Innovation by Design: Impact and Effectiveness of Public Support for Business Innovation
Bibliographic record
Abstract
As the 21st century unfolds, there is a growing recognition that the competitive global landscape is altering the context within which government support for innovation programs should be assessed. This monograph explores a number of conceptual and policy design issues relevant for the adoption of innovation policies. It reviews some of the conceptual frameworks used in leading industrial economies, as well as some countries that have experienced more rapid innovation-based (RIB) economic development. The monograph examines the program models that exist for the design and implementation of government support of business innovation at different jurisdictional levels. It places this examination within the context of two broad approaches found in the literature, the traditional neoclassical approach and more recent evolutionary approaches. The monograph explores the existing evidence on the impact of a range of policy instruments, drawing upon several recent reviews of both the academic and more policy-oriented literature. It situates this review in the context of a discussion ofthe shift in focus from research to technology development to innovation-based policies over the course of the postwar period. It asks what value the “policy mixes” approach adds to our understanding of the design and implementation of government programs for the support of business innovation. Finally, it addresses the question of how the introduction of innovation programs within a federal system complicates the evaluation of their impact and creates a need for greater policy alignment. In this respect, it asks what value the multilevel governance perspective, developed initially in the EU, but adopted in other countries, contributes to our understanding of how the effectiveness of policies is supported or constrained by the behaviour of other actors within a multilevel governance system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".