Supply chain risk management – I: Conceptualization, framework and planning process

Supply chain risk management (SCRM) is an interdisciplinary emerging area of research crossing over operations management, finance and marketing, among other disciplines. Conceptualization of SCRM is argued in reference to previous studies on risk identification, risk assessment, supply chain vulnerabilities and risk management approaches used. A SCRM framework is then developed based on taxonomies defined for risk events and risk management approaches. In line with this framework, a risk management planning process is proposed with an illustrative example

Supply chain risk management – II: A review of operational, financial and integrated approaches

This article is a sequel to Bandaly et al. (2011). Structured around the supply chain risk management (SCRM) typology and framework presented in the aforementioned article, this article provides a review on individual operational and financial risk management approaches reported in the literature. Avoidance, prevention and mitigation approaches reported are also summarized in tabular format for the four risk domains covered (internal operations, external stakeholders, marketplace and environment). Distinctions between operational and financial approaches are highlighted. A review of studies integrating both approaches is then presented. Areas for future research in SCRM are argued

International Journal of Production Research Integrated supply chain risk management via operational methods and financial instruments Integrated supply chain risk management via operational methods and financial instruments

Supply chain risk management (SCRM) is an emerging field that generally lacks integrative approaches across different disciplines. This study contributes to narrowing this gap by developing an integrated approach to SCRM using operational methods and financial instruments. We study a supply chain composed of an aluminium can supplier, a brewery and a distributor. The supply chain is exposed to aluminium price fluctuation and beer demand uncertainty. A stochastic optimisation model is developed for managing operational and financial risks along the supply chain. Using this model as a base, we compare the performance of an integrated risk management model (under which operational and financial risk management decisions are made simultaneously) to a sequential model (under which the financial risk management decisions are made after the operational risk management decisions are finalised). Through simulation-based optimisation and using experimental designs and statistical analyses, we analyse the performance of the two models in minimising the expected total opportunity cost of the supply chain. We examine the supply chain performance as a function of three factors, each at three levels: risk aversion, demand variability and aluminium price volatility. We find that the integrated model outperforms the sequential model in most but not in all cases. Furthermore, while the results indicate that the supply chain improves its performance by being less risk averse, there exists a threshold beyond which accepting a higher risk level is not justified. Managerial insights are provided for various business scenarios experimented with. Keywords: risk management; supply chain; finance; inventory; integrated methods; optimisation via simulation Introduction Risk management provides an important arena to visualise and understand the true nature of supply chain management and its interdisciplinary context. As corporate risk management spans several disciplines such as procurement, finance, operations and marketing, the approaches used to manage risks along a supply chain also need to be interdisciplinary. As reported in a survey by , the literature is short on studies using interdisciplinary and integrated approaches to supply chain risk management (SCRM). This article contributes to research on SCRM by examining an integrated approach to risk management using operational and financial risk management methods. The application venue considered is the beer industry with three members along its supply chain: an aluminium can supplier, a brewery and a beer distributor. Faced with beer demand uncertainty and volatile aluminium prices, a simulation-based optimisation model is developed which incorporates both operational and financial risk management methods. The operational risk management method exploits the timing and sizes of aluminium sheet procurements, as well as the inventory levels of raw material, work in process and finished goods maintained at all three supply chain members. The financial risk management method focuses on the optimal purchase of call, and put options on aluminium futures to manage aluminium price uncertainty and the uncertainty in aluminium demand. The optimisation model developed minimises the expected total opportunity cost of the supply chain over an eight-week peak demand period

Integrated Transportation - Inventory Models: A Review

As decision-making practices in industry shift from isolated, unilateral department decisions to multiparty supply chain planning, integrated modelling techniques have risen in popularity. Models that simultaneously address transportation and inventory decisions have been of particular interest. This article reviews Integrated Transportation-Inventory (ITI) models developed over the last two decades for various supply chain configurations. Recurring topics in such models are discussed and those growing in popularity are identified. Features and constraints inherent in ITI models are categorized and analysed. Finally, research gaps are highlighted with a focus on further aligning academic interests with current and emerging industry practices

BATI ANADOLU'DAKİ TERSİYER VE KUVATERNER YAŞLI VOLKANİK KAYAÇLARDA YENİ YAPILAN RADYOMETRİK YAŞ ÖLÇÜMLERİNİN YORUMU

Batı Anadolu'da geniş alanlarda yüzlekler veren ve çeşitli evrelerde meydana gelen Tersiyer ve Kuvaterner yaşlı volkanik kayaçlardan 17 örnek alınarak yaş problemlerine açıklık getirmek için K/Ar ve Rb/Sr yöntemleri ile radyometrik yaş ölçümleri yapılmış ve volkanizmanın bölgesel yorumlanmasına katkı sağlayacak jeokimyasal veriler elde edilmiştir. Ölçülen en eski yaş 18,0 ± 0,2 milyon yıl olarak andezit türde ve kalkalkalen nitelikli Selendi volkanitlerine, en yeni yaş ise 100.000-200.000 yıl ile alkali nitelikli bazaltik Kula volkanitlerine aittir