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- All HBS Web
(5,460)
- Faculty Publications (895)
- December 2018
- Article
Cross-boundary Teaming for Innovation: Integrating Research on Teams and Knowledge in Organizations
By: Amy C. Edmondson and Jean-François Harvey
Cross-boundary teaming, within and across organizations, is an increasingly popular strategy for innovation. Knowledge diversity is seen to expand the range of views and ideas that teams can draw upon to innovate. Yet, case studies reveal that teaming across knowledge... View Details
Keywords: Teams; Innovation; Groups and Teams; Innovation and Invention; Knowledge; Performance Effectiveness
Edmondson, Amy C., and Jean-François Harvey. "Cross-boundary Teaming for Innovation: Integrating Research on Teams and Knowledge in Organizations." Special Issue on Creating High Performance Teamwork in Organizations. Human Resource Management Review 28, no. 4 (December 2018): 347–360.
- 2018
- Working Paper
Diagnostic Bubbles
By: Pedro Bordalo, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with two well-known mechanisms: learning from prices and... View Details
Bordalo, Pedro, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. "Diagnostic Bubbles." NBER Working Paper Series, No. 25399, December 2018.
- November–December 2018
- Article
Online Network Revenue Management Using Thompson Sampling
By: Kris J. Ferreira, David Simchi-Levi and He Wang
We consider a network revenue management problem where an online retailer aims to maximize revenue from multiple products with limited inventory constraints. As common in practice, the retailer does not know the consumer's purchase probability at each price and must... View Details
Keywords: Online Marketing; Revenue Management; Revenue; Management; Marketing; Internet and the Web; Price; Mathematical Methods
Ferreira, Kris J., David Simchi-Levi, and He Wang. "Online Network Revenue Management Using Thompson Sampling." Operations Research 66, no. 6 (November–December 2018): 1586–1602.
- November 2018
- Case
Sportradar (A): From Data to Storytelling
By: Ramon Casadesus-Masanell, Karen Elterman and Oliver Gassmann
In 2013, the Swiss sports data company Sportradar debated whether to expand from its core business of data provision to bookmakers into sports media products. Sports data was becoming a commodity, and in the future, sports leagues might reduce their dependence on... View Details
Keywords: Sports Data; Data; Sport; Sportradar; Football; Soccer; Gambling; Betting; Betting Markets; Statistics; Odds; Live Data; Bookmakers; Betradar; Visualization; Integrity; Monitoring; Gaming; Streaming; 2013; St.Gallen; Algorithm; Mathematical Modeling; Carsten Koerl; Betandwin; Bwin; Wagering; Probability; Sports; Analytics and Data Science; Mathematical Methods; Games, Gaming, and Gambling; Transition; Strategy; Media; Sports Industry; Technology Industry; Information Technology Industry; Media and Broadcasting Industry; Europe; Switzerland; Asia; Austria; Germany; England
Casadesus-Masanell, Ramon, Karen Elterman, and Oliver Gassmann. "Sportradar (A): From Data to Storytelling." Harvard Business School Case 719-429, November 2018.
- October 2018 (Revised May 2019)
- Teaching Note
Intuit: Turbo Tax PersonalPro - A Tale of Two Entrepreneurs
By: Joseph Fuller, Shikhar Ghosh and Monica Baraldi
Teaching Note for HBS No. 816-048. The case tells the story of a product manager within Intuit who develops an idea for a new product that spans two of the company's existing business units—professional tax software, sold to accountants, and the consumer focused... View Details
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
- 2018
- Working Paper
Full Substitutability
By: John William Hatfield, Scott Duke Kominers, Alexandru Nichifor, Michael Ostrovsky and Alexander Westkamp
Various forms of substitutability are essential for establishing the existence of equilibria and other useful properties in diverse settings such as matching, auctions, and exchange economies with indivisible goods. We extend earlier models’ definitions of... View Details
Hatfield, John William, Scott Duke Kominers, Alexandru Nichifor, Michael Ostrovsky, and Alexander Westkamp. "Full Substitutability." Harvard Business School Working Paper, No. 19-016.
- August 2018 (Revised September 2018)
- Case
LendingClub (A): Data Analytic Thinking (Abridged)
By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.)
- August 2018 (Revised September 2018)
- Supplement
LendingClub (C): Gradient Boosting & Payoff Matrix
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
- 2018
- Working Paper
Bundling Incentives in (Many-to-Many) Matching with Contracts
By: Jonathan Ma and Scott Duke Kominers
In many-to-many matching with contracts, the way in which contracts are specified can affect the set of stable equilibrium outcomes. Consequently, agents may be incentivized to modify the set of contracts upfront. We consider one simple way in which agents may do so:... View Details
Keywords: Matching With Contracts; Contract Design; Bundling-proofness; Substitutability; Mathematical Methods
Ma, Jonathan, and Scott Duke Kominers. "Bundling Incentives in (Many-to-Many) Matching with Contracts." Harvard Business School Working Paper, No. 19-011, August 2018.
- August 2018
- Article
Deep Help in Complex Project Work: Guiding and Path-Clearing Across Difficult Terrain
By: Colin M. Fisher, Julianna Pillemer and Teresa M. Amabile
How do teams working on complex projects get the help they need? Our qualitative investigation of the help provided to project teams at a prominent design firm revealed two distinct helping processes, both characterized by deep, sustained engagement that far exceeds... View Details
Keywords: Helping; Rhythm; Prosocial Behavior; External Team Leadership; Social Construction; Time; Qualitative Methods; Field Research; Groups and Teams; Projects; Behavior; Leadership; Social and Collaborative Networks
Fisher, Colin M., Julianna Pillemer, and Teresa M. Amabile. "Deep Help in Complex Project Work: Guiding and Path-Clearing Across Difficult Terrain." Academy of Management Journal 61, no. 4 (August 2018): 1524–1553.
- August 2018
- Article
Extrapolation and Bubbles
By: Nicholas Barberis, Robin Greenwood, Lawrence Jin and Andrei Shleifer
We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals: an average of the asset’s past price changes and the asset’s degree of overvaluation. The two signals are in conflict, and investors... View Details
Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer. "Extrapolation and Bubbles." Journal of Financial Economics 129, no. 2 (August 2018): 203–227.
- June 2018 (Revised November 2018)
- Case
Innovation at Insigne Health
By: Srikant M. Datar, Linda A. Cyr and Caitlin N. Bowler
Insigne Health is a fictional for-profit, integrated health insurer/health care provider whose leadership believes that by shifting members’ focus from “sickness” to “well-being” it could increase the overall health of its insured population and decrease the resources... View Details
Keywords: Design Thinking; Behavior Change; Chronic Disease; Health Care; Health Care and Treatment; Design; Behavior; Change; Innovation and Management
Datar, Srikant M., Linda A. Cyr, and Caitlin N. Bowler. "Innovation at Insigne Health." Harvard Business School Case 118-042, June 2018. (Revised November 2018.)
- 2018
- Working Paper
Learning to Become a Taste Expert
By: Kathryn A. Latour and John A. Deighton
Evidence suggests that consumers seek to become more expert about hedonic products to enhance their enjoyment of future consumption occasions. Current approaches to becoming an expert center on cultivating an analytic mindset. In the present research the authors... View Details
Keywords: Hedonic; Wine; Expertise; Holistic; Analytic; Sensory; Taste; Learning; Experience and Expertise; Analysis; Perception
Latour, Kathryn A., and John A. Deighton. "Learning to Become a Taste Expert." Harvard Business School Working Paper, No. 18-107, June 2018.
- June 2018
- Article
Personal and Social Usage: The Origins of Active Customers and Ways to Keep Them Engaged
By: Clarence Lee, Elie Ofek and Thomas Steenburgh
We study how digital service firms can develop an active customer base, focusing on two questions. First, how does the way that customers use the service postadoption to meet their own needs (personal usage) and to interact with one another (social usage) vary across... View Details
Keywords: Customer Engagement; Adoption Routes; Word-of-Mouth; Digital Marketing; Bayesian Estimation; Customers; Communication; Consumer Behavior; Marketing; Internet and the Web; Analytics and Data Science
Lee, Clarence, Elie Ofek, and Thomas Steenburgh. "Personal and Social Usage: The Origins of Active Customers and Ways to Keep Them Engaged." Management Science 64, no. 6 (June 2018): 2473–2495. (Lead Article.)
- 2018
- Book
Kissinger the Negotiator: Lessons from Dealmaking at the Highest Level
By: James K. Sebenius, R. Nicholas Burns and Robert H. Mnookin (with a forward by Henry A. Kissinger)
As professors and practitioners with careers devoted to negotiation, we are often asked “Who are the world’s best negotiators? What makes them effective?” Inevitably Henry Kissinger’s name comes up as an elite, if controversial, negotiator from whom we can learn a... View Details
Keywords: History; Negotiation Process; Negotiation Tactics; Personal Development and Career; Negotiation Style; United States
Sebenius, James K., R. Nicholas Burns, and Robert H. Mnookin (with a forward by Henry A. Kissinger). Kissinger the Negotiator: Lessons from Dealmaking at the Highest Level. New York: HarperCollins, 2018.
- May–June 2018
- Article
Layoffs That Don't Break Your Company: Better Approaches to Workforce Transition
By: Sandra J. Sucher and Shalene Gupta
Today layoffs have become companies’ default response to the challenges created by advances in technology and global competition. Yet research shows that job cuts rarely help senior leaders achieve their goals. Too often, they’re done for short-term gain, but the cost... View Details
Keywords: Job Cuts and Outsourcing; Organizational Change and Adaptation; Employees; Transition; Strategic Planning
Sucher, Sandra J., and Shalene Gupta. "Layoffs That Don't Break Your Company: Better Approaches to Workforce Transition." Harvard Business Review 96, no. 3 (May–June 2018): 122–129.
- May 2018
- Article
Linda Babcock: Go-getter and Do-gooder
By: Max Bazerman, Iris Bohnet, Hannah Riley-Bowles and George Loewenstein
In this tribute to the 2007 recipient of the Jeffrey Z. Rubin Theory‐To‐Practice Award from the International Association for Conflict Management (IACM), we celebrate Linda Babcock's contributions to diverse lines of research, her tireless and effective efforts to put... View Details
Bazerman, Max, Iris Bohnet, Hannah Riley-Bowles, and George Loewenstein. "Linda Babcock: Go-getter and Do-gooder." Negotiation and Conflict Management Research 11, no. 2 (May 2018): 130–145.
- May 2018
- Article
Selection and Market Reallocation: Productivity Gains from Multinational Production
By: Laura Alfaro and Maggie X. Chen
Assessing the productivity gains from multinational production has been a vital topic of economic research and policy debate. Positive aggregate productivity gains are often attributed to within-firm productivity improvement; however, an alternative, less emphasized... View Details
Keywords: Productivity Gains; Multinational Production; Selection; Market Reallocation; And Within-firm Productivity; Multinational Firms and Management; Production; Performance Productivity; Competition; Mathematical Methods
Alfaro, Laura, and Maggie X. Chen. "Selection and Market Reallocation: Productivity Gains from Multinational Production." American Economic Journal: Economic Policy 10, no. 2 (May 2018): 1–38. (Also NBER Working Paper 18207. See Harvard Business School Working Paper, No. 12–111, 2015 for longer version.)
- November 2021
- Article
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,... View Details
Herlands, William, Edward McFowland III, Andrew Gordon Wilson, and Daniel B. Neill. "Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data." Proceedings of Machine Learning Research (PMLR) 84 (2018): 425–434. (Also presented at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.)