Calculating Price Elasticity

• US 20080040203A1
• Filed: 10/22/2007
• Published: 02/14/2008
• Est. Priority Date: 03/14/2002
• Status: Abandoned Application

• Current Assignee: Blue Yonder Group, Inc. (Panasonic Holdings Corporation)
• Original Assignee: Blue Yonder Group, Inc. (Panasonic Holdings Corporation)
• Inventors: Ranjan, Sushil, Ivanov, Boyko, Kalyan, Vibhu
• Application Number:
  US11/876,089
• Publication Number:
  US 20080040203A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0283 Price estimation or determination

Abstract

Calculating price elasticity includes accessing a number of demand models and demand data describing a number of items. The demand models are evaluated in accordance with the demand data. A demand model of the evaluated demand models is selected in response to the evaluation. A price elasticity is calculated according to the selected demand model.

Claims

1. A computer-implemented method for calculating price elasticity, the method performed using one or more computer systems each comprising one or more processing units and one or more memory units, the method comprising:

accessing a plurality of demand models;

accessing demand data describing a plurality of items;

evaluating the demand models in accordance with the demand data;

selecting a demand model of the evaluated demand models in response to the evaluation;

calculating a price elasticity according to the selected demand model by;

accessing a set of price elasticity values;

for each price elasticity value, determining a probability of the price elasticity value given an event, the demand data describing the event; and

determining a probable price elasticity value in accordance with the determined probabilities of the price elasticity value given the event; and

reporting the calculated price elasticity.

2. The method of claim 1, wherein evaluating the demand models in accordance with the demand data comprises evaluating the demand models according to a Schwarz information criterion.

3. The method of claim 1, wherein evaluating the demand models in accordance with the demand data comprises evaluating the demand models according to a regression specification error test.

4. The method of claim 1, further comprising:

generating a constraint in accordance with the price elasticity for a hierarchy of constraints, wherein the hierarchy of constraints comprises a sequence of levels, each level comprising an objective function and a set of constraints associated with the objective function;

determining a mathematical programming model representing a pricing plan problem for an item group comprising a plurality of items;

for each level of the sequence of levels;

selecting a level comprising an objective function and a set of constraints associated with the objective function;

determining an optimized boundary for the objective function;

generating a constraint from the optimized boundary; and

adding the generated constraint from the optimized boundary to the set of constraints of a next level;

optimizing an objective function of a last level of the sequence subject to the set of constraints associated with the objective function to yield an optimized result, the set of constraints comprising a constraint generated from the optimized boundary of a previous level; and

generating an optimized pricing plan in accordance with the optimized result, the optimized pricing plan associating a price with each item of the item group.

5. A system for calculating price elasticity, comprising:

a database operable to store a plurality of demand models and demand data describing a plurality of items; and

a module coupled to the database and operable to;

evaluate the demand models in accordance with the demand data;

select a demand model of the evaluated demand models in response to the evaluation;

calculate a price elasticity according to the selected demand model by;

accessing a set of price elasticity values;

for each price elasticity value, determining a probability of the price elasticity value given an event, the demand data describing the event; and

determining the most likely price elasticity value in accordance with the determined probabilities of the price elasticity value given the event; and

report the calculated price elasticity.

6. The system of claim 5, wherein the module is operable to evaluate the demand models in accordance with the demand data by evaluating the demand models according to a Schwarz information criterion.

7. The system of claim 5, wherein the module is operable to evaluate the demand models in accordance with the demand data by evaluating the demand models according to a regression specification error test.

8. The system of claim 5, further comprising an optimizer operable to:

generate a constraint in accordance with the price elasticity for a hierarchy of constraints, wherein the hierarchy of constraints comprises a sequence of levels, each level comprising an objective function and a set of constraints associated with the objective function;

determine a mathematical programming model representing a pricing plan problem for an item group comprising a plurality of items;

for each level of the sequence of levels;

selecting a level comprising an objective function and a set of constraints associated with the objective function;

determining an optimized boundary for the objective function;

generating a constraint from the optimized boundary; and

adding the generated constraint from the optimized boundary to the set of constraints of a next level;

optimize an objective function of a last level of the sequence subject to the set of constraints associated with the objective function to yield an optimized result, the set of constraints comprising a constraint generated from the optimized boundary of a previous level; and

generate an optimized pricing plan in accordance with the optimized result, the optimized pricing plan associating a price with each item of the item group.

9. Software for calculating price elasticity, the software encoded in a computer-readable media and when executed operable to:

access a plurality of demand models;

access demand data describing a plurality of items;

evaluate the demand models in accordance with the demand data;

select a demand model of the evaluated demand models in response to the evaluation;

calculate a price elasticity according to the selected demand model by;

accessing a set of price elasticity values;

for each price elasticity value, determining a probability of the price elasticity value given an event, the demand data describing the event; and

determining a probable price elasticity value in accordance with the determined probabilities of the price elasticity value given the event; and

report the calculated price elasticity.

10. The software of claim 9, wherein the software is operable to evaluate the demand models in accordance with the demand data by evaluating the demand models according to a Schwarz information criterion.

11. The software of claim 9, wherein the software is operable to evaluate 15 the demand models in accordance with the demand data by evaluating the demand models according to a regression specification error test.

12. The software of claim 9, further operable to:

generate a constraint in accordance with the price elasticity for a hierarchy of constraints, wherein the hierarchy of constraints comprises a sequence of levels, each level comprising an objective function and a set of constraints associated with the objective function;

determine a mathematical programming model representing a pricing plan problem for an item group comprising a plurality of items;

for each level of the sequence of levels;

selecting a level comprising an objective function and a set of constraints associated with the objective function;

determining an optimized boundary for the objective function;

generating a constraint from the optimized boundary; and

adding the generated constraint from the optimized boundary to the set of constraints of a next level;

optimize an objective function of a last level of the sequence subject to the set of constraints associated with the objective function to yield an optimized result, the set of constraints comprising a constraint generated from the optimized boundary of a previous level; and

generate an optimized pricing plan in accordance with the optimized result, the optimized pricing plan associating a price with each item of the item group.