| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | July 14, 2014 |
| Latest Amendment Date: | January 30, 2018 |
| Award Number: | 1363513 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Joy Pauschke
jpauschk@nsf.gov (703)292-7024 CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | July 15, 2014 |
| End Date: | June 30, 2019 (Estimated) |
| Total Intended Award Amount: | $376,988.00 |
| Total Awarded Amount to Date: | $376,988.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
110 8TH ST TROY NY US 12180-3590 (518)276-6000 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
NY US 12180-3522 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | HDBE-Humans, Disasters, and th |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The domain of this work - post-disaster debris removal operations - has become a focal concern for both Federal and state governments as the threat of extreme wind events (such as hurricanes and tornadoes) has extended to areas outside the southeast United States. Rapid and efficient debris removal is the first step toward successful recovery from disasters. This work will marshal data associated with debris removal following a recent large-scale tornado storm in Alabama to investigate these phenomena. This work is expected to benefit society by contributing to its ability to plan for and respond to large-scale disasters, particularly by improving understanding of the determinants of debris removal performance. In particular, it should develop models and lessens that will speed up the recovery process and make communities more resilient to disaster impacts. It will advance discovery while promoting learning by developing educational materials which will be integrated into undergraduate- and graduate-level course work, as well as into materials for practicing professionals. It will broaden participation of under-represented groups through their inclusion in the research team and enhance research infrastructure through the creation of data sets and analytic tools for use by other researchers. Results of this work will be broadly disseminated through publications and presentations in academic and practitioner venues, to include seminars organized to introduce new tools and techniques to the practice of debris management.
The central goal of this research is to extend and test theories that link team-level phenomena to organizational outcomes. The central focus is upon debris removal teams. A particular thrust of this work is on developing and evaluating new theory and methodologies to investigate (i) team-level phenomena that link team composition to team performance, and (ii) reciprocal relationships from team-level phenomena to organizational-level outcomes. To do so, it will extend current methodological approaches for examining these relationships within and across team and organizational levels. It will also explicitly model tradeoffs among different aspects of performance (effectiveness, efficiency and equality) in relation to team and organizational composition. This work benefits from access to a wealth of data associated with debris removal operations (including transactional records of every load of debris hauled by every team during this operation), as well as access to subject matter experts. A distinguishing feature of this research is its use of process-level data on team members and the work they perform. Validation will be undertaken from multiple perspectives, ranging from consultation with subject matter experts to archival research and classical statistical methods such as holdout samples.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The removal of debris following events such as large-scale hurricanes and tornado storms is a costly, time-consuming and persistent enterprise in the United States and in many other countries. Debris removal is vital to economic recovery and, in general, to the quality of life of those impacted by debris-inducing events. However, the size and scope of debris removal missions can render them difficult to control, monitor and assess--issues which have led to the deployment of large-scale tracking systems and other measures.
Through extensive partnerships with practice based on data from a series of tornadoes in Alabama in 2011, work under this grant has combined tracking data with advanced modeling and simulation techniques to yield implications in three broad areas. First, there is considerable variation in team and organizational performance over the lifetime of the mission, suggesting the need to monitor and control variability to improve overall performance. Second, computer-based simulations suggest that market-based control policies which are simpler than those used for this mission may yield better, less costly results. Third, further instrumentation of similar missions ought to yield even more robust models for managing and evaluating mission performance.
These implications area derived from fundamental advances in three areas. First, the use of objective and detailed operational data represents a paradigm change in the study of team-centered organizations, allowing questions of dynamics and control to be addressed in ways that questionnaire-based methods cannot support. Second, the research combines model- and data-driven approaches to yield validated models of system response to dispatcher behaviors, which in turn allows exploration of counterfactual policies of control (similar explorations would be prohibitively expensive in field settings). Third, it brings a wide array of advanced methodological approaches to bear in modeling the linkages from team-level behavior to organizational-level performance over time, again opening up an important frontier in the study of teams within organizations.
Last Modified: 02/07/2020
Modified by: David Mendonca
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