Tackling the sustainability issues with biofuels? a case study on the policy window of the Netherlands transitioning toward a "biobased economy"

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Title:	Tackling the sustainability issues with biofuels? a case study on the policy window of the Netherlands transitioning toward a "biobased economy"
Other Titles:	運用政策窗模型分析荷蘭能源政策變遷之研究 : 以生質燃料轉向生物經濟為例
Authors:	熊昔湘;Hsiung, Cindy, Sie-Shong
Contributors:	淡江大學歐洲研究所博士班苑倚曼;Yuan, Renee Yi-Mond
Keywords:	生物經濟;生質燃料政策;能源轉換;政策變遷;政策窗決策模型;Biobased Economy;Biofuels Policy;Energy Transition;Policy Change;Policy Window Model
Date:	2013
Issue Date:	2014-01-23 13:23:33 (UTC+8)
Abstract:	本研究旨在以金頓(John W. Kingdon)之政策窗決策模型(policy window model)分析荷蘭生質燃料政策轉向生物經濟(biobased economy)之政策變遷個案。荷蘭制定生質燃料政策乃基於歐盟會員國執行2003年生質燃料指令之義務，於執行初期設有生質燃料創新技術之研發與示範補助經費，然而研究逐漸發現生質燃料的永續性議題具有高度複雜性，而與食物鏈競爭的第一代生質燃料也引發全球性的爭議，因而要求政府擴大補助以發展較具永續性之生質能(biomass)技術。荷蘭政府於2007年10月針對化學、材料、能源與生質燃料等產業，公布自石油經濟轉型為生物經濟之政策願景，整合相關之現行能源與產業政策，並針對生質能之「非食品」創新工業應用和市場推進新增預算。生質燃料及其永續性議題之政策經驗，成為後石油時代生物經濟之政策先驅，而生質燃料亦從作為轉換汽車能源之政策工具，躍升為成就國家願景的基石之一。生質燃料政策轉向生物經濟之政策概念是如何被推往決策議程的? 為何決策發生在2007年此一特定時間點? 本研究依據政策窗模型之分析架構，釐出個案中影響政策變遷的「問題流」、「政策流」和「政治流」，並發現個案中的「政策企業家」為以農業部為主之政府官員、以生質能研究為優勢之大學和研究機構，以及於荷蘭經濟扮演重要角色之化學產業；其整合生物經濟之政策概念，於新聯合政府上台之際，向決策者行銷為能同時解決工業用生質能之永續性爭議、和符合經營國家競爭力所需之產業策略。當問題、政策與政治三流匯合，即開啟了機會之窗，使生物經濟之政策建議獲得決策者採納。本個案所呈現之實務經驗與理性決策模型相異，而金頓的政策窗模型則為失序狀態之政策系統提供適用之分析架構，運用於本研究具有良好的解釋能力。惟政策窗模型乃針對系統層級之政策變遷因素，並且較不著重媒體於政策過程中所扮演的積極角色，本研究建議未來運用該模型時能配合媒體理論和次系統層級之分析工具，以加強對於影響政策變遷之因素之分析能力。 This study aims to explain the policy transition in the Netherlands, from biofuels to ‘biobased economy,’ with the policy window model introduced by John W. Kingdon. The Dutch transport biofuels policy was installed primarily because of the obligation to implement EU legislation. As it became clear that biofuels sustainability was extremely complex issue and the use of food-based biomass for fuels was highly controversial, however, the Dutch government had not sufficiently addressed the need for subsidies and strategies for sustainable biomass technologies, until the broader industrial sectors, especially chemicals, also lobbied for support for the development of biobased raw materials. In October 2007, the government formulated an official vision on the biobased economy (BBE) for energy transition, which integrated existing energy programs and expanded the budget basis to stimulate innovation and market facilitation for biomass for non-food applications, to which the policy experience of biofuels, including their sustainability issues, became relevant. The biofuels policy thus was ‘upgraded’ from being an instrument of energy transition for the transport sector to a building block of the Dutch BBE. Whereas the way in which the policy developed appeared to be in sharp contrast to rational choice models, this study asks how has the BBE idea come to the policy agenda and at the particular timing of 2007? Kingdon’s model provides a useful analytical tool to identify structures in system anarchy and explains how policy change occurs in a seemingly haphazard policy process. Structured along the analytical framework of the policy window model, this study has assessed those critical factors in the ‘problems stream,’ the ‘policy stream,’ and the ‘political stream’ pertaining to the policy transition of our subject case; and identified the ‘policy entrepreneurs’ to be the governmental institute with agricultural portfolios, the knowledge institute specialized in biomass research, and the prominent chemical sector, who have packaged the BBE idea to be tackling the sustainability issues of biomass for non-food applications, and addressing the political need of the new coalition government for economic growth at the same time. As the three streams converged, a policy window thus was opened for the BBE. Kingdon’s model is found to be relevant and applicable in our case study, but as it focuses on the system level and also does not emphasize the role of the media in the policy process, complementary theories such as those on the subsystem level and media relations would add to the analytical strength in future applications of the model.
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