مقاله انگلیسی رایگان در مورد بررسی تاب آوری شبکه زنجیره تامین در حضور اثر فزونگر – الزویر ۲۰۲۰

elsevier

 

مشخصات مقاله
ترجمه عنوان مقاله بررسی تاب آوری شبکه زنجیره تامین در حضور اثر فزونگر
عنوان انگلیسی مقاله Exploring supply chain network resilience in the presence of the ripple effect
انتشار مقاله سال ۲۰۲۰
تعداد صفحات مقاله انگلیسی ۴۳ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۶٫۳۴۴ در سال ۲۰۱۹
شاخص H_index ۱۵۵ در سال ۲۰۲۰
شاخص SJR ۲٫۴۷۵ در سال ۲۰۱۹
شناسه ISSN ۰۹۲۵-۵۲۷۳
شاخص Quartile (چارک) Q1 در سال ۲۰۱۹
مدل مفهومی دارد
پرسشنامه ندارد
متغیر دارد
رفرنس دارد
رشته های مرتبط اقتصاد، مهندسی صنایع، مدیریت
گرایش های مرتبط لجستیک و زنجیره تامین، اقتصادسنجی، توسعه اقتصادی و برنامه ریزی، برنامه ریزی و تحلیل سیستم ها، مدیریت عملکرد، مهندسی مالی و ریسک
نوع ارائه مقاله
ژورنال
مجله  مجله بین المللی اقتصاد تولید – International Journal Of Production Economics
دانشگاه Dept. of Information Technology and Decision Sciences, Old Dominion University, Norfolk, VA, 23529, United States
کلمات کلیدی انعطاف پذیری شبکه زنجیره تأمین، گسترش ریسک، ساختار شبکه، ظرفیت ریسک نود
کلمات کلیدی انگلیسی Supply chain network resilience، Risk propagation، Network structure، Node risk capacity
شناسه دیجیتال – doi
https://doi.org/10.1016/j.ijpe.2020.107693
کد محصول E14744
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
دانلود رایگان مقاله دانلود رایگان مقاله انگلیسی
سفارش ترجمه این مقاله سفارش ترجمه این مقاله

 

فهرست مطالب مقاله:
Abstract

۱- Introduction

۲- Literature review

۳- SCNR framework

۴- Network resilience analysis

۵- Implications

۶- Conclusion

References

بخشی از متن مقاله:

Abstract

This study aims to investigate overall supply chain network resilience (SCNR) in the presence of ripple effect, or risk propagation, i.e. the phenomenon that disruptions at a few firms in a supply chain network (SCN) can spread to their neighboring firms, then eventually spread to other firms in the SCN. We begin by developing a multi-dimensional quantitative framework to measure SCNR, which includes three resilience dimensions based on three different network performance indicators. Given this framework, we then systematically explore the determining factors of SCNR and present a comprehensive analysis of how network structure and node risk capacity influence different aspects of SCNR. Our results clearly indicate the following important implications for managers. First, the influence of network type on SCNR tends to be more significant in the short-term than it is in the longer-term, given the ripple effect. Second, SCNR can be improved more effectively by enhancing node risk capacity than by adjusting network structure. Third, tradeoffs exist between the robustness of the network against a disruption and its ability to recover from that disruption. Fourth, different network performance indicators can provide different perspectives on SCNR. Together these help show that the multi-dimensional framework enables a better characterization of the complexity of SCNR, and thus that it provides support for more informed managerial decision-making about investing in improving resilience. The paper concludes the discussion by addressing opportunities for further extending the research effort.

Introduction

Modern supply chains are complex networks that are exposed to supply chain disruptions, which are operational shutdowns directly or indirectly caused by various risks such as natural disasters, political and economic factors, labor strikes, and material shortages (Bode and Wagner 2015; Craighead et al. 2007; Scheibe and Blackhurst 2017). A supply chain network (SCN) is vulnerable to disruptions not only because of the direct impacts of those disruptions, but also because of the ripple effect (also known as risk propagation) – the phenomenon that a sudden disruption at a few nodes in a SCN can spread to neighboring nodes, and eventually adversely impact other firms (Dolgui, Ivanov, and Sokolov 2018; 2 Scheibe and Blackhurst 2017; Li et al. 2019). The consequence of what is initially a local disruption can thus be substantial and long-lasting. As an example of this behavior, the hard disk drive (HDD) manufacturer Western Digital, which has a number of local factories in Thailand, suffered a 50% slump in HDD sales in the last quarter of 2011 because of major flooding in that country. These losses then affected a number of other firms within its extended supply chain. One of these firms was Hewlett Packard, a customer of Western Digital, which subsequently reported a 7% drop in revenues and blamed the HDD shortage for more than half of this decline (HP 2011). Intel, a supplier for HP, also posted a decrease in 4th Quarter revenues of $346 million as a result of lower demand following the flood (Intel 2011). Such results are common, as indicated by a recent study showing that 42% of supply chain disruptions originate below the tier one suppliers (Business Continuity Institute 2013).

ارسال دیدگاه

نشانی ایمیل شما منتشر نخواهد شد. بخش‌های موردنیاز علامت‌گذاری شده‌اند *