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. / There is no definitive blueprint for ending poverty and increasing prosperity across the globe, but the World Bank argues that inclusive economic growth is critical to achieving global development goals. This thesis focuses on supply chain financing, and its potential to make a positive and lasting impact on people and businesses in resource-constrained environments. It seeks to develop a better understanding of how supply chain and finance structures impact profits, sales growth and risk. The two-phased research design seeks to address the gap in the supply chain and development literature on supply chain finance in small and medium sized firms in developing countries. The first phase consists of exploratory, semi-structured interviews with stakeholders in international development, financing and supply chain management. The exploratory interviews were used to develop an understanding of how relevant stakeholders think about and make supply chain finance decisions. Additionally, the interviews were used to identify a company and supply chain for a multiple case study upon which the second phase of research is based. The company is a clean energy product distributor that has partnered with one of the largest banks in Kenya to provide consumer financing for clean energy products. The case analysis includes an in-depth examination of the company's financial performance by sales channel, drawing upon sales records and accounting documents. Interviews were conducted with the company's management, suppliers, sales force, retailers and bank lending agents. The mixed methods case study is used to extend hypotheses developed during the exploratory interviews and further develop theory on the role of financing in developing country supply chains. The exploratory interviews and case study are used to develop a framework of how stakeholders in consumer durable goods markets think about scale in developing countries. The World Bank's Logistics Performance Index (LPI) and Doing Business Report (DBR) data sets are used to demonstrate how organizations can base supply chain decisions on infrastructure, logistics and governance structures within a country. This research can be used by for-profit and not-for-profit entities when making resource allocation and supply chain design decisions in developing markets. / by Timothy W. Breitbach. / 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 408-417). / Established companies in technology-enabled industries such as software, telecommunications, pharmaceuticals, and semiconductors, have used corporate venture capital as a lever to access and screen technological advances, and to drive innovation outside the traditional firm boundaries. Recent years have witnessed emergence of a new wave of corporate venture capital funds that increasingly interact and compete with traditional venture capital firms in the entrepreneurial ecosystem. The incremental benefits of financing a startup through corporate venture capital have been a subject of study by researchers across Economics, Finance, Strategy, and Innovation fields. First, this thesis examines entrepreneurs' rationale for raising capital from corporate investors. Through the analysis of an online survey conducted with startups based in the US and founded between 2010-15, we identify that startups that operate in capital-intensive industries, such as life sciences and manufacturing, raise capital from corporate investors in order to establish strategic partnership with corporates, significantly more than do startups in capital-light industries such as enterprise and consumer software. Second, through an empirical analysis of a panel of 8,190 startups founded in the US between 2000-10, this thesis shows that corporate venture capital is more beneficial to startups that operate in capital-intensive industries. Using a bi-variate probit model, this thesis shows that startups backed by corporate venture capital are more likely to be acquired or go public, and that the likelihood of an exit event increases as capital-intensity of the industry magnifies, as measured by the level of fixed assets on companies' balance sheets. In addition, we provide empirical evidence that participation of corporate venture capital in a financing round, helps a capital-intensive startup to raise further funding from reputable traditional venture capital firms. Third, this thesis presents empirical evidence that establishing strategic collaboration between capital-intensive startups and corporate parents of venture capital firms, in forms of joint research, product development, or commercialization, is a main source of value for startups. Using data gathered on 130 corporate news announcements on strategic collaborations, this thesis shows that capital-intensive startups backed by corporate venture capital, are significantly more likely to succeed when they establish strategic collaboration with corporate parents. The final contribution of this thesis is a formal assessment of traditional venture capital firms' investment behavior in presence of corporate investors. We present a game-theoretic model and identify the circumstances under which traditional venture capital firms benefit financially from corporate investors participation in financing a capital-intensive startup. By leveraging data gathered on 8,190 startups, we apply the game-theoretic model and Monte-Carlo method to simulate financial returns for a traditional venture capital firm investing a capital-intensive startup in the pharmaceutical industry. / by Ali Farahanchi. / 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 281-313). / Power pools can reduce the cost of providing electricity and improve system reliability through coordinated use of energy resources. Realizing these benefits requires careful market design supported by technical, economic and institutional analysis of the system as it exists today and as it will likely evolve in the future. In this dissertation, I demonstrate this integrated approach through a detailed study of the design and operation of the Southern African Power Pool (SAPP). I develop a linear programming model of the SAPP system that explicitly represents hourly system operations to conduct this analysis. This model is then adapted through the addition of new input parameters or linear constraints to investigate different market design questions including how to implement bilateral contracts in the wholesale market and allocate costs for regional transmission investments. I also examine the design of regional institutions and their role to promote efficient investments and market behavior. The primary contributions from this work include a new method to design and incorporate security-motivated bilateral contracts into wholesale markets using Implicit Auctions with Security of Supply Guarantees; a regulatory framework for transmission planning and cost allocation designed specifically for supranational regional markets; a quantitative comparison of transmission pricing methods leading to recommendations to apply Beneficiary Pays for new lines and Average Participations for existing lines; recommended adjustments to transmission regulation to facilitate increased penetrations of renewable energy; and a proposed design for the regional regulator. I also identify several unique features of developing country power systems that may influence market design. Other markets in Africa, Asia and Central America contain similar technical and institutional characteristics that can lead to similar market challenges. The specific market rules and implementation steps developed for the SAPP may not apply in all regions but the integrated approach used in this thesis, combining technical models and institutional analysis to support regulatory decisions, could be generalized to other regional electricity markets. / by Amy Michelle Rose. / Ph. D. in Engineering Systems

Thesis: S.M. 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 (pages 79-82). / The automotive industry has been observing a trend of integrating new features into old vehicle designs to provide more convenience and flexibility to customers. However, it can be challenging to ensure safety without the support of appropriate techniques and tools for hazard analysis and requirement engineering. Systems Theoretic Process Analysis (STPA) is a hazard analysis technique that has been developed at MIT. It is based on systems and control theory and aims at capturing more causal factors leading to accidents, including component interactions. So far, STPA has been successfully applied to various industries. While there are tools that allow engineers to document the results of hazard analysis based on STPA, there are no tools that provide guidance during the analysis. Also, although a method is proposed to generate requirements from an STPA analysis, no tools have been developed to support that process. This thesis illustrates how tools can provide support for hazard analysis and requirement generation based on STPA, based on the proof of concept of a software tool that was developed at MIT. This STPA tool assists STPA Step I analysis by applying logical simplification to the original Step I results and automatically generating the simplified requirement in formal and executable forms. The simplified requirements are easily understandable and address all of the unsafe control actions identified in the original STPA analysis. The use of the STPA tool is illustrated through a case study of automotive systems that include multiple features. The STPA tool generates simplified and formal requirements for each individual feature based on STPA Step I results. In addition, it is also used to check whether conflicts between features have been resolved and to identify exactly what decisions should be made jointly between multiple design teams. / by Dajiang Suo. / S.M. in Engineering Systems

Thesis: M.C.P., Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2018. / Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2018.. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 91-93). / NGOs are an important actor in rural India, and are increasingly important in implementing water and sanitation infrastructure. This thesis first systematically investigates physical conditions that lead to good bacteriological water quality in rural India, and then investigates how NGOs are inserting themselves into this space. Ultimately, this work examines under what conditions NGOs are effective in advancing water and sanitation systems, with a focus on how they build up, empower, and utilize local community organizations to do so. Thus, the strategies of two NGOs working in rural India that have facilitated the implementation of water and sanitation infrastructure are analyzed using an extension of Field Theory by Asad & Kay (2014). The way these NGOs create alliances, use resources, and change frames to advance water and sanitation infrastructure are similar in some ways, while distinct in others. This analysis demonstrates that these organizations are able to harmonize and negotiate their development agenda with that of the state in order to make progress in water and sanitation systems. Combining a systems analysis of rural communities' water quality with an analysis of strategies of NGOs illuminates practical implications for how policymakers can expect these organizations to incorporate new technologies and policies. / by Sydney Brooks Beasley. / M.C.P. / 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, 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 99-109). / Photovoltaics (PV) have experienced notable development over the last forty years. PV module costs have declined 20% on average with every doubling of cumulative capacity, while global PV installations have increased at an average rate of 30% per year. However, costs must fall even further if PV is to achieve cost-competitiveness at high penetration levels and in a wide range of locations. Understanding the mechanisms that underlie the past cost evolution of PV can help sustain its pace of improvement in the future. This thesis explores the drivers of and constraints to cost reduction and large-scale deployment of PV. By developing novel conceptual and mathematical models, we address the following questions: (1) What caused PV's cost to fall with time? (2) How may materials constraints influence PV cost and deployment? These questions are addressed in the analyses presented in Chapters 2-4. Chapter 2 assesses the causes of cost reduction observed in PV modules since 1980. We develop a new model that identifies the causes of improvement at the engineering level and links these to higher-level mechanisms such as economies of scale. The methodology advanced can be used to evaluate the causes of improvements in any technology. By developing a model of PV modules, we find that in the early stages of the technology (1980-2001), improvements in the material usage and module conversion efficiency played an important role in reducing module cost. These improvements were mainly driven by research and development (R&D) efforts. As the PV technology matured (2001-2012), economies of scale from larger manufacturing plants resulted in significant gains. Both market-expansion policies and public R&D stimulated cost reduction, with the former contributing the majority of the cost decline from 1980 to 2012. Chapter 3 turns to assessing the materials constraints to PV cost reduction. We ask how fast metals production should be scaled up to match the increasing demand by the PV sector, if installations grow to meet a significant portion of energy demand. Unlike previous studies, which primarily used inherently uncertain factors such as reserves to estimate limits to technology scalability, we use past growth rates of a large set of metals as a benchmark for future growth rates. This analysis shows that thin-film PV technologies such as CIGS and CdTe that employ rare metals would require unprecedented growth rates in metals production even for the most conservative PV growth scenarios. On the other hand, crystalline silicon PV can provide 100% of global electricity without silicon exceeding the historical growth rates observed by all metals in the periodic table. Chapter 4 assesses the risks that material inputs bring to technologies today. This study develops cost-riskiness metrics based on the price behavior of metals along two dimensions: average price and price volatility. We first compare a large set of metals using these cost-riskiness metrics. We observe that metals obtained as byproducts have higher risk than major metals. We then apply these metrics to different PV technologies by treating them as a portfolio of metals. We find that designs such as CIGS and CdTe, which use byproduct metals with high average prices and price volatilities, show signals of cost-riskiness. The approach advanced here can serve as an assessment of the cost-riskiness of technologies introduced by their materials inputs. / by Goksin Kavlak. / 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 (pages 127-134). / Low-and-Middle Income Countries (LMICs) are experiencing a growing need for safe, effective, and affordable health services, especially medicines. Such trends are in part due to a continued epidemiologic transition from infectious to chronic, non-communicable diseases (NCDs). Today, NCDs account for a large portion of total global disease burden: 70% of deaths as per the World Health Organization (WHO). NCDs are projected to continue to undercut economic productivity and drive up health spending. Many NCDs are effectively treated using biologic therapies; or large molecules produced by, or involving, living cells. Recently, some of these therapies have been included on the WHO Model List of Essential Medicines. However, the molecular, manufacturing, regulatory, and supply chain features of biologics lead to relatively higher costs and complexity compared to small-molecule drugs, with implications on widespread access. As part of the Global Action Plan for the Prevention and Control of NCDs 2013-2020, an 80% target for global availability of affordable essential medicines has been set for all public and private providers. In order to reach this target, there is need to better understand the complex barriers to accessing biologics across the biopharmaceutical value chain. Current gaps in access indicate the potential need to re-orient the biopharmaceutical system in order to meet future projected healthcare demand in terms of quantity, quality, and affordability. There is also growing uncertainty within the biopharmaceutical ecosystem as to the best use of resources, design of policies, and development of technologies that will have the most cost-effective impact on maximizing the supply of and access to such biologics. This research specifically focuses on the manufacturing component of biologics access, providing an analysis of the benefits and risks across different production networks, with varying number and location of facilities. A cost modeling tool is presented for quantitatively analyzing different manufacturing design options. This is accomplished by comparing the cost of good (COGs) and net present cost (NPC) of different scenarios, using Trastuzumab (a monoclonal antibody drug used to treat HER-2+ breast cancer) as a case study. Finally, future research questions are presented, aimed at better understanding the drivers of variability in manufacturing cost across manufacturing networks, especially when considering differences in product type, locations, regulatory jurisdictions, geopolitical zones, and sociocultural norms. In light of changing global health patterns and increasing demand for quality, affordable care, the thesis presents tools that can be generalized for addressing tradeoffs, short-and- long term effects, and intended-and-unintended consequences of investments in global health. It holds the potential for assessing the potential impact of various innovations (policies, technologies, organizational structures and more) on complex, dynamic systems and provide an evidence-base to better inform future areas of research, design of policies, and development of technologies. / by Donovan G. Guttieres. / S.M. in Technology and Policy

Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2015. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 72-97). / In 2012, President Obama signed an Executive Order to improve access to mental health service for active duty members and for veterans. Two years later, in 2014, the President outlined 19 new executive actions to improve the lives of service members with a focus on improving access to mental health care. These actions placed a priority on improving the capacity to provide mental health care. This thesis examines ways of improving the capacity of the mental health system with a focus on system redesign. I review capacity planning, provide a literature review of simulation methods and present a simulation, and data analysis of Site Alpha, a U.S. Army Installation. I also use causal loop diagrams to explore other feasible scenarios that affect care capacity. The key take-away from this work is that system inefficiencies should be dealt with before more resources can be effectively added and used in the system. Another pertinent finding is that the distribution of the providers in the system should be improved. The system also contains high utilizer patients who must be considered when planning for care. The mental health system is extremely complex and risks becoming even more complex. However, by adopting a holistic, systems approach to capacity planning the complexity can be managed. / by Melvis Ngemasong Ngimndoh Chafac. / S.M. in Engineering Systems

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