Method and device for dynamically estimating price elasticity

A dynamic estimation and price technology, applied in the computer field, can solve problems such as multi-resources, increased server burden, and long time required for parameter estimation, so as to improve computing efficiency, improve computing accuracy and efficiency, and release computing resources. Effect

Inactive Publication Date: 2019-07-02
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This technology uses characteristic values called lags that indicate changes over time caused by factors like pricing behavior during trade agreements with buyers. By measuring these quantities, an algorithm predicts how much expensive something will cost each buyer compared against what they want beforehand. It then adjust prices based upon this prediction value, improving calculations speed while reducing computing resource usage. Additionally, the system integrates various features such as quality control measures and risk assessments into its own decision process, allowing users to make informed decisions about whether to purchase specific items from their chosen counterpart's listings when needed. Overall, this technology helps businesses optimize their profitability through efficient market analysis tools and provide valuable insights towards future trends.

Problems solved by technology

Technological Problem addressed by this patented technology relates to how to accurately predict future demand levels associated with different commoditized goods (like groceries) during online sale transactions without taking too much data and requiring excessive computing power compared to previous models.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and device for dynamically estimating price elasticity
  • Method and device for dynamically estimating price elasticity
  • Method and device for dynamically estimating price elasticity

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] Exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present invention to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0031] The prior art price elasticity calculation scheme usually adopts a regular calculation strategy, such as updating once a month. Each time, the newly generated data is added to the volume price calculation model to recalculate the price elasticity. The specific calculation method is mainly based on statistical analysis, supplemented by machine learning, and the program

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The embodiment of the invention provides a method and device for dynamically estimating price elasticity. The commodity data in the preset time span can be selected, so that the old data can be removed in the calculation process of the price elasticity, the new data can be introduced, the more effective data can be continuously updated to the calculation of the price elasticity, and the model estimation result is more effective. The method comprises the steps of determining an optimal attenuation model of a commodity; calculating an optimal attenuation period of the commodity according to theoptimal attenuation model; and according to the optimal attenuation period, weighting the commodity data in the preset time span according to the unit data points, and estimating the price elasticityof the commodity by using the weighted commodity data.

Description

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap