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Quantitatively evaluating the effects of price promotions using data mining

Gan, Min and Dai, Honghua 2013, Quantitatively evaluating the effects of price promotions using data mining. In Pooley, Rob, Coady, Jennifer, Linger, Henry, Barry, Chris, Lang, Michael and Schneider, Christoph (ed), Information systems development : reflections, challenges and new directions, Springer, New York, N.Y., pp.485-497, doi: 10.1007/978-1-4614-4951-5_39.

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Title Quantitatively evaluating the effects of price promotions using data mining
Author(s) Gan, Min
Dai, Honghua
Title of book Information systems development : reflections, challenges and new directions
Editor(s) Pooley, Rob
Coady, Jennifer
Linger, Henry
Barry, Chris
Lang, Michael
Schneider, Christoph
Publication date 2013
Chapter number 39
Total chapters 55
Start page 485
End page 497
Total pages 13
Publisher Springer
Place of Publication New York, N.Y.
Summary Price promotions (also called discount promotions), i.e. short-term temporary price reductions for selected items (Hermann 1989), are frequently used in sales promotions. The main objective of price promotions is to boost sales and increase profits. Quantitative evaluation of the effects of price promotions (QEEPP) is essential and important for sales managers to analyse historical price promotions and informative for devising more effective promotional strategies in the future. However, most previous studies only provide insights into the effects of discount promotions from some specific prospectives, and no approaches have been proposed for comprehensive evaluation of the effects of discount promotions. For example, Hinkle [1965] discovered that price promotions in the off-season are more favourable, and the effects of price promotions are stronger for new products. Peckham [1973] found that price promotions have no impact on long-term trend. Blattberg et al. [1978] identified that different segments respond to price promotions in different ways. Rockney [1991] discovered three basic types of effects: effects on discounted items, effects on substitutes and effects on complementary items.
Notes This paper was presented at the International Conference on Information Systems Development (20th : 2011 : Edinburgh, Scotland)
ISBN 1461449510
Language eng
DOI 10.1007/978-1-4614-4951-5_39
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890202 Application Tools and System Utilities
HERDC Research category B1 Book chapter
Copyright notice ©2013, Springer
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Document type: Book Chapter
Collection: School of Information Technology
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