The answer, according to Lupeng Zhang, Yulin Chang and Wenbo Chen of Beihang University’s School of Public Administration, is that the network grew nearly tenfold — from 8 participating central government agencies in 1978 to 73 by 2023 — without ever fracturing. Across five distinct historical stages, the network’s cohesion index never dropped below 0.68, and it actually reached its highest value in the most recent stage. In most large organisations, growth of that magnitude tends to dilute coordination; here, the researchers found the opposite. Scale and cohesion climbed together, and the timing of each structural shift lined up closely with successive upgrades in national science and technology missions.

The evidence base is unusually comprehensive. The team assembled 1,010 STI policy documents issued jointly by central government agencies between 1978 and 2023, treating every co-signed document as a collaboration link between the agencies involved. They then combined policy network theory with the mission-oriented innovation policy framework and applied multi-period social network analysis — a family of mathematical techniques that measure how densely connected a network is, which nodes sit at its centre, and how those positions change over time. Because the design is descriptive, the authors are careful to note that the findings support association between missions and network structure, not causal attribution. Even so, the patterns they document are striking enough to challenge a foundational expectation of Western policy network theory.

That expectation is the movement from a tightly knit

That expectation is the movement from a tightly knit policy community, in which a small set of actors with shared interests dominates a policy domain, toward a fragmented issue network, in which many participants with divergent interests interact at low levels of consensus and stability. The Chinese STI policy network traced in this study appears to move in the opposite direction: as the number of participating agencies multiplied, the density of ties and the overall cohesion of the network did not decay but strengthened. The authors interpret this as a possible third path — mission-driven orderly expansion — in which the escalation of national missions acts as a centripetal force, repeatedly pulling new agencies into a coordinated structure rather than scattering them into loosely coupled issue networks.

A central contribution of the analysis is the differentiation of agency roles. Rather than a single dominant core issuing directives to periphery, the mature network exhibits a division of labour among four distinct role types. Agenda Leaders set priorities and initiate policy action; Boundary Spanners connect otherwise separate clusters of agencies and broker information across institutional divides; Innovation Seeds introduce new themes and catalyse collaboration around emerging technological domains; and Resource Hubs supply the budgets, personnel and administrative capacity that allow joint policies to be implemented. This typology offers a vocabulary that can be applied to other state-led innovation systems, where the question is not simply who is central but what kind of centrality each actor occupies.

The five-stage periodisation also carries analytical weight. Each stage corresponds to a redefinition of the national science and technology mission — from the early reform era’s rebuilding of the research system, through successive strategic programmes, to the more recent emphasis on self-reliance in critical technologies. At each transition, the network absorbed new participants and reorganised internal roles, yet the cohesion index remained above 0.68 throughout. This suggests that mission upgrades functioned as coordination devices: they gave heterogeneous agencies a shared objective around which joint policy documents could be negotiated, and thereby sustained integration even as the network’s membership expanded dramatically.

Methodologically, the study illustrates the value of treating administrative documents as network data. Every policy issued jointly by two or more central agencies is a record of real coordination effort — agencies must align positions, share drafting responsibility and accept accountability together. Aggregating 1,010 such documents across 45 years produces a longitudinal network that can be partitioned into periods and compared statistically, revealing structural dynamics that single-case studies of individual policies cannot capture. Multi-period social network analysis, in particular, allows the researchers to distinguish durable structural features from transient fluctuations, and to track how individual agencies’ positions rose, fell or transformed as missions changed.

The descriptive design imposes limits that the authors acknowledge. Association between mission upgrades and network restructuring does not establish that missions caused the observed cohesion; other forces — administrative reforms, leadership priorities, changes in the policy agenda — could plausibly contribute, and disentangling them would require different research designs. The focus on central government agencies also leaves out the provincial and municipal levels, as well as the non-governmental actors that increasingly participate in innovation governance. Nonetheless, the finding that scale and cohesion rose together over nearly five decades is difficult to dismiss as coincidence, and it invites comparative work: do other state-led innovation systems show similar mission-driven network expansion, or is the pattern specific to China’s institutional configuration?

For policy network theory more broadly, the study poses a constructive challenge. The policy community-to-issue network trajectory was developed largely from pluralistic Western settings, where policy domains tend to fragment as more interests enter. The Chinese case suggests that in systems where the state assigns and periodically upgrades national missions, network evolution can follow a different logic — one in which expansion is deliberately managed and cohesion is treated as a policy objective in its own right. Extending network theory to accommodate such state-led dynamics, the authors argue, would require theorising missions not merely as policy content but as structural forces that shape who collaborates with whom.

The research was supported by the National Social Science Fund of China and a Major Special Project of Philosophy and Social Sciences Research from the Ministry of Education of China. The authors analysed publicly issued administrative documents, involving no human participants, and declare no competing interests. The article is published open access, making the full network data reconstruction and analytical detail available to researchers interested in testing the mission-driven expansion hypothesis in other national contexts and time periods.

Subject of Research: Science, Technology and Society

Article Title: How national missions reshape policy networks: evidence from China’s STI policy-making collaborative network, 1978–2023

Article References: Zhang, L., Chang, Y., & Chen, W. (2026). How national missions reshape policy networks: evidence from China’s STI policy-making collaborative network, 1978–2023. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-026-09004-y

Image Credits: AI Generated

DOI: 10.1057/s41599-026-09004-y

Keywords: China, STI policy, policy networks, mission-oriented innovation, social network analysis, innovation governance, science policy, collaborative networks, national, missions, reshape, policy

The research team, led by Manal Ali Almarashdah of Jadara University together with Ayman Abdalmajeed Alsmadi of Al Zaytoonah University of Jordan and Mohammad Ali Al-Afeef of Al Al-Bayt University, grounded their work in two complementary theoretical traditions: the resource-based view and dynamic capability theory. The resource-based view holds that valuable, rare and hard-to-imitate resources — such as an agile strategy process or a digitally committed leadership team — form the raw material of competitive advantage. Dynamic capability theory explains how firms sense opportunities, seize them and continuously reconfigure resources in fast-moving environments. In the study’s framework, strategic agility, digital orientation and innovation governance act as strategic resources, while FinTech capability maturity serves as the dynamic capability that converts those resources into measurable outcomes.

FinTech capability maturity is defined as an organization’s accumulated ability to systematically integrate, implement and continuously improve its use of financial technology — a progression that runs from basic digital adoption through data-driven innovation to fully integrated financial ecosystems. The authors argue that this construct fills a gap in the literature, which has often examined FinTech from the standpoint of customer adoption or technological implementation without identifying the organizational capability through which managerial decisions translate into performance. By positioning maturity as the central mediating capability, the study offers a unified explanation of how leadership actions produce long-term value in turbulent digital financial markets.

To test their model, the researchers surveyed 255 qualified informants working in Jordanian banks, financial institutions and FinTech organizations. Respondents included senior managers, digital transformation specialists, innovation managers, IT professionals, compliance officers and risk managers — all selected through purposive sampling to ensure direct knowledge of their organizations’ digital strategies and FinTech initiatives. The questionnaire contained 24 items across six constructs, adapted from previously validated measurement scales and reviewed by three academic experts before distribution. The sample size exceeded established requirements for partial least squares structural equation modeling, and the researchers assessed non-response bias and common method bias, finding no statistically significant differences between early and late respondents and full collinearity variance inflation factors below the recommended threshold of 3.3.

The analysis, conducted in SmartPLS 4, proceeded in two stages. The measurement models showed strong psychometric quality: all factor loadings exceeded 0.60, Cronbach’s alpha and composite reliability values surpassed the 0.70 benchmark, average variance extracted exceeded 0.50, and discriminant validity was confirmed using both the Fornell-Larcker criterion and the heterotrait-monotrait ratio. The structural model was then evaluated with bootstrapping based on 5,000 subsamples, testing five hypothesized direct relationships between the constructs.

The results were strikingly consistent. Strategic agility exerted the strongest influence on FinTech capability maturity, with a path coefficient of 0.406, followed by managerial digital orientation at 0.344 and innovation governance at 0.207, all statistically significant. Together, the three predictors explained 63.6 percent of the variance in FinTech capability maturity — a substantial share for organizational research. In turn, maturity showed powerful downstream effects: it explained 34.8 percent of the variance in service innovation performance, with a path coefficient of 0.590, and 46.0 percent of the variance in organizational responsiveness, with a coefficient of 0.678. Model fit statistics, including a standardized root mean square residual of 0.073, fell within acceptable limits, and all inner variance inflation values remained well below collinearity thresholds.

Each capability contributes through a distinct mechanism, the authors explain. Strategic agility enables firms to perceive technological shifts early and rapidly reallocate resources toward emerging FinTech opportunities, accelerating the adoption of artificial intelligence, blockchain and big data analytics. Managerial digital orientation shapes where money and attention flow: digitally oriented leaders champion experimentation, prioritize technology investments and cultivate cultures of continuous digital learning, which smooth the integration of FinTech solutions into existing operations. Innovation governance — the formal structures, policies and oversight committees that direct innovation activity — aligns technology investments with strategy, manages the risks of emerging technologies and helps organizations navigate the stringent regulatory demands of financial services, a factor the authors consider especially important in highly regulated markets like Jordan.

The downstream consequences are equally consequential for practice. Financial institutions with high FinTech capability maturity can fuse AI, blockchain and analytics with their service processes, producing personalized offerings, faster delivery and richer customer experiences — the hallmarks of superior service innovation performance. Maturity also underpins responsiveness: real-time data, advanced analytics and integrated digital systems allow firms to detect market shifts, react to regulatory changes, launch products quickly and coordinate responses across departments. The study situates these findings in Jordan’s rapidly digitalizing financial sector, where the Central Bank of Jordan has encouraged digital banking, mobile payments and regulatory technology, and where banks face simultaneous pressures from cybersecurity requirements, financial inclusion programs and FinTech entrants.

The authors draw pointed implications for policymakers and executives. Regulators should create innovation-friendly frameworks, including regulatory sandboxes, that let institutions experiment with AI, blockchain and open banking while safeguarding stability. Central banks are urged to embed digital leadership training and national FinTech awareness programs in digital transformation strategies. Financial institutions themselves are advised to benchmark their FinTech maturity regularly, tie digital objectives to executive performance evaluations, establish cross-functional innovation committees spanning business, technology, risk and compliance, and invest in scalable platforms and data-driven decision systems. Collaboration among banks, FinTech firms, universities and technology providers, the study adds, can accelerate knowledge diffusion and raise digital competence across the entire sector.

The researchers acknowledge limitations that temper interpretation. The cross-sectional design cannot establish causality over time, the Jordanian context may limit generalizability to other economies, and self-reported survey data carries residual bias risks despite procedural and statistical safeguards. The study tested only direct relationships and three predictors, leaving room for future work on mediators such as organizational learning and AI adoption, moderators like environmental uncertainty, and longitudinal designs tracking capability development. Even so, the core message stands out with unusual clarity: in emerging digital financial markets, sustained advantage flows not from technology purchases but from the managerial capabilities — agility, digital leadership and disciplined governance — that turn FinTech potential into organizational performance.

Subject of Research: How managerial capabilities drive FinTech capability maturity and organizational performance in financial institutions

Article Title: Strategic agility and digital orientation as drivers of FinTech capability and organizational performance

Article References: Almarashdah, M. A., Alsmadi, A. A., & Al-Afeef, M. A. (2026). Strategic agility and digital orientation as drivers of FinTech capability and organizational performance. Discover Global Society, 4(1), Article 239. https://doi.org/10.1007/s44282-026-00581-6

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00581-6

Keywords: FinTech, strategic agility, digital orientation, innovation governance, dynamic capability theory, resource-based view, digital transformation, service innovation, organizational responsiveness, Jordan, banking, PLS-SEM