Agent-based Simulation Design for Technology Adoption

The global consequences of climate change calls
for adoption of new technologies across all sectors of society.
However, it is important to know how fast new technologies are
adopted to reach the political climate goals. This paper
presents a method for designing agent-based simulations for
studying technology adoption. The method includes the design
of simulation population, agent adoption logic, and external
factors influencing agents’ adoption decisions. A case study of
the Danish commercial greenhouses’ adoption of a smart
energy solution is investigated. The result is presented with
Roger’s technology adoption curve which can be used to
demonstrate the desired adoption rate by regulating different
simulation parameters. The adoption rate of 50% with the
return on the investment of 3 and 5 years is investigated. The
greenhouse segment of growing pot plants with an area of more
than 20,000 m2 is found to be the innovators. The simulation
result shows that the population categories of the ‘innovators’,
‘early adopters’, and ‘early majority’ don’t change between the
return on investment time of 3 and 5 years. Furthermore, the
relation of the return on investment time and the initial cost is
close to linear. Hence, a lower/higher initial cost will result in a
shorter/longer return on investment time.