Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective

doi:10.1016/j.ecolmodel.2016.06.006

QIBEBT-IR > 工业生物燃气研究组

	Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective
	Xu, Wanying 1,2; Zhou, Chuanbin 1; Cao, Aixin 1; Luo, Min 1
	2016-10-10
发表期刊	ECOLOGICAL MODELLING
卷号	337 页码:63-72
摘要	Household food waste accounts for the largest fraction of municipal solid waste and becomes an emerging issue in the biogeochemical cycle of urban ecosystem. Multiple stakeholders with varied characteristics are involved in the food waste management; moreover, they can throw great impacts on the material flow of urban waste, in an industrial ecology perspective. However, the internal mechanism of food waste recycling and composting, regarding the behavior and interaction of different stakeholders, is not clear in previous studies. In this research, recycling and composting potential of household food waste is studied by applying the methodology of stakeholder analysis and social network model. The interest, attitude, power and knowledge of different stakeholders and their social networks were examined by interviews, with the studied case of Beijing, China. Result shows the significant difference of multiple stakeholders' properties. The governmental department of municipal solid waste management has the highest power and maximum interest on food waste recycling, whereas the key players (both high power and maximum interest) located in the midstream and downstream of food waste recycling (utilization of compost) are lacking. In addition, the stakeholders, who easily collect accurate information on food waste recycling, are also the ones most willing to share the knowledge. However, the knowledge and information of most stakeholders are insufficient and inaccurate. The density, node and centrality of the social networks on food waste recycling and composting indicate that here were inefficient connection or disjoint between downstream stakeholders and up/midstream stakeholders, however the some key nodes, e.g. composting utilization stakeholders (fertilizer plants) and municipal solid waste management service companies, could contribute more to bridge the social networks of food waste management. Using the tools of stakeholder analysis and social network models can help in understanding the internal mechanism and the complexity of the material flows of urban ecosystem. (C) 2016 Elsevier B.V. All rights reserved.
文章类型	Article
关键词	Food Waste Management Stakeholder Analysis Social Network Model Mechanism Industrial Ecology
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
DOI	10.1016/j.ecolmodel.2016.06.006
关键词[WOS]	NATURAL-RESOURCE MANAGEMENT ; OPTIMAL CONNECTIONS ; CHINA
收录类别	SCI ; SSCI
语种	英语
WOS研究方向	Environmental Sciences & Ecology
项目资助者	National Natural Science Foundation of China(71533004) ; China National Major Science and Technology Program for Water Pollution Control and Treatment(2014ZX07201)
WOS类目	Ecology
WOS记录号	WOS:000382591200008
引用统计
文献类型	期刊论文
条目标识符	http://ir.qibebt.ac.cn/handle/337004/8494
专题	工业生物燃气研究组
作者单位	1.Chinese Acad Sci, Ecoenvironm Sci Res Ctr, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China 2.Chinese Acad Sci, Qingdao Inst Bioenergy & Bioproc Technol, Key Lab Biofuels, Qingdao 266101, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Xu, Wanying,Zhou, Chuanbin,Cao, Aixin,et al. Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective[J]. ECOLOGICAL MODELLING,2016,337:63-72.
APA	Xu, Wanying,Zhou, Chuanbin,Cao, Aixin,&Luo, Min.(2016).Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective.ECOLOGICAL MODELLING,337,63-72.
MLA	Xu, Wanying,et al."Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective".ECOLOGICAL MODELLING 337(2016):63-72.