Fostering deep technology to face global challenges: a study of a Nordic country’s innovation policy

ABSTRACT

Deep techs help tackle global challenges, but there is a need for more knowledge about promoting them through innovation policies. This article aims to identify the elements of innovation policies that foster deep techs to tackle socio-environmental challenges. We employed a qualitative, exploratory-descriptive approach and conducted document analysis to examine Denmark's policy instruments. By examining innovation-related policies, we found that they are challenge-oriented, comprising education, funding, and collaboration approaches, and influenced by variables such as sector strategies, knowledge, and management. We have contributed in several ways. Firstly, conceptually, by proposing a theoretical framework for innovation policy to support deep technology solutions to global challenges. Secondly, government practices that affect the business environment by establishing elements oriented toward the composition of public policies; and thirdly, socially and economically, by supporting the fostering of deep tech ventures and environmental preservation.

KEYWORDS:
Deep technology; Innovation policy; Global challenges

1. Introduction

Governments worldwide are concerned with tackling significant problems in societies. Conversely, innovation policies are forms of public intervention to promote innovative solutions (EDLER et al., 2016; EDLER; FAGERBERG, 2017; FAGERBERG, 2017) as deep technologies, that have a high potential of facing these challenges. Deep technologies, also known as deep techs, are disruptive early-stage solutions that leverage scientific or engineering advances. They can address grand societal challenges, but specific approaches to innovation policies for their development and support could be necessary (DE LA TOUR et al., 2021; ROMASANTA et al., 2022).

However, while mainstream theory has investigated innovation policy in addressing significant social challenges (EDLER et al., 2016; BOON; EDLER, 2018; ROBINSON; MAZZUCATO, 2019; JANSSEN et al., 2021), combinations with deep technologies are in their early stages. Previous publications aimed mainly at deep tech conceptualisation (APODACA; MURRAY; FROLUND, 2022; ROMASANTA et al., 2022) and technical reports (DE LA TOUR et al., 2021; PORTINCASO et al., 2021), failing to approach scientifically the impact of innovation policy. More studies are needed to extend theoretical lenses to help determine and support this innovation. Furthermore, more practical advice is required for innovation policy to impact real-life policymaking (JANSSEN et al., 2021; HADDAD et al., 2022). Significant global challenges have deepened in the last few years (PACTO GLOBAL, 2021; UNITED NATIONS, 2021), with some countries having successfully faced these challenges through consistent policies that foster deep tech. In such a context, the central question of this paper is: How do innovation policies foster deep tech in response to socio-environmental challenges?

This paper aims to identify the constituent elements of proposed innovation policies in Denmark that address deep tech innovations, to promote responses to socio-environmental challenges. Denmark is considered a leading country in both deep tech innovation and environmental performance. As one of the Nordic countries, Denmark has a tradition of ecological concern and a reputation for consistently applying progressive environmental policies (KHAN; JOHANSSON; HILDINGSSON, 2021). There is also evidence that societal and environmental problems are being addressed by the country with Science, Technology, and Innovation policies (SCORDATO et al., 2022). Denmark ranks number 10 among the world’s most innovative countries in the Global Innovation Index 2022. It tops the 2022 Environmental Performance Index (WOLF et al., 2022), with leadership in sectors such as clean energy and sustainable agriculture. The investigation strategy employs a qualitative approach to analyzing a single case, utilizing secondary data collected from consulting official documents.

Our findings form the basis of a theoretical innovation policy framework to foster deep techs in addressing global challenges, which encompasses the main building blocks of strategic goals, innovation policy dimensions, and moderating variables. Based on the findings, propositions for public policies were indicated.

This investigation contributes to a more robust theoretical discussion on deep techs and innovation policy, expanding the research field and opening new avenues of study by understanding the phenomenon in its constituent elements.

Building on the work of Romasanta et al. (2022), Janssen et al. (2021), and Edler et al. (2016), the findings demonstrate that deep tech development necessitates a systemic articulation of actors, instruments, and goals aligned with public purpose. The research reinforces the central role of the State as a risk-taking coordinator (METCALFE, 2003; DOSI, 1988) and supports Chang’s (2002) argument that supporting emerging sectors is essential to reducing structural inequalities. From a practical standpoint, the research provides policymakers with actionable insights by identifying key elements for designing effective public innovation policies. Moreover, it frames deep tech innovation as a strategic lever for responding to environmental and social crises. It thus encourages the reconfiguration of educational, financial, and institutional frameworks to meet these challenges.

The article's structure includes seven sections, including the introduction. The second and third sections discuss the relationships between innovation policies, global challenges, and deep techs. The fourth section describes the method. Sections five and six present and analyze the results and discussion. Finally, the seventh section contains the concluding remarks and bibliographical references.

2. Innovation policy and societal challenges

The government is increasingly viewed as a crucial actor in shaping innovation and policies that support research, innovation, and experimentation essential for economic and social development (MAZZUCATO, 2015; FAGERBERG, 2013). Public action recommendations for innovation are mainly derived from neoclassical and evolutionary theory approaches.

The neoclassical approach has an indirect influence on innovation public policy, acknowledging the presence of the State in the economy only in situations where the market fails in its role of coordinating economic activity (COSTA, 2016). Nevertheless, for Mazzucato (2015), the neoclassical idea that the State should only intervene in cases where the market fails is based on a distorted and ideological view of its role in the economy. When one scrutinises the history of the main innovations that revolutionised life in society in more detail, one verifies the active, visionary, and courageous presence of the State at the root of these undertakings.

From an evolutionary perspective, public policy in innovation should focus on generating knowledge and its application in developing new technologies, products, processes, and organisational forms. Given that innovation results from an interactive process with systemic characteristics covering different institutions, the public entity is in a better condition to coordinate the actions of these actors involved in the innovation process than the firm or the individual agent, who is primarily concerned with their particular objective function (METCALFE, 2003; COSTA, 2016).

Nelson’s (1959) seminal work integrates the State as a central actor in technological evolution. This author argues that government-funded basic science research generates positive externalities that sustain technological innovation, even when there is no immediate return to the private sector. The work of Dosi (1988) focused on discussing the need for public policies to mitigate technological uncertainty. According to this author, the State plays a fundamental role in mitigating uncertainties associated with emerging technologies. It should act as a high-risk investor, actively shaping technological trajectories in strategic sectors. The idea that the state should protect nascent industries through subsidies, trade barriers, and investment coordination is defended by Chang (2002). He criticizes the idea that the market is self-sufficient, arguing that innovation requires strategic intervention to overcome structural inequalities.

In this context, the role of innovation public policy is to stimulate efforts toward new technological frontiers. Innovation policy is a public intervention designed to support the generation and diffusion of innovation, whether in the form of a new product, service, process, or business model. It overlaps and is linked to science, research, and technology policies (EDLER et al., 2016; EDLER; FAGERBERG, 2017). Innovation policy instruments are the operational forms of intervention by governments and public bodies. The design and implementation of systemic innovation policy depend on how innovation policy instruments are defined, customised, and combined to address “problems” related to system activities (BORRÁS; EDQUIST, 2013).

A shift in the direction of public innovation policy is observed, where innovation is not an objective in itself, but rather a means to a social end (EDLER et al., 2016; BOON; EDLER, 2018; ROBINSON; MAZZUCATO, 2019). Governments worldwide are increasingly concerned with tackling grand societal challenges (JANSSEN et al., 2021) and the significant problems societies face. A classic policy with innovation at its core is the Apollo Program, which mobilised substantial public investment and coordination to achieve a clearly defined technological objective: landing humans on the Moon. In contrast, the United Nations' Sustainable Development Goals (SDGs) represent a comprehensive challenge-driven policy framework with explicitly socio-environmental aims. They aim to align global innovation, investment, and governance systems with inclusive development and ecological sustainability. A framework that sees policy as market shaping and co-creating is necessary beyond the traditional ‘market failure’ framework (MAZZUCATO, 2016).

The societal challenges are the focus of one kind of “transformative innovation policy”: the mission-oriented innovation policy (HADDAD et al., 2022). Missions define objectives and provide concrete ways to address a social challenge, mobilising a diverse set of sectors to this end (MAZZUCATO; PENNA, 2016; JANSSEN et al., 2021). “Mission-oriented” policies are defined as systemic public policies that are at the frontier of knowledge, aiming to achieve specific goals or “big science to tackle big problems” (ERGAS, 1987). Suppose previously, missions had objectives such as taking a man to the moon, but in recent years. In that case, the traditional bases for innovation policies have expanded to contribute more explicitly to facing societal challenges. The complexity of these challenges could be tackled by focusing on a limited set of fundamental end-use categories that present an opportunity for a substantial restructuring of innovation policy, fostering experiments crucial for sociotechnical transitions (STEWARD, 2012).

The urgency of major technological transformations poses a significant challenge for public agents, and these fundamental transformations typically take many decades to develop and fully implement. Therefore, searching for ways to accelerate change and implementing policies that support research and innovation will be essential (FAGERBERG, 2017). Missions must create a long-term public agenda for innovation policies, address a social demand or need, and capitalise on the high potential of the country's science and technology system to develop innovations (MAZZUCATO, 2018).

In recent years, a significant shift has been observed in the orientation of innovation policies: innovation is no longer seen as an end in itself, but rather as a means to achieve broader societal goals (EDLER et al., 2016; BOON; EDLER, 2018; ROBINSON; MAZZUCATO, 2019). Governments have increasingly responded to grand societal challenges through more targeted policy approaches, notably mission-oriented strategies (JANSSEN et al., 2021). Countries such as Germany (2022), the United Kingdom (2017), Brazil (BRASIL, 2024b), and Denmark (SCORDATO; BUGGE; FEVOLDEN, 2020) have promoted innovations aligned with themes such as environmental sustainability, social inclusion and digital transformation. These initiatives signal a shift away from traditional innovation policy models and call for a new framework that recognizes the active role of the state in shaping and co-creating markets (MAZZUCATO, 2016), in line with the United Nations Sustainable Development Goals.

According to Mazzucato (2018), mission-oriented innovation policies diverge from traditional approaches by prioritising transformative societal challenges over sector-specific or incremental advancements. Emphasizing market creation rather than mere market correction, these policies drive systemic innovation through ambitious, cross-sectoral objectives. Unlike traditional policies focused solely on economic growth, mission-driven approaches align technological progress with sustainability and equity. Their portfolio-based strategy integrates incremental and breakthrough innovations, fostering adaptability and learning. By engaging multiple stakeholders and utilizing dynamic performance metrics, these policies enhance resource allocation, promote cross-sectoral spillovers, and facilitate public-private collaboration, ultimately increasing their effectiveness and long-term societal impact. In comparison to other single-innovation policies, missions have been accelerating change by creating a long-term public agenda for innovation policies and mobilising a diverse set of sectors to implement them in very concrete ways.

3. Deep technology

Deep Technologies are seen as the fourth wave of innovation and are essential to tackle the significant challenges of our time. The first wave comprised the successive industrial revolutions, while the second was characterized by the dependence on corporate research laboratories for scientific investigations. The third wave saw a decline in corporate research endeavors and the emergence of small, disruptive firms, shaping the renowned “Silicon Valley” paradigm. The fourth wave is gaining impetus, akin to the early Internet era (DE LA TOUR et al., 2021). Deep technology, also known as deep tech, typically refers to innovative solutions that leverage science and technology. Its meaning has evolved and taken on new contours with the development of the innovation ecosystem.

Despite being occasionally cited in the literature (LUTZ; STORMS, 1998), deep tech remains an underexplored concept (ROMASANTA et al., 2022). The term “deep tech” has become more widely used since the definition given in 2014 by Swati Chaturvedi, CEO and co-founder of the investment platform Propel (X), for the companies that employ this type of technology:

Deep Tech ventures are companies founded on a scientific discovery or a genuine technological innovation.

Deep tech has become a buzzword among venture capital circles and policymakers (ROMASANTA et al., 2022). A rigorous definition is needed to facilitate a profound understanding of its meaning, guiding innovation and economic policy. The MIT researchers Apodaca, Murray and Frolund (2022) describe the term as follows:

Deep tech is that part of the solution space based on breakthrough science and engineering.

From the analysis of a range of articles from industry, Romasanta et al. (2022) defined deep tech as:

Early-stage technologies are based on scientific or engineering advances, requiring lengthy development times, systematic integration, and sophisticated knowledge to create downstream offerings with the potential to address significant societal challenges.

Here we consider deep techs as radical or disruptive early-stage solutions based on scientific or engineering advances. A problem-oriented approach characterizes the deep tech approach, which involves the convergence of approaches and technologies, as well as a cyclic design, build, test, and learn process. They employ multiple technologies, with significant utilization of advanced technologies. Deep techs exhibit a range of characteristics related to time, capital intensity, and uncertainty, necessitating new or adapted approaches to their founding, growth, and support (APODACA; MURRAY; FROLUND, 2022; ROMASANTA et al., 2022).

Deep tech has great potential to address grand societal challenges and constitutes a critical vehicle for solving public value failures (MAZZUCATO, 2015). A survey launched by de la Tour et al. (2021) of 1277 deep tech companies showed that 97% considered contributing to at least one SDG related to health, climate, and sustainability challenges. Recent studies also reveal substantial opportunities for synergies between deep and digital technologies to enhance progress in sustainability further (TEKIC; ABUELEZ; TEKIC, 2024). The deep tech uncertainties constitute a source of potential market failure, leading to limited private actions that justify corrective state intervention (APODACA; MURRAY; FROLUND, 2022). The government's role in promoting and supporting deep tech development through innovation policies is crucial. With these points in mind, there is a need to deepen the field to understand the possibilities of influencing innovation policies for the more effective development of profound tech innovation aimed at societal challenges (BORRÁS; EDQUIST, 2013). Building on this growing research stream, this paper investigates how innovation policies promote deep tech in response to socio-environmental challenges.

4. Method

This qualitative investigation employs an exploratory-descriptive approach, aligning with the research objective. Qualitative data help generate the constituent elements when the phenomenon being studied is new or has not been investigated before, and it has the advantage of being an open theory construction (GRAEBNER; MARTIN; ROUNDY, 2012). This approach is related to the early stages of deep technology research (ROMASANTA et al., 2022), which signifies the value of exploring the emergence of this phenomenon more openly. We have conducted an analysis of documents related to Denmark, which we intend to investigate for the transferability of the results (GIOIA, 2021).

4.1 Denmark

Denmark is considered a representative country, both in terms of deep technological innovation and environmental performance (STARTUP GENOME, 2019; GLOBAL INNOVATION INDEX, 2022; WOLF et al., 2022). Recognizing that new technological solutions play a crucial role in achieving the green transition target, Denmark’s strategy, as outlined in the documents, establishes policies for research, innovation, development, and demonstration of innovative technologies. It aligns with the deep tech concept, which involves solutions containing scientifically based technologies with the potential to address grand societal challenges (ROMASANTA et al., 2022).

Denmark ranks number 10 among the world’s most innovative countries in the Global Innovation Index 2022, in addition to being at the top of the 2022 Environmental Performance Index (WOLF et al., 2022), with notable leadership in efforts to promote a clean energy future and sustainable agriculture. Additionally, Startup Genome (2019) identified Western Denmark as a high-growth ecosystem, boasting sector strengths in manufacturing robotics and life sciences. According to The Innovation Policy Platform, Denmark is a highly developed economy with solid business innovation and one of the world's most developed renewable energy technology sectors (ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT, 2022).

Denmark is one of the Nordic countries, which have an established tradition of ecological concern, with a reputation for placing progressive environmental policies at the heart of national politics (KHAN; JOHANSSON; HILDINGSSON, 2021). The state is assumed to play an essential role in various policy interventions, promoting technological change and innovation in green technologies in close relationships with relevant industries. There is evidence of a shift toward policies for transformative change, with a need to address societal and environmental problems through Science, Technology, and Innovation (STI) policies (SCORDATO; BUGGE; FEVOLDEN, 2020).

4.2 Data collection

This investigation was based on documentary analysis using secondary data from official public innovation policy-related documents. Policy strategies and instruments were examined as key components of the policy mix to achieve the paper's research objectives. We identified and selected official policy documents by searching on the Danish Ministry of Higher Education and Science website. The two most recent documents guiding innovation policy in Denmark were analyzed. They are:

• Document 1: Innovation Strategy 2012: Denmark – a Nation of Solutions. Enhanced cooperation and improved frameworks for innovation in enterprises (DENMARK, 2012).

• Document 2: Green Solutions of the Future – Strategy for Investments in Green Research, Technology, and Innovation (DENMARK, 2020).

Both national documents represent the most up-to-date strategic guidelines regarding the country’s innovation and technology agenda, particularly in promoting the green transition and strengthening science-based technological solutions.

Recognizing the crucial role of new technological solutions in achieving the green transition target, Denmark’s strategy, as outlined in the documents, establishes policies for research, innovation, development, and demonstration of innovative technologies. It aligns with the deep tech concept, which involves solutions containing scientifically based technologies with the potential to address grand societal challenges (ROMASANTA et al., 2022).

4.3 Data analysis

To analyze the data, we employed content analysis. The use of content analysis is justified because it allows articles to be adjusted to the timeline more freely and rigorously develops the characterization of the contents of the groups. The content analysis was applied by identifying in the documents quotes that refer to specific policy strategies and instruments.

For the data analysis, we employed the content analysis technique, drawing upon two well established methodological frameworks in qualitative research: the coding system proposed by Strauss and Corbin (1998) and the structured inductive theorisation approach developed by Gioia (2021). Both methods share the logic of grounded theory, relying on progressive coding to build analytical categories. Initially, open coding was applied, in which units of meaning were identified and organized into first-order categories. These were subsequently grouped through axial coding, enabling the emergence of second-order themes by establishing conceptual relationships (Figure 1.

Figure 1
Code Tree.

The similarities between the two methods—particularly the sequence of open and axial coding—enabled a systematic and coherent analysis of the policy documents. However, it was through Gioia’s (2021) approach that we advanced toward the construction of a conceptual data structure by identifying aggregate dimensions. This structure provided a visual representation of the articulation between emerging concepts and higher-order theoretical abstractions, as illustrated in Figure 1. The focus was on identifying “[…] nascent concepts not covered in the literature” (GIOIA, 2021, p. 25), ensuring that the analysis remained aligned with the exploratory and inductive nature of the study.”

4.4 Additional procedures

To reinforce the rigour of the research method described previously, we operationalised internal validation through cross-checking as a strategy to mitigate potential limitations regarding the validity of the analyses. Different researchers reviewed the research protocols to enhance the credibility of the research. We also conducted external validation by comparing the results of the three dimensions with existing literature on the topic.

5. Results: innovation policy to foster deep techs that face global challenges

Our findings form the basis of a proposed theoretical innovation policy framework to address global challenges faced by deep techs, as shown in Figure 2. This framework encompasses three main building blocks: strategic goal, innovation policy dimensions, and moderating variables.

Figure 2
Theoretical framework.

In summary, global challenges served as inputs to innovation policy's strategic goals. These strategic objectives required efforts in education, funding, and collaboration to promote deep techs. However, this interaction focused on establishing priority sectors for investment, generation, and utilization of knowledge and management practices. Ultimately, Danish policy successfully generated results related to deep tech innovation that address global challenges. Below, we explore all the blocks in detail, and based on the findings, propositions for public policies are proposed.

5.1 Challenges as strategic goals

The Danish innovation policies proposed challenges as strategic goals, mainly tackling societal and global challenges. The challenge-driven approach evolved from “demand-oriented” to “mission-driven,” with the primary objective of driving the green transition. This challenge-driven approach is represented in the extract below:

Innovation should be driven by societal challenges: the demand for solutions to specific societal challenges must be given higher priority in public innovation policy (Document 1).

Research and innovation were considered crucial in achieving Denmark's ambitious climate targets and safeguarding its nature and environment. The document's objective was to ensure that substantial public investments in research, innovation, and education would drive growth and job creation, while tackling societal challenges, particularly those most essential to meeting Denmark’s and the world’s climate ambitions. In this way, we indicate proposition 1:

P1: Public innovation policies should be guided by challenges translated into strategic objectives in order to promote deep techs that solve global challenges.

This proposition aligns with the vision of the government's role in market shaping, with challenge-led policies providing direction for growth that is more inclusive and sustainable (MAZZUCATO, 2016). Increasingly, innovation policies have been expected to address societal demands or even respond to the “Grand Challenges of our time” (DAIMER; HUFNAGL; WARNKE, 2012). The evolution of the challenge-driven approach from “demand-oriented” to “mission-driven” in Danish innovation policies corroborates the literature on the importance of creating a long-term public agenda for innovation policies to address a challenge (MAZZUCATO; PENNA, 2016; MAZZUCATO, 2018; JANSSEN et al., 2021). Since deep techs are early-stage technologies based on science with the potential to address grand societal challenges (ROMASANTA et al., 2022), their successful development leverages innovation policies guided by well defined challenges translated into strategic objectives.

However, governments can struggle to prioritise challenges to be addressed and to define strategic objectives effectively. As Yang (2022) noted, government management systems and mechanisms must be optimised to meet social development needs.

5.2 Innovation policy dimensions

Three policy dimensions seem to be essential for developing deep techs and working in close interaction: education, funding, and collaboration.

1. Education

Many deep tech companies are spin-offs of research infrastructures and academic groups, with founders from a scientific background, who later transition into business. The proposed policy focuses on innovation competencies in the educational sector to enhance innovation capacity. It also evolved to green education to strengthen the coherence between the study programs and the green transition, as shown in the extracts below:

Strengthen knowledge, cooperation, and innovation in education through recognition and attractive career paths for researchers and educators (Document 1).

The government will focus on supporting and strengthening the coherence between our study programs and the green transition (Document 2).

Several instruments have been proposed to support the promotion of innovation competencies in the educational sector, including increasing practice elements at all academic levels to foster innovation, promoting innovation entrepreneurship in teacher education, organizing innovation programs and competitions for students, and engaging with companies, among others. In this way, we indicate proposition 2:

P2: Public policies should promote innovation competencies in the educational sector in order to foster deep techs that solve global challenges.

This proposition aims to bridge the gap between scientific and business backgrounds, a crossover that remains challenging (ROMASANTA et al., 2022). Innovation education can be an effective way for scientists to develop the skills necessary to handle the diverse demands of running a company. Aligned with the proposition presented, the literature has demonstrated that practical science, technology, and innovation policies have education at their heart (OWUSU; ANTWI; ABUKARI, 2022), with a primary agenda to redefine the philosophy of education. For example, Cheng et al. (2020) have demonstrated that university–industry collaboration policies positively impact universities’ knowledge innovation and achievement transformations. Acquiring various skills through innovation education is a trend among higher education students, as innovation and entrepreneurship are top priorities for countries that provide funding and policies to promote these capacities (QIU; GARCÍA-ARACIL; ISUSI-FAGOAGA, 2023). As a key result of policies promoting innovation competencies in education, the government’s investment in new academic curricula provides a pipeline of deep tech talents that powers the entire ecosystem (PORTINCASO et al., 2021).

However, there are challenges in promoting innovation competencies in the educational sector. The culture at universities can create barriers to developing research that benefits companies and promotes personal gain.

1. Funding

Funding policy approaches were presented to ensure that more innovative products and solutions reached the market and evolved to build green research and innovation efforts, as shown below:

Funding for the partnerships will be outlined in the national budgets of the coming years (Document 1).

Adjust the legal basis for Innovation Fund Denmark so that the Fund has a clear green mandate as the key player to realise the political priorities in implementing funds for research and innovation, contributing to the green transition (Document 2).

Part of the proposed policies aimed to leverage private capital by applying public funds. Some examples of instruments offered are thematic calls for green research funding in public funds and programs, funds prioritised under missions, and funds to boost other market investments. Then proposition 3 is:

P3: Public innovation policies should address funding strategies to promote deep tech solutions that address global challenges.

To succeed in promoting deep techs through funding, public policies must consider the need for substantial initial capital and extended development cycles. It is necessary to create funds that integrate effectively into the investment chain, focusing on market gaps and considering the criteria for further rounds. It is also important to explore innovative investment models and architectures.

1. Collaboration

Aligned with Nelson (1959), this proposition considers that the State plays a crucial role in funding to reduce uncertainty in technological trajectories and generate positive externalities that drive innovation beyond immediate private sector returns. One main differentiator of deep techs is the amount of initial capital needed for their long development cycles. In the first funding rounds, deep tech startups require significantly more initial capital investment to develop their technologies further (ROMASANTA et al., 2022). In addition, the uncertainty in deep tech is shaped by factors such as insufficient knowledge, non-linearity, regulatory and technical risk, uncertain market demand and scale-up, unsure future returns, and high capital intensity. These elements constitute a source of potential market failure, leading to limited private actions that justify the corrective intervention of the State or other specialized investors or venture capitalists driven by criteria in addition to market returns (APODACA; MURRAY; FROLUND, 2022). Governments are a vital part of the backbone of deep tech investment, playing a pivotal role in providing the necessary funding for fundamental research that is too risky or far out for commercial relevance, and creating incentives to stimulate a continuous rate of investment (PORTINCASO et al., 202L). Innovation is a finance-consuming and risky activity (HALL; LERNER, 2010), so public and private funds must coexist consistently to develop innovation (ETZKOWITZ; ZHOU, 2017).

Many instruments were proposed to enhance collaboration in research, innovation, development, and commercialisation. This approach is represented in the extracts below:

The concrete missions are to be accomplished by green partnerships in which all relevant knowledge institutions, businesses, public authorities, and private players join forces in a joint research and innovation effort (Document 2).

Several pilot partnerships will be established to ensure experience with different cooperation models (Document 1).

New cluster organisations were supported in contributing to innovation through an interplay between research and knowledge environments, companies, and other relevant stakeholders. This investigation also highlights the importance of international collaboration in fostering deep techs. On this subject, we indicate proposition 4:

P4: Public innovation policies should promote local, regional, national, and international collaboration to foster deep tech solutions that address global challenges.

The success of deep tech relies on a deeply interconnected ecosystem of various actors, as collaboration and support from these entities are vital for their growth and prosperity (DE LA TOUR et al., 2021). Orchestration between different actors is essential, given that deep tech often involves numerous interdependent components within a heterogeneous ecosystem. This proposition supports the existing literature on the role of partnerships, networks, alliances, and international collaborative projects in fostering innovation. According to Czarnitzki, Ebersberger and Fier (2007), collaboration, in the form of partnerships and networks, is a relevant dimension that innovation policies should foster. A public policy to support R&D activities in research networks, partnerships, and joint alliances is considered by these authors a critical factor of success, as promoting these activities is vital for generating innovation spillovers. In addition, studies have noted that governments also focus on establishing internationalisation policies that foster collaborative projects in scientific research, technology, and innovation, as well as scholarships to promote the qualification of human talent, and funding schemes (WITJES; SIGL, 2014; ECHEVERRÍA-KING et al., 2023).

To effectively foster deep tech through collaboration, innovation policies must align the interaction objectives with the primary challenges of the existing solutions and with the country's long-term innovation agenda.

5.3 Moderating variables

Finally, we identify three influential variables in developing innovation policies: sectoral strategies, knowledge, and management.

1. Sectoral strategic

This variable implies that public policies should emphasize regional strategic sectors, mainly prioritising investments, collaboration, and education. On this subject, the document states:

Focus on concrete challenges within sectors where the need for new solutions and the potential for meeting the green objectives are the largest in Denmark and globally (Document 2).

Prioritise R&D, which supports Danish manufacturing. Therefore, the Danish government allocated DKK 40 million (€5.3 million) in 2013 for strategic research in future production systems (Document 1).

1. Knowledge

The innovation policies point out the knowledge variable. It refers to using previous studies and research to support the development of more effective policies. On this subject, the document states:

The European Research Area Committee evaluated the Danish innovation system (Document 1).

The Ministry of Environment and Food has launched a roadmap of research work to support core tasks in the fields of environment and food, particularly within climate transition at the national and international levels, for the period 2020-2030 (Document 2).

1. Management

The last variable presented in the innovation policies was management. Some management approaches and the efficiency of innovation processes have been developed. Promoted actions included payment-for-performance contracts, monitoring and impact assessments, and intelligent public procurement.

Closer coordination must be ensured, just as the undesirable overlap between individual schemes in the research and innovation system should be avoided (Document 1).

Monitoring and Impact Assessments of Green Research. A solid data and analysis basis is needed to monitor and assess the impact of green research and enhance the decision-making basis for political choices (Document 2).

All these variables were essential for the application of the innovation policies. In this way, we formulate proposition 5:

P5: Public innovation policies should consider factors related to strategic sectors, knowledge, and management to promote deep tech solutions that address global challenges.

Aligned with these findings, the proposition suggests that successful policy strategies and instruments that foster deep techs should focus on sectoral strategies, knowledge creation, and management. This proposition is aligned with the literature, which states that implementing specific public policy actions to promote innovation in sectors central to national economic growth is indispensable (ŠIPIKAL, 2013; SOUSA; ROCHA; SOUSA, 2019; SÁNCHEZ; SEGOVIA; LÓPEZ, 2020). On the other hand, although this investigation reveals that the proposed innovation policies were knowledge-based, studies report that research knowledge is not commonly utilized in policymaking (HAUNSCHILD; WILLIAMS; BORNMANN, 2023). Additionally, this study's proposition of management-based policies aligns with Yang's (2022) perception that specific government management systems and mechanisms need to be optimised to meet social development needs, which can be achieved through continuous innovation. As an example of evolution in policy management, in recent years, the focus on monitoring and evaluating public policies has intensified, particularly in the context of mission-oriented innovation policies. These discussions emphasize the need for new frameworks, tools, and methodologies to assess the systemic impacts of policies designed to address grand societal challenges (GOULDEN; KATTEL, 2024; PFEIFER; HELMING, 2024).

6. Discussion

This session addresses the theoretical, practical, social and economic implications and contributions of this investigation.

6.1 Theoretical contributions

The findings of this investigation make significant theoretical contributions to the field of innovation, addressing global challenges, particularly within the context of deep technologies (deep techs). Following Romasanta et al. (2022), we identify the basis of specific public policies to foster the emergence, consolidation, and impact of deep techs, emphasizing the role of innovation policy formulation as a catalytic mechanism for social transformation.

Contrasting with approaches that view innovation as an end in itself, our findings contribute to policy literature that is anchored in strategic objectives focused on overcoming social, economic, and environmental challenges. Corroborating Janssen et al. (2021) and Haddad et al. (2022), we address the empirical gap in the literature regarding the interface between deep technologies and global challenges. By demonstrating that social and environmental difficulties are incorporated as guiding principles within the policies analyzed, we broaden the understanding that promoting deep technologies requires a systemic articulation of instruments, actors, and missions. In this sense, we expand upon the proposition of Edler et al. (2016) by showing that policy effectiveness depends on technical design and the capacity to align innovation with public purpose.

Confirming Metcalfe (2003), our results reinforce that the State is central in coordinating the actors involved in the innovative ecosystem, especially when guiding technological trajectories in high complexity and uncertainty. Building on Dosi's (1988) understanding, we observe that, in addition to mitigating technological uncertainty, the State must act as a risk investor and orchestrator of mission-oriented efforts aimed at sociotechnical transformation. In this regard, we reinforce Chang’s (2002) argument that protecting and promoting emerging sectors, such as deep technologies, is crucial for mitigating structural inequalities and ensuring a sustainable transition.

6.2 Practical implications

This study offers relevant practical contributions for policymakers aiming to structure innovation policies that foster deep techs oriented toward addressing global challenges. Drawing from the Danish experience, five interdependent policy design principles are identified:

1. Challenge-oriented strategic frameworks

Innovation policies should be guided by societal and environmental challenges, operationalised as strategic policy objectives. The evolution from demand-driven to mission-oriented approaches—such as Denmark’s prioritisation of the green transition—demonstrates the effectiveness of aligning innovation efforts with long-term public missions (MAZZUCATO; PENNA, 2016; JANSSEN et al., 2021).

1. Promotion of innovation competencies in education

Deep tech development requires interdisciplinary skills that bridge scientific knowledge and entrepreneurial capabilities. Public policies should promote educational reforms that integrate innovation, sustainability, and business competencies across all levels of education (OWUSU; ANTWI; ABUKARI, 2022; QIU; GARCÍA-ARACIL; ISUSI-FAGOAGA, 2023), thereby enhancing the absorptive capacity and entrepreneurial potential of researchers.

1. Targeted and coordinated funding instruments

Given the capital-intensive and high-risk nature of deep tech ventures, public funding mechanisms must be designed to mitigate risk in early-stage development, attract private investment, and ensure continuity across funding stages. This includes mission-oriented funds, thematic calls, and blended financing instruments (APODACA; MURRAY; FROLUND, 2022; PORTINCASO et al., 2021).

1. Multi-level and international collaborative platforms

Innovation policies should actively foster collaboration among universities, research institutes, firms, and public agencies, both domestically and internationally. Deep tech ecosystems rely on knowledge-intensive partnerships and cross-sector synergies to accelerate development and diffusion (CZARNITZKI; EBERSBERGER; FIER, 2007; DE LA TOUR et al., 2021).

1. Sectoral prioritisation, knowledge-based policymaking, and policy management

Effective innovation policy requires clear sectoral priorities, systematic use of data and evidence, and modern governance mechanisms. These include continuous monitoring and evaluation, coordination between programs, and adaptive management tools that ensure coherence and responsiveness (SOUSA; ROCHA; SOUSA, 2019; HAUNSCHILD; WILLIAMS; BORNMANN, 2023; GOULDEN; KATTEL, 2024).

Together, these findings provide actionable insights for governments seeking to design and implement innovation policies that stimulate the emergence of deep tech solutions aligned with sustainable development and national competitiveness.

6.3 Social and economic implications

Socially, this study reinforces the role of innovation policy in addressing persistent societal challenges. By demonstrating how Denmark integrates a challenge-oriented approach into its innovation strategy, the findings offer a positive counterpoint to global critiques of ineffective policymaking. The results also guide ecosystem actors—such as NGOs, investors, and support organisations—on how to engage in and support the development of deep techs aligned with the public interest.

Economically, the research highlights the potential of deep tech innovation to drive development. By fostering ventures rooted in science and technology, such policies can stimulate job creation, increase tax revenues, and strengthen national industrial capabilities, while also generating positive environmental and social outcomes.

7. Final remarks, future research and limitations

The literature emphasizes the importance of supporting the generation and diffusion of deep technologies to address significant social challenges. However, it lacks an explanation of how to promote these solutions to face the challenges. In this study, we aim to bridge this gap by proposing innovative policy approaches to effectively support the development of deep technologies that address the global challenges of our time. To this end, our results showed that challenges must be translated into strategic objectives that guide effective innovation policies for education, funding, and collaboration. However, we also discovered a need to apply knowledge, management practices, and focus on strategic sectors in innovation policies to foster deep techs that face socio-environmental challenges.

Although our results are contributory, our research has limitations. Firstly, we explored a limited number of documents. By analyzing only one country, the records on innovation policy are few and far between. We encourage researchers to expand and deepen our analyses. Secondly, the authors were unable to develop alternative validation methods due to limited resources, including time and funding. We recommend applying interviews, questionnaires, and Delphi to generate more reliability in the proposed framework. Thirdly, we concentrated our analyses on proposed policies. Our research has not been able to analyze what happens in the implementation of these policies. We hope that further research will be able to verify the “real life” of these legislative applications. Finally, another limitation is that the document analysis was restricted to materials available in English. Given that policy details are often recorded in the local language, fluency in Danish could have revealed additional insights. Therefore, we recommend that future studies include collaboration with one or more local experts to enhance data collection and contextual interpretation.

Acknowledgments

Acknowledgment to Fundação Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, CNPq/Brazil), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP/ Brazil) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG/Brazil).

Data Availability Statement

The data supporting the findings of this study are publicly available in Denmark (2012, 2020).

• Source of funding:
  The authors declare that there is no funding.

References

• APODACA, O.; MURRAY, F.; FROLUND, L. What is “Deep Tech,” and what are Deep Tech Ventures? Cambridge: MIT Management Global Programs, 2022.
• BOON, W.; EDLER, J. Demand, challenges, and innovation: making sense of new trends in Innovation Policy. Science & Public Policy, Oxford, v. 45, n. 4, p. 435-447, 2018.
• BORRÁS, S.; EDQUIST, C. The choice of innovation policy instruments. Technological Forecasting and Social Change, Amsterdam, v. 80, p. 1513-1522, 2013.
• BRASIL. Ministério do Desenvolvimento, Indústria, Comércio e Serviços. Nova Indústria Brasil: Plano de Ação para a Neoindustrialização 2024-2026. Brasília, 2024b. Available from: https://www.gov.br/mdic/pt-br/composicao/se/cndi/plano-de-acao/nova-industria-brasil-plano-de-acao-2024-2026-1.pdf Access in: 22 Mar 202.
  » https://www.gov.br/mdic/pt-br/composicao/se/cndi/plano-de-acao/nova-industria-brasil-plano-de-acao-2024-2026-1.pdf
• CHANG, H. Kicking away the ladder: development strategy in historical perspective. London: Anthem Press, 2002.
• CHENG, H. et al The effect of university–industry collaboration policy on universities’ knowledge innovation and achievements transformation: based on innovation chain. The Journal of Technology Transfer, Indianapolis, v. 45, p. 522-543, 2020.
• COSTA, A. B. Teoria econômica e política de inovação. Revista de Economia Contemporânea, Rio de Janeiro, v. 20, n. 2, p. 281-307, 2016.
• CZARNITZKI, D.; EBERSBERGER, B.; FIER, A. The relationship between R&D collaboration, subsidies and R&D performance: empirical evidence from Finland and Germany. Journal of Applied Econometrics, Hoboken, v. 22, p. 1347-1366, 2007.
• DAIMER, S.; HUFNAGL, M.; WARNKE, P. Challenge-oriented policy-making and innovation systems theory: reconsidering systemic instruments. In: KOSCHATZKY, K. (Org.). Innovation system revisited: experiences from 40 years of fraunhofer ISI research. Stuttgart: Fraunhofer Verlag, 2012. v. 11, p. 217-234.
• DENMARK. Ministry of Higher Education and Science. Denmark: a nation of solutions. Enhanced cooperation and improved frameworks for innovation in enterprises. København, 2012. Available from: https://ufm.dk/en/publications/2012/denmark-a-nation-of-solutions Access in: 6 May 2023.
  » https://ufm.dk/en/publications/2012/denmark-a-nation-of-solutions
• DENMARK. Ministry of Higher Education and Science. Green solutions of the future: strategy for investments in green research, technology, and innovation. København, 2020. Available from: https://ufm.dk/en/publications/2020/green-solutions-of-the-future-strategy-for-investments-in-green-research-technology-and-innovation-1 Access in: 6 May 2023.
  » https://ufm.dk/en/publications/2020/green-solutions-of-the-future-strategy-for-investments-in-green-research-technology-and-innovation-1
• DE LA TOUR, A. et al Deep tech: the great wave of innovation. BCG/Hello Tomorrow, 2021. Available from: https://hello-tomorrow.org/wp-content/uploads/2021/01/BCG_Hello_Tomorrow_Great-Wave.pdf Access in: 26 Apr 2023.
  » https://hello-tomorrow.org/wp-content/uploads/2021/01/BCG_Hello_Tomorrow_Great-Wave.pdf
• DOSI, G. The nature of the innovation process. In: DOSI, G. et al (Org.). Technical change and economic theory London: Pinter, 1988. p. 221-238.
• ECHEVERRÍA-KING, L. et al Scientific collaborations between Latin America and Europe: an approach from science diplomacy towards international engagement. Science & Public Policy, Oxford, v. 50, n. 4, p. 794-806, 2023.
• EDLER, J.; FAGERBERG, J. Innovation policy: what, why & how. Oxford Review of Economic Policy, Oxford, v. 33, n. 1, p. 2-23, 2017.
• EDLER, J. et al Introduction: making sense of innovation policy. In: EDLER, J. et al. (Org.). Handbook of innovation policy impact Cheltenham: Edward Elgar Publishing, 2016. v. 1, p. 1-17.
• ERGAS, H. Does technology policy matter. In: GUELLEC, D. (Org.). Technology and global industry: companies and nations in the world economy. Washington: National Academy Press, 1987. p. 191-245.
• ETZKOWITZ, H.; ZHOU, C. The triple helix: university-industry-government innovation and entrepreneurship. London: Routledge, 2017.
• FAGERBERG, J. Schumpeter and the revival of evolutionary economics: an appraisal of the literature. Journal of Evolutionary Economics, Heidelberg, v. 13, n. 2, p. 125-159, 2013.
• FAGERBERG, J. Innovation policy: rationales, lessons and challenges. Journal of Economic Surveys, Hoboken, v. 31, n. 2, p. 497-512, 2017.
• GRAEBNER, M. E.; MARTIN, J. A.; ROUNDY, P. T. Qualitative data: cooking without a recipe. Strategic Organization, London, v. 10, n. 3, p. 276-284, 2012.
• GERMANY. Federal Ministry of Education and Research – BMBF. Progress report on the high-tech strategy 2025. Berlin, 2022. Available from: https://www.bmbf.de/SharedDocs/Publikationen/DE/FS/31557_Fortschrittsbericht_zur_Hightech_Strategie_2025_en.pdf?__blob=publicationFile&v=10 Access in: 22 Mar 2025.
  » https://www.bmbf.de/SharedDocs/Publikationen/DE/FS/31557_Fortschrittsbericht_zur_Hightech_Strategie_2025_en.pdf?__blob=publicationFile&v=10
• GIOIA, D. A systematic methodology for doing qualitative research. The Journal of Applied Behavioral Science, Thousand Oaks, v. 57, n. 1, p. 20-29, 2021.
• GLOBAL INNOVATION INDEX. What is the future of innovation-driven growth? 2022. Available from: https://www.wipo.int/edocs/pubdocs/en/wipo-pub-2000-2022-section1-en-gii-2022-at-a-glance-global-innovation-index-2022-15th-edition.pdf Access in: 26 Apr 2023.
  » https://www.wipo.int/edocs/pubdocs/en/wipo-pub-2000-2022-section1-en-gii-2022-at-a-glance-global-innovation-index-2022-15th-edition.pdf
• GOULDEN, A.; KATTEL, R. Designing and implementing mission-oriented policies: tools and resources from the field. London: UCL Institute for Innovation and Public Purpose, 2024.
• HADDAD, C. et al Transformative innovation policy: a systematic review. Environmental Innovation and Societal Transitions, Amsterdam, v. 43, p. 14-40, 2022.
• HALL, B. H.; LERNER, J. The financing of R&D and innovation. In: HALL, B. H.; ROSENBERG, N. (Org.). Handbook of the economics of innovation Amsterdam: Elsevier, 2010. p. 609-639.
• HAUNSCHILD, R.; WILLIAMS, K.; BORNMANN, L. How relevant is public policy and administration research for the policy sector? An empirical analysis based on Overton data. In: INTERNATIONAL CONFERENCE ON SCIENCE, TECHNOLOGY AND INNOVATION INDICATORS (STI 2023) 27., 2023, Leiden. Proceedings… Leiden: STI, 2023.
• JANSSEN, M. et al The promises and premises of mission-oriented innovation policy: a reflection and ways forward. Science & Public Policy, Oxford, v. 48, n. 3, p. 438-444, 2021.
• KHAN, J.; JOHANSSON, B.; HILDINGSSON, R. Strategies for greening the economy in three Nordic countries. Environmental Policy and Governance, Chichester, v. 31, n. 6, p. 592-604, 2021.
• LUTZ, J.; STORMS, C. The practice of technical and scientific communication. Norwood: Ablex Publishing Corporation, 1998. p. 30.
• MAZZUCATO, M. The entrepreneurial state: debunking public vs. private sector myths. London: Anthem Press, 2015.
• MAZZUCATO, M. From market fixing to market-creating: a new framework for innovation policy. Industry and Innovation, London, v. 23, n. 2, p. 140-156, 2016.
• MAZZUCATO, M. Mission-oriented innovation policies: challenges and opportunities. Industrial and Corporate Change, Oxford, v. 27, n. 5, p. 803-815, 2018.
• MAZZUCATO, M.; PENNA, C. The Brazilian innovation system: a mission-oriented policy proposal. Brasília: Centro de Gestão e Estudos Estratégicos, 2016. (Temas Estratégicos para o Desenvolvimento do Brasil).
• METCALFE, S. Equilibrium and evolutionary foundations of competition and technology policy: new perspectives on the division of labour and the innovation process. Revista Brasileira de Inovação, Campinas, v. 2, n. 1, p. 111-146, 2003.
• NELSON, R. R. The economics of invention: a survey of the literature. The Journal of Business, Chicago, v. 32, n. 2, p. 101-127, 1959.
• ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT – OECD. World Bank. The innovation policy platform Paris, 2022. Available from: https://www.innovationpolicyplatform.org/www.innovationpolicyplatform.org/content/denmark/index.html Access in: 6 May 2023.
  » https://www.innovationpolicyplatform.org/www.innovationpolicyplatform.org/content/denmark/index.html
• OWUSU, E. Y.; ANTWI, S. K.; ABUKARI, M. A. Tracing the implications of science, technology, and innovation policy on education in Ghana. In: CUKUROVA 9TH INTERNATIONAL SCIENTIFIC RESEARCHES CONFERENCE, 2022, Adana, Turkey. Proceedings… Turkey: IKSAD Publishing, 2022.
• PACTO GLOBAL. Objetivos de desenvolvimento sustentável. Brasília, 2021. Available from: https://brasil.un.org/pt-br/sdgs Access in: 26 Apr 2023.
  » https://brasil.un.org/pt-br/sdgs
• PFEIFER, L.; HELMING, K. Effective mission-oriented research: a new framework for systemic research impact assessment. Research Evaluation, Oxford, v. 33, p. rvae003, 2024. http://doi.org/10.1093/reseval/rvae003.
• PORTINCASO, M. et al The deep tech investment paradox: a call to redesign the investor model. BCG/Hello Tomorrow, 2021. Available from: https://hello-tomorrow.org/the-deep-tech-investment-paradox/ Access in: 16 July 2023.
  » https://hello-tomorrow.org/the-deep-tech-investment-paradox/
• QIU, Y.; GARCÍA-ARACIL, A.; ISUSI-FAGOAGA, R. Critical issues and trends in innovation and entrepreneurship education in higher education in the post-COVID-19 era in China and Spain. Education Sciences, Basel, v. 13, p. 407, 2023.
• ROBINSON, D.; MAZZUCATO, M. The evolution of mission-oriented policies: exploring changing market-creating policies in the US and European space sector. Research Policy, Amsterdam, v. 48, n. 4, p. 936-948, 2019.
• ROMASANTA, A. et al Deep tech: unveiling the foundations. Rochester: SSRN, 2022. (ESADE Working Paper, n. 276).
• SÁNCHEZ, S.; SEGOVIA, M.; LÓPEZ, L. Impact of public policies on the technological innovation in the renewable energy sector. International Journal of Energy Economics and Policy, Mersin, v. 10, n. 2, p. 139-159, 2020.
• SCORDATO, L.; BUGGE, M.; FEVOLDEN, A. Making innovation a mission? Overview of the implementation of mission-oriented innovation policies in Denmark, Finland and Sweden. Copenhagen: Nordic Council of Ministers, 2020.
• SCORDATO, L. et al Walking the talk? Innovation policy approaches to unleash the transformative potentials of the Nordic bioeconomy. Science & Public Policy, Oxford, v. 49, n. 2, p. 324-346, 2022.
• ŠIPIKAL, M. Tailoring innovation policies to sectors and regions: the case of Slovakia. Law and Economics Review, Oxford, v. 4, n. 4, p. 277-291, 2013.
• SOUSA, M. J.; ROCHA, A.; SOUSA, M. Digital and innovation policies in the health sector. In: EUROPEAN CONFERENCE ON KNOWLEDGE MANAGEMENT, 2019. Proceedings… Lisboa: ECKM, 2019.
• STARTUP GENOME. Global startup ecosystem report 2019 with new life sciences ecosystem ranking 2019. Available from: https://startupgenome.com/reports/global-startup-ecosystem-report-2019 Access in: 26 Apr 2023.
  » https://startupgenome.com/reports/global-startup-ecosystem-report-2019
• STEWARD, F. Transformative innovation policy to meet the challenge of climate change: sociotechnical networks aligned with consumption and end-use as new transition arenas for a low-carbon society or green economy. Technology Analysis and Strategic Management, London, v. 24, n. 4, p. 331-343, 2012.
• STRAUSS, A.; CORBIN, J. Basics of qualitative research: techniques and procedures for developing grounded theory. 2nd ed. Thousand Oaks: SAGE, 1998.
• TEKIC, Z.; ABUELEZ, A.; TEKIC, A. Technological synergies as antecedents of sustainable development: deep-tech versus shallow-tech perspective. Technology Analysis and Strategic Management, London, v. 36, n. 11, p. 3682-3696, 2024.
• UNITED KINGDOM. Department for Business, Energy & Industrial Strategy. Industrial strategy: the grand challenges. London, 2017. Available from: https://www.gov.uk/government/publications/industrial-strategy-the-grand-challenges/industrial-strategy-the-grand-challenges Access in: 22 Mar 2025.
  » https://www.gov.uk/government/publications/industrial-strategy-the-grand-challenges/industrial-strategy-the-grand-challenges
• UNITED NATIONS. Sustainable development goals. New York, 2021. Available from: https://brasil.un.org/pt-br/sdgs Access in: 26 Apr 2023.
  » https://brasil.un.org/pt-br/sdgs
• WITJES, N.; SIGL, L. The internationalization of Science, Technology & Innovation (STI): an emerging policy field at the intersection of foreign policy and science policy? In: JANSEN, A.; MÜNTE, P.; FRANZMANN, A. (Org.). Legitimizing science: national and global public, 1800-2010. Frankfurt: Campus, 2014. p. 245-272.
• WOLF, M. et al 2022 environmental performance index New Haven: Yale Center for Environmental Law & Policy, 2022. Available from: https://epi.yale.edu/epi-results/2022/component/epi Access in: 26 Apr 2023.
  » https://epi.yale.edu/epi-results/2022/component/epi
• YANG, M. Discussion on innovation strategy of government management in the new era. Modern Economics & Management Forum, Singapore, v. 3, n. 5, p. 333, 2022.

• Declaration of Editor Responsible for the Evaluation Process
  Editors Wilson Suzigan (Editor-in-Chief) and Renato de Castro Garcia (Deputy Editor) managed the peer-review process and supervised the article's progress through to final approval.

Publication Dates

• Publication in this collection
  20 Apr 2026
• Date of issue
  2026

History

• Received
  05 May 2024
• Reviewed
  21 Apr 2025
• Accepted
  28 July 2025