Firms are influenced by internal factors (resources and capabilities) and external factors (e.g., regulation) when taking the decision to eco-innovate. However, the analysis of the internal factors has received much less attention than the external ones. This paper aims to fill this gap in the literature by analyzing the role of resources, competences and dynamic capabilities (RCCs) as determinants (drivers and barriers) of different eco-innovation (EI) types. Those EI types contribute differently to the sustainable transition of the economy and society, i.e., towards the Circular Economy. The statistical analyses reveal that RCCs are quite relevant as determinants of EIs and that different RCCs are more or less relevant for different EI types. In particular, the determinants of systemic and radical EIs substantially differ from those for continuous improvements. Our results suggest that physical RCCs, involvement in green supply chains, an EI-friendly corporate culture, technology-push and market-pull and internal financing resources represent drivers to these EIs, whereas cooperation, organizational learning, an ISO ecological certification and technological path dependency are barriers. The results may guide firms to pursue competitive and sustainable advantage by innovating through certain EI types corresponding to available and dedicated RCCs. They may also be useful to policy makers who are willing to promote specific EI types.

Technological change has a relevant role to play in the transition towards a sustainable industry. However, slow diffusion of clean technologies can be observed in OECD countries. The analysis of the determinants and barriers to clean technology adoption should be a main goal of economists and social scientists. This paper shows that three sets of interrelated factors prevent but also stimulate the widespread adoption and diffusion of clean technology: these are factors external and internal to the firm, conditions of the potential adopters and characteristics of the environmental technology. These factors are included in the so-called 'triangular model', which is further applied to the analysis of clean technology adoption in the pulp and paper industry in Spain. The empirical study shows that clean technology adoption decisions are the result of an interaction between these factors, often involving contradictory signals for the potential adopter. The paper closes with some public policy recommendations for the effective and efficient promotion of clean technology diffusion.

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