Structural change in the presence of network externalities: a co-evolutionary model of technological successions

Abstract

The paper examines the conditions under which technological successions can occur in the presence of network externalities. A two-stage, multi-agent simulation model is presented in which product designs co-evolve with consumer preferences. It provides a rich framework in which to study the complex phenomenon of quality. Following an initial period, in which old technology firms develop their designs and externalities accrue, a technological shock occurs. New technology firms and new consumer classes enter the market. Data from the simulation model is analysed by identifying a robust econometric model of the probability of succession, given the immediate state of the post-shock market. 4 factors affecting the probability of a succession are identified. First, succession can occur if gains in direct utility from higher quality new technology goods outweigh the network utility of old technology goods. Second, sailing ship effects are possible. Old firms can innovate in order to see off the new entrants. Hence, a better initial (new technology) design does not guarantee succession. Third, a trade-off exists between quality and price. A succession will not occur if cost (price) differentials favour the old technology. Consequently, increasing returns in production enjoyed by established firms are an important barrier to successful entry. The fourth factor is time: the relative length of time old firms have to develop their products, and that which new firms have to develop their products.

A complex systems methodology to transition management

“…The methodology we proposed is complementary to alternative decision-theoretic approaches, such as real option theory, which are based on more stringent assumptions about agents' computational power and the information available to them (Trigeorgis 1996). Furthermore, our prospective approach can supplement other empirical methodologies in the field of transition management (Kemp 1994;Geels 2002;Hekkert et al 2007;Markard and Truffer 2008) as well as simulation models on technological transitions (Windrum and Birchenhall 2005;Van den Bergh 2007;Faber and Frenken 2009;Struben and Sterman 2008).…”

Incorporating social context and co-evolution in an innovation diffusion model—with an application to cleaner vehicles

“…Windrum and Birchenhall (2005) however, move ahead by presenting a multiagent framework that explicitly models consumers and firms. In their model, the nature and direction of technological innovation is determined by the interaction of heterogeneous consumer preferences and heterogeneous firm knowledge bases at the micro level.…”

“…However, demand and supply can be considered as two populations of (attributes of) actors that co-evolve (Saviotti 2005;Windrum and Birchenhall 2005;Dijk and Kemp 2010;Dijk and Yarime 2010;Safarzynska and Van den Bergh 2010). When we speak of demand and supply we thus mean the demand side and supply side.…”

“…This type of model includes (random) events and learning, which result in changes in the techno-economic characteristics of the technologies. Recently, some models of this type incorporated evolution of consumers, referred to as co-evolutionary modeling (Windrum and Birchenhall 2005;Windrum et al 2009a, b).…”

Cellular Automata with network incubation in information technology diffusion

“…Some important references, among others, are Young (2003), Moldovan and Goldenberg (2004), Newman (2003), Windrum and Birchenhall (2005), Boccara (2004), Boccara et al (1997), and Wolfram (1983). In particular, Cellular Automata are special models within Complex Systems theories.…”