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| Title: | 台灣半導體供應鏈：網絡分析
Taiwan Semiconductor Supply Chain: A Network Analysis |
| Authors: | 陳維勛
Chen, Wei-Xun |
| Contributors: | 何靜嫺
Ho, Shirley J
陳維勛
Chen, Wei-Xun |
| Keywords: | 網絡分析
冪次分配
中心性
集團
專利數量
Networks
Power Law
Degrees of Centrality
Cliques
Patent Numbers |
| Date: | 2023 |
| Issue Date: | 2023-08-02 13:42:56 (UTC+8) |
| Abstract: | 台灣半導體產業在世界上佔重要的地位。在台灣半導體供應鏈上游、中游和下游廠商包含生產超過27種產品。原本傳統的計算方式像是market share或是HHI無法完全的描述整個半導體供應鏈。所以我們用廠商營收的相關性建立三種不同的網路(threshold, MST and PMFG networks)，在檢查這三個網路是否具有實證網路的特徵。我們的研究表明PMFG networks可以最好的描述網路因為網路degree服從power law distribution。
使用建構出的PMFG網路計算描述網路和廠商的統計量，包含中心性、加權中心性和cliques。並且利用clique分析進一步將節點依照“production-related” 或 ‘product-related”進行分類，接著利用中心性和專利數量的關係，看是否創新行為是否具有傳染效果。
我們的研究發現(1) "production-related" cliques，當cliques至少包含上、中、下游其中一家廠商他的營運成本會比較低。 (2)比較 “cliques producing multiple products” 和 “cliques producing few products” 發現生產比較多產品的cliques他的EPS會比生產比較少產品的cliques來得高。(3)將cliques與金融上的表現連結發現當“three-categories cliques” 裡的廠商股價的平均相關係數最高。 (4)我們研究中心性和廠商專利數量之間的關係，betweenness centrality (BC), closeness centrality (CC), and eigenvector centrality (EC)對於專利數量有正且顯著的影響。 (5) 計算加權的中心性研究加權中心性與專利數量的關係。發現每個節點都使用他的總資產進行加權weighted closeness centrality對於專利數量的影響最大。換句話來說如果每個節點都使用廠商大小來加權我們可以進一步找出影響創新的網路特徵。
Taiwan’s semiconductor industry plays a crucial role in the globe. Our firms cover all upstream, midstream and downstream of the manufacturing process, and provide more than 27 products. Traditional metrics, such as market share or HHI, cannot fully describe the structure of semiconductor industry. As there is lack of actual transactions database, we employ methods that use firms’ revenue correlations to construct three networks (threshold, MST and PMFG networks), then we examine whether the three networks conform to the empirical characteristics of networks. Our analyses suggest that the PMFG network can best describe our data and follow the power law distribution.
We then calculate several metrics to measure the network properties and firm-specific characteristics in the constructed PMFG network, including particularly the degrees of centrality and the node-weighted degrees of centrality, and “cliques”. To further investigate the properties of cliques, we classify cliques according to whether the nodes are “production-related” or they are ‘product-related”. Finally, we investigate the relationship between firms’ degrees of centrality and the number of patents they hold, to see if there are contagious effects on firms` innovation activities.
Our results show that (1) for "production-related" cliques, if a clique contains at least one firm each from the upstream, downstream, and midstream, then the operating costs tend to be lower. (2) We compare “cliques producing multiple products” to “cliques producing few products”, and found that cliques producing multiple product categories tend to have higher average EPS than those producing fewer categories. (3) We examined the financial connection within cliques, and found that the “three-categories cliques” have the highest average correlation coefficient in member firms’ stock prices. (4) We explored the relationship between the centrality measures of firms and the number of patents, and found that betweenness centrality (BC), closeness centrality (CC), and eigenvector centrality (EC) had a positive and significant effect on patent counts. (5) We calculated the asset-weighted centrality to examine its impact on the number of patents. We found that after each node is weighted by the proportion of total asset, the weighted closeness centrality becomes most relevant for innovations. In other words, after weighing each node by its relative firm size, we can further identify the most relative network feature for innovations. |
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| Description: | 碩士
國立政治大學
經濟學系
110258025 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110258025 |
| Data Type: | thesis |
| Appears in Collections: | [經濟學系] 學位論文
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