Supply Chain Management

Companion textbook to the lecture

Course reader accompanying the lecture Supply Chain Management, winter semester 2026/27
Author

Prof. Dr. Matthias Kalverkamp & Prof. Dr. Thomas Kirschstein

Published

September 30, 2026

Preface

This textbook accompanies the lecture Supply Chain Management (SCM) and expands on the content of the lecture slides (slides/) in detailed, text-based form. It is intended as a course reader for self-study: while the slides serve as a visual aid to memory in the lecture, this book explains the same models, methods and case examples in full sentences, with derived formulas and runnable, commented R code.

This course reader is primarily AI-generated and requires further correction. Any errors can be reported to thomas.kirschstein@hs-rm.de.

Structure of the book

The chapters follow the lecture units, which are divided into three blocks: fundamentals of supply chain management, strategic design of supply chains and uncertainty and risk management in supply chains.

  1. Introduction and basic concepts of supply chain management — What is a supply chain? Flows, actors, structures, supply chain profit and double marginalisation.
  2. Value creation, strategic manufacturing and strategic fit — Value creation process, decoupling point, make-or-buy, implied uncertainty, strategic fit.
  3. Objectives, trade-offs and logistics costs — The SCM system of objectives, the tetrahedron of trade-offs, cost types and the introduction of the case study SushiFresh GmbH.
  4. Sustainability in supply chain management — In-depth treatment of the sustainability content from unit 3: environmental strategic fit, environmental SCM strategies, circular economy and circular supply chains.
  5. Facility location planning I — Qualitative methods (scoring model, AHP) and continuous methods (centre-of-gravity method, Weiszfeld algorithm).
  6. Facility location planning II — Discrete network planning models: transportation problem, warehouse location problem, heuristics and exact methods.
  7. Uncertainty in supply chains and pooling — Demand uncertainty, capacity and inventory pooling, safety stocks, the square-root law of risk pooling.
  8. The newsvendor model — Optimal order quantities under uncertainty, critical ratio, service level.
  9. The bullwhip effect and the Beer Game — Amplification of demand fluctuations along the chain, causes and countermeasures.

From Chapter 3  Objectives, Trade-offs and Logistics Costs onwards, a continuous case example accompanies the course reader: the fictitious SushiFresh GmbH produces fresh sushi boxes for supermarkets in the Rhine-Main area. As in the lecture, it is used to work through location choice, network design, safety stocks, production quantities and the bullwhip effect.

Each chapter follows the same structure:

  • Learning objectives at the beginning, so that it is clear which competences are to be acquired.
  • Conceptual explanations with examples from practice.
  • In-depth theory boxes (shaded purple), which present theoretical background, derivations and links to the academic literature in more detail than the slides.
  • Case study boxes (shaded yellow) on SushiFresh GmbH.
  • Mathematical derivations in easy-to-follow steps.
  • Commented R code that calculates and visualises the models directly — every code block is runnable and commented so that even students with no prior experience of R can follow the process. Alongside the subject content, basic R concepts (vectors, functions, data frames, the tidyverse, pipes |>, visualisation with ggplot2) are introduced step by step.
  • Review questions at the end of each chapter for self-assessment.

Prerequisites

  • Fundamentals of linear algebra and probability theory.
  • No prior knowledge of R required — the basics are introduced in the book.
  • Fundamentals of microeconomics are helpful but not essential.

Software

All R code in this book uses the following packages:

install.packages(c(
  "tidyverse",       # data manipulation (dplyr, tidyr) and visualisation (ggplot2)
  "plotly",          # interactive graphics
  "knitr",           # embedding R code in Quarto documents
  "kableExtra",      # formatted tables
  "sf",              # processing geodata
  "leaflet",         # interactive maps
  "ompr", "ompr.roi", "ROI.plugin.glpk",  # algebraic optimisation models (MILP)
  "scales"           # axis and number formatting in ggplot2
))

All example functions (e.g. for the centre-of-gravity method, the newsvendor model or the add/drop heuristic) are also bundled in R/scm_functions.R and are referenced at the appropriate points in the book.