Going green: the dynamics of green technological alliances

ABSTRACT

This paper investigates the impact of strategic technological alliances and environmental regulation, and their interaction, on the generation of green technologies. The empirical analysis is carried out on a newly constructed dataset of European firms over the period 2005–2011 and it is articulated in two steps. Firstly, we test the existence of a relationship between the environmental regulation, as measured by the OECD Environmental Policy Stringency index, and GTs, proxied by patent applications. We then employ a dynamic network analysis model to explore the dual role of GTs both as the determinant of the collaboration network and as the outcome of firms' collaboration strategies. We find that, even though there exists a strong and positive relationship, the regulatory framework has not a direct effect on GTs but rather it stimulates firms to search for new and qualified collaborations. Then, it is the nature and the structure of these collaborations that encourages firms to generate new green technological knowledge.

KEYWORDS:

• Green technologies
• environmental regulation
• firms' strategies
• innovation networks
• proximity
• dynamic network analysis

JEL CLASSIFICATION:

• O33

Acknowledgments

We are grateful for helpful comments from two anonymous referees and the editor. We thank Tom Snijders, Per Block, Christoph Stadtfeld and all the organizers of the 8th SIENA winter school (Zurich, 2016) for valuable suggestions on early stages of this paper and their precious help in the preliminary setting up of the dynamic network analysis model. We wish to thanks the participants of the Collaboration for Innovation Conference (Groningen, 2016), 4th Geography of Innovation Conference (Barcelona 2018), 6th IAERE Annual Conference 2018 (Turin, 2018), AAG Annual Meeting (New Orleans, 2018) where previous versions of this work have been presented.

Disclosure statement

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

Notes

1 See Crespi, Ghisetti, and Quatraro (2015) for a taxonomy of environmental policies. Typical examples are market-based instruments lie the Emission Trading System implemented by the European Union, or command and control instruments, like the regulation concerning the use of chemical compounds (REACh). These kinds of instruments constrain the actions of economic agents, to make them less harmful to the environment. In so doing, they create an incentive for the adoption and, consequently, the generation of green technologies.

2 SDC is a division of Thomson Financial and provides information on a wide range of financial transactions, including global new issues, securities trading, and mergers and acquisition. SDC tracks a very wide range of agreement types, including joint ventures, strategic alliances, research and development (R&D) agreements, sales and marketing agreements, manufacturing agreements, supply agreements, and licensing and distribution pacts.

3 An ‘only growing’ network can be defined as a network in which links can only be created but they are not dissolved.

4 Available at https://www.sites.google.com/site/patentdataproject.

5 The actual names parsing is performed using the utility stnd_compname of the Stata package reclink. Given its flexibility, the utility allows accounting for the specificity of different countries' name registration procedures and rules. This allows to obtain cleaned and standardized firms names in both AMADEUS and SDC database

6 The matching is performed by combining the matching routine ‘matchit’, described in Raffo and Lhuillery (2009), and the reclink Stata package. We employ a 2-grams matching algorithm, as it is considered an acceptable trade-off between the desired precision and recall rate.

7 Available at https://www.openrefine.org.

8 For each IPC listed in Haščič and Migotto (2015) we identify the corresponding CPCs using the concordance table available at https://www.cooperativepatentclassification.org/cpcConcordances.html.

9 It is worth stressing that the EPS index is measured at the country level, therefore, firms located in the same country are exposed to the same levels of Environmental Policy Stringency.

10 In the literature, there have been several attempts to estimate the most appropriate patent depreciation rate (Schankerman 1998; Pakes and Schankerman 1979). In this paper, we adopt an obsolescence rate at 15%, as it is the most commonly used value in the literature (see among others Hall, Jaffe, and Trajtenberg 2005; Keller 2002; McGahan and Silverman 2006; Nesta 2008).

11 Information on public institutional status are gathered from the SDC Platinum. In particular, each firm is listed as either: Private company, Public company, Subsidiary, Joint Venture, Governmental company, Investment company.

12 Firm size in proxied by the mean value of assets over the period 2005–2011.

13 According to Ripley, B Snijders, and Preciado (2011), the variable can have a maximum 10 non-negative integer values.