optimization of edvp in retail and e-commerce y.-h. chen, ph.d. information engineering / ic...

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Optimization of EDVP in Retail and E- Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

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Page 1: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Optimization of EDVP in Retail and E-Commerce

Y.-H. Chen, Ph.D.Information Engineering / IC

Ming-Chuan University

Page 2: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Every-Day-Value-Price (EDVP)

Utilized by US businesses in 2001. Increase sales by having more

people visit the stores or web sites (increased in-store traffic) through the offer of good deals on popular products.

Convenience of shopping at one place for the whole family.

Page 3: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Businesses

Super Wal-Mart, K-Mart (Blue-Light Merchandise), Target, Amazon, Tom Thumb, Kroger, Albertson, …, and other retailers.

Page 4: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Problems Decreased sales due to (inappropriate)

EDVP products. Increased store traffic is below

expectation. Increased store traffic does not cause

sales of other products. Reduced profit of EDVP products offsets

increased sales of other products. Negative profit due to low or free EDVP

product prices.

Page 5: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Problems (con’t)

Lack of knowledge about … the magnitude of price mark down

needed, and its quantitative impact to the sales of

other products.

Page 6: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Objective and Decisions

Objective: Maximize profit gain Decisions:

What products are good candidates for EDVP products?

How much price mark down? Store traffic v.s. real demand?

Page 7: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Model

Assumptions EDVP v.s. non-EDVP products. Sufficient product supply. No product disposal cost. Increased sales of non-EDVP products

is independent with the demand distribution of EDVP products.

Page 8: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Model (con’t)

Page 9: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Model (con’t)

where

px0s.t.

)(max

TPE

RQQcpQcpQcxpNPNPTP ))(()()(

Page 10: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Optimization

px

xka

xTPE

0s.t.

)(max

)()( cprcpaqk

2* kx

a

kTPE

4)(

2*

and

where

Page 11: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Optimization Chart

Page 12: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Business Strategy #1: Price Mark Down Decision

1. If the computed optimal price mark down is not feasible, we should not consider price mark down or we should give away the EDVP product for free (Corollary 1).

Page 13: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

EDVP Business Strategy #2:Product Selection

2. We can improve the optimal profit gain further by using different products in our problem (Corollary 2 and Lemma 2.1).

)()( cprcpaqk

2* kx

a

kTPE

4)(

2*

and

Page 14: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Business Strategy #3:Product Selection Details

3. If we consider different products to improve the optimal profit gain, we can use any combination of the following methods:

Replace any or both products with the ones having higher unit profit (Corollaries 3 and 4).

Replace any or both products with higher correlation between their demand quantities (Corollary 5).

Use a highly elastic product as our EDVP product (Corollary 6).

Page 15: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Business Strategy #3:Product Selection Details (con’t)

Page 16: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Grocery Chain Example

Watermelon: unit cost $1.00, unit price $5.99, unit profit $4.99.

Beef (per pound): unit cost $2.00, unit price $8.99, unit profit, $6.99.

Historical watermelon demand: 2000 units.

Traffic and demand ratio: 0.80.

Page 17: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Grocery Chain Example (con’t)

Page 18: Optimization of EDVP in Retail and E-Commerce Y.-H. Chen, Ph.D. Information Engineering / IC Ming-Chuan University

Grocery Chain Example (con’t)

Mark down watermelon unit price by $3.29, i.e., unit price becomes 5.99-3.29 = $2.70.

Watermelon sales is increased by 1645.

Maximal net profit gain from the price mark down is $1353.84 for a weekend.