Economics and Finance
The economics of transportation are incredibly complex; small changes in pricing and efficiency can have substantial ramifications on behavior. Transportation infrastructure projects are among the biggest public investments that we make. How should we fund public transit? What are the impacts of congestion pricing? How can we encourage coordination between ridesharing platforms? MIT researchers are exploring the answers to these important questions and more.
The research labs and faculty working in this area are shown below. You can see a full listing of the people and labs involved with the MIT Mobility Initiative by navigating to the people page and the labs page.
The Auto-ID Labs are the leading global research network of academic laboratories in the field of Internet of Things. The labs comprise seven of the world’s most renowned research universities located on four different continents. The labs believe that the next generation of the Internet of Things can revolutionize global commerce and provide previously unrealizable consumer benefits. The primary research partner is GS1 – a not-for-profit organization that is renowned for establishing standards for global commerce such as introducing barcodes to the retail industry almost 40 years ago.
Center for Real Estate, and Sustainable Urbanization Lab
The goal of the Sustainable Urbanization Lab (SUL) is to establish behavioral foundations for urban and environmental planning and policies aimed at sustainable urbanization in the most rapidly urbanizing regions of the world.
The SUL will be defined by three ‘blocks’: two of which are inter-related research themes: Environmental Sustainability and Place-based Policies and Self-Sustaining Urban Growth; the third block, an educational program the China Future City Program, will continue to serve as the teaching and research center of China’s urbanization on MIT campus.
Center for Transportation and Logistics
For more than four decades, the MIT Center for Transportation & Logistics (MIT CTL) has been a world leader in supply chain management education and research. MIT CTL has made significant contributions to supply chain and logistics and has helped numerous companies gain competitive advantage from its cutting-edge research. Launched in 1973, the MIT Center for Transportation & Logistics (CTL) is a dynamic solutions-oriented environment where students, faculty, and industry leaders pool their knowledge and experience to advance supply chain education and research.
Connection Science Living Labs
With its novel "Living Labs" paradigm for research in the field, MIT Connection Science brings together interdisciplinary experts to develop, deploy, and test - in actual living environments - new technologies and strategies for safe, trusted, data sharing. MIT is well positioned to take a leadership role in demonstrating not only how organizations can leverage data in the future, but how we collect, manage, and use personal information, from setting appropriate privacy policies to demonstrating systems that can implement it in practice.
Electric Aircraft Initiative
The MIT Electric Aircraft Initiative draws together efforts across MIT aimed at long-term research on electric aircraft. Research spans fundamental propulsion technology development for small drones through to overall aircraft configuration assessment for all-electric commercial aircraft. The focus is on the very long term: technologies that could result in near-silent propulsion and low or no emissions. You can learn more about the overall research areas or read our publications.
MIT’s Energy at Scale Center seeks to address the massive scaling requirements necessary for low-carbon technologies to make a substantial contribution to future global energy needs, in collaboration with industry, government, and nonprofit members. We examine economic, technical, environmental, political, and public opinion barriers for deployment. We explore these risks using our Integrated Global System Modeling (IGSM) framework that combines the Economic Projection and Policy Analysis (EPPA) model, MIT Earth System Model (MESM), as well as a portfolio of impact assessment models that focus on life‑sustaining resources (e.g., managed water systems, crop production, ecosystem/forest services, wind/solar/hydropower, and air quality). These linked computer models allow us to analyze a wide range of development pathways in the global energy, agricultural, transportation, and other key sectors.
Future Urban Mobility at SMART
The Future Urban Mobility IRG's grand challenge is to develop innovative mobility solutions that simultaneously tackle two opposing objectives: To improve the safety, comfort and time associated with transportation, getting individuals and good where they need to be, and when they need to be there; and to reverse the alarming, unsustainable energy and environmental trends associated with transportation, and devise transportation systems that materially enhance sustainability and societal well-being.
Humanitarian Supply Chain Lab
The mission of the MIT Humanitarian Supply Chain Lab is to understand and improve the supply chain systems behind public services and private markets to meet human needs. Based within the MIT Center for Transportation and Logistics, the Lab combines expertise in engineering, management, information technology, social science, economics, and other disciplines to drive practical innovation for humanitarian interventions. The lab has a diverse portfolio of projects to improve emergency response during crisis and to enable market development that improves resilience. Our theoretical and applied research is driven by active engagement with the private sector, government agencies, humanitarian, international development, and community organizations on several continents.
JTL Urban Mobility Lab
The JTL Urban Mobility Lab at MIT brings behavioral science and transportation technology together to shape travel behavior, design mobility systems, and improve transportation policies. They apply this framework to managing automobile ownership and usage, optimizing public transit planning and operation, promoting active modes of walking and cycling, governing autonomous vehicles and shared mobility services, and designing multimodal urban transportation systems.
Laboratory for Aviation and the Environment
The Laboratory for Aviation and the Environment is a research lab in the MIT Department of Aeronautics & Astronautics. The team is interdisciplinary, covering expertise in Aeronautical, Mechanical and Chemical Engineering, Atmospheric Science and Economics.
MIT Digital Supply Chain Transformation
Digital transformation is now a keystone of operational, organizational, and technological structures for companies and supply chains who desire to be competitive in the vision of the future business environment. Our work aims to support organizationally adaptable, technologically compatible, and economically viable transformation for improving performance.
The primary research examines new collaborative paradigms that arise while implementing different new digital technologies in supply chains. Our research domains are digital platforms, multidimensional collaboration, digital capabilities and Artificial Intelligence (AI) in supply chains. Our research fosters more visible, efficient, flexible and resilient networks. We apply quantitative research methodologies in order to assess how data-driven ecosystems create value.
The MIT FreightLab mission is to drive innovation into the freight transportation industry in order to reduce cost, minimize risk, and increase the level of service. Freight transportation is subject to highly volatile demand and costs that are typically outside of a firm’s ability to control or even influence. This is compounded by a dominant design in terms of how freight is historically procured and managed. FreightLab research focuses on working with companies to develop and implement real-world solutions to these challenges.
FreightLab objectives are to develop innovations in freight transportation planning and operations and drive them into practice. Recently, we have developed methods for forecasting both short term spot-market rates and longer-term contract rates. We are exploring alternative contract forms between shippers and carriers that increase the level of trust in the relationship and yield better results for both parties. Working with a wide range of shippers, carriers, and third-party providers, the freight lab team develops and delivers better ways to design, procure, and manage large-scale freight transportation systems.
MIT Sustainable Supply Chains
The MIT Center for Transportation & Logistics launched Sustainable Supply Chains in 2018 as an umbrella program that brings together our sustainability research, education, and outreach. Our goal is to connect research outcomes to practical settings, enabling companies and stakeholders to leverage supply chains as a beneficial force to reaching global sustainable development goals. We seek to improve visibility of supply chain impacts and develop strategies to help reduce them, so companies can better address consumer, political, and shareholder concerns. The lab has a wide portfolio of research projects including supply chain transparency, sustainable logistics, sustainable procurement, consumer purchasing behavior, and on. The research is inclusive of issues across the supply chain and spans social, environmental, and economic impact areas.
Megacity Logistics Lab
The Megacity Logistics Lab brings together business, logistics, and urban planning perspectives to develop appropriate technologies, infrastructures, and policies for sustainable urban logistics operations. Their work aims to promote new urban delivery models, from unattended home delivery solutions to smart locker systems, to click & collect services, to drone delivery. They are pushing the limits of existing logistics network designs as future city logistics networks need to support omni-channel retail models, smaller store formats, increased intensity of deliveries, coordinate multiple transshipment points, engage a wider range of vehicle technologies - including electric and autonomous vehicles - and support complex inventory balancing and deployment strategies.
Resilient Infrastructure Systems Lab
The Resilient Infrastructure Systems Lab seeks to improve the robustness and security of critical infrastructure systems by developing tools to detect and respond to incidents, both random and adversarial and by designing incentive mechanisms for efficient infrastructure management. They are working on the problems of cyber-physical security, failure diagnostics and incident response, network monitoring and control, and demand management in real-world infrastructures. They mainly focus on cyber-physical infrastructure systems for electric power, transportation, and urban water and natural gas networks.
The MIT Transit Lab leverages the value of large-scale, long-term research collaborations across transit agencies. Starting in 1992 under the leadership of Professor Nigel Wilson, the Lab has collaborated with metropolitan transit agencies and departments of transportation worldwide, developing and implementing technology for transit operations and planning. Past and ongoing research sponsors include the Chicago Transit Authority (CTA), Massachusetts Bay Transportation Authority (MBTA), Transport for London (TfL), and Mass Transit Railway (MTR, Hong Kong). These long-term engagements, in addition to projects with other transit agencies and international research centers, provide graduate students unique opportunities for applied research.
Engineering Systems Analysis for Design
Practical-oriented subject that builds upon theory and methods and culminates in extended application. Covers methods to identify, value, and implement flexibility in design (real options). Topics include definition of uncertainties, simulation of performance for scenarios, screening models to identify desirable flexibility, decision analysis, and multidimensional economic evaluation. Students demonstrate proficiency through an extended application to a system design of their choice. Complements research or thesis projects. Meets with IDS.333 first half of term. Enrollment limited.
Transportation Systems Analysis: Demand and Economics
Covers the key principles governing transportation systems planning and management. Introduces the microeconomic concepts central to transportation systems. Topics include economic theories of the firm, consumer, and market, demand models, discrete choice analysis, cost models and production functions, and pricing theory. Applications to transportation systems - including congestion pricing, technological change, resource allocation, market structure and regulation, revenue forecasting, public and private transportation finance, and project evaluation - cover urban passenger transportation, freight, maritime, aviation, and intelligent transportation systems.
Theory and application of modeling and statistical methods for analysis and forecasting of demand for facilities, services, and products. Topics include: review of probability and statistics, estimation and testing of linear regression models, theory of individual choice behavior, derivation, estimation, and testing of discrete choice models (including logit, nested logit, GEV, probit, and mixture models), estimation under various sample designs and data collection methods (including revealed and stated preferences), sampling, aggregate forecasting methods, and iterative proportional fitting and related methods. Lectures reinforced with case studies, which require specification, estimation, testing, and analysis of models using data sets from actual applications.
Applied Probability and Stochastic Models
A vigorous use of probabilistic models to approximate real-life situations in Finance, Operations Management, Economics, and Operations Research. Emphasis on how to develop a suitable probabilistic model in a given setting and, merging probability with statistics, and on how to validate a proposed model against empirical evidence. Extensive treatment of Monte Carlo simulation for modeling random processes when analytic solutions are unattainable.
Planning and Design of Airport Systems
Focuses on current practice, developing trends, and advanced concepts in airport design and planning. Considers economic, environmental, and other trade-offs related to airport location, as well as the impacts of emphasizing "green" measures. Includes an analysis of the effect of airline operations on airports. Topics include demand prediction, determination of airfield capacity, and estimation of levels of congestion; terminal design; the role of airports in the aviation and transportation system; access problems; optimal configuration of air transport networks and implications for airport development; and economics, financing, and institutional aspects. Special attention to international practice and developments.
Urban Last-Mile Logistics
Explores specific challenges of urban last-mile B2C and B2B distribution in both industrialized and emerging economies. Develops an in-depth understanding of the perspectives, roles, and decisions of all relevant stakeholder groups, from consumers, to private sector decision makers, to public policy makers. Discussion of the most relevant traditional and the most promising innovating operating models for urban last-mile distribution. Introduces applications of the essential quantitative methods for the strategic design and tactical planning of urban last-mile distribution systems, including optimization and simulation. Covers basic facility location problems, network design problems, single- and multi-echelon vehicle routing problems, as well as associated approximation techniques.
Global Energy: Politics, Markets, and Policy
Focuses on the ways economics and politics influence the fate of energy technologies, business models, and policies around the world. Extends fundamental concepts in the social sciences to case studies and simulations that illustrate how corporate, government, and individual decisions shape energy and environmental outcomes. In a final project, students apply the concepts in order to assess the prospects for an energy innovation to scale and advance sustainability goals in a particular regional market. Recommended prerequisite: 14.01. Meets with 15.219 when offered concurrently. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details. Preference to juniors, seniors, and Energy Minors.
Transportation Research Design
Seminar dissects ten transportation studies from head to toe to illustrate how research ideas are initiated, framed, analyzed, evidenced, written, presented, criticized, revised, extended, and published, quoted and applied. Students design and execute their own transportation research.
Advanced Seminar in Transportation Finance
Focuses on the theory and practice of transportation system finance, examining the range of relevant topics including basic public finance, politics, institutional structures, externalities, pricing, and the role of advanced technologies. Primarily oriented around land-based, surface transportation, although in their research students are welcome to examine air and maritime modes according to their interests. Explores issues across a range of contexts, including North America, Europe, Latin America, and Asia.
Econometric Data Science
Introduces regression and other tools for causal inference and descriptive analysis in empirical economics. Topics include analysis of randomized experiments, instrumental variables methods and regression discontinuity designs, differences-in-differences estimation, and regress with time series data. Develops the skills needed to conduct — and critique — empirical studies in economics and related fields. Empirical applications are drawn from published examples and frontier research. Familiarity with statistical programming languages is helpful. Students taking graduate version complete an empirical project leading to a short paper. Limited to 70 total for versions meeting together.
Mobility Ventures: Driving Innovation in Transportation Systems
This course is designed for students who aspire to shape the future of mobility. The course explores technological, behavioral, policy and systems-wide frameworks for innovation in transportation systems, complemented with case studies across the mobility spectrum, from autonomous vehicles to urban air mobility to last-mile sidewalk robots. Students will interact with a series of guest lecturers from CEOs and other business and government executives who are actively reshaping the future of mobility.
The Airline Industry
Overview of the global airline industry, focusing on recent industry performance, current issues and challenges for the future. Fundamentals of airline industry structure, airline economics, operations planning, safety, labor relations, airports and air traffic control, marketing, and competitive strategies, with an emphasis on the interrelationships among major industry stakeholders. Recent research findings of the MIT Global Airline Industry Program are showcased, including the impacts of congestion and delays, evolution of information technologies, changing human resource management practices, and competitive effects of new entrant airlines. Taught by faculty participants of the Global Airline Industry Program.
Overview of airline management decision processes, with a focus on economic issues and their relationship to operations planning models and decision support tools. Application of economic models of demand, pricing, costs, and supply to airline markets and networks. Examination of industry practice and emerging methods for fleet planning, route network design, scheduling, pricing and revenue management, with emphasis on the interactions between the components of airline management and profit objectives in competitive environments. Students participate in a competitive airline management simulation game as part of the subject requirements.
Air Transportation Systems Architecting
Addresses the architecting of air transportation systems. Focuses on the conceptual phase of product definition including technical, economic, market, environmental, regulatory, legal, manufacturing, and societal factors. Centers on a realistic system case study and includes a number of lectures from industry and government. Past examples include the Very Large Transport Aircraft, a Supersonic Business Jet and a Next Generation Cargo System. Identifies the critical system level issues and analyzes them in depth via student team projects and individual assignments. Overall goal is to produce a business plan and a system specifications document that can be used to assess candidate systems.
D-Lab: Supply Chains
Introduces concepts of supply chain design and planning with a focus on supply chains for products destined to improve quality of life in developing countries. Topics include demand estimation, process analysis and improvement, facility location and capacity planning, inventory management, and supply chain coordination. Also covers issues specific to emerging markets, such as sustainable supply chains, choice of distribution channels, and how to account for the value-adding role of a supply chain. Students conduct D-Lab-based projects on supply chain design or improvement. Students taking graduate version will complete additional assignments.
Statistics, Computation and Applications
Hands-on analysis of data demonstrates the interplay between statistics and computation. Includes four modules, each centered on a specific data set, and introduced by a domain expert. Provides instruction in specific, relevant analysis methods and corresponding algorithmic aspects. Potential modules may include medical data, gene regulation, social networks, finance data (time series), traffic, transportation, weather forecasting, policy, or industrial web applications. Projects address a large-scale data analysis question. Students taking graduate version complete additional assignments. Limited enrollment; priority to Statistics and Data Science minors and to juniors and seniors.
Data Mining: Finding the Models and Predictions that Create Value
Introduction to data mining, data science, and machine learning, methods that assist in recognizing patterns, developing models and predictive analytics, and making intelligent use of massive amounts of data collected via the internet, e-commerce, electronic banking, pointof-sale devices, bar-code readers, medical databases, and other sources. Topics include logistic regression, association rules, treestructured classification and regression, cluster analysis, discriminant analysis, and neural network methods. Presents examples of successful applications in credit ratings, fraud detection, marketing, customer relationship management, investments, and synthetic clinical trials. Introduces data-mining software focusing on R. Term project required. Meets with 15.062 when offered concurrently. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details.
Development Ventures is an exploratory Fall semester elective Action Lab on founding, financing, and building entrepreneurial ventures targeting developing countries, emerging markets, and underserved consumers everywhere.
Particular emphasis is placed on transformative innovations and exponentially scalable business models that can enable or accelerate major positive social change throughout the world.
Provides an introduction to supply chain management from both analytical and practical perspectives. Taking a unified approach, students develop a framework for making intelligent decisions within the supply chain. Covers key logistics functions, such as demand planning, procurement, inventory theory and control, transportation planning and execution, reverse logistics, and flexible contracting. Explores concepts such as postponement, portfolio management, and dual sourcing. Emphasizes skills necessary to recognize and manage risk, analyze various tradeoffs, and model logistics systems.
Logistics Systems Topics
Provides an introduction to supply chain management from both analytical and practical perspectives. Taking a unified approach, students develop a framework for making intelligent decisions within the supply chain. Covers key logistics functions, such as demand planning, procurement, inventory theory and control, transportation planning and execution, reverse logistics, and flexible contracting. Explores concepts such as postponement, portfolio management, and dual sourcing. Emphasizes skills necessary to recognize and manage risk, analyze various tradeoffs, and model logistics systems. SCM.271 meets with SCM.260 but requires fewer assignments and lectures.