MGMT 190 REVENUE MANAGEMENT FALL 2015 John Turner https://eee.uci.edu/15f/38291

Contact Information

Professor: John Turner Faculty Assistant: Ginger Smith Office: SB2 338 (Office: SB2 337, Phone: 949-824-2022) Phone: (949) 824-7941 Teaching Assistant: S. Ali Hojjat Email: [email protected] Email: [email protected] Skype ID: john.turner.uci Skype ID: ali.hojjat.uci Office Hours: Wednesdays 1PM-2PM Office Hours: Tuesdays 4-5PM (SB2 410) Other times by appointment Other times by appointment

Professor Bio

John Turner joined The Paul Merage School of Business in 2010 as an assistant professor of Operations and Decisions Technologies. He holds a Ph.D. in Operations Research from the Tepper School of Business, Carnegie Mellon University. For his doctoral work titled Ad Slotting and Pricing: New Media Planning Models for New Media, Turner was honored by INFORMS with the 2011 George B. Dantzig Dissertation Award. This award is given for the best dissertation in any area of operations research and the management sciences that is innovative and relevant to practice. More recently, Turner was named a 2012 Yahoo! Faculty Research & Engagement Program Scholar for his work in planning and scheduling online advertising, and was awarded the 2014 INFORMS William Pierskalla Best Paper Award in Health Care Management Science for his work on designing a trauma care system in Korea.

Turner's research interests include applied optimization, large-scale optimization, revenue management, media management, health care management, and problems that lie at the interface of operations and marketing. His research has been published in leading journals, including “Scheduling of Dynamic In-Game Advertising” in the journal Operations Research, “Planning of Guaranteed Targeted Display Advertising” in Operations Research, “Simultaneous Location of Trauma Centers and Helicopters for Emergency Medical Service Planning” in Operations Research, and “A Large U.S. Retailer Selects Transportation Carriers under Diesel Price Uncertainty,” in Interfaces.

Turner’s primary research stream addresses various problems in the planning, pricing, and scheduling of online advertising. Applications of his research include webpage banner ads, dynamic in-game advertising

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(ads that are seamlessly placed into 3D video games), electronic outdoor billboards, and the next generation of digital TV. Prior to his academic career, Turner worked in the IT industry as a consultant, as an operations analyst in retail distribution, and as a quantitative analyst in the financial sector. Turner also holds an M.S. in Operations Research from the Tepper School of Business at Carnegie Mellon University, and a B.Math., Honors Operations Research Co-op with a minor in Computer Science from the University of Waterloo, Canada.

Classroom Etiquette, Guidelines, & Policies

Academic Honesty By enrolling in this course, you agree to be bound by the University of California, Irvine’s policy on academic honesty (http://honesty.uci.edu/).

Attendance Your attendance for each class session is expected, as is your active participation. If you miss a class for personal or business reasons, please inform the instructor in advance if at all possible. Absences without pressing reasons indicate disinterest in the course and will reflect on your grade.

Add/Drop Deadline The Paul Merage School of Business abides by the campus’ course drop deadline of the end of the second week of the quarter. The end of the second full week is: Friday, October 9 (5:00PM). All add/drops are processed electronically through the campus WEBREG system.

Diversity & Inclusiveness Policy The University of California, in accordance with applicable Federal and State law and University policy, does not discriminate on the basis of race, color, national origin, religion, sex, gender identity, pregnancy, physical or mental disability, medical condition (cancer related or genetic characteristics), ancestry, marital status, age, sexual orientation, citizenship, or service in the uniformed services. The University also prohibits sexual harassment. This nondiscrimination policy covers admission, access, and treatment in University programs and activities.

Course Objectives

Revenue Management focuses on how a firm should set and update pricing and product availability decisions across its selling channels to maximize profitability. It is the science of selling the right product to the right customer at the right time for the right price, and can be viewed as the demand-side complement to traditional supply-side inventory management.

Using mathematical models and advanced analytics, we will study how airlines decide how many seats to reserve for high-paying business customers versus low-paying leisure customers, how hotels determine when to discount their rooms, and how rental car companies determine how many reservations to overbook. As well, we will study how auctions are used to price and sell online advertising, how advertising

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schedules are determined for several media vehicles, and how revenue management is being used by the health care, retail, and entertainment industries.

We will solve the optimization problems which yield solutions to revenue management problems using Excel and Excel Solver, and discuss various modeling pitfalls and practical data issues. In addition, we will learn high-level concepts that general managers and management consultants can use to apply revenue management techniques across a broad spectrum of industries.

Prerequisites: MGMT 101 Management Science

Course Overview

Class Meets Wednesday mornings, 9:00AM-11:50AM in SB1 2200 (campus map: http://www.uci.edu/visit/maps.php) Exceptions: 1. Veteran’s Day, Wednesday November 11th – Holiday (No class that week) 2. Final Project Presentations: • Wed, Dec 9th 8am-10am SB1 2200

Message Board Please post clarification questions about cases here, as well as conceptual questions about materials discussed in class: https://eee.uci.edu/boards/f15/ug-rm/

Course Materials

Required Materials • “Pricing and Revenue Optimization” by Robert Phillips, 2005. (ISBN: 978-0804746984) • Course Pack (for cases and articles); see: https://students.universityreaders.com/store/ • Lecture Notes (PowerPoint slides), posted on EEE before each class • Computer and Software: Microsoft Excel will be used throughout the course (any version 2007/2010/2013 will do). Please make sure you have access to a computer which has Microsoft Excel.

Extra Reading (Optional) • “Segmentation, Revenue Management, and Pricing Analytics” by Tudor Bodea and Mark Ferguson, 2014. (ISBN: 978-0415898331) • “The Future of Pricing: How Airline Ticket Pricing Has Inspired a Revolution” by E. Andrew Boyd, 2007. (ISBN: 0230600190) • “Revenue Management” by Robert G. Cross, 1997. (ISBN: 978-0767900331)

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Grading

Class Participation 5% Case Presentation and Critique 15% (breakdown: 10% presentation, 5% critique) Homework (breakdown: 2 graded 20% assignments, 10% each) Midterms (breakdown: 2 short 35% midterms, 17.5% each) Final Project (breakdown: 5% proposal, 25% 10% presentation, 10% write-up) TOTAL 100%

Class Participation (5%) All students are expected to have read any case studies that will be discussed in class, so that they may participate in discussions.

Case Presentation & Critique (15%) The class will be divided into a number of groups for this activity. For each class that a case study is to be presented, one group will present and another will critique. The “presenting” group will be graded on their ability to clearly convey the main principles underlying the case study, and the insights they have figured out. The “critiquing” group will be graded on their ability to engage the presenting group and the rest of the class in a discussion about the topics at hand. Both the “presenting group” and the “critiquing group” must read and prepare the case, but their responsibilities differ. While the presenting group should prepare PowerPoint slides to discuss the main points and their suggested course of action, the critiquing group’s contributions can be more informal and may consist of a list of alternative courses of action and their pros and cons, listed on the whiteboard and discussed in-class. The class will be divided into 14 groups of approximately 4 students for this activity. Each group will either present one case, or critique one case. There are 7 cases in total. Therefore, each student should select one presenting group and one critiquing group, and will get exposure to two different cases.

Homework (20%) Two homework assignments will expose students to solving revenue optimization models in Excel Solver and using the newsvendor model to determine optimal booking limits and optimal overbooking levels. The homework assignments are technical in nature, and should be done as a group (suggestion: use your case study groups).

Midterms (35%) Two short midterms will be held in-class. The midterms will test your general understanding of concepts covered in-class, as well as the technical skills covered on the most recent homework. You may use any handwritten or printed notes, as well as the textbook as a reference (the midterms are open-book), but the only electronics allowed are regular scientific calculators to help with arithmetic (you will need it, so please make sure you have one!). Phones, laptops, and graphing calculators will not be allowed.

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Final Project (25%) The class will be divided into a number of groups for this activity (suggestion: use your case study groups). Each group should have 3-4 students. The task is to produce a business plan that outlines how revenue management and price optimization could be implemented at a company or in an industry of your choice. Creative, out-of-the-box thinking is encouraged. Include a discussion of implementation issues, how risks and opportunities may be managed, challenges that may be encountered in transitioning to an information system that supports revenue management, dealing with customer perceptions, etc. There are three deliverables for the final project: 1) a one-page proposal that describes in 2-3 paragraphs what your topic will be; 2) a short PowerPoint presentation in the final week of classes; 3) a written report (6-8 pages double-spaced), along with a description of how each student in the group individually contributed to the finished product.

Acknowledgements This course is a fusion of similar courses offered at INSEAD, Carnegie Mellon, and the University of Maryland. Special thanks to Itir Karaesmen, Ioana Popescu, and Nicola Secomandi for the foundations they and others have laid in the teaching of revenue management.

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Course Schedule

Class #1 (Sept 30) Activities: • Introduction to Revenue Management • Review of Excel Solver • Modeling customer behavior using price • Suggested Reading: Phillips Chapters 1 response functions, and their connection to and 2 willingness-to-pay distributions • Maximization of revenue and profit of a single product selling at a single price, given a known price response function

Class #2 (Oct 7) Activities: • Fitting price response functions to data • Review of Linear Regression in Excel • How market segmentation (and versioning in • Reading (R1): “Versioning: The Smart particular) boosts revenues Way to Sell Information” • Price elasticity and pricing rules-of-thumb • Suggested Reading: Phillips Chapter 3 • Discussion of fairness issues in RM implementations • Application: optimal pricing of concert tickets

Class #3 (Oct 14) Activities: • The logit price response model • Case Study (S1): “What Price Vertigo?” • Fitting the logit price response model to • Suggested Reading: Phillips Chapter 4 disaggregated transaction data using Maximum Likelihood Estimation • Price differentiation and market segmentation • Application: RM for cruise lines

Class #4 (Oct 21) Activities: • Working around modeling pitfalls: imperfect • Case Study (S2): “Copa Cruises” segmentation, arbitrage, and cannibalization • Reading (R2): “Easy Profit: A Revenue • Pricing when supply is constrained Management Pilot” • Peak-load pricing and diversion strategies • Homework #1 Due • Introduction to quantity-control revenue • Suggested Reading: Phillips Chapter 5 management • Applications: time-of-day pricing in electricity markets, hotel group reservation pricing, airline seat reservations

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Class #5 (Oct 28) Activities: • Accounting for opportunity costs: the • Case Study (S3): “Congestion Charging newsvendor model and Littlewood’s Rule in London: Road Pricing to Reduce • Accounting for opportunity costs: optimal Emissions” overbooking • Final Project: Proposals Due • Applications: airline and hospitality industry • Suggested Reading: Phillips Chapters 6 examples and 7 • Examples solved in-class

Class #6 (Nov 4) Activities: • Guest Speaker: Cara Davidoff, Revenue • Midterm #1 Today Manager, Marriott Hotels • Suggested Reading: Phillips Chapter 9 • Quantity-control RM in practice: the Expected Marginal Seat Revenue (EMSR) model and dynamic booking control • Applications: manufacturing, RM integrated with inventory systems, loyalty programs

Class #7 (Nov 18) Activities: • Guest Speaker: Scott Chandler, Managing • Reading (R3): “Starting with Good Director of Revenue Management and Inputs: Unconstraining Demand Data in Continuous Improvement, American Airlines Revenue Management” • Forecasting and data issues: uncensoring • Suggested Reading: Phillips Chapter 11 demand

Class #8 (Nov 25) Activities: • Auctions • Case Study (S5): “Break.com” • Markdown Pricing • Case Study (S7): “Hong Kong Grand” • Applications: trucking contracts, online • Homework #2 Due advertising, retail merchandising • Suggested Reading: Phillips Chapter 10

Class #9 (Dec 2) Activities: • Implementation concerns • Case Study (S4): “The Right Price • Measuring the performance of RM systems Consultants” • • Tips for managing RM projects Reading (R4): “Texas Children’s • Tips for launching your RM career Hospital” • Midterm #2 Today • Applications: healthcare contracts

Class #10 - Wed, Dec 9 @ 8am-10am SB1 2200 Activities: • Student Presentations. • Final Project: Student Presentations Note the earlier than usual start time. • Final Project: Written Report Due

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List of Cases and Reading Materials

Cases S1-S7 will be assigned to students as part of the Case Presentation & Critique part of the course. Notice that we will use the cases in a different order than they are printed in the course pack!

Case # Case Short Name Case Full Name Where Is It? S1 “Vertigo” “What Price Vertigo?” Course pack p. 1 S2 “Copa Cruises” “Copa Cruises - Welcome Aboard” Course pack p. 7 S3 “Road Pricing” “Congestion Charging in London: Road Pricing to Course pack p. 23 Reduce Emissions” S4 “Right-Price” “The Right-Price Consultants” Course pack p. 71 S5 “Break.com” “Break.com” Course pack p. 39 S6 “Bloomingdale's” “Markdown Pricing Optimization at Course pack p. 53 Bloomingdale's” S7 “Hong Kong Grand” “Revenue Management at the Hong Kong Course pack p. 85 Grand: The Dine in Grandeur Dilemma"

Readings R1-R4 will be presented by the instructor; students should read these before they are presented.

Reading # Reading Name Where Is It? R1 “Versioning: The Smart Way to Sell Information” Course pack p. 11 R2 “Easy Profit: A Revenue Management Pilot” Course pack p. 29 R3 “Starting with Good Inputs: Unconstraining Demand Data” Course pack p. 37 R4 “Texas Children’s Hospital” Course pack p. 63

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