Tech Competition Simulation
This simulation is about market structure concepts and fundamental market dynamics. It includes mergers and acquisitions within the same industry and their impacts on market dynamics. Each round represents a year of activity for their company in the computer market. Students in teams will have a look at historical data during the first round. They have access to ten years of historical data, and in particular, they can see how many computers were sold per year with an Intel core and an AMD core. They can have access also to the amount of aggregated spending on marketing that happened each year in the past ten years for the whole industry.
Introduction - 30 minutes
Game Play - 1 hour to 1.5 hours
Debrief - 45 minutes to 1 hour
They do not have firm-level data, as it would be costly – or even impossible for private companies – in the real world. Teams could share this information with other teams voluntarily, allowing professors to introduce the concept of collusion, for instance, and the international regulations on business information availability. During each round, teams decide four parameters in two categories: production and marketing.
When teaching Microeconomics, Business or Industrial Organization, teachers may feel a little lonely in the classroom when addressing the concepts around the market structure (pure and perfect competition, monopoly, oligopoly) (de Marcellis-Warin et Warin 2020). Teachers often use mathematical formalization to show the differences between these concepts. Using the mathematical toolbox may help some students, and may confuse some other students even further. The same issue is even more prominent when teaching MBA students or business management students overall, as these concepts seem pretty loosely defined when mathematics is not part of the pedagogical toolbox as it is the case for most management courses. In the literature, it is more and more recognized that experiential learning would provide students (in management and economics majors) a better understanding of the critical concepts and analytical frameworks (Lokhande, Cadotte, et Agrawal 2019).
This simulation is by Prof. Thierry Warin, Professor in Data Science for International Business at HEC Montréal