<p> The scholarly research on emergency supply chain management acknowledges its inherent significance in efficacious disaster response, however, what is unknown is how to employ alternative means of transportation, specifically hybrid airships, to deliver relief aid direct to a point of need amidst a lack of intact infrastructure following disaster. The purpose of this study was to investigate subject matter expert opinions to determine the level of consensus on how to apply the innovative transportation mode of hybrid airships to emergency supply chain management through delivery of emergency supplies direct to a point of need despite a lack of intact infrastructure following a disaster event. It addresses the following research question: How do subject matter experts envision effective employment of hybrid airships in emergency supply chain management within the United States? This research was a qualitative, Type 2 case study of Hurricane Sandy utilizing the examination of publicly available documents and focused interviews. The interview sample was a criterion-based selection of subject matter experts who participated in the logistical response to Hurricane Sandy, and the sample of documents were obtained from the Federal Emergency Management Agency (FEMA). Qualitative data analysis was used to identify and interpret themes throughout the data, and content clouds were specificity used to assist in visualizing interview transcript data. The consensus among subject matter experts is that hybrid airship application to emergency supply chain management should commence via a FEMA initiative to preposition the craft regionally throughout FEMA zones. Future research should address integration challenges through a Delphi study to poll a broader range of subject matter experts to refine consensus on hybrid airship employment in disaster logistics.</p><p>
Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10747168 |
Date | 05 June 2018 |
Creators | Lynch, Sarah R. |
Publisher | Capella University |
Source Sets | ProQuest.com |
Language | English |
Detected Language | English |
Type | thesis |
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