The Engineering of Innovation Crises: How Markets Hijack Scientific Credibility and Fracture Society
The Engineering of Innovation Crises: How Markets Hijack Scientific Credibility and Fracture Society
Narrative Construction, Mass Media, and Technology Forecasting Agencies Distorting Innovation Trajectories
Author: Monica Bianco, Ecosystems Cooperation advisor -CRF Italy
Abstract
The innovation economy in the Western world has become progressively detached from scientific rigor, driven by financialized narratives and artificially manufactured expectations. Agencies like Gartner, supported by media amplification and investment-driven agendas, have systematically shaped research and development trajectories toward speculative targets rather than grounded societal needs. This article analyzes the mechanisms by which technological narratives are constructed, the systemic consequences of their failures, and the erosion of scientific credibility that results. It calls for a deep rethinking of research evaluation, innovation governance, and the role of communication in restoring public trust and authentic technological progress.
Introduction
Research and innovation are critical pillars of societal development, but their alignment with public interest and scientific rigor has been severely compromised. The Western innovation system, increasingly financialized, no longer responds to societal needs but to speculative cycles orchestrated by narrative construction, media amplification, and investment agencies. As Sarewitz (2020) points out, “innovation has become less about solving real problems and more about maintaining the machinery of expectation and hype” [1]. This has profound consequences not only for technological failure rates but also for the social contract between science and society.
The Manufacturing of Technological Trajectories: The Role of Forecasting Agencies
The primary mechanism of distortion begins with technology forecasting agencies, notably Gartner, Forrester, and IDC. Gartner’s “Hype Cycle” model, introduced in the mid-1990s, became a template for framing emerging technologies along a predictable curve: inflated expectations, inevitable disillusionment, and eventual (but rare) productive adoption.
However, a systematic analysis by Fenn and Raskino (2019) admits that “only a small fraction of technologies identified as transformational achieve meaningful societal penetration” [2]. Studies like Blosch (2020) criticize these models as “self-referential systems that reward the agencies’ own visibility rather than the technologies’ societal impact” [3].
Concrete examples abound. Gartner predicted in 2011 that autonomous vehicles would reach full market viability by 2020; as of 2024, the technology remains heavily limited by infrastructural, regulatory, and ethical challenges [4]. Similarly, the 2015 prediction that blockchain would transform supply chain management globally within five years failed to materialize: recent analyses report that “over 90% of blockchain supply chain projects initiated between 2017 and 2020 were abandoned or failed to scale” (Zhao et al., 2023) [5].
These failures are not anomalies but structural features of a predictive system designed more to stimulate investment waves than to assess scientific readiness. Gartner and similar agencies rarely revisit or audit their past forecasts, relying instead on the market’s short memory and the perpetual search for the “next big thing.”
Narrative Reinforcement through Mass Media and Investment Ecosystems
The manufacturing of innovation crises would be impossible without the active cooperation of mass media systems. Journalists, often without the technical background necessary for critical evaluation, replicate press releases generated by companies, universities, and think tanks.
Scheufele and Krause (2019) found that “over 65% of science news articles rely heavily on uncritically reproduced press releases” [6], amplifying narratives without verifying experimental validation, scalability, or real-world constraints.
Massive attention given to pseudo-breakthroughs — such as graphene revolutions, perovskite solar cells achieving commercialization within two years, or biodegradable plastics — follows the same script: early-stage laboratory results are extrapolated into imminent market disruptions without regard for energy balances, environmental costs, or economic viability. As Pisano (2022) notes, “science hype creates misaligned expectations that not only lead to financial losses but erode the public’s ability to discern real innovation from opportunistic narrative construction” [7].
Structural Consequences: Bubbles, Disillusionment, and the Degradation of Scientific Literacy
The consequences of this system extend far beyond individual technological failures. Financial and technological bubbles systematically drain public resources and private investments away from more resilient, grounded innovation paths. As the European Investment Bank notes in its 2023 Innovation Report, “over 30% of EU venture capital funding between 2015 and 2020 was allocated to sectors later deemed overvalued or underperforming” [8].
Territories and smaller research centers, lacking access to major investment ecosystems or media visibility, are structurally marginalized. Innovation policies become reactive rather than proactive, forcing alignment with globalized hype cycles that do not reflect local needs or capabilities.
At the educational level, the impact is devastating. Young researchers, trained in an environment dominated by publication metrics and media narratives, prioritize fast results and alignment with fashionable topics over deep experimentation and interdisciplinary exploration. As Ioannidis (2021) warns, “the metric-driven system risks creating a generation of researchers more adept at gaming indicators than at contributing to robust knowledge production” [9].
Ultimately, these dynamics fracture societal trust. The public, after repeated cycles of overhyped promises and technological underperformance, becomes skeptical of scientific announcements and disengages from serious innovation discourse. Jasanoff (2020) notes that “the erosion of public trust in science is not primarily due to anti-scientific attitudes but to the visible complicity of science in speculative economic agendas” [10].
Conclusion: Toward a New Governance of Innovation
Restoring scientific credibility and sustainable innovation requires dismantling the mechanisms that manufacture speculative futures. Technology forecasting must be critically regulated, with mandatory auditing of predictive performance and public disclosure of forecast success rates.
Science communication must move beyond amplification of promises and engage critically with uncertainties, risks, and developmental timescales. Research funding agencies must prioritize experimental rigor, reproducibility, and territorial anchoring over media visibility and speculative alignment.
Finally, society must reaffirm that innovation is not an automatic outcome of financial speculation but a difficult, iterative process that demands patience, critical reflection, and systemic responsibility.
Only by confronting the fabrication of innovation crises at their roots can we rebuild a science that serves humanity rather than speculative cycles.
References
- Sarewitz, D. (2020). “Can Science Solve the Real Problems of Humanity?” Issues in Science and Technology, 36(4).
- Fenn, J., & Raskino, M. (2019). Mastering the Hype Cycle: How to Choose the Right Innovation at the Right Time. Harvard Business Review Press.
- Blosch, M. (2020). “Gartner Hype Cycles: A Critical Reassessment.” Journal of Technology Forecasting and Social Change, 157, 120103.
- Litman, T. (2023). “Autonomous Vehicle Implementation Predictions: Implications for Transport Planning.” Victoria Transport Policy Institute Report.
- Zhao, Y., Zhou, M., & Li, S. (2023). “Blockchain Adoption in Supply Chains: Successes, Failures, and Lessons.” Journal of Business Logistics, 44(2).
- Scheufele, D. A., & Krause, N. M. (2019). “Science audiences, misinformation, and fake news.” Proceedings of the National Academy of Sciences, 116(16), 7662–7669.
- Pisano, G. P. (2022). “Bubbles in Innovation: When Good Ideas Get Hijacked by Hype.” Harvard Business Review.
- European Investment Bank (2023). Innovation Report 2023: Rebalancing Growth and Sustainability.
- Ioannidis, J. P. A. (2021). “Meta-research: Why research on research matters.” PLOS Biology, 19(3), e3000961.
- Jasanoff, S. (2020). Science and Public Reason. Routledge.
