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Show Results For
- All HBS Web
(1,794)
- People (9)
- News (316)
- Research (1,043)
- Events (15)
- Multimedia (10)
- Faculty Publications (863)
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- July 2021
- Article
Electronic Trace Data and Legal Outcomes: The Effect of Electronic Medical Records on Malpractice Claim Resolution Time
By: Sam Ransbotham, Eric Overby and Michael C. Jernigan
Information systems generate copious trace data about what individuals do and when they do it. Trace data may affect the resolution of lawsuits by, for example, changing the time needed for legal discovery. Trace data might speed resolution by clarifying what events... View Details
Keywords: Analytics and Data Science; Lawsuits and Litigation; Digital Transformation; Welfare; Health Industry
Ransbotham, Sam, Eric Overby, and Michael C. Jernigan. "Electronic Trace Data and Legal Outcomes: The Effect of Electronic Medical Records on Malpractice Claim Resolution Time." Management Science 67, no. 7 (July 2021): 4341–4361.
- Article
Core Earnings: New Data and Evidence
By: Ethan Rouen, Eric C. So and Charles C.Y. Wang
Using a novel dataset, we show that components of firms' GAAP earnings stemming from ancillary business activities or transitory shocks are significant in frequency and magnitude. These components have grown over time and are dispersed across various sections of the... View Details
Keywords: Core Earnings; Transitory Earnings; Non-operating Earnings; Quantitative Disclosures; Equity Valuation; Big Data; Business Earnings; Financial Reporting; Valuation; Analytics and Data Science
Rouen, Ethan, Eric C. So, and Charles C.Y. Wang. "Core Earnings: New Data and Evidence." Journal of Financial Economics 142, no. 3 (December 2021): 1068–1091.
- February 2021
- Article
Testing the Waters: Behavior across Participant Pools
By: Erik Snowberg and Leeat Yariv
We leverage a large-scale incentivized survey eliciting behaviors from (almost) an entire university student population, a representative sample of the U.S. population, and Amazon Mechanical Turk (MTurk) to address concerns about the external validity of experiments... View Details
Keywords: Lab Selection; External Validity; Experiments; Behavior; Surveys; Analytics and Data Science; Analysis
Snowberg, Erik, and Leeat Yariv. "Testing the Waters: Behavior across Participant Pools." American Economic Review 111, no. 2 (February 2021): 687–719.
- July 2018
- Article
Reimagining Health Data Exchange: An Application Programming Interface-Enabled Roadmap for India
By: Satchit Balsari, Alexander Fortenko MD, MPH, Joaquin A. Blaya PhD, Adrian Gropper MD, Malavika Jayaram LLM, Rahul Matthan LLM, Ram Sahasranam, Mark Shankar MD, Suptendra N. Sarbadhikari PhD, Barbara Bierer, Kenneth D. Mandl MD, Sanjay Mehendale MD, MPH and Tarun Khanna
In February 2018, the Government of India announced a massive public health insurance scheme extending coverage to 500 million citizens, in effect making it the world’s largest insurance program. To meet this target, the government will rely on technology to... View Details
Keywords: Health Information Exchange; India; Health APIs; Health Care and Treatment; Information; Analytics and Data Science; Information Technology; Health Industry; India
Balsari, Satchit, Alexander Fortenko MD, MPH, Joaquin A. Blaya PhD, Adrian Gropper MD, Malavika Jayaram LLM, Rahul Matthan LLM, Ram Sahasranam, Mark Shankar MD, Suptendra N. Sarbadhikari PhD, Barbara Bierer, Kenneth D. Mandl MD, Sanjay Mehendale MD, MPH, and Tarun Khanna. "Reimagining Health Data Exchange: An Application Programming Interface-Enabled Roadmap for India." Journal of Medical Internet Research 20, no. 7 (July 2018).
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- October 2022
- Supplement
Single Earth: Science White Paper Supplement
By: Rembrand Koning and Emer Moloney
Science White Paper prepared by Single.Earth to give an overview of the models and solutions it has developed. View Details
Keywords: Business Startups; Entrepreneurship; Climate Change; Environmental Sustainability; Green Technology; Natural Resources; Pollution; Analytics and Data Science; Marketing; Product Marketing; Product Launch; Product Positioning; Markets; Market Timing; Strategy; Green Technology Industry; Estonia
- 22 Nov 2016
- First Look
November 22, 2016
and Ananth Raman Abstract—To set inventory service levels, suppliers must understand how changes in inventory service level affect demand. We build on prior research, which uses analytical models and laboratory experiments to study the... View Details
Keywords: Sean Silverthorne
- 23 Aug 2010
- Research & Ideas
The Drive to Acquire’s Impact on Globalization
classic trading system of exchange is identified with David Ricardo, the early nineteenth-century economist who first analytically clarified it. Imagine that tribe A is good at both hunting and fishing, but more efficient at hunting.... View Details
Keywords: by Paul R. Lawrence
- 30 Oct 2006
- First Look
First Look: October 31, 2006
(2007) Abstract This edited volume contributes analytical depth to the diverse debates on accountability in modern organizations. It explores the nature, forms and impacts of accountability efforts in civil society organizations, public... View Details
Keywords: Sean Silverthorne
- 08 Jul 2008
- First Look
First Look: July 8, 2008
such behaviors led to undesirable consequences, even if they saw those behaviors as acceptable before they knew its consequences. Furthermore, our results demonstrate that a rational, analytic mindset can override the effects of one's... View Details
Keywords: Martha Lagace
- 2022
- Article
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations
By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
A critical problem in the field of post hoc explainability is the lack of a common foundational goal among methods. For example, some methods are motivated by function approximation, some by game theoretic notions, and some by obtaining clean visualizations. This... View Details
Han, Tessa, Suraj Srinivas, and Himabindu Lakkaraju. "Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022). (Best Paper Award, International Conference on Machine Learning (ICML) Workshop on Interpretable ML in Healthcare.)
- 2022
- Article
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations
By: Jessica Dai, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach and Himabindu Lakkaraju
As post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to ensure that the quality of the resulting explanations is consistently high across all subgroups of a population. For instance, it... View Details
Dai, Jessica, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach, and Himabindu Lakkaraju. "Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 203–214.
- 2020
- Working Paper
Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective
We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the... View Details
Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science
Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
- January 2018
- Article
Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
By: Edward L. Glaeser, Scott Duke Kominers, Michael Luca and Nikhil Naik
New, "big" data sources allow measurement of city characteristics and outcome variables at higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big data has the most value for... View Details
Glaeser, Edward L., Scott Duke Kominers, Michael Luca, and Nikhil Naik. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life." Economic Inquiry 56, no. 1 (January 2018): 114–137.
- 08 Nov 2011
- First Look
First Look: Nov. 8
income taxation. I show analytically how age dependence improves policy on both the intratemporal and intertemporal margins. I use detailed numerical simulations, calibrated with data from the U.S. PSID, to generate robust policy... View Details
Keywords: Sean Silverthorne
- 16 Jan 2019
- Research & Ideas
What Football Firings Teach Managers About Staying Relevant
to pass the ball. Coupled with a growth in analytics and innovative offensive schemes, the NFL has seen an explosion in passing offense over the past two decades. The New England Patriots and head coach Bill Belichick have been at the... View Details
- February 2021 (Revised May 2021)
- Case
SafeGraph: Selling Data as a Service
By: Ramana Nanda, Abhishek Nagaraj and Allison Ciechanover
Set in January 2021, the CEO of SafeGraph, a four-year-old startup that sold Data as a Service, looked to the future. His aim was to become the most trusted source for data about a physical place. The company provided points of interest (POI) and foot traffic data on... View Details
Keywords: Data As A Service; Monetization; Pricing; Business Startups; Analytics and Data Science; Consumer Behavior; Analysis; Business Model; Health Pandemics; Information Industry; United States
Nanda, Ramana, Abhishek Nagaraj, and Allison Ciechanover. "SafeGraph: Selling Data as a Service." Harvard Business School Case 821-082, February 2021. (Revised May 2021.)
- 07 Jan 2013
- Lessons from the Classroom
Culture Changers: Managing High-Impact Entrepreneurs
does business management mean in this context? For some MBA students, the answers are something of an awakening. The ways that they have traditionally added value—by implementing top-notch business practices, using deep analytical skills... View Details
- 31 Jul 2006
- Research & Ideas
When Not to Trust Your Gut
in determining how and when to abandon intuition in favor of a more deliberate, analytical approach. Intuition And Rationality In Negotiation To explain why individuals don't always think rationally and logically, Keith Stanovich of the... View Details
Keywords: by Max H. Bazerman & Deepak Malhotra
- 11 Nov 2014
- First Look
First Look: November 11
Internet: adding digital sensors to its machines; connecting them to a common, cloud-based software platform; investing in software development capabilities; building advanced analytics capabilities; and embracing crowd-based product... View Details
Keywords: Sean Silverthorne