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Just‐in‐time Functional Model Empirical Test and Validation

Just‐in‐time Functional Model Empirical Test and Validation It has been proposed that the just‐in‐time (JIT) philosophy can be effectively integrated systemwide to yield increased efficiencies and excellence throughout an organization. Greater understanding is needed as to what this entails. The researchers empirically test and attempt to validate a previously developed basic functional model of JIT comprising three components – respect for people in the system, the execution system and planning process prerequisites – needed to support JIT′s goal of elimination of waste through a process of continual improvement. Regression model results support the hypothesized relationships between the model components and the JIT waste‐elimination goal. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Physical Distribution & Logistics Management Emerald Publishing

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References (30)

Publisher
Emerald Publishing
Copyright
Copyright © 1994 MCB UP Ltd. All rights reserved.
ISSN
0960-0035
DOI
10.1108/09600039410066150
Publisher site
See Article on Publisher Site

Abstract

It has been proposed that the just‐in‐time (JIT) philosophy can be effectively integrated systemwide to yield increased efficiencies and excellence throughout an organization. Greater understanding is needed as to what this entails. The researchers empirically test and attempt to validate a previously developed basic functional model of JIT comprising three components – respect for people in the system, the execution system and planning process prerequisites – needed to support JIT′s goal of elimination of waste through a process of continual improvement. Regression model results support the hypothesized relationships between the model components and the JIT waste‐elimination goal.

Journal

International Journal of Physical Distribution & Logistics ManagementEmerald Publishing

Published: Aug 1, 1994

Keywords: Just‐in‐time; Kaizen; Logistics; Manufacturing; Modelling; Regression analysis; Surveys

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