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Design of a Mechanism for Promoting Honesty in E-Marketplaces

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Design of a Mechanism for Promoting Honesty in E-Marketplaces

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Design of a Mechanism for Promoting Honesty in E-Marketplaces

  1. 1. Design of a Mechanism for Promoting Honesty in E-Marketplaces Jie Zhang and Robin Cohen University of Waterloo Presented by Sahithi Thandra 1 CS 886-Winter 2016
  2. 2. 2 CS 886-Winter 2016 How do you rate your experience with us ?
  3. 3. 3 This is Unfair!
  4. 4. 4 CS 886-Winter 2016 Incentive mechanism
  5. 5. 5 CS 886-Winter 2016 ✦ Centralized Approach. ✦ Buyers model other Buyers and select trustworthy people as their neighbours. ✦ Sellers model reputation of buyers and give discounts to the reputable buyers hoping to make profits out of future transactions. Incentive mechanism
  6. 6. 6 CS 886-Winter 2016 1. Private Reputation: It is calculated based on their ratings for commonly rated sellers Priv(A) = (no.of matched ratings) / (total no.of common ratings) 2. Each rating in the network is judged by central server for its fairness 3. Public Reputation: It is based on all ratings for all sellers in the market ever rated by an advisor. Pub(A) = (no.of fair ratings given by A) / (total no.of ratings) How does Buyer select its Advisors ?
  7. 7. 7 CS 886-Winter 2016 ✦ Buyer computes trust value of each advisor based on its private and public reputation Trust(A) = W*Priv(A) + (1-W)*Pub(A) ✦ It selects advisors as neighbours that exceed certain threshold. How does Buyer select its Advisors ?
  8. 8. 8 CS 886-Winter 2016 Non-price Features Delivery Time (day) Warranty (Year) Weights 0.4 0.6 Descriptive Value 7 3 1 1 2 3 Numerical Value 3 5 10 3 5 10 Buyer Choosing Winning Seller Buyer B’s Evaluation Criteria for product P
  9. 9. 9 CS 886-Winter 2016 ✦ Suppose Buyer ‘B’ has 1 neighbour ‘A’ ✦ Sellers S1,S2,S3,S4 submitted bids for product ‘P’ ✦ B has not transacted with any of these sellers previously Buyer Choosing Winning Seller T T1 T2 T3 T4 T5 S1 0 0 0 1 1 S2 - - - - - S3 1 1 1 1 1 S4 1 1 1 1 0 Ratings of Sellers provided by ‘A’
  10. 10. 10 CS 886-Winter 2016 ✦ Buyer ‘B’ calculates private and public reputations of all the sellers. ✦ Based on weights of each component, trust value of sellers is calculated ✦ All the sellers exceeding a certain threshold are considered trustworthy ✦ Now Buyer ‘B’ selects the seller that offers highest valuation for the product ✦Value(P) = Weight*NumericalValue - Price(P) Buyer Choosing Winning Seller
  11. 11. 11 CS 886-Winter 2016 ✦ Buyers {B1, B2,…B6} requested the same product ‘P’ Seller Bidding Buyers’ Requests Buyer Neighbors B1 B2 B5 B6 B2 B4 B5 B6 B3 B4 B5 B6 B4 B3 B5 B6 B5 B3 B4 B6 B6 B3 B4 B5 Neighbours of Buyers
  12. 12. 12 CS 886-Winter 2016 ✦ We calculate reputation of all the buyers ✦N(B6) = 5 -> R(B6) = 5/6 =0.83 ✦ Next, Seller provides more discount to reputable buyers by increasing the quality or decreasing the price of item ✦ In this way, we address unfair ratings and provide benefits to both parties. Seller Bidding Buyers’ Requests
  13. 13. 13 CS 886-Winter 2016

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