Three Essays on Mobile Application Developers’ Product Offering Strategies

Abstract

In the recent years, mobile applications (apps) have been immensely changing the way of communication, socialization, work, and recreation through mobile devices. Mobile app developers usually face challenges in product offering decisions. In the dissertation I study app developers’ product offering decisions when facing the setting of multiple platforms, in-app purchase (IAP), and in-app advertisement (IADV). In specific, I construct various analytical models in order to capture different conditions faced by app developers. In the first essay, I develop an analytical framework to address a product offering problem for an app developer that introduces paid or free apps in a two-platform market. When offering a paid app, I find that the developer should launch the product in the more profitable platform that has relative advantages in user base and willingness to pay; whether the developer should launch the same app in a second platform depends on the app launching cost. I find that launching free apps in both platforms is a better choice as long as users are tolerant to advertisements in the app. If users are not tolerant to advertisements, the developer should launch the app in the more profitable platform. Furthermore, I find that if users’ disutility sensitivity to advertisement is very small, it is better to introduce the free app rather than the paid app. In the second essay, I consider mobile app developers’ product versioning decisions by focusing on IAP. Should a developer provide consumers an app (free or paid) with IAP option in one platform (e.g., Android or iOS), and how should it design and price the basic app and IAP? I find that the answer to the former question is “it depends”, although in most situations offering IAP is a better choice. I also compare forward-looking and myopic strategies and show that the former always outperforms the latter. In the third essay, I focus on app developers’ decision on the frequency of displaying ads to current users; also, I examine app developers’ revenue model selection. From app developers’ perspective, I show that under information asymmetry condition it is possible to figure out the optimal ad frequency. Furthermore, “trial and then free without ads” (TF) is always suboptimal. “Trial and then paid” (TP) strategy is dominant if market size is small; otherwise, “trial and then free with ads” (TFA) strategy is dominant. The welfare analysis suggests that any of the above three strategies can result