When Algorithms Go Shopping: Analyzing Business Models for Highly Autonomous Consumer Buying Agents

Abstract

Consumer buying agents (CBAs) are software programs that automate tasks in the consumer buying process (e.g., product search and evaluation). Recently, CBAs have the ability to nearly automate the whole buying process, executing transactions with only minimal human involvement. With the rise of such highly autonomous CBAs, updates to business models (BM) of involved parties are expected (e.g., adding a sales channel and increasing customer value). However, our understanding of BMs for highly autonomous CBAs remains limited. In this work we aim to close this gap. We investigate 23 cases and develop a BM taxonomy for highly autonomous CBAs. We further encode these cases into the taxonomy and derive BM patterns. Our work contributes to research by setting a foundation for the conceptual understanding of BMs for highly autonomous CBAs. Practitioners can use our taxonomy and patterns for strategic guidance and to support BM innovation.