Master 2020/2021

Management of Logistic Risks in Supply Chains

Type: Elective course (Strategic Management of Logistics and Supply Chains in the Digital Economy)

Area of studies: Management

Delivered by: Department of Operations Management and Logistics

Where: Graduate School of Business

When: 1 year, 4 module

Mode of studies: offline

Instructors: Denis Gusev

Master’s programme: Стратегическое управление логистикой и цепями поставок в цифровой экономике

Language: English

ECTS credits: 4

Contact hours: 32

Course Syllabus

Abstract

The main purpose of the discipline is to teach students the methodology and methods of construc-tion and the practical application of the models representing the economic risks, methods of analysis and comparison of alternatives in terms of risk, economic risk management methods, using traditional and modern technologies in the format of the supply chain. Discipline is read for Master's student in the first year of the specialty. The course program in-cludes conducting seminars. Topics of the studies are given in the relevant thematic terms. In these classes students practice skills in the use of risk management techniques based on the knowledge of the relevant theoretical material. The program provides a student's control work. Independent work of the student also includes: learning the theoretical material at a level sufficient for understanding the topics and sections of the course, and to participatie in the seminars, which will consolidate the skills of risk management tech-niques.

Learning Objectives

• The main purpose of the discipline is to teach students the methodology and methods of construc-tion and the practical application of the models representing the economic risks, methods of analysis and comparison of alternatives in terms of risk, economic risk management methods, using traditional and modern technologies in the format of the supply chain.
• Based on current requirements needed to consider the logistics risks in the supply chain as a result of the discipline, the students must: - be able to freely navigate in applied research on the analysis and management of risks in the supply chain; - know and use in their future activities of the appropriate methods and models in the format of the problems of analysis and economic risk management in supply chains, including – • methods of risk analysis and management based on the classical approach of the theory of risk; • methods of risk analysis and management based on the concept of utility; • methods of analysis and risk management through the use of a decision tree; • methods of market risk management; • methods of redistribution of logistics risks; • methods of logistics risks based on their diversification; • methods of logistics security risks. - understand of the assessment of the adequacy of the models - to establish the possibility of their application, to correctly interpret the findings of these in terms of the modeling tasks of logistics systems.

Expected Learning Outcomes

• Ability to compar and select the alternatives in terms of risk to the supply chain
• Ability to use method of decision tree for risk management in supply chains
• Ability to use methods and models of risk redistribution to the supply chain
• Ability to use methods and models of risk diversification in the supply chain
• Ability to use risk management of financial leverage in the supply chain

Course Contents

• Topic 1 Selecting the best solutions in terms of risk in supply chain management Topic 1.1 Comparing the alternatives in terms of risk to the supply chain
  Risk as an economic category. Model representation of risk: pure risks; soft and hard risks when analyzing supply chains; commercial risks. The concept of "income-risk", the concept of "yield-risk." The need for other approaches to the evaluation and assessment of risks in the supply chain: the format of the concept of expected utility. Interpretation and application in relation to the economic problems of risk management in the supply chain. The problem of comparing alternatives. The concept of the unit of level lines in the format of the classical approach of risk theory. The formal definition of the level lines. Features comparison of risky alternatives in the space of "Income-risk"; specificity of their comparisons in space "Yield-Risk." Accounting for decision-makers to the risk of the relationship: the notion of equivalence of curves and indifference curves. Formalization of procedures for the comparison of alternatives in terms of risk. Parametric representation of the level lines. Features of the level lines that are due to the risk attitude of the decision maker. The specifics of the decision-making in risk manage-ment in the spaces "Income-risk" and "risk-yield". Classification of DM with the attitude to risk. The ability to compare alternatives in the format of the concept of utility. The concept of the utility function. The main properties of the utility function and the probabilistic interpretation. At-tributes comparison of alternatives, determines convexity / concavity of the utility function. Fea-tures and specificity of the experimental measurement of utility in the format of risk manage-ment models for supply chains.
• Topic 1.2 Method of decision tree for risk management in supply chains
  The general scheme of the method of decision tree. Features of its implementation for the tasks of risk management in supply chains, formulated in an expanded form: their formalization based on the decision tree. Procedure for constructing decision tree. Procedure for assigning parameters of the decision tree. Analysis on the basis of a decision tree: convolution procedure and blocking. Choosing the best solutions in the space of "Income-Risk" in the modeling of the supply chain. EVC - cri-teria (expected value). Feature of his level lines and use format. MVC - criteria (significant variance): the possibility of taking into account the specifics of the decision-maker attitude to risk. The concept of "risk-free equivalent income" in the format of the final result in the optimization of alternative supply chain. The possibility of other approaches to the formalization of criteria / selection functions in the optimization of solutions in terms of risk to the supply chain. Solutions in the format of the concept of utility. EUC-criteria (expected utility). Risk premium and the "risk-free equivalent income" in the format of EUC-criterion. In-terpretation and application of optimization problems in supply chains. Features of the implementation procedures of the convolution in the various selection criteria or opti-mization decisions under risk: EVC-test format; MVC-test format; format of EUC-criterion. The specificity of these procedures for terminal fragments of the decision tree. Features such procedures for the inter-mediate fragments. Choosing the best decisions based on the relationship to the risk of DM. Accountability of additional features / options offered by the market, for modifications of the models to optimize the supply chain in terms of risk-based decision tree.
• Topic 2 Methods of risks dissipation in supply chain management Topic 2.1 Methods and models of risk redistribution to the supply chain
  Possibility of redistribution of risk in the optimization model of supply chain management. Redistribu-tion of risk based on changes in contractual conditions of supply. Redistribution of risk based on changes in ownership interests in the related logistics processes, in particular, taking into account the involvement of logistics intermediaries. Formalization of optimization solutions based on methods of risk transfer. To use the machine level lines and the indifference curve in the space of "Income-Risk" or space "Yield-Risk" for finding optimal solutions. Model of risk redistribution in a format specific business proposals in the supply chain: 1) model to give rise to an unacceptable risk; 2) the model result of the absence of adequate finan-cial resources. Model of risk redistribution problems as a special case of models of risk diversification in the supply chain.
• Topic 2.2 Methods and models of risk diversification in the supply chain
  The concept of risk diversification on a content / verbal level. The nature and attributes of the proce-dures diversification of economic risks. Removable and systematic risks. Portfolio strategies and their for-mal representation. The most basic model of risk diversification in the format of two business proposals. Accounting perfect negative correlation in the format of such models of diversification of risk: the risk-free opportunity to implement appropriate risk proposals; graphic interpretation in space "Income-Risk" and in the space of "yield-risk." Accounting perfect positive correlation in the format of such models of diversifi-cation of risk: the risk-free features of the implementation of risky proposals, graphic interpretation. Mod-els of risk diversification, suggesting that one of the proposals of business is risk-free; specificity of their graphical representation in the space of "Income-Risk" and in the space of "yield-risk." Generalization of models of risk diversification, involving an arbitrary number of assay format offers business. Features of optimal portfolio strategies: the effective boundary of admissible portfolios. The optimal market portfolio. The capital market line (CML - capital market line) and submitted it possible compromise between the in-crement of risk and yield increment. Market price of risk. Line of the securities market. The concept of the coefficient of "beta". Properties factor "beta". Interpretation of the coefficient of the "beta" as a measure of risk. The possibility of optimizing decisions under risk based on the use of the coefficient of "beta".
• Topic 3 Risk management of financial leverage in the supply chain
  The concept of the effect of financial leverage on a content / verbal level. Formalization of the concept of risk of financial leverage: the specificity of the decisions in the format criteria MVC; singularities of solutions in the format criteria MVC. Accounting model the cost of borrowing in the analysis of the ef-fect of financial leverage. Selecting shoulder leverage at financial risk management models leverage optimization problems in supply chains.

Assessment Elements

• Activity (Work on seminars, аnalitical note and other homeworks)
  Analitic note (as homework) is needed. Other two possible homeworks are voluntary
• Exam
  The exam consists of a written part (1 acad. hour) and an oral part (they are held on the same day). When giving the final mark for the exam, the marks of these two indicated parts / stages are taken into account with equal weights (for the corresponding marks, a scale in the form of percentages will be used). At the same time, to encourage more active work, both in the study of the discipline and work related to the possible use of the presented materials in the format of scientific research, the following is practiced. The partly oral stage of the exam can be credited before its start (as a result of the learning process correlated with the answers to special questions, as well as with specially performed tasks or developments close to scientific ones, for example, that caused a student to speak at a scientific conference or participate in a scientific competition. student papers, etc.). The mandatory attributes of such procedures related to the partial credit of the oral part / stage of the exam include the fulfillment of the following conditions. 1) They must be open, i.e. not only a specific student is notified of this, but an announcement is made to the entire group of students or the entire stream. 2) They must be specific, i.e. in this case, it will certainly be specified which part related to the oral stage of the exam will be credited; 3) They should be accessible to every student wishing to use this format of the teaching procedure. Partial credit for the oral stage of the exam will only affect the assessment of that stage. At the same time, partial credit for the oral stage of the exam is possible provided that the student is present at the written part, and also, in addition, in the absence of violations during the written part of the exam (in accordance with the regulations of the HSE)

Interim Assessment

• Interim assessment (4 module)
  For the period of distance learning (session - 4 module) the following changes are made. 1) The exam is conducted in writing based on the developed test questions and tasks through the StartExam system (the volume of such questions will be calculated for a duration of 2 academic hours). 2) The previously noted possibility of partial reading of the stage of the oral exam before it begins will now be implemented differently (since there will be no specified oral stage of the exam). Namely, the special tasks performed in the learning process will be taken into account on the basis of additional bonuses introduced by the student (ai, i = 1, 2). In this case, the corresponding bonuses will be added to the resulting indicator reflecting the score received on the test questions of the exam. The conclusion of the resulting grade for the discipline will be implemented according to the following non-linear formula: Result = min {10; 0.4 * Activity + 0.6 * (mark for examination testing + a1 + a2)}. Activity - the arithmetic mean for work in the classroom and for homework; ai - received bonuses, and i = 0, if the i-th special. the task is not credited; ai = 0.75, if such an assignment is partially credited; ai = 1.5, if it is counted in full, i = 1, 2. The exam is conducted in writing on the StartExam platform without proctoring

Bibliography

Recommended Core Bibliography

• Elements of financial risk management, Christoffersen, P. F., 2003

Recommended Additional Bibliography

• Financial institutions management : a risk management approach, Saunders, A., 2018
• Heiko A., Vennemann C. R., & Darkow I. L. (2010). Corporate foresight and innovation management: A portfolio-approach in evaluating organizational development. Futures, 42(4), 380-393.
• Minh-Thu Tran-Nguyen, Le-Diem Bui, & Thanh-Nghi Do. (2019). Decision trees using local support vector regression models for large datasets. Journal of Information and Telecommunication, (0), 1. https://doi.org/10.1080/24751839.2019.1686682
• Rachev, S. T., Fabozzi, F. J., & Stoyanov, S. V. (2008). Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization : The Ideal Risk, Uncertainty, and Performance Measures. Hoboken, N.J.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=219812
• Smirnov Alexander D. (2018). Stochastic Logistic Model of the Global Financial Leverage. The B.E. Journal of Theoretical Economics, (1), 1. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.bpj.bejtec.v18y2018i1p20n3