Monitoring Innovation in Dynamic Ecosystems: From Strategy to Behaviour

As innovation ecosystems evolve, so do the roles of those within them. In the 4Growth project, we explore not just who the key players are, but how they interact, position themselves, and drive adoption. This requires a closer look at how innovation flows, from upstream creators to downstream users, and how we can monitor these dynamics in real time.

Upstream and Downstream Actors

Digital ecosystems involve both upstream and downstream actors:

• Upstream ecosystems are made up of foundational contributors, those who develop the technologies, infrastructure, and standards:
  • In digiproduct ecosystems: researchers, manufacturers, and test labs.
  • In data ecosystems: software developers, data scientists, cloud infrastructure providers.

Their role is to ensure innovations are viable, scalable, and interoperable.

• Downstream ecosystems include users and decision-makers who adopt and apply innovations:
  • Farmers, foresters, agribusinesses, and public agencies play this role in digiproduct ecosystems.
  • In data ecosystems, downstream users might engage through dashboards, decision-support systems, or mobile apps.

Downstream actors shape adoption trajectories. Their feedback loops are vital to ensure products and services align with real-world needs. Just as importantly, their trust in the quality and relevance of data drives uptake.

Navigating the Ecosystem Space

Innovation doesn’t follow a straight line. It unfolds within what we call the ecosystem space, a strategic landscape where actors define their roles, build relationships, and determine value exchange.

Ecosystem scoping refers to the process by which actors:

• Identify relevant collaborators
• Position themselves strategically
• Define how they engage with data, technology, and networks

To support this, 4Growth applies the PARATA principle:

• Potential Actors – who could add value?
• Actively Relevant Actors – who is already involved?
• Targetable Actors – who can be strategically engaged?

This helps map dynamic ecosystems, especially where actors take on multiple or shifting roles over time.

Monitoring Innovation in Practice

To understand how innovation spreads through these ecosystems, we use both behavioural and diffusion models:

• The Bass Diffusion Model helps track how early adopters and imitators drive uptake.
• The COM-B model (Capability, Opportunity, Motivation – Behaviour) offers insight into what enables or blocks adoption.
• API-based data extraction and Large Language Models (LLMs) are being tested to monitor adoption trends in real time—providing both top-down and bottom-up insights.

These tools help identify bottlenecks, emerging opportunities, and behavioural patterns at scale.

From Scoping to Policy

One key insight is that ecosystem scoping is actor-specific: each stakeholder navigates the innovation space according to their goals, constraints, and resources. Unlike market scoping, this includes non-monetary dimensions such as:

• Access to data
• Knowledge sharing
• Institutional influence

This calls for flexible policy tools that reflect the diversity and dynamism of digital innovation spaces.

Monitoring innovation today means tracking how actors engage with complex ecosystems—not just whether a product sells. By understanding strategy, behaviour, and relationships, we can build better tools, smarter engagement models, and more adaptive policies.

This blog is the second in a two-part series exploring how the 4Growth project maps innovation in digital agriculture and forestry.