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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Main Authors: SUNG, Nahk Hyun, LEE, Jae Kyu
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2000
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Online Access:https://ink.library.smu.edu.sg/sis_research/1157
http://dx.doi.org/10.1016/S0167-9236(99)00095-0
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Institution: Singapore Management University
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spelling 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
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Retail pricing models
Expert systems
Price point determination rules
Computer Sciences
Management Information Systems
spellingShingle 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
description 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.
format text
author SUNG, Nahk Hyun
LEE, Jae Kyu
author_facet SUNG, Nahk Hyun
LEE, Jae Kyu
author_sort 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
title_full_unstemmed Knowledge Assisted Dynamic Pricing for Large-Scale Retailers
title_sort knowledge assisted dynamic pricing for large-scale retailers
publisher Institutional Knowledge at Singapore Management University
publishDate 2000
url https://ink.library.smu.edu.sg/sis_research/1157
http://dx.doi.org/10.1016/S0167-9236(99)00095-0
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