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

2019 ◽  
Vol 9 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Seyed Mahdi Shavarani
Keyword(s):  
Facility Location ◽  
Large Scale ◽  
Hybrid Genetic Algorithm ◽  
Optimum Number ◽  
Humanitarian Relief ◽  
Coverage Area ◽  
Content Type ◽  
Relief Distribution ◽  
Multi Level ◽  
Post Disaster

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.

Post-disaster transportation of seriously injured people to hospitals

2018 ◽  
Vol 8 (2) ◽  
pp. 227-251 ◽  
Author(s):  
Seyed Mahdi Shavarani ◽  
Bela Vizvari
Keyword(s):  
Large Scale ◽  
Nearest Neighbor ◽  
Hybrid Genetic Algorithm ◽  
Real Life ◽  
Humanitarian Relief ◽  
Large Area ◽  
Routing Problem ◽  
Content Type ◽  
Emergency Vehicles

Purpose The purpose of this paper is to deal with the transportation of a high number of injured people after a disaster in a highly populated large area. Each patient should be delivered to the hospital before the specific deadline to survive. The objective of the study is to maximize the survival rate of patients by proper assignment of existing emergency vehicles to hospitals and efficient generation of vehicle routes. Design/methodology/approach The concepts of non-fixed multiple depot pickup and delivery vehicle routing problem (MDPDVRP) is utilized to capture an image of the problem encountered in real life. Due to NP-hardness of the problem, a hybrid genetic algorithm (GA) is proposed as the solution method. The performance of the developed algorithm is investigated through a case study. Findings The proposed hybrid model outperforms the traditional GA and also is significantly superior compared to the nearest neighbor assignment. The required time for running the algorithm on a large-scale problem fits well into emergency distribution and the promptness required for humanitarian relief systems. Originality/value This paper investigates the efficient assignment of emergency vehicles to patients and their routing in a way that is most appropriate for the problem at hand.

Suggestions for large-scale, postdisaster reconstruction involving indigenous populations: a participatory approach to recovery after Typhoon Morakot

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sung Lun Tsai ◽  
Chiho Ochiai ◽  
Min Hui Tseng ◽  
Chuan Zhong Deng
Keyword(s):  
Large Scale ◽  
Community Organization ◽  
Structured Interview ◽  
Indigenous Populations ◽  
Quantitative Methodology ◽  
Typhoon Morakot ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Extent Of Damage ◽  
Post Disaster

Purpose The participatory method, a major factor for a successful post-disaster reconstruction (PDR) project, is applied in various stages of the PDR. However, the application of this method for PDR involving indigenous populations is underexplored. Therefore, this paper aims to analyze the critical factors that can influence the participatory PDR in the indigenous context. Design/methodology/approach Two large-scale, indigenous, post-disaster relocation projects after the 2009 Typhoon Morakot were selected as case studies. The qualitative and quantitative methodology (semi-structured interview and questionnaire) were applied in the research. Findings A participation-friendly policy, community organization, the extent of damage, flexibility of nongovernmental organizations, understanding of the participatory concept and mutual trust were found to be essential factors that profoundly influence participation in PDR projects. Originality/value This study contributes by providing guidelines for future participatory PDR projects, especially in the indigenous context.

Rival governments risk permanent division of Yemen

2016 ◽  
Keyword(s):  
Saudi Arabia ◽  
Economic Reform ◽  
Large Scale ◽  
Central Government ◽  
Major Change ◽  
Humanitarian Relief ◽  
Content Type ◽  
Reform Programme ◽  
The Creation ◽  
The Military

Subject Yemen partition prospects. Significance The August 6 launch by the Huthis and loyalists of former President Ali Abdallah Saleh of a joint ruling body to govern Yemen has led to the collapse of peace talks, and an escalation in the conflict with forces aligned to Saudi Arabia and the internationally recognised government of President Abd Rabbu Mansour Hadi. The UN has said that the creation of the Supreme Political Council (SPC) violates Security Council resolutions on resolving the conflict. It also brings Yemen a step closer towards the creation of a new central government in Sana'a rivalling Hadi's government based in Aden. Impacts A new UN peace initiative is unlikely to succeed unless there is a major change in the military situation. Prolonged conflict in Yemen will distract Saudi focus and resources from its domestic economic reform programme. Large-scale humanitarian relief and reconstruction will only begin following a (currently unlikely) deal on a unity government.

Mount Merapi eruption

2019 ◽  
Vol 9 (2) ◽  
pp. 292-322 ◽  
Author(s):  
Bertha Maya Sopha ◽  
Risqika Edni Doni Achsan ◽  
Anna Maria Sri Asih
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Coordination Mechanism ◽  
Uneven Distribution ◽  
Content Type ◽  
Agent Based ◽  
Last Mile ◽  
Relief Distribution ◽  
Post Disaster

Purpose Uneven distribution and mistarget beneficiaries are among problems encountered during post-disaster relief operations in 2010 Mount Merapi eruption. The purpose of this paper is to develop an empirically founded agent-based simulation model addressing the evacuation dynamics and to explore coordination mechanism and other promising strategies during last-mile relief delivery. Design/methodology/approach An agent-based model which was specified and parameterized by empirical research (interviews and survey) was developed to understand the mechanism of individual decision making underlying the evacuation dynamics. A set of model testing was conducted to evaluate confidence level of the model in representing the evacuation dynamics during post-disaster of 2010 Mount Merapi eruption. Three scenarios of last-mile relief delivery at both strategic and operational levels were examined to evaluate quantitatively the effectiveness of the coordination mechanism and to explore other promising strategies. Findings Results indicate that the empirically founded agent-based modeling was able to reproduce the general pattern of observable Internal Displaced Persons based on government records, both at micro and macro levels, with a statistically non-significant difference. Low hazard perception and leader-following behavior which refuses to evacuate are the two factors responsible for late evacuation. Unsurprisingly, coordination through information sharing results in better performance than without coordination. To deal with both uneven distribution and long-term demand fulfillment, coordination among volunteers during aid distribution (at downstream operation) is not sufficient. The downstream coordination should also be accompanied with coordination between aid centers at the upstream operation. Furthermore, the coordination which is combined with other operational strategies, such as clustering strategy, using small-sized trucks and pre-positioning strategy, seems to be promising. It appears that the combined strategy of coordination and clustering strategy performs best among other combined strategies. Practical implications The significant role of early evacuation and self-evacuation behavior toward efficient evacuation indicates that human factor (i.e. hazard perception and cultural factor) should be considered in designing evacuation plan. Early warning system through both technology and community empowerment is necessary to support early evacuation. The early warning system should also be accompanied with at least 69 percent of the population performing self-evacuation behavior for the effective evacuation. As information sharing through coordination is necessary to avoid redundant efforts, uneven distribution and eventually to reduce unmet demand, the government can act as a coordinating actor to authorize the operation and mobilize the resources. The combination of coordination and another strategy reducing lead time such as clustering analysis, thus increasing responsiveness, is seemly strategy for efficient and effective last-mile relief distribution. Originality/value Literature on coordination is dominated by qualitative approach, which is difficult to evaluate its effectiveness quantitatively. Providing realistic setting of the evacuation dynamics in the course of the 2010 Mount Merapi eruption, the empirically founded agent-based model can be used to understand the factors influencing the evacuation dynamics and subsequently to quantitatively examine coordination mechanisms and other potential strategies toward efficient and effective last-mile relief distribution.

Using an Agent-Based Behavior Modeling for Finding Humanitarian Relief Center Location in an Earthquake Zone

2013 ◽  
pp. 876-891
Author(s):  
Numan Celebi
Keyword(s):  
Emergency Management ◽  
Facility Location ◽  
Risk Index ◽  
Facility Location Problem ◽  
Behavior Modeling ◽  
Earthquake Risk ◽  
Humanitarian Relief ◽  
Agent Based ◽  
Relief Distribution ◽  
Earthquake Zone

Every year many different disasters occur in the world. The numbers of disasters has increased, especially in recent years. Emergency management of contingency has attracted by many researchers, who used analytical methods to find the optimal locations of humanitarian relief distribution center(s). This study sets up a model for humanitarian relief center facility location problem. This model considers some characteristics such as earthquake risk index, population density index, and transportation index to determine the optimal facility location center to respond the victims when an earthquake or disaster occurs. The method is based on a mathematical model for locating facility center. The author applies this model in a city in Turkey, and then the model is solved as an agent based behavior modeling according to the particle swarm optimization. Finally, the results are presented.

Cross-cultural application of a practice-oriented acquiescence measure

2019 ◽  
Vol 36 (3) ◽  
pp. 391-415 ◽  
Author(s):  
Carolin Krautz ◽  
Stefan Hoffmann
Keyword(s):  
Large Scale ◽  
Power Distance ◽  
Cross Cultural ◽  
Cultural Dimensions ◽  
Content Type ◽  
Country Level ◽  
Consumer Study ◽  
Multi Level ◽  
High Level ◽  
Level Analysis

Purpose Extant research shows that acquiescence response style (ARS) is culture-bound and may bias the results of comparative cross-cultural studies. Conventional measures of ARS are difficult to apply in practice. To overcome this limitation, the purpose of this paper is to propose an alternative, practice-oriented measure, namely, pARS. The authors apply Hofstede’s cultural dimensions (Hofstede et al., 2010) to test whether pARS is culture-bound. The cross-cultural study provides a high level of cross-cultural generalisability due to the extensive number of surveyed countries (n=30) and subjects (n=236.089). The authors run multi-level analysis to identify within- and between-country-level predictors. Design/methodology/approach On the individual level, the authors use data of a large-scale cross-cultural study, including 236.089 consumers from 30 countries worldwide. The authors apply several methods to test for the culture-boundness of pARS. First, they apply correlation analysis to replicate existing cross-cultural results and to ensure nomological validity. Second, applying ordinary least square regression, the authors simultaneously test the six Hofstede cultural dimensions (Hofstede et al., 2010) and investigate interactions between the dimensions. Finally, they use multi-level analysis to confirm the stability of culture-bound results, controlling for individual- and country-level variability. Findings The paper introduces an alternative measure for acquiescence (pARS), which is particularly suitable for shorter questionnaires. A large-scale consumer study with 236.089 respondents in 30 countries supports the culture-bound validity of pARS. The authors confirm construct validity and the nomological network of pARS. Contrasting existing studies, multi-level analysis demonstrates that a high level of power distance majorly leads to ARS. Therefore, cross-cultural researchers need to control for ARS in countries high in power distance, especially when paired with high uncertainty avoidance. Originality/value A large-scale consumer study with 236.089 respondents from 30 countries shows that respondents from various countries differ significantly in their level of acquiescence. The study confirms that power distance is the most relevant cultural dimension to explain these differences. Although ARS may bias the results of comparative cross-cultural studies, it is rarely controlled by market research studies outside the academic realm. The present work proposes and establishes the validity of a practice-oriented measure of acquiescence, namely, pARS. pARS is particularly suitable for shorter questionnaires. In contrast to prior approaches, applying pARS does not require adding non-substantive items to the questionnaire.

Reforming primary healthcare: from public policy to organizational change

2015 ◽  
Vol 29 (1) ◽  
pp. 92-110 ◽  
Author(s):  
Frédéric Gilbert ◽  
Jean-Louis Denis ◽  
Lise Lamothe ◽  
Marie-Dominique Beaulieu ◽  
Danielle D'amour ◽  
...  
Keyword(s):  
Primary Care ◽  
Public Policy ◽  
Primary Healthcare ◽  
Policy Development ◽  
Large Scale ◽  
Professional Autonomy ◽  
Content Type ◽  
Scale Change ◽  
Large Scale Change ◽  
Multi Level

Purpose – Governments everywhere are implementing reform to improve primary care. However, the existence of a high degree of professional autonomy makes large-scale change difficult to achieve. The purpose of this paper is to elucidate the change dynamics and the involvement of professionals in a primary healthcare reform initiative carried out in the Canadian province of Quebec. Design/methodology/approach – An empirical approach was used to investigate change processes from the inception of a public policy to the execution of changes in professional practices. The data were analysed from a multi-level, combined contextualist-processual perspective. Results are based on a longitudinal multiple-case study of five family medicine groups, which was informed by over 100 interviews, questionnaires, and documentary analysis. Findings – The results illustrate the multiple processes observed with the introduction of planned large-scale change in primary care services. The analysis of change content revealed that similar post-change states concealed variations between groups in the scale of their respective changes. The analysis also demonstrated more precisely how change evolved through the introduction of “intermediate change” and how cycles of prescribed and emergent mechanisms distinctively drove change process and change content, from the emergence of the public policy to the change in primary care service delivery. Research limitations/implications – This research was conducted among a limited number of early policy adopters. However, given the international interest in turning to the medical profession to improve primary care, the results offer avenues for both policy development and implementation. Practical implications – The findings offer practical insights for those studying and managing large-scale transformations. They provide a better understanding of how deliberate reforms coexist with professional autonomy through an intertwining of change content and processes. Originality/value – This research is one of few studies to examine a primary care reform from emergence to implementation using a longitudinal multi-level design.

Humanitarian supply chain management: modeling the pre and post-disaster relief operations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Agarwal ◽  
Ravi Kant ◽  
Ravi Shankar
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Facility Location ◽  
Disaster Relief ◽  
Evacuation Planning ◽  
Content Type ◽  
Disaster Relief Operations ◽  
Relief Operations ◽  
Humanitarian Supply Chain ◽  
Post Disaster

Purpose This study proposed a mathematical model for decision-making in the pre- and post-disaster phases. This research aims to develop a mathematical model for three important fields in the context of humanitarian logistics; stock prepositioning, facility location and evacuation planning in the humanitarian supply chain (HSC) network design. Design/methodology/approach This study applied three optimization techniques; classical approach (CA), pattern search algorithm (PSA) and Genetic Algorithm (GA) to solve the proposed mathematical model. The proposed mathematical model attempts to minimize the total relief items supply chain cost and evacuation chain cost of the HSC. A real case study of cyclone Fani, 2019 in Orissa, India is applied to validate the proposed mathematical model and to show the performance of the model. Findings The results demonstrate that heuristic approach; PSA performs better and optimal solutions are obtained in almost all the cases as compared to the GA and CA. Research limitations/implications This study is limited to deterministic demands in the affected regions, and different scenarios of the disaster events are not considered. Social implications The finding reveals that the proposed model can help the humanitarian stakeholders in making decisions on facility location, relief distribution and evacuation planning in disaster relief operations. Originality/value The results of this study may offer managerial insights to practitioners and humanitarian logisticians who are engaged in HSC implementation.

Assessing industry differences in marketing innovation using multi-level modeling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ajax Persaud ◽  
Shu Wang ◽  
Sandra R. Schillo
Keyword(s):  
Empirical Evidence ◽  
Large Scale ◽  
Business Strategies ◽  
Customer Engagement ◽  
Firm Level ◽  
Data Set ◽  
Content Type ◽  
Marketing Innovation ◽  
Industry Level ◽  
Multi Level

Purpose Currently, the bulk of research on marketing innovation focuses on various firm-level dimensions using relationships from the technological (product and process) innovation literature. Research on industry-level differences in marketing innovation is lacking. Testing relationships form the technological paradigm in the context of the marketing innovation paradigm is also lacking. This paper aims to present empirical evidence on both aspects using a large-scale data set. Design/methodology/approach This study uses two large-scale datasets, each consisting of approximately 4,000 Canadian enterprises in 18 industries. The data was collected by Statistics Canada in 2009 and 2012 through its nationwide Survey of Innovation and Business Strategies program. Two widely used theoretical frameworks, resource-based view of the firm and the competitive perspective, are used to generate constructs and hypotheses in relation to marketing innovation. The data was analyzed using multi-level logistic regression. Findings The findings show that industry-level competition is a much more important driver of marketing innovation than firm-level competition. The authors also show that marketing constructs that are significant in the context of technological innovation are also significant for marketing innovation. Research limitations/implications This study extends the firm-level literature by providing evidence of how industry-level dynamics enhances marketing innovation. The study also provides empirical evidence from Canadian enterprises that complement those from other countries. Practical implications A deeper understanding of the drivers of marketing innovation can enable managers to enact innovation strategies that can enhance organizational performance, differentiate themselves and enhance customer engagement and brand image. Originality/value As one of the few studies to examine industry-level differences in marketing innovation, the authors show that disaggregating competition into industry-level and firm-level provides a clearer picture of how competition advances marketing innovation. Additionally, this study is the first of its kind to provide empirical evidence on Canadian enterprises, thereby complementing evidence on marketing innovation from other countries. Thus, this study makes a theoretical and empirical contribution to the emerging marketing innovation literature.

A hybrid approach for cost-optimized lateral transshipment in a supply chain environment

2016 ◽  
Vol 22 (4) ◽  
pp. 860-878
Author(s):  
Dilupa Nakandala ◽  
Henry Lau ◽  
Andrew Ning
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Inventory Management ◽  
Large Scale ◽  
Hybrid Approach ◽  
Hybrid Genetic Algorithm ◽  
Hill Climbing ◽  
Initial Population ◽  
Content Type ◽  
Lateral Transshipment

Purpose – When making sourcing decisions, both cost optimization and customer demand fulfillment are equally important for firm competitiveness. The purpose of this paper is to develop a stochastic search technique, hybrid genetic algorithm (HGA), for cost-optimized decision making in wholesaler inventory management in a supply chain network of wholesalers, retailers and suppliers. Design/methodology/approach – This study develops a HGA by using a mixture of greedy-based and randomly generated solutions in the initial population and a local search method (hill climbing) applied to individuals selected for performing crossover before crossover is implemented and to the best individual in the population at the end of HGA as well as gene slice and integration. Findings – The application of the proposed HGA is illustrated by considering multiple scenarios and comparing with the other commonly adopted methods of standard genetic algorithm, simulated annealing and tabu search. The simulation results demonstrate the capability of the proposed approach in producing more effective solutions. Practical implications – The pragmatic importance of this method is for the inventory management of wholesaler operations and this can be scalable to address real contexts with multiple wholesalers and multiple suppliers with variable lead times. Originality/value – The proposed stochastic-based search techniques have the capability in producing good-quality optimal or suboptimal solutions for large-scale problems within a reasonable time using ordinary computing resources available in firms.

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