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Emrouznejad, Ali; Rostami-Tabar, Bahman; Petridis, Konstantinos (2016)
Publisher: Elsevier
Journal: Technological Forecasting and Social Change
Languages: English
Types: Article
Subjects: Business and International Management, Applied Psychology, Management of Technology and Innovation
To compare the accuracy of different forecasting approaches an error measure is required. Many error measures have been proposed in the literature, however in practice there are some situations where different measures yield different decisions on forecasting approach selection and there is no agreement on which approach should be used. Generally forecasting measures represent ratios or percentages providing an overall image of how well fitted the forecasting technique is to the observations. This paper proposes a multiplicative Data Envelopment Analysis (DEA) model in order to rank several forecasting techniques. We demonstrate the proposed model by applying it to the set of yearly time series of the M3 competition. The usefulness of the proposed approach has been tested using the M3-competition where five error measures have been applied in and aggregated to a single DEA score.
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    • Ali Emrouznejad is a Professor and Chair in Business Analytics at Aston Business School, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. Dr. Emrouznejad is Editor of Annals of Operations Research, Associate Editor of Socio-Economic Planning Sciences, Associate Editor of IMA journal of Management Mathematics, Senior Editor of Data Envelopment Analysis journal, and member of editorial boards or guest editor in several other scientific journals. He has published over 80 articles in top ranked journals; he is author of the book on “Applied Operational Research with SAS”, editor of the books on “Performance Measurement with Fuzzy Data Envelopment Analysis”, “Managing Service Productivity” and “Handbook of Research on Strategic Performance Management and Measurement”. He is also co-founder of Performance Improvement Management Software (PIM-DEA), see http://www.DEAzone.com.
    • Bahman Rostami-Tabar is an assistant professor of operations and supply chain management in the School of Strategy and Leadership at Coventry University in the UK. In 2013, Bahman received the MIM best paper award (IFAC) and was also successful in Campus France Scholarship award (2009-2013). His research interests include Forecasting, data aggregation, information sharing and humanitarian supply chain management.
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