1. Discussion of: How do Platform Participants respond to an Unfair Rating? An Analysis of a Ride-Sharing Platform using a Quasi-Experiment
Anuj Kapoor and Catherine Tucker By
Qiang (David) Gao
Baruch College, City University of New York

2. Summary
Study how biased negative reviews from taxi riders affect taxi driver’s behaviors using six-month a taxi-sharing data.
Exploit the driver replacement
It may cause rider to give biased lower ratings
Examine the effect of biased lower ratings on driver’s response
Negative response to biased lower rating (i.e., less driver efforts) leads to more lower ratings
Investigate the consequence of biased lower rating
Drivers are more likely to leave the platform

3. From https://thepointsguy
From If you’re a driver, well, if your rating goes below a certain threshold, you won’t be driving for much longer. Uber is encouraging riders to be more fair when it comes to rating their UberPool driver. Say, for example, you request an UberPool and aren’t happy with the rider(s) you got paired with and gave the driver a lower rating because of it. Now, if you don’t give a five-star rating to your UberPool driver, you’ll be able to give more feedback on why you rated the way you did.

4. from https://www. theverge
from incentivized-reviews-ban-vine-program-product-biasAmazon Amazon is cracking down on biased customer reviews Yet studies have shown that incentivized reviewers are less likely to give products negative feedback and review hundreds of products on average, potentially affecting the overall sales performance of otherwise mediocre items.

5. Importance Important question to study.
Most existing studies regarding peer reviews focus on
The reliability of review ratings
The impact of review
The impact of biased positive review
How about the impact of biased negative reviews?

6. Comments Comment #1: Biased review definition
Comment #2: Selection issue
Comment #3: Result interpretations and alternative models

7. Comment 1: Biased review definition
Negative Rating Biased Rating
Current definition
Biased rating: Drivers with 5* ratings earlier but lower rating later as replacements
Original argument: “a bad review is often an absent review”
Using other drivers’ reviews as benchmark?
Using all rating levels?
Negative reviews
About drivers or other things?
Any text?

8. Comment #2: Selection issue
Current data:
Total 550,000 trips
3% of these trips reassigned
Many missing reviews after reassignment
Selection biases?

9. Comment #3: Results interpretations and alternative models
Result interpretations
Some interpretations need to be clearer
e.g., Using IV will increase driver negative responses effects, why?
Some results need further explanations.
e.g., “drivers with a low rating are not more likely to leave the platform than the drivers with higher ratings”.
How large is this effect?
It may be better using standard deviation.
Alternative models
To verify LPM, conditional logit model with individual fixed effects.

10. Thank You!