Pricing and Competition in Mobile App Markets
Ning-Yao Pai and Yung-Ming Li
Institute of Information Management, National Chiao Tung University, Hsinchu, Taiwan
Keywords: Two-Sided Market, Game Theoretical Analysis, Mobile App Market, Pricing Strategy.
Abstract: With the fast growth in smart phones, tablets and apps markets, the competition is increasing between
market platform such as Android and iOS. And the growth numbers of apps available and downloaded, the
competition between app market platforms are also very intensive. The economic behaviours of participants
are determined by market factors, such as the effects of the number of apps available in the market and the
number of users purchasing mobile platform devices and download apps. In this research, we analyse the
pricing issues (subscription fee and revenue sharing ratio) in apps market under the scenarios of
monopolistic and duopolistic apps markets.
1 INTRODUCTION
With the fast growth in smart phones, tablets and
apps markets, the competition is increasing between
Android and iOS. According to comScore Reports
(source: comScore), the top smart phone operating
system in the United States was Android with 52.2%
of all smart phone owners, while Apple’s iOS was
the second most common smart phone operating
system with 40.6% of the market. BlackBerry OS
ranked third with 3.6 percent share, followed by
Microsoft with 3.2% share and Symbian with 0.2
percent of the market. IDC reports that, in 2013,
1,004.2 million smart phones were sold worldwide
and a sale of smart phone in Q4 2013 is 284.4
million (source: IDC). The growth number of apps
and the number of downloads of apps are also very
impressive. App Store is the official Apple online
app distribution system for iPad, iPhone, and iPod
touch, and Google Play (Android Market) is a digital
application distribution platform for Android
operated by Google. Both Google Play and App
Store launched in 2008. In July 2013, there were
more than 1,000,000 apps available for Android, and
the estimated number of apps downloaded from
Google Play was 50 billion (source:
www.androidanalyse.com). In December 2013,
Apple's App Store contained more than 1,006,557
apps, which have collectively been downloaded
more than 60 billion times (source:
www.macrumors.com). The amount of apps and
support are important indicators to rational
customers who have the will to purchase smart
phone. And mobile device OS determines the costs
and difficulty of apps development. With the
increasing number of smart phone users each day,
meanwhile, there is an equal increase in the number
of app developers. Although the developers have a
lot of mobile platforms to choose from, they are
likely to choose the most popular one or two
platforms, iOS and Android.
App market is a two sided market, it provides
platform to bring two types of participants (Bakos
and Katsamakas, 2008), such as apps users and apps
developers. A two-sided market is two sets of
participants interact through a platform and the
decisions of each set of participants affects the
outcomes of the other set of participants (Rysman,
2009). The apps market economy is different from
the past economy. There are three elements
combined in the economy: mobile device, operating
system provider, and apps channel. Such as Apple
Inc., its best-known mobile device products are the
iPhone and iPad. It is also the iOS operating system
provider and the apps platform App Store which is
the official Apple online application distribution
system. Different apps markets have different
management or usage rules. Google Play, for
example, inherited from the Android system which
is free and open, Google also takes an open
management strategy on app publishing. It does not
set strict management and process for developers
261
Pai N. and Li Y..
Pricing and Competition in Mobile App Markets.
DOI: 10.5220/0005056802610266
In Proceedings of the 11th International Conference on e-Business (ICE-B-2014), pages 261-266
ISBN: 978-989-758-043-7
Copyright
c
 2014 SCITEPRESS (Science and Technology Publications, Lda.)

when publishing an app on Google Play. App Store
is another type of apps platform. In order to maintain
a consistent quality assurance, before app
publishing, an app must be examined through the
review process to ensure that the iOS system device
users can get the best experiences. Apps become a
highly competitive market, because it not only can
create enormous revenue, but also drive hardware
sales, advertising and technology innovation. The
massive software business opportunity becomes the
new Blue Ocean of business competition, and an
important driving force of industrial transformation.
With the rapid growth of hardware sales, the rapid
growth of apps accompanies.
In this paper, from the mobile platform
infrastructure aspect, we aim to contribute to the
effort of proposing the model to analyse apps
market’s competing strategy between platforms.
Therefore, a natural issue faces us is the analysing
business (revenue) model for mobile apps markets.
We consider the models of two types of apps
markets: one is the monopolistic apps market, and
the other is the duopolistic apps market. In the apps
market setting, we need to consider two types of
participants: apps providers and apps users. Each
participant has its profit function and utility function
respectively. The economic behavior of participants
are determined by market factors, such as the effects
of the number of apps available in the market and
the number of users purchasing mobile platform
devices and downloading apps in the apps market.
The apps market platforms are assumed to maximize
their profits, and need to consider the factors that
critically influence profits such as the apps quality,
varieties, provision fee, and download fee etc.
Specifically, the profit function of the apps market
platform is composed of apps market subscription
fee and apps revenue sharing from apps providers.
For instance, Google Play has a one-time
subscription fee of $25; iOS developer program on
App Store is $99 a year. The two app market
platforms get 30% of app sales revenue and share
70% of app sales revenue to app developers. In a
duopolistic apps market, the market shares of apps
providers and users are different in the two
platforms. Therefore, we will study the effect of
competition on the apps market revenue model
development.
On the apps platform, there are many factors
influencing the obtainable profit, such as mobile
device price, the apps subscription fee, the number
of apps available in the market, the number of app
developers, the quality of apps, and the apps
publishing rules. We want to develop the optimal
pricing strategy (subscription fee) of the apps market
platform. How does a platform company set the apps
market subscription fee? How does competition
affect the pricing scheme? The game theoretical
models, which are mainly used to extend the
decision context to the competitive environment,
will be developed in the whole research structure. It
is important to do a deep analysis and modelling for
all different kinds of participant behavior in various
market structures which reflect the real world
situations.
The remainder of the paper is organized as
follows. In section 2, we review the related
literatures. Section 3 we describe the models of two
types of apps market and discuss the implications of
our analytical results. Finally, Section 4 provides
concluding remarks and discusses future research
directions.
2 RELATED LITERATURE
A two-sided market is two sets of participants
interact through a platform in which the decisions of
each set of participants affect the outcomes of the
other set of participants (Economides and
Katsamakas, 2006). There are many Internet
intermediaries providing two-sided marketplace;
they operate platforms to bring together two types of
participants, such as buyers and sellers (Bakos and
Katsamakas, 2008). Two-sided market can be found
in many Internet intermediaries, such as operating
systems composed of users and developers;
recruitment sites composed of job seekers and
recruiters; search engines composed of advertisers
and consumers. The well-known companies that
operating platform including Match.com, eBay,
Google, Facebook and others. There exist same-side
and cross-side network effects in two-sided markets,
and each network effect can be either positive or
negative. In this paper, we use the two-sided market
structural characteristics to analyse apps market.
Shy (2001) proposed software are the supporting
service for the hardware, and the variety of software
that supports a hardware influences the value of this
hardware device. Users can get more utilities when
joining a platform that provides higher variety
compatible products. Through the indirect network
effect, user’s purchase behaviour will be altered
(Mantena et al., 2010) in the information goods
(software application / video games). With the
ICE-B2014-InternationalConferenceone-Business
262

network effects, the two types of participants attract
to each other and the platform’s value is dependent
on the number of both sides of the groups
(Eisenmann et al., 2006). Platforms attend to do
more efforts to their business model, and they give
overall considerations to attract two-sided users
while making money (Rochet and Tirole, 2003). The
competition occurs between platforms that have to
attract two-sided participants to transact on them.
The platform can charge the fees
(commission/access fees) to the buyers or to the
sellers, in terms of overall market conditions, the
consumers on the one side of the platform are
permitted free entry (S. Li et al., 2010). Rysman
(2009) show that openness means two strategic
points on two-sided markets; one is the amount of
sides to pursue, the other is how to compete with
rival platforms. In this research, we will model and
examine the pricing strategies for the mobile app
markets, which are an emerging popular type of
two-sided market.
3 THE MODEL
We consider the apps market platform with two
types of participants: apps providers and apps users.
A typical apps user has heterogeneous value creation
rate on the apps market platform, where value
creation rate is uniformly distributed within an
interval. The higher personal value creation rate or
the higher total number of apps download, the
higher apps user’s utility. Besides, because of
Google Play and App Store have different apps
publishing policy, the expected quality of apps also
influence the user’s utility. The user utility function
of using mobile devices that is determined by
individual value creation rate, the total number of
apps download, the expected quality of apps, and the
mobile platform device price. The apps users will
purchase the mobile device and apps when they have
non-negative utility.
Assume there are totally potential
0

apps
providers and potential
0

apps users in the apps
markets. A typical apps user i has heterogeneous
value creation rate
i
v
on the apps market platform,
where
i
v
is uniformly distributed within an interval
[0, 1]. We represent the created value creation for
apps user as
i
vq

, where
q
is the expected quality
of apps and

is the total number of apps available
in the market. The apps market platform earns
revenues from users when they purchased apps.
Apps users will evaluate the quality and the number
of apps to download to decide whether to download
free apps or do nothing. Notice that apps users may
download some paid apps and get some free apps.
The value creation rate
i
v
can be interpreted as a net
value which has deducted the charge of purchasing
apps. In order to be able to use apps, the apps users
must pay a price
p to purchase a mobile device.
The utility of each apps user with
i
v
is defined as
follows:
, Purchase the mobile device and apps
0 , Purchase none
i
i
vq p
U
 




(1)
According to the apps user utility function, we
observe that the apps users will purchase the mobile
device and apps in non-negative utility,
0
i
U 
.
Hence, we have the set of purchased users
{| }
i
p
Div
q


and the demand of users is
0
||1
p
D
q







.
A typical apps provider j has heterogeneous
revenue creation rate
j
r on the apps market platform,
where
j
r
is uniformly distributed within an interval
[0, 1]. Not every apps user will buy the apps; some
users pay for apps and some users download free
apps.
j
r
is a random variable, it means the average
revenue and benefits gained from per apps user. App
providers which provide a free app can still have
revenues, such as through advertising, in-app
purchase, provided a paid subscription advanced
version, ad-free version with an additional fee. Some
free app providers want to increase goodwill, or
provide extra service to customers. For instance,
some restaurants provide a free app that allows their
customers to book in the app prior to going to the
restaurant. Moreover, some stores provide a free app
to get services or obtain goods in the stores that
realize the business model of online to offline. We
represent the generated revenue for apps provider as
j
r

, where

is the total number of apps users
purchasing the mobile device and apps. The
expected benefits from providing apps is
jj
ru

.
Assume

(
01



) proportion of the app
providers provide a paid app. They can gain revenue
sharing from apps market platform. The expected
revenue sharing ratio of apps is denoted as
j
u


,
where
01



. Furthermore,
1


proportion of
PricingandCompetitioninMobileAppMarkets
263

the app providers provide a free app and they will
retain all the benefit (
1
j
u

). Assume parameter f
represents the apps market subscription fee for an
app provider. The profit function of apps provider
j
is defined as follows:
, Subscribes to the apps market and develops apps
0 , Subscribes none and develops none
jj
j
ru f 








(2)
According to the apps provider profit function,
we observe that the apps providers will subscribe to
the apps market and develop apps in non-negative
profit,
0
j

 . Hence, we have the set of subscribed
apps supplier
{| }
j
j
f
Sjr
u


. The total number of
apps available in the market is
||
f
S


 
,
which includes the number of paid apps
0
1
f








and the number of free apps

0
11
f
f




 


.
The notations used in the model are summarized in
Table 1.
3.1 Monopolistic Apps Market
While monopolistic apps market does not currently
exist in the real world, we treat the scenario as a
model for an early stage of the market and use this
baseline model as a benchmark for comparison.
When there is only one apps market platform in the
market, we represent the profit function of the apps
market platform as:



1|
mj
fErjS


    
(3)
The first part of the profit function is the revenue
from apps market subscription fee; the second part is
the revenue from selling apps to users that deducted
some revenue shared to apps providers. For
expression simplification, we denote
/pq  
.
Since the platform will choose the best pricing
strategies (apps market subscription fee) to
maximize its profit, we can derive the optimal
subscription fee for the apps market platform as:
Table 1: Notations used in the model.
Notation Description
0

Potential apps users in the apps markets
0

Potential apps providers in the apps markets
i
v
A typical apps user i has heterogeneous value
creation rate on the apps market platform

The total number of apps available in the
market
q
The expected quality of apps
p
The mobile platform device price
i
U
The utility function of the apps user
j
r
A typical apps provider j has heterogeneous
revenue creation rate
j
r on the apps market
platform
j
u
The expected benefits from providing apps

The total number of apps users purchasing the
mobile device and apps

The expected revenue sharing ratio of apps
f
The apps market subscription fee
j

The profit function of the apps provider
m

The profit function of the apps market platform
Examining (4) , we have the following results.
PROPOSITION 1. The apps market platform
subscriptionb fee decrease with the number of apps
providers.
When the number of apps providers is increasing;
the platform would like to earn profit from sales
apps, and therefore the subscription fee is decreasing.
Figure 1: The impact of the number of apps providers on
subscription fee level.




 

22 222 22 222
0000 00000 00000
22 222
0000000
222 2 22 2
2222 2
f
                      

     
  
          

          
(4)
0
50
100
150
200
250
300
100 200 300 400 500 600 700 800 900 1000
f
ρ
0
f
ICE-B2014-InternationalConferenceone-Business
264

If there are more free apps in the market, the
platform would not make profit from sales apps. In
order to keep the profit level, the apps market
platform subscriptionb fee increases with the
number of free apps.
3.2 Duopolistic Apps Market
In this subsection, we consider a market with two
apps market platforms in the market. Assume there
are two competing apps market platform A and B.

portion of apps users having higher preference to
market platform brand A (
A
iD
) and
1


portion
apps users having higher preference to apps market
platform brand B (
B
iD
), the disutility for a user to
use a less preferred mobile platform is denoted as

.and

portion of apps providers having higher
development skill in apps market platform brand A
(
A
j
S

) and 1


portion apps users having higher
development skill in apps market platform brand B
(
B
j
S

).

is the extra cost for an app provider to
develop apps in a less preferred market platform.
The utility of each apps user with
i
v
is defined as
follows:
, Buy mobile device and apps, for
, Buy mobile device and apps, for
0 , Buy none
ik k k k
iikkk k
vq p i D
Uvq p iD





 



, where
{,}kAB

(5)
The profit function of apps provider
j is defined as
follows:
, Subscribes to the apps market and develops apps, for
, Subscribes to the apps market and develops apps, for
0 , Subscribes none and develops
j
jk k k
j
jjk k k
ru f j S
ru f j S



 
none





, where
{,}kAB
(6)
When there are two apps market platforms in the market, we represent the profit function of each apps market
platform as






1, ,
kkk k kjkk
f
Er k AB

     
,
(7)
Denote
*
A
f
and
*
B
f
are undercut-proof equilibrium subscription fees (Shy, 2001; Li and Lin, 2009). In this
conditions that both competing apps market platforms have no incentive to undercut its subscription fee are









*
11
D
AA A Aj A B A AjAA
fErf Er


        
and
 










*
11 11 1
D
B
BBBjBABBjBB
fEr fEr


             
, (8)
where

1
AS

   
,

1
B
S

   
, and
0
1
S
p
q









. The expected revenue value of
A


paid apps providers develop apps (subscribed apps supplier) in platform A is denoted

Aj
Er
, and

B
j
Er
is the
expected value of

1
B



paid apps providers develop apps (subscribed apps supplier) in platform B.


D
Aj
Er
is the expected value of
A


subscribed apps supplier in platform A and


D
B
j
E
r
is the expected value of
B


subscribed apps supplier in platform B. Assume the expected revenue sharing ratio of apps in two apps
market platforms are the same,
AB

 
and d is equal to
1


.
The symmetric subscription fees can be obtained:
 








222222222
*
22 22 2
211 2 42 2
44 1
BBA BBA
A
dd d d d
f
dd

                  
   
    

 
, (9)
 








222222222
*
22 22 2
21 2 42 1
44 1
BA BA
B
dd d d d
f
dd

























   
     

 
(10)
f
PricingandCompetitioninMobileAppMarkets
265

Examining (9) and (10), we have the following
results.
PROPOSITION 2. Under competition, the apps
market platform subscription fee increases with the
market share of apps users.
Figure 2 shows the subscription fee increases
with the market share of apps users.
Figure 2: The impact of θ on subscription fee.
4 CONCLUSION AND FUTURE
WORKS
In this paper, utilizing the methodologies of game
theoretic and economic modelling, we analyze the
platform subscription fee under the structures of the
monopolistic and duopolistic apps market platforms.
In monopolistic apps market, we find that the apps
market platform subscription fee decrease with the
number of apps providers. In duopolistic apps
market, the apps market platform subscription fee
increases with the market share of apps users.
There are several issues which can be further
studied. First, we assume that the expected quality of
apps is the same. It would be interesting to develop a
model that apps have different quality which would
affect apps user’s utility. Second, the role of
difficulty of developing apps can be incorporated
into the model. The difficulty of developing apps
will affect the incentive of the apps providers to
choose which apps market platform to subscribe and
develop apps. Third, the role of apps review policy
and quality assurance can be incorporated into the
model. The decision of review policy can be further
analyzed in our model.
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