Strategic interaction
> Making Game Theory work for managers
INCREASINGLY, corporate managers have to tackle more difficult business situations. Established businesses are intentionally targeted by startups using disruptive technologies and novel business models to upset the industrial order and trigger shifts in demand, industrial capacity, and market prices. And the kneejerk reaction of managers is to take the rational approach: to anticipate a range of outcomes based on probable decisions by key stakeholders and to collate the advantages and disadvantages of each option. But, myriad issues suggest there is no single and precise answer to any problem. In this article, we discuss why Game Theory (GT) may provide an informed support to any decision by managers.
Originally, GT addressed zerosum games, in which one person’s gains result in losses for the other participants. Later, GT became the study of mathematical models of conflict and cooperation between intelligent rational decisionmakers. The theory did not really exist as a unique field until the paper by John von Neumann in 1928. In 1944, he co-wrote Theory of Games and Economic Behavior with Oskar Morgenstern. Since then, GT has been widely applied. Applications include a wide array of economic phenomena and approaches, such as auctions, bargaining, mergers and acquisitions, pricing, fair division, duopolies, oligopolies, social network formation, and across such broad areas as political economy, experimental economics, and industrial organisation.
In business settings, GT has been applied rationally to derive predictions of behaviour for all players. It does so by seeking some form of equilibrium, or balance, based on a specific set of assumptions. Then it tries to predict the most likely scenario. A game of GT must specify the following elements: the players of the game, the information and actions available to each player at each decision point, and the payoffs for each outcome. A game theorist typically uses these elements, along with a solution concept of their choosing, to deduce a set of equilibrium strategies for each player such that, when these strategies are employed, no player can profit by unilaterally deviating from his strategy. For instance, in economic environment of oligopoly, when control over the supply of a commodity is in the hands of a small number of producers, the actions to be taken by players would affect the key metrics such as revenues, prices, and expenses. These equilibrium strategies determine an equilibrium to the game – a stable state in which either one outcome occurs or a set of outcomes occur with known probability. So, there will be a series of “snapshots”. For example, a local retailer faces a new player planning to open its own store in the same neighbourhood. Depending on assumptions (e.g. value propositions, channels, cost structures, customer demand), several scenarios and strategies may be drawn. The probable scenarios include: the retailer to cut prices to retain the market share; “wait-and-see” the actions of the newcomer and then secure the greatest value by reacting properly.
However, the bone of contention of GT is the assumption that all players will act rationally. In reality, human nature is competitive. An additional scenario to the earlier example is to allow the newcomer to exist in a particular niche where the local retailer is weakest. For instance, the newcomer is an e-commerce and the incumbent is brick-and-mortar. Due to competitive nature of business, the incumbent retailer will likely shift its best strategy from coexistence to counterattack when the market is increasingly favouring the e-commerce channel.
Nevertheless, GT provides the corporate decision makers with informed support for a wide range of behavioural relations: to decide whether to market a product