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題名:政府政策對企業技術擴散與經營效率的影響-以資源產業為例
作者:陳依兌 引用關係
作者(外文):Yi-Tui Chen
校院名稱:國立中央大學
系所名稱:企業管理研究所
指導教授:張東生
學位類別:博士
出版日期:2009
主題關鍵詞:隨機邊界模型組織學習效果擴散效果環境政策成本效率Environmental policyCost efficiencyStochastic frontier analysisOrganizational learning effectDiffusion effect
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擴散效果與效率評估已被廣泛的運用在分析政策對環境的影響,本文利用擴散效果模型探討政策效果下,資源回收服務系統與台灣電力公司的廢氣排放系統中的技術擴散,結果說明政策對於環境保護會產生明顯的效果,同時在技術的擴散效果發生後,在技術擴散效果下,技術的更新將會帶來營運成本的上升,因此,本文更利用效率評估的方法探討擴散效果帶來成本上升後的影響,本文的分析結果將可以對環境保護提供較好的政策設計。
首先,本文以擴散效果模型、組織學習模型與交互模型探討資源回收服務系統的成效,實證結果明確的說明擴散效果、組織學習效果與交互效果為影響資源回收系統的主要因素,除此之外,環境政策明顯的影響擴散效果與組織學習效果,這也是促進資源回收服務加速擴散的主因,而擴散效果、組織學習效果與交互效果對環境皆帶來正面的影響;同時也可以觀察到環境政策公佈後,技術的擴散效果也存在於台灣台灣電力公司的廢氣排放系統,因此在本文的第二階段,本文以logistic模型討論廢氣排放系統的技術擴散與政策對環境的衝擊,利用排放系統所形成的懸浮微粒、硫氧化物與氮氧化物的排放數量探討台灣電力公司內技術擴散的效果。結果顯示,當已被預期的政策公佈對擴散效果所帶來的研發會產生負的作用,而將環境標準限制與經濟工具兩種方式搭配的政策將對擴散效果所帶來的研發有正面的效果。由於技術的擴散所帶來的研發將會促使台灣電力公司的營運成本上升,因此本文利用隨機邊界模型估計台灣電力公司的成本效率,並考慮何種因素將會影響到成本效率。一般來說,利用Hausman test將可以找出個別效果與投入要素是否具有相關性以避免產生偏誤的估計結果,同時也可以檢測模型是否可以準確的估計出結果,而在無偏誤的檢定結果下,隨機邊界模型也可以說明規模經濟是否存在於台灣電力公司,並且利用logistic模型找出影響效率的外在因素。
The policy impact on the environmental protection has been widely discussed by diffusion effect and efficiency evaluation. In this study, the diffusion effect is employed in the fields of MSW (Municipal Solid Waste) recycling and emission technology of TPC (Taiwan Power Company), and our results reveal that policies have a significant effect on environmental protection. The efficiency evaluation is further used to analyze the cost efficiency of TPC after the technology update to comply for the emission standard.
We demonstrate that the implementation of recycling policy brings the diffusion effect on recycling service. Firstly, we employ three models, including the diffusion effect model, the organizational learning effect model, and the interaction model to explain the performance of MSW recycling service. Based on the amount of recyclable waste in Taiwan, we show that the diffusion effect and learning effect have significantly impacts on MSW recycling service. In addition, environmental policy has a significant influence on environmental diffusion and organizational learning, and leads to the accelerating performance of MSW recycling. Moreover, the interaction of diffusion and organizational learning has a positive impact on MSW recycling performance.
Similarly, it can also be observed that the diffusion of emission technology exists in TPC. In the second part of this study, we employ a logistic model to describe clean technology diffusion and examine the impacts of environmental policy (emission standards and economic instruments). The plant is characterized by TSP (Total Suspended Particulate), SOx (Sulfer Oxide), and NOx (Nitric Oxide) emissions in 14 power plants provided by TPC. The results show that the regulated emission standard provides a negative effect on technology diffusion as the effect may be attributed to the anticipation and flexibility of regulations with respect to their effects on innovations. Our results demonstrate that the ‘mixed policy’ (an integration of environmental standards and economic instruments) has a positive effect on technology diffusion for NOx but remains limited for TSP and SOx.
Due to the diffusion of innovation, TPC may invest on technology update that also promotes the increase on cost. Therefore, we use a SFA (stochastic frontier analysis) to estimate the efficiency of TPC in the third part of this study. In most previous studies, the efficiency estimated by Panel Data without endogeneity testing may bring a biased estimator resulted from the correlation between input and individual effect. A Hausman test is conducted in this paper to examine the endogeneity of input variables and, thus, an appropriate model is selected based on the test result.
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