Word-of-Mouth Networks and Adoption Cascades

Abstract

We examine how word-of-mouth learning may lead to uniform and possibly inefficient actions in finite time among a network of agents. In our model, agents are identically informed a priori and observe network neighbors’ actions as well as the payoffs of some or all of those actions (a stylization of word-of-mouth communication of product choice and consumption experience). We identify conditions under which actions become uniform in finite time, in which agents disregard observed payoffs and imitate observed actions. Our results also allow us to interpret critical mass and network brokerage effects through word-of-mouth learning without invoking extraneous utility assumptions.