已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Do the barriers of multi-tier sustainable supply chain interact? A multi-sector examination using resource-based theory and resource-dependence theory

业务 供应链 产业组织 意外事故 资源依赖理论 资源(消歧) 权变理论 持续性 环境经济学 营销 知识管理 微观经济学 经济 计算机科学 生物 语言学 哲学 计算机网络 生态学
作者
Pushpendu Chand,Pradeep Kumar Tarei
出处
期刊:Journal of Purchasing and Supply Management [Elsevier BV]
卷期号:27 (5): 100722-100722 被引量:14
标识
DOI:10.1016/j.pursup.2021.100722
摘要

In a geographically dispersed multi-tiered supply chain, managing sustainable practices throughout the entire upstream network is increasingly challenging for the lead firm. But often, it is the lead firm that is held responsible for the lack of non-sustainable practices by any of its suppliers in the network. This can potentially damage the reputation of the lead firm. Moreover, complex inter-relationship among multi-tier sustainable supply chain management (MSSCM) barriers tends to constrain the cascading of sustainability. Consequently, the strategies in overcoming the MSSCM barriers show limited impact. Thus, exploring the mutual interaction among MSSCM barriers is crucial as removing one barrier can intensify or diminish the effect of another barrier. This research unpacks the intra-firm, inter-firm, and contingency barriers for multi-tiered supplier network. A grey-based multi-criterion decision-making approach is adopted in establishing mutual relationships among MSSCM barriers. In addition, a combined resource-based theory and resource-dependence theory supports the theoretical anchoring. The MSSCM barriers are studied for supply networks which involve three lead firms, five tier-one suppliers, and ten lower-tier suppliers selected from automobile, beverage, and home appliances industries. The research provides a granularity of the MSSCM barriers’ by analysing the meaningful relationship at the individual tier-firm level and aggregated level.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
咪咪完成签到,获得积分10
刚刚
可爱的函函应助陈思思采纳,获得10
4秒前
4秒前
5秒前
科研通AI5应助英俊溪灵采纳,获得10
7秒前
7秒前
Libra发布了新的文献求助10
8秒前
飞逝的快乐时光完成签到 ,获得积分10
8秒前
10秒前
狂野傲南发布了新的文献求助10
12秒前
咪咪发布了新的文献求助10
12秒前
lixuerui完成签到,获得积分10
13秒前
17秒前
18秒前
21秒前
小北完成签到,获得积分10
21秒前
21秒前
21秒前
22秒前
杨然完成签到 ,获得积分10
22秒前
华仔应助syx采纳,获得10
22秒前
陈思思发布了新的文献求助10
23秒前
nobody完成签到 ,获得积分10
23秒前
wyr525完成签到,获得积分10
24秒前
Jia发布了新的文献求助10
24秒前
敏感草丛完成签到,获得积分20
25秒前
wyr525发布了新的文献求助10
26秒前
野性的小松鼠完成签到 ,获得积分10
27秒前
星辰大海应助Libra采纳,获得10
29秒前
沉静方盒发布了新的文献求助10
30秒前
英俊的铭应助科研通管家采纳,获得10
34秒前
大个应助科研通管家采纳,获得10
34秒前
小马甲应助科研通管家采纳,获得10
34秒前
丘比特应助科研通管家采纳,获得10
34秒前
34秒前
chunjuan应助科研通管家采纳,获得50
34秒前
ipcy完成签到,获得积分10
35秒前
所所应助正直的友容采纳,获得10
35秒前
SciGPT应助消失的岛屿采纳,获得10
35秒前
Jia完成签到,获得积分20
36秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Machine Learning Methods in Geoscience 1000
Resilience of a Nation: A History of the Military in Rwanda 888
Evaluating the Cardiometabolic Efficacy and Safety of Lipoprotein Lipase Pathway Targets in Combination With Approved Lipid-Lowering Targets: A Drug Target Mendelian Randomization Study 500
Crystal Nonlinear Optics: with SNLO examples (Second Edition) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3733275
求助须知:如何正确求助?哪些是违规求助? 3277475
关于积分的说明 10002708
捐赠科研通 2993338
什么是DOI,文献DOI怎么找? 1642645
邀请新用户注册赠送积分活动 780574
科研通“疑难数据库(出版商)”最低求助积分说明 748892