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Intra-Platform Competition: The Role of Strategic and Operational Evolution in App Success

A software-based platform brings app developers and customers together. It creates new opportunities for app developers to compete in a
dynamically changing marketplace. To survive in intra-platform competition, app developers have to successfully manage and evolve their apps.
Intra-platform competition is inherently dynamic due to the rapid growth in apps. Understanding how to be successful in this competition is a
critical issue for app developers. In this study, I draw on evolutionary economics theory to reveal what drives app success in intra-platform
competition. The research model was tested using survey data collected from 218 app developers on Google Play and objective data collected from
three websites (Google Play, AppAnnie, and AppBrain). This study found that the online customer monitoring routine is positively associated with
both strategic evolution and operational evolution. Meanwhile, strategic evolution is positively associated with operational evolution.
Furthermore, this study found that operational evolution is positively associated with app market performance. This study has three
contributions to theory. First, by focusing on the content of evolution such as what and how an app evolves, this study proposes a more
comprehensive conceptualization of evolution that includes both strategic evolution and operational evolution, rather than simply the speed of
evolution. Second, this study empirically tests the intertwined relationships among strategic evolution, operational evolution, and app market
performance, which promote a sound understanding of evolution and its impacts on app success. Third, this study identifies three types of online
monitoring routines that allow app developers to continue observing environmental changes in the market. It reveals how app developers leverage
their online monitoring routines to influence the evolution of their apps. In this way, this study helps us better understand the role of online
monitoring routines in app evolution. This research also makes two contributions to practice. First, unlike previous studies that suggested that
fast evolution of an app can lead to better performance, this study shows app developers that how they evolve an app matters. By investigating
the impacts of these two types of evolution on app success, this study provides suggestions to app developers that help them improve their app
market performance, when they have limited resources to allocate to app evolution. Second, this study also shows app developers that continually
observing customers' activities can help them discover ways to evolve their apps, and thus increase an app's market performance. This finding
shows app developers the importance of online monitoring routines and helps small or startup app developers with limited resources understand
how to access market environment information. / A Dissertation submitted to the Department of Business Analytics, Information Systems and Supply Chain in
partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2018. / August 31, 2018. / Includes bibliographical references. / Ashley A. Bush, Professor Co-Directing Dissertation; Xinlin Tang, Professor Co-Directing Dissertation; Ruby
(Pui Wan) Lee, University Representative; Guangzhi Shang, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_661201
ContributorsLiu, Yi (author), Bush, Ashley A. (professor co-directing dissertation), Tang, Xinlin (professor co-directing dissertation), Lee, Ruby P. (university representative), Shang, Guangzhi (committee member), Florida State University (degree granting institution), College of Business (degree granting college), Department of Business Analytics (degree granting departmentdgg)
PublisherFlorida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text, doctoral thesis
Format1 online resource (135 pages), computer, application/pdf

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