Responding to Unfair Ratings on Ride-Sharing Platforms
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Anuj Kapoor and Catherine Tucker
By
Qiang (David) Gao
Baruch College, City University of New York
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
From https://thepointsguy.com/2017/04/uber-changing-rating-system/
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.
from
https://www.theverge.com/2016/10/3/13155578/amazon-
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.
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
?
Comments
•
Comment #1: Biased review definition
•
Comment #2: Selection issue
•
Comment #3: Result interpretations and alternative models
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?
Comment #2: Selection issue
•
Current data:
•
Total 550,000 trips
•
3% of these trips reassigned
•
Many missing reviews after reassignment
•
Selection biases?
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.
Thank You!
Study investigates how biased negative reviews affect taxi drivers' behaviors on a ride-sharing platform, leading to consequences such as lower ratings and drivers leaving the platform. Platform participants' responses to unfair ratings are analyzed, highlighting the importance of fair feedback and its impact on driver performance.
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Presentation Transcript
Discussion of Discussion of: : How do Platform Participants respond to an How do Platform Participants respond to an Unfair Rating? An Analysis of a Ride Unfair Rating? An Analysis of a Ride- -Sharing Platform using a Quasi Platform using a Quasi- -Experiment Sharing Experiment Anuj Kapoor and Catherine Tucker By Qiang (David) Gao Baruch College, City University of New York
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
From https://thepointsguy.com/2017/04/uber-changing-rating-system/ 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.
from https://www.theverge.com/2016/10/3/13155578/amazon- 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.
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?
Comments Comment #1: Biased review definition Comment #2: Selection issue Comment #3: Result interpretations and alternative models
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?
Comment #2: Selection issue Current data: Total 550,000 trips 3% of these trips reassigned Many missing reviews after reassignment Selection biases?
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.
