Adaptive Value Networks

  • Datta S
  • Betts B
  • Dinning M
  • et al.
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If a typhoon in the South China Sea impacts the shipment and delivery of memory chips to an assembly plant in Mexico City, you can count on the ripple effect to impact financial service providers, manufacturers and suppliers, shippers in charge of logistics and of course, the end-consumer. Can we plan to reduce the risk arising from such uncertainties? Can businesses (semiconductor plants, banks, logistics providers) cooperate to minimize uncertainties? Conventional wisdom states that uncertainties are equivalent to accidents and hence by nature remain unpredictable. However, application of tools and technologies based on emerging standards may partially disprove such wisdom. Focus on demand management may be the guiding light for supply chain practitioners. Can we collapse information asymmetries (between manufacturers and their lending institutions, for example) and add far more value to networks or demand webs? Real-time operational adaptability is key, especially in fast ‘clockspeed’ industries. Confluence of emerging tools, technologies and standards are required to converge to catalyze the evolution of such adaptable enterprise. Can real-time distributed data, in-network processing, Agent-based autonomy, taken together, tame the Bullwhip Effect? Can t he (semantic) web catalyze the “Nash Equilibrium” of people (games) and information (theory) in our quest for real time “predictive” decision support systems? We will explore a few of these issues and how they may coalesce to enable the adaptive value network of the future.




Datta, S., Betts, B., Dinning, M., Erhun, F., Gibbs, T., Keskinocak, P., … Samuels, M. (2006). Adaptive Value Networks. In Evolution of Supply Chain Management (pp. 3–67). Kluwer Academic Publishers.

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