Defining logistics preparedness: a framework and research agenda

Jahre, Marianne; Pazirandeh, Ala; Wassenhove, Luk Van

doi:10.1108/jhlscm-04-2016-0012

Cited by 58 publications

(71 citation statements)

References 69 publications

(130 reference statements)

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“…Constraint (11) makes sure that each node is assigned to its corresponding closest centre. Constraints (12) and (13) define the binary and positive variables.…”

Section: Problem Definition Assumptions and Formulationmentioning

confidence: 99%

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Shavarani¹

2019

JHLSCM

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Purpose Previously use of drones as a relief distribution vehicle was studied in several studies where required number of drones and the best locations for the relief centers were investigated. The maximum travel distance of drones without a need to recharge is limited by their endurance. Recharge stations can be used to extend the coverage area of the drones. The purpose of this paper is to find the best topology for both relief centers and recharge stations to cover a large-scale area with minimum and feasible incurred costs and waiting times. Design/methodology/approach A multi-level facility location problem (FLP) is utilized to find the optimum number of relief centers and refuel stations and their locations. It is supposed that the demand occurs according to Poisson distribution. The allocation of the demand is based on nearest neighborhood method. A hybrid genetic algorithm is proposed to solve the model. The performance of the algorithm is examined through a case study. Findings The proposed method delivers increased efficiency and responsiveness of the humanitarian relief system. The coverage area of the drones is extended by refuel stations, total costs of the system are reduced and the time to respond an emergency, which is an important factor in survival rate, is significantly decreased. Originality/value This study proposes a multi-level FLP to simultaneously account for recharge stations, relief centers and the number of required drones to cover all the demand for relief in a post-disaster period.

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“…Constraint (11) makes sure that each node is assigned to its corresponding closest centre. Constraints (12) and (13) define the binary and positive variables.…”

Section: Problem Definition Assumptions and Formulationmentioning

confidence: 99%

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Shavarani¹

2019

JHLSCM

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“…Research on logistics preparedness mainly concerns network design and warehouse location for prepositioning of goods (Kunz and Reiner, 2012), a focus also seen in practice (Jahre et al 2016b). Prepositioning can be viewed as strategic stock and is only one among many strategies suggested in the SCRM-literature.…”

Section: "Where Is the Crisis Management Component Of [Humanitarian Omentioning

confidence: 99%

Humanitarian supply chain strategies – a review of how actors mitigate supply chain risks

Jahre

2017

JHLSCM

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Purpose of this paper This paper links humanitarian logistics (HL) and supply chain risk management (SCRM) to provide an understanding of risk mitigation strategies that humanitarian organizations use, or could use, to improve their logistics preparedness. Design/methodology/approachBased on systematic reviews of strategies in SCRM and supply chain strategies (SCS) in HL literature, a framework is developed and used to review published case studies in HL. FindingsThe study finds that humanitarian actors use a number of the strategies proposed in the framework, particularly those related to strategic stocks, postponement, and collaboration. Strategies related to sourcing and procurement, however, especially those on supplier relationships, seem to be lacking in both research and practice. Research limitationsThe study is based on secondary data and could be further developed through case studies based on primary data. Future studies should explore the generalizability of the findings. Practical implicationsPractitioners can use the framework to identify potential new SCS and how strategies can be combined. Findings can help them to understand the abnormal risks of main concern, how they may impact normal risks, and provide ideas on how to tackle trade-offs between different risks. Societal implicationsThe results can support improvements in humanitarian supply chains, which will provide affected people with rapid, cost-efficient, and better-adapted responses.What is original/value of paper The paper connects SCRM and HL to develop a framework and suggest propositions on how humanitarian actors can mitigate supply chain risks. Questioning the focus on strategic stock it suggests complementary or alternative strategies for improving logistics preparedness.

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“…PRI is a costly process, which necessitates adequate financial resources. Most humanitarian organizations suffer from financial problems and have limited financial resources for PRI (38). Such limitations affect the quantity and quality of PRI (30).…”

Section: Financial Problems and Limitationsmentioning

confidence: 99%

Factors Affecting the Prepositioning of Relief Items for Natural Disasters: A Systematic Review

Sharifi-Sedeh

Ardalan

Torabi

et al. 2020

Iran Red Crescent Med J

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Context: Humanitarian logistics aims to reduce the suffering of disaster victims by fulfilling their immediate needs. A key component of humanitarian logistics is the prepositioning of relief items (such as water and food) for effective emergency response. Objectives: This study aimed to explore factors affecting the prepositioning of relief items for natural disasters. Data Sources: This was a systematic review. Relevant articles were retrieved from Google Scholar, PubMed, Web of Science, and Scopus databases. We also assessed other gray literature. Data Extraction: Data were summarized and analyzed through thematic content analysis. Overall, 22 final articles were included in the study. Articles that referred to the prepositioning of relief items were included in the study. Results: Factors affecting the prepositioning of relief items were categorized into four main categories and eight sub-categories. These categories included site selection, preparation, and management of warehouse (with two sub-categories of warehouse site selection, warehouse workforce); risk management studies (with two sub-categories of uncertainty, and demand estimation); infrastructures (with two sub-categories of transportation infrastructures, and other infrastructures); and financial and sociopolitical factors (with two sub-categories of financial problems and limitations sociopolitical factors). Conclusions: Appropriate identification of factors that affect relief-item prepositioning can help decision-makers design appropriate models for prepositioning.

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Defining logistics preparedness: a framework and research agenda

Cited by 58 publications

References 69 publications

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Humanitarian supply chain strategies – a review of how actors mitigate supply chain risks

Factors Affecting the Prepositioning of Relief Items for Natural Disasters: A Systematic Review

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