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Mark Ferguson,G. Shang, P. Pekgün, and M. Galbreth
Darla Moore School of BusinessUniversity of South Carolina
Estimating the Value of a Money-Back-Guarantee (MBG)
Policy in an Online Retail Context
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Cost: processing returnsBenefit: higher willingness-to-pay
The basic tradeoff for MBGs
no returns, $100 return & refund
How much now?
1. Lots of research on the cost2. Scant research on the benefit
3. Benefits are difficult to quantify
consumer electronics sold online
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How to quantify MBG value?Company Product price
Forward shipping
Return shipping Change
Amazon full refund no refund consumer pay onceBest Buy full refund not clear consumer pay onceDell 85% to 100% no refund consumer pay neverHP full refund no refund consumer pay neverLenovo 85% no refund consumer pay neverSears 85% to 100% no refund consumer pay onceShure full refund no refund consumer pay neverSony 85% to 100% no refund consumer pay neverTarget full refund no refund retailer pay onceWal-Mart full refund no refund consumer pay once
1. Three characteristics for a typical MBG2. Little between-product variation in
MBGs3. Little longitudinal variation in MBG
Hard to quantify the value of MBG
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Data from eBay: 3 appealing features1. Match the three common characteristics
Refund for product price, no refund for forward shipping, buyer pays for return shipping
2. Variation in MBG policy for identical products
3. Consumer’s product valuation measured from auction prices
How we quantify the value of MBGs
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Structured web-crawling
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Structured web-crawling
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Structured web-crawling
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Procedure:1. Select product2. Collect product information3. Identify completed auctions of the product4. Collect transaction information5. Collect seller information
Outcome (after data cleaning) 2946 transactions of 86 consumer electronic
products sold on eBay during 1st quarter of 2013
Structured web-crawling
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Product Price Differences: with MBGs versus without MBGs
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Summary of Auctions Captured
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Desired economic interpretation: If a seller switches from no-MBG to MBG, how
much will consumers’ willingness-to-pay increase?
Main technical challenge: Whether to offer MBG is an endogenous variable.
Consequence: OLS biased IV approach (e.g. 2SLS) biased We use an error correlation based ML estimator
to address endogeneity.
Econometric approach
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Transaction Related:1. Number of bids2. Duration3. Weekend/ time of day/ month4. Order processing time5. Shipping options (stand, economy, exped)
Seller Related:1. eBay store2. Seller tenure
Product Related:1. Average price2. Number of units sold3. Number of reviews
Regression Model Controls
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It depends on forward shipping cost:
It also depends on seller reputation: More positive reviews increase value of MBG More negative reviews decrease value of MBG
Main estimation resultsno returns, $100 return & refund
How much now?
Forward shipping
Value of MBG How much now?
$0 $5.2 $105.2$10 $4.0 $104$20 $2.8 $102.8
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Value of MBG as a function of the forward shipping charge
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What should the shipping fee be?
• When returns rate are high, either charge high shipping fee or do not offer a MBG
• For low return rates, the best shipping fee depends on the recovery value of the returned products
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Value of MBG is smaller than 10% of the product value
Forward shipping fee: Treated by consumers as an implicit restocking
fee Erodes the value of MBG very quickly Makes the one-size-fits-all return policy even
less optimal for online retailers Our increase in valuation estimates can be
combined with the cost of returns to construct a MBG optimization model
Key findings
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A seller who offers free forward shipping and has an average reputation could expect 5.16% increase in consumer’s product valuation if it switches from not offering MBG to offering MBG
A forward shipping charge erodes the value of a MBG policy significantly - if 20% of total price paid is attributed to shipping, then the value of a MBG is close to zero
Positive and negative seller reputations have separate and opposing effects on the value of MBGs
Key take-aways
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Thanks for your participation and feedback!
Questions?
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How does endogeneity arise? DV: consumer’s product valuation Endo. Regressor: seller’s decision to offer MBG Some unobserved factors affect both
What are these unobserved factors? Example: return-related seller reviews Affect likelihood to offer MBG Affect product valuation when there is MBG
Both IV and our approach account for these
IV versus our approach
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However, IV also assumes: Return-related reviews will also affect
product valuation when there is no MBG. That is, return experience matters even when
there is no chance to return. Not realistic…
In contrast, our approach does not make this assumption
We model two error correlations: one with no-MBG, the other with MBG they can be different
IV versus our approach
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