Skip to main content

STREAM: Stability-based Realization of Economic Performance and Management

  • Chapter
Adaptive Supply Chain Management
  • 2787 Accesses

Abstract

In this chapter we develop the conceptual basics of the approach to balancing SC economic performance and stability as the primary objective in SC planning and optimization. The developed concept is named STREAM (Stability-based Realization of Economic Performance and Management). The concept STREAM, as the name implies, is based on the idea that the SC’s potential economic performance will be realized through the SC’s stability. The conceptual model of STREAM is based on conceptualizing the subject domain from uniform SCM and system-cybernetic positions by means of the interconnected considerations of (1) control and perturbation influences in SCs and (2) verbally describable properties of an SC as a business process (for example, security and flexibility) and theoretically attributed properties of an SC as a complex system (for example, adaptability and resilience). Finally, general algorithms of SC (re)planning under uncertainty are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Ashby WR (1956) An Introduction to Cybernetics. Chapman & Hall, London

    MATH  Google Scholar 

  • Casti JL (1979) Connectivity, complexity and catastrophe in large-scale systems. Wiley-Interscience, New York and London

    MATH  Google Scholar 

  • Cheng TCE, Wu YN (2006) A multiproduct, multicriterion supply-demand network equilibrium model. Oper Res 54(3):544–554

    Article  MATH  MathSciNet  Google Scholar 

  • Cobb JD (1984) Controllability, observability and duality in singular systems. IEEE Trans Automat Contr 29:1076–1082

    Article  MathSciNet  Google Scholar 

  • Daganzo CF (2004) On the stability of supply chains. Oper Res 52(6):909–921

    Article  MATH  Google Scholar 

  • Dashkovskiy S, Rüffer BS, Wirth FR (2005) A small-gain type stability criterion for large scale networks of ISS systems. Decision and Control and European Control Conference CDC-ECC, Seville:5633–5638

    Google Scholar 

  • Disney SM, Towill DR (2002) A discrete linear control theory model to determine the dynamic stability of vendor managed inventory supply chains. Int J Prod Res 40(1):179–204

    Article  MATH  Google Scholar 

  • Disney SM, Towill DR, Warburton RDH (2006) On the equivalence of control theoretic, differential, and difference equation approaches to modeling supply chains. Int J Prod Econ 101:194–208

    Article  Google Scholar 

  • Glickman TS, White SC (2006) Security, visibility, and resilience: The keys to mitigating supply chain vulnerabilities. Int J Logist Syst Manag 2(2):107–119

    Google Scholar 

  • Ivanov D (2009) Adaptive aligning of planning decisions on supply chain strategy, design, tactics, and operations. Int J Prod Res, in press

    Google Scholar 

  • Ivanov D, Sokolov B, Kaeschel J (2010) A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations. Eur J Oper Res 200:409–420.

    Article  MATH  Google Scholar 

  • Kaneko O, Misaki T, Fujii T (2006) On controllability of discrete event systems in a behavioral framework. J Comput Syst Sci 45(4):513–517

    Article  MathSciNet  Google Scholar 

  • Kleindorfer PR, Saad GH (2005) Managing disruption risks in supply chains. Prod Oper Manag 14(1):53–68

    Google Scholar 

  • Koumboulis FN, Mertzios BG (1999) On Kalman's controllability and observability criteria for singular systems. Circ Syst Signal Process 18(3):269–290

    Article  MATH  MathSciNet  Google Scholar 

  • Lalwani CS, Disney S, Towill DR (2006) Controllable, observable and stable state space representations of a generalized order-up-to policy. Int J Prod Econ 101:172–184

    Article  Google Scholar 

  • Lyapunov AM (1966) Stability of motion. Academic Press, New-York and London

    MATH  Google Scholar 

  • Ogata K (1997) Modern control engineering. Prentice Hall International, London

    Google Scholar 

  • Ostrovsky M (2008) Stability in supply chain networks. Prod Oper Manag 98(3):897–923

    MathSciNet  Google Scholar 

  • Polderman JW, Willems JC (1998) Introduction to mathematical systems theory: a behavioral approach. Springer, New York

    Google Scholar 

  • Ponomarov SY, Holcomb MC (2009) Understanding the concept of supply chain resilience. Int J Logist Manag 20(1):124–143

    Article  Google Scholar 

  • Popov VM (1973) Hyperstability of control systems. Springer, Berlin and New York

    MATH  Google Scholar 

  • Prigogine I, Nicolis G (1977) Self-Organization in Non-Equilibrium Systems. John Wiley and Sons, New York

    Google Scholar 

  • Quyang Y (2007) The effect of information sharing on supply chain stability and the bullwhip effect. Eur J Oper Res 182:1107–1121

    Article  Google Scholar 

  • Rice JB, Caniato F (2003) Building a secure and resilient supply network. Supply Chain Management Review, September/October:22–30

    Google Scholar 

  • Riddalls CE, Bennett S (2002) The stability of supply chains. Int J Prod Res 40(2):459–475

    Article  MATH  Google Scholar 

  • Ritchie B, Brindley C (2007) An emergent framework for supply chain risk management and performance measurement. J Oper Res Soc 58:1398–1411

    Article  MATH  Google Scholar 

  • Sheffi Y (2005) The resilient enterprise. MIT Press, Massachusetts

    Google Scholar 

  • Son Y-J, Venkateswaran J (2007) Hierarchical supply chain planning architecture for integrated analysis of stability and performance. Int J Simulat Process Model 3(3):153–169

    Article  Google Scholar 

  • Stefani RT, Shahian B, Savant CJ, Hostetter GH (2002) Design of feedback control systems. Oxford University Press, Oxford

    Google Scholar 

  • Sterman JD (2000) Business dynamics: systems thinking and modeling for complex world. McGraw-Hill/Irwin, New Jersey

    Google Scholar 

  • Van de Vonder S, Demeulemeester E and Herroelen W (2007) A classification of predictivereactive project scheduling procedures. J Sched 10(3):195–207

    Article  MATH  MathSciNet  Google Scholar 

  • Warburton RDH, Disney SM, Towill DR, Hodgson JPE (2004) Further insights into "The stability of supply chains". Int J Prod Res 42(3):639–648

    Article  MATH  Google Scholar 

  • Yang J, Wang J, Wong CWY, Lai KH (2008) Relational stability and alliance performance in supply chain. Omega 36:600–608

    Article  Google Scholar 

Download references

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag London Limited

About this chapter

Cite this chapter

(2010). STREAM: Stability-based Realization of Economic Performance and Management. In: Adaptive Supply Chain Management. Springer, London. https://doi.org/10.1007/978-1-84882-952-7_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-84882-952-7_7

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-951-0

  • Online ISBN: 978-1-84882-952-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics