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<title>Engineering Systems - Ph.D. / Sc.D.</title>
<link>http://hdl.handle.net/1721.1/7885</link>
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<dc:date>2013-05-20T11:53:40Z</dc:date>
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<title>The MQ-9 Reaper remotely piloted aircraft : humans and machines in action</title>
<link>http://hdl.handle.net/1721.1/78515</link>
<description>The MQ-9 Reaper remotely piloted aircraft : humans and machines in action
Cullen, Timothy M
Remotely piloted aircraft and the people that control them are changing how the US military operates aircraft and those who fly, yet few know what "drone" operators actually do, why they do what they do, or how they shape and reflect remote air warfare and human-machine relationships. What do the remote operators and intelligence personnel know during missions to "protect and avenge" coalition forces in Iraq and Afghanistan and how do they go about knowing what they know? In an ethnographic and historical analysis of the Air Force's preeminent weapon system for the counterinsurgencies in the two countries, this study describes how social, technical, and cognitive factors mutually constitute remote air operations in war. Armed with perspectives and methods developed in the fields of the history of technology, sociology of technology, and cognitive anthropology, the author, an Air Force fighter pilot, describes how distributed crews represent, transform, and propagate information to find and kill targets and traces the observed human and machine interactions to policy assumptions, professional identities, employment concepts, and technical tools. In doing so, he shows how the people, practices, and machines associated with remotely piloted aircraft have been oriented to and conditioned by trust in automation, experience, skill, and social interactions and how they have influenced and reflected the evolving operational environment, encompassing organizations, and communities of practice.
Thesis (Ph. D. in Technology, Management, and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology, Management, and Policy Program, 2011.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 290-298).
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<dc:date>2011-01-01T05:00:00Z</dc:date>
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<title>Influencing managerial cognition and decisions using scenarios for long-range planning</title>
<link>http://hdl.handle.net/1721.1/78483</link>
<description>Influencing managerial cognition and decisions using scenarios for long-range planning
Phadnis, Shardul Sharad, 1978-
This dissertation presents empirical findings related to two aspects of long-range planning: scenario planning as a planning method and cognition of planners. Long-range planning situations are encountered when designing public infrastructures (e.g. transportation systems) as well as developing strategies for corporate enterprises (e.g. firms' supply chains), due to the long implementation times and/or long lives of the invested assets. Such investments tend to have high stakes, face extreme uncertainty about the future environment they encounter, and have an open-systems nature as the implementation and operation of assets affects and is affected by the actions of many and diverse stakeholders. Three research questions pertaining to these aspects are answered in this work as three stand-alone studies. The first study (Chapter 2) examines the effects of scenario planning on long-range investment decisions made by field experts. The results of three field experiments show that experts systematically change their investment decisions and/or their confidence in them after evaluating the investments in a scenario. Field experts are also more likely to invest in flexible strategies after being exposed to multiple scenarios. The second study (Chapter 3) presents an extensive and an abridged version of the scenario creation process. Instead of seeing scenario-creation as an art, this research provides two versions of a more engineered scenario-creation process, and demonstrates their application in two separate field studies. Both versions of the process are presented with detailed instructions and rationale for performing each step. This study also provides clear definitions of the terms used in the process description and grounds them in the organizations literature. The third study (Chapter 4) explores the relationship between a manager's perceptions and beliefs about future environment, and the strategies s/he recommends. Using a prospective research design, this study first tests three hypotheses about general characteristics of managerial cognition. A closer look at different cognitive types in this data reveals unsuspected patterns in strategic thinking of managers of different types. A typology of managerial cognition is built using this inherent variation. Inductive analysis shows that managers of different cognitive types envision strikingly different types of strategies.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 209-222).
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<dc:date>2012-01-01T05:00:00Z</dc:date>
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<title>Human and modeling approaches for humanitarian transportation planning</title>
<link>http://hdl.handle.net/1721.1/78482</link>
<description>Human and modeling approaches for humanitarian transportation planning
Gralla, Erica Lynn
Recent disasters have highlighted the need for more effective supply chain management during emergency response. Planning and prioritizing the use of trucks and helicopters to transport humanitarian aid to affected communities is a key logistics challenge. This dissertation explores ways to improve humanitarian transportation planning by building on the strengths of both humans and models. The changing, urgent, multi-objective context of humanitarian aid makes it challenging to formulate and deploy useful planning models. Humans are better able to understand the context, but struggle with the complexity of the problem. This research investigates the strengths and weaknesses of human transportation planners in comparison with models, with the goal of supporting both- better human decision-making and better models for humanitarian transportation planning. Chapter 2 investigates how experienced humanitarian logisticians build transportation plans in a simulated emergency response. Based on an ethnographic study of ten logistics response teams, I show how humans come to understand the problem and its objectives through sensemaking, and solve it through a search-like series of decisions guided by goal-oriented decision rules. I find that the definition of objectives is an important strength of the sensemaking process, and that the human reliance on greedy search may be a weakness of human problem-solving. Chapter 3 defines a performance measure for humanitarian transportation plans, by measuring the importance of the objectives identified in the ethnographic study. I use a conjoint analysis survey of expert humanitarian logisticians to quantify the importance of each objective and develop a utility function to value the performance of aid delivery plans. The results show that the amount of cargo delivered is the most important objective and cost the least; experts prefer to prioritize vulnerable communities and critical commodities, but not to the exclusion of others. Chapter 4 investigates the performance of human decision-making approaches in comparison to optimization models. The human decision-making processes found in Chapter 2 are modeled as heuristic algorithms and compared to a mixed-integer linear program. Results show that optimization models create better transportation plans, but that human decision processes could be nearly as effective if implemented consistently with the right decision rules.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references.
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<dc:date>2012-01-01T05:00:00Z</dc:date>
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<title>Measuring supply chain carbon efficiency : a carbon label framework</title>
<link>http://hdl.handle.net/1721.1/78481</link>
<description>Measuring supply chain carbon efficiency : a carbon label framework
Craig, Anthony (Anthony J.)
In the near term, efficiency improvements represent a key option for reducing the impacts of climate change. The growing awareness of climate change has increased the attention regarding the carbon emissions "embedded" in the products we consume. This increased attention creates a need to measure and improve the carbon efficiency of the supply chains that produce those goods. In this thesis we present a method for measuring the carbon efficiency of a supply chain that recognizes the decentralized nature of supply chains. First, drawing from concepts in supply chain performance measurement and eco-efficiency we propose a definition of supply chain carbon efficiency that is consistent with the idea of a product's carbon footprint. We present Life Cycle Assessment (LCA), a method for quantifying the environmental impact of a product or service, as the appropriate method of measuring a product's carbon footprint and demonstrate the use of LCA through a case study involving the supply chain of bananas. Next, we characterize the difficulty and uncertainty in performing an LCA of a supply chain through an analysis of our case study of bananas. We present a framework to reduce the uncertainty though the concept of a carbon label. The carbon label provides a system where firms can measure the carbon footprint of their activities and share this information with their supply chain partners. We identify the role of third parties in facilitating information sharing and define the characteristics that describe the carbon label. Finally, we demonstrate how the carbon label works in the context of the supply chain. Through an analysis of the mode and carrier assignment steps in an integrated supply chain we develop new metrics that show how sharing information can increase the accuracy of the measured carbon footprint and improve decision-making. We provide incentive for firms to share information through the development of a vertical differentiation model of product carbon labels. Our model shows how consumer demand for lower carbon products drives reductions in the carbon footprint throughout the supply chain and induces firms to voluntarily disclose their carbon footprint.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 273-293).
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<dc:date>2012-01-01T05:00:00Z</dc:date>
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