iiinova — where your digital self keeps evolving

Reposted by Michelangelo Rossi

Brett Hollenbeck @bretthollenbeck.bsky.social · 11/07/2025

🚨Free data alert!! 🚨 Please share. Large new dataset of Amazon product reviews, including full text and photos and product characteristics, with individual *reviews labeled as fake reviews*. I believe this is the first publicly available data of this kind. github.com/bretthollenb...

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Reposted by Michelangelo Rossi

Leonardo Madio @leonardomadio.bsky.social · 03/01/2025

📢 Su Lavoce.info con miei coautori @kdbtran.bsky.social @micherossi.bsky.social and Mark Tremblay approfondiamo un tema cruciale per il mercato digitale (partendo da un nostro recente studio empirico): come la trasparenza nelle piattaforme influisce sui prezzi e sull’efficienza del mercato.

lavoce.info

Home page - Lavoce.info

Ultimi articoli Lasciamo parlare i dati Fact-checking I commenti dei nostri redattori

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Reposted by Michelangelo Rossi

Aaron Roth @aaroth.bsky.social · 30/12/2024

EC 2025 will be held at Stanford from July 7-12. Itai Ashlagi and I are the chairs. The abstract deadline is February 3, and the paper deadline is February 10. The scope is inclusive of many topics across CS, economics, and operations research. Submit your best work!

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Ananya Sen @ananyasen.bsky.social · 18/12/2024

My first post on Bluesky! Excited to share my paper with Yixing Chen and Xiaoxia Lei "Trade-offs in Leveraging External Data Capabilities: Evidence from a Field Experiment in an Online Search Market" has been accepted for publication in Management Science! papers.ssrn.com/sol3/papers....

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Michelangelo Rossi @micherossi.bsky.social · 17/12/2024

Holding the supply side fixed, transparency helps consumers and could also reduce overall prices, but if sellers change prices due to the policy, things can get tricky ...

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Michelangelo Rossi @micherossi.bsky.social · 17/12/2024

⏳ Only 3 days left to submit your paper for the Paris Conference. 🗼✨ www.digitaleconomics-paris.fr/conference-2...

digitaleconomics-paris.fr

Digital Economics Paris - Conference 2025

Paris Conference on Digital Economics

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

Thanks! I agree: price increases are not necessarily welfare decreasing (especially for sellers). Moreover, it is hard to measure the reduction of guests’ search costs with more transparency… so any welfare analysis is very complex in this framework

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

Curious to learn more?☝️ Check out the full paper: papers.ssrn.com/sol3/papers.... We uncover a fascinating mechanism linking transparency to pricing strategies in digital markets. Feedback and thoughts are welcome!

papers.ssrn.com

Transparency of Add-On Fees on Peer-to-Peer Platforms: Evidence from Airbnb

This paper investigates the impact of price transparency on equilibrium prices and fees by considering a policy change implemented by Airbnb that affected the t

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

Policy implications: Price transparency isn’t universally good or bad. While it reduces search costs and obfuscation, it can also lead to price increases in some cases. Regulation needs to consider both demand-side and supply-side effects carefully.

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

The core insight: transparency changes how hosts (not just guests) look at prices. When rivals’ total prices are clearer, hosts adjust their strategies. This is especially impactful in peer-to-peer platforms where pricing frictions exist and some hosts and guests might be naive or have search costs.

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

Key results: • Listings with high cleaning fees reduced them by 2-4% post-policy.⬇️ • But listings without cleaning fees raised their nightly prices by 5-6%.⬆️ Why? Greater transparency let some hosts realize their prices were too low, prompting increases.

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

Airbnb hosts set nightly prices and cleaning fees. Before 2019, EU guests only saw cleaning fees at checkout. After a regulatory push, Airbnb made these fees visible upfront. Using a difference-in-differences approach, we studied the impact on prices and fees.

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Michelangelo Rossi @micherossi.bsky.social · 16/12/2024

How does price transparency affect a market?🤔 In our new paper, Kevin Tran, @leonardomadio.bsky.social, Mark J. Tremblay, and I analyze Airbnb’s policy change in the EU, where cleaning fees became fully transparent. The surprising finding: transparency doesn’t lead to lower prices. Here’s why:

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

📚 Overall, our work sheds new light on how consumer heterogeneity shapes online ratings and offers practical solutions to improve rating systems. We’re excited to see it published in Management Science! (14/15) #Ecommerce #Ratings #ConsumerBehavior #ManagementScience #DataScience #IMDb #MovieLens

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

📊 Our findings have important implications for platform design. By understanding these biases and applying corrections, platforms can deliver more reliable ratings, benefiting consumers and (high-quality) producers alike. (13/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

💡 Conversely, simply overweighting the ratings of experienced users, a common practice on several platforms, can actually backfire, further penalizing high-quality movies. (12/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

Yes! Once debiasing the ratings, this movie’s rating goes up! In particular, this movie is one of the biggest “winners” of our debiasing procedure. (11/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

🎞️ A notable case of this bias? The French movie "The Unknown Girl", selected for the Palme d’Or Cannes in 2016, is rated 6.5 on IMDb. That’s relatively low… but is it due to the fact that most of the raters were experienced, stringent users? (10/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

After applying it, the corrected ratings better align with external measures of quality, such as the Oscars and Metacritic scores. It also helped fix those ranking reversals! (9/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

🔄 However pervasive, this bias can be undone. We developed an algorithm to de-bias ratings by adjusting for user stringency. Our approach doesn’t require us to take a stance on users’ expertise. Rather, we let ratings and individual stringencies iterate until they converge. (8/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

📉 It gets worse. Ratings need not just be compressed, they can actually lead to ranking reversals: in about 8% of cases, lower-quality movies get higher ratings than better ones due to this biased. This further skews future consumer choices! (7/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

And since experienced users’ ratings represent a higher share of ratings for higher quality products… IMDb ratings are compressed, that is, they penalize high-quality films compared to their lower quality alternatives. That’s the exact opposite of what we’d like IMDb to do! (6/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

A 7 out of 10 from a user with 10000 ratings is harder to obtain than one from a user with 5 ratings! Absent a normalization, we’re comparing apples with oranges. (5/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

In other words: experienced users choose better movies on average ➡️ they get used to higher quality, and form higher reference points ➡️ they rate more harshly, for any quality level. (4/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

How about ratings' differences between experienced and novice users? This is where it gets interesting. Experience users rate virtually ALL movies more harshly, independent of genre, year, quality, actors, director, and more. (3/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

🎬 We analyzed data from IMDb and MovieLens to examine how experienced vs. novice users choose and rate movies. The findings? Unsurprisingly, experienced users tend to watch higher quality movies on average than their novice peers. (2/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

Have a look at this example: everyone agrees product A is better… and yet product B gets better ratings. Do we also see this in real-world data? (1/15)

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

We dive deep into how aggregating the online ratings of consumers with different experience levels leads to surprising biases. It’s a long paper – with theory, data, and a debiasing algorithm at the end – so, here's a breakdown!👇

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Michelangelo Rossi @micherossi.bsky.social · 09/12/2024

🧵 Excited to share that our paper, "The Good, The Bad, and The Picky: Consumer Heterogeneity and the Reversal of Product Ratings" (joint with Tommaso Bondi and Ryan Stevens), is forthcoming at Management Science!

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Reposted by Michelangelo Rossi

Erik Brynjolfsson @erikbryn.bsky.social · 01/12/2024

Here's a great starter pack of economists working on AI. Who else should be on this list? bsky.app/starter-pack...

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Reposted by Michelangelo Rossi

Jakob Schneebacher @jschneebacher.bsky.social · 08/11/2024

Welcome, new #EconSky joiners! I have updated my starter pack - now with over 120 IO, org econ, innovation and firm dynamics researchers. If you think I have forgotten someone, please let me know. go.bsky.app/Rchu8QX

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Michelangelo Rossi @micherossi.bsky.social · 01/12/2024

Hi everyone! I am Michelangelo Rossi, an assistant prof at Télécom Paris. I’m here mainly to share my research on digital economics, quantitative marketing, and how we can better regulate digital platforms. Feel free to reach out!

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