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- All HBS Web (323)
- Faculty Publications (144)
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- All HBS Web (323)
- Faculty Publications (144)
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- Article
Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates
By: J. Peter Scoblic
Would-be forecasters have increasingly extolled the predictive potential of Big Data and artificial intelligence. This essay reviews the career of Sherman Kent, the Yale historian who directed the CIA’s Office of National Estimates from 1952 to 1967, with an eye toward... View Details
Keywords: National Security; Analytics and Data Science; Analysis; Forecasting and Prediction; History
Scoblic, J. Peter. "Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates." Texas National Security Review 1, no. 4 (August 2018).
- 11 Jan 2007
- Working Paper Summaries
A Perceptions Framework for Categorizing Inventory Policies in Single-stage Inventory Systems
Keywords: by Noel Watson
- Article
Big Other: Surveillance Capitalism and the Prospects of an Information Civilization
By: Shoshana Zuboff
This article describes an emergent logic of accumulation in the networked sphere, 'surveillance capitalism,' and considers its implications for 'information civilization.' The institutionalizing practices and operational assumptions of Google Inc. are the... View Details
Keywords: Surveillance Capitalism; Big Data; Google; Information Society; Privacy; Internet Of Everything; Rights; Economic Systems; Analytics and Data Science; Internet and the Web; Ethics
Zuboff, Shoshana. "Big Other: Surveillance Capitalism and the Prospects of an Information Civilization." Journal of Information Technology 30, no. 1 (March 2015): 75–89.
- 2019
- Article
Does Big Data Enhance Firm Innovation Competency? The Mediating Role of Data-driven Insights
By: Maryam Ghasemaghaei and Goran Calic
Grounded in gestalt insight learning theory and organizational learning theory, we collected data from 280 middle and top-level managers to investigate the impact of each big data characteristic (i.e., data volume, data velocity, data variety, and data veracity) on... View Details
Ghasemaghaei, Maryam, and Goran Calic. "Does Big Data Enhance Firm Innovation Competency? The Mediating Role of Data-driven Insights." Journal of Business Research 104 (2019): 69–84.
- 2021
- Working Paper
Time Dependency, Data Flow, and Competitive Advantage
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details
Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage
Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
- 15 Sep 2015
- First Look
September 15, 2015
Operations Management Analytics for an Online Retailer: Demand Forecasting and Price Optimization By: Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi Abstract—We present our work with an online retailer, Rue La La, as an... View Details
Keywords: Sean Silverthorne
- April 2008
- Tutorial
Finance: An Introductory Online Course
By: Timothy A. Luehrman, Brenda W. Chia and Michelle Rendall
The Finance Online Course provides a fundamental understanding of the principles, analytical tools, and knowledge needed to make good investment and financing decisions. The course introduces students to finance ratios, forecasting methods, capital structure theory,... View Details
- 12 Oct 2006
- First Look
First Look: October 12, 2006
Working PapersDo Corporate Social Responsibility Ratings Predict Corporate Social Performance? Authors:Aaron K. Chatterji, David I. Levine, and Michael W. Toffel Abstract Ratings of corporations' environmental activities and... View Details
Keywords: Sean Silverthorne
- August 2021 (Revised February 2024)
- Case
Data Science at the Warriors
By: Iavor I. Bojinov and Michael Parzen
The case explores the development and early growth of a data science team at the Golden State Warriors, an NBA team based in San Francisco. The case begins by explaining the initial rationale for investing in data science, then covers a debate on the appropriate team... View Details
Keywords: Digital Marketing; Analysis; Forecasting and Prediction; Technological Innovation; Information Technology; Analytics and Data Science; Sports Industry; San Francisco; United States
Bojinov, Iavor I., and Michael Parzen. "Data Science at the Warriors." Harvard Business School Case 622-048, August 2021. (Revised February 2024.)
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- Article
Is it Better to Average Probabilities or Quantiles?
By: Kenneth C. Lichtendahl, Yael Grushka-Cockayne and Robert L. Winkler
We consider two ways to aggregate expert opinions using simple averages: averaging probabilities and averaging quantiles. We examine analytical properties of these forecasts and compare their ability to harness the wisdom of the crowd. In terms of location, the two... View Details
Keywords: Probability Forecasts; Quantile Forecasts; Expert Combination; Linear Opinion Pooling; Forecasting and Prediction
Lichtendahl, Kenneth C., Yael Grushka-Cockayne, and Robert L. Winkler. "Is it Better to Average Probabilities or Quantiles?" Management Science 59, no. 7 (July 2013): 1594–1611.
- 2010
- Working Paper
The Unbundling of Advertising Agency Services: An Economic Analysis
By: Mohammad Arzaghi, Ernst R. Berndt, James C. Davis and Alvin J. Silk
We address a longstanding puzzle surrounding the unbundling of services occurring over several decades in the U.S. advertising agency industry: What accounts for the shift from bundling to unbundling of services and the slow pace of change? Using Evans and Salinger's... View Details
Keywords: Advertising; Change; Forecasting and Prediction; Cost; Price; Analytics and Data Science; Surveys; Marketing Strategy; Media; Service Operations; Agency Theory; Mathematical Methods; Advertising Industry; United States
Arzaghi, Mohammad, Ernst R. Berndt, James C. Davis, and Alvin J. Silk. "The Unbundling of Advertising Agency Services: An Economic Analysis." Harvard Business School Working Paper, No. 11-039, September 2010.
- Article
Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy
By: Edward Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to... View Details
Keywords: User-generated Content; Operations; Tournaments; Policy-making; Machine Learning; Online Platforms; Analytics and Data Science; Mathematical Methods; City; Infrastructure; Business Processes; Government and Politics
Glaeser, Edward, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 114–118.
- 2011
- Chapter
Regional Trade Integration and Multinational Firm Strategies
By: Pol Antras and C. Fritz Foley
This paper analyzes the effects of the formation of a regional trade agreement on the level and nature of multinational firm activity. We examine aggregate data that captures the response of U.S. multinational firms to the formation of the ASEAN free trade agreement.... View Details
Keywords: Forecasting and Prediction; Trade; Foreign Direct Investment; Multinational Firms and Management; Globalized Markets and Industries; Analytics and Data Science; Agreements and Arrangements; United States
Antras, Pol, and C. Fritz Foley. "Regional Trade Integration and Multinational Firm Strategies." In Costs and Benefits of Regional Economic Integration in Asia, edited by Robert J. Barro and Jong-Wha Lee. Oxford University Press, 2011.
- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details
- April–May 2024
- Article
Gone with the Big Data: Institutional Lender Demand for Private Information
By: Jung Koo Kang
I explore whether big-data sources can crowd out the value of private information acquired through lending relationships. Institutional lenders have been shown to exploit their access to borrowers’ private information by trading on it in financial markets. As a shock... View Details
Keywords: Analytics and Data Science; Borrowing and Debt; Financial Markets; Value; Knowledge Dissemination; Financing and Loans
Kang, Jung Koo. "Gone with the Big Data: Institutional Lender Demand for Private Information." Art. 101663. Journal of Accounting & Economics 77, nos. 2-3 (April–May 2024).
- July 2023
- Article
Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations
By: Dawson Beutler, Alex Billias, Sam Holt, Josh Lerner and TzuHwan Seet
In 2001, Dean Takahashi and Seth Alexander of the Yale University Investments Office developed a deterministic model for estimating future cash flows and valuations for the Yale endowment’s private equity portfolio. Their model, which is simple and intuitive, is still... View Details
Beutler, Dawson, Alex Billias, Sam Holt, Josh Lerner, and TzuHwan Seet. "Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations." Journal of Portfolio Management 49, no. 7 (July 2023): 144–158.
- July 2010 (Revised December 2011)
- Background Note
Marketing Analysis Toolkit: Pricing and Profitability Analysis
By: Thomas J. Steenburgh and Jill Avery
Pricing is one of the most difficult decisions marketers make and the one with the most direct and immediate impact on the firm's financial position. This toolkit will introduce the fundamental terminology and calculations associated with pricing and profitability... View Details
Keywords: Forecasting and Prediction; Price; Profit; Management Analysis, Tools, and Techniques; Marketing Strategy; Demand and Consumers; Measurement and Metrics; Strategic Planning; Mathematical Methods; Retail Industry
Steenburgh, Thomas J., and Jill Avery. "Marketing Analysis Toolkit: Pricing and Profitability Analysis." Harvard Business School Background Note 511-028, July 2010. (Revised December 2011.)
- 2018
- Working Paper
Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e., nowcasting and forecasting) and by providing additional context about how the local... View Details
Keywords: Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change." NBER Working Paper Series, No. 24952, August 2018.
- June 2023
- Article
How New Ideas Diffuse in Science
By: Mengjie Cheng, Daniel Scott Smith, Xiang Ren, Hancheng Cao, Sanne Smith and Daniel A. McFarland
What conditions help new ideas spread? Can knowledge entrepreneurs’ position and develop new ideas in ways that help them take off? Most innovation research focuses on products and their reference. That focus ignores the ideas themselves and the broader ideational... View Details
Keywords: Innovation Adoption; Natural Language Processing; Knowledge; Science; Innovation and Invention; Knowledge Sharing; Analytics and Data Science
Cheng, Mengjie, Daniel Scott Smith, Xiang Ren, Hancheng Cao, Sanne Smith, and Daniel A. McFarland. "How New Ideas Diffuse in Science." American Sociological Review 88, no. 3 (June 2023): 522–561.