Knowledge Assisted Dynamic Pricing for Large-Scale Retailers
It is very difficult for large-scale retailers to price thousands of items dynamically reflecting all constraints and policies. To solve this problem, we adopt a combined model approach that contingently selects appropriate pricing models and integrates them. The three proposed models are cost-plus,...
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sg-smu-ink.sis_research-21562010-12-22T08:24:06Z Knowledge Assisted Dynamic Pricing for Large-Scale Retailers SUNG, Nahk Hyun LEE, Jae Kyu It is very difficult for large-scale retailers to price thousands of items dynamically reflecting all constraints and policies. To solve this problem, we adopt a combined model approach that contingently selects appropriate pricing models and integrates them. The three proposed models are cost-plus, competitor-referenced, and demand-driven models. Since each model can be converted to a set of interval and point constraints, we have developed price point determination rules, which find a price point from the weighted interval and point constraints. A prototype system, Knowledge-Assisted Pricing Assistant (KAPA) is developed with this idea. According to our experiment involving 76 cases with 54 pricing experts, KAPA performed consistently, with human experts, about 89.5% accurate. This approach can be a very effective pricing scheme in the electronic marketing era. 2000-06-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/1157 info:doi/10.1016/S0167-9236(99)00095-0 http://dx.doi.org/10.1016/S0167-9236(99)00095-0 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Retail pricing models Expert systems Price point determination rules Computer Sciences Management Information Systems |
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Retail pricing models Expert systems Price point determination rules Computer Sciences Management Information Systems SUNG, Nahk Hyun LEE, Jae Kyu Knowledge Assisted Dynamic Pricing for Large-Scale Retailers |
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It is very difficult for large-scale retailers to price thousands of items dynamically reflecting all constraints and policies. To solve this problem, we adopt a combined model approach that contingently selects appropriate pricing models and integrates them. The three proposed models are cost-plus, competitor-referenced, and demand-driven models. Since each model can be converted to a set of interval and point constraints, we have developed price point determination rules, which find a price point from the weighted interval and point constraints. A prototype system, Knowledge-Assisted Pricing Assistant (KAPA) is developed with this idea. According to our experiment involving 76 cases with 54 pricing experts, KAPA performed consistently, with human experts, about 89.5% accurate. This approach can be a very effective pricing scheme in the electronic marketing era. |
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text |
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SUNG, Nahk Hyun LEE, Jae Kyu |
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SUNG, Nahk Hyun LEE, Jae Kyu |
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SUNG, Nahk Hyun |
title |
Knowledge Assisted Dynamic Pricing for Large-Scale Retailers |
title_short |
Knowledge Assisted Dynamic Pricing for Large-Scale Retailers |
title_full |
Knowledge Assisted Dynamic Pricing for Large-Scale Retailers |
title_fullStr |
Knowledge Assisted Dynamic Pricing for Large-Scale Retailers |
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Knowledge Assisted Dynamic Pricing for Large-Scale Retailers |
title_sort |
knowledge assisted dynamic pricing for large-scale retailers |
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Institutional Knowledge at Singapore Management University |
publishDate |
2000 |
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https://ink.library.smu.edu.sg/sis_research/1157 http://dx.doi.org/10.1016/S0167-9236(99)00095-0 |
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