When is the right time to risk everything on new technology?
“Timing is everything” when a company plans to invest in new technology. New models based on mathematics and economic theory can help them hit the bull’s eye.
When is the best time for investing in new technology or new products? That question concerns a lot of companies.
The investments at stake are often huge, and the negative consequences can be many if the timing or technology chosen is the wrong one.
– There are general investment models for calculating the profit at different points of time. But it is definitely challenging to find the exact best moment. Calculating the optimal timing is a comprehensive study, says Espen Stokkereit.
He has a master’s degree in economics and recently finished his PhD in mathematics, where he has combined the two disciplines and developed methods aimed to simplify hitting the right moment for investmests. Amongst his collaborators is researcher Kristina R. Dahl at the Department of Mathematics at UiO.
– Obviously there is a lot of uncertainty as to what is the smart thing to do. We don’t know how the future unfolds.
However, Stokkereit has redrafted the mathematical equations to eliminate the uncertainty. His studies show that regardless of changes, the model will work.
Exposed to competition or not?
Stokkereit’s model shows that the main analytical evaluations needed prior to investing in new technology, concern whether or not your field is exposed to competition - and if there are different technologies to choose from.
His starting point is a model with two companies, a so-called duopoly model, and he has looked at it from the perspectives of both.
– The choice of company A will affect company B – and vice versa. If company A invests in one technology, company B will often pay close attention to see if that investmest was a good one and make their choices with this in mind. Should they copy company A or take another path?
The fact that many will choose to evaluate their competitor’s outcome before they make their own investments, results in a tendency to postpone investments for companies who lack monopoly in their market.
When Apple outsmarted Nokia
As one example of this dynamics, Stokkereit points to Apple’s introduction of the smartphone Iphone in 2007. Until that point Nokia had dominated the cell phone market. The Finnish gigant had little faith in the Iphone at first and did not change their own investment plans.
Other competitors, like Samsung, were quicker to invest in smartphones. Nokia first invested in similar technology when Iphone was already a mega success. That turned out to be too late.
– Apple was the innovator, the one to make the first move. Nokia had to find out if they would copy Apple’s choice or go in another direction. In the end they chose to copy Apple’s technology, but the long timespan gave Apple an important period of near monopoly. This delay was expensive for Nokia.
A big risk for the innovator
Stokkereit points out that there is a big risk in being the innovator. Yet at the same time the innovator can get a head start and experience a period of approximate monopoly if they succeed.
– But it’s cheaper and easier to copy the innovator, who has often spent a lot of time and resources. The companies that follow in their path also have knowledge of how things turned out for the innovator.
Stokkereit emphasises the importance of understanding which elements to consider for the model to capture what you are interested in without complicating the picture. In the real world there are also other factors, like politics, legislation and regulations, to consider. Also it is crucial whether one’s approach is of a social economic or business economic perspective.
– This is obviously complicated, there are oceans of different choices. Mathematic models can’t give all the answers, but they can be a guide, says Stokkereit.
Better models with interdisciplinary research
Stokkereit’s supervisor Nils Christian Framstad at the Department of Economics indicates that analysis of large investments has become a large and important field of expertise.
– We know that mathematical and statistical models are more widely used, for instance by banks and other financial institutions that model the behavior of companies, he says. He underlines the importance of getting an overview and at the same time cultivate and understand the different parts.
According to Framstad, mathematics and statistics play a crucial role in economic models.
– This shows the importance of Stokkereit’s bilateral competence. His PhD is an important contribution pulling things in the right direction.
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