Seminar – How Machine Learning Can Enhance Theory-building

Dr Florian Ellsaesser, Frankfurt School of Finance and Management and Professor Eric Tsang, University of Texas at Dallas

A major reason for the success of machine learning has been its ability to represent two aspects of social phenomena that are resistant to representation by traditional statistics: hidden generative structures and path dependence. We use organisational routines, much studied in management, as a site to demonstrate this ability and, accordingly, the potential for the algorithms used in machine learning to advance management theory.

Speaker bio

Eric W.K. Tsang is the Dallas World Salute Distinguished Professor at the Jindal School of Management, University of Texas at Dallas, and is also a fellow of the Academy of International Business. He received his PhD from Cambridge Judge Business School. Before joining academia, he was a corporate banker at HSBC in Hong Kong. His main research interests include organisational learning, strategic alliances, corporate social responsibility, and philosophical analysis of methodological issues. He has published in leading business journals, such as Academy of Management Journal, Academy of Management Review, Journal of International Business Studies, Marketing Science, MIS Quarterly, and Strategic Management Journal.

Dr Florian Ellsaesser is Assistant Professor at the Frankfurt School of Finance and Management. He teaches technical classes on deep learning and Nnatural language processing in the Master in Data Science. He completed his undergraduate degree in Economics and Philosophy in the UK. His PhD at the University of Cambridge was a comparison of three approaches to explanation in management research, focusing on causal inference and the construction of explanatory frameworks. For one of his research papers Florian received the Oxford, Cambridge, Warwick Interdoctoral Conference Best PhD Paper award. During his PhD he began to study Mathematics and has continued ever since. After his PhD Florian first worked as a strategy consultant and then as a project manager at McKinsey & Company. He then moved into the entrepreneurial world and was involved in founding a number of technology startups. He also published on causal inference and machine learning in the Academy of Management Review and the Strategic Management Journal. Florian’s main research interest lies in decision making under uncertainty and the application of machine learning to managerial and organisational problems.