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Improving the performance of popular supply chain forecasting techniques

Research output: Contribution to journalJournal articlepeer-review

Published

Standard

Improving the performance of popular supply chain forecasting techniques. / Spithourakis, Giorgos; Petropoulos, Fotios; Babai, Mohamed; Nikolopoulos, Konstantinos; Assimakopoulos, V.

In: Supply Chain Forum: An International Journal, Vol. 12, No. 4, 2011, p. 16-25.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Spithourakis, G, Petropoulos, F, Babai, M, Nikolopoulos, K & Assimakopoulos, V 2011, 'Improving the performance of popular supply chain forecasting techniques', Supply Chain Forum: An International Journal, vol. 12, no. 4, pp. 16-25. <http://www.supplychain-forum.com/article.cfm?num=27&art=226>

APA

Spithourakis, G., Petropoulos, F., Babai, M., Nikolopoulos, K., & Assimakopoulos, V. (2011). Improving the performance of popular supply chain forecasting techniques. Supply Chain Forum: An International Journal, 12(4), 16-25. http://www.supplychain-forum.com/article.cfm?num=27&art=226

Vancouver

Spithourakis G, Petropoulos F, Babai M, Nikolopoulos K, Assimakopoulos V. Improving the performance of popular supply chain forecasting techniques. Supply Chain Forum: An International Journal. 2011;12(4):16-25.

Author

Spithourakis, Giorgos ; Petropoulos, Fotios ; Babai, Mohamed ; Nikolopoulos, Konstantinos ; Assimakopoulos, V. / Improving the performance of popular supply chain forecasting techniques. In: Supply Chain Forum: An International Journal. 2011 ; Vol. 12, No. 4. pp. 16-25.

Bibtex

@article{7928cb69ddea4e458b5d1500ff533339,
title = "Improving the performance of popular supply chain forecasting techniques",
abstract = "This paper empirically investigates the extension of the use of an aggregation-disaggregation forecasting approach for intermittent demand (ADIDA) to fast moving demand data, addressing the need of supply chain managers for accurate forecasts. After a brief introduction to the framework and its background, an experiment is set up to examine its performance on data from the M3-Competition. The relevant forecasting methodology and in-sample optimization techniques are described in detail, as well as the core experimental structure and real data. Empirical results of forecasting accuracy performance are presented and discussed, placing further emphasis on the managerial implications of the framework{\textquoteright}s being a simple, cost-efficient and universally implementable forecasting method self-improving mechanism. Finally, all conclusions are summarized and guidelines for prospective research are proposed.",
keywords = "Forecasting, Fast moving demand, Temporal aggregation, Empirical investigation, Forecasting framework",
author = "Giorgos Spithourakis and Fotios Petropoulos and Mohamed Babai and Konstantinos Nikolopoulos and V Assimakopoulos",
year = "2011",
language = "English",
volume = "12",
pages = "16--25",
journal = "Supply Chain Forum: An International Journal",
issn = "1625-8312",
publisher = "KEDGE Business School",
number = "4",

}

RIS

TY - JOUR

T1 - Improving the performance of popular supply chain forecasting techniques

AU - Spithourakis, Giorgos

AU - Petropoulos, Fotios

AU - Babai, Mohamed

AU - Nikolopoulos, Konstantinos

AU - Assimakopoulos, V

PY - 2011

Y1 - 2011

N2 - This paper empirically investigates the extension of the use of an aggregation-disaggregation forecasting approach for intermittent demand (ADIDA) to fast moving demand data, addressing the need of supply chain managers for accurate forecasts. After a brief introduction to the framework and its background, an experiment is set up to examine its performance on data from the M3-Competition. The relevant forecasting methodology and in-sample optimization techniques are described in detail, as well as the core experimental structure and real data. Empirical results of forecasting accuracy performance are presented and discussed, placing further emphasis on the managerial implications of the framework’s being a simple, cost-efficient and universally implementable forecasting method self-improving mechanism. Finally, all conclusions are summarized and guidelines for prospective research are proposed.

AB - This paper empirically investigates the extension of the use of an aggregation-disaggregation forecasting approach for intermittent demand (ADIDA) to fast moving demand data, addressing the need of supply chain managers for accurate forecasts. After a brief introduction to the framework and its background, an experiment is set up to examine its performance on data from the M3-Competition. The relevant forecasting methodology and in-sample optimization techniques are described in detail, as well as the core experimental structure and real data. Empirical results of forecasting accuracy performance are presented and discussed, placing further emphasis on the managerial implications of the framework’s being a simple, cost-efficient and universally implementable forecasting method self-improving mechanism. Finally, all conclusions are summarized and guidelines for prospective research are proposed.

KW - Forecasting

KW - Fast moving demand

KW - Temporal aggregation

KW - Empirical investigation

KW - Forecasting framework

M3 - Journal article

VL - 12

SP - 16

EP - 25

JO - Supply Chain Forum: An International Journal

JF - Supply Chain Forum: An International Journal

SN - 1625-8312

IS - 4

ER -