Updates management in mobile applications: iTunes versus Google Play

• Date: 01 June 2019
• Published date: 01 June 2019
• Author: Fabio M. Manenti,Franco Mariuzzo,Stefano Comino
• DOI: http://doi.org/10.1111/jems.12288

Received: 18 May 2016

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Revised: 8 May 2018

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Accepted: 20 August 2018

DOI: 10.1111/jems.12288

ORIGINAL ARTICLE

Updates management in mobile applications: iTunes

versus Google Play*

Stefano Comino

1

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Fabio M. Manenti

2

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Franco Mariuzzo

3

1

Dipartimento di Scienze Economiche

e Statistiche, Universita’di Udine, Udine,

Italy

2

Dipartimento di Scienze Economiche

ed Aziendali “M. Fanno”, Universita’

di Padova, Padova, Italy

3

School of Economics and Centre for

Competition Policy, University of East

Anglia, Norwich, UK

Correspondence

Fabio M. Manenti, Dipartimento di

Scienze Economiche ed Aziendali

“M. Fanno,”Universita’di Padova, Via

del Santo 33, Padova 35123, Italy.

Email: fabio.manenti@unipd.it

Funding information

University of Padua, Grant/Award

Number: Progetto di Ateneo 2014;

Economic and Social Research Council,

Grant/Award Number: RES‐578‐28‐0002

Abstract

This paper focuses on a specific strategy that developers of mobile

applications may use to stimulate demand: The release of updates. We

develop a theoretical analysis that shows that developers have incentives to

release updates when experiencing a drop in performance. The predictions of

the model are then tested using an unbalanced panel of top 1,000 apps in

iTunes and Google Play for five European countries. We estimate that while

in iTunes the release of an update stimulates a 26% increase in download

growth, in Google Play updates play a less significant role. This difference is

partly due to systematic differences in apps and in developers operating in

the two stores (“selection effect”), and partly to a lack of quality control on

apps and updates in Google Play (“quality check effect”). These findings

highlight the crucial importance of an appropriate management of updates

as well as the relevance of institutional characteristics of the app stores.

KEYWORDS

buzz, downloads, Google Play, iTunes, multi-homing, mobile applications, quality check, updates

A lot of app developers will see a large spike in downloads right at launch, and shortly after see these numbers

slowly dwindle. The question I get asked in this situation is, “How do I continue growth?”The answer is […]in

order to continue growth you need to provide constant value, which […] also means updating your app! That

said, I always encourage my students to update their apps and keep iterating to get feedback, which helps boost

downloads. Letting your apps collect dust is the same as letting them fail […]

Chad Mureta

1

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INTRODUCTION

On November 25, 2015, Wooga released version 6.3.0 of its well‐known arcade game Diamond Dash. This version of the

software followed the 6.2.0 update by 1 month and a half which, itself, was released only 2 weeks after version 6.1.0.

From November 2011—the time the app was launched in iTunes—to November 2015, Diamond Dash was updated

nearly 60 times, on average more than once per month. This is not an exception. The frequent release of updates is a

J Econ Manage Strat. 2019;28:392–419.wileyonlinelibrary.com/journal/jems392

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© 2018 Wiley Periodicals, Inc.

*Paper presented at the 2015 annual conferences: Economics of ICTs (Telecom ParisTech), French Economic Association, Centre for Competition

Policy, and at the 2016 annual conferences: Florence School of Regulation, International Industrial Organization Society, Royal Economic Society,

Association of Southern European Economic Theorists, and Jornadas de Economia Industrial.

common feature among apps: In our sample, apps are updated on average every 13 days in Google Play and every

58 days in iTunes.

With millions of apps available in various stores, developers face a tremendous challenge. Not only do they struggle

to catch the attention of prospective users (Bresnahan, Davis, & Yin, 2014), but they also fiercely compete for usage.

Competition among developers is so harsh that app markets are labelled as “hypercompetitive”(Datta &

Sangaralingam, 2013). As suggested by the quote from the distinguished entrepreneur and blogger Chad Mureta, the

frequent release of updates represents a natural strategy to maintain performance in such competitive environment.

Developers update their apps not only to introduce new features or functionalities, thus (potentially) increasing the

quality of the software, but also to stimulate what is known as the “buzz”around the app. Typically, when an app is

upgraded, its new features are likely to be presented and discussed in dedicated blogs, in online magazines or among

users of social networks. Also, developers usually promote the new versions of their apps through several channels or

directly in the “What’s New”section of the app stores. Generating buzz is essential to stay on top of the

hypercompetitive app markets. Only those apps that are able to get noticed and to attract users’attention can survive

and possibly thrive.

Besides the high degree of competition, another relevant feature characterising the app market is the skewness of the

distribution of downloads and usage. According to Appbrain.com, in Google Play more than 2 million apps out of 2.8

million have less than 1,000 downloads each while, by comparison, just 50,000 apps have more than 1 million

downloads. Similarly, for app usage, Google (2015) shows that, on average, only one‐out‐of‐four installed apps is

actually used daily; a similar fraction of apps is installed but never used. In a competitive environment where either you

win big or you drastically fall down in ranking, it is even more compelling to adopt an effective management of updates

to attract customer attention.

In this study, we study the effectiveness of releasing updates to improve app performance, and for this purpose, we

employ data on apps distributed in the two most popular app stores: iTunes and Google Play. Interestingly, the two

stores follow different policies regarding the release of apps and updates. The functionality section of the iTunes “App

store review guidelines”explicitly sets a strict screening of app quality. For example, apps that exhibit bugs or that are

in a beta/trial version are going to be rejected by the store. Similarly, applications that are considered not very useful or

that include undocumented or hidden features inconsistent with the description of the app are rejected. By contrast,

publication in Google Play does not go through a similar quality check as developers with a “simple click of the mouse”

can publish apps and updates instantaneously.

1

In this paper, we argue that these institutional differences have

important consequences on the characteristics of updates and on how they affect the performance of apps.

We start our analysis by presenting a stylised theoretical framework that focuses on the developers’decisions about

whether to update their mobile applications. We show that, in an attempt to “revive”their app, developers are more

likely to release an update when they observe a worsening of the performance. Interestingly, our analysis highlights

that the incentives to update might be so strong that a developer could decide to also release an update of low quality to

counter a drop in performance; by stimulating the buzz surrounding their app, developers might succeed in attracting

users’attention even with an update that makes little improvement to the software code. This result suggests an

interesting prediction based on the institutional differences characterising the two stores. The strong incentives to

release new versions of the software induce developers in Google Play to release both high‐and low‐quality updates,

thus diluting the effects on downloads. This strategy cannot be used in iTunes provided that the strict control

implemented by Apple limits the ability of developers to release low‐quality updates. Hence, we expect that updates

have a stronger impact on downloads in iTunes than in Google Play.

Figure 1 provides preliminary support to our argument. The figure shows the kernel density of the growth in

downloads of the apps in our sample, distinguishing between apps that have been updated during the period of

observation and apps that have not been updated. Interestingly, in Google Play the two density functions nearly

perfectly overlap; this suggests that updated and nonupdated apps perform very similarly in terms of downloads. On the

contrary, in iTunes the density function of nonupdated apps is more asymmetric and concentrated on the negative

values of download growth rate. According to this figure, updates seem to have a different impact on app performance

in the two stores.

To investigate the impact of updates, we use an unbalanced panel of the top 1,000 apps distributed in iTunes and in

Google Play, in five European countries. Our estimates confirm that updates have a stronger impact on downloads in

iTunes than in Google Play. The analysis suggests that this result is partly related to a “selection effect”(systematic

differences in the apps and developers operating in the two stores) and partly to the “quality check effect.”To isolate the

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