We praise experimentation but reward compliance. We celebrate innovation but reject the rebel. We assemble platforms but silence feedback. And we rarely ask: will the loop run?

Innovation ecosystems are not activated by structure. They are activated by circulation. And what governs circulation is not policy, but feedback. Feedback is not just a technical signal. It is shaped by culture.

We mistake the presence of institutions for the presence of motion. But presence is not flow. The system may be complete, the actors aligned, the vision clear, and yet the loop never turns. Not because the system is broken, but because no one gave it permission to run.

This is the blind spot. We think we’ve built the machine. But the machine does not start. It sits. It decays. Not through collapse, but through silence.

To understand why, consider a system dynamics model adapted from research across 20 national ecosystems. These models mapped five types of actors: Orchestrators who define missions, developers who build, regulators who enforce, integrators who combine and research partners; most often, universities.

Yet in none of the reinforcing or balancing loops were universities the initiators. They played a role but they did not supply ignition.

Consider the Attractiveness Loop. When an ecosystem becomes attractive, firms enter. That entry leads to more variation, which enables co-development. That produces pilot projects, which, if successful, make the ecosystem even more attractive. It is a classic reinforcing loop. However, the trigger is not research quality but market perception.

Another loop shows that more funding leads to joint research, which produces knowledge outputs. These feed into more pilots, which attract more funding. Again, the university amplifies but it does not ignite. The trigger is not discovery, but capital.

A third loop is fueled by perception. Visibility or hype draws firm entry. That entry increases outputs, which create more visibility. Universities may contribute evidence but the engine runs on narrative.

But not all loops are reinforcing. Some loops stall ecosystems.

For example, more private capital can reduce openness. As sharing drops, co-development slows. With fewer pilots, the case for future investment weakens. This is a balancing loop. And it demonstrates that even well-resourced ecosystems can stall when openness becomes a liability.

In another loop, failed pilots reduce stakeholder expectations. When expectations fall, fewer firms enter. With fewer pilots attempted, pessimism deepens. A single failed test, if mishandled, can shut down an entire engine. And once the mood shifts, no institution can recover momentum alone.

The pattern is clear: universities participate in these loops, but they are not the lead variable. They are platforms, not triggers. Their presence is necessary, but not sufficient.

Yet many national frameworks still treat universities as keystones. The Triple Helix model, for example, positions the university as one-third of an innovation triad, alongside industry and government. It assigns equal agency. But it does not explain what happens when power is asymmetric or when culture resists collaboration.

The National Systems of Innovation framework encourages institutional coordination, assuming that if the right actors are present, collaboration will emerge. But it fails to explain why interaction so often fails to take hold.

Technology transfer theory explains how discoveries can become usable assets. But it assumes that if incentives are aligned, knowledge will flow. It does not explain why innovations often die before they even enter the pipeline.

Experiential learning theory emphasizes training through doing. Many universities have embraced this via internships, lab work and capstone projects. But even if students are prepared, firms may not be culturally ready to receive them.

Innovation capability maturity models help organizations measure their progress. But capability is not the same as permission. A system may be ready but unwilling.

Person–environment fit theory shows why innovators thrive in aligned environments, but it also explains why they leave when conformity is rewarded instead.

These models are structurally correct, however, structure alone is not sufficient. What they lack is cultural diagnosis because ecosystems don’t fail at the policy level. They fail at the point of behavior.

To understand this, consider a corporate–university partnership widely referenced in innovation case archives, often cited as "The Lab That Never Launched".

The initiative was signed. The leadership aligned. The budget approved. The facility built. The staff appointed. Yet after two years, not a single pilot emerged.

This was not a failure of planning. It was a failure of loop activation. The system had components, but lacked permission.

Short-term orientation combined with high uncertainty avoidance creates risk-averse shared values. These values suppress risk-taking, meaning fewer risk-takers apply. A preference grows for stable, predictable jobs. Over time, the talent pool becomes conformity-driven. Performance systems reinforce delivery, not discovery. Results remain stable. Appetite for innovation declines. The loop completes itself by entrenching risk aversion. The system has no incentive to change. And so, it doesn’t.

In a second loop, uncertainty avoidance strengthens conservatism. Hiring favors predictability and risk-neutral talent is selected. These hires reinforce existing norms. Performance systems run smoothly but exclude deviance. Appetite for exploration weakens. Cultural pressure drops. The result is not dysfunction but controlled sameness. The system protects itself from innovation by design.

Only one loop has the potential to reverse this: Rebel talent integration. If deviant thinkers had been intentionally recruited, innovation capability could have risen. That capability would have generated pressure to act. Pressure would raise appetite. Appetite would reinforce the integration of more rebel minds. This could have been a reinforcing loop.

But it never spun because the system filtered for conformity, not curiosity. The loop remained theoretical.

Across both models—one national, one organizational—the pattern holds. Innovation requires permission. Feedback loops do not self-activate, rather, they spin only when systems allow them to.

We focus on strategy, platforms, design. We host summits. We revise policies. But we do not ask: Which behaviors are permitted, or which are excluded.

We say we want innovation but we hire for harmony. We build new spaces but we reject discomfort. We call for co-creation but we select for compliance. So the loop fails before it begins.

Culture is not the soft side of the system. It is the gatekeeper of feedback. And without feedback, no ecosystem circulates.

Until institutions ask what they are still refusing to hear, no structure, no matter how well built, will ever move.

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Toronata Tambun is a doctoral researcher in corporate innovation ecosystems at School of Business and Management, Bandung Institute of Technology (SBM–ITB), where Leo Aldianto is the head of Entrepreneurship and Technology Management Expertise Group.