# Reviews, Biases and Six-sigma

49 Pages Posted: 25 Jun 2019

See all articles by Ningyuan Chen

## Ningyuan Chen

University of Toronto at Mississauga - Department of Management; University of Toronto - Rotman School of Management

Independent

## Kalyan Talluri

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences

Date Written: June 20, 2019

### Abstract

Reviews for products and services written by previous consumers have become an influential input to the purchase decision of customers. Many service businesses monitor the reviews closely, for feedback as well as detecting service flaws, and they have become part of the performance review for service managers with rewards tied to improvement in the aggregate rating. It is therefore of great importance to understand how much the public ratings reflect true quality of the product or service. Many empirical papers have documented a bias in the aggregate ratings, arising due to various causes: an inherent self-selection in writing reviews, as well as customers' bounded rationality in evaluating previous reviews. While there is a vast empirical literature analyzing reviews, theoretical models that try to isolate and explain the ratings bias are relatively few, and most are based on a rational Bayesian learning assumption on the part of consumers. However, writing a review requires some effort in itself and it seems unlikely that consumers would make the considerable effort to do a Bayesian update of their beliefs before making purchases. Assuming consumers simply substitute the average rating they see as a proxy for quality, we give a precise characterization of the effect of biases in the ratings arising from two sources (i) an acquisition bias, when consumers confound ex-ante innate preferences for a product or service with ex-post experience and service quality and do not separate the two, and (ii) an under-reporting bias, when consumers with extreme positive or negative ratings are more likely to write reviews than consumers with moderate product ratings. We develop a parsimonious choice model for consumer purchase decisions and show that both sources lead to an upward bias. Based on our theoretical characterization, we give two important practical applications for a service firm: (a) estimation of true process quality and its variability for the firm's internal performance, Six-$\sigma$ and quality programs (b) effect on pricing and assortment decisions of the firm, when potential customers purchase based on the biased ratings. Our results give insight into how quality, prices and customer feedback are intricately tied together for service firms.

Keywords: social learning, bounded rationality, choice probability, assortment optimization, pricing, process variability

JEL Classification: D83

Suggested Citation

Chen, Ningyuan and Li, Anran and Talluri, Kalyan, Reviews, Biases and Six-sigma (June 20, 2019). Available at SSRN: https://ssrn.com/abstract=3407477 or http://dx.doi.org/10.2139/ssrn.3407477

Register