Omnichannel retail operations with ship-to-store and ship-from-store options under supply disruption

Omnichannel retailing strategies are widely used in practice and have been extensively studied in recent years, but few studies have explored omnichannel retailing operations in response to supply disruption in the post-pandemic era. To fill this gap, this study explores whether the adoption of omnichannel fulfillment options (i.e., ship-from-store and ship-to-store options) can mitigate the risk of supply disruption in a supply chain where a retailer orders products from a reliable supplier and a risky supplier, respectively. Under the omnichannel retailing strategy, the retailer’s order quantity from the risky supplier may increase or decrease while that from the reliable supplier may increase. Interestingly, it is possible to achieve a win–win–win outcome when the supply disruption risk is high and the market share of the channel offered by the risky supplier is low. Moreover, the entire supply chain benefits from the omnichannel retailing strategy even if it faces a high level of disruption risk.

Modeling of the resilient supply chain system from a perspective of production design changes

Building an effective resilient supply chain system (RSCS) is critical and necessary to reduce the risk of supply chain disruptions in unexpected scenarios such as COVID-19 pandemic and trade wars. To overcome the impact of insufficient raw material supply on the supply chain in mass disruption scenarios, this study proposes a novel RSCS considering product design changes (PDC). An RSCS domain model is first developed from the perspective of PDC based on a general conceptual framework, i.e., function-context-behavior-principle-state-structure (FCBPSS), which can portray complex systems under unpredictable situations. Specifically, the interaction among the structure, state and behavior of the infrastructure system and substance system is captured, and then a quantitative analysis of the change impact process is presented to evaluate the resilience of both the product and supply chain. Next, a case study is conducted to demonstrate the PDC strategy and to validate the feasibility and effectiveness of the RSCS domain model. The results show that the restructured RSCS based on the proposed strategy and model can remedy the huge losses caused by the unavailability of raw materials.

Quantity Flexibility Contract Model for Emergency Procurement Considering Supply Disruption

Supply chain disruption risk usually poses a serious challenge to the management of emergency supplies procurement between the government and enterprises in cooperation.To research the impact of supply chain disruption on the supply and demand sides of emergency supplies for disaster relief,the emergency procurement model based on quantity flexibility contract is constructed.The model introduces a stockout disruption to measure the degree of supply chain disruption and uses per unit of material relief value to quantify government disaster relief benefits.Further,it analyzes the basic pricing strategy and the agreed order quantity between the government and enterprises,focusing on the negative impact of supply disruption on the government and enterprises.The model deduction and data analysis results show that supply disruption creates a“lose-lose”situation for governments and enterprises,reducing their benefits and willingness to cooperate.Finally,a sensitivity analysis is conducted on the case data to explain the decision-making changes in the contract price and flexibility parameters between the government and enterprises before and after the supply disruption.

Intelligent Manufacturing Systems in COVID‑19 Pandemic and Beyond:Framework and Impact Assessment

Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks.The intelligent manufacturing(IM)systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms.The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network,which mitigates the severity of industrial chain disruption.In this study,we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks.Considering the constraints of the IM resources,we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic.