Doctor of Philosophy (PhD)
Stephenson Department of Entrepreneurship & Information Systems
Aggregators increasingly exert their control over suppliers through digital algorithms. A prominent example is the algorithmic management of visibility. When suppliers enter an aggregator’s ecosystem, they have to compete for visibility with a significant number of competitors. Despite the importance and vast number of suppliers that compete within aggregator’s ecosystems, few studies have investigated the idiosyncratic competitive dynamics they face. By adopting the point of view of suppliers, I investigate how they can improve their visibility by carrying out competitive actions. Specifically, extending competitive repertoire theory, I investigate the role of competitive repertoires configured by suppliers in their pursuit of superior visibility. In the first essay I conduct an exploratory analysis to uncover the competitive dynamics faced by suppliers when competing in an algorithmically managed ecosystem. In particular, in the second essay I conceptualize two types of competitive repertoires that are dependent on their degree of co-specialization with the aggregator’s platform. By doing so I identify multiple pathways, which are orthogonal to traditional competitive action types, leading to superior performance when competing for visibility within a platform-based ecosystem. In the third essay, I investigate the role of ecosystem-specific experience and competitive repertoire carried out by suppliers when entering the ecosystem during the particular case of receiving an algorithmic boost. I assemble a unique dataset from the dominant food delivery aggregator in Europe. The results show that suppliers who gain higher levels of ecosystem-specific experience and carry out more aggressive competitive repertoires maximize their visibility. Yet, as demonstrated by the second essay, sustaining visibility over long periods of time remains challenging.
Rodriguez, Joaquin Alfredo, "Competing in the Algorithmic Economy: A Literature Review and Empirical Assessment" (2021). LSU Doctoral Dissertations. 5560.
Available for download on Thursday, May 25, 2028