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Article

Digitalisation, Digital Governance, and Eco-Innovation: Evidence from Cross-Country Data in 2022

by
Keisuke Kokubun
Graduate School of Management, Kyoto University, Kyoto 606-8501, Japan
Information 2026, 17(3), 306; https://doi.org/10.3390/info17030306
Submission received: 17 February 2026 / Revised: 19 March 2026 / Accepted: 21 March 2026 / Published: 22 March 2026
(This article belongs to the Special Issue Standards Digitisation and Digital Standardisation)
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Abstract

This study examines the relationship between digitalisation and eco-innovation across countries, with a particular focus on the role of digital government and digital standardisation. Using cross-country data for 2022, eco-innovation is proxied by environment-related patenting activity, while digitalisation is measured using the United Nations E-Government Development Index (EGDI). Employing a combination of ordinary least squares, population-weighted regressions, spline specifications, and quantile regressions, we document three main findings. First, digitalisation is positively and robustly associated with eco-innovation across countries. Second, the relationship is non-linear, with marginal effects that strengthen at higher levels of digital development, suggesting important complementarities between digital capabilities and national innovation systems. Third, the association between digitalisation and eco-innovation is heterogeneous across the distribution of eco-innovation, with particularly strong associations observed among countries with intermediate levels of innovative activity. Taken together, these findings suggest that digitalisation is systematically associated with eco-innovation across countries and indicate the potential relevance of digital governance and digital standardisation to sustainable technological change.

1. Introduction

Achieving sustainable development requires not only technological advances in environmental domains but also institutional and governance structures capable of supporting innovation and diffusion. In recent years, digitalisation has emerged as a key structural transformation shaping economic activity, public administration, and innovation systems [1,2]. In the digital transformation literature, digitalisation is increasingly understood not merely as the adoption of information and communication technologies, but as a broader institutional transformation that reshapes organizational structures, governance mechanisms, and coordination processes [3,4]. Beyond improving efficiency and connectivity, digitalisation can fundamentally alter how environmental challenges are addressed by reducing information costs, enhancing coordination, and improving regulatory transparency. In this respect, digitalisation can also be understood as a complementary institutional condition that shapes the direction of technological change, in a manner consistent with the literature on directed technical change induced by environmental regulation [5].

2. Literature Review and Conceptual Background

2.1. Digital Transformation as Information Infrastructure

Digitalisation is widely understood as a process through which digital technologies restructure organisational processes, economic coordination, and institutional arrangements. Vial [6] defines digital transformation as fundamental organisational change enabled by information, computing, communication, and connectivity technologies. Yoo et al. [7] emphasise the reprogrammability, data homogenisation, and generativity of digital technologies, enabling new forms of recombination and innovation.
From an information systems perspective, digital infrastructures are socio-technical systems evolving through interactions among technical standards, organisational routines, and institutional environments (Tilson et al. [8]; Henfridsson and Bygstad [9]). Innovation emerges from integrating digital capabilities with institutional structures, facilitating knowledge creation and diffusion (Mergel et al. [10]; Dawes [11]). Digitalisation should therefore be conceptualised as an information infrastructure that enhances interoperability, reduces coordination costs, and supports innovation.

2.2. Digital Government and Institutional Capacity

Digital government represents a critical institutional dimension of digital transformation. It refers to the use of digital technologies to improve public administration, service delivery, and governance capacity (Luna-Reyes and Gil-Garcia [12]; Fountain [13]; Gil-Garcia [14]). Digital government infrastructures facilitate information processing, integration, and dissemination across public and private sectors.
These systems function as coordination platforms linking firms, research institutions, and regulatory authorities (Brynjolfsson and McAfee [15]; Forman et al. [16]). By improving transparency, interoperability, and accessibility, digital government enhances institutional capacity and innovation outcomes.

2.3. Digital Standardisation and Information Interoperability

Digital standardisation is a fundamental component of digitalisation. Standards ensure interoperability and compatibility (Hanseth and Lyytinen [17]; Lyytinen and King [18]). They reduce fragmentation and uncertainty, facilitating coordination and innovation (David and Greenstein [19]; Blind [20]).
Digital infrastructures rely on shared standards linking government, firms, and institutions. The E-Government Development Index reflects national digital integration and interoperability (United Nations [21]). Although EGDI does not directly measure standardisation separately, it captures integration embedded in digital infrastructures.

2.4. Digitalisation and Eco-Innovation

Empirical evidence increasingly links digitalisation to eco-innovation and environmental performance. Cross-country and regional studies show that digital development improves environmental governance and green technological progress (Ren et al. [22]; Sun and Guo [23]; Zhang et al. [24]). At the firm and regional levels, digital technologies enhance knowledge diffusion and innovation efficiency (Mäkitie et al. [25]; Xie et al. [26]).
Digital government also plays an important role. E-government development is associated with improved environmental sustainability and green innovation efficiency (Androniceanu and Georgescu [27]; Li and Lou [28]). Digital governance strengthens state capacity by improving coordination and regulatory effectiveness (Peng [29]), enabling policy coherence (Margetts and Dunleavy [30]; OECD [31]).
However, digitalisation may also generate unintended environmental effects. Efficiency gains can increase energy consumption and environmental costs (Lange et al. [32]; Wang et al. [33]), while weak governance may create coordination failures (Chen [34]).
Digital government infrastructures facilitate eco-innovation by improving coordination and organisational performance (Atobishi et al. [35]). EGDI provides a comprehensive measure of these capabilities (United Nations [21]).
Despite this growing literature, several gaps remain.
First, most studies focus on private-sector or regional digitalisation.
Second, national-level digital government remains underexplored.
Third, existing research rarely considers institutional complementarities.
Innovation outcomes depend on complementary capabilities (Acemoglu et al. [36]; Cirera et al. [37]; Dechezleprêtre and Sato [38]).
Finally, distributional heterogeneity remains insufficiently examined (Ren et al. [22]; Zhang et al. [24]).

2.5. Research Gap and Contribution

This study addresses these gaps by examining how digital government development is associated with eco-innovation across countries.
Conceptualising digital government as a national-level information infrastructure, this study contributes to the information systems literature by demonstrating how digital infrastructures shape innovation outcomes at the macro level. Figure 1 presents the conceptual model guiding the empirical analysis. Digital government development—captured by the E-Government Development Index (EGDI) and its core components—is expected to be associated with eco-innovation through regulatory coordination, information transparency, and administrative efficiency. These institutional conditions may be linked to lower transaction costs and to the diffusion and commercialisation of environmentally related technologies. This interpretation is consistent with the environmental economics literature showing that well-designed regulatory and institutional frameworks can promote innovation without undermining competitiveness [39].

3. Data and Empirical Strategy

3.1. Eco-Innovation

Eco-innovation is proxied by environment-related patenting activity drawn from the OECD ENV-TECH database. Environment-related patents are widely used in the literature as an indicator of eco-innovation, as they capture inventive efforts aimed at reducing environmental impacts or improving resource efficiency [40,41,42].
Patent counts are adjusted for population size and expressed as patents per million inhabitants to ensure comparability across countries of different sizes. To mitigate the influence of extreme values and skewness commonly observed in patent data, we apply logarithmic transformations and additionally employ winsorised measures of patent intensity at the upper and lower tails of the distribution. These transformations are standard practice in cross-country innovation studies and help ensure the robustness of the empirical results.

3.2. Digitalisation

Digitalisation is measured using the United Nations E-Government Development Index (EGDI), which captures the extent of digital government development across countries. EGDI is a composite index constructed from three core dimensions: online service provision, telecommunication infrastructure, and human capital [21].
Importantly, EGDI reflects not only technological readiness but also institutional capacity and the ability of governments to design, implement, and coordinate digital public services. As such, it provides a comprehensive proxy for digital governance rather than merely digital infrastructure. This feature makes EGDI particularly suitable for analysing the role of digitalisation in public-sector-driven innovation processes, where institutional quality, regulatory capacity, and information management are central [21,30].

3.3. Empirical Strategy

The baseline empirical specification relates eco-innovation outcomes to EGDI scores using cross-sectional regressions for the year 2022. To examine the robustness of the results and to capture potential non-linearities and heterogeneity, we estimate a series of complementary models:
  • Baseline OLS regressions, estimating the average association between digitalisation and eco-innovation;
  • Population-weighted OLS regressions, accounting for cross-country differences in population size;
  • Winsorised regressions, reducing sensitivity to extreme observations in patent counts;
  • Spline regressions, allowing for non-linear effects of digitalisation across different levels of EGDI;
  • Quantile regressions, examining heterogeneity in the digitalisation–eco-innovation relationship across the conditional distribution of eco-innovation outcomes [42].
Heteroskedasticity-robust standard errors are reported for all mean regressions. For quantile regressions, bootstrap standard errors are employed to ensure reliable inference.

4. Results: Digitalisation and Eco-Innovation

The empirical analysis follows the conceptual framework illustrated in Figure 1, which links digital government development to eco-innovation through institutional capacity, while explicitly allowing for non-linear and heterogeneous effects across countries. Based on this framework, the following sections empirically evaluate these relationships using cross-country data for the year 2022.
Table 1 reports the regression results examining the association between digitalisation and eco-innovation across countries. Panel A presents mean effects estimated using ordinary least squares (OLS) and spline regressions. Across all linear specifications, the coefficient on the E-Government Development Index (EGDI) is positive and statistically significant at the 1% level, indicating a robust positive relationship between digital government development and environment-related patenting activity. This result remains stable when eco-innovation is measured in logarithmic form, when regressions are weighted by population, and when the dependent variable is winsorised to mitigate the influence of extreme observations.
The consistency of these findings across alternative specifications supports the argument that digital government development plays a systematic role in fostering eco-innovation. Moreover, the use of spline regressions allows the analysis to capture potential non-linearities in this relationship, which is consistent with theoretical arguments emphasizing complementarities between digital capabilities, institutional quality, and innovation systems [36,37,38].
The positive baseline relationship between digitalisation and eco-innovation is illustrated graphically in Figure 2, which plots environment-related patent intensity against EGDI across countries in 2022. The fitted linear relationship reveals a clear upward-sloping pattern, suggesting that countries with more advanced digital government infrastructures tend to exhibit higher levels of eco-innovative activity.
The spline specification in column (4) provides further evidence of non-linearity in this relationship. All spline components are positive and statistically significant, suggesting that the marginal effect of digitalisation on eco-innovation increases as countries reach higher levels of digital development. This non-linear pattern is visualised in Figure 3, which shows fitted values from the spline regression along with confidence intervals. The figure indicates a convex relationship, implying that digitalisation yields disproportionately larger eco-innovation gains once a sufficiently high level of digital maturity is achieved. This pattern is consistent with theories of technological complementarities [36,37]. Recent evidence further supports this interpretation, as digital technologies have been shown to generate substantial productivity and innovation gains only once complementary capabilities and institutions are sufficiently developed [38].
To examine heterogeneity across the eco-innovation distribution, we employ quantile regression techniques following Koenker and Bassett [42]. Panel B reports the results of the median (τ = 0.5) quantile regression, which reveal substantial distributional heterogeneity in the relationship between digitalisation and eco-innovation. The estimated coefficient on the E-Government Development Index (EGDI) remains positive and highly significant, and its magnitude exceeds that obtained from the mean-based regressions.
This finding suggests that the association between digital government development and eco-innovation is particularly pronounced among countries located around the middle of the eco-innovation distribution, rather than being driven solely by top-performing economies. The pattern is further illustrated in Figure 4 and is consistent with recent quantile-based evidence showing heterogeneous effects of digitalisation on green innovation outcomes [43]. These results suggest that digitalisation may be particularly relevant for countries with intermediate levels of innovative capacity, where institutional improvements may be more closely associated with observable innovation outputs.
To assess the robustness of the baseline results and to explore the institutional mechanisms underlying the observed relationships, Table 2, Table 3 and Table 4 report additional analyses. These tables provide supplementary information to support the main empirical analysis. Specifically, Table 2 reports descriptive statistics for all variables included in the analysis. Table 3 decomposes the E-Government Development Index (EGDI) into its core sub-indices—Online Service Index, Telecommunication Infrastructure Index, and Human Capital Index—to identify which dimensions of digital government are most strongly associated with eco-innovation. Finally, Table 4 lists all countries included in the sample, thereby clarifying the geographical coverage and external validity of the findings.

5. Discussion

By explicitly modeling non-linear and heterogeneous patterns, this study extends previous empirical work that typically assumes linear relationships between digitalisation and innovation. The results suggest that the association between digitalisation and eco-innovation becomes stronger after a certain level of institutional and digital maturity has been reached, thereby providing a more nuanced understanding of how digital transformation may relate to sustainable development across countries.
The results provide several insights into the role of digitalisation in shaping eco-innovation across countries. First, the consistently positive association between the E-Government Development Index (EGDI) and environment-related patenting suggests that digitalisation is broadly associated with eco-innovation. As illustrated in Figure 2, countries with more advanced digital government infrastructures tend to exhibit systematically higher levels of eco-innovative activity. By improving information accessibility, administrative efficiency, and coordination between public and private actors, digital government may be associated with lower transaction costs and fewer barriers to innovation in environmentally relevant domains [22,30].
More importantly, the non-linear pattern identified in the spline regression—and visualised in Figure 3—indicates that the relationship between digitalisation and eco-innovation is not uniform across levels of digital development. The strengthening marginal effects observed at higher EGDI levels point to the presence of possible complementarities between digital capabilities and national innovation systems. In countries with limited digital infrastructure and weak institutional capacity, marginal improvements in digitalisation may be insufficient to be associated with substantial eco-innovation outcomes. By contrast, once a critical level of digital maturity is achieved, digital tools and standards may be more closely integrated within regulatory frameworks, research networks, and market mechanisms, and this integration may be associated with higher levels of eco-innovative activity. This pattern is consistent with the literature on technological complementarities and capability thresholds, which emphasises that the productivity and innovation returns to digital technologies depend crucially on complementary organisational and institutional conditions [36,37,38].
The convex, non-linear relationship shown in Figure 3 is consistent with the argument that digitalisation may require a certain “governance threshold” before stronger associations with eco-innovation become observable. In countries with low digital maturity, the potential association between digitalisation and eco-innovation may be weaker because of high administrative costs or the lack of interoperable standards—a form of “digital friction” that may limit the diffusion of environmental technologies [21]. This finding suggests that interoperable digital systems and administrative integration may be associated with eco-innovation. However, because the present analysis does not directly measure formal standard-setting activities, the E-Government Development Index should primarily be interpreted as a proxy for digital governance capacity rather than as a direct measure of digital standardisation. Moreover, the finding that digitalisation is most strongly associated with eco-innovation among countries with intermediate innovative capacity suggests that these nations may have integrated digital tools into their regulatory frameworks while avoiding the excessive complexity that can lead to diminishing marginal returns in highly advanced economies [44].
The results are consistent with the conceptual framework presented in Figure 1. In particular, the stronger associations observed for telecommunication infrastructure and online service provision (Table 3) are consistent with the argument that digital standardisation and service interoperability—rather than digital skills alone—may represent important institutional channels linked to eco-innovation. Although the analysis does not directly measure formal standard-setting activities, the components of the EGDI may capture de facto standardisation through interoperable digital services, harmonised administrative procedures, and integrated public-sector platforms.
These results are also consistent with recent evidence suggesting that digital technologies contribute to innovation only when embedded within supportive institutional and governance frameworks [38,44]. The observed non-linear patterns therefore do not necessarily reflect purely technological impacts, but may instead reflect the interaction between digital systems and institutional capacity. In this sense, digitalisation may be associated with eco-innovation not mechanically, but through its relationship with coordination, regulatory fragmentation, and the diffusion of environmentally relevant technologies within well-functioning governance structures.
Additional evidence further illustrates possible institutional channels underlying this relationship. In particular, Table 3 shows that telecommunication infrastructure and online service provision are more strongly associated with eco-innovation than the human capital component alone, highlighting the central role of digital connectivity and service delivery in green innovation. This finding suggests that the association between digitalisation and eco-innovation may depend less on digital skills in isolation and more on the extent to which digital systems are embedded in interoperable administrative and regulatory frameworks that support information flows and coordination across actors.
The quantile regression results further reveal substantial heterogeneity across the distribution of eco-innovation. As illustrated in Figure 4, the association between digitalisation and eco-innovation is strongest around the median of the eco-innovation distribution, while remaining positive but weaker at both the lower and upper tails. This pattern indicates that digital development may be particularly relevant for countries with intermediate levels of eco-innovative capacity. In such contexts, digitalisation may be associated with weaker institutional and informational constraints, allowing countries to translate existing technological capabilities more effectively into observable innovation outcomes. By contrast, countries at the lower end of the distribution may lack complementary inputs—such as human capital, research infrastructure, or financial resources—while countries at the upper end may already operate close to the technological frontier, where further digitalisation may be less strongly associated with additional innovation outcomes.
Taken together, the evidence from the tables and figures suggests that digitalisation should not be viewed merely as a neutral technological upgrade, but rather as a structural component of development that interacts closely with institutional quality and innovation capacity. The association between digital transformation and eco-innovation therefore appears to depend on the broader developmental context, reinforcing the possible importance of coordinated investments in digital infrastructure, innovation systems, and environmental policy frameworks. This interpretation is consistent with recent studies emphasising that digital technologies generate innovation benefits primarily when supported by adequate institutional and governance conditions [38,44].

6. Policy Implications

The findings of this study suggest several possible policy implications for governments seeking to promote eco-innovation through digital transformation. First, the consistently positive relationship between digitalisation and eco-innovation suggests that investments in digital government infrastructure may be associated not only with administrative efficiency gains but also with broader environmental benefits. Policies aimed at expanding e-government services, improving digital interoperability, and enhancing data transparency may be associated with higher eco-innovative activity by reducing informational frictions, regulatory uncertainty, and coordination costs faced by firms and innovators.
Second, the non-linear effects identified in the analysis imply that piecemeal or isolated digital initiatives are unlikely to be effective in low–digital-capacity settings. In countries at early stages of digital development, policy efforts should prioritise foundational digital infrastructure, institutional capacity building, and basic digital literacy. Without these complementary conditions, marginal improvements in digitalisation are unlikely to translate into meaningful gains in eco-innovation. This finding highlights the importance of sequencing in digital policy: establishing core digital standards and administrative capabilities is a prerequisite for leveraging digitalisation as a driver of green innovation [30,38].
Third, the heterogeneous associations observed across the distribution of eco-innovation point to the need for differentiated policy strategies. The particularly strong association between digitalisation and eco-innovation among countries with intermediate levels of eco-innovation suggests that “middle performers” may offer the highest returns to digital policy interventions. For these countries, targeted investments in digital platforms, regulatory sandboxes, and standardised data-sharing frameworks may help unlock latent innovative potential by supporting coordination between government agencies, research institutions, and private firms [44].
Finally, the results suggest that digital standardisation may be a relevant policy consideration. Harmonised digital standards—such as interoperable data formats, unified reporting systems, and common platforms for environmental information—may be associated with greater scalability and diffusion of eco-innovations across sectors and national boundaries. From a policy perspective, aligning digital transformation strategies with environmental and innovation policies may help avoid fragmentation and increase synergies. International cooperation on digital standards may therefore be associated with broader diffusion of eco-innovative technologies and may support sustainable development pathways.

7. Limitations and Future Research

Several limitations of this study should be acknowledged, which also point to promising directions for future research.
First, the empirical analysis is based on cross-sectional data for a single year (2022), which limits the ability to draw strong causal inferences regarding the impact of digitalisation on eco-innovation. Although the results reveal robust associations and systematic patterns of non-linearity and heterogeneity, future studies could employ panel data to examine dynamic relationships and better address potential issues of reverse causality and omitted variable bias. While the analysis controls for income and education, the relatively small sample size (57 countries) reflects data availability constraints for environment-related patenting and digital government indicators in 2022. Table 4 documents the full list of countries included in the analysis, covering advanced, upper-middle-income, and emerging economies, thereby clarifying the scope and limits of external validity.
Second, digitalisation is proxied by the E-Government Development Index (EGDI), which primarily captures public-sector digital capacity. Although EGDI is well-suited to the study’s focus on digital governance and institutional standardisation, it does not fully capture other dimensions of digital transformation, such as private-sector digital adoption, firm-level technology use, or platform-based innovation. Future research could therefore integrate EGDI with complementary indicators—such as broadband penetration, cloud computing adoption, or digital skills measures—to provide a more comprehensive assessment of how different dimensions of digitalisation interact with eco-innovation [23,45].
Third, eco-innovation is measured using environment-related patent counts, which reflect inventive activity but do not necessarily capture the diffusion, commercialisation, or environmental impact of green technologies. Patent quality and relevance may also vary across countries and technological fields. Future work could extend the present analysis by incorporating alternative outcome measures, such as green technology deployment, environmental performance indicators, or firm-level innovation outcomes, in order to better assess the real-world implications of digitalisation for sustainable development [25,39].
Finally, while this study highlights the importance of digital standardisation and institutional complementarities, it does not explicitly model the specific policy mechanisms through which digitalisation affects eco-innovation. Future research could explore more granular channels—such as regulatory transparency, data interoperability, or digital public procurement systems—and examine how international coordination on digital standards shapes the cross-border diffusion of eco-innovative technologies. Such extensions would further strengthen the understanding of how digital governance contributes to sustainability transitions and long-term innovation performance.

8. Conclusions

This study examines the relationship between digitalisation and eco-innovation using cross-country data for 2022, with a particular focus on the role of digital government and digital standardisation. Using environment-related patenting as a proxy for eco-innovation and the E-Government Development Index (EGDI) as a measure of digitalisation, the analysis yields three main findings.
It is important to clarify that this study does not claim that digitalisation per se automatically leads to eco-innovation. Rather, the empirical analysis provides evidence of a robust association between digital government development—as captured by the E-Government Development Index—and eco-innovation outcomes.
The contribution of this study therefore lies in identifying the institutional dimension of digitalisation, rather than in evaluating digital technologies in general. By focusing on digital governance, the analysis highlights how institutional coordination, regulatory capacity, and standardised digital systems may be related to differences in innovation outcomes across countries.
First, digitalisation is positively and robustly associated with eco-innovation across countries. This relationship remains stable across multiple model specifications, including population-weighted regressions and winsorised estimations, suggesting that the observed effects are not driven by outliers or scale-related biases. Second, the relationship is non-linear: spline regressions indicate that the association between digitalisation and eco-innovation becomes stronger at higher levels of digital development, pointing to possible complementarities between digital capabilities and national innovation systems. Third, quantile regression results reveal substantial heterogeneity across the distribution of eco-innovation, with the strongest effects observed among countries at intermediate levels of innovative activity.
Taken together, these findings suggest that digitalisation is systematically associated with eco-innovation across countries and should be understood as part of a broader institutional context related to innovation outcomes. In this context, digital standardisation—through interoperable systems, harmonised data frameworks, and transparent digital governance—may be one relevant factor associated with the eco-innovation benefits observed in digitally more advanced settings [25,30,45].
By highlighting the non-linear and distribution-dependent patterns of association between digitalisation and eco-innovation, this study contributes to the growing literature on digital governance and sustainable innovation. The results suggest the possible importance of coordinated digital and environmental policy strategies and point to digital standardisation as a potentially relevant factor in discussions of eco-innovation and sustainable development.
Because the present analysis is cross-sectional, these findings should be interpreted as evidence of association rather than as confirmation of causal mechanisms.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Figure 2. Digitalisation and eco-innovation. This figure shows the baseline relationship between digitalisation and eco-innovation across countries in 2022. Digitalisation is measured by the E-Government Development Index (EGDI), while eco-innovation is proxied by the logarithm of environment-related patents per million inhabitants. The solid line represents fitted values from a linear regression, with the shaded area indicating the 95% confidence interval. The figure reveals a strong positive association between digital development and eco-innovation.
Figure 2. Digitalisation and eco-innovation. This figure shows the baseline relationship between digitalisation and eco-innovation across countries in 2022. Digitalisation is measured by the E-Government Development Index (EGDI), while eco-innovation is proxied by the logarithm of environment-related patents per million inhabitants. The solid line represents fitted values from a linear regression, with the shaded area indicating the 95% confidence interval. The figure reveals a strong positive association between digital development and eco-innovation.
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Figure 3. Digitalisation and eco-innovation. This figure illustrates the non-linear relationship between digitalisation and eco-innovation across countries in 2022. The horizontal axis reports the E-Government Development Index (EGDI), while the vertical axis shows the logarithm of environment-related patent counts per million inhabitants. The solid line represents fitted values from a spline regression, and the shaded area denotes the 95% confidence interval. The figure indicates a convex relationship, suggesting that the marginal effect of digitalisation on eco-innovation strengthens at higher levels of digital development.
Figure 3. Digitalisation and eco-innovation. This figure illustrates the non-linear relationship between digitalisation and eco-innovation across countries in 2022. The horizontal axis reports the E-Government Development Index (EGDI), while the vertical axis shows the logarithm of environment-related patent counts per million inhabitants. The solid line represents fitted values from a spline regression, and the shaded area denotes the 95% confidence interval. The figure indicates a convex relationship, suggesting that the marginal effect of digitalisation on eco-innovation strengthens at higher levels of digital development.
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Figure 4. Heterogeneous effects of digitalisation across the distribution of eco-innovation. This figure presents quantile regression estimates of the effect of digitalisation (EGDI) on eco-innovation in 2022. Points indicate coefficient estimates at the 25th, 50th, and 75th percentiles of the eco-innovation distribution, while vertical bars denote 95% confidence intervals. The results reveal substantial heterogeneity: the impact of digitalisation is strongest around the median of the distribution, indicating that digital capabilities disproportionately enhance eco-innovation in countries with intermediate levels of innovative activity.
Figure 4. Heterogeneous effects of digitalisation across the distribution of eco-innovation. This figure presents quantile regression estimates of the effect of digitalisation (EGDI) on eco-innovation in 2022. Points indicate coefficient estimates at the 25th, 50th, and 75th percentiles of the eco-innovation distribution, while vertical bars denote 95% confidence intervals. The results reveal substantial heterogeneity: the impact of digitalisation is strongest around the median of the distribution, indicating that digital capabilities disproportionately enhance eco-innovation in countries with intermediate levels of innovative activity.
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Table 1. Digitalisation and Eco-Innovation (2022).
Table 1. Digitalisation and Eco-Innovation (2022).
Panel A. Mean effects (OLS and spline regressions)
(1) Baseline OLS(2) Pop.-Weighted OLS(3) Winsorised OLS(4) Spline Regression
Dependent variablel_env_patl_env_patl_env_pat_wl_env_pat_w
EGDI12.31 ***10.28 ***12.19 ***
(1.145)(2.032)(1.122)
Spline term 1 3.593 ***
(0.429)
Spline term 2 4.390 ***
(0.966)
Spline term 3 4.185 ***
(0.403)
Constant−6.451 ***−4.714 ***−6.357 ***1.123 ***
(0.932)(1.558)(0.912)(0.355)
Observations57575757
R20.6270.6520.6240.663
Panel B. Distributional effects (Quantile regression, τ = 0.5)
Median (τ = 0.5)
Dependent variablel_env_pat_w
EGDI13.01 ***
(1.236)
Constant−6.942 ***
(1.016)
Observations57
Notes: Standard errors are reported in parentheses. Panel A reports heteroskedasticity-robust standard errors. Panel B reports bootstrap standard errors. Eco-innovation is measured as the logarithm of environment-related patents per million inhabitants. Digitalisation is proxied by the E-Government Development Index (EGDI). *** p < 0.01.
Table 2. Descriptive Statistics (2022).
Table 2. Descriptive Statistics (2022).
VariableMeanStd. Dev.MinMaxN
Log env.-related patents per million (winsorised)3.5301.6160.3826.11257
E-Government Development Index (EGDI)0.8110.1050.5270.97257
Online Service Index0.7800.1290.4200.98357
Telecommunication Infrastructure Index0.7950.1330.3950.98057
Human Capital Index0.8570.0990.5761.00057
Log GDP per capita9.8801.0657.49811.58557
Tertiary enrollment rate (%)70.44025.70921.033166.66653
Notes: This table reports descriptive statistics for the cross-section of countries used in the empirical analysis. Eco-innovation is measured as the logarithm of environment-related patents per million inhabitants (winsorised). Digitalisation is proxied by the E-Government Development Index (EGDI) and its subcomponents. GDP per capita and tertiary enrollment rates are obtained from the World Development Indicators.
Table 3. Digitalisation, Income, and Eco-Innovation: Robustness and Decomposition (2022).
Table 3. Digitalisation, Income, and Eco-Innovation: Robustness and Decomposition (2022).
Panel A. Digitalisation with Income and Education Controls
Variables(A1)
Online Service Index1.863 (1.174)
Telecommunication Infrastructure Index1.353 (1.872)
Human Capital Index1.432 (2.602)
Log GDP per capita0.964 * (0.166)
Constant−9.747 *** (0.947)
Observations57
R20.763
Panel B. EGDI Components without Income Control
Variables(A2)
Online Service Index2.203 (1.577)
Telecommunication Infrastructure Index7.769 *** (1.700)
Human Capital Index1.515 (2.845)
Constant−5.668 *** (1.116)
Observations57
R20.656
Dependent variable: Log of environment-related patents per million inhabitants (winsorised). Notes: Robust heteroskedasticity-consistent standard errors are reported in parentheses. Eco-innovation is measured as the logarithm of environment-related patents per million inhabitants, winsorised at the 1st and 99th percentiles. Digitalisation components are derived from the United Nations E-Government Development Index (EGDI): Online Service Index, Telecommunication Infrastructure Index, and Human Capital Index. GDP per capita is measured in constant prices (log). *** p < 0.01, * p < 0.10.
Table 4. List of Countries Included in the Analysis (2022).
Table 4. List of Countries Included in the Analysis (2022).
CategoryNumber of Countries
Advanced economies20
Upper-middle-income economies18
Lower-middle/emerging economies12
Total57
Notes: This table reports the list of countries included in the empirical analysis. All countries have complete information on eco-innovation (environment-related patents), digitalisation (EGDI), population, and control variables for the year 2022. Advanced economies: Andorra; Australia; Austria; Belgium; Canada; Denmark; Finland; France; Germany; Ireland; Israel; Italy; Japan; Luxembourg; Netherlands; Norway; Sweden; Switzerland; United Kingdom; United States. Upper-middle-income economies: Argentina; Brazil; Bulgaria; Chile; Colombia; Croatia; Czech Republic; Greece; Hungary; Lithuania; Latvia; Mexico; Poland; Portugal; Romania; Saudi Arabia; Slovak Republic; Slovenia. Lower-middle-income and emerging economies: Bangladesh; Egypt; India; Iran; Lebanon; Moldova; Morocco; Peru; Philippines; Serbia; South Africa; Ukraine. Country classification broadly follows the World Bank income classification. The sample includes a wide range of income levels and institutional contexts, allowing for meaningful cross-country comparison. Small states (e.g., Andorra) are retained due to complete data availability on patenting and digital government indicators. The presence of both advanced and developing economies supports the external validity of the results, while the relatively small sample size reflects data availability constraints for environment-related patenting in 2022.
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Kokubun, K. Digitalisation, Digital Governance, and Eco-Innovation: Evidence from Cross-Country Data in 2022. Information 2026, 17, 306. https://doi.org/10.3390/info17030306

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Kokubun K. Digitalisation, Digital Governance, and Eco-Innovation: Evidence from Cross-Country Data in 2022. Information. 2026; 17(3):306. https://doi.org/10.3390/info17030306

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Kokubun, Keisuke. 2026. "Digitalisation, Digital Governance, and Eco-Innovation: Evidence from Cross-Country Data in 2022" Information 17, no. 3: 306. https://doi.org/10.3390/info17030306

APA Style

Kokubun, K. (2026). Digitalisation, Digital Governance, and Eco-Innovation: Evidence from Cross-Country Data in 2022. Information, 17(3), 306. https://doi.org/10.3390/info17030306

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