Mission Impossible: The Influence of Incumbent Industries on Mission-Oriented Innovation Policy Targeting Carbon Lock-In
Bibliographic record
Abstract
In this paper, we explore how the power wielded by regional incumbents has impacted subnational innovation agendas. Our findings suggest that the design of mission-oriented innovation policies should be more attentive to regional innovation policies and their relationship to how innovation may serve to bolster incumbents and not undermine them. We use a case-study of innovation in fossil fuels. Recently, innovation policy literature has explored innovation policy and global climate as a major topic. On the one hand, carbon lock-in has been used to explain why there has been such difficulty in reducing carbon emissions, in many cases, despite an increasing emphasis of mission-innovation policies. On the other hand, mission-innovation policies are believed to be a key to the development of disruptive innovations that could break this carbon intensive path dependency. Although the two literatures explore the same problem, there could be more integration. While carbon lock-in is being considered in the mission- innovation literature, it nevertheless has been largely overlooked at the mission-setting stage. On the other hand, the lock-in literature has tended to overlook the findings of mission-oriented innovation literature in offering solutions, which suggests that there is a more productive role for mission-oriented innovations in breaking free of previous constraints to serve in the low-carbon energy transition. To make our case, we argue it is important to distinguish among the various impacts disruptive innovations have on the market shares of incumbents’. We propose the following three schema: new market, market rewarding and market destroying. By variegating the potential impact of innovations, we suggest that mission-oriented innovation polices may be designed to only support certain types of innovations that do not directly undermine the market share of incumbents. Using a detailed case study of the Province of Alberta, Canada, we then explore the roleof the province’s mission-oriented policy in the development of technology to produce the Canadian oil sands. The case study illustrates how incumbents influenced the establishment and direction of the mission’s goal. Shifts in incumbency opposition toward the province’s mission-oriented innovation policy coincided with the changing impact of the innovation from being market destroying to market rewarding. We suggest that future researchshould be more attentive to the role of incumbents in influencing mission-oriented innovation policy and the importance of their influence at the mission-setting stage. Furthermore, we suggest that to meet the grand challenge of addressing climate change through mission-oriented innovation policies, these policies must be designed to break free of these institutional constraints.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".