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Strategy and Game Theory for Management

Indian Institute of Management Ahmedabad via Coursera

Overview

Game theory explores the art of how people make decisions in situations where their choices affect each other. Learn core game theory frameworks through practical application-based learning to transform your and your organization’s performance. With the increasing complexity of today’s world, game theory offers valuable frameworks and tools to navigate uncertainty and establish scientific rigor for strategy. Today, game theory has applications across businesses (advertising, digital markets, mergers and acquisitions, cartels, innovation etc.) along with policy. This course on game theory is developed based on courses being offered at IIMA for the past several years by Prof Viswanath Pingali, an award-winning faculty member at IIMA. This course emphasizes an intuitive approach to game theory rather than focusing on quantitative techniques. This course helps you acquire a competitive edge through enhanced strategic thinking, structured problem-solving, and optimal decision-making in complex situations., The course also discusses behavioral economics insights, where applicable. We try and answer a few questions (not exclusive): (1) Why do price wars happen? (2) What is the problem of commons, and what are its implications for the climate change debate? (3) How do modern businesses operate and what are some implications? (4) Why is culture at firms and economies so difficult to change? (5) What is the unicorn mania that is dominating today’s conversation? (6) Why did some companies offer much larger warranty than the market norm? (7) Why is winning risky in markets with uncertainty and how could information asymmetry lead to market failure?

Syllabus

  • Week 1: Why People Don't Cooperate?
    • This module aims to introduce you to the game theory course. It introduces you to some real-life questions that you can solve by using the concepts we will learn over the course. Following this, the course introduces you to the idea of a game and to some simple games. Subsequently, the module explores the most famous game in game theory: Prisoners’ Dilemma, where smart people find no incentive to cooperate with each other. The module further explores some real-life examples of prisoners’ dilemma. All learning components will be updated upon the official launch of the course
  • Week 2: Nash Equilibrium
    • This module introduces you to the famous concept of Nash Equilibrium. What do you do when there is no Dominant Strategy or Dominated Strategies? Where do thought processes converge? This module further explores several interesting phenomena like Stag Hunt, Battle of Sexes, and Hawk Dove Games. We will explore why some inefficient outcomes happen despite all the players knowing that they are suboptimal. We will also explore questions like whether equilibrium means efficient. All learning components will be updated upon the official launch of the course
  • Week 3: Sequential Games
    • This module introduces you to the games that are sequential in nature. That is, we look at the cases where players alternate in their moves. Further, there are cases where games repeat themselves. We will look further at when we can expect competitors to cooperate in a prisoners’ dilemma situation. We will also explore some interesting games such as the ultimatum game and the trust game. All learning components will be updated upon the official launch of the course
  • Week 4: Games when there is Uncertainty in Information
    • Often, full information is not available, especially regarding the other players. In this module, we will look at scenarios with partial information. We will explore several interesting applications of such games and look into concepts like winners’ curse and adverse selection. We will also explore the link between biology and game theory All learning components will be updated upon the official launch of the course
  • Peer Review Assignment

Taught by

Prof. Viswanath Pingali

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4.9 rating at Coursera based on 19 ratings

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