{"title":"供应网络演化及其拓扑结构如何影响供应链绩效?","authors":"P. Orenstein","doi":"10.1109/SMRLO.2016.98","DOIUrl":null,"url":null,"abstract":"The idea of this research is to explore the evolution of a supply chain using an empirical approach. This can be achieved by harnessing the power of Bloomberg data with network visualization software. Such an investigation will help identify supply chain archetypes as well as lead to an understanding of how these supply chains might change over time. Coupled with additional secondary data sources, we could learn more about how these changes might be impacted by, and impact, firm performance. In this paper, we explore a number of supply networks and develop their associated supply chain maps. We use key metrics from social network analysis to quantify the nature of these networks and understand how they evolve. This empirical data is then used to create a paradigm which explains the structure of these supply networks. We use the maps and the metrics developed to describe them to draw preliminary conclusions about how supply network topology impacts its performance.","PeriodicalId":254910,"journal":{"name":"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)","volume":"76 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"How Does Supply Network Evolution and Its Topological Structure Impact Supply Chain Performance?\",\"authors\":\"P. Orenstein\",\"doi\":\"10.1109/SMRLO.2016.98\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The idea of this research is to explore the evolution of a supply chain using an empirical approach. This can be achieved by harnessing the power of Bloomberg data with network visualization software. Such an investigation will help identify supply chain archetypes as well as lead to an understanding of how these supply chains might change over time. Coupled with additional secondary data sources, we could learn more about how these changes might be impacted by, and impact, firm performance. In this paper, we explore a number of supply networks and develop their associated supply chain maps. We use key metrics from social network analysis to quantify the nature of these networks and understand how they evolve. This empirical data is then used to create a paradigm which explains the structure of these supply networks. We use the maps and the metrics developed to describe them to draw preliminary conclusions about how supply network topology impacts its performance.\",\"PeriodicalId\":254910,\"journal\":{\"name\":\"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)\",\"volume\":\"76 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMRLO.2016.98\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMRLO.2016.98","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

摘要

本研究的想法是利用实证方法探索供应链的演变。这可以通过利用彭博数据和网络可视化软件的力量来实现。这样的调查将有助于确定供应链原型,并导致对这些供应链如何随时间变化的理解。再加上额外的辅助数据源,我们可以更多地了解这些变化如何受到公司绩效的影响。在本文中,我们探索了一些供应网络,并开发了相关的供应链图。我们使用社交网络分析的关键指标来量化这些网络的性质,并了解它们是如何演变的。然后使用这些经验数据来创建解释这些供应网络结构的范式。我们使用地图和开发的指标来描述它们,以得出关于供应网络拓扑如何影响其性能的初步结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
How Does Supply Network Evolution and Its Topological Structure Impact Supply Chain Performance?
The idea of this research is to explore the evolution of a supply chain using an empirical approach. This can be achieved by harnessing the power of Bloomberg data with network visualization software. Such an investigation will help identify supply chain archetypes as well as lead to an understanding of how these supply chains might change over time. Coupled with additional secondary data sources, we could learn more about how these changes might be impacted by, and impact, firm performance. In this paper, we explore a number of supply networks and develop their associated supply chain maps. We use key metrics from social network analysis to quantify the nature of these networks and understand how they evolve. This empirical data is then used to create a paradigm which explains the structure of these supply networks. We use the maps and the metrics developed to describe them to draw preliminary conclusions about how supply network topology impacts its performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Health - Promoting Nature of the Urban Space Stochastic Analysis of Systems Exposed to Very Unlikely Faults In Memory of Professor Igor Ushakov: In Memory of Our Colleague and Friend Holistic Approach to Passenger Terminal Risk Estimation Effective Bandwidth Estimation in Highly Reliable Regenerative Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1