Queueing Network Modeling and Lead Time Compression of Electronic Procurement

Raju, CVL and Narahari, Y (2002) Queueing Network Modeling and Lead Time Compression of Electronic Procurement. In: IEEE International Conference on Robotics and Automation, 2002. ICRA '02, 11-15 May, Washington, Vol.1, 763-768.

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Abstract

Procurement, i.e., the process of obtaining materials or services and managing their inflow into organizations, is a critical process in supply chain management. Internet technologies offer attractive opportunities to reduce purchasing costs while increasing the speed and efficiency of the procurement process through seamless network integration and automated execution of key tasks. This paper attempts to model e-procurement from a lead time perspective, to capture the effects of Internet technologies on the procurement lead time. The model we develop is a multiclass queueing network called a probabilistic reentrant line. The model captures several important facets of an e-procurement process, such as use of electronic RFQ (re-quest for quotation) in systematic sourcing, use of Internet auctions in spot purchasing, contention for procurement resources, randomness in execution times of procurement tasks, and concurrent execution of multiple procurement activities. The analysis of the queueing model suggests that end-to-end lead times in e-procurement can be compressed in ingenious ways using standard queueing theoretic techniques.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright 1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords:	Procurement process, mean cycle time;e-procurement;Multiclass queueing networks;Reentrant line
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	03 Feb 2006
Last Modified:	19 Sep 2010 04:23
URI:	http://eprints.iisc.ac.in/id/eprint/5262

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