In-app Advertisements Research Articles

How do mobile app users react to embedded advertising? A perspective from psychological reactance theory

ABSTRACT This study investigated the effects of in-app advertisements (in-app ads) on user responses based on psychological reactance theory. Three types of in-app ads were categorised: banners, pop-up graphics and pop-up video clips. The study also examined the moderating effect of prior negative experiences on the relationship between in-app ad appearance and advertising clutter and in-app ad appearance and advertising scepticism. A total of 1,343 valid questionnaires were collected for each type of in-app ad. Structural equation modelling (SEM) analysis revealed that the duration and frequency of different ads had distinct effects on users' negative psychological reactance, leading to behaviours of ignoring and resisting the ads. Moreover, advertising clutter not only positively influenced advertising scepticism but also increased advertising avoidance, subsequently impacting both the tendency to ignore and resist the advertised content. Prior negative experiences played a moderating role in the banner and pop-up graphic ad models. In conclusion, this study recommends that app developers avoid overwhelming sensory stimulation when displaying ads to reduce the complexity of visual perception. Improving content innovation can help minimise users perceiving the ads as obtrusive. Furthermore, emphasising the relevance of advertisements by integrating them effectively with app functions can increase user ad acceptance.

Click fraud detection for online advertising using machine learning

Advertising corporations have moved their focus to online and in-App advertisements in response to the expansion of digital technologies and social media. Online advertising represents the primary revenue source for advertising networks that serve as the middlemen between advertisers and advertisement publishers. The advertising networks pay the publisher of the advertisement based on the number of clicks through to advertisers, following the pay-per-click (PPC) payment scheme. However, there is a growing security issue with this payment approach known as Click Fraud. Click fraud is the illegal process of clicking on pay-per-click advertisements to increase publishers' revenue or deplete advertisers' budgets. Artificial intelligence techniques have been increasingly employed to solve complicated challenges in different research areas, including cybersecurity, to achieve unexpected outcomes. In this paper, several Machine Learning models were constructed to establish whether the user is a human or a bot and conducted a comparative performance analysis using a set of evaluation metrics. We used a real captured dataset detailing Internet users' behavior while navigating websites. We extracted a set of features related to users’ behaviors, including the number of webpages viewed during the browsing session, the duration of the browsing journey, and the actions performed. The empirical results revealed that all the considered models obtained good results, where the random forest algorithm surpassed all other algorithms in all evaluation metrics.

Analysis on the in-app advertising contract of a mobile platform and two competitive app developers

Moblie platform is an online store for distributing mobile apps and designed to connect mobile app developers and users. Mobile platform launches in-app advertisement for their advertisers to monetize the mobile app market. Unlike traditional advertising, the profitability of in-app advertising is not only affected by the decision of the platform, but also by the decision of the app developer, and they will share the advertising revenue. We develop an app advertising revenue sharing model with two competitive app developers and one mobile platform. The mobile platform is the leader, and the two app developers are the follower. Our analysis shows that the two app developers may choose to publish or not publish adds. If publishing, app developers may choose to offer a free app with in-app ads, or choose to offer a paid app with in-app ads. These results can be categorized into seven ranges for the platform's given revenue share of advertisement. In addition, we find the platform's optimal choice of ad revenue share is affected by the quality of advertisement. With the improvement of advertising quality, the revenue sharing ratio will first remain unchanged, then decrease, and finally increase. This is caused by the platform's subsidization strategy for app developers.

DeviceWatch: A Data-Driven Network Analysis Approach to Identifying Compromised Mobile Devices with Graph-Inference

We propose to identify compromised mobile devices from a network administrator’s point of view. Intuitively, inadvertent users (and thus their devices) who download apps through untrustworthy markets are often lured to install malicious apps through in-app advertisements or phishing. We thus hypothesize that devices sharing similar apps would have a similar likelihood of being compromised, resulting in an association between a compromised device and its apps. We propose to leverage such associations to identify unknown compromised devices using the guilt-by-association principle. Admittedly, such associations could be relatively weak as it is hard, if not impossible, for an app to automatically download and install other apps without explicit user initiation. We describe how we can magnify such associations by carefully choosing parameters when applying graph-based inferences. We empirically evaluate the effectiveness of our approach on real datasets provided by a major mobile service provider. Specifically, we show that our approach achieves nearly 98% AUC (area under the ROC curve) and further detects as many as 6 ~ 7 times of new compromised devices not covered by the ground truth by expanding the limited knowledge on known devices. We show that the newly detected devices indeed present undesirable behavior in terms of leaking private information and accessing risky IPs and domains. We further conduct in-depth analysis of the effectiveness of graph inferences to understand the unique structure of the associations between mobile devices and their apps, and its impact on graph inferences, based on which we propose how to choose key parameters.

Recruiting Black Men Who Have Sex With Men (MSM) Couples via Dating Apps: Pilot Study on Challenges and Successes.

BackgroundHIV disproportionately impacts Black men who have sex with men (MSM), and targeting the primary relationship (ie, couples) using mobile technology for health holds promise for HIV prevention. Web-based recruitment of MSM is commonly employed in HIV prevention and intervention research. However, little known about recruiting Black MSM couples on the internet in the United States.ObjectiveThis study describes the process of recruiting Black MSM couples over social networking and dating apps frequented by MSM. We describe the activities for recruiting, screening, and enrolling participants as part of a randomized trial employing a multipronged recruitment approach.MethodsBlack MSM in couples were recruited via three apps (ie, Jack’d, Adam4Adam, and Growlr) between May 2020 and March 2021 during the COVID-19 pandemic in the United States. Black MSM couples were eligible if one or both partners are Black, MSM, and living with HIV, and if both partners were 18 years or older, and have been together for at least 2 months in what they both consider a primary relationship (ie, one in which both partners reported feeling most committed to over any other partner or relationship).ResultsA total of 10 Black MSM couples (n=20) were enrolled via social networking apps. App recruitment activities were a combination of passive (eg, in-app advertisements) and active (eg, direct messaging of users) engagement. Recruitment approaches varied by the social networking app owing to differences in app features. A full-time recruiter experienced challenges such as bugs (ie, technical errors in computer program or system), navigating technical requirements specific to each app, and web-based harassment.ConclusionsDespite challenges, it was possible to recruit Black MSM couples virtually into research as part of a multipronged recruitment strategy. We identify tips for using web-based dating and other social networking apps as part of a recruitment strategy in future research with Black MSM couples.

Utilization of a mobile phone application to increase access to sexual and reproductive health information, goods, and services among university students in Uganda

BackgroundInnovations to increase access to sexual and reproductive health (SRH) information, goods, and services are needed, particularly in low-income settings. This study assessed the utilization of a mobile phone application (MPA) to increase access to SRH information, goods, and services among university students in Uganda.MethodsWe conducted a cross-sectional analysis of data from: (1) an endline survey performed as a consequence of a randomized controlled trial (RCT) of the effectiveness of the MPA, and (2) data from use of the MPA for accessing information, goods, and services over the 6-month time period of the RCT, obtained from in-MPA data collection service providers. We performed descriptive analysis of participant characteristics and their association with the utilization of the MPA using logistic regression; analyses of MPA use for accessing different types of information, goods, and services by gender; and analyses of functionality attributes of the MPA and related services.ResultsIn the study population of young (median 22 years) predominantly female (61%) students, the utilization of the MPA by those who downloaded it was high (81% overall, 82% female, and 82% male). The most popular information portal was the frequently asked questions (71% utilization); the most popular goods were condoms for males (77% utilization) and sanitary pads for females (94% utilization); and the most popular service was HIV testing and counseling (60% utilization). The MPA demonstrated predominantly positive (responsiveness, non-distracting in-app advertisements, and ease of use) attributes.ConclusionA mobile phone app to increase access to SRH information, goods, and services among university students in Uganda demonstrated high utilization. The results of this study support ongoing and future technical improvement efforts and research on effectiveness, economic efficiency, and scalability, along the continuum of activities to scale this intervention in order to improve SRH in low-income settings.Trial RegistrationMUREC1/7 No. 07/05-18. Registered; June 29, 2018.

In-app advertising: a two-step qualitative comparative analysis to explain clicking behavior

Purpose Individuals only click on a very small fraction of the in-app advertisements (ads) they are exposed to. Despite this fact, organizations spend generously placing in-app ads without theoretical knowledge of how the structure and the semantics of in-app ads influence individuals’ clicking behavior. This study aims to identify how the processing of structural and semantic factors leads to clicking behavior. Design/methodology/approach Based on the limited capacity theory, this paper proposes that the sequential processing of structural and semantic factors leads to clicking behavior. To mirror the sequential process, this paper applies a process-oriented configurational approach and performs a two-step qualitative comparative analysis (QCA) using 262 incidents of exposure to in-app ads. Findings The results support the proposed sequential processing and show that neither structural nor semantic factors alone lead to clicking behavior. This paper reveals four different paths of sequential processing of in-app ads that lead to clicking behavior. The results show that individuals click on non-animated in-app ads even though these are perceived as irritating or privacy-concerning. When the in-app ads are animated, individuals do only click on them when these are not irritating, privacy-concerning and personalized. Research limitations/implications Organizations can use these findings to improve their in-app ads and generate more clicks. This study recommends that organizations place in-app ads in a prominent location, design them similar to the design of the app and use bright colors. The advertising message needs to have new and relevant information in a credible and entertaining way. Depending on the degree of personalization, organizations should use different sizes of the in-app ad and only use animation if it is unlikely that the in-app ad caused irritation or privacy concerns. Practical implications Organizations can use these findings to improve their in-app ads and generate more clicks. This paper recommends that organizations place in-app ads in a prominent location, design them similar to the design of the app and with bright colors. The advertising message needs to have new and relevant information in a credible and entertaining way. Depending on the degree of personalization, organizations should use different sizes of the in-app ad and only use animation if it is unlikely that the in-app ad caused irritation or privacy concerns. Originality/value From the in-app ad perspective, this study is the first to theoretically develop and empirically show the sequential processing of structural and semantic factors of in-app ads. From the methodological perspective, this study applies an advanced configurational two-step QCA approach, which is capable of analyzing sequential processes and is new to marketing research.

Studying Ad Library Integration Strategies of Top Free-to-Download Apps

In-app advertisements have become a major revenue source for app developers in the mobile app ecosystem. Ad libraries play an integral part in this ecosystem as app developers integrate these libraries into their apps to display ads. In this paper, we study ad library integration practices by analyzing 35,459 updates of 1,837 top free-to-download apps of the Google Play Store. We observe that ad libraries (e.g., Google AdMob) are not always used for serving ads -- 22.5% of the apps that integrate Google AdMob do not display ads. They instead depend on Google AdMob for analytical purposes. Among the apps that display ads, we observe that 57.9% of them integrate multiple ad libraries. We observe that such integration of multiple ad libraries occurs commonly in apps with a large number of downloads and ones in app categories with a high proportion of ad-displaying apps. We manually analyze a sample of apps and derive a set of rules to automatically identify four common strategies for integrating multiple ad libraries. Our analysis of the apps across the identified strategies shows that app developers prefer to manage their own integrations instead of using off-the-shelf features of ad libraries for integrating multiple ad libraries. Our findings are valuable for ad library developers who wish to learn first hand about the challenges of integrating ad libraries.

Factors Related to User Ratings and User Downloads of Mobile Apps for Maternal and Infant Health: Cross-Sectional Study.

BackgroundMobile health apps related to maternal and infant health (MIH) are prevalent and frequently used. Some of these apps are extremely popular and have been downloaded over 5 million times. However, the understanding of user behavior and user adoption of these apps based on consumer preferences for different app features and categories is limited.ObjectiveThis study aimed to examine the relationship between MIH app characteristics and users’ perceived satisfaction and intent to use.MethodsThe associations between app characteristics, ratings, and downloads were assessed in a sample of MIH apps designed to provide health education or decision-making support to pregnant women or parents and caregivers of infants. Multivariable linear regression was used to assess the relationship between app characteristics and user ratings, and ordinal logistic regression was used to assess the relationship between app characteristics and user downloads.ResultsThe analyses of user ratings and downloads included 421 and 213 apps, respectively. The average user rating was 3.79 out of 5. Compared with the Apple App Store, the Google Play Store was associated with high user ratings (beta=.33; P=.005). Apps with higher standardized user ratings (beta=.80; P<.001), in-app purchases (beta=1.12; P=.002), and in-app advertisements (beta=.64; P=.02) were more frequently downloaded. Having a health care organization developer as part of the development team was neither associated with user ratings (beta=−.20; P=.06) nor downloads (beta=−.14; P=.63).ConclusionsA majority of MIH apps are developed by non–health care organizations, which could raise concern about the accuracy and trustworthiness of in-app information. These findings could benefit app developers in designing better apps and could help inform marketing and development strategies. Further work is needed to evaluate the clinical accuracy of information provided within the apps.

Moderating Factors Affecting Intention to Access In-App Advertisements

Role of moderator in research is significant. Many researchers consider moderator in terms of control factors or constants; however, moderator can significantly increase value of research model. In this article, a review is made of recent literature to identify potential moderators for in-app advertisements adoption models. In-app advertisements is an evolving technology which is spreading at varying speed across the globe. There is scope of research in this field. Recent research articles are reviewed to identify potential moderators. Their proposed relationships in various scenarios are presented. At the end of the review, relevant moderators for in-app advertisement adoption models are presented with examples how researchers can find relevant moderators in a scenario.

A longitudinal study of popular ad libraries in the Google Play Store

In-app advertisements have become an integral part of the revenue model of mobile apps. To gain ad revenue, app developers integrate ad libraries into their apps. Such libraries are integrated to serve advertisements (ads) to users; developers then gain revenue based on the displayed ads and the users’ interactions with such ads. As a result, ad libraries have become an essential part of the mobile app ecosystem. However, little is known about how such ad libraries have evolved over time. In this paper, we study the evolution of the 8 most popular ad libraries (e.g., Google AdMob and Facebook Audience Network) over a period of 33 months (from April 2016 until December 2018). In particular, we look at their evolution in terms of size, the main drivers for releasing a new version, and their architecture. To identify popular ad libraries, we collect 35,462 updates of 1,840 top free-to-download apps in the Google Play Store. Then, we identify 63 ad libraries that are integrated into the studied popular apps. We observe that an ad library represents 10% of the binary size of mobile apps, and that the proportion of the ad library size compared to the app size has grown by 10% over our study period. By taking a closer look at the 8 most popular ad libraries, we find that ad libraries are continuously evolving with a median release interval of 34 days. In addition, we observe that some libraries have grown exponentially in size (e.g, Facebook Audience Network), while other libraries have attempted to reduce their size as they evolved. The libraries that reduced their size have done so through: (1) creating a lighter version of the ad library, (2) removing parts of the ad library, and (3) redesigning their architecture into a more modular one. To identify the main drivers for releasing a new version, we manually analyze the release notes of the eight studied ad libraries. We observe that fixing issues that are related to displaying video ads is the main driver for releasing new versions. We also observe that ad library developers are constantly updating their libraries to support a wider range of Android platforms (i.e., to ensure that more devices can use the libraries without errors). Finally, we derive a reference architecture from the studied eight ad libraries, and we study how these libraries deviated from this architecture in the study period. Our study is important for ad library developers as it provides the first in-depth look into how the important mobile app market segment of ad libraries has evolved. Our findings and the reference architecture are valuable for ad library developers who wish to learn about how other developers built and evolved their successful ad libraries. For example, our reference architecture provides a new ad library developer with a foundation for understanding the interactions between the most important components of an ad library.

Game in the Game: Examining In-App Advertising in Mobile Sports Games

The purpose of this study is to examine in-app advertisement within mobile games and the content of the advertisement. The universe of this study is sports game applications under games category in Apple Store. The sample is 32 sports games that were selected by random sampling method among popular games listed under sports category in Apple Store. Determined advertisements were analysed with the content analysis method. As a result of the research; it has been determined that sports games that are examined under mobile applications, primarily contain in-app advertisements for strategy, shopping, casino and bank applications, and games. Accordingly, more than half of the ads in evaluated mobile sports games were about mobile games and in-apps about mobile sports games were less. When in-app games were investigated in terms of appearance on screen, the great majority of mobile sport game ads were interstitial ads. As a conclusion; in spite of the changes in entertainment concept as a result of the developments in mobile technology, it has been determined that sport is used as direct or indirect marketing material as it is in the approach of traditional sports marketing. The implications from this research include a better understanding of how in-app advertising is being used to sports marketing and marketing communication.

Mobile Apps for Blood Pressure Monitoring: Systematic Search in App Stores and Content Analysis.

BackgroundUsing a mobile app for self-management could make it easier for patients to get insight into their blood pressure patterns. However, little is known about the availability, quality, and features of mobile apps targeting blood pressure.ObjectiveThe goal of the research was to determine the availability, functionality, and quality of mobile apps that could be used for blood pressure monitoring purposes.MethodsA systematic app search was performed based on the standards for systematic reviews. We searched the Dutch official app stores for Android and iOS platforms using predefined keywords and included all English and Dutch mobile apps targeting blood pressure. Two independent assessors determined eligibility and quality of the apps using the 5-point Mobile App Rating Scale (MARS). Quality scores of the apps with and without 17 a priori selected characteristics were compared using independent sample t tests.ResultsA total of 184 apps (104 Android, 80 iOS) met the inclusion criteria. The mean overall MARS score was 2.63 (95% CI 2.55-2.71) for Android and 2.64 (95% CI 2.56-2.71) for iOS. The apps Bloeddruk (4.1) and AMICOMED BP (3.6) had the highest quality scores on the Android and iOS platforms, respectively. Of the app characteristics recorded, only pricing, in-app advertisements, and local data storage were not associated with the quality scores. In only 3.8% (7/184) of the apps, involvement of medical experts in its development was mentioned, whereas none of the apps was formally evaluated with results published in a peer-reviewed journal.ConclusionsThis study provides an overview of the best apps currently available in the app stores and important key features for self-management that can be used by health care providers and patients with hypertension to identify a suitable app targeting blood pressure monitoring. However, the majority of the apps targeting blood pressure monitoring were of poor quality. Therefore, it is important to involve medical experts in the developmental stage of health-related mobile apps to improve the quality of these apps.

Understanding In-App Ads and Detecting Hidden Attacks through the Mobile App-Web Interface

Mobile users are increasingly becoming targets of malware infections and scams. In order to curb such attacks it is important to know how these attacks originate. We take a previously unexplored step in this direction. Numerous in-app advertisements work at this interface: when the user taps on the advertisement, she is led to a web page which may further redirect until the user reaches the final destination. Even though the original applications may not be malicious, the Web destinations that the user visits could play an important role in propagating attacks. We develop a systematic static analysis methodology to find ad libraries embed in applications and dynamic analysis methodology consisting of three components related to triggering web links, detecting malware and scam campaigns, and determining the provenance of such campaigns reaching the user. Our static analysis system identified 242 different ad libraries and dynamic analysis system was deployed for a two-month period and analyzed over 600,000 applications while triggering a total of about 1.5 million links in applications to the Web. We gain a general understanding of attacks through the app-web interface and make several interesting findings including a rogue antivirus scam, free iPad scams, and advertisements propagating SMS trojans.

Factors Affecting Attitudes and Behavioral Intentions Toward In-app Mobile Advertisements

ABSTRACTMobile apps show a heavy usage pattern and compelling growth figures. This study seeks to examine consumers' attitudes toward in-mobile advertisements in terms of mobile advertising value. The samples are from the United Kingdom (UK) and India because the nationals of these countries exhibit a high degree of dissimilarity in a number of Hofstede's cultural dimensions. The findings suggest that factors such as perceived entertainment, credibility, and information significantly improve attitudes toward in-app advertisements, and that the effectiveness of these advertisements is based on cultural differences. The participants from India exhibited more positive attitudes toward in-app advertisements than their counterparts from the UK. The entertainment factor had a greater impact on Indian, while credibility and information had a more significant impact on smartphone users from the UK.

The influence of the propensity to trust on mobile users' attitudes toward in-app advertisements: An extension of the theory of planned behavior

In-app advertising is one of the fastest growing areas in social commerce. Building on previous studies of e-commerce and psychological theories, this paper examines a theoretical model that extends the theory of planned behavior to include the propensity to trust and trust as antecedents of mobile users' attitudes toward in-app advertisements. The model was tested with 480 young Chinese mobile users. Results of structural equation modeling indicated that users' propensity to trust affected their trust in in-app advertising, and this in turn affected their attitudes toward in-app advertisements and their intention to watch in-app advertisements. In addition, subjective norm and perceived behavioral control were found to positively predict users' intention to watch in-app advertisements, which in turn affected their behavioral response. Practical implications are provided to increase users' trust and promote favorable attitudes toward in-app advertisements.

Apriori Rule--Based In-App Ad Selection Online Algorithm for Improving Supply-Side Platform Revenues

Today, smartphone-based in-app advertisement forms a substantial portion of the online advertising market. In-app publishers go through ad-space aggregators known as Supply-Side Platforms (SSPs), who, in turn, act as intermediaries for ad-agency aggregators known as demand-side platforms. The SSPs face the twin issue of making ad placement decisions within an order of milliseconds, even though their revenue streams can be optimized only by a careful selection of ads that elicit appropriate user responses regarding impressions, clicks, and conversions. This article considers the SSP's perspective and presents an online algorithm that balances these two issues. Our experimental results indicate that the decision-making time generally ranges between 20 ms and 50 ms and accuracy from 1% to 10%. Further, we conduct statistical analysis comparing the theoretical complexity of the online algorithm with its empirical performance. Empirically, we observe that the time is directly proportional to the number of incoming ads and the number of online rules.

Mobile App Development Ecosystem - Lessons from Four African Countries

This paper presents an assessment of existing mobile application (app) business models that are targeted at people living at the base of the pyramid (BoP) or that are suitable for people living at the BoP. The purpose of the paper is to address specific pain points for app developers and to provide practical, actionable advice. The recommendations of this paper are specific to each of four countries: Ghana, Mozambique, Nigeria and Zambia. In assessing the app markets in each of the four countries, it quickly becomes clear that there is a wide range of business models. Part of the business model is unique to the sector and to the business problem that the app is attempting to solve. In order to provide maximum value for app developers, this research focuses on three areas that are common to all business models: *Revenue sources - How to generate revenue is at the heart of any business model. App developers have to choose how to make money from their products and services. The options include in-app advertisement, pay per download of content or app, in-app purchases, upgrade of a free app to a more feature-rich one in exchange for a fee (freemium) and subscriptions. *Distribution channels - The availability of a mobile application is dependent upon its distribution network. Distribution can take place either via an app store, a mobile operator (through USSD services, for example) or through a local distribution network. *Payment facilities - The main payment options for app developers include premium SMS, airtime transfer, mobile money and bank-based payments such as electronic transfers and payment by cheque, or with debit and credit cards. In addition to an analysis of the three common business model areas, there is a brief assessment of the significant role of incubators in in supporting app developers. However, the impact of incubators is only partially realised and the paper has several recommendations. The key findings in each of the three business model areas as well as for app incubators are: *Revenue sources - Multi-sided platforms are an under-exploited business model. Providing a service to consumers that is paid for by businesses - the other side of the platform - means that apps are more likely to make a profit and be sustainable. Of course, the multi-sided model is dependent on addressing a problem or need experienced by both sides of the equation: consumers and businesses. *Payment facility - Premium SMS is the ideal payment facility because it reaches all mobile subscribers regardless of phone type. However, premium SMS is challenging because the MNO revenue share can be very high. Nevertheless, the finding of this report is that rates are negotiable and MNOs are beginning to realise that their high revenue share is slowing market growth. At the same time increasing Smartphone penetration and mobile money adoption rapidly creates alternative payment facilities, outside MNO control. *Distribution platform - MNO stores are ideal distribution channels because of their access to local subscribers, but this is unrealised. As a result, independent distribution is the most common option. For feature phones, the Ovi Store is a viable alternative but this is only an option in Nigeria where the Ovi Store has a local presence. As smartphone adoption increases, Google Play will become dominant, and there is a commercial opportunity for Google in terms of registering developers as merchants. Currently, this is not possible in any African country. *Incubators & hubs - Every hub or incubator visited by the team was staffed by inspiring and motivated personnel. It is clear that the more structured the environment, the more beneficial the process will be for developers in terms of providing specific programs at regular and planned intervals. The target is to better mix the commercial realities of launching a business with the technical skills already available in each of the hubs. This paper identifies business models for mobile applications that target the BOP, i.e., those that live on less than US$2.5 a day and that are revenue generating in in Ghana, Nigeria, Zambia and Mozambique. The key theme informing the analysis was as follows: can an environment be created that would support an explosion of mobile applications such as in Europe and North America? There is clearly an opportunity - in 2012, the mobile application economy was worth US$53 billion and is expected to expand at a 28% compound annual growth rate up to 2016, reaching US$143 billion. In comparison, the app economy in Africa is minuscule, and the likelihood of the number of mobile applications growing explosively is low. GitHub, an online resource for developers to store code, shows that only 0.12% of its users are from Africa out of a developer base of nearly 4 million.

Estimating Demand for Mobile Applications in the New Economy

In 2013, the global mobile app market was estimated at over US$50 billion and is expected to grow to $150 billion in the next two years. In this paper, we build a structural econometric model to quantify the vibrant platform competition between mobile (smartphone and tablet) apps on the Apple iOS and Google Android platforms and estimate consumer preferences toward different mobile app characteristics. We find that app demand increases with the in-app purchase option wherein a user can complete transactions within the app. On the contrary, app demand decreases with the in-app advertisement option where consumers are shown ads while they are engaging with the app. The direct effects on app revenue from the inclusion of an in-app purchase option and an in-app advertisement option are equivalent to offering a 28% price discount and increasing the price by 8%, respectively. We also find that a price discount strategy results in a greater increase of app demand in Google Play compared with Apple App Store, and app developers can maximize their revenue by providing a 50% discount on their paid apps. Using the estimated demand function, we find that mobile apps have enhanced consumer surplus by approximately $33.6 billion annually in the United States, and we discuss various implications for mobile marketing analytics, app pricing, and app design strategies.This paper was accepted by Alok Gupta, special issue on business analytics.

Apps marketplaces and the telecom value chain

We can conclude that smartphones and apps marketplaces are a game changer as they truly enable innovation at the edge. Mobile app usage will put considerable pressure on mobile access networks, requiring extensive R&D to improve spectral efficiency and expensive investments to increase network capac ity. Ecosystem growth is only sustainable if the value appropria tion by members is commensurate with their investment risks. Certain app marketplace features, such as in-app payment and in-app advertisement, need to stay open and configurable to avoid value misappropriation, and the industry needs to work together to ensure that such openness can be ensured.