Supply Chain Finance (SCF) enables buying firms and their suppliers to jointly optimize their cash flows. It comprises a third party, the so called SCF provider, which facilitates attractive funding to suppliers for financing payment terms. SCF always involves a digital platform to facilitate efficient onboarding of suppliers and efficient transacting. As SCF is beneficial for all involved parties – buyers, suppliers, SCF providers – it is frequently called a win-win-win solution.

The vast benefits of SCF raise a central research question: What are the true benefits of SCF and why are not all firms using SCF to the maximum extent? 

In our research, we examine SCF from multiple perspectives. We find that, in part, SCF can be understood from an innovation adoption perspective as it is new to many firms. We further find that a combination of rational efficiency motive drivers and legitimacy motive drivers explains how quickly suppliers adopt SCF. Put in simpler terms, our results indicate how buying firm can make their suppliers adopt SCF faster. In more recent studies, we examine a data set to better understand how SCF benefits are split between different actors. There are multiple ways through which suppliers can benefit from SCF which we also investigate.

Firms increasingly depend on their supply chain to efficiently provide goods and services at the right time, at the right place and in the right quantity. While there are many upsides in leveraging the unique skills and capabilities of suppliers, there are also some risks. What if supply gets disrupted? What if a supplier faces manufacturing problems? Supply chain resilience is concerned with those questions and managing potential risks pro-actively, that is, before they impact the flow of goods.

In our research, we examine how supply chain glitches (e.g., disruptions or delays in the flow of goods) can impact the value of a firm as measured through stock prices and abnormal returns. We further investigate how Twitter moderates this relationship and find that firms tend to suffer more from supply chain glitches if those lead to a stronger and more negative reaction in Twitter.

Taking a slightly different focus, we also study the impact of supplier default risks on sourcing and pricing decisions of a manufacturing firm. Using game theory, we study strategies for manufacturing firms to maintain long-term competition through a forward looking supplier selection strategy.

Digital transformation has two components: technology and management. Technology is about how we can use hardware and software to support and automate tasks. Management is more about how this affects processes, workers, and managers and about setting the right incentive to maximize the impact of this digitalizing. We are fascinated by new, digital technology and the inherent opportunities, and we contribute research from a managerial perspective.

For instance, we examine questions related to the use of augmented reality in production settings by exploring not only the benefits but also the downsides. We further conduct experiments with virtual reality and examine how it impacts our way of learning, understanding, and memorizing.

A standard assumption in the context of supply chain and operations management is that people are risk neutral and seek to maximize their income and the profits of the firms the work for. To some extent, this assumption works fairly well – after all, most workers and managers are interested in the well-being of their firm.

But workers and managers often follow slightly different objectives; they do not always maximize profits primarily (some are risk averse, some are loss averse, some use heuristics, etc). In our research we examine some implications related to incentivization issues in supply chains. We further examine learning effects in the context of augmented reality in manufacturing ramp-up contexts.

Empirical methods always build on observations and data. In our research context, this relates typically to firms or supply chains. We use econometric approaches including hazard rate models, panel analysis, propensity score matching, and maximum likelihood estimation of structural models to analyze secondary data. Such data is typically not generated for the sole purpose of conducting research and thus provides more external validity.

While econometric approaches have the advantage of being close to reality, examining causal effects is always problematic (though not impossible). When research questions require testing causality, we leverage experiments, either in laboratory settings (which allow for high degrees of standardization and replicability) or in the field (which allow for higher external validity).

In several of our studies we use game theory to derive analytical insight. Using game theory, questions such as “what should a firm do?” or “how would other firms act, if they anticipated these strategies?” can be answered. Game theory uses the language of games (e.g., “game”, “player”, “actions”); but it is otherwise quite serious and quantitative. It often helps to answer questions about hypothetical situations where no data yet exists. For instance, should a buying firm that has the choice between two suppliers out of which one is under financial distress opt for the distressed or nondistressed supplier? What are the implications of either choice on future competition? In contrast to simulations, game theory typically helps to generate structural insight that only depends on structural assumptions, but not specific, numerical values.

Since 01/20

Technical University Munich: Assistant Professor (tenure track)

 

04/16 - 11/19

EBS Universität: Habilitation, mentor: Prof. Dr. Markus Kreutzer

 

04/16 - 12/19

EBS Universität: Juniorprofessor for Operations Management

 

06/13 - 03/16

EBS Universität: Postdoctoral Researcher

 

10/11 - 10/15

Fernuniversität Hagen: Bachelor of science in mathematics

 

01/10 - 05/13

EBS Universität: Doctorate, supervisor: Prof. Dr. Michael Henke

 

10/12 - 04/13

Carlson School of Management, University of Minnesota: Visiting scholar (ca. 6 months stay)

 

10/05 - 07/09

Universität Paderborn: Diploma in industrial engineering (B.Sc.+M.Sc. equivalent, 5 years program)

 

09/07 - 05/08

Dublin City University: Visiting student at DCU Business School

• International Journal of Operations & Production Management, best Reviewer Award, 2020
• PROECO Editorial Board – Annual Reviewer Award, 2020
• EBS Junior Research Award, 2017
• EBS Junior Research Award, 2016
• Decision Sciences Journal – Outstanding Reviewer, 2014
• ISCM Doctoral Student Award, 2013
• Emerald/EFMD Outstanding Doctoral Research Award: Logistics and SCM, 2013
• Faculty Award for Outstanding Study Performance, 2009

• Deutsche Forschungsgemeinschaft (DFG) Grant (Since 2022)
• DAAD Travel Grant (POMS Conference) (2019)
• Doctorate-scholarship: Studienstiftung des deutschen Volkes (“German National Academic Foundation”) (2010 – 2013)
• Study-scholarship: Studienstiftung des deutschen Volkes (“German National Academic Foundation”) (2005 – 2009)
• Friedrich Flick Förderstiftung (2007 – 2008)