Looking for resilience along value creation processes

The determinants of eco-innovation strategies. An empirical investigation of two European countries

Ida D’attoma, Silvia Paceii

The present paper is a work in progress focusing on the driving forces behind the adoption of different types of eco-innovation mode in German manufacturing sectors compared to Romania over 2012-2014, through an empirical analysis of the community innovation survey (CIS). To this end, in our empirical study, we considered a measure of eco-innovation performance that counts different types of eco-innovation that enterprises have undertaken. Moreover, we considered a wide and comprehensive set of potential drivers, including “technology push”, “regulatory push-pull” and “firm specific factors” clusters of drivers. Due to the count nature of our dependent variable and to the large presence of zeros, we estimate a zero-inflated negative binomial model. Given the early stage of this study, in the present paper preliminary findings on the differences in the determinants of eco-innovation in the two countries will be presented.

Environmental innovation, or eco-innovation, is commonly understood as innovations that are associated with environmental benefits. Differently from traditional innovation, eco-innovation ‘emphasizes the firms’ mitigation of negative impacts on the natural environment’ (Liao and Tsai, 2018). Some papers discussed the existence of a positive relationship between eco-innovation and firm performance and growth, thus motivating the identification and the analysis of trigger factors for eco-innovation. The early study of Russo and Fouts (1997) found that the more enterprises eco-innovate, the greater the positive impacts on their performance. Firms implementing eco-innovation tend to be recognized in a positive sense (Buysse and Verbeke, 2003) by consumers that are nowadays increasingly aware of environmental topics. Not only to obtain or enhance social legitimacy but also to react or pre-empt their rival’s environmental moves, corporations are inclined to use eco-innovation strategies to exploit emerging opportunities (Liao and Tsai, 2018).

In this scenario, investigating eco-innovation determinants can be helpful for policy-makers and managers who wish to promote its adoption and diffusion (Ghisetti and Pontoni, 2015). Although there has been a significant increase in eco-innovation knowledge, some conflicting results are still present in the literature (Bitencourt et al., 2020; Díaz-Garcia et al., 2015). Moreover, over the past decade, many empirical works have analysed the drivers of eco-innovation for single countries and especially among manufacturing firms because of their higher environmental impact (Jové-Llopis and Segarra-Blasco, 2018) but there is still a lack of country comparisons (Horbach, 2016; Ghisetti et al al. 2015 as exceptions).

In light of this, the main purpose of this study was to analyse the main factors enhancing firms focusing on a different number of eco-innovations in Germany and Romania. Specifically, the following research questions were asked:

RQ1: what types of factors do enhance firms focusing on a different number of eco- innovations?

RQ2: how does the context influence these relations in different countries?

We considered data taken by the Community Innovation Survey (CIS) in 2014. We constructed a count measure of eco-innovativeness and then we analysed its determinants by estimating a zero-inflated negative binomial model (Greene, 2009; Hilbe, 2007).

We decided to compare Germany – that is an eco-innovation leader, to Romania, that is a catching up with eco-innovation country. According to the European innovation scoreboard, Germany was a strong innovator in 2013, whereas Romania was the less innovative one. Germany is also Romania’s most important trading partner and the second largest foreign direct investor in the country. Given the intense interplay between them it is worth analysing eco-innovation determinants they might share, by not forgetting that they do not share the same institutional/regulatory context.

#CIS data #eco-innovation #eco-innovation drivers #zero-inflated negative binomial- regression