The Badge That Taxes Everyone Who Doesn't Wear It

Based on the research ofHeeyon Kim, Qian Wang, and Martina Montauti, "When Certification Backfires: Negative Spillovers on Noncertified Offerings in Airbnb Plus," Organization Science, 2026

In February 2018, Airbnb launched Plus, a certification badge awarded only to listings that passed an in-person, 100-plus-point inspection, in Los Angeles. San Diego did not get the program until that fall. That staggered rollout gave Heeyon Kim, Qian Wang, and Martina Montauti a clean natural experiment: compare revenue at noncertified listings in a city that just got Plus against a city that had not, before and after. The result ran against decades of certification theory that treats a quality signal as, at worst, neutral for everyone who does not hold it. Noncertified listings in Los Angeles lost revenue the moment Plus arrived, not because anything about them had changed, but because something next to them had.

Two Earlier Studies Said the Opposite

Kim, Wang, and Montauti are not the first economists to run the numbers on Airbnb Plus, and that is what makes the finding land. In 2023, Sanjeev Dewan, Jooho Kim, and Tingting Nian published a staggered difference-in-differences study of the same program in MIS Quarterly. They found Plus certification lifted the weekly booking rate of certified listings by about 6.8 percent, and estimated the platform gained roughly 37,500 dollars in annual revenue for the average two-kilometer zone that had one or more Plus listings, compared with matched zones that had none. A year later, Chen Wang, Erica Williams, Jun Xie, and Jing Chen found an even larger effect in Management Science: Plus launches were associated with a 15.8 to 16.2 percent increase in booked nights at the market level, which they attributed mainly to reduced search friction, a benefit they argued reached certified and noncertified listings alike.

Read together, the earlier literature said certification is close to a free lunch: it helps the certified, and it either helps or barely touches everyone else, because a clearer signal for some travelers should mean less wasted search for all of them. Kim, Wang, and Montauti's contribution is to show that the free lunch depends on which mechanism is doing the work. Reduced search friction is real, but so is a second, quieter channel: once a traveler can see which listings Airbnb vouched for, the ones it did not vouch for stop looking merely unverified and start looking suspect. Both mechanisms can operate in the same market. The new paper shows the second one can dominate for the hosts who hold no other credential.

The Contrast Effect, Not the Information Effect

The mechanism the authors isolate is contrast, not disclosure. A badge does two things at once. It tells a buyer something true about the listing that earned it, and it changes the meaning of every listing that did not. Before Plus existed, an uncertified listing's lack of a professional inspection was unremarkable, because every listing lacked one. After Plus launches nearby, the same listing, with the same photos, the same reviews, and the same price, now sits beside offerings the platform itself vetted. The absence of a checkmark becomes informative purely by comparison, and travelers read that absence as a signal of risk the listing never actually carried.

That is why the effect in Los Angeles was not uniform. Kim, Wang, and Montauti find it is attenuated, not eliminated, when noncertified hosts have other credible quality signals available, such as a long review history or an established reputation, when the noncertified listing differs enough from Plus listings that the two are not naturally compared (different price tier, property type, or neighborhood), and when guests have an easy way to substitute off the platform entirely, which lowers how much any single listing's relative standing matters. Each moderator points to the same underlying logic: the harm is proportional to how directly a traveler is invited to put the certified and the noncertified listing side by side and ask which one to trust.

Etsy's Star Seller: The Same Shadow, Untested

Etsy runs a structurally similar program. Star Seller is a badge Etsy reviews and awards on the first of every month, based on the past three months of a shop's customer-service record: message response rate, on-time shipping and tracking, and average review rating, on top of minimum order and sales thresholds. Etsy's own help pages state plainly that the badge does not directly affect search ranking and that shops without it are not penalized. That is the platform's stated intent. Whether it holds up against a contrast effect is an open question nobody has yet run Kim, Wang, and Montauti's kind of natural experiment on. Hypothetically, if two nearly identical mugs sit in the same search results and only one carries a Star Seller ribbon, a buyer comparing them may read more risk into the unbadged shop than its actual return rate or shipping record would justify, exactly the dynamic the Airbnb study documents. No public study has measured this for Etsy specifically, so treat it as a plausible extension of the mechanism, not a confirmed finding.

A badge does not only tell a buyer whom to trust. By elimination, it tells them whom not to.

LinkedIn and Uber: Certification Scaled to Millions

The same mechanism shows up at a different scale once certification stops being a one-time program and becomes permanent platform furniture. LinkedIn began verifying identities with CLEAR in 2023 and, by late 2024, had verified about 55 million of its roughly one billion members, with badges rolling out into the main feed that November. Verification there is not about product quality, it is about identity, but the contrast logic is identical: once a verified checkmark exists at all, an unverified profile does not read as merely unverified, it reads as less vetted than the growing share of the network that now carries the mark, even though nothing about that profile changed the day the program launched.

Uber Pro applies the same logic inside a single workforce rather than across it. Drivers are sorted into Blue, Gold, Platinum, and Diamond tiers based on points and ratings, and higher tiers unlock real, visible advantages, rider-app recognition, priority support, and access to premium trip types among them. Every tier boundary is a small Airbnb Plus: the driver just below the Gold threshold has not changed, but a rider comparing two nearby cars now sees one flagged as more vetted than the other. Multiply one certification boundary into four tiers and you multiply the number of contrast lines running through the same labor pool, each one a place where a status the platform chose to make visible can quietly redistribute demand away from someone who did not fail any standard, they simply sit on the wrong side of a line the platform drew.

What a Platform Owes the Listings It Doesn't Highlight

Airbnb eventually walked Plus back. The program was effectively deprioritized by mid-2020 and formally discontinued on November 6, 2023, replaced by Guest Favorites, an algorithmically awarded badge that updates continuously and reaches roughly two million listings rather than a small, manually inspected set. That redesign looks, in hindsight, like an unplanned fix for exactly the problem Kim, Wang, and Montauti later diagnosed: a badge that reaches a much larger, constantly refreshed share of the marketplace draws far fewer sharp, visible contrast lines than one that crowns a small, static elite. Whether Airbnb retired Plus because of cost, pandemic disruption, or this spillover is not something the record settles, but the shape of its replacement is consistent with taking the contrast problem seriously.

The broader lesson generalizes past any one marketplace. Certification programs are usually evaluated on a single question: does the badge help the people who earn it? That is the wrong question to stop at. The right one is whether the badge changes what everyone without it now appears to be, and whether that change is a cost the platform is willing to own. A quality signal that only ever adds information is free. A quality signal that works partly by contrast is a transfer, from the many who do not have it to the few who do, and transfers need to be measured, not assumed away.