The effect of innovation on environmental, social and governance (ESG) practices

Abstract

Purpose

This paper aims to investigate if and to what extent environmental, social and governance (ESG) practices are influenced by innovation, measured by investment in research and development (R&D) and the number of patents developed by companies.

Design/methodology/approach

To test this hypothesis, the authors estimated a regression model for the panel data considering a time horizon of eight years. The analysis was conducted on a sample of listed firms operating in the industrial sector in France, Germany, Italy, Spain, the UK and the USA.

Findings

The empirical analysis shows that there is a positive and significant relationship between ESG practices and innovation. Companies investing more in R&D and patents have better ESG performance.

Originality/value

This study contributes to the existing literature by improving the understanding of the importance of innovation in improving ESG practices for firms in the industrial sector. Furthermore, it provides empirical evidence of the ability of innovation to be a valuable tool for sustainable industry development through R&D investment and patent development.

Citation

Dicuonzo, G., Donofrio, F., Ranaldo, S. and Dell'Atti, V. (2022), "The effect of innovation on environmental, social and governance (ESG) practices", Meditari Accountancy Research, Vol. 30 No. 4, pp. 1191-1209. https://doi.org/10.1108/MEDAR-12-2020-1120

1. Introduction

In recent years, companies, investors and consumers have been turning their focus toward increasingly crucial corporate sustainability (Melinda and Wardhani, 2020). The topic of sustainability is leading most organizations to pay more and more attention to the environment, its conservation (Kotze et al., 2010) and the development of a sustainable corporate culture that encourages the optimization of business operations (Nowak et al., 2011). Sustainability implies constant and ideally increasing well-being (environmental, social and economic) with a view to leaving future generations a quality of life that is not inferior to the present one.

Corporate sustainability is often observed by considering ESG factors (Buallay, 2019; Drempetic et al., 2019). The environmental aspect refers to a company’s ability to efficiently use natural resources in its processes, thereby reducing environmental emissions. The social dimension measures a company’s capacity to promote ethical values and generate trust in its employees, ensuring respect for human rights. Finally, the governance dimension refers to a company’s capacity to act in the interests of its shareholders through efficient corporate management systems and effective processes.

A useful tool to promote sustainable business is innovation (Barbieri et al., 2010; De Santis and Presti, 2018). It is clear that efforts to achieve sustainability goals, such as increasing resources and energy efficiency, are inextricably linked to technological progress. Without technology and innovation, there will be no opportunity for growth, let alone industrialization and without industrialization, there will be no economic development and no well-being for individuals (Carayannis et al., 2015). Indeed, it is widely recognized in the literature that there is a relationship between innovation and sustainability performance (Ahmad and Wu, 2021). However, the results are not conclusive. On the one hand, previous studies have analyzed the relationship bi-directionally (CSR-innovation and innovation-CSR) (Gallego-Álvarez et al., 2011). On the other hand, prior findings are mixed in terms of signs, showing both a positive (Carrasco and Buendía-Martínez, 2016; Du and Li, 2019) and a negative relationship (von HØivik and Shankar, 2011; Marsat and Williams, 2014; Mithani, 2017).

According to institutional theory, the values institutionalized within a society very often represent the ideals that organizations set for themselves to follow (Meyer and Roman, 1991). Within the context of these values, sustainability is, especially in the current scenario, one of the main pillars of strategic decisions and medium-to long-term company growth. In this sense, institutional theory may explain how the pressures exerted by society influence a company’s sustainability practices and the shifts in internal organizational practices in terms of new internal processes, practices and structures (Campbell, 2007; Lombardi et al., 2021; Matten and Moon, 2008). As observed by the European Commission (2008), engagement with stakeholders can push the innovation activity of companies toward more sustainable practices (Carrasco and Buendía-Martínez, 2016; European Commission, 2008).

Companies operating in the industrial sector, due to pollutant emissions from production activities, are among the main companies responsible for environmental pollution (Arango-Miranda et al., 2018; Nartey, 2018). In the past few decades, the industrial sector has begun to embrace the concept of sustainability, as demonstrated by large companies articulating sustainability strategies and publishing annual reports that track progress toward economic, environmental and social goals (Kunz et al., 2013). These efforts have contributed to considerable reductions in the environmental impacts of production processes through waste reduction, resource conservation and the development of clean production initiatives (Kotze et al., 2010; Renukappa et al., 2012).

In light of the above considerations, this study analyzes whether firms in the industrial sector use innovation to improve their sustainability performance in response to institutional pressure. Few empirical studies have demonstrated the relationship between corporate ESG initiatives and innovative performance (Zhang et al., 2020a); however, studies focusing on the relationship between ESG performance and a firm’s economic and financial performance are prevalent (Do and Kim, 2020). Furthermore, few studies investigating the relationship between ESG performance and innovation have focused on green innovation (Xu et al., 2021).

The present study aims to extend the literature on this topic by providing empirical evidence of the relationship between innovation, as measured by R&D expenditures and patent production, and ESG performance in the industrial sector.

To achieve our goal, we conducted a regression analysis on panel data to estimate the effect on the dependent variable related to the sustainability (ESG score) of R&D expenditures, patents and environmental innovation scores as a predictor of the level of green innovation. The results show that there is a positive and significant relationship between the explanatory variables under investigation and ESG score (dependent variable).

This study offers theoretical and practical implications. First, this study contributes to previous literature by analyzing the impact of R&D investment, firms’ abilities to develop patents (in terms of the number of patents developed annually), on the improvement of sustainable practices of industrial firms that operate in European and US contexts. Second, this study provides useful insights for managers trying to build innovation strategies.

The paper is structured as follows: Section 2 presents the literature review; Section 3 describes the research methodology; Section 4 shows the results of empirical analysis; Section 5 discusses the conclusions; and finally, Section 6 presents theoretical and practical implications and recommendations for future research.

2. Literature review

There are an increasing number of measures promoted by the international community to steer companies toward sustainable development, such as the Paris Agreement on Climate Change in 2015 and the 2030 Agenda for Sustainable Development Goals (SDGs), the goal of which is to stimulate investment choices that safeguard environmental quality (Ying and Xin-gang, 2021). The interest shown by investors and consumers in corporate sustainability issues (Melinda and Wardhani, 2020) has led most organizations to pay increasing attention to the environment by developing a sustainable corporate culture (Kotze et al., 2010; Tarquinio and Posadas, 2020). Achieving sustainable performance requires companies to integrate ESG aspects into business strategy (Atan et al., 2016), and the ESG score is the most widely used variable in the literature for measuring sustainable performance (Xu et al., 2021).

The choice of firms to integrate ESG practices often has positive effects in terms of reduced costs, improved product quality and higher customer satisfaction (De Klerk and De Villiers, 2012; Magon et al., 2018). These benefits often lead to improved firm performance; in fact, some studies have found that ESG practices have a positive and significant impact on return on assets (ROA) (Almeyda and Darmansya, 2019) as well as on competitive advantage and corporate reputation (Alsayegh et al., 2020; Chen et al., 2015; Zhai et al., 2018). According to others, however, integrating ESG practices does not necessarily improve corporate profitability (Buallay, 2019; Farooq, 2015; Zaman et al., 2021), due to the high investment costs in R&D that the path to sustainability requires (Marsat and Williams, 2014). Indeed, achieving and improving ESG performance requires firms to invest in R&D (Fernández et al., 2021; Triguero et al., 2018).

Innovation represents the tool most companies use to initiate their sustainable change path, addressing earnings management, corporate social responsibility, accountability and transparency (Lombardi and Secundo, 2020), by adopting innovations that take into account the three dimensions of sustainability (i.e. ESG) (Barbieri et al., 2010). The innovation capacity of firms can be measured through R&D expenditures or technological output, such as patents or patent applications (Broadstock et al., 2020). Previous literature has investigated the association between innovation and sustainability performance although it shows mixed results (Ahmad and Wu, 2021). In particular, there are studies that analyze the relationship bidirectionally (i.e. the link between CSR and innovation and between innovation and CSR) (Gallego-Álvarez et al., 2011); others have found a positive association (Carrasco and Buendía-Martínez, 2016; Du and Li, 2019) or a negative association (Marsat and Williams, 2014; Mithani, 2017; von HØivik and Shankar, 2011).

In the USA, for example, investments in innovation oriented toward sustainability have increased by more than 40% since 2015 (US SIF Foundation, 2018) and the development of patents instrumental in improving ESG performance is also steadily increasing (Xu et al., 2021). Therefore, companies that want to improve their ESG performance must engage in innovation activities by investing in R&D (Aras et al., 2018).

A relevant form of innovation for sustainability goals is green innovation. While innovation is defined as “a continuous improvement in the overall ability of companies to generate innovation to develop new products to meet market needs” (Szeto, 2000, p. 150), the shift to the concept of green innovation requires a change in the concept of technological innovation, focusing on aspects of eco-innovation or environmental innovation (Ahmad and Wu, 2021). The integration of environmental innovation into corporate strategy is increasingly common, representing one of the factors that can strengthen corporate competitiveness (Chen et al., 2015; Zhai et al., 2018), fostering long-term value creation for the benefit of shareholders and improving engagement with stakeholders relevant to the company (Ilyas and Osiyevskyy, 2021; Nicolò et al., 2021). Green innovation is a useful tool for promoting the sustainable success of an industry while maintaining its environmental benefits (Ghadimi et al., 2020; Zhang et al., 2019; Zhang et al., 2020b).

In the environmental context, it is therefore essential to assess the impact of business activities on the environment and the company’s ability to offer products and services that can meet climate and environmental challenges. The efficient use of natural resources, optimization of production processes (eco-innovation), and development of technologies that reduce environmental impact (eco-design) are typical actions of a corporate strategy focused on environmental innovation (Kemp and Pearson, 2007). Specifically, eco-innovation refers to the pursuit of SDGs according to a logic of “responsible” behavior as a result of mitigating the ecological pressures caused by production processes and making natural capital resilient to these pressures (OECD, 2018). Although such a strategy guarantees an improvement in performance and corporate image (Liao, 2020) while being positively valued by institutional investors, it requires incurring significant costs that negatively affect profitability (García-Sánchez et al., 2020). Although investments in eco-innovation and eco-design may negatively affect financial performance in the short term, the return on such investments may exceed the relative cost of the initial investment in the long term (García-Sánchez et al., 2021). Therefore, to develop these technological capabilities and implement environmentally friendly innovations (Jové-Llopis and Segarra-Blasco, 2018), firms must invest in R&D (Fernández et al., 2021; Triguero et al., 2018).

Based on the foregoing, the interest of academics and practitioners has focused on the impact of ESG on a firm’s economic and financial performance (Do and Kim, 2020), while few studies have empirically investigated the relationship between ESG performance and innovation performance in general (Zhang et al., 2020a), including green innovation (Xu et al., 2021). As sustainability represents a widely institutionalized value in modern society, as evidenced by numerous companies that have developed business models in line with new social needs based on economic efficiency and respect for the environment and human rights (Barbieri, 2007), it is interesting to analyze whether companies, in response to social pressures, recognize innovation as a tool to improve their ESG performance. The European Commission (2008) has highlighted how corporate stakeholders influence the innovation activity of companies toward more sustainable practices (Carrasco and Buendía-Martínez, 2016; European Commission, 2008).

In light of these considerations and given that ESG is an expression of the concept of green economy, CSR and responsible investment (Deng and Cheng, 2019), this study aims to analyze whether the ability to innovate, measurable through investment in R&D and patents (Broadstock et al., 2020), improves ESG performance (Fernández et al., 2021; Triguero et al., 2018). It tests the following research hypothesis:

H1.

Innovation, measured by R&D and patents, positively influences ESG performance in the industrial sector.

3. Research design

To test our hypothesis, we used a panel data regression model, which is useful for examining a given sample of firms over time (Wooldridge, 2010). This model has several major advantages over conventional cross-sectional or time series data sets, including more accurate inference of model parameters, uncovering dynamic relationships and controlling the impact of omitted variables (Hsiao, 2014). The panel data regression model is a valuable tool for examining the incremental contribution of innovation to sustainability.

3.1 Sample and data collection

The analysis focused on 1,787 listed firms operating in the industrial sector in France, Germany, Italy, Spain, the UK and the USA. These countries were chosen because they represent major European Union (EU) economies and more than half of the EU’s international activities (Bpifrance, 2018; EUROSTAT, 2016; Symons et al., 2002); and the USA is the largest economy in the world.

Given the large emissions of pollutants and production activity energy consumption, it is important to analyze the industrial sector (Zhu et al., 2021). In addition, the industrial sector is a powerful player within society and thus can have a significant influence on regional and global sustainability outcomes (Kunz et al., 2013).

Our final sample consisted of 182 firms for which data on ESG scores and the number of patents developed were available for the period of analysis. We constructed an eight-year panel dataset from 2013 to 2020. The period of analysis came immediately after a conference that took place in Rio de Janeiro in 2012, the aim of which was to renew the political commitment to sustainable development by seeking to steer companies toward common sustainability goals (Naciti, 2019).

Longitudinal data observations exist for the same companies in several different periods (Kennedy, 2008). A panel data set has multiple entities, each of which has repeated measurements at different periods. Panel data may have individual (group) effects, time effects or both, which are analyzed using fixed-effect or random-effect models.

The data regarding R&D, environmental innovation score and ESG practices have been extrapolated by the Refinitiv database (previously called Thomson Reuters Asset4) and the Datastream database. In addition, the number of patents developed by each company was hand-collected by “Espacenet,” which is a free online service developed by the European Patent Office together with the member states of the European Patent Organization (Vincent et al., 2017). This database contains national patents from many European states, as well as European, international, and national patents from other countries. In addition, we used the US Patent and Trademark Office (USPTO) database as a further source of data, which is considered reliable for studying the global innovation model (Su, 2017).

3.2 Research model

The analysis was carried out using panel data analysis. Using the fixed-effects model, it is possible to identify a set of characteristics specific to each unit that remains constant over time. Fixed-effect regression models have as many intercepts as there are units. Conversely, the random-effects model treats individual effects as part of the error term and then considers them stochastic components unrelated to regressors.

More specifically, the estimation model is as follows:

Yi,t=β0+β1Xi,t+αi+ui,t

where the i and t indices represent the company identifier and the period (year), respectively; the dependent variable (Y_i,t) is the ESG score, β₀ is the constant and X_i,t refers to a vector of independent variables. We intended to test the research hypothesis using the following model:

ESGi,t=β0+β1LnR&Di,t+β2Patentsi,t+β3CSR_Comi,t+β4GRI_Guidi,t+β5EISi,t+β6Prod_respi,t+β7TAi,t+β8Mkt_capi,t+β9ROAi,t+ αi+ ui,t

3.3 Dependent variable

In line with previous studies (Drempetic et al., 2019; Shahbaz et al., 2020; Xu et al., 2021), we used Refinitiv’s ESG performance data (ESG score) as the dependent variable. The ESG score is the result of three sub-scores related to the ESG areas. the categories that make up the environment pillar (E) are as follows:

• resource use, which refers to the ability of enterprises to reduce the use of resources, such as materials, water or energy, and to identify eco-efficient solutions for the production of products;

• emission reduction; and

• innovation, which refers to the ability of the enterprise to adopt technological solutions to reduce environmental costs and create new market prospects.

In terms of social aspects (S), the following are considered:

• the focus on the workforce (i.e. the ability of the company to create satisfaction for its employees, maintain gender diversity and ensure equal opportunities for all);

• the focus on human rights;

• the protection of community aspects, measured by the company’s involvement in the protection of public health and respect for business ethics; and

• product responsibility, which reflects the ability of a company to produce goods or provide services that integrate customer health, safety, integrity and privacy.

Finally, with regard to screening in terms of corporate governance (G), the following are considered:

• the skills of management;

• shareholder protection in terms of the company’s ability to ensure fair treatment for shareholders; and

• corporate social responsibility strategies in terms of the company’s ability to integrate economic, financial, social and environmental dimensions into business management.

In the corporate governance pillar, in addition to the analysis of the structure and composition of the board of directors as internal information, the role of companies in protecting other stakeholders is also examined.

The overall ESG score is the arithmetic mean of the three scores and is expressed as a percentage.

3.4 Independent and control variables

R&D expenditure and patents are typical proxies for innovation input and output (Cruz-Càzares et al., 2013). R&D investment is a representation of a firm’s technological knowledge. According to previous studies (Liao et al., 2021; Qi et al., 2018; Zhang et al., 2020a), innovation performance is also measured by the total number of patents (Xu et al., 2021), so we included the number of patents and hand-collected data as explanatory variables.

To avoid model specification errors, we checked for additional variables that could affect the ESG score. We used the presence of a committee for CSR (Shahbaz et al., 2020), the adoption of guidelines for Global Reporting Initiative (GRI) reports (Drempetic et al., 2019), the commitment of a company’s management in supporting R&D of eco-efficient products or services (Arena et al., 2018), the ability of a company to produce quality goods and services designed for reuse, recycling or reduction of environmental impact (Duque-Grisales et al., 2020), size (Khaled et al., 2021), market capitalization (Pasquini-descomps, 2016) and ROA as control variables. Table 1 presents a summary of the measurements of all variables.

4. Results and discussion

4.1 Descriptive statistics

Table 2 shows descriptive statistics for dependent and independent variables, both for each individual year of analysis and for the aggregated period (2013–2020). The descriptive statistics include the minimum, maximum, mean and standard deviation.

The average level of ESG performance (ESG score) of the companies analyzed was 54.11%, with a maximum of 92.98%. This reveals that the sustainability performance of the companies for the period 2013–2020 was very satisfactory in terms of the scoring definition. The amount of R&D investment over the entire period of analysis shows an average value of €243,267.90, with a maximum of €4,627,000. During the whole period of analysis, the average number of patents was 84, with a maximum value of 1998 in 2020. In addition, 65% of the sample had a committee for CSR, and 99% of the examined companies published their CSR reports in accordance with GRI guidelines. The average environmental innovation score was 37.92%, and the maximum value was 99.38%, suggesting that many of the companies used technologies to increase their level of sustainability. This result was also confirmed by the variable “product responsibility,” which had an average value of 55.10 during the examined period. In terms of total assets and market capitalization, the average value was €11,500,000 (maximum value €152,000,000) for total assets and €11,200,000 (maximum value €183,000,000) for market capitalization. Finally, ROA had an average value of 6.50.

We checked the normality of the sets of residuals using the Jarque–Bera Lagrange multiplier test. Based on a p-value greater than 0.05, the null hypothesis cannot be rejected. Therefore, the residuals were distributed normally. In other words, there is no violation of the hypothesis of normal distribution for the error terms, as the residuals are normal.

4.2 Correlation analysis

To assess the correlation of a variable simultaneously with two or more variables, we performed a multiple correlation analysis (Pearson correlation). The correlation matrix (Table 3) highlights a positive relationship between the dependent variable and the study’s explicative independent variables. A company’s sustainability performance (ESG score) was found to be positively associated with innovation performance, which was measured in this study by the amount of R&D investment and the number of patents. The other control variables included in the econometric model were also positively correlated with the dependent variable ESG score.

Furthermore, we performed the variance inflation factor (VIF) test to check for multicollinearity among the variables. Chatterjee and Hadi (2012) indicated a VIF value of 10 as a cut-off for considering high correlations between variables. In the present case, the VIFs were all less than 3, suggesting the absence of multicollinearity (Table 4).

4.3 Findings

Linear regressions were performed with fixed and random effects, verifying solidity both for heteroskedasticity and for correlation. To identify which model, the fixed-effects or the random-effects model, would best describe our analysis, we performed the Hausman test and the Breusch–Pagan test. To this end, we ran the same regressions without consideration of robustness. The Hausman test, which presented a chi-square p-value greater than 10%, suggested the use of a random-effects model. Subsequently, the Breusch–Pagan test was performed, which, presenting a p-value lower than 10%, confirmed that the second specification (fixed-effects model or random-effects model) must be used. On the basis of this test, and as the p-value of the Hausman test was greater than 10%, the random-effects model was used.

To verify the joint statistical significance of the temporal effects, for each regression in relation to the resulting p-values, it was possible to affirm that the null hypothesis could be accepted and therefore the temporal effects were always statistically significant at 1%, 5% or 10%. The results of our analysis are reported in Table 5.

Using the random effects model, the two explanatory variables (R&D and patents) were statistically significant at 1% and 10%, and both had a positive association with the ESG score. Among the control variables, those related to company size (TA and Mkt_cap) and company profitability (ROA) were not significant. On the contrary, the variable indicating the presence or absence of a sustainability committee, as well as the variable indicating the adoption or lack of adoption of the GRI guidelines, were statistically significant at 1%. The variable measuring a company’s ability to produce products or offer services that promote responsibility, efficiency, cost-effectiveness and environmental sensitivity was also significant and positively associated with the ESG score. Finally, the environmental innovation score (EIS) variable indicating a company’s ability to reduce environmental costs and burdens for its customers and thus create new market opportunities through new environmental technologies and processes or eco-designed products, was significant at 1%.

The evidence supports our research hypothesis. A positive impact of R&D investment and patent development on ESG performance was found (Broadstock et al., 2020). Indeed, an increase in R&D investment led to an improvement in the ESG score. At the same time, the increase in the number of patents developed by each company also had a positive impact on the ESG score. These results suggest that companies that are inclined to innovate are also those that perform better in terms of adopting ESG practices. Therefore, there is a positive and significant relationship between sustainable performance, as measured by the ESG score, and innovation performance, as measured by R&D investment, and the number of patents developed.

Furthermore, the findings show a positive and significant relationship expressed by the variable EIS, which indicates a company’s ability to create new market opportunities through new environmental technologies and processes or eco-designed products. This result is consistent with the literature, which states that technological innovation offers the greatest opportunity to transform organizations and societies toward more sustainable behaviors (Stolze et al., 2012).

The CSR sustainability committee regressor was a dummy variable. It assumed a value of 1 when the company had a CSR committee; otherwise, it was 0. The evidence showed that the presence of a CSR committee positively affected the ESG score, resulting in an increase of 5.63%. This finding is in line with numerous studies on the implementation of ESG practices by firms, and it confirms the benefit of a sustainability committee, which has the task of promoting the principles and values of sustainable development and proposing related objectives, programs and initiatives for CSR issues, thereby translating into an improvement in the level of corporate sustainability (Shahbaz et al., 2020). The control variable “Product responsibility” also had a positive and significant impact at 1% on the ESG coefficient.

The chi-square test in our model had a p-value of 0.000. The regressors were all jointly significant at 1% and therefore had an effect on the ESG score.

For a regression model to be satisfactory, the R-sq must, in accordance with the theory, have values greater than 50% (Nau, 2019). Although the regressors were all statistically significant using the random-effects model, both individually and jointly, the overall R-sq (i.e. the average between the R-sq in the groups and the R-sq within the groups) was 54.79%.

With regard to the temporal effects, they were statistically significant at 1%, and consequently it is possible to say that they also influenced the dependent variable (ESG score).

5. Discussion and conclusion

The focus of companies on sustainability issues has increased significantly in recent years as a result of worsening environmental pollution and the climate change crisis (Ying and Xin-gang, 2021). The growing interest of companies in sustainability issues is also the result of social pressures to do so, as suggested by institutional theory (Meyer and Roman, 1991). This has encouraged the adoption of more sustainable production policies (Kotze et al., 2010) and the development of business models in line with new ESG requirements (Barbieri, 2007). Instrumental to the pursuit of these objectives and, more generally, to sustainable development is innovation (Maffei et al., 2019; van der Velden, 2018), promoting the reduction of the environmental impact of business processes through the efficient use of resources (Cappiello et al., 2013; Recker et al., 2012). Innovation in general is accompanied by environmental innovation in terms of eco-innovation or eco-design, which are among the tools that promote the development of a sustainable corporate culture (Ahmad and Wu, 2021) and strengthen corporate competitiveness (Ilyas and Osiyevskyy, 2021; Nicolò et al., 2021).

Although the importance of innovation in improving ESG performance is recognized in the literature, there are still only a few empirical studies that analyze this relationship (Zhang et al., 2020a) with a focus on the relationship between ESG and green innovation (Xu et al., 2021). This stems from the increased attention paid by academics to investigating the relationship between ESG performance and firms’ economic and financial performance (Do and Kim, 2020). This study aims to fill this gap by investigating the relationship between R&D and patent investment and firm ESG performance.

The analysis focused on a sample of 182 companies observed for 8 years from 2013 to 2020, providing an integrative framework highlighting the relationships between the adoption of ESG practices and corporate innovation. We considered the ESG scores to provide insight into the role of companies in contributing to sustainability performance. To this end, we analyzed a company’s proactivity in innovating and the potential associations between innovation and ESG performance. The results suggest that companies investing more in innovation (measured by R&D investment and patents) show better ESG performance than less innovative companies. These findings are consistent with the assertion of institutional theory that companies that are more focused on sustainability issues recognize the importance of innovation in achieving these goals, leading to a better corporate image and reputation.

Environmental sustainability and innovation are the two main guidelines of the Next Generation EU which is a European Union plan aimed at supporting member states affected by the COVID-19 pandemic and promoting a sustainable, zero-emission economy. Therefore, innovation, and environmental awareness must be addressed by all players with a univocal and synergistic approach, because for society to rest on solid foundations of development and prosperity in the future, innovation must be increasingly allied with sustainability and vice versa.

Therefore, the positive relationship between ESG performance and innovation is crucial because it signals the awareness of industrial companies of the instrumentality of investment in innovation, both for sustainable development and survival. Indeed, it is essential for companies to integrate sustainability objectives with corporate competitiveness goals, as they represent two closely linked dimensions. In this context, innovation is the most effective way to achieve both corporate and ESG sustainability objectives.

6. Research implications, limitations and future research

The academic community, practitioners and policy makers can draw on the theoretical and practical implications of our results to address the problems of integrating new technologies into ESG sustainability practices with a better understanding of the positive effects of innovation on company sustainability. In this sense, our contribution has practical implications, as the results could spur companies to invest in innovation to realize a positive effect on sustainability.

Given the positive and significant correlation between corporate innovation and ESG practices, national regulators should strengthen laws associated with sustainability practices to ensure greater transparency in disclosure, especially in light of the different theoretical frameworks that exist for non-financial disclosure that limit the comparability of statements (European Commission, 2017).

Regarding the effect of eco-innovation on ESG practices, our study, by showing a positive relationship, provides important practical implications for practitioners and companies investing in innovation. In other words, companies should be encouraged to continuously increase their level of innovation by improving their ESG performance. Therefore, it would be relevant for policymakers to disseminate specific subsidies for companies’ innovation activity, thus indirectly supporting their ESG practices as well.

Finally, we stress the limitations of our study. The data set includes only companies listed in France, Germany, Italy, Spain, the UK and the USA, with specific reference to the industrial sector. Therefore, the results are not generalizable to the universe of companies, operating in other business sectors. In this sense, future research could investigate the effects of the same variables in other contexts. In addition, other factors influencing ESG performance, such as corporate governance, in terms of qualitative and quantitative composition of the board of directors, as well as systematic risk, should be considered in further research. Although our work looks at the logical link between innovation and sustainability, future research could yield interesting information about the relationship between sustainability and evolving generic green digital technologies. Furthermore, future studies could investigate these issues in different economic sectors and examine the differences or similarities between the results.

Table 1.

Variable description

Independent variables	Variable code	Variable description
Research and development	LnR&D	Logarithm of the amount of investment in Research and Development
No. of patents	Patents	Number of patent application
Control variables	Variable code	Variable description
CSR sustainability committee	CSR_Com	Does the company have a CSR sustainability committee?
GRI report guidelines	GRI_Guid	Is the company's CSR report published in accordance with the GRI guidelines?
Environmental innovation score	EIS	Environmental innovation category score reflects a company's capacity to reduce the environmental costs and burdens for its customers, and thereby creating new market opportunities through new environmental technologies and processes or eco-designed products
Product responsibility	Prod_resp	Product responsibility reflects a company's ability to produce products or offer services that promote responsibility, efficiency, cost-effectiveness and environmental sensitivity
Ln total assets	TA	Ln Total Assets
Market capitalization	Mkt_cap	Total market value of a company's outstanding shares of stock
Return on assets	ROA	ROA is calculated as the net profit divided by the total assets

Table 2.

Descriptive statistics

ESG	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	46.662	47.873	51.141	52.637	54.732	57.048	60.348	62.508	54.119
SD	17.616	17.823	18.440	18.133	17.487	17.459	16.024	14.968	18.030
Min	4.01	3.29	4.02	6.02	11.83	15.03	14.67	13.09	3.29
Max	86.97	83.09	86.03	88.15	90.72	90.2	92.98	88.67	92.98
R&D	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	236,315.7	232,444.2	232,639.9	244,020.6	236,005.8	250,020.1	267,193.4	247,607.4	243,267.9
SD	490,792.4	478,711.6	492,921.1	586,255.3	476753.1	496,524.6	508,550.6	446,917.1	496,458.1
Min	0	0	71	86	44	0	221	114	0
Max	3,071,000	3,047,000	3,331,000	4,627,000	3,179,000	3,269,000	3,219,000	2,476,000	4,627,000
Patents	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	67.170	76.890	86.582	85.626	87.686	85.818	86.554	99.296	84.453
SD	174.532	201.915	240.144	234.789	231.996	234.076	231.262	274.163	229.091
Min	0	0	0	0	0	0	0	0	0
Max	1,129	1,397	1,737	1,792	1,820	1,642	1,706	1,998	1,998
CSR_Com	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	0.664	0.642	0.598	0.598	0.620	0.642	0.692	0.769	0.653
SD	0.473	0.480	0.491	0.491	0.486	0.480	0.462	0.422	0.475
Min	0	0	0	0	0	0	0	0	0
Max	1	1	1	1	1	1	1	1	1
GRI_Guid	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	1	1	1	1	1	0.986	1	1	0.998
SD	0	0	0	0	0	0.117	0	0	0.042
Min	1	1	1	1	1	0	1	1	0
Max	1	1	1	1	1	1	1	1	1
EIS	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	31.873	34.158	36.332	36.872	37.648	40.037	43.714	42.774	37.926
SD	31.815	31.076	31.137	31.452	31.473	31.615	31.572	31.579	31.620
Min	0	0	0	0	0	0	0	0	0
Max	99.36	99.34	99.38	97.16	97.4	97.92	99.21	99.1	99.38
Prod_resp	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	48.967	48.942	52.936	54.875	57.498	58.246	58.565	60.812	55.105
SD	30.960	30.860	30.210	30.546	29.518	29.249	28.691	27.154	29.897
Min	0	0	0	0	0	0	0	0	0
Max	99.5	99.44	99.66	99.72	99.73	99.78	99.87	99.84	99.87
TA	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	10,000,000	10,200,000	10,500,000	10,600,000	11,100,000	12,100,000	13,600,000	14,100,000	11,500,000
SD	14,500,000	14,800,000	14,900,000	14,800,000	15,500,000	17,700,000	20,000,000	21,100,000	16,900,000
Min	99,307	61,622	60,603	52,875	58,615	51,995	61,484	56,373	51,995
Max	89,700,000	92,600,000	94,100,000	89,700,000	92,000,000	117,000,000	133,000,000	152,000,000	152,000,000
Mkt_cap	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	8,820,158	9,487,616	9,004,906	9,965,626	12,700,000	11,100,000	14,100,000	14,800,000	11,200,000
SD	14,300,000	15,500,000	135,000,000	15,500,000	21,400,000	19,800,000	23,700,000	24,700,000	19,100,000
Min	13727	9655	106604	124190	112458	58125	31473	26142	9655
Max	102,000,000	105,000,000	96,400,000	99,500,000	174,000,000	183,000,000	183,000,000	146,000,000	183,000,000
ROA	2013	2014	2015	2016	2017	2018	2019	2020	2013–2020
Mean	6.477	6.821	6.892	6.307	7.44	7.987	7.217	3.639	6.597
SD	6.473	7.875	6.906	6.560	5.835	8.030	7.329	9.286	7.442
Min	−22.06	−53.22	−17.96	−17.06	−15.32	−17.32	−17.84	−54.66	−54.66
Max	29.66	45.23	35.98	39.44	27.52	73.86	58.19	35.66	73.86

Table 3.

Correlation matrix

	ESG	R&D	Patents	CSR_Com	GRI_Guid	EIS	Prod_resp	TA	Mkt_cap	ROA
ESG	1
R&D	0.3084***	1
Patents	0.1478***	0.5206***	1
CSR_Com	0.5216***	0.1563***	0.1264***	1
GRI_Guid	0.0705*	−0.0653	−0.0894**	−0.0155	1
EIS	0.5065***	0.3050***	0.1927***	0.1999***	0.0541	1
Prod_resp	0.5107***	0.1019***	0.0264	0.2430***	0.0626	0.2704***	1
TA	0.4773***	0.6577***	0.3081***	0.1940***	−0.0296	0.2911***	0.1873***	1
Mkt_cap	0.2664***	0.5577***	0.4069***	0.1405***	−0.0082	0.1344***	0.0074	0.5963***	1
ROA	−0.1686***	−0.0220	−0.0902***	−0.1316***	0.0079	−0.1332***	−0.1112***	−0.1821***	0.0905***	1

Table 4.

Variance inflation factor

Variable	VIF
R&D	2.41
Patents	1.64
CSR_Com	1.11
GRI_Guid	1.03
EIS	1.11
Prod_resp	1.12
TA	2.11
Mkt_cap	2.25
ROA	1.21
Mean VIF	1.55

Table 5.

Regression results

Model	(A)	(B)	(C)
	Pooled OLS	Fixed effects	Random effects
	Coefficient	Coefficient	Coefficient
	(Robust SE)	(Robust SE)	(Robust SE)
R&D	1.89** (0.589)	3.145*** (1.299)	2.012*** (0.898)
Patents	0.005* (0.003)	0.001 (0.005)	0.005* (0.003)
CSR_Com	8.39*** (2.21)	4.696 (2.917)	5.63*** (2.099)
GRI_Guid	9.67*** (3.22)	1.42*** (0.462)	2.08*** (0.364)
EIS	0.134*** (0.04)	0.207*** (0.032)	0.187*** (0.031)
Prod.resp	0.227*** (0.036)	0.171*** (0.034)	0.202*** (0.030)
TA	−0.619 1.049	1.47 (3.337)	−0.476 (1.24)
Mkt_cap	0.00 0.00	0.00 0.00	0.00 0.00
ROA	−0.010 (0.106) (0.504)	−0.097 (0.071) (omitted)	−0.088 (0.073) (0.545)
Hausman test	16.08
	(p-value = 0.412)
Breusch and Pagan test	198.48
	(p-value = 0.000)
Years	2013–2020	2013–2020	2013–2020
Temporal effects	No	Yes	Yes
Standard errors for grouped data	Yes	Yes	Yes
R-square	58.19	36.34	54.79
Statistics F	–	–	Chi-square
			588.7***

Notes:

*** = significant at 1%; ** = significant at 5%; * = significant at 10%.

Parentheses indicate the standard error of robust regression