A Refinement of the Classical Order Point Model

Farhad Moeeni, Stephen Replogle, Zariff Chaudhury and Ahmad Syamil
Additional contact information
Farhad Moeeni: Arkansas State University, USA
Stephen Replogle: Arkansas State University, USA
Zariff Chaudhury: Arkansas State University, USA
Ahmad Syamil: Arkansas State University, USA

International Journal of Information Systems and Supply Chain Management (IJISSCM), 2012, vol. 5, issue 3, 43-57

Abstract: Factors such as demand volume and replenishment lead time that influence production and inventory control systems are random variables. Existing inventory models incorporate the parameters (e.g., mean and standard deviation) of these statistical quantities to formulate inventory policies. In practice, only sample estimates of these parameters are available. The estimates are subject to sampling variation and hence are random variables. Whereas the effect of sampling variability on estimates of parameters are in general well known in statistics literature, literature on inventory control policies has largely ignored the potential effect of sampling variation on the validity of the inventory models. This paper investigates the theoretical effect of sampling variability and develops theoretically sound inventory models that can be effectively used in different inventory policies.

Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/jisscm.2012070103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jisscm:v:5:y:2012:i:3:p:43-57

Access Statistics for this article

International Journal of Information Systems and Supply Chain Management (IJISSCM) is currently edited by John Wang

More articles in International Journal of Information Systems and Supply Chain Management (IJISSCM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().