Finite time horizon fill rate analysis for multiple customer cases

B. Abbasi, Z. Hosseinifard, O. Alamri, D. Thomas, J. P. Minas

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The item fill rate – defined as the fraction of demand that is immediately satisfied from on-hand stock – is commonly used as a performance measure in service level agreements between customers and suppliers. Under such agreements, the fill rate is measured over a finite horizon (the performance review period) and the supplier faces a financial penalty if an agreed target is not met. The distribution of the item fill rate (fill rate) determines the probability of exceeding the agreed target, it is therefore a point of interest in SLA coordination. The average finite horizon fill rate decreases with an increase in performance review period length. However, the impact of performance review period length on the shape of the fill rate distribution is not well understood. Past studies of finite horizon fill rate only consider a single customer in the supply chain. In this study, we analyze fill rate distributions for a supplier that has multiple customers each with their own service level agreement. We examine the effects of performance review period length, choice of demand fulfillment (service) policy and correlation between customers’ demands on both the average fill rate and the probability of achieving the target fill rate. This study provides new insights into service level agreement coordination between suppliers and customers. For instance, the results show that a supplier with multiple customers must take care with choosing a service policy, as rationing will affect the fill rate distribution and hence the realized service level.

Original languageEnglish (US)
Pages (from-to)1-17
Number of pages17
JournalOmega (United Kingdom)
Volume76
DOIs
StatePublished - Apr 2018

Fingerprint

Time horizon
Suppliers
Finite horizon
Service level agreement
Supply chain
Penalty
Service levels
Performance measures
Rationing

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

Cite this

Abbasi, B., Hosseinifard, Z., Alamri, O., Thomas, D., & Minas, J. P. (2018). Finite time horizon fill rate analysis for multiple customer cases. Omega (United Kingdom), 76, 1-17. https://doi.org/10.1016/j.omega.2017.03.004
Abbasi, B. ; Hosseinifard, Z. ; Alamri, O. ; Thomas, D. ; Minas, J. P. / Finite time horizon fill rate analysis for multiple customer cases. In: Omega (United Kingdom). 2018 ; Vol. 76. pp. 1-17.
@article{71be212ee75949999c40e987eda1e22e,
title = "Finite time horizon fill rate analysis for multiple customer cases",
abstract = "The item fill rate – defined as the fraction of demand that is immediately satisfied from on-hand stock – is commonly used as a performance measure in service level agreements between customers and suppliers. Under such agreements, the fill rate is measured over a finite horizon (the performance review period) and the supplier faces a financial penalty if an agreed target is not met. The distribution of the item fill rate (fill rate) determines the probability of exceeding the agreed target, it is therefore a point of interest in SLA coordination. The average finite horizon fill rate decreases with an increase in performance review period length. However, the impact of performance review period length on the shape of the fill rate distribution is not well understood. Past studies of finite horizon fill rate only consider a single customer in the supply chain. In this study, we analyze fill rate distributions for a supplier that has multiple customers each with their own service level agreement. We examine the effects of performance review period length, choice of demand fulfillment (service) policy and correlation between customers’ demands on both the average fill rate and the probability of achieving the target fill rate. This study provides new insights into service level agreement coordination between suppliers and customers. For instance, the results show that a supplier with multiple customers must take care with choosing a service policy, as rationing will affect the fill rate distribution and hence the realized service level.",
author = "B. Abbasi and Z. Hosseinifard and O. Alamri and D. Thomas and Minas, {J. P.}",
year = "2018",
month = "4",
doi = "10.1016/j.omega.2017.03.004",
language = "English (US)",
volume = "76",
pages = "1--17",
journal = "Omega",
issn = "0305-0483",
publisher = "Elsevier BV",

}

Abbasi, B, Hosseinifard, Z, Alamri, O, Thomas, D & Minas, JP 2018, 'Finite time horizon fill rate analysis for multiple customer cases', Omega (United Kingdom), vol. 76, pp. 1-17. https://doi.org/10.1016/j.omega.2017.03.004

Finite time horizon fill rate analysis for multiple customer cases. / Abbasi, B.; Hosseinifard, Z.; Alamri, O.; Thomas, D.; Minas, J. P.

In: Omega (United Kingdom), Vol. 76, 04.2018, p. 1-17.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Finite time horizon fill rate analysis for multiple customer cases

AU - Abbasi, B.

AU - Hosseinifard, Z.

AU - Alamri, O.

AU - Thomas, D.

AU - Minas, J. P.

PY - 2018/4

Y1 - 2018/4

N2 - The item fill rate – defined as the fraction of demand that is immediately satisfied from on-hand stock – is commonly used as a performance measure in service level agreements between customers and suppliers. Under such agreements, the fill rate is measured over a finite horizon (the performance review period) and the supplier faces a financial penalty if an agreed target is not met. The distribution of the item fill rate (fill rate) determines the probability of exceeding the agreed target, it is therefore a point of interest in SLA coordination. The average finite horizon fill rate decreases with an increase in performance review period length. However, the impact of performance review period length on the shape of the fill rate distribution is not well understood. Past studies of finite horizon fill rate only consider a single customer in the supply chain. In this study, we analyze fill rate distributions for a supplier that has multiple customers each with their own service level agreement. We examine the effects of performance review period length, choice of demand fulfillment (service) policy and correlation between customers’ demands on both the average fill rate and the probability of achieving the target fill rate. This study provides new insights into service level agreement coordination between suppliers and customers. For instance, the results show that a supplier with multiple customers must take care with choosing a service policy, as rationing will affect the fill rate distribution and hence the realized service level.

AB - The item fill rate – defined as the fraction of demand that is immediately satisfied from on-hand stock – is commonly used as a performance measure in service level agreements between customers and suppliers. Under such agreements, the fill rate is measured over a finite horizon (the performance review period) and the supplier faces a financial penalty if an agreed target is not met. The distribution of the item fill rate (fill rate) determines the probability of exceeding the agreed target, it is therefore a point of interest in SLA coordination. The average finite horizon fill rate decreases with an increase in performance review period length. However, the impact of performance review period length on the shape of the fill rate distribution is not well understood. Past studies of finite horizon fill rate only consider a single customer in the supply chain. In this study, we analyze fill rate distributions for a supplier that has multiple customers each with their own service level agreement. We examine the effects of performance review period length, choice of demand fulfillment (service) policy and correlation between customers’ demands on both the average fill rate and the probability of achieving the target fill rate. This study provides new insights into service level agreement coordination between suppliers and customers. For instance, the results show that a supplier with multiple customers must take care with choosing a service policy, as rationing will affect the fill rate distribution and hence the realized service level.

UR - http://www.scopus.com/inward/record.url?scp=85016777925&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85016777925&partnerID=8YFLogxK

U2 - 10.1016/j.omega.2017.03.004

DO - 10.1016/j.omega.2017.03.004

M3 - Article

AN - SCOPUS:85016777925

VL - 76

SP - 1

EP - 17

JO - Omega

JF - Omega

SN - 0305-0483

ER -