EMPIRICAL INVESTIGATION OF USERS’ SUCCESSFUL STRATEGIES IN ONLINE PLATFORMS - EVIDENCE FROM CROWD-SOURCING AND SOCIAL MEDIA PLATFORMS

Abstract

With the proliferation and constant growth of online platforms, there has been an increasing interest among academicians and practitioners to understand various aspects of these platforms, including the effective design of platforms, their governance and user engagement. This dissertation seeks to add to this stream of research by leveraging large-scale unstructured data and corresponding data analytics and econometric techniques to examine users’ strategies in online social media and crowdsourcing platforms and gain insights into factors that lead to successful outcomes. The first essay examines the content strategies of closely competing firms on Twitter with a focus on how the similarity/dissimilarity of their content strategies impacts their online outcomes. I find that firms that are more adept at leveraging higher-level social media affordances, such as interactivity, collaboration, and online contests to differentiate their content strategies experience better outcomes as compared to their closest rivals that only leverage the basic technological affordances of social media. The second essay examines successful strategies of users (designers) in a crowdsourcing platform wherein clients post contests to solicit design solutions for a monetary reward. This study uses state-of-the-art deep learning and image analysis techniques to examine the strategies of experienced and less-experienced designers in open contests where later-entrants can potentially leverage information spillovers from earlier design submissions within a contest. I find that while later-entrants typically leverage information spillovers from earlier submissions in a contest, only experienced designers who are able to integrate information from multiple highly-rated early submissions are more likely to be successful. The third essay examines users’ strategies in response to the introduction of an Artificial Intelligence system for logo design in an online crowdsourcing design platform. In analyzing what differentiates successful contestants from the others, I find that the successful contestants significantly increase focus (i.e., the number of re-submissions per contest) and increase the emotional content as well as the complexity of their designs, in response to the introduction of the AI system. Collectively, the findings from these studies add to our understanding of successful strategies in online platforms and provide valuable insights to theory and practice.