If you had Ames, Iowa on your bingo card for hotbeds of innovation research — Bingo. Indeed the technology adoption curve (aka the most important curve in history) was invented by rural sociologists at Iowa State College some 70 years ago.* A little history. Image
WW2 put pressure on US food supplies, and a variety of technological innovations in agriculture promised improved yields. The rural sociologists were mostly concerned how these improved technologies could be made attractive to farmers, a notoriously skeptical bunch. Image
In the 1940s two researchers at ISC, Bryce Ryan and Neal Gross, conducted field research on how Iowa famers adopted the novel hybrid seed corn. Their report already contained the key ingredients: risk preferences, social contagion, geographic spread, and the logistic curve. Image
Early work focused on the individual decision process and mapped it into 5 deliberation stages: Awareness, Interest, Evaluation, Trial, Adoption; summarized in a special report called "The Diffusion Process" by ISC sociologists Joe Bohlen and George Beal in 1957. Image
An accompanying pamphlet called "How farm people accept new ideas" already proposed to speed up the adoption process by seeding the learning network with a new type of adoption leader, or, as we would call them today: social influencer. Image
In their report, George Beal and Joe Bohlen already delineated the means of communication by which the various types of adopters, clustered by risk preference into five categories, could be reached: from friends and neighbors to salesmen, mass media, and govt agencies. Image
One of George Beal's students at ISC, Everett Rogers, became a professor Ohio State. In 1962 he published a book based on his dissertation called "The Diffusion of Innovations", which became one of the most-cited publications in the social science. Image
Rogers also pointed out the role of the "invisible college", researchers at various institutions sharing a paradigmatic framework, in the diffusion of new knowledge. In the case of the adoption curve itself, that college was mostly made up of Midwestern land grant schools. Image
Ryan and Gross did their early work under the head of the department of economics and sociology, Theodore W. Schultz, the 1979 Nobelist and still the only agricultural economist to receive the prize. Schultz himself was very interested in how farmers picked up new knowledge. Image
But Schultz left Iowa State in 1943 over the fallout of what has become known as the oleomargarine wars, when he took on the powerful Iowa dairy industry. He joined the U Chicago econ program and steered it to national fame, in what might be called the "margarine revolution". Image
So it was left to Schultz's PhD student Zvi Griliches to work out the economic angle of the technology adoption process, which he did with his 1957 Econometrica article "Hybrid corn: an exploration in the economics of technological change", focusing on geographic spread. Image
Everett Rogers later joined the Stanford faculty, which is likely where Geoffrey Moore discovered the adoption curve and added his own "chasm", all while failing to mention those whose intellectual efforts preceded his own.
*As Valente & Rogers point out in their history of the adoption curve, Ames, Iowa might only be the origin of the US research, and the true inventor was more likely French professor Gabriel Tarde with his 1903 book, "The Laws of Imitation". Image
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More from @oliverbeige

Mar 8
That Ukraine thing. I have to admit that I had little to say about the topic, and I didn't pay much attention to frontline shifts or photo-ops in fatigues. The flag-waving and treating the war as some kind of real-life video game was more than a bit unseemly. That said... /1
It was and should've been very clear to anyone with a passing knowledge of strategy that by the time Ukraine switched from a mobile, asymmetric warfare to a grinding trench war of attrition against a resource rich hegemonial power in Nov 2022 its chances of winning evaporated. /2
It's pretty much the last thing one should do in an asymmetric scenario. It still boggles the mind that a major power like the US would misjudge the situation so badly. There was, to stay in the timeframe, the same strategic incompetence on display as during the Corona crisis. /3
Read 21 tweets
Feb 15
There seems to be some trouble understanding the new "transactional" geopolitical stance of the US by those not conversant in politics, strategy, or English. The fundamental idea of a transaction is that it's entered voluntarily and based on an expectation of mutual benefit. /1
If that mutual expectation is no longer given, the transaction is subject to termination or renegotiation, typically at the instigation of the party that no longer benefits – which can also be both parties. /2
An important element to any negotiation is the best available outside option. Beside negotiation skills, divergence in outside options is the key determining factor for how mutually created benefits are divided between parties. /3
Read 7 tweets
Feb 2
I'm mildly amused about the commentariat drawing up Harberger triangles from Econ 101 to "show" that Trump's tariffs are "bad for the economy". That's literally demonstrating that they haven't learned anything new over the last 30 years – or even the last five. /1
Trump has been pretty blunt that he sees the US offshoring its extraction and manufacturing base (its industry for short) as a fatal strategic blunder that sits at the heart of its declining role in the global theater, and that he intends to reverse this. /2
A strategic blunder shared among all administrations of the Reagan-to-Obama era, and the oft-forgotten key element of Trump's political ascendancy was that he pushed the Republican "country club" establishment aside before he did the same with the Democrats. /3
Read 16 tweets
Dec 6, 2024
As a pretty good rule of thumb, you can think of the political travails of most Western economies as a rearguard of an increasingly washed-out center against encroaching, increasingly doctrinary challenges from left and right, with the doctrinary left holding a terrain advantage.
The end of the Hotelling era as I call it, or more popularly, the end of the Merkel era. Left behind by most of the credentialed class that happily moved over to the left-doctrinary camp there's a smattering of hold-outs in the center who cling to dear life for nostalgic reasons.
There's on an abstract level some justification for it. The functioning of a nation state critically depends on an orderly transfer of power, something only a Hotelling competition over the ideological center (the famous "median voter") can provide.
Read 7 tweets
Apr 3, 2024
Emerging public discussion in 🇩🇪 that the internal debate of the German health office @rki_de didn't match the political pronouncements, centering on 17 March 2020 and the call to increase Covid hazard level from "moderate" to "high".

A good opportunity to recapitulate...
...the biggest mistakes that drove the response to the pandemic.

1⃣ The perpetual lack of recognition that we were observing events that had occurred weeks before, and the refusal to account for this.

What exactly happened on March 17? Nothing much in terms of the spread. /2
Like most other countries, Germany started to expand testing rapidly, leading to a massive increase in cumulative numbers, dramatically visualized in dashboards and charts.

But the rate of positive tests (MPC in my nomenclature) stayed mostly the same thru March. /3
Read 44 tweets
Aug 7, 2023
The German health authority @rki_de has evaluated the efficacy of pandemic restrictions it supported, and unsurprisingly it awarded itself a good grade. Overall everything worked out quite well, it says. We looked under the hood and found some surprises. A thread (🇩🇪 below). /1
For starters, in order to show that an intervention had a hypothesized causal effect, a study has to be able to reject the null hypothesis. The null hypothesis generically says that the observed curved, with its ups and downs, was not caused by the hypothesized factors. /2
To reject the null hypothesis in a setting like this, a study has to show two things: that an effect happened after an intervention ("post hoc"), and that it happened because of the intervention ("propter hoc"). The RKI study ignores the first and fails at the second. /3
Read 28 tweets

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