The authors built their analysis on a structured review of 57 peer-reviewed studies, integrating three established theoretical lenses: the Triple Helix Model, which describes the interplay of universities, industry, and government; the National Innovation Systems framework, which treats innovation as the product of interconnected institutions; and Governance Theory, which focuses on how relationships among actors are coordinated and steered. By weaving these perspectives together, the team set out to identify what distinguishes transitional settings from mature innovation systems such as those in Western Europe or North America. Their conclusion is that conventional models of university-industry collaboration, which typically assume well-functioning institutions as a starting condition, simply do not travel well to post-conflict and post-authoritarian environments. In those contexts, the institutions themselves are part of the problem.

The evidence assembled in the review points to a cluster of mutually reinforcing barriers. Weak institutional coordination means that universities, firms, and public agencies often operate in silos, with no effective body aligning their priorities. Fragmented policy frameworks leave research and innovation initiatives scattered across ministries and programs without coherent strategy. Limited mutual trust between academics and business leaders discourages the long-term commitments that joint research and development requires. Insufficient university autonomy and research capacity prevent institutions from acting as reliable partners, while misaligned incentives—where academic careers reward publications rather than applied outcomes, and firms demand short-term returns—undermine the willingness to cooperate on either side. Beneath all of this lie historically embedded institutional legacies that continue to shape behavior long after formal political transitions have occurred.

What makes these findings technically significant is the way the authors reframe the problem. Rather than treating governance as a fixed backdrop, they propose understanding it as a dynamic process: a sequence of institutional coordination, trust-building, policy alignment, and progressive consolidation of relationships among universities, industry, and government. In this view, institutional fragility and historical legacies are not obstacles to be overcome before collaboration can begin, but integral dimensions of the collaboration process itself. This context-sensitive collaborative governance perspective extends the Triple Helix and innovation-system approaches by foregrounding the mechanisms required for university-industry relationships to emerge, stabilize, and generate sustainable research and development outcomes in environments where those relationships have never functioned smoothly.

Kosovo and Albania serve as the study’s illustrative contexts, and their profiles are instructive for a much wider set of countries. Both are economies in transition, shaped by post-conflict or authoritarian legacies, with higher education sectors that have expanded rapidly but often without commensurate investment in research infrastructure or institutional autonomy. Firms in both countries tend to be small and medium-sized enterprises with limited internal research capacity, which means they have much to gain from academic partnerships but few resources to initiate them. Public institutions, meanwhile, frequently lack the coordination capacity to broker and sustain such partnerships. The result is an innovation ecosystem in which every actor has reasons to collaborate but no reliable framework for doing so—a situation the authors argue is characteristic of transitional economies more broadly.

The conceptual contribution of the paper lies in connecting previously fragmented strands of literature. Work on institutional governance, innovation systems, and university-industry relations has largely developed in parallel, with each field addressing a piece of the puzzle. By bringing them together, Nuka and colleagues establish a conceptual foundation for future empirical investigation in Kosovo, Albania, and comparable transition economies. This matters because empirical research in such settings has often imported frameworks designed for mature systems, producing findings that misdiagnose local realities. A framework that explicitly accounts for institutional fragility allows researchers to ask more precise questions: not merely whether collaboration exists, but what governance conditions enable it to emerge and endure.

The practical implications are equally concrete. For policymakers, the study argues for more coherent policies that align research, innovation, and industrial strategies rather than leaving them dispersed across agencies. For universities, it highlights the need for institutional capacity-building and greater autonomy so that academic institutions can act as credible, responsive partners. For industry stakeholders, it points toward trust-based partnerships built on realistic expectations and aligned priorities rather than one-off transactions. The authors emphasize that these interventions are interdependent: policy coherence without trust-building produces paper frameworks, while trust without institutional capacity produces fragile pilot projects that collapse when key individuals move on. Sustainable collaboration, in their account, requires progress on all fronts simultaneously.

The study also situates university-industry collaboration within the broader agenda of sustainable development, positioning well-governed research partnerships as a mechanism for advancing Sustainable Development Goals 4, 8, 9, and 17—covering quality education, decent work and economic growth, industry, innovation and infrastructure, and partnerships for the goals. This framing reflects a growing recognition that innovation-led development in emerging economies cannot be achieved by universities or firms alone. When collaboration functions, it channels academic knowledge into productive capacity, creates demand-driven research agendas, and builds the absorptive capacity that allows economies to adopt and adapt new technologies. When it fails, the result is a persistent gap between what universities produce and what economies need, reinforcing dependence on imported knowledge and limiting local innovation.

For the international research community, the paper offers a caution against one-size-fits-all innovation policy. Donor programs and national strategies alike have often assumed that establishing technology transfer offices, incubators, or matching funds will automatically generate collaboration, mirroring models that succeeded in mature systems. The Kosovo and Albania evidence suggests that such instruments underperform when the underlying governance relationships are absent. The authors’ framework implies that interventions should be sequenced and designed to build coordination capacity, trust, and aligned incentives first, creating the conditions in which conventional collaboration tools can then take root. As transition economies worldwide—from the Western Balkans to Central Asia—seek to convert expanding higher education systems into engines of innovation, this study provides both a diagnostic lens and a roadmap, arguing that the quality of governance relationships, not the mere presence of universities, firms, and public institutions, determines whether research and development collaboration can flourish and endure.

Subject of Research: Governance of university-industry R&D collaboration for innovation in transition economies

Article Title: Governance of university industry research and development collaboration for innovation in transition economies

Article References: Nuka, D., Troshani, I., & Mijo, K. C. (2026). Governance of university industry research and development collaboration for innovation in transition economies. Discover Sustainability. https://doi.org/10.1007/s43621-026-04736-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04736-y

Keywords: university-industry collaboration, R&D governance, transition economies, innovation systems, Triple Helix model, Kosovo, Albania, institutional trust, sustainable development goals, research policy, Governance, university

The authors argue that the explanation for this paradox cannot be found in the biology of the edited plants themselves. Instead, they contend, it lies in the way the technology is embedded within broader social structures. To make that argument, they reach back several decades, before CRISPR was invented, to the work of the German-born Canadian physicist and philosopher of technology Ursula M. Franklin, who lived from 1921 to 2016. In her book The Real World of Technology, first delivered as lectures in 1989 and published in 1990, Franklin developed a framework that the Freiburg researchers believe helps explain why genome-edited crops have met such different receptions on either side of the Atlantic and across sectors of application.

Franklin’s central insight was that technologies are never merely tools. In her view, every technology is in fact an entire system, shaped jointly by regulation, markets, institutions and culture. A genome-editing enzyme such as Cas9 is, on this reading, only the visible tip of a much larger formation that includes patent regimes, seed markets, food-safety authorities, agricultural traditions, media narratives and consumer expectations. Franklin’s work explored how such technological systems influence power, authority and everyday life, and in this respect her thinking echoes ideas developed earlier by social historians and philosophers such as Michel Foucault, Lewis Mumford and Jacques Ellul, all of whom analyzed technology as a force that organizes society rather than a neutral instrument within it.

Applying this framework to CRISPR reveals why the risk-based argument familiar from plant science has failed to settle the debate. European regulation of genome-edited plants has its origins in a 2018 ruling of the Court of Justice of the European Union, which held that organisms produced by new mutagenesis techniques fall within the scope of existing genetically modified organism legislation. That judgment entrenched a regulatory pathway built on traceability and labelling requirements established for transgenic organisms, including the traceability and labelling framework laid down by European rules from 2003. Under such a system, a plant whose genome differs from a conventionally bred counterpart by only a small deletion or point mutation can nonetheless be classified, tracked and labelled as a genetically modified organism, even though the molecular outcome is one that traditional breeding could also have produced.

From a technical standpoint, the distinction is indeed difficult to defend on scientific grounds. Genome editing with CRISPR–Cas typically introduces small insertions, deletions or base substitutions at targeted loci. Conventional mutagenesis breeding, which has been practiced for decades using chemical or radiation treatments, produces random mutations across the genome and is exempt from the strict genetically modified organism rules in many jurisdictions. Site-directed nuclease editing is, in effect, a more precise version of mutagenesis, with far fewer unintended changes to monitor. The 2014 analysis by Frank Hartung and Jürgen Schiemann, cited in the commentary, examined precisely these questions of equivalence and risk. Yet, as the Freiburg team emphasizes, the regulatory treatment of a product does not track its biological properties but its production process—a decision that is legal and political rather than scientific.

The policy landscape, however, has begun to shift. In 2023 the European Commission put forward a proposal for a regulation on plants obtained by certain new genomic techniques and their food and feed, seeking to differentiate between categories of genome-edited plants according to the type of genetic change involved. That process culminated in June 2026 with Regulation (EU) 2026/1388 on plants obtained by certain new genomic techniques and their products, which amends the earlier 2017/625 regulation on official controls. This legislative move represents an attempt to build a more differentiated system, one that can distinguish targeted edits indistinguishable from conventional breeding outcomes from more extensive modifications. For the commentary’s authors, the episode illustrates Franklin’s point in real time: the technology’s fate is being decided not in the laboratory but in the architecture of rules, institutions and market arrangements that surround it.

What, then, would a sustainable innovation system for CRISPR in plant science look like? The commentary’s argument suggests several components. First, regulation must be technically coherent, meaning that the category into which a plant falls should reflect the nature and scale of the genetic change rather than the method used to create it. Second, transparency and traceability need to serve public trust rather than functioning as ends in themselves; if consumers cannot see how decisions are made, labelling schemes risk becoming symbolic battlegrounds rather than informative tools. Third, the benefits of the technology must be distributed in ways that farmers, breeders and consumers can recognize, since an innovation system that concentrates value in a few patent holders is unlikely to sustain broad social license. Fourth, public engagement has to treat citizens as participants in shaping the system, not merely as audiences to be persuaded of its safety.

The contrast between medicine and agriculture sharpens this point. In therapeutic applications, genome editing is evaluated within a well-established institutional framework of clinical trials, ethics committees and health technology assessment, and it addresses conditions that individual patients and their families experience as urgent and personal. In plant breeding, by contrast, the same molecular intervention is situated within agricultural systems marked by long-running debates over industrial farming, seed ownership, pesticide use and the concentration of the food supply. The technology is not judged in isolation; it inherits the anxieties and political commitments attached to the system it enters. Franklin’s framework makes this inheritance explicit, and it explains why campaigns that focus exclusively on communicating the molecular facts have repeatedly failed to move public opinion in the European agricultural context.

The economists’ perspective adds a further layer. The commentary invokes Kenneth Boulding, whose work on economic imagery and evolution emphasized that societies live by narratives and images as much as by material flows. Genome-edited plants, in this light, compete not only on agronomic performance but on the story they are embedded in—are they a continuation of human stewardship of crops, or an escalation of corporate control over the food chain? Building a durable innovation system means attending to that narrative infrastructure deliberately: who is seen to benefit, who is seen to decide, and what risks are seen to matter. The authors’ use of Franklin and Boulding signals that the scientific community must engage these questions on their own terms rather than dismissing them as misunderstandings of the science.

Ultimately, the Freiburg commentary makes a claim that reaches beyond plant biology to the governance of emerging technologies in general. CRISPR–Cas is a genuinely transformative tool, capable of precise, targeted and increasingly diverse genetic interventions, and its technical trajectory continues to accelerate. Whether that capability translates into societal benefit in agriculture depends on assembling the surrounding system—regulation, markets, institutions and culture—into a configuration that is scientifically sound, economically viable, socially trusted and ethically defensible. The new European regulatory framework of 2026 offers an opening, but the deeper lesson from Franklin is that no single ruling settles the matter. A sustainable innovation system is not a finished artifact but an ongoing practice of aligning technological capability with public values, and the genome-editing debate in plant science is now one of its most instructive real-world tests.

Subject of Research: Societal and regulatory dimensions of CRISPR genome editing in plant breeding

Article Title: CRISPR beyond biology: building a sustainable innovation system

Article References: Barbez, E., Boldt, J., & Kleine-Vehn, J. (2026). CRISPR beyond biology: building a sustainable innovation system. Nature Plants, 12(9), 1648-1649. https://doi.org/10.1038/s41477-026-02410-9

Image Credits: AI Generated

DOI: 10.1038/s41477-026-02410-9

Keywords: CRISPR, genome editing, plant breeding, Ursula Franklin, EU regulation, new genomic techniques, agricultural biotechnology, science policy, public acceptance, GMO legislation, innovation systems, Nature Plants

The review, authored by Yaqi Bi, Ruijia Guo, and Xingming Fan, frames the comparison through two contrasting models. The first is an innovation-driven cycle, in which private companies are the principal engine of research and development, sustained by strong intellectual property protection and reinvested profits. The second is a public institution-centered cycle, in which government research organizations drive the core of breeding work. The distinction, the authors stress, is institutional rather than technological. Both countries now share access to the same molecular toolkit of genomic selection, high-throughput phenotyping, and programmable gene editing, which makes the stubborn performance gap all the more telling as evidence that institutions, not laboratory techniques, are doing the differentiating work.

In the American system, that machinery runs on private capital. Companies such as Corteva, which spent approximately 1.4 billion U.S. dollars on research and development in 2024, operate within a legal framework anchored by the Plant Variety Protection Act and patent law, allowing them to recoup massive breeding investments and plow returns into the next generation of hybrids. This closed loop of investment, protection, and profit has produced remarkable efficiency, particularly in selecting maize adapted to high planting densities, the cornerstone of large-scale intensive farming. But the model carries risks of its own. Strict intellectual property regimes and intense market concentration can crowd out small firms and public researchers, and the review notes that consolidation may narrow the genetic diversity of the germplasm pool, encouraging variety homogenization. The United States has historically balanced these pressures through public funding of basic research via the USDA Agricultural Research Service and the Land Grant University system, alongside policy measures aimed at promoting competition and transparency in the seed sector.

China’s system has followed a different trajectory. Breeding has long been concentrated in public institutions such as the Chinese Academy of Agricultural Sciences and provincial academies, and despite enormous government investment, the pipeline from laboratory to market has repeatedly broken down. Weak intellectual property protection historically allowed a practice the authors call imitation breeding, in which enterprises made slight modifications to existing varieties and profited at low cost. That business model gutted the incentive for genuine research investment, fragmenting the seed market into thousands of small companies with little capacity for innovation. The consequences are visible in the genetics: although thousands of new maize varieties are approved in China every year, more than 80 percent of the varieties promoted in the main production belts trace back to the backbone parental lines Zheng 58 and Chang 7-2 and their derivatives. That narrow genetic base proved dangerously fragile when southern rust swept the Huang-Huai-Hai region in 2021, causing large-scale yield losses because most promoted varieties shared a susceptible background.

The turning point came in 2021 with the launch of China’s Seed Industry Revitalization Action Plan, which explicitly designates seed companies as technological innovation entities and redirects research resources toward competitive commercial firms. Reforms such as the green channel and consortium testing have given enterprises more autonomy in variety evaluation, while approval standards have shifted from pure yield toward wide adaptability, accelerating the pace of variety upgrading. Perhaps most consequential is the 2021 amendment to the Seed Law, effective March 2022, which establishes an Essentially Derived Varieties system. Under the EDV framework, commercialized varieties modified from protected originals require the original owner’s approval, a mechanism designed to sever the profit chain of imitation breeding and push companies toward original innovation built on new germplasm and new technology. The authors caution, however, that a time lag is inevitable between policy enactment and market transformation, and that consolidating thousands of fragmented firms into globally competitive leaders will take years to materialize in measurable genetic gain.

Regulatory divergence over gene editing sharpens the contrast further. The United States, under the SECURE rule implemented in 2020, applies a product-based framework: gene-edited traits that could be achieved through conventional breeding, such as SDN-1 edits, are effectively exempt from regulatory review, enabling rapid commercial iteration of insect-resistant and herbicide-tolerant varieties. China historically regulated by process, treating the technique rather than the product as the trigger, but its 2022 guidelines for the safety evaluation of gene-edited plants introduced a tiered system for crops lacking exogenous DNA. Applicants can now proceed directly to a safety certificate after the intermediate test stage, cutting the commercialization cycle to roughly one to two years. The results followed quickly: China authorized its first safety certificate for gene-edited high-oleic-acid soybeans in 2023 and approved gene-edited maize in 2024. This positions China in the middle ground of the global regulatory landscape, between the permissive American model and the European Union’s process-based regime, which imposes full GMO-equivalent assessment and, according to the review, acts as a strong deterrent to private investment.

The quantitative indicators assembled by the authors reveal how deeply institutions shape breeding objectives, which in turn shape the crop itself. American hybrids achieved their highest documented genetic gain of 81 kilograms per hectare per year under high planting densities, reflecting decades of private investment in plant architecture suited to mechanized, intensive agriculture. Chinese varieties recorded a higher figure of 94.7 kilograms per hectare per year, but the review is emphatic that the two numbers are not directly comparable, having been drawn from different studies, periods, germplasm, and planting densities. The contrast reflects divergent breeding goals rather than superior Chinese progress: China has historically prioritized yield stability for smallholders farming scattered, variable land, while the U.S. pursues density tolerance, which delivers resilience and stable yields at equal or lower input levels. China is now raising planting densities and shifting toward intensive production, where optimizing density has been shown to lift grain yield under Chinese field conditions.

Nitrogen use efficiency tells a similar institutional story. Measured as grain produced per unit of applied nitrogen, American maize reached 49.0 kilograms per kilogram of nitrogen in 2017, nearly double the Chinese figure of 25.8. The gap, the authors argue, is not primarily technical. In the profit-driven American cycle, companies invest heavily in high-efficiency varieties because fertilizer savings translate directly into margins, and embedding nitrogen efficiency as an explicit breeding goal has improved it without sacrificing yield. In China’s output-maximizing model, fertilizer subsidies historically pushed nitrogen efficiency into a secondary role behind total production. That calculus is changing as China embraces green development, and nitrogen use efficiency has now become a key criterion in variety approval, a revision of past priorities under the government-led system. Meanwhile, R&D spending patterns are converging: China’s top seed companies have sharply increased investment, and enterprise-led innovation consortia signal a shift from a dispersed structure toward a consolidated, research-centered model.

The global implications extend well beyond the two superpowers. Brazil offers the template the review finds most instructive: after establishing the public research corporation EMBRAPA in the 1970s, the country passed plant variety protection and biosafety laws in the 1990s and early 2000s, attracting multinational firms while building local champions into an efficient public-private division of labor, with EMBRAPA supplying germplasm and pre-breeding support and private companies handling commercialization. India presents the cautionary mirror image. Despite a vast public research network under ICAR, weak intellectual property protection, a fragmented seed market, and wavering biotechnology regulation outside cotton have deterred private investment, leaving maize yields below the world average. For developing economies, the authors conclude, public funding alone is insufficient; even resource-constrained breeding programs can raise genetic gain per unit cost by optimizing scheme design, but breaking technology lock-in requires moderate government intervention paired with credible IP frameworks.

The review’s ultimate message is that neither pure market forces nor pure state planning suffices. The ideal system pairs public funding of high-risk basic research and guardianship of germplasm diversity with a competitive private sector that translates technology into farmers’ fields, the balance China is now attempting through systematic reform. And even institutional repair will not be enough on its own: converting new germplasm into faster, more predictable genetic gain will require data-driven breeding platforms that integrate genomic selection, high-throughput phenotyping, and shared databases within the smart-breeding frameworks now emerging worldwide. For a crop that underpins food security for billions, the yield gap between Beijing and Washington is ultimately a measure of institutional design, and the race to close it will be won in lawbooks and boardrooms as much as in the field.

Subject of Research: Comparative analysis of maize breeding innovation systems and their systemic drivers of breeding efficiency in China and the United States

Article Title: Systemic drivers of maize breeding efficiency in China and the U.S.

Article References: Bi, Y., Guo, R., & Fan, X. (2026). Systemic drivers of maize breeding efficiency in China and the U.S.. Journal of Agriculture and Food Research, 31, Article 103301. https://doi.org/10.1016/j.jafr.2026.103301

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103301

Keywords: maize, breeding efficiency, China, United States, intellectual property, gene editing, seed industry, genetic gain, nitrogen use efficiency, innovation systems, food security, EDV system