ABSTRACT
Sunley, 2003), the notion of clusters is widely used in economic geography, innovation
studies and related disciplines.
An extensive body of work has focused attention on explaining why clusters exist and
what the main characteristics of “functioning” or fully developed clusters are. Compared
to these static approaches, dynamic views on long-term cluster evolution have received
less attention. Arguably, the question of how clusters develop and change over time is
not new (Frenken et al., 2014) and has been a subject of research in the past (see, for
instance, Storper & Walker, 1989; Tichy, 2001). In recent years, there has been a
growing recognition of the need to further develop and elaborate on dynamic perspectives
on clusters to gain better insights into potential forms of their long-term evolution (see, for
instance, Lorenzen, 2005; Bergman, 2008; Menzel & Fornahl, 2010; Isaksen, 2011). A
popular model in this field of research is the cluster life-cycle approach. It has been
heavily inspired by earlier work on (spatial) product life cycles (Vernon, 1966; Cox,
1967; Thompson, 1968; Utterback & Abernathy, 1975) and studies of industry life
cycles (Klepper, 1997, 2007).
