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نتیجه جستجو - Supply chain risk

تعداد مقالات یافته شده: 31
ردیف عنوان نوع
1 Wood supply chain risks and risk mitigation strategies: A systematic review focusing on the Northern hemisphere
خطرات زنجیره تامین چوب و استراتژی های کاهش خطر: یک مرور سیستماتیک با تمرکز بر نیمکره شمالی-2021
This paper presents a systematic literature review on both the risks affecting wood supply security and risk mitigation strategies by quantitative and qualitative data analysis. It describes wood-specific supply chain risks, thereupon resulting impacts and counteracting strategies to ensure supply. Risks, impacts, and strategies are documented as basis for a comparative analysis, discussion of results, challenges and research gaps. Finally, the suitability and the limitations of the chosen methodology and the achieved results are discussed. Scanning wood supply chain risks and supply strategies, most of the reviewed papers focus on wood supply for bioenergy generation and only a few studies investigate wood supply chain risk issues for the sawing, wood panel, pulp and paper industries, or biorefineries.This review differs significantly from other reviews in this field as it considers the entire wood value chain including recent studies on new chemical wood-based products and thus provides a more complete picture of the wood-based bioeconomy. Consequently, it contributes to the literature by providing an overarching investigation of the risks affecting wood supply security and possible side effects of a growing wood-based bioeconomy. It was found that comprehensive value chain analyses considering established wood products, large-volume bioenergy products, as well as established and new chemical wood-based products in the context of wood supply security are missing. Studies that map the entire wood value chain with its multilevel interdependences and integrating cascading use of wood are lacking.
Keywords: Wood supply | Wood supply chain risk | Supply risk mitigation | Wood supply strategy | Wood-based bioeconomy
مقاله انگلیسی
2 Beware suppliers bearing gifts!: Analysing coverage of supply chain cyber security in critical national infrastructure sectorial and cross-sectorial frameworks
مراقب تأمین کنندگان هدیه باشید!: تجزیه و تحلیل پوشش امنیت سایبری زنجیره تامین در زیرساخت های مهم ملی بخش های بخشی و بین بخشی-2021
Threat actors are increasingly targeting extended supply chains and abusing client-supplier trust to conduct third-party compromise. Governments are concerned about targeted attacks against critical national infrastructures, where compromise can have significant adverse national consequences. In this paper we identify and review advice and guidance offered by authorities in the UK, US, and the EU regarding Cyber Supply Chain Risk Management (C-SCRM). We then conduct a review of sector specific guidance in the three regions for the chemical, energy, and water sectors. We assessed frameworks that each region’s sector offered organisations for C-SCRM suitability. Our results found a range of interpretations for “Supply Chain” that resulted in a diversity in the quantity and quality of advice offered by regional authorities, sectors, and their frameworks. This is exacerbated by the lack of a common taxonomy to support supply chain procurement and risk management that has led to limited coverage in most C-SCRM programs. Our results highlight the need for a taxonomy regarding C-SCRM and systematic guidance (both general and sector specific) to enable controls to be deployed to mitigate against supply chain risk. We provide an outline taxonomy based on our data analysis to promote further discussion and research.
Keywords: Cyber security | Supply chain | Risk management | Critical national infrastructure | Common taxonomy
مقاله انگلیسی
3 Evaluation on risks of sustainable supply chain based on optimized BP neural networks in fresh grape industry
ارزیابی خطرات زنجیره تأمین پایدار بر اساس شبکه های عصبی بهینه شده BP در صنعت انگور تازه-2021
In order to improve the risk evaluation and management in fresh grape supply chain and enhance the sustainable level of the supply chain, this study applied neural network to evaluate the risk of fresh grape supply chain from the perspective of sustainable development. Firstly, the possible risk factors in the supply chain were identified and the risk evaluation index system were proposed; then risk evaluation models based on single BP and optimized BP (GABP and PSO-BP) neural network were established; and then the models were trained, tested and evaluated using data set from supply chain survey. The survey and analysis results showed that the risk of fresh grape supply chain was at a low level but the risk in each link was discrepant, the biggest risk was the risks among the links in the chain (R0), and the high risk dimensions were the economic risk, social risk and cooperation risk; most risky events were located in the second quadrant (small probability & high damage risk events). The results of models training and testing indicated that the optimized model was superior to single BP neural network for risk assessment in grape sustainable supply chain, and the PSO-BP model was more accurate and suitable with less evaluation errors and a bigger R2. The results also extracted the risk factors that contributed most to the overall risk of grape sustainable supply chain. This paper enriches the method of supply chain risk assessment theoretically, and provides practical suggestions for risk prevention, stable operation and sustainability improvement of fresh grape supply chain.
Keywords: Sustainable supply chain | Supply chain risk | GA-BP neural network | PSO-BP neural network | Risk evaluation
مقاله انگلیسی
4 Improving supply chain resilience through industry 4:0: A systematic literature review under the impressions of the COVID-19 pandemic
بهبود انعطاف پذیری زنجیره تأمین از طریق صنعت 4:0: بررسی ادبیات سیستماتیک تحت تأثیر همه گیری COVID-19-2021
The COVID-19 pandemic is one of the most severe supply chain disruptions in history and has challenged practitioners and scholars to improve the resilience of supply chains. Recent technological progress, especially industry 4.0, indicates promising possibilities to mitigate supply chain risks such as the COVID-19 pandemic. However, the literature lacks a comprehensive analysis of the link between industry 4.0 and supply chain resilience. To close this research gap, we present evidence from a systematic literature review, including 62 papers from high-quality journals. Based on a categorization of industry 4.0 enabler technologies and supply chain resilience antecedents, we introduce a holistic framework depicting the relationship between both areas while exploring the current state-of-the-art. To verify industry 4.0’s resilience opportunities in a severe supply chain disruption, we apply our framework to a use case, the COVID-19-affected automotive industry. Overall, our results reveal that big data analytics is particularly suitable for improving supply chain resilience, while other industry 4.0 enabler technologies, including additive manufacturing and cyber-physical systems, still lack proof of effectiveness. Moreover, we demonstrate that visibility and velocity are the resilience antecedents that benefit most from industry 4.0 implementation. We also establish that industry 4.0 holistically supports pre-disruption resilience measures, enabling more effective proactive risk management. Both research and practice can benefit from this study. While scholars may analyze resilience potentials of under-explored enabler technologies, practitioners can use our findings to guide industry 4.0 investment decisions.
Keywords: Industry 4.0 | Supply chain risk management | Supply chain resilience | Supply chain disruption | Digital supply chain | Literature review
مقاله انگلیسی
5 Information transmission along supply chains: Stock price reaction of suppliers upon a customers release of qualitative risk information
انتقال اطلاعات در طول زنجیره های تأمین: واکنش قیمت سهام تأمین کنندگان پس از انتشار اطلاعات ریسک کیفی توسط مشتری-2021
We examine suppliers’ stock price reaction to the disclosure of qualitative risk information from important customers. By leveraging recent advances in textual analysis, we quantify customers’ qualitative information disclosure and use it to gauge the spontaneous stock price reaction of the supplier’s stock. Using a sample of 2028 customer-supplier-firm observations in China, we find that, on average, the stock price of a supplier negatively reacts to its customer’s qualitative risk information disclosure. Our findings are robust to alternative metric of qualitative risk disclosure, alternative metric of stock price reaction, after accounting for customer stock returns, and after mitigating selection bias. Moreover, when comparing the magnitudes of coefficients, we find the impact of the qualitative risk information disclosure on suppliers’ stock price is larger than the firm, industry, and macroeconomic information embedded in the same annual report; its value is also greater than the impact of a customer’s negative stock price. Last, we show that the adverse impact of customers’ qualitative risk information disclosure is more salient if the customers are relatively important or the information is more useful to investors. We discuss implications of our findings to supply chain risk management.
Keywords: Qualitative risk information | Supply chain | Stock price reaction
مقاله انگلیسی
6 Risk assessment of agricultural supermarket supply chain in big data environment
ارزیابی ریسک زنجیره تأمین سوپرمارکت های کشاورزی در محیط داده های کلان-2020
Article history:Received 20 November 2019Received in revised form 30 June 2020 Accepted 14 July 2020Available online 16 July 2020Keywords:Big dataAgricultural super-docking Supply chainRisk analysisWith the application of big data in all walks of life, big data thinking is effectively improving the cir- culation efficiency of agricultural products supply chain by driving management changes in business decision-making and f¨armer-supermarket dockinga¨ s an innovative mode of agricultural products circu- lation. Based on the current situation of China’s agricultural supermarket supply chain development, this paper makes an in-depth study on the supply chain risk of agricultural products of large retail enterprises under the mode of a¨ gricultural supermarket docking¨, and then introduces the agricultural supermarket docking supply chain under the big data environment. This paper uses big data to analyze the risks that may arise in the supply chain of a¨ gricultural supermarket docking¨in large retail enterprises. This paper from the aspects of production, processing, distribution, retail and consumption, introduces the new risks of agricultural supermarket supply chain after introducing big data. Secondly, Qualitative analysis and quantitative calculation are combined to conduct risk assessment. Through empirical analysis, the ranking of all risk factors is obtained, and the relevant fuzzy evaluation grade and risk evaluation criteria are given. Through expert evaluation, a new risk ranking is also obtained, which is not much different from the results of empirical analysis, and the empirical results are also verified. Therefore, develop this study is helpful to prevent the risk of agricultural supermarket supply chain connection. At the same time, the information integration, sharing and feedback of the big database provide a new idea for the optimization of the supply chain connecting agricultural production.it also has reference significance for other supply chain risk management.© 2020 Elsevier Inc. All rights reserved.
Keywords: Big data | Agricultural super-docking | Supply chain | Risk analysis
مقاله انگلیسی
7 Supply chain risk management considering put options and service level constraints
مدیریت ریسک زنجیره تأمین با توجه به گزینه ها و محدودیت های سطح خدمات-2020
This paper considers a supply chain composed of a supplier and a retailer who commits to a service level to make end-users happy and promote sales. To reduce the losses resulting from the high demand volatility, the retailer purchases put options from the supplier to adjust its initial order. The optimal ordering and production policies with and without put options under the service level constraint are derived. We find that, in the two cases, the expected profits of the retailer are non-increasing in the service level constraint while that of the supplier are non-decreasing in it. Model comparison reveals that with put options, the retailer will offer higher service level and earn more profit than without; such effect is more salient when the demand is more variable. However, the put option contract will not always benefit the supplier especially when the service constraint is high. We also find that put option contract can effectively improve the decentralized system’s performance, but this only happens when the service constraint is low. In addition, we find that put option contract have no better capability than wholesales price contract in coordinating the supply chain in the presence of a service level constraint.
Keywords: Risk management | Supply chain management | Put option contract | Service level constraints | Operations-finance-marketing interfaces
مقاله انگلیسی
8 A novel plithogenic TOPSIS- CRITIC model for sustainable supply chain risk management
یک مدل TOPISIS- انتقادی plithogenic جدید برای مدیریت ریسک پایدار زنجیره تأمین-2020
The trend of considering supply chain sustainability with an absence of attention to sustainability risks may disturb the business future. The role of risk management is concentrated in identifying and analyse the influence of loss to business, social and environment, get ready by coverage budget, and derive strategies to protect supply chain sustainability against these risks. Risk management assists the com- pany’s performance to be more confident in supply chain sustainability decisions. The extent of the risk is based on the organization’s magnitude, so the sustainable supply chain risk management strategies of large firms require to be more advanced. The purpose of this research is the estimation of sustainable supply chain risk management (SSCRM). The proposed methodology in this paper is a combination of plithogenic multi-criteria decision-making approach based on the Technique in Order of Preference by Similarity to Ideal Solution (TOPSIS) and Criteria Importance Through Inter-criteria Correlation (CRITIC) methods. In order to evaluate the proposed model, we present a real-world case study of the Tele- communications Equipment Company. The results show the importance of each criterion to evaluate SSCRM and the ranking of the three telecommunications equipment categories.© 2019 Elsevier Ltd. All rights reserved.
Keywords: Risk management | Supply chain sustainability | Plithogeny | TOPSIS | CRITIC
مقاله انگلیسی
9 Predicting supply chain risks using machine learning: The trade-off between performance and interpretability
پیش بینی ریسک های زنجیره تأمین با استفاده از یادگیری ماشین: مبادلات بین عملکرد و تفسیر-2019
Managing supply chain risks has received increased attention in recent years, aiming to shield supply chains from disruptions by predicting their occurrence and mitigating their adverse effects. At the same time, the resurgence of Artificial Intelligence (AI) has led to the investigation of machine learning techniques and their applicability in supply chain risk management. However, most works focus on prediction performance and neglect the importance of interpretability so that results can be understood by supply chain practitioners, helping them make decisions that can mitigate or prevent risks from occurring. In this work, we first propose a supply chain risk prediction framework using data-driven AI techniques and relying on the synergy between AI and supply chain experts. We then explore the trade-off between prediction performance and interpretability by implementing and applying the framework on the case of predicting delivery delays in a real-world multi-tier manufacturing supply chain. Experiment results show that prioritising interpretability over performance may require a level of compromise, especially with regard to average precision scores.
Keywords: Supply chain risk management | Risk analysis | Risk prediction | Machine learning | Interpretability
مقاله انگلیسی
10 The moderating impact of supply network topology on the effectiveness of risk management
تاثیر واسطه ای مکان شبکه تامین روی سودمندی مدیریت خطر-2018
While supply chain risk management offers a rich toolset for dealing with risk at the dyadic level, less attention has been given to the effectiveness of risk management in complex supply networks. We bridge this gap by building an agent based model to explore the relationship between topological characteristics of complex supply networks and their ability to recover through inventory mitigation and contingent rerouting. We simulate upstream supply networks, where each agent represents a supplier. Suppliers connectivity patterns are generated through random and preferential attachment models. Each supplier manages its inventory using an anchor-and-adjust ordering policy. We then randomly disrupt suppliers and observe how different topologies recover when risk management strategies are applied. Our results show that topology has a moderating effect on the effectiveness of risk management strategies. Scale-free supply networks generate lower costs, have higher fill-rates, and need less inventory to recover when exposed to random disruptions than random networks. Random networks need significantly more inventory distributed across the network to achieve the same fill rates as scale-free networks. Inventory mitigation improves fill-rate more than contingent rerouting regardless of network topology. Contingent rerouting is not effective for scale-free networks due to the low number of alternative suppliers, particularly for short-lasting disruptions. We also find that applying inventory mitigation to the most disrupted suppliers is only effective when the network is exposed to frequent disruptions; and not cost effective otherwise. Our work contributes to the emerging field of research on the relationship between complex supply network topology and resilience.
keywords: Supply chain risk management |Complex supply networks |Random networks |Scale-free networks |Inventory mitigation |Contingent rerouting |Agent-based modelling
مقاله انگلیسی
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