Title: 新竹科學園區產業群聚因素影響分析
Assessing the Critical Factors to Industrial Clustering in Taiwan HsinChu Science Park
Authors: 孫嘉祈
Lin, Grace T R
Keywords: 灰預測;馬可夫鏈;產業群聚;驅動力;新竹科學園區;DEMATEL;Grey forecasting model;Markov chain;industrial cluster;driving force;Taiwan Hsinchu Science Park;Decision Making Trial and Evaluation Laboratory (DEMATEL)
Issue Date: 2008
Abstract: 本論文將分為兩部分研究,首先,本論文將預測新竹科學園區半導體產業與電腦周邊產業,2001年至2007年之產值預測,本論文應用平滑指數模型、灰預測模型與馬可夫灰預測模型為預測工具,由預測結果得知半導體產業其成長率呈現緩慢下降趨勢,而電腦周邊產業則為衰退趨勢,半導體產業與電腦周邊產業其產值超過新竹科學園區整體產值之百分之五十,而台灣產業群聚為台灣國家競爭優勢主要來源,產業群聚能提升生產力,促進新企業發展與創新,並提升行銷與顧客關係,因此,如何改善新竹科學園區整體產值下降,對於企業家與政府而言將是一個重要且急迫的任務,基於此,引發本論文進行第二部分之研究, 本論文第二部分研究欲瞭解產業群聚發展背後之驅動力為何,本論文引用Porter (1980) 國家競爭優勢與群聚驅動力概念,為本論文第二階段之探討主軸。 本論文試著探討不同驅動力對產業成長之影響程度,並探索驅動力彼此間之關係程度, 基於此研究目的,本論文以鑽石模型 (Porter, 1980) 與文化概念,探討產業成長驅動力之優先排序情況,本論文以DEMATEL為研究工具,探討不同驅動力之影響關係,並描繪出驅動力之因果關係圖,判別何者為影響驅動力,何者為被影響驅動力 以提供台灣產業與政府相關策略建議,由研究結果得知主要影響驅動力為要素秉賦條件與當地需求條件,而產業結構、策略與競爭程度,相關支援產業與政府支援為台灣新竹科學園區群聚成長之間接驅動力 最後本論文將根據研究結論提出相關群聚政策,以幫助政府或產業分析師改善台灣產業群聚政策。
This research includes two parts. First, we want to forecast the annual output using the exponential smoothing forecasting model, the GM (1, 1) model, and the Grey-Markov model. The period of this research is from 2001 to 2007. The computer and semiconductor industries are the research examples for estimating model. From our estimation results, we understand that the annual output of the semiconductor industry will slow down in the future while that of the computer industry has a decreasing trend. The annual values of semiconductor industry and computer industry account for over 50% for the Hsinchu Science Industrial Park (HSIP). Industrial clusters can be seen as a main source of national competitiveness, serving to upgrade productivity, new business formation and innovation, and advance marketing/customer relations for Taiwan. Therefore, how to improve the alarmingly decreasing annual output and industrial value of HSIP is a critical and urgent task for industrial practitioners and government officials of Taiwan now and in the future. This point therefore triggers our research motivation for next step. Therefore, the second part of this research is to contribute to the understanding of the casual and effect factors among those influencing an industrial cluster. Another core viewpoint anchored in this section is that national competitive advantages can be achieved by industrial clusters. That is, we would like to make use of the concepts of national competitiveness proposed by Porter (1980) and cluster drivers toward cluster value to conduct our second part of research. We try to examine the impacts of and determine the relationships among different driving forces. To this end, we adopt the Diamond Model (Porter, 1998) in addition to the concept of culture to give the priority to these driving forces. This research then applies the Decision Making Trial and Evaluation Laboratory (DEMATEL) to address the related issues. Discussing the relationship between different drivers and making a causal map that finds out the causal group and effect group, this research provides Taiwan industries and government with some strategic recommendations. From our results, we know that the major causal dimensions are local demand conditions and factor conditions. The factors of cure, firm structure, strategy, and rivalry, related and supporting industries, and government support as the indirect factors will be affected by the two causal factor, factor conditions and local demand conditions for the growth of industrial clusters in Taiwan. Finally we will attempt to draw upon our policy analysis results in order to assist government officials or industrial analysts in improving Taiwan’s industrial cluster policy and fostering the growth of the clusters.
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