenue
94.83
107
124.29
144.67
163.37
M-Pesa revenue as share of total
12.4%
15.8%
17.6%
18.4%
20.0%
Mobile data revenue as share of total
4.8%
4.9%
5.3%
6.4%
9.1%
Table 3: OECD 30 calls 100 SMS basket values in Kenya
Operator
Product
Basket USD
Orange Kenya
Tujuane tariff
2.2
Airtel Kenya
Tosha Montly
2.5
Airtel Kenya
Tosha Weekly
2.6
Airtel Kenya
Freelanga Free tariff
2.7
Airtel Kenya
KLUB 254
2.8
Safaricom
Uwezo
2.9
Orange Kenya
Holla
3.0
Airtel Kenya
Tosha Daily
3.0
Airtel Kenya
Vuka
3.0
Airtel Kenya
Yu Jichanue na MOSMOS
3.2
Table 3: OECD 30 calls 100 SMS basket values in Kenya
Operator
!15
The OECD user basket doesn’t provide much insight into the various strategies of operators in
Kenya. The difference between the cheapest basket and Safaricom is not large enough to
differentiate operators enough to draw large numbers of new subscribers or to convert existing
ones.
1GB data basket
The three major operators in Kenya offer a 1GB basket for the price of Ksh. 500. There is no
differentiation based on data prices.
BVI
In Kenya, the dominant operator, Safaricom, does not offer bundles that combines data with voice
and SMS. With its market share of subscribers at 66% (Figure 6), it can afford not to. All of the bundle
packages from Orange Kenya and Airtel Kenya offer more on-net than off-net minutes. Airtel’s Amua
plan has the best value in the market - offering unlimited on-net calls, unlimited on-net sms and
300MB of data at a cost of USD 3 (assuming 1 month validity) and a BVI score of 1.9.
The Amua Plan from Airtel and the Holla plan from Orange offer significant value to the subscriber.
However, the value offered is considerably lower than in other countries, such as Namibia or Uganda.
While Airtel and Orange are testing the waters with products such as the Amua Plan, there is still
significant upside, as the case study on Namibia will show.
Summary
What is driving Safaricom’s increasing revenues is not data but the competitive advantage its mobile
money platform MPESA offers. MPESA’s revenue nearly tripled between 2011 and 2015. Safaricom
thus does not need to engage in price bundling strategies or behave defensively towards OTTs or
offer voice and SMS prices that are cheapest in the market. Safaricom’s market share and financial
position is so secure, with 76% of the voice market, 66% of total subscribers that Safaricom can afford
to not be antagonistic towards OTTs.
In order to attract subscribers, Airtel and Orange need to differentiate themselves. Basic data
products are insufficient because pricing for 1GB of data is the same between all three operators.
Orange Kenya
Usinyamaze
3.4
Airtel Kenya
Ongea Mob Jioni Pack Yu
4.6
Airtel Kenya
Freedom Ten (Yu)
5.1
Table 3: OECD 30 calls 100 SMS basket values in Kenya
Product
Basket USD
Table 3: OECD 30 calls 100 SMS basket values in Kenya
Operator
Table 4: Bundled Value
Index
Cost
Ksh
Validity
Free
Minutes
Free
SMS
Free
MB
Social Media
MB
FX USD
Q2 2015
BVI
Airtel
Daily Tosha 100
29.8
Day
450
15000
3000
0
100.7
1.6
Weekly Tosha 100
27.8
Week
420
14000
2800
0
100.7
1.6
Monthly Tosha 100
29.8
Month
450
15000
3000
0
100.7
1.6
Amua plan (Yu product)
3.0
Day
0
600
300
0
100.7
1.9
Orange
Holla
4.5
Day
0
0
300
0
100.7
1.8
!16
Top-Up products offering unlimited on-net SMS or voice is one way to differentiate the smaller
operators from Safaricom.
Case Study - South Africa
Vodacom and MTN are the two dominant operators in South Africa. Vodacom and MTN have a
market share of 39% and 32% respectively. Cell C is gaining subscribers and market share. Telkom
Mobile is struggling and has 3% of the market. MTN and Vodacom have consistently increased their
subscriber numbers, though their growth has slowed in comparison to Cell C. Overall, the South
African mobile market continues to expand.
Figure 8: Market share by subscriber numbers in South Africa, 2014 (Source: Brookhurst, 2015)
Both operators are facing increasing growth rates in data revenue as users increasingly take up
mobile broadband services. For FY 2015 MTN’s data contributed 23.8% to its overall revenue, while
Vodacom’s data revenue increased to 21.8% (see Figure 2).
With the substitution away from voice and towards OTT, and the increase in number of active SIM
cards the ARPUs of Vodacom and MTN have been decreasing since 2012 (Figure 11). This despite
the fact that both operators increased postpaid prices for all postpaid contracts mid-contract at the
beginning of 2015.
!17
39%
3%
32%
26%
Cell C (Oger Telecom)
MTN
Telkom Mobile
Vodacom
Figure 9: ARPU for Vodacom and MTN (Source: MTN 2015, Vodacom 2015)
The increase in data revenue and the growth thereof, implies that the decrease in blended ARPU is
attributable to (1) falling voice revenues and (2) an increase in the number of SIM cards.
OECD user basket
The OECD user basket shows that Telkom Mobile is the cheapest operator in South Africa. The cost
of the OECD user basket is USD 3.8 and the nearest competitor is Cell C at USD 5.9. MTN and
Vodacom are close behind with products that costs USD 6.3.
2010
2011
2012
2013
2014
2015
154.0
134.1
122.0
108.0
92.0
184.0
183.0
157.0
128.0
125.0
113.0
Vodacom MTN
Table 5: Revenues in R(m)
2013
2014
2015
Vodacom
Mobile voice
29,151
28,135
25,855
Mobile messaging
3,027
2,675
2,522
Mobile Data
8,882
10,974
13,538
MTN
Mobile voice
22,125
19,677
Mobile messaging
2,365
2,069
Mobile Data
8,656
9,264
Table 6: OECD basket value
Operator
Product
OECD USD
Vodacom South Africa
Prepaid Anytime
15.9
Vodacom South Africa
Prepaid Standard
15.9
MTN South Africa
MTN Muziq
14.0
MTN South Africa
MTN Zone Per Second
11.4
Vodacom South Africa
Vodacom 4 less
11.4
Telkom Mobile
Talk more
10.3
Cell C
Easychat standard
8.8
Cell C
trace mobile
8.8
Vodacom South Africa
Power Bonus
8.8
Vodacom South Africa
Daily Free Calls
8.8
Vodacom South Africa
Anytime Per Second
7.8
Table 6: OECD basket value
Operator
!18
Telkom Mobile is the cheapest but its market share is too small to represent a serious threat to the
other three operators. Cell C undercuts both Vodacom and MTN, but the difference is small and
doesn’t provide any insight into Cell C’s strategy to differentiate itself and attract new subscribers or
existing MTN and Vodacom subscribers.
1GB data basket
Telkom mobile is attempting to attract data subscribers by offering a 1GB package for USD 7. The
next cheapest package is from Cell C and Vodacom for USD 10.5. Vodacom is matching Cell C’s
price - Telkom Mobile is too small to have an impact on Vodacom’s subscriber numbers. MTNs
pricing is higher than Vodacom’s, so a pure data play is not its strategic focus.
Like the OECD basket, the 1GB data basket shows that the operators are competing at roughly the
same level - pricing is very similar. To get insight into how the operators are differentiating
themselves, we turn to the BVI.
BVI
Like Kenya, the dominant operator in South Africa, Vodacom, does not offer bundles. MTN is the
second largest operator and offers 10 types of bundles. The bundle with the best score on the BVI is
MTN’s Sky UnlimitedUncapped product. This product offers unlimited voice and text (off and on-net)
and 10 GB of data for USD 112.5. This is an effective strategy against OTTs because unlimited calls,
data and SMS means that there is no real benefit to consumers to use OTTs.
Cell C offers only one bundled product, infinity. This product offers unlimited voice calls, 1000 SMS’s
and 1GB of data for USD 70 per month.
MTN South Africa
MTN Talk free
7.1
Cell C
99c for real
7.0
Virgin Mobile
Prepaid
7.0
Virgin Mobile
1 2 FREE!
7.0
MTN South Africa
MTN Pay Per Second
6.3
Vodacom South Africa
Vodacom Prepaid 79c
6.3
Cell C
66c
5.9
Telkom Mobile
Sim-SONKE
3.8
Table 6: OECD basket value
Product
OECD USD
Table 6: OECD basket value
Operator
Table 7: 1GB basket value
Q1 2016
Cell C
10.5
MTN South Africa
11.3
Telkom Mobile
7.0
Vodacom South Africa
10.5
Virgin Mobile
12.3
!19
MTN clearly sees OTTs as an existential threat and is hoping to counter it by offering attractive top-up
bundles. Vodacom and MTN South Africa have vehemently opposed OTT players in the mobile
broadband market. This opposition arose with the prominence of Facebook mobile and WhatsApp.
Summary
Like Safaricom, both Vodacom and MTN are market leaders, have healthy EBITDA’s and have
increased investment substantially over the last six financial years. However, unlike Safaricom, MTN
and Vodacom are openly opposed to OTT services and believe they should be regulated as
opposed to innovating around it. MTN wishes to regulate WhatsApp yet offers other non telco OTT
services such as its online television viewing platform MTN Vu, similar to Safaricom, while Vodacom
offers Deezer (an online radio service).
Cell C has gained market share significantly over the last 5 years, moving to its present position of
26% of subscribers. However, as the Namibian case study will show, there is significant scope to
increase its market share by offering a top-up bundle that more closely matches MTN’s Sky
UnlimitedUncapped product, with unlimited voice, SMS and 10GB of data.
Table 8: Bundled Value
Index
Cost
(ZAR)
Validity
Free
Minutes
Free
SMS
Free
MB
Social Media
MB
FX USD
Q4 2015
BVI
Cell C
infinity
70.3
Month
7,200
1,000
1,024
0
14.2
0.36
MTN
MTN Sky Daily
166.7
Day
4,500
12,000
600
0
14.2
0.20
MTN-to-MTN Sky Daily
52.8
Day
0
0
300
0
14.2
0.20
MTN Sky Super 1GB
70.3
Month
3,000
12,000
1,000
0
14.2
0.40
MTN Sky Absolute 2GB
140.4
Week
600
1,600
8,000
0
14.2
0.50
MTN Sky Super
Uncapped
1897.5
Day
67,500
84,000
90,000
0
14.2
0.50
Boosta 39
16.5
Other
0
600
1,200
0
14.2
0.70
Boosta 189
26.6
Other
0
1,000
2,000
0
14.2
0.70
Boosta 339
23.9
Month
0
700
2,000
0
14.2
0.80
Boosta 79
16.7
Other
0
600
1,500
0
14.2
0.90
MTN Sky
unlimitedUncapped
112.5
Month
4,500
12,000
10,000
0
14.2
1.00
!20
Case Study - Namibia
MTC Namibia is the market leader, but contrary to Vodacom (S.A) and MTN’s (S.A) oppositional
stance to OTT, or Safaricom’s laissez faire approach, MTC has embraced OTT’s. MTC’s financial
performance shows that dominant operators can benefit from OTT developments and the migration
from mobile voice to mobile broadband.
The product with the highest BVI is Telecom Namibia’s Jiva Plus. NS30 (US$ 2.1) per week gives the
user 1.3 GB data, 500 MB social media data, 100 minutes and 700 SMS. MTC’s highest BVI is a top up
product with 7 days validity. 1GB of data, 510 MB social media data, 100 minutes and 700 SMS cost
N$30. For a month this means 4 GB of data, 2.2 GB of social media data, 2800 SMS and 400 any time
any network minutes for N$ 120 (US$ 7.6). The MTC product has been in the market for over a year
and TN Mobile copied it initially with its Jiva product. The promotion that it is currently running with
Jiva plus tops the value for the customer compared to MTC’s Aweh Gig by providing more data.
Table 8 lists the top up products for MTC and Telecom Namibia and calculates the BVI for each.
MTC has a major advantage in offering top up bundles that Telecom Namibia cannot match due to
its dominance. Above 99% market share of outgoing calls means that termination rate payments to
Telecom Namibia are insignificant. MTC can thus pursue a strategy of constant ARPUs. A sequence of
four Aweh Gig or Aweh Prime top-ups would give MTC N$ 120 revenue (excluding VAT). If used by
all prepaid subscribers of MTC it would yield N$ 3.5 billion a year for prepaid only. It’s current total
revenue is N$2 billion in total.
While not all prepaid subscribers can afford to spend N$ 120 a month, this strategy also has the
benefit of competing effectively with Over The Top (OTT) services such as Facebook, WhatsApp,
Skype, Viper, Talkray, FaceTime etc. The vast number of bundled SMS and minutes means that using
OTTs for domestic communication does not bring any cost benefit to consumers. The top up strategy
of MTC can be seen as a transition to flat rate prices seen in Europe and the US for the postpaid
market, but in the case of Namibia for prepaid.
Table 9: Bundled Value
Index
Cost
N$
Validity
Free
Minutes
Free
SMS
Free
MB
Social
Media MB
FX USD
Q2 2015
BVI
MTC
Aweh Super
50
7 Days
700
1500
350
710
14.2
3.8
Aweh Prime
30
7 Days
350
700
200
210
14.2
2.6
Aweh Gig
30
7 Days
100
700
1000
510
14.2
7.6
Aweh Go
12
7 Days
50
150
50
60
14.2
1.6
TN
Mobile
TN Mobile 20
19
7 Days
20
20
20
0
14.2
0.2
TN Mobile 50
49
30 Days
50
50
50
0
14.2
0.2
Business Lite
149
30 Days
150
150
150
0
14.2
0.2
JIva
30
7 Days
100
700
1000
0
14.2
5.2
Jiva Plus
30
7 Days
100
700
1300
500
14.2
9.0
Jiva Surf
40
7 Days
150
1000
1300
500
14.2
6.9
!21
Conclusion
The paper shows that embracing OTTs and providing prepaid products that resemble flat rate
pricing is the most successful strategy to retain revenues. The paper also shows how zero rated OTTs
can be used to gain market share for new entrants.
In all three countries - Kenya, Namibia and South Africa - mobile penetration has increased, driven
mainly by lower prepaid prices. But the increased mobile penetration has come at a cost for some
operators: As migration from voice to internet takes place, and markets expand with increases in
lower income users joining networks, all main operators bar Safaricom have experienced declining
voice revenues. The extent of this decline has been more visible for South African operators
Vodacom and MTN, who have historically had a strong postpaid base pushing up average revenues.
With the entrance of Cell C (the third market entrant) competition increased along with a
concomitant increase in mobile penetration. Decreases in mobile termination rates and
subsequently voice call prices, increases in postpaid rates in 2015 and a slow move towards data
and OTT have had an impact on overall revenues.
The exception to this trend has been Safaricom in Kenya. As this paper has shown, MPESA
contributes 20% of revenues for Safaricom. Its dominant position in the financial services market (via
MPESA) means that churn is low and it is able to watch the impact of OTTs and top-up bundling in
other markets first.
Figure 10: Change in Blended ARPU (Base year 2010) - Financial Years 2011-2015
It is Namibia that is showing how the trend towards lower voice and SMS and higher data usage is an
opportunity. In the case of MTC, its blended ARPUs are the lowest out of all operators but its strategy
of bundling data, SMS and voice means that its ARPU has been nearly flat for the last 4 years and its
revenue has flattened in the last three years. MTCs strategy means that it gets a consistent return on
its investment. In contrast, Vodacom and MTN are seeing a declining return on investment as voice
and SMS revenues decline. MTC’s strategy means that it is ranked second on the BVI, compared to
!22
0
0.325
0.65
0.975
1.3
2011
2012
2013
2014
2015
87%
79%
70%
58%
96%
108%
120%
127%
128%
86%
87%
84%
88%
99%
85%
70%
68%
61%
Vodacom MTC Safaricom MTN
Kenya (ranked 10th) and South Africa (ranked 12th). Table 8 provides a brief summary of the rankings
for each country based on the BVI, 1GB data package and the OECD user basket.
The approach of benchmarking voice and SMS in order to compare countries (as in the OECD user
basket) fails to explain how dynamic and innovative the mobile sector is. New strategies to retain
revenues and shore up subscribers are continually being tested. The BVI is a critical tool in evaluating
operator strategies. The combination of the OECD user basket, the 1GB data basket and the BVI
provides insight into which strategies are working and which need to be tested more thoroughly as
well as the potential opportunities for smaller operators such as Airtel and Orange in Kenya and
CellC in South Africa.
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Table 9: Comparison between dominant operators
Kenya
South Africa
Namibia
Number of Mobile operators
3
4
2
Marketshare of dominant operator in terms of active SIM
67%
MTN 33%
Vodacom 42%
96%
Marketshare of dominant operator in terms of traffic
76%
NA
99%
Cheapest OECD Basket
USD
2.23
3.82
6.12
Ranking
4
13
21
Cheapest 1 GB
USD
4.97
6.97
5.3
Ranking
7
19
12
Highest Bundled Top up
BVI
1.92
1.1
7.79
Ranking
10
12
2
Share of Data Revenue of total for dominant operator FY 2014
6.4%
23.8%
30%
!23
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Supplementary resource (1)

... Mobile phone development and mobile Internet are at the forefront of an innovation drive that is transforming the market. Market transformation is also accelerated by the decline in smartphone prices, growing access to the Internet, and an explosive increase in user-generated content especially from social media platforms, search engines, and other content service providers [1]. ...
... This has a negative impact on CSP voice revenue, which is estimated to continue decreasing in the next few years. Studies show that telecom operators can expect fierce competition in the future from freemium-model services [1]. ...
Chapter
Full-text available
The telecommunication industry is facing constant changes in its operations and business environment. One of the major causes of these changes is the rise of Over The Top (OTT) service providers that have developed and implemented innovative new business models that are disrupting the traditional telecommunication industry. In this paper we investigate the impact of OTT business models on Communication Service Providers (CSPs) in the Rwandan telecommunication market. We seek to understand the business models and strategies CSPs and OTTs are employing to stay relevant in the market, the advantages and disadvantages of each model, and to assess whether they are applicable in the Rwandan telecommunications market. The findings and recommendations highlight some of the major trends and business models in the telecommunication markets, and can be used to provide insight for CSPs and regulators to build strong business strategies and relevant regulations.
... e. Ensure same version of an IM or SIP client was installed on all the S4Ms by using their Android Package Kit (APK) file rather than the Google Play Store. 9. Results Collection and Evaluation: For battery consumption, PTut was configured to record consumption excluding the power usage of WiFi radio and LCD screen in the log file. ...
Conference Paper
Full-text available
Low-end smartphones with sub $50 price tags provide affordable device ownership to low-income populations. However, their limited capacity, when combined with the need for multimodal connectivity, raises usage concerns in rural off-grid regions. Some off-grid regions in sub-Saharan Africa provide recharge facilities using solar power and charge money for the service. Adding data bundle costs to frequent recharge costs, affordability of low-end smartphones becomes questionable in such areas. Community-controlled solar-powered wireless mesh network models with Session Initiation Protocol capability could alleviate the network usage cost conundrum and consume less power in low-end smartphones with the usage of WiFi. This paper reports on investigations that reveal usage of WiFi consumes less battery than 3G, 2G and Bluetooth. In addition, we feel that lowering recharge costs also requires battery consumption knowledge of the over-the-top applications. Using automated voice calls, this paper reports on battery and data consumption by multiple popular social media applications using one type of low-end smartphone. Data consumption was calculated with the objective of learning how to lower data bundle costs by selecting the application with least data consumption. Battery consumption due to CPU usage by the applications was also measured. Results show that WhatsApp consumes the least battery amongst instant messengers and also the least data over all apps measured. SipDroid consumes the least battery overall. Additionally, the reported experiments provide a framework for future experiments aimed at evaluating battery and data consumption by other smartphone applications.
Thesis
This qualitative study explored the use of mobile-based social media technologies in the library services at the Federal University Lafia, North Central Nigeria. The purpose was to understand the academic information-seeking behaviour of the student library users while using mobile-based social media and other mobile-based technologies. A further purpose was to identify some of the barriers the students encountered when seeking information. Meyer’s (2016) information behaviour model provided the conceptual framework for the study. For this reason, the literature review and the empirical data were structured according to the six major information behaviour components identified in the model. These are information, user, context, technology, information needs, and information activities. Meyer’s model recognises technology as an important enabler of information behaviour. After clarifying these concepts, the discussion explored mobile technologies and mobile applications to acquire an understanding of these technologies and applications and the way in which they could be employed by a library to enhance its services. After that, the literature review focused on the way in which mobile technologies and social media are employed by users (especially students) to seek information that is supportive of their information needs. In this discussion, the influence the interplay between context and the users’ cognitive, affective and sensorimotor structures have on the users’ information needs and seeking behaviour was explored. The study used a descriptive qualitative phenomenology research design to gain insight into participating students’ experiences using mobile-based social media technologies as a phenomenon. A total of 21 undergraduate students who were in their second to fourth year of study were interviewed using semi-structured interviews. The findings revealed that the use of mobile-based social media in information-seeking is affected by the participants’ cognitive and affective structures which shaped their attitudes towards information sources and the way in which they use them. In addition, certain personal and environmental barriers seem to affect the participants’ information-seeking activities. In order to get access to information that would satisfy their information needs, the participants relied on online social media groups. The use of Meyer’s information behaviour model enabled an understanding of the reasons why students use mobile technologies and social media when seeking academic information and the means they employ to deal with their academic task-related information needs when they lack the necessary knowledge and skills to seek information in the library. This understanding enabled the researcher to graphically illustrate the participating students’ information-seeking behaviour while using mobile technologies and social media. Some recommendations could also be made to improve the library’s services. These include the aggressive promotion of library services and information resources to users with frequently conducted user surveys. Such surveys would support the library management in keeping abreast with their users’ information needs and would guide the development of a reliable environment that is conducive to users’ information-seeking activities which are focused on satisfying their information needs.
Article
Full-text available
Vodacom, MTN and CellC justified recent increases in their postpaid product prices with claims of rising input costs. These price increases have taken the form of increases in monthly subscriptions, out of bundle rates, and the quantity of bundled minutes, SMSs and data. Some plans remain unchanged but most plans face direct or indirect price increases. A new tool has been developed by Research ICT Africa to analyse postpaid price changes across operators and across Africa, taking very diverse postpaid features of products on offer into account. This tool is the Postpaid Value Index (PVI).
Article
Full-text available
Purpose – This paper aims to provide an answer as to whether fibre to the home and other types of fixed internet access still have a role to play in Africa beyond a few urban elites, as well as what business models are likely to be successful in the African context. Design/methodology/approach – The paper uses data from nationally representative ICT household surveys conducted in 12 African countries in 2012. These data are complemented by an OECD broadband pricing methodology and data. In addition to the OECD basket methodology, own baskets were defined to capture the complexity of African products, and to draw out the different business models for fixed and mobile broadband. Findings – The paper demonstrates that if fixed internet is provided as an uncapped service at an affordable price, it has a chance to at least co-exist with mobile broadband in Africa. The availability of fixed internet is rapidly diminishing where it is offered as a capped service and not at prices similar to mobile broadband. The paper also demonstrates that fixed-line telecommunication companies should to focus on data only before mobile operators do, and they lose out once again. Practical implications – In Africa, mobile voice overtook fixed voice at the turn of the millennium with the introduction of prepaid services. Ten years later, mobile internet is rapidly overtaking fixed internet by overcoming key obstacles to fixed internet access. While the developed world discusses the merits of fixed and mobile broadband, it is clear that for Africa, fixed broadband in the form of fibre to the home, or even plain ADSL, will only reach a few urban elites in the next decade. Fixed-line operators then should rethink their pricing and investment strategies: they are advised to invest in high-speed technologies such as VDSL or fibre to the home, if fixed broadband is to stand a chance against mobile broadband. Whether fixed-line operators will lose the data battle as well will be determined by their business decisions as well as by policy and regulatory interventions. Originality/value – This paper uses primary household and individual data that allows for a better understanding of internet access and use in Africa. The analysis of internet access prices for ADSL against prepaid and post-paid mobile broadband is used to assess broadband business strategies across 12 African countries. The paper provides policymakers and regulators with the evidence required for an informed ICT policy and regulation and it recommends business strategies that should be pursued by operators to improve broadband sector performance.
Article
Full-text available
Purpose – The purpose of this paper is to analyse internet access and use trends in 11 African countries based on household and individual ICT survey data. Design/methodology/approach – The study uses nationally representative data for households and individuals in residential and semi-residential areas, as defined by national census sample frames for 11 African countries. Findings – While the 2007/2008 African ICT access and use survey demonstrated alarmingly little access to the internet on the continent, together with a large-scale absence of computers and smart phones, compounded by the high cost of connectivity, the mobile phone is now the key entry point for internet use. Internet access has increased significantly across all countries, as a result increasing internet penetration to 15.5 per cent across the 11 African countries surveyed by Research ICT Africa in 2011/2012. Mobile internet requires fewer ICT skills, less financial resources and does not rely on electricity at home, compared to computers or laptops. Other findings highlight the unevenness of internet take-up across and within countries. Thus, while the majority of the countries under investigation demonstrate increased mobile internet take-up, in Rwanda, Tanzania and Ethiopia, internet use remains negligible. In those countries where mobile internet is boosting connectivity, this is being driven by social networking applications. Practical implications – The policy implications of the shift in significant numbers from negligible internet access at public access points serviced primarily by fixed access lines to mobile internet access are significant. Just as traditional reform strategies of increasing competition in the market increased access to voice services more successfully than traditional universal service strategies, mobile again appears to be addressing the internet gap. Competition in mobile markets appears to address the efficiency gap in the market, resulting in an increase in the choice of services and a reduction in prices. Strategies that seek to aggregate users at public access points, funded by complex levies and subsidies again seem to have been overtaken by the increasing availability of mobile internet access, as feature phones and smart phone become more available to individual users. Social implications – Understanding prepaid mobile internet further provides a pro-poor dimension to public policies seeking to improve internet access, which historically has been available and affordable to the elite. The rest of the society had to rely on public access points, whether private internet cafés or schools and libraries. Originality/value – This paper uses primary data that allow a better understanding of internet access and use in Africa. It provides policymakers and regulators with the evidence required for an informed ICT policy and regulation.
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