📈Business Microeconomics Unit 9 – Game Theory in Strategic Decision-Making

Key Concepts and Definitions

• Game theory studies strategic interactions between rational decision-makers
• Players are the individuals, groups, or entities making decisions in a game
• Strategies are the complete plans of action that players can choose from
• Payoffs represent the outcomes or rewards for each player based on the chosen strategies
• Zero-sum games have a fixed total payoff, where one player's gain is another's loss (poker)
• Non-zero-sum games allow for win-win or lose-lose outcomes (prisoner's dilemma)
• Perfect information games provide all players with complete knowledge of the game's structure and payoffs (chess)
• Imperfect information games involve uncertainty or hidden information (auction bidding)

Historical Context and Development

• Game theory originated in the 1920s with the work of mathematician John von Neumann
• Von Neumann's 1928 paper "Theory of Parlor Games" laid the foundation for the field
• In 1944, von Neumann and economist Oskar Morgenstern published "Theory of Games and Economic Behavior"
  • This seminal work expanded game theory's applications to economics and decision-making
• John Nash's contributions in the 1950s, including the Nash equilibrium, revolutionized game theory
• In the 1960s and 1970s, game theory gained prominence in various fields, such as political science and biology
• The 1994 Nobel Memorial Prize in Economic Sciences was awarded to Nash, John Harsanyi, and Reinhard Selten for their pioneering work in game theory
• Recent advancements include evolutionary game theory and behavioral game theory, which incorporate insights from biology and psychology

Types of Games and Strategies

• Static games are played simultaneously, with players making decisions without knowledge of others' choices (rock-paper-scissors)
• Dynamic games involve sequential decision-making, where players take turns and can observe previous actions (chess)
• Cooperative games allow players to form binding agreements and collaborate (business partnerships)
• Non-cooperative games do not permit enforceable agreements, and players act independently (price competition)
• Pure strategies specify a single action for each decision point in a game
• Mixed strategies assign probabilities to different actions, allowing for randomization
• Dominant strategies outperform all other strategies, regardless of opponents' choices
• Dominated strategies are inferior to other strategies and should be avoided

Nash Equilibrium and Dominant Strategies

• Nash equilibrium is a set of strategies where no player can improve their payoff by unilaterally changing their strategy
  • At Nash equilibrium, each player's strategy is a best response to others' strategies
• In a pure strategy Nash equilibrium, players choose specific actions
• Mixed strategy Nash equilibrium involves players randomizing their actions based on probabilities
• Dominant strategy equilibrium occurs when all players have a dominant strategy
  • In this case, the dominant strategy equilibrium is also a Nash equilibrium
• Prisoner's dilemma is a famous example of a game with a dominant strategy equilibrium
  • Confessing is the dominant strategy for both prisoners, leading to a suboptimal outcome
• Iterated elimination of dominated strategies can help identify Nash equilibria in some games

Applications in Business Decision-Making

• Game theory helps businesses make strategic decisions in competitive markets
• Oligopoly markets, with a few dominant firms, can be modeled using game theory (Cournot or Bertrand competition)
• Pricing strategies, such as price matching or price discrimination, can be analyzed using game theory
• Entry deterrence games explore how incumbent firms can prevent new competitors from entering the market
• Bargaining and negotiation situations, such as labor negotiations or mergers and acquisitions, can be studied using cooperative game theory
• Auction theory, a branch of game theory, helps businesses design optimal auction mechanisms (first-price sealed-bid auctions)
• Game theory can also inform decisions related to advertising, research and development, and supply chain management

Limitations and Criticisms

• Game theory assumes players are rational and self-interested, which may not always hold in reality
• The assumption of common knowledge, where all players know the game's structure and each other's rationality, is often unrealistic
• Game theory models can be sensitive to small changes in assumptions or payoffs
• Some games may have multiple Nash equilibria, making it difficult to predict outcomes
• Behavioral factors, such as emotions, biases, and bounded rationality, are not fully captured by traditional game theory
• Evolutionary game theory and behavioral game theory attempt to address some of these limitations
  • Evolutionary game theory incorporates dynamic processes and population dynamics
  • Behavioral game theory integrates insights from psychology and experimental economics

Real-World Case Studies

• The Cuban Missile Crisis (1962) can be analyzed as a dynamic game of imperfect information
  • The U.S. and Soviet Union's strategies and payoffs were shaped by incomplete information and credible threats
• Airfare pricing among airlines can be modeled as a repeated prisoner's dilemma
  • Collusion to maintain high prices is tempting but unstable, as airlines have incentives to undercut each other
• Spectrum auctions, used by governments to allocate radio frequencies, employ game theory to design efficient allocation mechanisms
  • The FCC's pivotal spectrum auction in 1994 used a simultaneous multiple-round auction format
• Crowdfunding platforms, such as Kickstarter, can be studied using game theory
  • Backers' decisions to pledge funds are influenced by factors such as project quality, social proof, and risk aversion
• The "Tragedy of the Commons" illustrates a social dilemma where individual incentives lead to collective overexploitation of a shared resource (overfishing)

Advanced Topics and Future Directions

• Mechanism design, also known as reverse game theory, focuses on designing rules and incentives to achieve desired outcomes
  • It has applications in auction theory, voting systems, and contract design
• Stochastic games incorporate probabilistic transitions between states, allowing for the analysis of dynamic situations with uncertainty
• Cooperative game theory has advanced with the development of solution concepts like the Shapley value and the core
• Algorithmic game theory explores the computational complexity of finding equilibria and designing efficient algorithms
• Behavioral game theory continues to grow, incorporating insights from prospect theory, hyperbolic discounting, and social preferences
• Experimental game theory uses laboratory and field experiments to test game-theoretic predictions and study human behavior
• Applications of game theory are expanding to areas such as cybersecurity, environmental economics, and public health
• The integration of game theory with other disciplines, such as machine learning and network science, opens new avenues for research and practical applications