Date of Publication

2004

Document Type

Master's Thesis

Degree Name

Master of Science in Industrial Engineering

Subject Categories

Industrial Engineering

College

Gokongwei College of Engineering

Department/Unit

Industrial Engineering

Thesis Adviser

Dennis T. Beng Hui

Defense Panel Chair

Rosemary R. Seva

Defense Panel Member

Dennis E. Cruz
Eric A. Siy

Abstract/Summary

Consumer buying decision is an important element of a company's effort to maximize market potential. The background of the study is a given scenario that a vendor-managed inventory (VMI) model is used to operate the inventory logistics of consigned products over a retail chain store network of identical size and characteristic. The study primarily introduces the use of a decision support system (DSS) method in coming up with a tool to improve the operations of the store network, through quantitative reports that guide the decision maker. A key issue discussed in this study is the use of probabilistic demand behavior of a consumer, based on the demographic segmentation of consumers in the respective area of coverage of individual retail chain stores. In completion of the study, two major DSS-VMI guidelines are derived and implemented. The first set are guidelines on how to device consumption plans for initial inventory distribution And the second set are guidelines for periodically evaluating in terms of a financial perspective the inventory status for the event of inventory reallocation, wherein a monthly scheme of evaluation was tested to be more effective based on the two sample companies used in the study. Finally, a detailed representation of a VMI system on leaseback or consigned scenario and additional information on consumer behavior, DSS, operations research, statistics and simulation are discussed in this study.

Abstract Format

html

Language

English

Format

Electronic

Accession Number

CDTG003810

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer optical disc ; 4 3/4 in.

Keywords

Decision support systems; Industrial engineering; Production management; Inventory control; Chain stores

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