An analysis of metrics used to measure performance in green and sustainable supply chains

被引:313
|
作者
Ahi, Payman [1 ]
Searcy, Cory [1 ]
机构
[1] Ryerson Univ, Dept Mech & Ind Engn, Toronto, ON M5B 2K3, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Metrics; Indicators; Performance measures; Sustainable supply chain management (SSCM); Green supply chain management (GSCM); MANAGEMENT-PRACTICES; REVERSE LOGISTICS; SOCIAL-RESPONSIBILITY; CONCEPTUAL-FRAMEWORK; MEASUREMENT SYSTEMS; PRODUCT-RECOVERY; NETWORK; DEFINITIONS; METHODOLOGY; PROCUREMENT;
D O I
10.1016/j.jclepro.2014.08.005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The purpose of this study is to identify and analyze the metrics that have been published in the literature on green supply chain management (GSCM) and sustainable supply chain management (SSCM). The metrics Were identified based on a structured content analysis of 445 articles published up to the end of 2012. A total of 2555 unique metrics were identified. The majority of the metrics were used only once, which indicates a lack of agreement on how performance should be measured in these areas. Five metrics were used more than 20 times: quality (31 times), air emissions (28), greenhouse gas emissions (24), energy use (24), and energy consumption (21). As highlighted in that list, multiple metrics were used to measure similar issues in many cases. For example, a detailed analysis showed that 76 different metrics were identified for issues focusing on water. As a part of the analysis conducted, each metric was classified according to 13 key characteristics of SSCM drawn from the literature. The analysis showed that environmental issues were represented to the greatest extent. Over one-third of the identified metrics were classified as cross-cutting metrics, meaning that they addressed more than one key characteristic of SSCM. Based on the analysis conducted, an original conceptual framework for structuring the development of metrics in GSCM and SSCM is presented. This paper presents one of the first in-depth investigations of the use of metrics in GSCM and SSCM. It is anticipated that the analysis and framework will provide a strong basis for future academic and practitioner work. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:360 / 377
页数:18
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