More from these Authors

• Working Paper | HBS Working Paper Series | 2019

  Collusion in Brokered Markets

  John William Hatfield, Scott Duke Kominers and Richard Lowery

  The U.S. residential real estate agency market presents a puzzle for economic theory: commissions on real estate transactions have remained constant and high for decades even though agent entry is frequent and agents’ costs of providing service are low. We model the real estate agency market, and other brokered markets, via repeated extensive form games; in our game, brokers first post prices for customers and then choose which agents on the other side of the market to work with. We show that prices appreciably higher than the competitive prices can be sustained (for a fixed discount factor) regardless of the number of brokers; this is done through strategies that condition willingness to transact with each broker on that broker’s initial posted prices. Our results can thus rationalize why brokered markets exhibit pricing high above marginal cost despite fierce competition for customers; moreover, our model can help explain why agents and platforms who have tried to reduce commissions have had trouble entering the market.

  Citation:

  Hatfield, John William, Scott Duke Kominers, and Richard Lowery. "Collusion in Brokered Markets." Harvard Business School Working Paper, No. 20-023, September 2019.  View Details

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• Article | Operations Research Letters | September 2019

  Optimizing Reserves in School Choice: A Dynamic Programming Approach

  Franklyn Wang, Ravi Jagadeesan and Scott Duke Kominers

  We introduce a new model of school choice with reserves in which a social planner is constrained by a limited supply of reserve seats and tries to find an optimal matching according to a social welfare function. We construct the optimal distribution of reserves via a quartic-time dynamic programming algorithm. Due to the modular nature of the dynamic program, the mechanism is strategy-proof for reserve-eligible students.

  Keywords: matching; reserves; dynamic programming; Marketplace Matching; Mathematical Methods;

  Citation:

  Wang, Franklyn, Ravi Jagadeesan, and Scott Duke Kominers. "Optimizing Reserves in School Choice: A Dynamic Programming Approach." Operations Research Letters 47, no. 5 (September 2019): 438–446.  View Details

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• Case | HBS Case Collection | August 2019

  Rand Fishkin at Moz (B)

  Thomas R. Eisenmann

  In 2016, senior management at Moz, a venture capital-backed startup providing software tools for digital marketing professionals, must decide how to address a looming cash flow crisis precipitated by failed efforts to broaden its product line. Seattle-based Moz had originally focused only on search engine optimization (SEO) software. Aiming to accelerate growth, over the past three years the startup had launched products targeted at content marketers, social media marketers, and small local businesses. Adoption of these new products had been disappointing, and the resource drain and distraction of launching them had reduced the growth of Moz's core SEO product. Management was wrestling with whether to either: 1) shut down or sell the new products; or 2) double down on the new products, funding further investment in them by selling the core SEO business or milking it as a "cash cow."

  Keywords: Startups; scaling; Entrepreneurship; Failure; Diversification; Growth Management;

  Citation:

  Eisenmann, Thomas R. "Rand Fishkin at Moz (B)." Harvard Business School Case 820-003, August 2019.  View Details

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