OIT 334: Design for Extreme Affordability
This course is a Bass Seminar. Project course jointly offered by School of Engineering and Graduate School of Business. Students apply engineering and business skills to design product or service prototypes, distribution systems, and business plans for entrepreneurial ventures that meet that challenges faced by the world's poor. Topics include user empathy, appropriate technology design, rapid prototype engineering and testing, social technology entrepreneurship, business modeling, and project management. Weekly design reviews; final course presentation. Industry and adviser interaction. Limited enrollment via application; see
http://extreme.stanford.edu/index.html for details.
Units: 4

Grading: GSB Letter Graded
Instructors:
Beach, D. (PI)
;
Cone, T. (PI)
;
Coulson, S. (PI)
;
Gorodsky, J. (PI)
;
Patell, J. (PI)
OIT 356: Electronic Business
This course focuses on the intersection of strategy and information technology. It considers how you can take advantage of new technology opportunities and how they change the structure of firms, industries and value chains, with an emphasis on business issues. Case studies include Salesforce.com, Apple, Netflix, Evernote, Linden Lab (Second Life), Amazon.com and Zappos. Classes combine lecture and case study discussions and the workload is above the GSB average. While the advanced course will generally cover the same topics as
OIT 256, it will go into more advanced techniques in a number of areas.
Units: 3

Grading: GSB Letter Graded
Instructors:
Mendelson, H. (PI)
OIT 364: Global Operations
Globalization of businesses has resulted in companies having to manage global networks of suppliers, integrators, contract manufacturers, logistics service providers, distributors, and service support operators in geographically dispersed locations. The customer network is also globally distributed. This course will focus on (1) how global and international companies can overcome the geographical, cultural, and organizational barriers, and leverage the strengths of the network to create values, and (2) how these companies may use different ways to manage operations in different regions to take full advantage of the local strengths and limitations. The course will be based on cases on innovative strategies and tactics used by global and international companies.
Units: 3

Grading: GSB Letter Graded
Instructors:
Lee, H. (PI)
OIT 367: Analytics from Big Data
The objective of this course is to analyze realworld situations where significant competitive advantage can be obtained through largescale data analysis, with special attention to what can be done with the data and where the potential pitfalls lie. Students will be challenged to develop businessrelevant questions and then solve for them by manipulating large data sets. Problems from advertising, eCommerce, finance, healthcare, marketing, and revenue management are presented. Students learn to apply software (such as R and SQL) to data sets to create knowledge that will inform decisions. The course covers fundamentals of statistical modeling, machine learning, and datadriven decision making. Students are expected to layer these topics over an existing facility with mathematical notation, algebra, calculus, probability, and basic statistics.
Units: 4

Grading: GSB Letter Graded
Instructors:
Bayati, M. (PI)
OIT 558: Designing LargeScale Nudge Engines
In many of the challenges faced by the modern world, from overcrowded road networks to overstretched healthcare systems, large benefits for society come about from small changes by very many individuals. This course survey the problems and the cost they impose on society. It describes a series of pilot projects which aim to develop principles for inducing small changes in behavior in Societal Networkstransportation networks, wellness programs, recycling systems and, if time permits, energy grids. Students will learn how lowcost sensing and networking technology can be used for sensing individual behavior, and how incentives and social norming can be used to influence the behavior. The effectiveness of this approach in pilots conducted in Bangalore (commuting), Singapore (public transit system), Stanford (congestion and parking), and a wellness program at AccentureUSA will be discussed. Students may experience the incentive platform as participants.nnThis course significantly overlaps with
OIT 258  Incentive Mechanisms for Societal Networks. If you took this class last year, you may not take
OIT 558.
Units: 1

Grading: GSB Pass/Fail
Instructors:
Prabhakar, B. (PI)
OIT 562: Supply Chain Management & Technology
This course offers an overview of eight technologies for enterprise computing. They are: ERP (Enterprise Resource Planning), EAI (Enterprise Application Interface), data mining, cloud computing, eCommerce, RFID/NFC, mobile technologies, and social network data analytics. On each topic, we discuss underlying technologies and applications using a variety of business cases.
Units: 2

Grading: GSB Letter Graded
Instructors:
Whang, S. (PI)
OIT 565: The Role of Information Technology in the New Energy Economy
One of the most interesting and underexplored areas in modern technology is, as Dan Reicher at Stanford has put it, "where energy technology (ET) meets information technology (IT)". The main driver of widespread use of computing in the modern age is the rapid reduction in the cost of computing services caused by Moore's law. At the same time, a substantial increase in the energy efficiency of computing (doubling every year and a half for more than six decades) has led to a proliferation of mobile computers, sensors, and controls, with implications that have only recently begun to be understood.nnnThis class will explore the direct and indirect implications of applying information technology to the production, delivery, and use of energy and associated services. It will first review current knowledge about the direct energy use associated with information technology, including data centers, personal computers, cellular telephones, mobile sensors, and other IT equipment. It will also summarize the state of knowledge about the types, amount, and growth rates of energy services delivered in the US and globally. Finally, it will explore the applications to which information technologies have been put in the energy industry, ranging from the use of visualization and analysis techniques to improve the results of oil and gas exploration, to the computeraided design of wind turbines and automobiles, to the implications of wireless sensors and controls for the more efficient and effective use of energy. The class will culminate in student projects, typically business plans for new ventures using IT to radically transform how we understand and respond to the world around us.
Units: 2

Grading: GSB Letter Graded
OIT 602: Dynamic Pricing and Revenue Management I
In tandem with
OIT 603, this course explores the application of stochastic modeling and optimization to two closely related problem areas: (a) dynamic price selection, and (b) dynamic allocation of limited capacity to competing demands. As background, students are assumed to know stochastic process theory at the level of Statistics 217218, microeconomics at the level of Economics 202N, and optimization theory at the level of MS&E 211, and to have some familiarity with the basic ideas of dynamic programming. Additional dynamic programming theory will be developed as needed for the applications covered. Emphasis will be on current research topics, especially in the realm of airline revenue management.
Units: 2

Grading: GSB Letter Graded
OIT 603: Dynamic Pricing and Revenue Management II
In tandem with
OIT 602, this course explores the application of stochastic modeling and optimization to two closely related problem areas: (a) dynamic price selection, and (b) dynamic allocation of limited capacity to competing demands. As background, students are assumed to know stochastic process theory at the level of Statistics 217218, microeconomics at the level of Economics 202N, and optimization theory at the level of MS&E 211, and to have some familiarity with the basic ideas of dynamic programming. Additional dynamic programming theory will be developed as needed for the applications covered. Emphasis will be on current research topics, especially involving customized pricing of financial services.
OIT 602 is not a prerequisite for
OIT 603 but is highly recommended.
Units: 2

Grading: GSB Letter Graded
OIT 624: Theory of Inventory Management
The course provides students a strong theoretical background in several fundamental aspects underlying inventory theory. Topics include deterministic inventory models (EOQ, Poweroftwo policies, ELS, serial and assembly networks), the Newsvendor model, multiperiod stochastic inventory theory, serial and multiechelon models, approximation algorithms, batch ordering and lostsales models, infinitesimal perturbation analysis, distributionfree inventory theory, models for joint pricing and inventory decisions. The course also provides an overview of relevant mathematical concepts used in inventory theory, including convexity, duality, probability theory, finite and infinite state Markov decision processes, and comparative statics.
Units: 3

Grading: GSB Letter Graded
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