Service outsourcing and disaster response methods in a relief supply chain

Wang, Xihui; Wu, Yunfei; Liang, Liang; Huang, Zhimin

doi:10.1007/s10479-014-1646-y

Cited by 80 publications

(57 citation statements)

References 22 publications

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“…It shall also contribute to the prediction of the magnitude of the disaster. Wang et al (2016) advocated the importance of the conjunction of proactive response method and logistic expertise for effective relief efforts. Knowledge about the number of victims is of prime concern for planning the amount of relief resources required for planning the rescue operations.…”

Section: Phase Imentioning

confidence: 99%

Impact of internet of things (IoT) in disaster management: a task-technology fit perspective

et al. 2017

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Disaster management aims to mitigate the potential damage from the disasters, ensure immediate and suitable assistance to the victims, and attain effective and rapid recovery. These objectives require a planned and effective rescue operation post such disasters. Different types of information about the impact of the disaster are, hence, required for planning an effective and immediate relief operation. The IoT technology available today is quite mature and has the potential to be very useful in disaster situations. This paper analyzes the requirements for planning rescue operation for such natural disasters and proposes an IoT based solution to cater the identified requirements. The proposed solution is further validated using the task-technology fit (TTF) approach for analyzing the significance of the adoption of IoT technology for disaster management. Results from the exploratory study established the core dimensions of the task requirements and the TTF constructs. Results from the confirmatory factor analysis using PLS path modelling, further, suggest that both task requirements and IoT technology have significant impact on the IoT TTF in the disaster management scenario. This paper makes significant contributions in the development of appropriate constructs for modeling TTF for IoT Technology in the context of disaster management.

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Section: Phase Imentioning

confidence: 99%

Impact of internet of things (IoT) in disaster management: a task-technology fit perspective

et al. 2017

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“…Inventories undergo change in storage in time they may become partially or entirely unfit for consumption. A similar trade-off between the time and the resources assumes significant importance during the military relief operations in times of natural calamities like flood, cyclone, hurricane, etc (Wang et al, 2016). Another important task for any organization that moves cargo and people is to decide how many vehicles or platforms it needs.…”

Section: Introductionmentioning

confidence: 99%

Optimising integrated inventory policy for perishable items in a multi-stage supply chain

Dolgui

Tiwari

Yerasani

et al. 2017

International Journal of Production Research

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The value of perishable products is most affected by the time delays in a supply chain. A major issue is how to integrate the existing practices in production, inventory holding and distribution, besides considering the perishable nature of the products, so as to deliver an optimized policy for the perishable commodities. Standard inventory control models are often not adequate for perishable products and there is a need for a new integrated model to focus on consolidation of production, inventory and distribution processes. We develop such a mathematical model to search for an optimal integrated inventory policy for perishable items in a multi-stage supply chain. We specifically assume the exponential deterioration rate so as to be consistent with the growth rate of the micro-organisms responsible for deterioration. We propose and analyze some general properties of the model and apply it to a three-stage supply chain. We show that this integrated model which includes inventory control and fleet selection can be optimized with an evolutionary technique like genetic algorithm. A novel genetic algorithm that avoids revisits and employs a parameter-less self-adaptive mutation operator is developed. The results are compared with those obtained with CPLEX for small sized problems. We show that our model and optimization approach gives near optimal results for varied demand scenarios.

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“…Different relief supplies are usually classified and studied separately. For example, Wang et al, (2014) classifies a relief supply as perishable or imperishable, and advocates adopting different purchasing methods to cope with different relief supplies. Our study shows that PPOC can coordinate a relief supply chain dealing with any types of relief supplies, and is suitable for wider range of applications.…”

Section: Discussionmentioning

confidence: 99%