Trade-In Programs in the Context of Technological Innovation with Herding

Abstract

We study optimal pricing strategies and consequent market shares’ dynamics in a transition from an old and established technology to a new one. We simulate an agent-based model, in which a large population of possible buyers decide whether to adopt or not depending on prices, private signals and herding behavior. The firm, on its part, sets prices to maximize revenues. We show that trade-in programs, in practice comparable to very aggressive discounts, are supported by a rational attitude

Measuring Brand Awareness in a Random Utility Model

“…In order to compute the values of s and x at the equilibrium, we rely on a random utility model inspired by [4,12]. In detail, for each single actor i = 1, ., N, we set…”

“…This eventually results in setting a non-cooperative game, in which each agent makes his choice given an expectation of the population outcome. Similarly to [12], agents do not communicate or coordinate, rather each individual knows the common distribution of the heterogeneous shocks j , for j = i. In other words, we impose rational expectations: each agent has a correct belief about others' preferences; moreover, we assume that each agent shares the same expectation about other player's actions f .…”

“…h The presence of multiple equilibria is due to the non-linearity of the system (7) and has significant consequences on the strategic behavior of firms (see, for instance, [12]). In standard random utility models, it is shown that for {q A , q B } large enough, multiple equilibria may appear.…”

“…In particular, actors are prone to imitate the behavior of the majority, thus, proving to be influenced by social interactions in their decision-making. In [12], the Brock and Durlauf paradigm is transferred into a game-theoretical language, thus highlighting the strategic behaviour of a large population of players subject to social interactions.…”

“…In the present paper, we extend the model in [12] to the case of a duopoly: two competitors, characterized by different levels of brand awareness and prices, offer a new technology on the market. These quantities enter as parameters into a wellposed random utility model and, eventually, shape the level of market shares for the two technologies at the equilibrium.…”