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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 reduced uncertainty. This paper seeks to explore this phenomenon using

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.
ContributorsYoo, Eunae (Author) / Maltz, Arnold (Thesis director) / Pfund, Michele (Committee member) / Fowler, John (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor)
Created2013-05