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A lot of factors:

1) People definitely did get away with this, all the time. Historically, researchers had no obligation (at least that was practically enforced) to maintain and share their data and code. Peer review would check for specific methodological flaws and nothing deeper. If someone emailed you about your 1995 study in 2005, you'd say "I no longer have the code," or, more likely, simply never email them back.

2) In a highly competitive landscape where cheating is effective, the "winners" will be heavily selected for willingness to maximize the use of cheating. Even if only 1% of the population is willing to commit explicit fraud, that 1% is going to be heavily overrepresented in a world where explicit fraud gets you the top-tier publications that bring you to prominence.

3) Ariely and Gino both made millions of dollars from their fraud that they will not have to give back. It's worth emphasizing how poorly Ariely's fraud was executed -- he did the laziest possible fraud and easily converted it into money and prestige.

4) Related to the first point, it's hard to overstate how much the culture has shifted since the '08-'12 time period. The replication crisis was just kicking into gear, and only among people who were paying attention to that type of thing. Ariely didn't come up reading Andrew Gelman's blog. There's simply far more light on any paper today than there would've been 10 years ago -- statistical and methodological understanding have come a long way as cohorts of academics came up in the shadow of the replication crisis. Having established credible groups like Data Colada to centralize these analyses has also been a big deal; tenured profs can't bully Data Colada by threatening their career progression the same way they could if accused via email by a random grad student.

I agree with most of your comments but perhaps with a different emphasis, and you're right, some people do get away with falsifying data but the risks are very high when that data actually matters and is subject to scrutiny.

I amplify my comments below in my reply to droopyEyelids.

I think the missing piece is your belief that "As sure as day follows night, they'll eventually get caught"

Academic research is sort of a "Tyranny of Structurelessness"[1] system where people can't risk alienating themselves from the underlying power structures or it'll destroy their career. On top of that, there isn't a good mechanism to report fraudulent research. So when someone finds a paper that can't be replicated, the sensible thing to do is ignore it and move on. Causing a ruckus will get them labeled a troublemaker, and there isn't any guarantee it'll make a difference.

And further, there are no material incentives for exposing a bad paper. It doesn't get the researcher another citation which is their currency. It just wastes time they could have spent working towards a new paper of their own.

https://www.jofreeman.com/joreen/tyranny.htm

I essentially agree with what you say, similarly bweing's comment above but despite that committing scientific fraud is just such a risky business. If one falsifies results and the subject matter turns out to be irrelevant in the grand scheme of things one might get away with it because it is irrelevant. — no one would care anyway. If it's high profile and contentious then one's likely to get caught out either sooner or later.

Let's take two cases. The Piltdown man fraud took place in 1912 and it wasn't until over 40 years later in the '50s that it was conclusively determined as a fraud, it then took about another 60 years to determine who the fraudster was. Right, the fraudster got away with the deception in his lifetime but he goes down in history with his reputation in tatters. Whether he considered this or not or perhaps he was hoping to be discovered and wanted to get himself in the history books when his name would otherwise be lost to history is a moot point.

Now to the infamous Jan Hendrik Schön https://en.m.wikipedia.org/wiki/Sch%C3%B6n_scandal. He was caught out quickly. My background is electronics so I understand what he did and I can say his chances of getting caught were damned high and he was caught. He must have known the risk he was taking, how could he not when the fraud was intrinsically recognizable by its nature? Then he makes his situation worse by virtue of repeating the fraud many times, so he was left without a 'plausible deniability' defense on grounds of a mistake/error/mix-up etc.

He's obviously not completely stupid or he wouldn't have been in that job. I'll rephrase that, he's not so stupid that he wouldn't recognize the risks. So why did he ruin his reputation? He deliberately shot himself in the foot without good reason—unless his reason was to become notorious.

People may think they can get away with faking data but if it's in a high profile field with others hanging off their results things will go pear-shaped very quickly. Remember, we've had excellent tools like Benford's Law for years and that's damned good at detecting forged data: https://en.m.wikipedia.org/wiki/Benford%27s_law.

Knowing what I know there's no way I'd risk my reputation faking data, I'd forever be living fear of being caught out. Moreover, I wouldn't do it for ethical reasons, as in the end I'd be not only cheating others but also myself.

You are assuming that the rest of the researches are interested in exposing them. They may be in the same boat (institutions), paid by the same people to produce similar "research".

Notice the terrible punishment that happened to Ariely: https://scholars.duke.edu/person/dan

Hint: not much happened.

Still on the faculty roster. Still "Distinguished Professor of Behavioral Economics".

So why not fake data and cheat? You might get discovered, but by then, you'd have given tons of TED talks, speaking engagements and probably made millions of dollars. You get to keep that and you get coast relax as a professor for the rest of your life.