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- 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 August 2023)
- Case
Safecast: Bootstrapping Human Capital to Big Data
By: Ethan Bernstein and Stephanie Marton
On March 11, 2011, at 2:46pm, a 9.1-on-the-Richter-scale, six-minute long earthquake unleashed a tsunami that ravaged the Tohoku region of Japan, damaging the Fukushima Daiichi Nuclear Power facility and releasing sufficient radioactive material into the air and ocean... View Details
Keywords: Citizen Science; Creative Commons; Open Data; Open Architecture; Volunteer-based Organization; Fukushima Daiichi Nuclear Power Facility; 311; Nuclear; Radiation; Crowdsourcing; Bgeigie; Geiger Counters; Kickstarter; Sustainability; Sustainable Business And Innovation; Design; Energy Generation; Social Entrepreneurship; Human Capital; Innovation and Invention; Crisis Management; Organizational Structure; Organizational Design; Information Technology; Business Model; Energy Industry; Technology Industry; Japan; North and Central America; Europe
Bernstein, Ethan, and Stephanie Marton. "Safecast: Bootstrapping Human Capital to Big Data." Harvard Business School Case 419-033, October 2018. (Revised August 2023.)
- October 2018
- Case
BreezoMeter: Making Air Pollution Data Actionable
By: Frank V. Cespedes, Allison M. Ciechanover and Margot Eiran
The case focuses on an Israeli startup that provides actionable air pollution data and forecasts. The company has over 50 enterprise customers and its tool reached a million people daily in 67 countries. The co-founders wrestle with which markets and customers to focus... View Details
Keywords: Startups; Entrepreneurship; Business Startups; Pollutants; Analytics and Data Science; Sales; Marketing; Decision Choices and Conditions; Technology Industry; Israel; United States
Cespedes, Frank V., Allison M. Ciechanover, and Margot Eiran. "BreezoMeter: Making Air Pollution Data Actionable." Harvard Business School Case 819-058, October 2018.
- October 2018
- Case
Fundraising at St. Camillus Hospital
By: Srikant M. Datar and Caitlin N. Bowler
St. Camillus is a fictional non-profit hospital in rural Maine facing a serious budget deficit. As Director of Marketing, Victoria Stern is building a team to modernize the hospital fundraising efforts. An interview with a promising candidate, who is also a digital... View Details
Keywords: Data Analysis; Data Privacy; Data Governance; Non-profit; Health Care; Fundraising; Data Security; Analytics and Data Science; Safety; Governance; Ethics; Health Care and Treatment; Cybersecurity
Datar, Srikant M., and Caitlin N. Bowler. "Fundraising at St. Camillus Hospital." Harvard Business School Case 119-027, October 2018.
- October 2018 (Revised July 2023)
- Case
Innovation at Uber: The Launch of Express POOL
By: Chiara Farronato, Alan MacCormack and Sarah Mehta
Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This product offers a reduced price to riders willing to carpool, walk a short distance to/from their pick-up and drop-off points, and wait a... View Details
Keywords: Innovation and Management; Innovation Leadership; Innovation Strategy; Technological Innovation; Information Technology; Mobile and Wireless Technology; Applications and Software; Digital Platforms; Decision Making; Technology Industry; California; San Francisco
Farronato, Chiara, Alan MacCormack, and Sarah Mehta. "Innovation at Uber: The Launch of Express POOL." Harvard Business School Case 619-003, October 2018. (Revised July 2023.)
- 2018
- Book
The Gift of Global Talent: How Migration Shapes Business, Economy & Society
By: William R. Kerr
The global race for talent is on, with countries and businesses competing for the best and brightest. Foreign talent has transformed U.S. science and engineering, reshaped the economy, and influenced society at large. But America is bogged down in thorny debates on... View Details
Kerr, William R. The Gift of Global Talent: How Migration Shapes Business, Economy & Society. Stanford, CA: Stanford Business Books, 2018.
- 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.)
- September 2018
- Case
Verisk: Trailblazing in the Big Data Jungle
By: Andrew Wasynczuk, Francesca Gino and Karim Sameh
This case revolves around Verisk Analytics' initiatives to drive innovation throughout the firm's many business verticals. Verisk, originally named ISO, started life as an insurance rating agency in the early 1970s, acting as an intermediary between insurance companies... View Details
Keywords: Verisk; Argus; Wood Mackenzie; Insurance; Energy; Analytics; Data; Big Data; Acquisitions; Acquisition Strategy; Innovation; Organic Growth; Innovation Strategy; Innovation Leadership; Technological Innovation; Acquisition; Growth and Development Strategy; Analytics and Data Science; Insurance Industry; Energy Industry; Consulting Industry; United States; United Kingdom; New York (state, US); England
Wasynczuk, Andrew, Francesca Gino, and Karim Sameh. "Verisk: Trailblazing in the Big Data Jungle." Harvard Business School Case 919-014, September 2018.
- Article
The Critical Role of Second-order Normative Beliefs in Predicting Energy Conservation
By: Jon M. Jachimowicz, Oliver P. Hauser, Julia D. O'Brien, Erin Sherman and Adam D. Galinsky
Sustaining large-scale public goods requires individuals to make environmentally friendly decisions today to benefit future generations. Recent research suggests that second-order normative beliefs are more powerful predictors of behaviour than first-order personal... View Details
Keywords: Climate Change; Energy; Environmental Sustainability; Household; Behavior; Values and Beliefs; Forecasting and Prediction
Jachimowicz, Jon M., Oliver P. Hauser, Julia D. O'Brien, Erin Sherman, and Adam D. Galinsky. "The Critical Role of Second-order Normative Beliefs in Predicting Energy Conservation." Nature Human Behaviour 2, no. 10 (October 2018): 757–764.
- Article
Uninformed Consent
By: Leslie K. John
Companies want access to more and more of your personal data—from where you are to what’s in your DNA. Can they unlock its value while respecting consumers’ privacy? View Details
Keywords: Personal Data; Privacy; Customers; Analytics and Data Science; Ethics; Governing Rules, Regulations, and Reforms
John, Leslie K. "Uninformed Consent." Special Issue on The Big Idea: Tracked. Harvard Business Review (website) (September–October 2018).
- September 2018
- Article
What Does It Take to Change an Editor's Mind? Identifying Minimally Important Difference Thresholds for Peer Reviewer Rating Scores of Scientific Articles
By: Michael Callaham and Leslie John
Study objective—We define a minimally important difference for the Likert-type scores frequently used in scientific peer review (similar to existing minimally important differences for scores in clinical medicine). To our knowledge, the magnitude of score change... View Details
Callaham, Michael, and Leslie John. "What Does It Take to Change an Editor's Mind? Identifying Minimally Important Difference Thresholds for Peer Reviewer Rating Scores of Scientific Articles." Annals of Emergency Medicine 72, no. 3 (September 2018): 314–318.e2.
- Third Quarter 2018
- Article
Why and How Investors Use ESG Information: Evidence from a Global Survey
By: Amir Amel-Zadeh and George Serafeim
Using survey data from a sample of senior investment professionals from mainstream (i.e., not SRI funds) investment organizations, we provide insights into why and how investors use reported environmental, social, and governance (ESG) information. Relevance to... View Details
Keywords: ESG; ESG (Environmental, Social, Governance) Performance; Sustainability; Investment Management; Investment Strategy; Metrics; Standard Setting; Accounting Standards; Finance; Investment; Information; Environmental Sustainability; Governance; Performance Effectiveness; Strategy
Amel-Zadeh, Amir, and George Serafeim. "Why and How Investors Use ESG Information: Evidence from a Global Survey." Financial Analysts Journal 74, no. 3 (Third Quarter 2018): 87–103.
- August 2018 (Revised September 2018)
- Case
Predicting Purchasing Behavior at PriceMart (A)
By: Srikant M. Datar and Caitlin N. Bowler
This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (A)." Harvard Business School Case 119-025, August 2018. (Revised September 2018.)
- August 2018 (Revised September 2018)
- Supplement
Predicting Purchasing Behavior at PriceMart (B)
By: Srikant M. Datar and Caitlin N. Bowler
Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details
Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (B)." Harvard Business School Supplement 119-026, August 2018. (Revised September 2018.)
- August 2018 (Revised April 2019)
- Case
Chateau Winery (A): Unsupervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
- August 2018 (Revised April 2019)
- Supplement
Chateau Winery (B): Supervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- 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 (B): Decision Trees & Random Forests
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
... View Details
... View Details
Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, 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.)
- August 2018
- Case
Christine Lagarde (A): A French Prime Minister Calls
By: Julie Battilana and Carin-Isabel Knoop
This case covers formative events and influences in Christine Lagarde’s childhood and her trajectory from studying political science and law to heading the world’s largest law firm. As she prepares to transition back to practice in 2005, the new Prime Minister of... View Details
Battilana, Julie, and Carin-Isabel Knoop. "Christine Lagarde (A): A French Prime Minister Calls." Harvard Business School Case 419-017, August 2018.