Embedded analytics: improving decision support for humanitarian logistics operations

被引:28
|
作者
Griffith, Daniel A. [1 ]
Boehmke, Bradley [1 ]
Bradley, Randy V. [2 ]
Hazen, Benjamin T. [1 ]
Johnson, Alan W. [1 ]
机构
[1] US Air Force, Dept Operat Sci, Inst Technol, 2950 Hobson Way, Wright Patterson AFB, OH 45433 USA
[2] Univ Tennessee, Dept Mkt & Supply Chain Management, 304 Stokely Management Ctr,916 Volunteer Blvd, Knoxville, TN 37996 USA
关键词
Business analytics; Big data analytics; Humanitarian logistics; Decision tree; Embedded analytics; Data science; SUPPLY CHAIN MANAGEMENT; BIG DATA; PREDICTIVE ANALYTICS; DATA SCIENCE; EMERGENCY; TECHNOLOGIES; CHALLENGES; MODEL; AID;
D O I
10.1007/s10479-017-2607-z
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Analytical techniques continue to advance in efficacy, as well as complexity. However, it is sometimes unrealistic to employ complex analyses during time-constrained humanitarian disaster operations. We propose that simple, embedded analytics tools can provide an effective and practical means toward managing humanitarian operations. In this paper, we demonstrate a real-world application of our technique in a patient evacuation context. This paper contributes to literature and practice by showing how simple analytic methods and open-source imagery tools can offer significant value to the humanitarian operations literature. The application also highlights some challenges to drawing a clear picture from disparate data sources in the humanitarian operations domain.
引用
收藏
页码:247 / 265
页数:19
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