Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. / Page 136 blank. Cataloged from PDF version of thesis. / Includes bibliographical references (pages 129-135). / Foodborne illness outbreaks impose enormous health and economic burdens in the US. Identifying the origin of the contaminated food causing an outbreak is a challenging problem due to the complexity of the food supply and the absence of coherent labeling and distribution records. Current investigative methods are slow, resource intensive, and the overwhelming majority of investigations are unsuccessful in identifying the location source of an outbreak. New tools and approaches that take advantage of modern data and analytical techniques are needed to more quickly identify outbreak origins and prioritize response efforts. The practical objective of this work is to improve the food safety regulator's ability to efficiently locate the source of an outbreak while contamination-caused illnesses are occurring, thereby resolving investigations earlier and averting potential illnesses. This thesis develops new methods that leverage currently unutilized or underutilized sources of information to identify the location source of an outbreak. A novel, network-theoretic approach to source detection is developed that (1) immediately identifies all feasible source locations, (2) ranks the feasible locations by the likelihood that each one is the true source, and (3) develops a decision model for guiding investigators to implement effective interventions. The approach functions on food system network data, reported cases of illness at specific times and locations, and a prior probability function over likely sources. The methodology is the first to be designed specifically for tracing back outbreaks on food distribution networks. A Monte Carlo simulation environment was developed to evaluate traceback performance and robustness across a wide range of network structures and outbreak scenarios. When compared against existing traceback methods, both those currently in practice and those in academic literature, this methodology demonstrates significant improvements in accuracy, efficiency, and speed. Specific results suggest the approach can provide substantial benefits to the investigation process by identifying the source early enough in an outbreak's progression that a substantial fraction of cases of illness can be averted. These computational results serve as a powerful first step towards validating the accuracy and applicability of the approach. The immediate next step will be to demonstrate accuracy when applied to real food distribution networks. While acquiring representative network data for this purpose presents significant practical challenges, an additional contribution of this work is the identification of a representative network model that can be integrated with the source identification methodology, forming a holistic traceback framework. / by Abigail Lauren Horn. / Ph. D. in Engineering Systems

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 291-309). / This dissertation presents a method for estimating the tonnage and composition of non-hazardous industrial waste (NHIW) flows in the United States. For thirty years, it has been an accepted fact that NHIW is generated at a rate of 6.9 billion Mg per year, making it the largest waste flow in the country by more than an order of magnitude. However, this value was generated in 1985, has not been updated since, and is thought to account largely for the weight of dilute process water disposed in surface impoundments rather than solid waste generated by industry. To address this data gap, and lacking the resources to collect new, national-scale information, I propose an approach by which three independent estimates of NHIW generation based on existing data are used to corroborate each other at the industry sector level. The individual estimates are compared in triangulation so as to control for the errors, uncertainties and other validity concerns unique to each. The methods are: forecasting from historical waste accounts, modeling industrial materials flows to calculate lost mass, and up-scaling state-level data reported to the Pennsylvania Residual Waste Program. I apply the triangulation method to three industrial sectors for the year 2010, yielding estimates of (all in million Mg) 9.7-14.9 from pulp and paper, 21.2-24.7 from iron and steel, and 0.96-1.24 from petroleum refining. These values suggest that the total quantity of NHIW is measured in the hundreds of millions of Mg, not the billions as claimed by the prevailing EPA account. It therefore appears that NHIW generation rates are comparable to those of municipal solid waste. Accurate waste accounting based on reliable, repeatable, and efficient methods is an important tool for characterizing current environmental challenges and understanding trends and the effects of key drivers. Waste accounts are also essential for developing and tracking progress on sustainability strategies like industrial symbiosis, in which wastes like NHIW are used as substitutes for raw materials throughout the economy. The method developed here satisfies these needs and answers what has been an open question for nearly three decades. / by Jonathan Seth Krones. / Ph. D. in Engineering Systems

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 58). / Uganda is a developing country in East Africa that faces high poverty rates among a confluence of socio-political issues. In the pursuit of fiscal and political stability, international development organizations are working to create an environment in which business prospers and livelihoods are resilient. Agriculture, in particular, employs 75% of the population and accounts for 85% of Uganda's export earnings. However, many smallholder farmers experience volatile cashflows around crop cycles. Consequently, farmer livelihoods are vulnerable to uncertain growing conditions, market price fluctuations, and financial shocks, such as hospital bills or school fees. Subject to a high degree of uncertainty, it is difficult for farmers to improve their quality of life through agriculture alone. Agribusinesses--commodity traders in particular-are well positioned to help farmers access knowledge, goods, and services to increase yields and improve crop quality In some cases, provision of knowledge, goods, and services aligns with an agribusiness's regular profit-earning strategies. For example, some traders provide farmers with financing to purchase seeds and fertilizer at the beginning of the growing season; the farmer benefits from less cash volatility while the trader ensures crops will be available at harvest. This thesis explores the extent to which trader business strategies might be leveraged to mutually benefit agribusiness growth and farmer livelihoods. Specific goals were to identify common business strategies used by agricultural commodity traders and understand the mechanisms by which certain business strategies also benefit farmers. Semi-structured interviews and subsequent qualitative analysis shed light on the types of business strategies traders adopt. System dynamics modeling was then used to explain why certain strategies can be mutually beneficial. The combination of qualitative and quantitative methods yielded unique insight on ways mutually-beneficial behavior might be encouraged. / by Katherine R. Picchione. / S.M. in Technology and Policy

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. / Thesis: S.M. in Technology and Policy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 78-80). / The importance of public acceptance within the decision-making process for large-scale, municipal water projects is widely understood and documented. In order to assess the role of public perception on the acceptance of alternative water sources, this paper broadly evaluates public preference for alternative water source and water conservation programs through a user-based approach. Choice-based conjoint analysis was utilized as a quantitative method to determine which design attributes make alternative water sources, specifically desalination and recycled water facilities, more appealing to communities. An online survey was taken by 306 respondents in California, Florida, and Texas. Respondents were analyzed on an aggregate level to identify overall perception of, familiarity with, and preference for desalinated and recycled water. The results indicate significant importance placed on specific attributes such as cost and environmental impact, as opposed to the water program type and location of the proposed facility. Findings based on subpopulations of respondents suggest that preference between water program types were fairly consistent among different demographics, but varied on characteristics such as increased familiarity and perceived reliability of currently provided tap water. / by Janet H. Yun. / S.M. / S.M. in Technology and Policy

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references. / This thesis frames design in infrastructure public-private partnerships (P3s) as an exercise in negotiated collaboration. I investigate whether the collaborative design process in P3s can systematically deliver the benefits of innovation in design. The focus is on two aspects of the design process: project co-design, and collaboration mechanism. I find that both aspects enable innovation by driving project actors to learn about the design space and develop a shared understanding of the design problem. Learning through shared understanding not only improves quantifiable payoffs (Objective Value) but also enhances the actors' psycho-social outcomes (Subjective Value). Co-design is a process in which project actors simultaneously design technical and contractual features of a project. I developed a tradespace model to visualize and explore value trade-offs from co-design, using a desalination P3 as a project case. Co-design is a fundamental improvement over the traditional sequential design process because it reveals the zone of negotiated agreement, a frontier set of designs available to project actors, that can help them meet their own objectives while balancing value trade-offs. The combination of flexible modular designs and risk sharing revenue guarantee mechanisms emerged as a frontier design choice in the co-design analysis. Communication and common knowledge are two different collaboration mechanisms that affect the design choices of project actors. A controlled design experiment with 112 experienced designers tested the relative effects of these two mechanisms. The role-playing designers negotiated design decisions for a desalination P3 using the co-design tradespace model. Only the communication mechanism systematically shifted outcomes. To increase the reliability of meeting uncertain water demand, the firm traded away an expected net present value profit share of 24% (p<0.001) on average, subject to the parameter assumptions. The water authority increased contractual payments by an expected net present value share of 6.6% (p<0.001) on average. Final designs in the exercise were on average 97.5% reliable in meeting uncertain water demand. Communication dominated common knowledge as a collaboration mechanism because it enabled participants to learn about the effects of modularity and revenue guarantees on counter-party outcomes and use these design features to negotiate value trade-offs. Objective Value represents the technical (reliability) and economic (profits, payments) payoffs to project participants. Subjective Value on the other hand captures social psychological outcomes such as the degree of trust and rapport between collaborators and perceived fairness and legitimacy of the process, which are important for the partnering relationship. Participants in the collaboration experiment overwhelmingly reported high Subjective Value scores, which are positively correlated with both their improved understanding of the project's design objectives (r = 0.37, p = 0.41, p<0.001) and their ability to communicate with collaborators to agree on design choices (r = 0.36, p = 0.36, p = 0.001). This work directly addresses the literature on infrastructure public-private partnerships and shows how negotiated collaboration can create objective as well as psychosocial benefits for a stronger partnering relationship. The co-design approach speaks to the literature on systems design to emphasize how a systems view can help designers balance trade-offs. The experimental study is a methodological contribution to both the design and negotiations literature, applying the Subjective Value framework in an integrated design setting. / by Vivek A. Sakhrani / Ph. D. in Engineering Systems

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / This thesis takes an interdisciplinary look at wind energy innovation and diffusion through a historical case study and system dynamic quantitative model. The former uses a framework known as actor-network- theory (that allows technical as well social forces to shape historical outcomes) and applies it to an in-depth case study of the history of the technology throughout several époques. Rather than simplifying the story of the technology into a case of winners and losers, as past studies have done, this work demonstrates the complexity of the history of wind technology where many individuals in different countries, companies and national governments, all play a key role in both direct and indirect development of the technology. Without the confluence of activity from these different groups across time and space, the story of wind energy would be very different. In particular, the history shows how the technology develops and diffuses in different regions at different times in different eras, but that traces of each époque survive into the next so that the overall history of wind energy technology has some continuous threads and an accumulation of global learning. This perspective serves as a basis for the development of a system dynamics model of wind energy development and deployment. The model examines the interplay of technology innovation and diffusion dynamics where markets for the technology are local but innovation and learning is global. Wind energy for electricity generation has overcome significant volatility in local markets over the last several decades thanks to the global aggregation of demand from different countries at different times. At the same time, the persistent presence of a market somewhere in the world at any given time has allowed continuous innovation and technology learning to take place. Looking forward, these local and global feedbacks for innovation and diffusion have important implications for the further development of technology and its ability to become a prominent global source of electricity generation. / by Katherine Dykes. / Ph. D. in Engineering Systems

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 143-167). / Persistent and bioaccumulative toxins like mercury pose unique challenges for environmental governance. The complexity of their movement through coupled social, technological, and natural systems can make it difficult to trace their path from emissions to wider impacts, as emissions and impacts can be separated both in time and space. This separation can make it difficult to assess whether different management and policy proposals will effectively reduce negative impacts. Focusing primarily on mercury, this dissertation explores how we can use interdisciplinary tools and approaches-from atmospheric modelling to community engaged research-to better trace this path from policy to human impacts, in support of environmental decision-making at multiple levels of governance. Combining simulation modelling, statistical, and qualitative approaches, it considers three aspects of the path from policy to impacts: how policy translates into emissions changes, how emissions changes translate into changes in environmental concentrations and fluxes, and finally how these environmental concentrations and fluxes impact the well-being of human communities. Taken together, the three studies highlight the need to take into account how social, technical, and natural systems interact, as well as the uncertainty, variability, and pluralism that exist within them, in our efforts to manage these toxic pollutants. In the first study, I investigate the social and technical factors that affect the domestic implementation of a global environmental treaty (the United Nations Minamata Convention on Mercury) in major emitter countries in Asia, and their potential implications for emissions and global transport using a scenario-based modelling approach. I project that the benefit of avoided emissions and deposition over Asia are large, even when considering a scenario where the Convention allows large flexibility in implementation. These benefits are primarily driven by India, where even modest improvements in mercury capture are projected to result in large emissions decreases given future economic growth. I also find that climate change policies that promote the transitioning away from fossil may be as effective as strict end-of-pipe pollution control approaches for mitigating mercury emissions. In the second study, driven by interests from community research partners in the Great Lakes region-an area vulnerable to mercury pollution-I use chemical transport modelling experiments to explore the conditions under which regional and global policy change can be statistically detected by wet deposition monitoring networks. I find that, given the magnitude of expected emissions decreases, detecting policy-related decreases in wet deposition in the Great Lakes region on the decadal scale will be challenging as the magnitude of noise-in particular interannual meteorological variability-can exceed this signal. These results suggest that these variabilities need to be better quantified and taken into account in both the design of policies for effectiveness and evaluation of policy compliance. In the third study, I investigate the role that university-community partnerships can play in the long-term management of persistent pollutants through an empirical case study of the Superfund Research Program, which has recently required that grantees engage communities impacted by the hazardous substances that they study. I argue that community engagement in practice often supports a community building function-engagement operates as a space where knowledge about pollutants and shared identities of being impacted by these pollutants can be co-produced. Because persistent pollutants can implicate new people across time and space, often in ways that are difficult for those affected to discern, I suggest that supporting the constitution of what I call communities of concern is a critical way that university-based researchers can support the long-term management of persistent pollutants. I propose a conceptual framework to characterize and assess the functions that academic partners can perform in supporting the constitution of communities of concern around persistent pollutants. Further, I call attention to the institutional conditions that can enable this work to continue within academic contexts. / by Amanda Giang. / Ph. D. in Engineering Systems

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. / Some pages printed landscape orientation. Cataloged from PDF version of thesis. / Includes bibliographical references (pages 342-351). / This work proposes a merger of Tradespace Exploration with System Dynamics modeling techniques in a complementary approach. It tests the value of this mixed method for modeling the multiplicity of inputs and complexity of feedback loops that affect the cost, schedule and performance of satellite constellations within the Department of Defense. The resulting simulation enables direct comparison of the effect of changing architectural design points and policy choices with respect to satellite acquisitions and fielding. A generation-over-generation examination of policy choices is made possible through the application of soft systems modeling of experience and learning effects. The resulting model enables examination of possible futures given variations in assumptions about both internal and external forces on a satellite production pipeline. This thesis performs a policy analysis examining the current path of the Global Positioning System acquisition and compares it to equivalent position navigation and timing capability delivered through a variety of disaggregated options while varying: design lives, production quantities, non-recurring engineering and time between generations. The extensibility of this technique is investigated by adapting the model to the mission area of Weather and Climate Sensing. This thesis then performs a policy analysis examining different disaggregated approaches for the Joint Polar Satellite, focusing on the impact of complexity. Discussion of factors such as design choices, context variables, tuning variables, model execution and construction is also included. / by Paul A. La Tour. / Ph. D. in Engineering Systems

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2017. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / "June 2017." Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 237-247). / Intellectual property lock-in is a wicked problem particularly pervasive under monopsony market structures, such as the Department of Defense (DoD). However, little research exists on the mechanisms of action that induce intellectual property lock-in. This work postulates the conjuncture of architecture and intellectual property is one such mechanism of action and erects a research methodology to investigate this link. This dissertation began with a review of literature, which revealed more research is needed into basic trends or estimates of magnitude for intellectual property lock-in. To quantitatively frame the magnitude of the problem an investigation was conducted into all DoD contracts for the last eight fiscal years to establish bounds. These results were used to formulate a conceptual model of the problem and suggest the concept of intellectual property architecture, which is the conjuncture of architecture and intellectual property. To investigate links between intellectual property architecture and lock-in, an intermediate-N fuzzy-set Qualitative Comparative Analysis research approach was formulated and executed using 14 DoD software cases representing over 34 million lines of code. The model used three input conditions: high quality technical architecture, accessible intellectual property architecture, and unlimited rights to study the avoidance of lock-in. The fuzzy-set Qualitative Comparative Analysis concluded intellectual property architecture or unlimited rights were quasi-necessary conditions for the avoidance of lock-in. Additionally the model yielded both a five condition conservative expression and two condition parsimonious expression for sufficient conditions. From those expressions, this research concludes three direct findings. First, intellectual property architecture is an empirically supported mechanism of action for the avoidance of lock-in. Implying, intellectual property architecture, absent any other explanatory conditions, is sufficient to avoid lock-in. Second, the research herein finds evidence to support a novel taxonomy of intellectual property architectures. Allowing practitioners to understand potential trade-offs between architecture and intellectual property lock-in. Third, intellectual property architecture or unlimited rights is a theoretically supported expression for the avoidance of lock-in. This finding implies that as few as two conditions are required to understand whether a case may, or may not, avoid lock-in. / by Christopher W. Berardi. / Ph. D. in Engineering Systems

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 89-96). / As global manufacturing systems shift towards flexible and small-batch production, product developers and policy-makers have an opportunity to encourage more inclusive industrialization strategies. It is hypothesized that networks of informal-sector producers can provide an effective and ethical model for production; yet, due to a lack of research into these possibilities, both product developers and policy-makers are unaware of the latent potential. This thesis addresses the gap by analyzing a globally-competitive firm comprised of informal-sector producers, and making comparisons with other manufacturing models across both the developed and developing world. The author develops a categorization system for better understanding the costs and benefits of each model, and creates a framework to explain how new product developers evaluate key tradeoffs in making manufacturing decisions. The author then explores the prospect of creating a "virtual factory" of distributed microfactories through a case study of the ethical jewelry producer Soko in Nairobi, Kenya. Soko coordinates brass, horn, and bone jewelry production across 2500 craft microfactories, and its wares are cost-competitive with mid-tier jewelry brands in major retail stores worldwide. Soko's overall effectiveness is analyzed through quantitative analysis of the company's finances and impact reports, in-depth interviews with the company's co-founder, and field research in Nairobi. The tradeoffs inherent in Soko's production model are evaluated through the lens of the aforementioned decision-making framework. Key questions include, can artisanal microfactories compete with large-scale automation and industrialization? In what cases might smaller-scale production have an advantage over larger-scale models? Under the right circumstances, the case of Soko proves that networked microfactory production can be both cost-competitive (especially when handmade qualities are accentuated) and ethical; Soko creates opportunities for advancement across its network of artisans, who maintain ownership over their means of production. It is concluded that systems such as Soko's can provide a model for socially-inclusive production strategies that build upon informal infrastructure. Even if Soko itself only impacts a small number of full-time artisans, a series of ethical, aggregating producers like Soko could collectively provide a larger-scale benefit. / by Anna Waldman-Brown. / S.M. in Technology and Policy