On the qualitative analysis, the study is to address the policy delivery effectiveness issue.

To address the closing gap between policy makers and people, a comparative study has been done on the cluster initiative decision models. Taiwan, EU, and US was assessed to make the differentiation how economies drive their cluster initiatives. The three models came out differently, Taiwan is the top-down model, EU is the bottom-up model, and the US have the interactive model. Taiwan focuses on technology excellence by encourage innovations. The EU sets their shared vision on solving important human issues for a better living environment, and EU has an observatory platform for everyone to use for their industrial cluster initiatives. The US has the cluster mapping tool released by the Commerce Department to create jobs by utilizing the latest regional cluster information.

The US model currently solves a bottleneck problem of knowledge sharing, which is the world current technological shortfall, too much information and lack of organizations.

For the quantitative analyses, the research defines Taiwan’s cluster code for the calculation of growth rates and redefines Taiwan’s economic districts based on the


regional specializations. A digit-sliced evaluation tool is designed to evaluate the

dynamics of regional and cluster analyses. The economic landscape then is derived from the clustered specialties. By analyzing revenue, employment and wages growth rates, the researcher derives the dynamic landscape of the five-year census data from 2006-2011.

The employment shares give the clustering information on industries, and city and districts are defined based on the clustering effects. Revenue growth tells how well a cluster is doing after an external shock. Wage and employment growths are indicators on the labor pool demand and supplies. From Taiwan’s growth dynamics, a dominated cluster is identified, Information Technology and Analytical Instrument, demonstrating the spillovers of employment by the rising wages.

Through the inductive research, Taiwan’s industries are identified with two models of industrial agglomeration. One is the spillover model, and the other one is the supply-chain migration model. The two models have different wage growth patterns. The spillovers’ model has the wage growth rising with the dominate city leading the highest wages and spreading employment out to the lower-waged adjacent cities. On the other hand, the supply-chain migration model shows a cluster of similar strong clusters with growth rates running in parallel, and the wages is very close among the specialized cities.

There is no leader in wages nor the wages are rising sharply.

IT industry has the knowledge-based spillovers model and the highest cluster salary from Hsinchu area. The dominated cluster attracts over 50% of workforce in the region and spreads over to the neighboring regions from north to south stopping at Taichung. The supply-chain migration model has machine tooling industries (Production Machinery and Heavy Equipment and among other Metal Working Technology, etc.) concentrating in the middle region especially clustered in Taichung and Changhua cities. The strong (over 5% workforce participations regionally) clusters are growing in a similar pace. The field surveys confirm the findings that many enterprises receive orders from the IT industry, and many have factories in China or Southeast Asia for lower labor cost and make export diversions to compensate the lack of FTA problems in Taiwan. The local regions have difficulty attracting workforce participation due to industry upgrade and lack of skilled


workers. The revenue-compensation ratios show that the wage in the Machine Tooling industries are much less than the IT industry.

Through the regional and cluster analyses, industrial dynamics are identified with some alarming facts. One alarming phenomenon throughout Taiwan is that the downstream products such as Downstream Metals, Wood, Furniture, Footwear products are facing stringent market competitions are facing steep declines despite the upstream

manufacturing are growing. This impact all regions especially the production regions from the middle regions southward. The dynamic assessment from the cluster growths indicates the Downstream Metal Product cluster having the revenue declines and the employment declines in almost all cities (See Figure 153). This means the market

competition is causing the declines for Taiwan. On the other hand, for the Transportation and Logistics cluster, the revenue and wages are all rising, but the employment rates are all declining (Figure 154); this is an indication of labor pool shortage. The transportation industry is booming due to the web order merchandizing. Every country with web access are recruiting shipping staff, and Taiwan’s low wage has lost on the labor competition in this case.

One noticeable cluster is the Business Services which is growing in revenue and

employment across the board mostly from north to south, spreading throughout the main island and outward, and the wage is still low and declining with less

revenue-compensation ratio about three times. This is an indication that the Business Services industry is in demand, and the labor pool is not saturated, but the service skills have not reached the knowledge demanded professional base. In the meantime, this cluster has not reached the specialization level in many cities. More development can be done to elevate the quality of labor pool in this cluster.

Some small clusters are growing but still very specializing and small such as

Biopharmaceuticals and Medical Devices (less than 3% total combined in employment shares). A case study is done on Taiwan’s Bioeconomy since this industry has been on the policy maker’s list to incubate, but has not reached prosperity yet. The cluster map has derived two regions in this industry. The North district (Taipei and New Taipei) of Taipei regions has more research institutes working on pharmaceutical research and has


the most populated workforce in this region. For the Southwest region, especially Tainan has good potentials for the expansion of Nutraceuticals and Medical Devices clusters utilizing the local specializations of food and textile production machine tooling

industries. The local specialized production machinery industry and the science park can provide the complementary supports to the knowledge and skill development for the labor pools. The capacity is still available and open in the area. This is where policies may help in terms of aiding the embryonic incubation.

The outer islands are segregated and isolated in general and not correlated with the main island’s growths, therefore, is studied separately. The outer islands are primarily military based and are active in tourism due to the open trade agreement with China. The risk of instability is high due to its political dependency. One cluster on the rise is the Aerospace Vehicle cluster in Kinmen which may help to create local specialization and employment.

The Business Services cluster is rising as well, and more education training can be provided throughout regions.

在文檔中 台灣經濟形貌: 增進公共政策效益之動態群聚模式 - 政大學術集成 (頁 162-165)