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Alok Gupta, Wolfgang Ketter, Eric van Heck, and Meditya Wasesa. Real-Time Support for Auctioneers to Determine Optimal Clock Start for Multi-Unit Sequential Dutch Auctions. In Eighth Workshop on e-Business, pp. 1–6, AIS, December 2009.
Enterprises continuously seek decision support tools that can help automate and codify business decisions. This is particularly true in the business of consumer electronics manufacturing where components are often interchangeable and several manufacturers can supply the same component over the life of a product. In this kind of dynamic environment, businesses are faced with the choice of signing long-term (possibly quite risky) contracts or of waiting to procure necessary components on the spot market (where availability may be uncertain). Having analytical tools to analyze previous and forecast future market conditions is invaluable. We analyze a supply chain scenario from an economic perspective that involves both component procurement and sales uncertainties. The data we analyze comes from a multi-agent supply chain management simulation environment (TAC SCM) which simulates a one-year product life-cycle. The availability of simulation logs allows us access to a rich set of data which includes the requests and actions taken by all participants in the market. This rich informational access enables us to calculate supply and demand curves, examine market efficiency, and see how specific strategic behaviors of the competing agents are reflected in market dynamics.
@InProceedings{Gupta09WeB,
author = {Alok Gupta and Wolfgang Ketter and Eric van Heck and Meditya Wasesa},
title = {Real-Time Support for Auctioneers to Determine Optimal Clock Start
for Multi-Unit Sequential Dutch Auctions},
booktitle = {Eighth Workshop on e-Business},
pages = {1--6},
year = {2009},
month = {December},
abstract = {Enterprises continuously seek decision support tools
that can help automate and codify business decisions. This is
particularly true in the business of consumer electronics
manufacturing where components are often interchangeable and
several manufacturers can supply the same component over the life
of a product. In this kind of dynamic environment, businesses are
faced with the choice of signing long-term (possibly quite risky)
contracts or of waiting to procure necessary components on the
spot market (where availability may be uncertain). Having
analytical tools to analyze previous and forecast future market
conditions is invaluable. We analyze a supply chain scenario from
an economic perspective that involves both component procurement
and sales uncertainties. The data we analyze comes from a
multi-agent supply chain management simulation environment (TAC
SCM) which simulates a one-year product life-cycle. The
availability of simulation logs allows us access to a rich set of
data which includes the requests and actions taken by all
participants in the market. This rich informational access enables
us to calculate supply and demand curves, examine market
efficiency, and see how specific strategic behaviors of the
competing agents are reflected in market dynamics.},
organization = {AIS},
publisher = {AIS},
bib2html_pubtype = {Refereed Workshop/Symposium},
bib2html_rescat = {Trading Agents: Supply-Chain Management},
}
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