Matching Items (2)

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Finding the Best Fit to Maximize Responsiveness in Humanitarian Logistics: An Information Processing Perspective

Description

Within humanitarian logistics, there has been a growing trend of adopting information systems to enhance the responsiveness of aid delivery. By utilizing such technology, organizations are able to take advantage of information sharing and its benefits, including improved coordination and

Within humanitarian logistics, there has been a growing trend of adopting information systems to enhance the responsiveness of aid delivery. By utilizing such technology, organizations are able to take advantage of information sharing and its benefits, including improved coordination and reduced uncertainty. This paper seeks to explore this phenomenon using organizational information processing theory. Drawing from complexity literature, we argue that demand complexity should have a positive relationship with information sharing. Moreover, higher levels of information sharing should generate higher responsiveness. Lastly, we examine the effects of organizational structure on the relationship between information sharing and responsiveness. We posit that the degree of centralization will have a positive moderation effect on the aforementioned relationship. The paper then describes the methodology planned to test these hypotheses. We will design a case-based simulation that will incorporate current disaster situations and parameters experienced by Community Preparedness Exercise and Fair (COMPEF), which acts as a broker for the City of Tempe and various humanitarian groups. With the case-based simulation data, we will draw theoretical and managerial implications for the field of humanitarian logistics.

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Date Created
2013-05

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Dynamics of information distribution on social media platforms during disasters

Description

When preparing for and responding to disasters, humanitarian organizations must run effective and efficient supply chains to deliver the resources needed by the affected population. The management of humanitarian supply chains include coordinating the flows of goods, finances, and information.

When preparing for and responding to disasters, humanitarian organizations must run effective and efficient supply chains to deliver the resources needed by the affected population. The management of humanitarian supply chains include coordinating the flows of goods, finances, and information. This dissertation examines how humanitarian organizations can improve the distribution of information, which is critical for the planning and coordination of the other two flows. Specifically, I study the diffusion of information on social media platforms since such platforms have emerged as useful communication tools for humanitarian organizations during times of crisis.

In the first chapter, I identify several factors that affect how quickly information spreads on social media platforms. I utilized Twitter data from Hurricane Sandy, and the results indicate that the timing of information release and the influence of the content’s author determine information diffusion speed. The second chapter of this dissertation builds directly on the first study by also evaluating the rate at which social media content diffuses. A piece of content does not diffuse in isolation but, rather, coexists with other content on the same social media platform. After analyzing Twitter data from four distinct crises, the results indicate that other content’s diffusion often dampens a specific post’s diffusion speed. This is important for humanitarian organizations to recognize and carries implications for how they can coordinate with other organizations to avoid inhibiting the propagation of each other’s social media content. Finally, a user’s followers on social media platforms represent the user’s direct audience. The larger the user’s follower base, the more easily the same user can extensively broadcast information. Therefore, I study what drives the growth of humanitarian organizations’ follower bases during times of normalcy and emergency using Twitter data from one week before and one week after the 2016 Ecuador earthquake.

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Created

Date Created
2018