Abstract
This paper aims to contribute to enlarge a geography of eco-innovation. The objective is to study what kind of spatial externalities (specialization, related and unrelated variety) has the most positive impact on eco-innovation, according to firm’s location (rural, peri-urban, urban). We empirically test this framework using a hurdle negative binomial model on firm-level data drawn from the French Community Innovation Survey (CIS). The results show that spatial externalities have different effects depending on the firm’s engagement and breadth of eco-innovation as well as on its location. Marshallian specialization has a positive effect both on engagement and breadth of eco-innovations unlike unrelated variety, which negatively impacts breadth of eco-innovation. With regard to the firm’s location, related variety is particularly correlated with the eco-innovation breadth of rural firms, whereas specialization is positively correlated with the breadth of eco-innovations of peri-urban firms. As for urban firms, spatial externalities seem to have less impact on their eco-innovation related behavior.
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Notes
We have access to confidential individual data for these two surveys following a statistical confidentiality agreement. See https://www.casd.eu/en/. This allows us to have access to all the information, and in particular the accurate location (at the municipality level) of plants and head offices of firms.
We use the level A38 of the French Aggregated Nomenclature (2008 NA), which divides the manufacturing sector into 12 large categories of activities (see Table 4 in Appendix). Level A38 is an international intermediate level between sections and divisions that is suitable for the purpose of characterizing a breakdown into manufacturing sectors.
Many of the questions on innovation capacities are addressed only for innovative firms in the French CIS. This limits the construction of control variables on the whole population. Consequently, we retained the permanent presence of an internal R&D team, with the assumption that non-innovative firms over a 3-year period did not have this resource.
One could notice that this engagement and breadth aggregate the 14 types of environmental benefits (see table 2). We could test the impact of externalities only on engagement in eco-innovation for each of the 14 types of eco-innovation. We have selected a few results on specific types of eco-innovations that shed light on the results obtained with our general model. First, we confirm a significant positive effect of urban (12 out of 14 types) and peri-urban (9 out of 14) on eco-innovation engagement. For eco-innovations aiming at environmental benefits obtained during the production process, the engagement of firms in the two eco-innovations “Reduction of CO2 emissions per unit of output” and “Reduction of air, water, noise or soil pollution” is favored by specialization (as our model also shows), while the diversification externalities (related and unrelated) are not significant. The other results for these two types of eco-innovation are in line with the results of our model. For eco-innovations during the consumption process, the results are more contrasted. The eco-innovation aiming at a reduction in the amount of packaging waste is influenced by externalities in a similar way to our model. This eco-innovation develops regardless of the type of territory (no positive effect of urban or peri-urban areas). This is less the case for other eco-innovations aiming at an environmental benefit during the use of the product, where the agri-food industry is lagging behind. Another element to highlight for this type of eco-innovation concerns the positive impact of a local market, which tends to show that the proximity with the customer favors the engagement in eco-innovations related to the use of the product. The logit results are available upon request.
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Acknowledgements
This research has been conducted with the support of the labex " SMS : Structuring Social Worlds" (ANR-11-LABX-0066) and of the project " Repro-Innov " (PSDR4-INRAE/Regional Council of Occitania). We thank the editors and reviewers for their comments and advice as well as Olivier Pauly for his support in statistical processing.
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Galliano, D., Nadel, S. & Triboulet, P. The geography of environmental innovation: a rural/urban comparison. Ann Reg Sci 71, 27–59 (2023). https://doi.org/10.1007/s00168-022-01149-3
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DOI: https://doi.org/10.1007/s00168-022-01149-3