Prof. Dr. Tobias Schoenherr
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Academic Career Length
22Years (2005-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications27 September 2011 in Supply Chain Management: An International Journal
Journal Article
RTRao Tummala
Rao Tummala
Tobias SchoenherrPurpose: The purpose of this paper is to propose a comprehensive and coherent approach for managing risks in supply chains.Design/methodology/approach: Building on Tummalaet al.'s Risk Management Process (RMP), this paper develops a structured and ready‐to‐use approach for managers to assess and manage risks in supply chains.Findings: Supply chain risks can be managed more effectively when applying the Supply Chain Risk Management Process (SCRMP). The structured approach can be divided into the phases of risk identification, risk measurement and risk assessment; risk evaluation, and risk mitigation and contingency plans; and risk control and monitoring via data management systems. Specific techniques for conducting this process are suggested.Originality/value: While supply chain risk management is an emerging and important topic in our dynamic and interconnected world, conceptual frameworks providing a clear meaning and normative guidance are scarce (Manuj and Mentzer, 2008). This paper presents such a framework, offering structure and decision support for managers.
9 September 2011 in Journal of Operations Management
Journal Article
Tobias SchoenherrMSMorgan Swink
Morgan Swink
15 February 2013 in International Journal of Production Research
Journal Article
CBConstantin Blome
Constantin BlomeTobias SchoenherrDRDaniel Rexhausen
Daniel Rexhausen
This paper investigates the fundamental building blocks of supply chain agility, which are conceptualised as supply- and demand-side competence. While the former refers to production and supply management related activities, the latter refers to distribution and demand management related activities. The model further assesses the influence of supply chain agility on operational performance, as well as its mediating role in the relationship between supply- and demand-side competence and performance. Within this framework, process compliance, i.e. how well supply chain management processes are internally executed by the firm's employees, is viewed as an enabler (moderator) on the relationship between supply chain competencies and supply chain agility. Theoretical substantiation is provided by the resource-based view of the firm augmented with the dynamic capabilities perspective. The model is tested with data from 121 supply chain management professionals. Implications for both academic theory development and supply chain and production management practice are provided.
28 February 2015 in Journal of Business Logistics
Journal Article
Tobias SchoenherrCSCheri Speier‐Pero
Cheri Speier‐Pero
1 November 2019 in International Journal of Production Research
Journal Article
VMV. K. Manupati
V. K. Manupati
Tobias SchoenherrMRM. Ramkumar
M. Ramkumar
SWStephan M. Wagner
Stephan M. WagnerSPSai Krishna Pabba
Sai Krishna PabbaRSR. Inder Raj Singh
R. Inder Raj Singh
Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike.
1 January 2014 in International Journal of Production Economics
Journal Article
CBConstantin Blome
Constantin BlomeTobias SchoenherrDEDominik Eckstein
Dominik Eckstein
About Me
Tobias Schoenherr is the Hoagland-Metzler Endowed Professor in Purchasing and Supply Management. Recently recognized to be among the Top 10 thoughts leaders worldwide in supply chain management research, he is an award-winning scholar and teacher focusing on the area of sourcing, with a particular interest in buyer-supplier relationships. He has served two terms as a Co-Editor-in-Chief for the International Journal of Operations and Production Management.
Professor Schoenherr holds a Ph.D. in Operations Management and Decision Sciences from Indiana University, Bloomington, from where he also obtained his B.Sc. and M.B. He also holds a Diplom-Betriebswirt (FH) from the European School of Business, Reutlingen University, Germany, and is an APICS Certified Supply Chain Professional (CSCP). Dr. Schoenherr has taught purchasing, operations and supply chain management courses, both graduate and undergraduate, at Michigan State University, Indiana University, Eastern Michigan University, Rotterdam School of Management at Erasmus University (The Netherlands), Yonsei University (South Korea), the International Graduate Business School in Zagreb (Croatia), and the Central European University, Budapest (Hungary).
Professor Schoenherr’s work has appeared in more than 75 peer-reviewed publications, including Management Science, the Journal of Marketing Research, the Journal of Operations Management, Production and Operations Management, Decision Sciences, and others.
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