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Estimating the Value of a Money-Back-Guarantee (MBG) Policy in an Online Retail Context

Estimating the Value of a Money-Back-Guarantee (MBG) Policy in an Online Retail Context. Mark Ferguson, G. Shang, P. Pekgün , and M. Galbreth Darla Moore School of Business University of South Carolina. The basic tradeoff for MBGs. Cost: processing returns

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Estimating the Value of a Money-Back-Guarantee (MBG) Policy in an Online Retail Context

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  1. Estimating the Value of a Money-Back-Guarantee (MBG) Policy in an Online Retail Context Mark Ferguson, G. Shang, P. Pekgün, and M. Galbreth Darla Moore School of Business University of South Carolina

  2. The basic tradeoff for MBGs • Cost: processing returns • Benefit: higher willingness-to-pay no returns, $100 return & refund How much now? • Benefits are difficult to quantify • Lots of research on the cost • Scant research on the benefit consumer electronics sold online

  3. How to quantify MBG value? • Three characteristics for a typical MBG • Little between-product variation in MBGs • Little longitudinal variation in MBG Hard to quantify the value of MBG

  4. How we quantify the value of MBGs • Data from eBay: 3 appealing features • Match the three common characteristics • Refund for product price, no refund for forward shipping, buyer pays for return shipping • Variation in MBG policy for identical products • Consumer’s product valuation measured from auction prices

  5. Structured web-crawling

  6. Structured web-crawling

  7. Structured web-crawling

  8. Structured web-crawling • Procedure: • Select product • Collect product information • Identify completed auctions of the product • Collect transaction information • Collect seller information • Outcome (after data cleaning) • 2946 transactions of 86 consumer electronic products sold on eBay during 1st quarter of 2013

  9. Product Price Differences: with MBGs versus without MBGs

  10. Summary of Auctions Captured

  11. Econometric approach • 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.

  12. Regression Model Controls • Transaction Related: • Number of bids • Duration • Weekend/ time of day/ month • Order processing time • Shipping options (stand, economy, exped) • Seller Related: • eBay store • Seller tenure • Product Related: • Average price • Number of units sold • Number of reviews

  13. Main estimation results return & refund no returns, $100 How much now? • 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

  14. Value of MBG as a function of the forward shipping charge

  15. 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

  16. Key findings • 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

  17. Key take-aways • 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

  18. Questions? Thanks for your participation and feedback!

  19. IV versus our approach • 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

  20. IV versus our approach • 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 Back

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