10. Cluster Analyses and Case Studies
10.1. Two Taiwan’s Agglomeration Models
10.1.1. Spillovers Model - IT Cluster
Competitions and innovations are constant challenge for a strong cluster. Local competition helps to improve the quality of product and service delivery. Innovation drives forward the changes. Spillovers potential is calculated with the assumption that the cluster has agglomerated into a strong cluster with a saturation of employment.
Previously, the test for the cluster is 5% of a city’s employment. Furthermore, the cluster is growing in all three rates, revenue, employment, and wages. The strong growth is providing a condition for the spillovers either the manpower shortage or lack of trained
labor, and a demand for rising revenue. The market demands are driving the employment to go up and wage to rise due to the labor shortage, and the spillover is mostly to spread over to the adjacent locations that is the spillovers of enterprises. The co-location factor makes the spillover a natural shift. Both Taoyuan and Miaoli are good examples of the spillovers from Hsinchu. Hsinchu once reaching its saturation with either very high wage (highest in Taiwan.), or undersupply of labor can lose market shares. More companies will be established in the adjacent cities for the benefit of co-location and spillover effects. We will find the growth rates of adjacent cities on Figure 69.
Figure 69 IT Cluster Growth Map.
Source: Taiwan National Statistics Bureau
IT is a dominated cluster in the Northwest District, and cities within this District are experiencing the spillovers. First take a look at the IT cluster’s growth of all cities. IT dominates in Hsinchu and New Taipei. The adjacent cities of Hsinchu are New Taipei, Taoyuan, Miaoli and Taichung. Both Hsinchu City and Country are stagnated in
employment and revenue growths. The adjacent city of New Taipei has revenue growth, but stagnate in employment growth. Miaoli the next city with the district is enjoying a
three-dimensional growth. It has the highest employment growth according to the Figure 69.
Figure 70 IT Cluster Dynamics.
Source: Taiwan National Statistics Bureau
From the Figure 70, we see the revenue is also on a high growth as well as the wages.
Both Hsinchu cities have declined in revenue. Figure 72 listed all the cities in the co-location adjacencies. We can actually see the spillovers from the highest LQ out to the neighboring cities.
Revenue-to-compensation ratio is often used by businesses owners to gauge labor efficiency. For some researchers use the reverse ratio of compensation-revenue ratio interchangeably that the newer and smaller companies tend to have higher growth rates with a bigger compensation-revenue ratio, but overtime, it improves as the firms expand and sustain successfully. Older firms, in general, slow down on growth (Bracker &
Pearson, 1986, p. 517). Here the revenue-compensation ratio is used to represent businesses’ profitability as well. A revenue-compensation ratio below tells the rising cities of IT clusters.
129 Figure 71 Revenue-Compensation Ratio of IT cluster.
Source: Taiwan National Statistics Bureau
Three cities, New Taipei, Taoyuan and Miaoli, are three larger workforce group with high labor efficiency growths in the IT clusters. Both Hsinchu regions with the highest wages are facing efficiency declines with less profits42F42F43. The adjacent cities’ high growth rates are signs of spillovers.
Below list all the factors for the IT cluster:
Figure 72 Spillovers Potential Factors for IT Cluster.
IT Cluster Wage
43 The revenue-compensation ratio is an indication of labor efficiency. The more efficient labor management can save cost, thus, be more profitable for shareholders.
Hsinchu 5.8% -1.8% 1.6% 69,729 36.5% 9.2% 3.9 913
Hsinchu City 7.5% -1.8% 1.8% 135,441 52.7% 17.9% 5.6 1,094
Miaoli 2.9% 27.7% 23.1% 38,253 27.0% 5.1% 2.9 704
Taichung 2.2% 6.4% 6.6% 67,074 7.1% 8.9% 0.8 647
Changhua -0.7% 3.6% 0.5% 4,181 1.3% 0.6% 0.1 468
Nantou 6.4% -7.7% -7.1% 3,465 4.0% 0.5% 0.4 898
Yunlin -2.4% -18.4% -1.8% 2,998 2.6% 0.4% 0.3 508
Chiayi 2.5% 16.5% 12.2% 796 0.9% 0.1% 0.1 425
Chiayi City 1.8% -1.8% -2.8% 411 0.7% 0.1% 0.1 568
Tainan 4.8% -8.9% -7.8% 24,200 4.6% 3.2% 0.5 695
Kaohsiung 3.9% -2.6% -1.0% 60,985 7.8% 8.1% 0.8 658
Pingtung 2.9% 4.0% 4.1% 797 0.6% 0.1% 0.1 421
Yilan 4.8% 39.9% 13.8% 1,932 2.1% 0.3% 0.2 491
Hualien 16.4% 101.7% 40.7% 72 0.1% 0.0% 0.0 790
Taitung -7.0% 28.3% 3.2% 9 0.0% 0.0% 0.0 276
Penghu 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0 0
Kinmen 264.2% 648.6% 68.8% 14 0.1% 0.0% 0.0 640
Lienchiang 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0 0
Source: Taiwan National Statistics Bureau
Both Hsinchu City (5.6) and County (3.9) have two highest concentrations and high wage growths especially Hsinchu City with an over 7% growths, and both are facing revenue declines. Hsinchu City, highly specialized with an over 52.7% shares of City
employment. New Taipei, Taoyuan, and Miaoli, the adjacent cities demonstrate around 20% growths in revenue, and Miaoli especially has an 23% employment growths.
Taichung shows moderate growths but all positive growth rates which indicates the growing momentum is strong, and the LQ is approaching the national level. Both Hsinchu City and County, the hub, is showing a saturation of labor with wage rising rapidly. The drop of revenues indicates the spillovers are shifting to the neighboring cities. The spillovers started from the highest wage of two Hsinchu from 1,094K and 913k spreading to the adjacencies to the lower wage cities (Miaoli of 704k, Taoyuan of 717k, New Taipei, 773k) which confirms the labor pool saturation. The average wages in the three cities clearly confirm the spillover effects. Both Hsinchu City and County are over NT$900,000 in annual wages, and Taoyuan and Miaoli are a bit over NT$700,000.
Hsinchu City has the highest average wages among all cities over NT$ one millions annual average wages. We can also conclude that the spillover starts from the highest wage region and spreads out to the lower wage regions.
Further test needs to see where the spillover stops, going further south to see if Taichung has spillovers to the next city Changhua, and the numbers prove the answer “It stopped at Taichung”. Changhua has employment growths of 0.5% and wages declines of 0.7% in this cluster; despite the revenue growths of 19%, the employment share is a little over 1%, and the wages of NT$467k is way below that of spilling over cities of NT$700k; in the meantime, the LQ is 0.14 which is a very low participation ratio. The conclusion is drawn that the spillovers stop at Taichung. Taiwan’s IT cluster’s empirical case proves the variable relations of spillovers effects. The spillovers slowly spread to the next adjacent location.
The cluster agglomeration takes spillovers into account that, activities naturally spreads over to highly demanded and growing industries, and the knowledge and experiences spills over to other applications or industries. For the research question: What causes spillovers in an industrial cluster? The conclusion is drawn from the above observations:
Spillovers is not a cause; it is an effect.
Spillovers is caused by the shortage of labor. Spillovers occurs when labor pool reaches saturation.
Revenue spillovers happens when employment and wages rise simultaneously in high rates.
Wage rises when labor pool is undersupplied, and if the wages drop, it is an indication of oversupply of labor pool.
The available workforces supplied by the labor pool is a critical factor to trigger the spillover effects. It can impede the revenue growth if labor pool is in shortage.
Wage is an indication for the saturation of the labor pools. When wage rises, it can trigger the spillover effects, especially the wage is much higher than the adjacency locations.
Business will try to look for alternatives.
Wage and labor participation are the measures for the labor saturation; the higher the saturation, the more scares of the available labor and higher the wages.
Wages and employment growth are dependent on revenue growth (business income).
And the labor supply contextually influences the employment and wages.
Spillovers mostly occur in the knowledge-based industries, which the spillovers occur when the labor pool cannot provide the immediate productive manpower. The productive labor is defined to be the knowledge-based or highly-skilled people, who take more than a year to be trained for the knowledge or skills.
For Taiwan, an annual contract is considered to be a long-term position. This also implies that the shortage of low knowledge and skilled labor supply pool does not trigger the spillovers as long as the labor pool is not saturated, or the labor pool can be fueled from other industries without a long-term training. This summarizes not all industries carry spillover effects, that only those industries require knowledge-based or highly-skilled people can create a spillover effect provided the supply of manpower is not a limit.
Spillovers are inhibited by the higher wages in the adjacent location.
Spillover does not work when the adjacent location has a higher wage than other cities in the same cluster. Taipei provides the proof for this claim. The spillovers will go to the location with a lower pay such as Taoyuan and Miaoli with available labor pools and lower wages. Besides, Taipei has an average of NT$950k, the second highest of all cities.
With LQ of 0.3 means there is better pays for other jobs than the IT jobs in Taipei. In other words, people have more choices to select from.
LQ can be a gauge for a location that is ready for spillovers. When a cluster has a low LQ (much lower than 1), the location has not developed the labor pool needed for spillovers; then the location will not be the candidate for the spillover. Changhua is the case for IT cluster with a LQ of 0.1 with a very low location shares of 0.6%. Taichung has a LQ of 0.8 which is close to the specialization qualification of 1 and much higher location shares of 9% with all three growth rates are positive; this means that Taichung is receiving spillovers most likely from both Hsinchu City and County since both have
revenue drops in the IT cluster. This is a clear case of revenue spillover with both wages and employment rising with high percentages in both Hsinchu.
From the observations, the cluster spillover theory is enhanced with the following properties:
1. The revenue is market demand driven in an open free market.
The market demands trigger the need for solving important societal demands, which requires high knowledge or difficult skills for the solutions, and the solution will serve a mass market.
2. The mass market means the solution impacts many lives.
3. The solution requires time and money to invest in final deliveries to solve societal demands, and the investment will generate returns in profits for the funds infused.
For example, making a toothbrush is not a challenge technically or requires difficult skill set, but making comfortable shoes can be challenging since it requires the experience and skills to make good moldings for the curves of feet to make them comfortable for many people. Italian’s shoe industry demonstrates this expertise. Flora Holland created a high-tech logistics system from a farming industry into a sophisticated floral trading platform to meet the floral market’s demands. They are not short of flower growers in the world, and flowers can be very cheap in some parts of the world to create a price competition. FloraHolland faced the price-cut competition severely years ago, and designs a turnkey solution to overcome the problem. Their turnkey solution requires a team of skillful people to design and maintains a complex and the world-class logistics system and trading platform. It delivers the freshest flowers to anywhere in the world from any growers in the world. Any growers may join the platform to sell their flowers and benefit from the fairest commission for the logistics and selling. This type of system takes knowledge, experience, and technology to solve the problem of pricing competition. People who work in the industry have converted from a local grower to an international flower provider. The flower cluster soon agglomerates in Holland and internationally. The demand for the labor pool has gained varieties of job backgrounds such as computer scientists, logistic managers, and trading analysts. Soon Flora Holland established more sites within Holland and other places in the world. The trainings go along with the system is important too, so that FloraHolland is not short of labor to expand their businesses. At the end, the business agglomerated internationally.
4. Both wage and employment are influenced by the labor pool supplies. Undersupply of manpower can cause the wage to go high, and oversupply of manpower can cause the wage to go down. The labor pool supply can also directly influence the
employment to go high or low depending on the supplies.
5. Cluster spillovers are the works spreading to the adjacent location with available labor pools.
10.1.2. Supply-Chain Migration Model - Production Technology and Heavy