top of page

How innovations attract actors: Insights from 20 years of experimenting with marine energy renewable

Astract

New technologies are necessary to address climate change, but their development and implementation can have different impacts on decarbonizing the energy system and transforming the economy. This work adds to previous efforts to conceptualize how technology innovation influences industrial change (Fontes et al., 2019; Dolata, 2009). The transformative capacity of new technologies depends on technological characteristics as well as contextual variables (Bergek et al., 2015), as shown, for example, in the case of Marine Renewable Energy Technologies or MRET (Fontes et al., 2019). The context influences the development of complementary interactions with existing industries, which are critical to access key resources and markets, but this requires organizational and institutional changes that remain little understood (Markard and Hoffman, 2016). Hence, this study aims to address the following question: Which are the conditions that enable a new technology to involve the largest number of sectors and induce their transformation? In particular: Which factors lead firms to engage with new technology innovation?

The conceptual framework combines contributions from the sustainable transitions literature with those from economic complexity, economic geography, and strategic management. This comprises research on firm diversification into related activities (Laurens et al., 2018), investigation that extends the concept of relatedness beyond technology to encompass other competences (Neffke and Hening, 2013; Tanner, 2014), research on how regions diversify into new industries (Martin and Sunley, 2016; Fornahl et al, 2012), and the debate on the role of related/unrelated diversification in new path creation (Boschma, 2017; Janssen and Frenken, 2019).

We derive a set of hypothesis concerning the factors that influence firms’ decisions to engage with the new technologies. Thus, the propensity to enter into the new field is expected to be higher:

H1. When firms belong to sectors that are associated with the development of the technology and are identified as the core complementary sectors (Hidalgo et al., 2007);

H2. When firms are from sectors that are less proximate to the technology, but that provide competencies and resources that enable the full operation of complex technologies (Fontes et al., 2019);

H3. When firms display characteristics that have been shown to make them more likely to engage in diversification (Laurens et al, 2018): greater dimension, higher technological competence, greater innovation capacity.

The empirical research addresses the case of wave energy and offshore wind in Portugal, focusing on the firms from sectors that can contribute with competences and resources to their development (Scheme 1). Firms were identified through: i) secondary sources, firms involved in MRET as partners or suppliers in experimental projects; ii) a questionnaire targeting firms from sectors identified as potential contributors to the development, production, installation and operation of MRET (OTEO, 2014). This provided a set of firms with different attitudes towards MRET. The objective was to uncover the determinants of firms’ decision to become involved in the development of these new technologies. For this purpose we collected data on firms’ characteristics, sector of activity and innovation capacity from a variety of databases (e.g. Amadeus, Cordis, ANI, EspaceNet). In addition we created a new variable “complementarity” which indicates whether the firm’s sector of activity is among the core sectors defined for MRET (cf. Wind, 2009).

We used standard binary logit regressions to estimate the effect of a set of determinants in the decision of firms to develop activities in MRET (see Appendix 1 and Table 1). Graph 1 shows actual and predicted impacts on activity for four key variables. The variable “complementarity” is negative and statistically significant, meaning that firms from sectors unrelated to core sectors are 2.6 to 3.7 times more likely to become involved in MRET. This result confirms hypothesis 2 while refuting hypothesis 1. On the other hand, firms more technologically advanced (“Medium to High technology”) and participating in national research projects are significantly less likely to participate in the development of MRET. However, the probability slightly increases for larger companies and for those that have not low technological content. These results partially validate hypothesis 3.

Therefore it appears to be unnecessary to have a high technology content and strong innovation capacity to engage with the emerging MRET, and potentially benefit the opportunities for change this entails (Fontes et al., 2019). These opportunities may be open to firms from traditional sectors, providing that they have a certain dimension, which gives them conditions for engaging in product or market diversification. The research also finds that these firms are often likely to be active in sectors that are not part of the “complementary core”. This suggests that technologies that have more significant transformative potential have an impact that goes beyond sectors with greater proximity to the technology. It is now necessary to further confirm these results and explore them in greater depth, namely to better understand the importance of unrelated diversification.


Keywords: system transformation, relatedness, diversification, energy technologies.


References:

Bergek, A., Hekkert, M., Jacobsson, S., Markard, J., Sandén, B., & Truffer, B. (2015). Technological innovation systems in contexts: Conceptualizing contextual structures and interaction dynamics. Environmental Innovation and Societal Transitions, 16, 51-64.

Boschma, R., Coenen, L. Frenken, K. & Truffer, B. (2017) Towards a theory of regional diversification: combining insights from Evolutionary Economic Geography and Transition Studies, Regional Studies 51: 31-45.

Dolata, U. (2009). Technological innovations and sectoral change: Transformative capacity, adaptability, patterns of change: An analytical framework. Research Policy, 38(6), 1066-1076.

Fontes M., Bento N., Andersen A.D. (2019), Unleashing the transformative potential of innovations: context, complementarities and competition, Proceedings of the 10th International Sustainability Transitions Conference, Ottawa, Canada, June 23-26.

Fornahl, D., Hassink, R., Klaerding. K., Mossig, I. and Schröder, H. (2012) From the old path of shipbuilding onto the new path of offshore wind energy? The case of northern Germany. European Planning Studies 20:835–55.

Hidalgo, C. A., Klinger, B., Barabási, A. L., & Hausmann, R. (2007). The product space conditions the development of nations. Science, 317(5837), 482-487.

Janssen, M. and Frenken, K. (2019) Cross-specialisation policy: rationales and options for linking unrelated industries, Cambridge Journal of Regions, Economy and Society, 12(2): 195–212.

Laurens, P., Le Bas, C. and Lhuillery, S. (2018), Firm Specialization in Clean Energy Technologies: The Influence of Path Dependence and Technological Diversification, Revue d’Economie Industrielle, Vol. 164, available at:https://doi.org/10.4000/rei.7625.

Markard, J., & Hoffmann, V. H. (2016). Analysis of complementarities: Framework and examples from the energy transition. Technological forecasting and social change, 111, 63-75.

Martin, R., and Sunley P. (2006) Path dependence and regional economic evolution. Journal of Economic Geography, 6, 395–437.

Neffke, F. and Henning, M. (2013) Skill relatedness and firm diversification, Strategic Management Journal, 34: 297–316 (2013

OTEO (2014) Offshore Renewable Energy–Current Status and Future Perspectives for Portugal. Observatório Tecnológico para as Energias Offshore, INEGI, Porto.

Tanner, A. N. (2014) Regional Branching Reconsidered: Emergence of the Fuel Cell Industry in European Regions, Economic Geography 90(4): 403–427.

Vona, F. (2019). Job losses and political acceptability of climate policies: why the ‘job-killing’ argument is so persistent and how to overturn it. Climate Policy, 19(4), 524-532.

Wind, I. (2009). HS Codes and the Renewable Energy Sector. Research and Analysis, International Centre for Trade and Sustainable Development (ICTSD), <https://www.ictsd.org › files › downloads › 2009/09>

Scheme 1. Structure of the research.




Graph 1. Observed and predicted effects of key variables in Activity


 

Bento, N., Fontes, M. and Barbosa, J. (2020) How innovations attract actors: Insights from 20 years of experimenting with marine energy renewable technologies in Portugal, oral presentation at Workshop Dinâmicas Socioeconómicas e Territoriais Contemporâneas V, 21-22 Janeiro 2020, DINAMIA’CET-IUL, Lisboa.

 

Programa do Workshop:

Programa _Workshop DINAMIA
.pdf
Download PDF • 204KB

How innovation attract innovators_20Jan'
.
Download • 789KB

Comments


bottom of page