Pathways to Energy Transition: A Faceted Taxonomy

G. Böhm, Rouven Doran, Annika Rødeseike, H. Pfister
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引用次数: 8

Abstract

Abstract The article deals with the public perception of energy transition pathways, that is, of strategies towards sustainable ways of energy use. Implementing sustainable pathways poses a major challenge for organizations and society. Using a facet theoretical approach, we investigate the structure of people’s mental models of such pathways. Three facets are defined capturing the conceptual structure of transition pathways. Facet A (Level) distinguishes three elements: individual behaviors, societal actions, and technologies. Facet B (Type) distinguishes energy efficiency from curtailment pathways. Facet C (Impact domain) distinguishes five domains of potential impact of an energy transition pathway: economy, community, human health, nature, and life quality. A computer-administered survey with items derived from the facet design was administered to a student sample (N = 106). A multidimensional scaling analysis yields regional regularities for Facets A and B. For Facet A polar regions can be clearly distinguished according to the facet elements. Facet B shows regions exhibiting a modular structure with curtailment pathways located in the center and efficiency pathways in the periphery. Facet C shows a less clear pattern, showing the two elements economy and nature at opposing ends of an axial structure. Implications for the communication and management of sustainable energy transitions in society and organizations are discussed.
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能源转型之路:多面分类法
摘要:本文讨论了公众对能源转型途径的看法,即对可持续能源利用方式的策略。实施可持续发展道路对组织和社会构成了重大挑战。使用面理论的方法,我们研究了这种途径的人的心理模型的结构。三个方面被定义捕捉转换路径的概念结构。Facet A (Level)区分了三个要素:个人行为、社会行为和技术。Facet B(类型)区分能源效率和弃风路径。Facet C(影响域)区分了能源转换路径的五个潜在影响域:经济、社区、人类健康、自然和生活质量。对学生样本(N = 106)进行了计算机管理的问卷调查,问卷中包含来自面设计的项目。对Facet A和b进行多维尺度分析,得出了它们的区域规律。对于Facet A,可以根据Facet元素清晰地区分极区。Facet B显示了具有模块化结构的区域,其中削减路径位于中心,效率路径位于外围。面C显示了一个不太清晰的模式,显示了经济和自然两个元素在轴向结构的两端相对。对社会和组织中可持续能源转型的沟通和管理的影响进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.60
自引率
14.30%
发文量
13
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