What is the Cost of Venting? Evidence from eBay

This paper uses data collected from eBay's website to identify why buyers fail to leave (negative) feedback in online markets. Empirical results con¯rm that the fear of retaliation may be an important motivation for buyers not to leave (negative) feedback, while the time and effort cost of reporting may be not.reputation, feedback, asymmetric information

Money Talks? An Experimental Study of Rebate in Reputation System Design

Reputation systems that rely on feedback from traders are important institutions for helping sustain trust in markets, while feedback information is usually considered a public good. We apply both theoretical models and experiments to study how raters' feedback behavior responds to different reporting costs and how to improve market efficiency by introducing a pre-commitment device for sellers in reputation systems. In particular, the pre-commitment device we study here allows sellers to provide rebates to cover buyers' reporting costs before buyers make purchasing decisions. Using a buyer-seller trust game with a unilateral feedback scheme, we find that a buyer’s propensity to leave feedback is more sensitive to reporting costs when the seller cooperates than when the seller defects. The seller’s decision on whether to provide a rebate significantly affects the buyer’s decision to leave feedback by compensating for the feedback costs. More importantly, the rebate decision has a significant impact on the buyer's purchasing decision via signaling the seller's cooperative type. The experimental results show that the rebate mechanism improves the market efficiency.reputation, trust, feedback mechanism, asymmetric information, public goods, experimental economics

A Dollar for Your Thoughts: Feedback-Conditional Rebates on eBay

We run a series of controlled field experiments on eBay where buyers are rewarded for providing feedback. Our results suggest that the feedback rate increases when a rebate is given, though the effect is small. Moreover, the nature of buyer feedback is influenced by rewards: buyers are more likely to give positive feedback following a high-quality transaction (fast shipping) and less likely to give negative feedback following a low-quality transaction (slow shipping). In sum, you can buy feedback but you cannot buy unbiased feedback

What is the Cost of Venting? Evidence from eBay

This paper uses data collected from eBay's website to identify why buyers fail to leave (negative) feedback in online markets. Empirical results con¯rm that the fear of retaliation may be an important motivation for buyers not to leave (negative) feedback, while the time and effort cost of reporting may be not

What is the Cost of Venting? Evidence from eBay

This paper uses data collected from eBay's website to identify why buyers fail to leave (negative) feedback in online markets. Empirical results con¯rm that the fear of retaliation may be an important motivation for buyers not to leave (negative) feedback, while the time and effort cost of reporting may be not

Money Talks? An Experimental Study of Rebate in Reputation System Design

Reputation systems that rely on feedback from traders are important institutions for helping sustain trust in markets, while feedback information is usually considered a public good. We apply both theoretical models and experiments to study how raters' feedback behavior responds to different reporting costs and how to improve market efficiency by introducing a pre-commitment device for sellers in reputation systems. In particular, the pre-commitment device we study here allows sellers to provide rebates to cover buyers' reporting costs before buyers make purchasing decisions. Using a buyer-seller trust game with a unilateral feedback scheme, we find that a buyer’s propensity to leave feedback is more sensitive to reporting costs when the seller cooperates than when the seller defects. The seller’s decision on whether to provide a rebate significantly affects the buyer’s decision to leave feedback by compensating for the feedback costs. More importantly, the rebate decision has a significant impact on the buyer's purchasing decision via signaling the seller's cooperative type. The experimental results show that the rebate mechanism improves the market efficiency

Money Talks? An Experimental Study of Rebate in Reputation System Design

Reputation systems that rely on feedback from traders are important institutions for helping sustain trust in markets, while feedback information is usually considered a public good. We apply both theoretical models and experiments to study how raters' feedback behavior responds to different reporting costs and how to improve market efficiency by introducing a pre-commitment device for sellers in reputation systems. In particular, the pre-commitment device we study here allows sellers to provide rebates to cover buyers' reporting costs before buyers make purchasing decisions. Using a buyer-seller trust game with a unilateral feedback scheme, we find that a buyer’s propensity to leave feedback is more sensitive to reporting costs when the seller cooperates than when the seller defects. The seller’s decision on whether to provide a rebate significantly affects the buyer’s decision to leave feedback by compensating for the feedback costs. More importantly, the rebate decision has a significant impact on the buyer's purchasing decision via signaling the seller's cooperative type. The experimental results show that the rebate mechanism improves the market efficiency

A Dollar for Your Thoughts: Feedback-Conditional Rebates on eBay

We run a series of controlled field experiments on eBay where buyers are rewarded for providing feedback. Our results suggest that the feedback rate increases when a rebate is given, though the effect is small. Moreover, the nature of buyer feedback is influenced by rewards: buyers are more likely to give positive feedback following a high-quality transaction (fast shipping) and less likely to give negative feedback following a low-quality transaction (slow shipping). In sum, you can buy feedback but you cannot buy unbiased feedback

Decision Making Using Rating Systems: When Scale Meets Binary

Rating systems measuring quality of products and services (i.e., the state of the world) are widely used to solve the asymmetric information problem in markets. Decision makers typically make binary decisions such as buy/hold/sell based on aggregated individuals' opinions presented in the form of ratings. Problems arise, however, when different rating metrics and aggregation procedures translate the same underlying popular opinion to different conclusions about the true state of the world. This paper investigates the inconsistency problem by examining the mathematical structure of the metrics and their relationship to the aggregation rules. It is shown that at the individual level, the only scale metric (1,. . . ,N) that reports people's opinion equivalently in the a binary metric (-1, 0, 1) is one where N is odd and N-1 is not divisible by 4. At aggregation level, however, the inconsistencies persist regardless of which scale metric is used. In addition, this paper provides simple tools to determine whether the binary and scale rating systems report the same information at individual level, as well as when the systems di®er at the aggregation level

Decision Making Using Rating Systems: When Scale Meets Binary

Rating systems measuring quality of products and services (i.e., the state of the world) are widely used to solve the asymmetric information problem in markets. Decision makers typically make binary decisions such as buy/hold/sell based on aggregated individuals' opinions presented in the form of ratings. Problems arise, however, when different rating metrics and aggregation procedures translate the same underlying popular opinion to different conclusions about the true state of the world. This paper investigates the inconsistency problem by examining the mathematical structure of the metrics and their relationship to the aggregation rules. It is shown that at the individual level, the only scale metric (1,. . . ,N) that reports people's opinion equivalently in the a binary metric (-1, 0, 1) is one where N is odd and N-1 is not divisible by 4. At aggregation level, however, the inconsistencies persist regardless of which scale metric is used. In addition, this paper provides simple tools to determine whether the binary and scale rating systems report the same information at individual level, as well as when the systems di®er at the aggregation level