Stages of Supply Chain Disruption Response: Direct,Constraining, and Mediating Factors for Impact Mitigation

It is well established that supply chain disruptions can have a severe negative impact on firms and general wisdom suggests that this impact can be mitigated by quick responses. Aside from a few anecdotes, however, little is known about the decision‐making process that leads to speedy responses and about its impeding and supporting antecedents. Using the organizational information‐processing perspective, this empirical study unravels the disruption management process along a sequence of four stages—disruption recognition, disruption diagnosis, response development, and response implementation—and hypothesizes constraining and mediating effects of these stages. The findings contribute to an improved understanding of the role that the decision stages play in mitigating supply chain disruptions, and confirm the prediction that the speed with which information is processed and the stages are worked through positively affects supply chain performance. In addition, the findings suggest that one of the stages, diagnosis, acts as a constraining factor to the other stages. The stages also play a mediating role between the impact that the disruption has and a firm's readiness (prior to a disruption), dependence on a key supplier, and supply chain complexity. This provides guidance to decision makers in the application of resources both prior to a negative event and during a disruption recovery.     

Keep Your Friends Close? Supply Chain Design and Disruption Risk

In this article, we evaluate the relationship between supply chain design decisions and supply chain disruption risk. We explore two supply chain design strategies: (i) the dispersion of supply chain partners to reduce supply chain disruption risk versus (ii) the co‐location of supply chain partners to reduce supply chain disruption risk. In addition, we assess supply chain disruption risk from three perspectives: the inbound material flow from the supplier (supply side), the internal production processes (internal), and the outbound material flow to the customer (customer side) as a disruption can occur at any of these locations. We measure disruption risk in terms of stoppages in flows, reductions in flow, close calls (disruptions that were prevented at the last minute), disruption duration (time until normal operation flow was restored), and the spread of disruptions all the way through the supply chain. We use seemingly unrelated regression (SUR) to analyze our data, finding that lead times, especially supply side lead times, are significantly associated with higher levels of supply chain disruption risk. We find co‐location with suppliers appears to have beneficial effects to the reduction of disruption duration, and, overall supply side factors have a higher impact when it comes to supply chain disruption risk than comparable customer side factors.     

Older adults' narratives about a flood disaster: Resilience, coherence, and personal identity

Older adults are a vulnerable group in a disaster and are more at risk of adverse effects as a result. This paper draws on the use of narrative theory in health and gerontology studies to examine how a disruptive disaster was storied. Narrative interviews were conducted with nine older adults aged over 65 years who had recently experienced a flood disaster. The participants' narratives about the disruptive event were integrated with past personal events that spanned more than seven decades. The disaster became a reference point for previous challenging experiences, which created biographical continuity, coherence and order over time. Furthermore, the disaster stories were about biography and identity, and showed how older adults made sense of the flood from a life-course perspective. The use of narrative approaches provides an insight into how the flood disaster was experienced, and reveals how four older adults storied their experiences of a significant life challenge.     

Selection of resilient supply portfolio under disruption risks

This paper deals with the optimal selection and protection of part suppliers and order quantity allocation in a supply chain with disruption risks. The protection decisions include the selection of suppliers to be protected against disruptions and the allocation of emergency inventory of parts to be pre-positioned at the protected suppliers. The decision maker needs to decide which supplier to select for parts delivery and how to allocate orders quantity among the selected suppliers, and which of the selected suppliers to protect against disruptions and how to allocate emergency inventory among the protected suppliers. The problem objective is to achieve a minimum cost of suppliers protection, emergency inventory pre-positioning, parts ordering, purchasing, transportation and shortage and to mitigate the impact of disruption risks by minimizing the potential worst-case cost. As a result a resilient supply portfolio is identified with protected suppliers capable of supplying parts in the face of disruption events. A mixed integer programming approach is proposed to determine risk-neutral, risk-averse or mean-risk supply portfolios, with conditional value-at-risk applied to control the risk of worst-case cost. Numerical examples are presented and some computational results are reported.     

At the boundary: Post-COVID agenda for business and management research in Europe and beyond

A rapidly growing body of scholarly research discusses the impact of the COVID-19 pandemic on business and management research. This Reflection on Europe takes stock of the situation and reflects critically on the deeper changes to the business ecosystem which the pandemic may engender. Based on surface level observations in three different contexts of business research, the analysis uncovers changes to underlying market circumstances which point towards radical shifts in the boundary conditions between business and society. The article concludes with suggestions for a post-COVID research agenda.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

神州电脑通过破坏性创新赢得竞争优势的案例分析

本文基于Christensen提出的破坏性创新（Disruptive innovation，又称裂变式创新、颠覆式创新）的三维模型，以神舟电脑作为典型案例，进行了深入的案例研究，研究了其实施破坏性创新的背景、实施方式、绩效贡献、成功原因等几个方面。研究发现：神舟电脑适时运用了破坏性创新的方式，迅速取得了市场竞争优势，从新兴企业逐渐成长为行业的主流企业之一。神舟的破坏性创新模式很值得我国新兴企业借鉴。     

Placement disruption in long-term kinship and nonkinship foster care

The purpose of this study was to explore factors related to placement disruption in long-term kinship and nonkinship foster care in a Nordic country.     

Anti-social youth? Disruptions in care and the role of ‘behavioral problems’

This paper explores the mechanisms behind the disturbingly high occurrence of placement disruption among young people in out-of-home care. Discussions have usually been framed in a vocabulary of risk and protection, with the bulk of research designed for singling out factors that correlate with stability and discontinuity in care arrangements. From this research tradition, we have learned that ‘behavioral problems’ are by far the strongest predictor for disruptions in care. By exploring the quality of care as experienced by young people themselves, this study suggests an alternative strategy. Findings suggest that disruptions occur as a result of complex social relations, as when young people struggle to fit in among other troubled youth in demanding residential settings. The paper concludes that labels such as ‘behavioral problems’ may have a reifying effect that individualizes the problem of care disruption while not being particularly helpful in explaining the phenomenon.     

Selection of supply portfolio under disruption risks

This paper deals with the optimal selection of supply portfolio in a make-to-order environment in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order to minimize total cost and mitigate the impact of disruption risks. The selection of suppliers and allocation of orders is based on price and quality of purchased parts and reliability of delivery. The two types of disruption scenarios are considered: scenarios with independent local disruptions of each supplier and scenarios with local and global disruptions that may result in all suppliers disruption simultaneously. The problem is formulated as a single- or bi-objective mixed integer program and a value-at-risk and conditional value-at-risk approach is applied to control the risk of supply disruptions. The proposed portfolio approach is capable of optimizing the supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.