China: from consumer goods manufacturer to innovation leader ?
Bibliographic record
Abstract
In this study, we will first explore the definition of innovation and reverse innovation. Innovation is on every lip now and it is important to explore and define clearly their exact meaning for this study. Reverse innovation is one of the most important concepts in a study about China. As Roger L. Martin, dean of the Rotman School of Management, University of Toronto said, “Water may not flow uphill but innovation does!” and it is something we have to examine since it might be the key for the Western countries’ companies to stay competitive against the Chinese ones. This study will then examine the current state of innovation in the Western countries and in China to dress a rapid image of where innovation stands now and whether it is shifting from Western countries to China. We will also dress an overview of the current economic situation in China, the world’s second largest economy rising strongly for many years. China is having a worrying indebtedness situation caused by a huge investment in construction to counter the decline of GDP caused by the 2008 crisis in the Western countries. We will see how China wants to solve that by investing in innovation, helped by many factors such as the good market opportunities, the strong capital availability and a wish from the government to change its economy from production and investment driven economy to an innovation driven economy by promoting technological innovation. Finally, with the example of the smartphone industry, we will analyze in what extent China effectively raised its investment in innovation and how its smartphone production and exports are booming. We will conclude by dressing two possible scenarios for its future that could be a crisis such as the one the Western countries knew in 2008, or to become the world’s innovation leader.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".