The Development of Relations between Taiwan and the People's Republic of China in the High-Technology Economic Sector
Bibliographic record
Abstract
competition between China and Taiwan to attract high-tech industry investment recently has become increasingly severe. This study presents an in-depth analysis of the cross-strait (Taiwan, China) high-tech industry, considering the areas of industrial environment, government policy and industrial performance. This investigation examines the likely influence of WTO entry on increasing industry competition. It reveals that considerable development space exists for improving cross-strait relationships and that a competitive and cooperative relationship may appear during the transformation process. 1. Introduction Chinese comprise the bulk of the population of Asia. However, owing to different political views, the Taiwan Strait has separated China into two different states, the People's Republic of China (PRC) and the Republic of China (ROC, Taiwan) since 1949. cross-strait relationship refers to the interaction between these two sides. Following 50 years of separation, both sides developed respective advantages and specialties in science technology. Recently, the high-tech industry has not only created numerous high-tech elites and employment opportunities, but also exerted some very positive effects on international trade, making both sides significant players in the global market. With the global economy remaining gloomy, the Chinese market has attracted enterprises from all over the world. Since its formal WTO entry in 2001, China has been aggressively preparing for challenges from global trade competition. This phenomenon has significantly influenced investment in high-tech industry in China. Many other countries in the world are striving to prevent the magnetic effect between China and Taiwan in high-tech industry. Corporate management thus must create a cross-strait high-tech industry, involving industrial environment, industrial history and industrial infrastructure, to keep up with the development of the Chinese high-tech industry in Asia and succeed in the competitive international market. 2. Criteria for Assessing Industrial Competitiveness Most researchers from an economic or management point of view study the industrial international competitiveness based on an overall economic environment outside the industry and industrial structure. In The Competitive Advantage of Nations , Porter (1990) applied the Diamond Model to interpret the origins of national competitiveness, including five key elements: factor conditions, demand conditions, related and supporting industries, firm strategy, organizational structure, and two additional elements: government and chance. If a nation has good overall performance in all seven conditions, it will be competitive in some industry in the world. Rugman & D'Cruz (1993) and Rugman & Verbeke (1993) proposed a modified version of the Double Diamond Model that they applied to interpret the trade relationship among Canada, Mexico and U.S.A. Porter (1991) considered that since the Diamond Model is continuing the theory on competitive strategy and advantage and has been verified by field investigations and studies involving hundreds of industry types in dozens of countries (Grein and Craig, 1996), its theory is accountable and has integrity. On the other hand, Buckley (1985) adopted a perspective based on the competitive process to identify the determinants of international competitive as being competitive capability, management process and competitive performance. D'Cruz and Rugman (1993) employed the Five Partner Model to emphasize the importance of upstream suppliers and market scale to international competitiveness. Freemantle (1996) found that improving British industrial competitiveness requires both specialized division of labor and basic infrastructure for scientific and technical development. Gardener (1990) emphasized the complete integration of research academia, university, industry, government, the importance of technology transfer and high-tech industrial parks to make international competitiveness into a national characteristic. …
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".