Forecasting Demand in the Grocery Sector of the Retail Industry:  Comparing the Performance of  Machine Learning and Econometric Methods  on Extreme Promotional Intensities

Additional Metadata
Keywords	Sales Forecasting, Machine learning, Econometric forecasting method, Promotional sales forecasting, single step, baseline plus lfit
Thesis Advisor	Rooderkerk, Robert, Tsoukalas, Angelos
Persistent URL	hdl.handle.net/2105/69576
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Garrido Tenorio, Klaus. (2023, August 17). Forecasting Demand in the Grocery Sector of the Retail Industry: Comparing the Performance of Machine Learning and Econometric Methods on Extreme Promotional Intensities. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/69576

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