Ijioui / Emmerich / Ceyp | Strategies and Tactics in Supply Chain Event Management | E-Book | sack.de
E-Book

E-Book, Englisch, 362 Seiten, eBook

Ijioui / Emmerich / Ceyp Strategies and Tactics in Supply Chain Event Management

E-Book, Englisch, 362 Seiten, eBook

ISBN: 978-3-540-73766-7
Verlag: Springer
Format: PDF
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)



This book gives unique insights into the Supply Chain Event Management (SCEM) of world-leading companies. Aims, methods, instruments as well as resources and budgets in SCEM are discussed. The book offers real case studies from Top 100 companies. The reader will gain a strong understanding of the way to deal with problems along the supply chain and how to avoid them. SCEM allows timelines to be met with decreased cost and risks.
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Zielgruppe


Professional/practitioner

Weitere Infos & Material


Conceptual Design and Case Studies of Supply Chain Event Management.- Transparency in Global Supply Chain Networks — Methods and Tools for Integrated Supply Chain Event Management.- Supply Chain Event Management in the Pharmaceutical Industry — Status and Outlook.- Event Based Process Performance Management.- Interfaces @ Supply Chain Event Management.- Proactive Event Management in the Supply Chain of Aircraft Spare Parts.- Supply Chain Event Management: Managing Risk by Creating Visibility.- Supply Chain Risk Management: A Neural Network Approach.- Performance Management in the Value Chain.- Supply Chain Event Management in the Retail Sector — Three Steps to Success.- Design, Implementation and Evaluation of a Performance Measurement System for Virtual Enterprises in the Aerospace Industry.- Usage and Promotion of Employee Potentials in Modern Production Systems.- Added Value by Outsourcing of SCEM Solutions: Background and Technical Basis.- Holistic and Pragmatic Approach on Proactive Supply Chain Event Management.- Supply Chain Event Management (SCEM): A Strategic Application of Business Process Management (BPM).- Supply Chain Event Management: Innovation in Logistics Services.- SCEM-System to Support the Development of Consumer Promotion.- Dynamic Models for Simulation and Optimization of Supply Networks.- Design of an Organisational Structure to Govern the Dynamic Behaviour of Aviation-oriented Orders with Multiple Priorities.- Focused Interviews.- SCEM at Telecommunications Service Providers — Useful or Superfluous?.- The Change of REFA Methods by Supply Chain Event Management Considering Globalisation.- Supply Chain Event Management by FORD of Europe.- Supply Chain Event Management in the Financial World.- A Personal Field Report.- Supply Chain Event Management & Strategic Networking.


Supply Chain Risk Management: A Neural Network Approach (p. 99-100)

Frank Teuteberg
E-Business and Information Systems & Research Center for Information Systems in Project and Innovation Networks (ISPRI),
Katharinenstraße 1, 49074 Osnabrück, Germany

Introduction

Effective supply chain risk management (Hallikas et al. 2002, Harland et al. 2003, Henke et al. 2006) requires the identification, assessment and monetization of risks and disruptions, as well as the determination of the probability of their occurrence and the development of alternative action plans in case of disruptions (cf. Zsidisin 2003, Zsidisin et al. 2004, Zsidisin et al. 2000, Vidal a. Goetschalckx, 2000). Companies traditionally use multiple sources for material procurement and/or hold safety stocks to avoid vulnerability. However, these strategies can negatively impact the supply chain performance, leading to higher purchase and logistics costs. The aim of this chapter is to illustrate how the implementation of the supply chain risk management concept can be improved by using a neural network approach.

The chapter is organized as follows: in the next section basic and theoretical concepts of supply chain risk management are presented. Section 3 outlines a framework for categorizing and analyzing risks in supply chains. In section 4, we present a neural network approach that can be applied to assess various risks in supply chains. In section 5 preliminary results of our neural network experiments are presented and discussed. In the final section some conclusions are drawn. We also provide recommendations for future research.

Supply Chain Risk Management – Theoretical Background

Since the mid-eighties the supply chain management concept has been discussed intensively in practice and within the scientific community.

However, besides enjoying successes, the supply chain management approach also faces new challenges (Barry 2004, Jung et al. 2004). The occurrence of new risks such as uncertain demand, the increasing vulnerability of supply chains due to trends such as globalization, saturation of markets or terrorist attacks have forced companies to establish new concepts for risk assessment. It is therefore necessary to define a "manageable" security/risk level which is ultimately a socalled trade-off between supply chain costs, security and performance (e.g. taking on responsibility in the case of disruptions in supply chains). Thus the supply chain management concept has to be enhanced by methods of complexity and risk management. Figure 1 illustrates the trade-off between supply chain costs and supply chain security.


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