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- Article
Measuring the Effectiveness of Competition in Defense Procurement: A Survey of the Empirical Literature
By: James J. Anton and Dennis A. Yao
This article surveys the literature that has attempted to measure competition's effects on defense procurement. The focus is on conceptual underpinnings of models rather than technical aspects of estimation procedures. While providing valuable insight, the models are...
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Keywords:
Performance Effectiveness;
Competition;
Surveys;
Value;
Economics;
Forecasting and Prediction;
Programs;
Power and Influence;
Management Analysis, Tools, and Techniques
Anton, James J., and Dennis A. Yao. "Measuring the Effectiveness of Competition in Defense Procurement: A Survey of the Empirical Literature." Journal of Policy Analysis and Management 9, no. 1 (Winter 1990): 60–79. (Harvard users click here for full text.)
- July 1987 (Revised October 2009)
- Background Note
A Method For Valuing High-Risk, Long-Term Investments: The "Venture Capital Method"
By: William A. Sahlman and Daniel R Scherlis
Describes a method for valuing high-risk, long-term investments such as those confronting venture capitalists. The method entails forecasting a future value (e.g., five years from the present) and discounting that terminal value back to the present by applying a high...
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Keywords:
Forecasting and Prediction;
Entrepreneurship;
Venture Capital;
Investment;
Risk Management;
Valuation
Sahlman, William A., and Daniel R Scherlis. A Method For Valuing High-Risk, Long-Term Investments: The "Venture Capital Method". Harvard Business School Background Note 288-006, July 1987. (Revised October 2009.)
- July 1986 (Revised August 1987)
- Background Note
Note on Comparative Advantage
By: David B. Yoffie and John J. Coleman
Discusses David Ricardo's theory of comparative advantage and the refinement of his model developed by Eli Heckscher and Bertil Ohlin. Presents several criticisms of the Heckscher-Ohlin theory, including Wassily Leontief's empirical demonstration that the nature of...
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Yoffie, David B., and John J. Coleman. "Note on Comparative Advantage." Harvard Business School Background Note 387-023, July 1986. (Revised August 1987.)
- January 1986 (Revised April 1987)
- Background Note
Models for Updating Demand Forecasts
Keywords:
Forecasting and Prediction
Schleifer, Arthur, Jr. "Models for Updating Demand Forecasts." Harvard Business School Background Note 186-180, January 1986. (Revised April 1987.)
- January 1983 (Revised September 1983)
- Case
E.T. Phone Home, Inc.: Forecasting Business Demand
By: John F. Cady and Frank V. Cespedes
Describes a process for forecasting market demand for an emerging technology--cellular radio. The student must critically evaluate the demand model and the market estimates, and modify them as appropriate in order to develop a marketing plan and budget.
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Keywords:
Budgets and Budgeting;
Forecasting and Prediction;
Marketing Strategy;
Demand and Consumers;
Business Processes;
Technology
Cady, John F., and Frank V. Cespedes. "E.T. Phone Home, Inc.: Forecasting Business Demand." Harvard Business School Case 583-121, January 1983. (Revised September 1983.)
- Forthcoming
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that...
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Keywords:
Churn;
Churn Management;
Churn/retention;
Assortment Planning;
Retail;
Retailing;
Retailing Industry;
Preference Heterogeneity;
Assortment Optimization;
Customers;
Retention;
Consumer Behavior;
Forecasting and Prediction;
Retail Industry
Anderson, Eric, Chaoqun Chen, Ayelet Israeli, and Duncan Simester. "Canary Categories." Journal of Marketing Research (JMR) (forthcoming). (Pre-published online November 29, 2023.)
- Forthcoming
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety...
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Keywords:
Autonomy;
Chatbots;
New Technology;
Brand Crises;
Mental Health;
Large Language Model;
AI and Machine Learning;
Behavior;
Well-being;
Technological Innovation;
Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology (forthcoming). (Pre-published online October 26, 2023.)
- Research Summary
Customer-Centricity as a Vehicle for Organic Growth
By: Ranjay Gulati
This body of work examines the mechanics of how firms grow profitably in commoditizing markets. Underlying the "customer-centricity" that many firms embrace today is a factor that will determine their success with this effort: enabling collaboration across...
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- Forthcoming
- Article
FinTech Lending and Cashless Payments
By: Pulak Ghosh, Boris Vallée and Yao Zeng
Borrower's use of cashless payments both improves their access to capital from FinTech lenders and predicts a lower probability of default. These relationships are stronger for cashless technologies providing more precise information, and for outflows. Cashless payment...
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- Forthcoming
- Article
Imagining the Future: Memory, Simulation and Beliefs
By: Pedro Bordalo, Giovanni Burro, Katherine B. Coffman, Nicola Gennaioli and Andrei Shleifer
How do people form beliefs about novel risks, with which they have little or no experience? Motivated by survey data on beliefs about Covid we collected in 2020, we build a model based on the psychology of selective memory. When a person thinks about an event,...
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Bordalo, Pedro, Giovanni Burro, Katherine B. Coffman, Nicola Gennaioli, and Andrei Shleifer. "Imagining the Future: Memory, Simulation and Beliefs." Review of Economic Studies (forthcoming).
- Research Summary
Making Machine Learning Models Interpretable
I work on developing various tools and methodologies which can help decision makers (e.g., doctors, managers) to better understand the predictions of machine learning models.
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- Research Summary
Overview
By: Iavor I. Bojinov
Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of...
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- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the...
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- Forthcoming
- Article
Perceptions about Monetary Policy
By: Michael D. Bauer, Carolin Pflueger and Adi Sunderam
We estimate perceptions about the Federal Reserve’s monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions varies substantially over time,...
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Bauer, Michael D., Carolin Pflueger, and Adi Sunderam. "Perceptions about Monetary Policy." Quarterly Journal of Economics (forthcoming).
- Forthcoming
- Article
Reflexivity in Credit Markets
By: Robin Greenwood, Samuel G. Hanson and Lawrence J. Jin
Reflexivity is the idea that investors' biased beliefs affect market outcomes and that market outcomes in turn affect investors’ future biases. We develop a dynamic behavioral model of the credit cycle featuring this two-way feedback loop. Investors form beliefs about...
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Greenwood, Robin, Samuel G. Hanson, and Lawrence J. Jin. "Reflexivity in Credit Markets." Journal of Finance (forthcoming).
- Research Summary
Selection, Reallocation, and Spillover: Identifying the Sources of Gains from Multinational Production (with Maggie Chen)
By: Laura Alfaro
Quantifying the gains from multinational production has been a vital topic of economic research. Positive productivity gains are often attributed to knowledge spillover from multinational to domestic firms. An alternative, less stressed explanation is firm selection... View Details
- Research Summary
Selective Attention and Learning
What do we notice, and how does this affect what we learn? Standard economic models of learning ignore memory by assuming that we remember everything. But there is growing recognition that memory is imperfect. Further, memory imperfections do not stem from limited... View Details
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