Search results
1 – 10 of over 3000Chang Hoon Oh, Jennifer Oetzel, Jorge Rivera and Donald Lien
The purpose of this study is to examine how foreign firms consider natural disaster risk in subsequent investment decisions in a host country and whether different location…
Abstract
Purpose
The purpose of this study is to examine how foreign firms consider natural disaster risk in subsequent investment decisions in a host country and whether different location portfolios can serve to mitigate investment risk.
Design/methodology/approach
The author sample includes data on 437 Fortune Global 500 firms and their initial entry into Chinese provinces between 1955 and 2008.
Findings
Using a fixed effects logit model of discrete time event history analysis, results show that geographic proximity to same multinational corporation (MNC) subsidiaries and different MNC subsidiaries from the same home country mitigates the negative effect of natural disasters on MNC entry into an affected province, while geographic proximity to other MNC subsidiaries from different home countries does not.
Originality/value
The knowledge needed to respond to severe disasters appears to be highly context-specific and shared only between firms with a high degree of commonality and trust.
Details
Keywords
Sanjeewa Wickramaratne, Janaka Ruwanpura, Upul Ranasinghe, Samanthi Walawe‐Durage, Varuna Adikariwattage and S.C. Wirasinghe
The purpose of this paper is to propose a methodology for a priori classification of natural disasters that occur in Sri Lanka, through the development of a set of weighted…
Abstract
Purpose
The purpose of this paper is to propose a methodology for a priori classification of natural disasters that occur in Sri Lanka, through the development of a set of weighted parameters based on the product of the disaster impact and the affected area, in order to prepare mitigation plans.
Design/methodology/approach
Experts' opinions were used for developing the parameters. Through a facilitated workshop, the weights of the disasters were obtained from experts involved in disaster mitigation at the local, regional and national levels in Sri Lanka. A correlation analysis was used to determine the most appropriate independent measures of disaster impact and affected area, the product of which was used to rank the identified disasters for further action.
Findings
For the pre‐selection of major disasters, the study showcases four weighted parameters, one of which is identified as the best. In total, five disasters have been singled out for further consideration in Sri Lanka. The product of the affected area factor, based on administrative area classification, and the impact factor, out of the two considered, that places a higher weight on minor disasters, is shown to be the best criterion.
Research limitations/implications
The geographical distribution of the participants (experts) does influence the results, and those available for the workshop were not fully representative of all Sri Lanka's provinces.
Originality/value
The paper emphasizes the importance of the consideration of the area impacted rather than the classification, which is based solely on the severity of the impact. The categorization of disasters based on experts' opinions and the related analysis revealed a priority order for planning for certain identified disasters.
Details
Keywords
The literature was reviewed to locate the most relevant social-psychology theories, factors, and instruments in order to measure New York State resident attitudes and social norms…
Abstract
Purpose
The literature was reviewed to locate the most relevant social-psychology theories, factors, and instruments in order to measure New York State resident attitudes and social norms (SNs) concerning their intent to evacuate Hurricane Irene in the summer of 2011. The purpose of this paper is to develop a model which could be generalized to improve social policy determination for natural disaster preparation.
Design/methodology/approach
A post-positivist ideology was employed, quantitative data were collected from an online survey (nominal, binary, interval, and ratio), and inferential statistical techniques were applied to test theory-deductive hypotheses (Strang, 2013b). Since the questions for each hypothesized factor were customized using a pilot for this study, exploratory factor analysis were conducted to ensure the item validity and reliabilities were compared to a priori benchmarks (Gill et al., 2010). Correlation analysis along with logistic and multiple regression were applied to test the hypothesis at the 95 percent confidence level.
Findings
A statistically significant model was developed using correlation, stepwise regression, ordinary least squares regression, and logistic regression. Only two composite factors were needed to capture 55.4 percent of the variance for behavioral intent (BI) to evacuate. The model predicted 43.9 percent of the evacuation decisions, with 13.3 percent undecided, leaving 42.8 incorrectly classified), using logistic regression (n=401 surveyed participants).
Research limitations/implications
Municipal planners can use this information by creating surveys and collecting BI indicators from citizens, during risk planning, in advance of a natural disaster. The concepts could also apply to man-made disasters. Planners can use the results from these surveys to predict the overall likelihood that residents with home equity (e.g. home owners) intend to leave when given a public evacuation order.
Practical implications
Once municipal planners know the indicators for personal attitudes (PAs) (in particular) and SNs, they could sort these by region, to identify areas where the PAs were too low. Then additional evacuation preparation efforts can be focussed on those regions. According to these findings, the emphasis must be focussed on a PA basis, describing the extreme negative impacts of previous disasters, rather than using credible spokespersons, to persuade individuals to leave.
Originality/value
A new model was created with a “near miss disaster” severity factor as an extension to the theory of reasoned action.
Details
Keywords
The purpose of this study is to evaluate whether the media's disaster coverage reflects the messages disseminated by state emergency management agencies (SEMAs).
Abstract
Purpose
The purpose of this study is to evaluate whether the media's disaster coverage reflects the messages disseminated by state emergency management agencies (SEMAs).
Design/methodology/approach
SEMAs were selected as the unit of analysis because the 2008 National Response Framework designates SEMAs with primary responsibility for managing disaster planning and coordinating the inter‐governmental response to disasters. Specifically, this study identifies ten disaster frames SEMAs use through a qualitative content analysis of all the media releases distributed by three SEMAs (n=303) during a two‐year time frame. It then evaluates whether the coverage reflects SEMA's frames through a quantitative content analysis of 1,088 newspaper articles.
Findings
Taken as a whole, the research indicates that framing allows the media to efficiently tell disaster stories, but the media's disaster frames often are not ideal from the perspective of emergency managers. These frames also are affected by individuals and groups outside of the media as well as cultural and societal values.
Originality/value
The paper can help emergency managers identify which disaster frames are best suited for information subsidies (e.g. media releases) and which frames may be better suited for direct‐to‐the public dissemination (e.g. community meetings and public service announcements).
Details
Keywords
Ali Beiki Ashkezari, Mahsa Zokaee, Erfan Rabbani, Masoud Rabbani and Amir Aghsami
Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This…
Abstract
Purpose
Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.
Design/methodology/approach
In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.
Findings
Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.
Originality/value
The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.
Details
Keywords
Fatemeh Sabouhi, Ali Bozorgi-Amiri and Parinaz Vaez
This study aims to minimize the expected arrival time of relief vehicles to the affected areas, considering the destruction of potential routes and disruptions due to disasters…
Abstract
Purpose
This study aims to minimize the expected arrival time of relief vehicles to the affected areas, considering the destruction of potential routes and disruptions due to disasters. In relief operations, required relief items in each affected area and disrupted routes are considered as uncertain parameters. Additionally, for a more realistic consideration of the situations, it is assumed that the demand of each affected area could be met by multiple vehicles and distribution centers (DCs) and vehicles have limited capacity.
Design/methodology/approach
The current study developed a two-stage stochastic programming model for the distribution of relief items from DCs to the affected areas. Locating the DCs was the first-stage decisions in the introduced model. The second-stage decisions consisted of routing and scheduling of the vehicles to reach the affected areas.
Findings
In this paper, 7th district of Tehran was selected as a case study to assess the applicability of the model, and related results and different sensitivity analyses were presented as well. By carrying out a simultaneous sensitivity analysis on the capacity of vehicles and the maximum number of DCs that can be opened, optimal values for these parameters were determined, that would help making optimal decisions upon the occurrence of a disaster to decrease total relief time and to maximize the exploitation of available facilities.
Originality/value
The contributions of this paper are as below: presenting an integrated model for the distribution of relief items among affected areas in the response phase of a disaster, using a two-stage stochastic programming approach to cope with route disruptions and uncertain demands for relief items, determining location of the DCs and routing and scheduling of vehicles to relief operations and considering a heterogeneous fleet of capacitated relief vehicles and DCs with limited capacity and fulfilling the demand of each affected area by more than one vehicle to represent more realistic situations.
Details
Keywords
Miao Liu, Eric Scheepbouwer and Sonia Giovinazzi
The purpose of this paper is to synthesise critical success factors (CSFs) for advancing post-disaster infrastructure recovery and underpinning recovery authorities in decision…
Abstract
Purpose
The purpose of this paper is to synthesise critical success factors (CSFs) for advancing post-disaster infrastructure recovery and underpinning recovery authorities in decision making when facing future disasters.
Design/methodology/approach
The seismic recovery after the Canterbury (NZ) earthquake sequence in 2010-2011 was selected as a case study for identifying CSFs for an efficient recovery of infrastructure post-disaster. A combination of research approaches, including archival study, observations and semi-structured interviews were conducted for collecting data and evidences by engaging with participants involved at various tiers in the post-disaster recovery and reconstruction. The CSFs are evaluated and analysed by tracking the decision-making process, examining resultant consequences and foreseeing onwards challenges.
Findings
Six salient CSFs for strengthening infrastructure recovery management after disasters are identified. Furthermore, the study shows how each of these CSFs have been incorporated into the decision-making process in support of the post-disaster recovery and what difficulties encountered in the recovery process when implementing.
Practical implications
The proposed CSFs provide a future reference and guidance to be drawn on by decision makers when project-managing post-disaster recovery operations.
Originality/value
The value of the paper is that it bridges the gap between managerial contexts and technical aspects of post-disaster recovery process in an effort to rapidly and efficiently rebuild municipal infrastructure.
Details
Keywords
Elberier O. Mohammed and Babiker A. Abdul Rahman
Examines disasters in Africa between 1964 and 1991. Looks at types, trends, distribution and compares natural and man‐made disasters. Data from the office of the US Foreign…
Abstract
Examines disasters in Africa between 1964 and 1991. Looks at types, trends, distribution and compares natural and man‐made disasters. Data from the office of the US Foreign Disaster Assistance are used. The major natural hazards are drought, floods, cyclones, earthquakes and volcanoes. Major man‐made hazards are civil strife, displaced persons, food shortages and epidemics.
Somaye Fathalikhani, Ashkan Hafezalkotob and Roya Soltani
In the past two decades, the growth in the number and severity of disasters causes a rapid increase in the presence of NGOs for more effective response and efficient management of…
Abstract
Purpose
In the past two decades, the growth in the number and severity of disasters causes a rapid increase in the presence of NGOs for more effective response and efficient management of disasters. The NGOs must spend part of their resources on attracting funds to fulfill their humanitarian goals. However, limited number of donors and received contributions leads to a competition among NGOs for fundraising. Therefore, managing the relationship between these organizations and donors is very important. This paper aims to examine the competitive and coopetitive behavior of NGOs to model the interaction.
Design/methodology/approach
To achieve this purpose, by using game theory, two mathematical programing models are presented to examine the two inter-organizational interactions among NGOs.
Findings
The results show that if the NGOs work together, all the organizations, donors and affected people will benefit, and the accrued disaster will be managed more efficiently.
Practical implications
The expressed benefits of coopetition of NGOs can be an incentive for them to work together to manage disasters effectively.
Originality/value
To the best of authors’ knowledge, no research has considered the impact of the coopetition of NGOs in achieving their social mission successfully. Therefore, this paper can be seen as a valuable resource in this field.
Details