Abhijit Sengupta

A large number of modern consumer focussed industries are characterised by fast paced technology driven innovations - smart phones and other computing devices, software, home audio and video technologies, automobiles, pharmaceuticals etc. being a few notable examples. Such industries are research driven and are characterised by their unique technological ecosystems. Competition within such industries is not limited to pricing and marketing strategies alone, but is driven by R&D as well, whereby new features, new variants and upgraded technology is c onstantly being introduced to attract customers (Frambach, 1993). Consequently, firms often tend to use the existing intellectual property (IP) framework within their industries as a standard tool against rivals - both for defensive and offensive purposes (Litchenber, 2002).

We study the evolutionary dynamics of brand competition in a market where two firms are competing against each other. A brand's strategy at each period could be either to innovate on its own or to copy the rival or maintain the same position as before. Consumers are heterogenous, they interact with each other, and under bounded rationality choose one of the products every period, based on their characteristics and price. A multi-agent simulation has been designed under three specifications - no network, a random network and a 2-level network. The cases of no networks, random networks and 2-level networks of different densities give very different results in terms of attainment of equilibrium. Moreover, convergence is always more frequent and faster in case of dense 2-level networks and in the case of sparse random networks. It was also noticed that a skew in the distribution of consumers in the characteristics space leads to more variation in equilibrium values as well as in the likelihood of convergence