Regional eco-innovation trajectories

ABSTRACT

Given that eco-innovations and the associated renewal of regional economic structures are pivotal in addressing environmental challenges, regional research is increasingly focusing on their spatio-temporal dynamics. While green technological and industrial path developments in specific regions have received considerable attention, little effort has been made to derive general patterns of environmental inventive activities across regions. Drawing on unique data capturing both green incumbent and green start-up activities in the 401 German NUTS-3 regions over the period 1997–2018, this paper sheds light on how eco-innovation activities unfold in different regional contexts. For this purpose, we introduce sequence analysis methods into the research toolkit of research on regional development. These novel methods allow us to understand to what extent regions engage in eco-innovation activities, how these activities change over time and to what extent similar or unique eco-innovation trajectories (co)evolve. Based on this empirical approach, we distinguish different types of regional eco-innovation trajectories and find a strong persistence and path dependency in green regional development.

KEYWORDS:

• Eco-innovation
• green regional development
• path dependency
• regional transitions
• sequence analysis

Acknowledgements

The authors are very grateful to Ingo Liefner and Henning Kroll for their contribution to the development of the research question as well as to Anne Otto and Lars Mewes for the stimulating exchange on the potentials of sequence analytical methods for regional research. Moreover, the authors would like to thank Sandra Gottschalk and Johannes Bersch for accessing and helping with ZEW’s company database. This study also benefited greatly from the numerous comments at the RSA Conferences in London & Ljubljana (November 2022; June 2023) and at a research seminar at GSSI in L’Aquila (February 2023).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Recent work has also taken up aspects of directionality and normativity to further develop the RIS approach. See, for example, Tödtling et al.'s (2022) notion of ‘challenge-oriented RISs’ (CoRISs).

2 In this study, we make use of Ward hierarchical clustering methods. However, the results are also robust to other methods of clustering, such as partitioning or divisive analyses (e.g. Gabadinho et al. 2011; González-Leonardo, Newsham, and Rowe 2023).