Using vulnerability performance indicators to attain food supply chain robustness

High effectiveness and leanness of modern supply chains (SCs) increase their vulnerability, i.e. susceptibility to disturbances reflected in non-robust SC performances. Both the SC management literature and SC professionals indicate the need for the development of SC vulnerability assessment tools. In this article, a new method for vulnerability assessment, the VULA method, is presented. The VULA method helps to identify how much a company would underperform on a specific Key Performance Indicator in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision about whether process redesign is appropriate and what kind of redesign strategies should be used in order to increase the SC's robustness. The applicability of the VULA method is demonstrated in the context of a meat SC using discrete-event simulation to conduct the performance analysis.     

Green supply chain management practices in India: an empirical study

This paper presents an empirical study of green supply chain management (GSCM) practices in the Micro, small and medium enterprises (MSMEs) in India. Although the research in the area of GSCM has grown in recent times, the literature has yet to furnish an accepted explanation for why green practices are to be manifested in supply chain management given external and internal pressures. These MSMEs have been involved in such green supply chain practices only to the extent of their participation as suppliers, distributors and in other capacities as business partners. This study confirms and validates that Indian MSMEs face significant pressures from external stakeholders to adopt GSCM practices. Among internal pressures, on-the-job training forces MSMEs in India to adopt GSCM practices. It has been also established that external pressures and adoption of GSCM are fully mediated by internal pressures.     

Evaluation of the green supply chain management practices: a fuzzy ANP approach

Environmentally responsible manufacturing, green supply chain management (GSCM), and related principles have become important strategies for companies to achieve profit and gain market share by lowering their environmental impacts and increasing their efficiency. As environment has become a key strategic consideration in supply chains, this study examines the components and elements of GSCM and suggests a novel GSCM evaluation framework. It also provides a real-case study of Ford Otosan, one of the pioneering companies about environmental subjects in Turkey, to illustrate the industrial application of our theoretical assessment model. The identified components are integrated into a strategic assessment and evaluation tool using analytical network process (ANP). The dynamic characteristics and complexity of the GSCM analysis environment make the ANP technique a suitable tool for this study. Moreover, to cope with ambiguity and vagueness of the decision maker's evaluations, the fuzzy extension of the ANP method is preferred.     

An integrated modelling approach for raw material management in a steel mill

An integrated modelling approach combining optimisation models with simulation is proposed for coordinated raw material management at steel works throughout the whole supply chain management process. The integrated model is composed of three components: ship scheduling, yard operation simulation and material blending models. The ship scheduling model determines which brands, how much and when they should be arrived, and the problem is modelled as mixed integer linear programming. The simulation model is used to simulate the whole processes from ships’ arrivals to the retrieval of the materials through the berthing and unloading the raw materials. Finally, the raw material blending model is developed for determining the brand and quantity of raw materials to be used. The proposed integrated modelling approach for raw material management has been successfully implemented and applied at steelwork to provide shipping schedules and predict future inventory levels at stock yards. By coordinating all the activities throughout the entire raw material supply chain management process, this article proposes an integrated approach to the problem and suggests a guideline by the appropriate simplification. The quantitative nature of the optimisation model and simulation facilitates an assessment of the risk factors in the supply chain, leading to an evaluation of a wide variety of scenarios and the development of multiple contingency plans. Further research is expected to supplement the ship scheduling models with heuristics for the idiosyncratic constraints of maritime transportation.     

Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands

This article considers the inventory management problem in a supply chain with uncertain replenishment lead-times and uncertain demands. The optimal integrated inventory management (IIM) policy is developed using stochastic dynamic programming theory. The IIM policy is contrasted with two pull-type vendor-managed inventory policies (VMI-1 and VMI-2) and a traditional retailer-managed inventory policy (RMI). Computational results show that in such stochastic supply chains, IIM performs about 23, 15, and 3% better than the optimised RMI, VMI-1 and VMI-2 policies, respectively, while two VMI policies are about 8 and 20% better than the best RMI. The basestock-based VMI-2 is a very good form of VMI. The ANOVA analysis reveals that the replenishment lead-times have the largest effect on the relative performance between IIM and other policies. Numerical examples demonstrated that the IIM policy has good structural properties and can be characterised by a set of switching curves.     

Market Impact on IT Security Spending

Traditionally, IT security investment decisions are made in isolation. However, as firms that compete for customers in an industry are closely interlinked, a macro perspective is needed in analyzing these decisions. We utilize the notions of direct‐ and cross‐risk elasticity to describe the customer response to adverse IT security events in the firm and competitor, respectively, thus allowing us to analyze optimal security investment decisions. Examining both symmetric and asymmetric duopoly cases using a continuous‐time Markov chain (CTMC) model, we demonstrate that optimal IT security spending, expected firm profits and willingness of firms to cooperate on security improvements are highly dependent on the nature of customer response to adverse events. We also examine the investment problem when security attacks on different firms are correlated.     

考虑鉴真服务和消费者偏好的混合E-供应链决策研究

鉴真服务平台通过提供鉴真服务,为线上商品的出售提供了质量保障,切实提高了消费满意度,降低了线上产品退货率。对此,本文构建了由鉴真服务E-供应链和传统E-供应链组成的混合E-供应链系统;运用Stackelberg博弈,求解集中式和分散式决策下的最优定价策略及利润;分析鉴真努力程度对各模型运作的影响,并对不同模型的最优决策进行比较;最后通过数值分析,对模型结论进行验证。研究表明：1)无论是集中式决策还是分散式决策,两个渠道的产品销售价格均随鉴真努力程度的增大而增加,而混合E-供应链总利润随鉴真努力程度的增大先减小后增大;2)分散式决策模式中,鉴真渠道的产品销售价格在销售商主导模型下更高,而销售商总利润和鉴真平台利润在鉴真平台主导模型下更高,且鉴真平台所获取的佣金及鉴真平台的利润均随鉴真努力程度的增大而增加,销售商总利润随鉴真努力程度的增加先减小后增大;3)集中式决策模式中混合E-供应链的总利润最高,且此时主要利润为销售商所得。本文的研究进一步丰富和发展了混合E-供应链决策理论,而且为鉴真服务平台和线上销售商的经营决策提供参考。     

智联产品服务供应链研发运维多阶段联合优化与协调

在智联化和服务化背景下,智能产品服务系统成为制造企业转型升级的重要方向。产品的“智能”和“互联”特性给供应链中的产品和服务都带来了新的变化。考虑产品的“智能”和“互联”对产品、服务的需求和成本的影响,构建了供应链两阶段动态博弈模型。刻画了分散决策和集中决策下供应链的最优运作行为,基于产品收益和服务收益提出了“双元收益共享”的供应链协调机制。通过算例分析,探讨了“服务化”、“智能互联”与“双元收益共享”契约对供应链利润的影响。研究表明,智联产品供应链中融入智能服务,不总是能增加供应链利润,存在“服务化悖论”;当产品智联化后,智能互联特性加强了产品与服务的融合,使供应链各方的利润都有较大提高;“双元收益共享”契约不仅能实现供应链Pareto改进,还能提高消费者剩余。     

政府奖励机制下闭环供应链的利他关切性决策

考虑政府奖励机制的影响,文章对闭环供应链中的利他关切性决策进行研究。文章首先构建了制造商是否利他关切的两种分散决策和集中决策模型,并求解给出最优回收决策和政府最优奖励决策;然后,对各模型的最优决策进行比较分析,讨论制造商的利他关切对决策的影响。在此基础上,设计“数量折扣联合固定费用-成本共担”契约,对闭环供应链系统进行协调。最后,通过数值算例验证模型结论。研究表明：(1)政府奖励强度的设置存在阈值。只有当奖励强度大于阈值时,奖励机制才有效,才能促进废旧品的回收。(2)制造商的利他关切行为有利于系统获利,但不利于制造商利润的增长,但是这种利他行为扩大了制造商和零售商的谈判空间,有利于协调机制的实施;(3)政府最优奖励强度与WEEE回收价格和价格敏感系数正相关,与利他系数正相关。并且,政府奖励强度的增加有利于“数量折扣联合固定费用-成本共担”契约协调机制的达成。     

基于工序异质性的关键链项目缓冲监控

通过关键链项目缓冲监控可以防止缓冲在项目执行阶段被浪费,并保证项目的工期,有效的监控方法有利于提升项目的整体绩效。为了克服统一缓冲监控方法的不足,在保证项目工期的基础上,本文考虑成本因素对项目的影响,提出了一种基于工序成本和工期敏感度的差别动态缓冲监控模型。该模型考虑工序异质性将工序划分为成本敏感型工序和工期敏感型工序,根据工序的综合感知效用进行缓冲监控分配,并结合敏感度对不同类型的工序设置不同的监控基准点和纠偏措施。仿真结果表明,差别监控相对于统一的监控模式有利于实现项目工期和成本的双优化,验证了本文方法的有效性。