Adoption of Blockchain Applications Part 1

An experiment about early adopters at MIT and its significance.

 

In 2014, Christian Catalini, an Assistant Professor of Technological Innovation at the Massachusetts Institute of Technology, and Catherine Tucker, a distinguished Professor of Management at the same school, ran a very interesting experiment. The goal of the experiment was to study what happens to a new technology when the technology starts to spread.

During the experiment, 4,494 undergraduate students at the MIT have received funds in Bitcoin equivalent to USD$100 per student. The money came from the MIT Bitcoin Club, which has raised the funds for the experiment from the MIT alumni. To receive the funds, students had to sign up for a waitlist and during the sign-up process they had to answer a number of questions about themselves and the ways they would typically use technology. Students had five days to sign up for the waitlist and about 70% of all MIT undergraduates did so before the deadline. A few weeks later the organizers of the experiment distributed the funds to the digital wallets of the students.

For the experiment to be successful and for its organizers to be able the question about what happens to a new technology and its treatment by early adopters of technology, the organizers needed three things. First, they needed to be able to figure out the natural order and process of adoption of technology. Second, they needed a way to distinguish between early adopters and all other users. Third, they needed information about how various individuals adopt technology over time.

 

Goals and execution of the experiment

To meet their goals, the authors of the experiment randomly chose 50% of students and then delayed giving them the funds in bitcoin by two weeks compared to other 50% of the participants. Neither the students who have received the coins late nor the students who have received the coins two weeks early knew when they would receive the coins when they were signing up to participate in the experiment. When receiving the coins, they also didn’t get any explanation as to why they were receiving them at this very time and as to when others would receive the coins. As a result of this approach, some participants identified by the experiment as early adopters of technology have received their bitcoins two weeks earlier than other early adopters.

To determine who was an early adopter and who was not, the authors of the experiment used data from the surveys and the order in which students signed up to participate in the experiment. The assumption of Catalini and Tucker was that early adopters of technology were likely to sign up right away after hearing about the giveaway while those not particularly interested in technology would sign up closer to the deadline. This way, Catalini, and Tucker labeled the first 25% of those who have signed up as early adopters.

 

How large corporations launch products

The process that the organizers of the experiment used to identify early adopters was similar to how technology companies such as Google and Facebook roll out updates to their users. Typically, tech companies would either have waitlists and distribute new products and services to people who have signed up first or they would identify early adopters by measuring certain data and then creating segments of the users based on the data.

With Apple and its introduction of new products such as new iPhones, the process works in a similar way and is even easier to see and understand because it happens at physical stores of the company. Apple would typically present a new product during a conference or an event and then announce the date when the product will become available at a store. Then, people would make a line in front of the store, which is similar to getting onto a waitlist. On the day Apple makes its products available, those who were in line first get the product first when they walk into a retail store and pay for the product.

 

Results of the experiment

During the experiment, Catalini and Tucker found that most students decided to keep their Bitcoins in the hopes of the price of the coin going up. The cashout rate among the students who got their coins two weeks earlier than others was 9.8% and 9.6% for students who received their coins two weeks later. However, among those whom the authors of the experiment labeled as “early adopters,” the difference was much more significant. It was 10.8% among non-delayed early adopters and almost double that figure, 18.3%, for the students who received their coins two weeks later.

Most of the literature about technology and spreading of technology points out the positive role early adopters play in making the technology popular. For example, a person that stands in line for hours to get a new iPhone is likely to talk about his purchase to his friends and family and tell them how excited he or she is about the device and how many things the device can do. However, the results of the Catalini and Tucker show that when early adopters do not get the technology early, they are likely to ignore the technology. This fact may explain why certain industries may be slow at adopting blockchain technology even though the industries may historically be more likely to adopt new technologies quickly.