Congratulations to Michael Weber, a former visiting student at CDE, who received the SAP Student Award for his thesis, “Highly Autonomous Consumer Buying Agents: Analyzing the Influence on Business Models” written as part of his coursework at Chair for Information Systems and Business Process Management at the Technical University of Munich and in cooperation with QUT’s Centre for the Digital Economy.
The SAP award is given to an inspiring work that has succeeded in expanding the theory in new, innovative, and practical ways.
Michael wrote his thesis under the supervision of Prof. Helmut Krcmar (TUM), Prof. Marek Kowalkiewicz (QUT), and Joerg Weking (TUM).
We are very proud of Michael’s achievement, and wish him all the best for his future career!
Below is the commendation delivered together with the award (translated from German):
The award is given to an inspiring work that has succeeded in skillfully expanding the theory in a new, innovative practical ways. Mr Weber’s master’s thesis can be classified in the research field of IT-driven business models. In practice, the work examines how autonomous agents are changing business models in the consumer business. In other words, how do companies have to react when a customer is no longer a person, but an algorithm? How do autonomous agents change business models?
In doing so, Mr Weber focused on the business benefits, such as the business models of autonomous agents. The aim of the master’s thesis was to find business model patterns that reflect the changes caused by autonomous buying agents in the consumer business. For this purpose, Mr Weber first analysed the literature on digital business models, autonomous buying agents and their areas of application in order to create a framework for the work.
The subsequent practical part of the work analyzed 23 case studies of successful autonomous buying agents. Examples are shopping with Amazon Alexa or a printer that automatically reorders ink cartridges. Mr Weber then cleverly combined an inductive approach with the case studies and deductive approach from theory to create a taxonomy of business models for autonomous buying agents. This taxonomy served as the basis for deriving three clusters and eight sub-clusters of common business model patterns for autonomous buying agents. The business model taxonomy and business model patterns show what companies have to adjust to when the customer is not a person but an algorithm or an autonomous agent.
The results also have important implications for future research. The classifications of business models for autonomous buying agents can be used as constructs in future theories. For example, it can be examined which pattern is successful in which context. Thus, the work not only shows clear recommendations for action but also contributes to a basis for future research on autonomous buying agents.
Parts of the master’s thesis have already been presented at an Australian conference for service research (SERVSIG 2020) and at the German conference for business informatics (WI 2020) and successfully published in two articles. After successfully completing his studies at the chair of business informatics of Prof. Krcmar, Mr Weber decided to start as a research assistant and doctoral candidate. Here he would like to further investigate how businesses can successfully implement artificial intelligence and apply it in new business models.