外部性
创新经济学
生态经济学
经济
可持续发展
诱导创新
订单(交换)
进化经济学
经济体制
持续性
产业组织
技术变革
新古典经济学
生态学
微观经济学
宏观经济学
生物
财务
标识
DOI:10.1016/s0921-8009(99)00112-3
摘要
While innovation processes toward sustainable development (eco-innovations) have received increasing attention during the past years, theoretical and methodological approaches to analyze these processes are poorly developed. Against this background, the term eco-innovation is introduced in this paper addressing explicitly three kinds of changes towards sustainable development: technological, social and institutional innovation. Secondly, the potential contribution of neoclassical and (co-)evolutionary approaches from environmental and innovation economics to eco-innovation research is discussed. Three peculiarities of eco-innovation are identified: the double externality problem, the regulatory push:pull effect and the increasing importance of social and institutional innovation. While the first two are widely ignored in innovation economics, the third is at the least not elaborated appropriately. The consideration of these peculiarities may help to overcome market failure by establishing a specific eco-innovation policy and to avoid a ‘technology bias’ through a broader understanding of innovation. Finally, perspectives for a specific contribution of ecological economics to eco-innovation research are drawn. It is argued that methodological pluralism as established in ecological economics would be very beneficial for eco-innovation research. A theoretical framework integrating elements from both neoclassical and evolutionary approaches should be pursued in order to consider the complexity of factors influencing innovation decisions as well as the specific role of regulatory instruments. And the experience gathered in ecological economics integrating ecological, social and economic aspects of sustainable development is highly useful for opening up innovation research to social and institutional changes. © 2000 Elsevier Science B.V. All rights reserved.
科研通智能强力驱动
Strongly Powered by AbleSci AI