Does new product growth accelerate across technology generations?

Abstract

The academic literature on the growth acceleration of new products presents a paradox. On the one hand, the diffusion literature concludes that more recently introduced products show faster diffusion than older ones. On the other hand, technology generation literature argues that growth rate, at least as measured by diffusion parameters, remains constant across generations. We resolve this apparent paradox by testing whether growth acceleration occurs across technology generations while controlling for the passing of time. We check acceleration across 39 distinct technology generations in 12 product markets. The results show that intergeneration acceleration occurs in time to takeoff but not with respect to Market Lett (2010) The Wharton School, University of Pennsylvania, Philadelphia, PA, USA e-mail: peresren@wharton.upenn.edu diffusion parameters (i.e., p and q). We show that takeoff acceleration is mostly driven by technology vintage (i.e., the passage of time) rather than generational shifts. Thus, time is a factor that accelerates early growth, but generational shifts do not. This result also holds when controlling for the effects of market vintage when the market is either business-to-business or business-to-consumer as well as when the technology is process-or product-based.

Dynamic Model of Markets of Successive Product Generations

“…This characteristic is evident in the empirical sales data (triangles) fitted by the solid line. Investigations of multiple generations also suggested that their unit sales exhibit a nearly equivalent initial growth phase [37]. This is also the case here.…”

The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries

“…In the following sections, after describing the data, we will start by investigating the differences in the patterns of MSN adoptions across four G7 countries, 6 by estimating the Bass parameters of innovation, p, and imitation, q, together with their ratio, q/p (see Stremersch, Muller, & Peres, 2010;Stremersch et al, 2007). We will then investigate the existence and role of network externalities for these diffusion processes using the Gamma/Shifted Gompertz curve approach (Bemmaor, 1994;Bemmaor & Lee, 2002), with a specific focus on the role played by the skew parameter α (Meade & Islam, 2008).…”

Measuring the duration of formative phases for energy technologies

“…This result contributes to the debate on accelerated diffusion. Studies of multiple consumer durables show no evidence of a shorter incubation time (Kohli et al, 1999) or of diffusion acceleration over time (Stremersch et al, 2010;Peres et al, 2010). However, Golder and Tellis (1997) find evidence of decreasing time to takeoff of products introduced after World War II, and Meade and Islam (2006) similarly discuss studies that suggest an increase of diffusion speed over the past century.…”