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Policy instruments' effectiveness for facilitating industrial symbiosis: A UK–China comparative study from firms' perspectives

工业共生体系 业务 激励 工业生态学 概念框架 背景(考古学) 公司治理 持续性 产业组织 主题分析 交易成本 过程管理 定性研究 经济 社会学 工程类 生态学 社会科学 古生物学 财务 生物 微观经济学 废物管理
作者
Yuan Tao,Ying Xiong,Stephen Evans,Qi Feng,Lei Zhang
出处
期刊:Journal of Industrial Ecology [Wiley]
标识
DOI:10.1111/jiec.13581
摘要

Abstract Industrial symbiosis (IS) can be a powerful business concept to achieve sustainability and generate significant co‐benefits by utilizing waste from one factory as input to another factory in industrial complexes. However, the adoption of IS is not as expected, partly due to inadequate tailoring to the diverse institutional contexts across different regions. Existing research on facilitating IS has primarily focused on individual countries or industries, lacking insight into the mechanisms and pathways adopted in countries with different economic development levels and policy approaches in facilitating IS. This study conducts a comparative analysis of two facilitated IS initiatives between the United Kingdom and China, where the “parks” are expended to “countries.” The objective is to clarify what policy instruments work well under what conditions in fostering facilitated IS from firms' perspectives. Qualitative methods including semi‐structured interviews, on‐site observations, and archival analysis are employed to collect data, which is analyzed by using thematic coding based on a conceptual framework for comparing the speed‐dating/exogenous IS model. The research finding is that effective facilitation of IS requires tailoring policy instruments to its institutional context, leveraging economic incentives in more decentralized economic systems which are driven predominantly by the needs and initiatives of businesses or local community, and administrative mandates in relatively centralized governance environments. The study emphasizes the importance of developing facilitation approaches adapted to diverse institutional contexts for promoting IS and the cross‐learnings between these models potentially advancing implementation.
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