Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
  • Research
    • Research
    • Publications
    • Global Research Centers
    • Case Development
    • Initiatives & Projects
    • Research Services
    • Seminars & Conferences
    →
  • Publications→

Publications

Publications

Filter Results: (1,720) Arrow Down
Filter Results: (1,720) Arrow Down Arrow Up

Show Results For

  • All HBS Web  (1,720)
    • People  (9)
    • News  (316)
    • Research  (1,050)
    • Events  (15)
    • Multimedia  (10)
  • Faculty Publications  (863)

Show Results For

  • All HBS Web  (1,720)
    • People  (9)
    • News  (316)
    • Research  (1,050)
    • Events  (15)
    • Multimedia  (10)
  • Faculty Publications  (863)
← Page 42 of 1,720 Results →
  • November 2019
  • Article

How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework

By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details
Keywords: Nerlove-Arrow Framework; Stock-of-goodwill; Dynamic Panel Data; Serial Correlation; Instrumental Variables; Sales Effectiveness; Detailing; Analytics and Data Science; Sales; Analysis; Performance Effectiveness; Pharmaceutical Industry
Citation
Find at Harvard
Read Now
Related
Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework." Management Science 65, no. 11 (November 2019): 5197–5218.
  • February 2011
  • Supplement

Dataset for "Slots, Tables, and All That Jazz: Managing Customer Profitability at the MGM Grand Hotel" (CW)

By: Dennis Campbell and Francisco de Asis Martinez-Jerez
Datasets of gaming and hotel customers to perform analysis for the case. View Details
Keywords: Analytics and Data Science; Games, Gaming, and Gambling; Las Vegas
Citation
Purchase
Related
Campbell, Dennis, and Francisco de Asis Martinez-Jerez. Dataset for "Slots, Tables, and All That Jazz: Managing Customer Profitability at the MGM Grand Hotel" (CW). Harvard Business School Spreadsheet Supplement 111-711, February 2011.
  • 01 Mar 2013
  • News

Faculty Books

Enterprise Analytics: Optimize Performance, Process, and Decisions through Big Data edited by Thomas Davenport (FT Press) This book, a collection of research papers from the International Institute for Analytics, addresses a wide variety of topics in managing business... View Details
  • Career Coach

Lee Scott

Lee started her career in the nonprofit sector. She has spent the last few years transitioning into an impact investing role. She can provide advice on switching sectors and strategizing how to build out relevant skillsets. Work Experience: J.P. Morgan (MBA... View Details
  • 2023
  • Article

Experimental Evaluation of Individualized Treatment Rules

By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
Citation
Find at Harvard
Read Now
Related
Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
  • September 2016 (Revised March 2017)
  • Module Note

Strategy Execution Module 3: Using Information for Performance Measurement and Control

By: Robert Simons
This module reading explains how managers use information to control critical business processes and outcomes. The analysis begins by illustrating how managers use information to communicate goals and track performance. Then the focus turns to the choices that managers... View Details
Keywords: Management Control Systems; Implementing Strategy; Strategy Execution; Organization Process; Feedback Model; Innovation; Uses Of Information; Big Data; Benchmarking; Decision Making; Information; Performance Evaluation; Analytics and Data Science
Citation
Purchase
Related
Simons, Robert. "Strategy Execution Module 3: Using Information for Performance Measurement and Control." Harvard Business School Module Note 117-103, September 2016. (Revised March 2017.)
  • October 2000 (Revised April 2003)
  • Background Note

Project Finance Research, Data, and Information Sources

By: Benjamin C. Esty and Fuaad Qureshi
Documents the major sources of project finance research and data. It is to be a reference guide for MBA students writing for the elective curriculum course, Large-scale Investment, and for others interested in the field of project finance. View Details
Keywords: Analytics and Data Science; Project Finance; Research; Investment
Citation
Find at Harvard
Related
Esty, Benjamin C., and Fuaad Qureshi. "Project Finance Research, Data, and Information Sources ." Harvard Business School Background Note 201-041, October 2000. (Revised April 2003.)
  • August 2024
  • Technical Note

Introduction to Data Analysis in Python

By: Michael Parzen and Jo Ellery
This note introduces Python as a tool for data science, including the Pandas library for data analysis. View Details
Keywords: Analytics and Data Science
Citation
Educators
Purchase
Related
Parzen, Michael, and Jo Ellery. "Introduction to Data Analysis in Python." Harvard Business School Technical Note 625-016, August 2024.
  • 2023
  • Working Paper

Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial intelligence and machine learning business applications. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms)... View Details
Keywords: Analytics and Data Science
Citation
SSRN
Read Now
Related
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
  • 14 Dec 2015
  • Research & Ideas

Deflategate and the Sustained Success of the New England Patriots

organizations involved. But Deflategate isn’t the only issue examined by the case. “What started essentially as an analytics exercise ended up as a much broader analysis of the data, the sport, the NFL, and how it’s organized and how it’s... View Details
Keywords: by Roberta Holland; Sports
  • Forthcoming
  • Article

Slowly Varying Regression Under Sparsity

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details
Keywords: Mathematical Methods; Analytics and Data Science
Citation
Find at Harvard
Read Now
Purchase
Related
Bertsimas, Dimitris, Vassilis Digalakis Jr, Michael Lingzhi Li, and Omar Skali Lami. "Slowly Varying Regression Under Sparsity." Operations Research (forthcoming). (Pre-published online March 27, 2024.)
  • 2024
  • Working Paper

Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python

By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Citation
SSRN
Read Now
Related
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
  • May 8, 2020
  • Article

Which Covid-19 Data Can You Trust?

By: Satchit Balsari, Caroline Buckee and Tarun Khanna
The COVID-19 pandemic has produced a tidal wave of data, but how much of it is any good? And as a layperson, how can you sort the good from the bad? The authors suggest a few strategies for dividing the useful data from the misleading: Beware of data that’s too broad... View Details
Keywords: COVID-19 Pandemic; Health Pandemics; Analytics and Data Science
Citation
Register to Read
Related
Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
  • Article

Beyond Statistics: The Economic Content of Risk Scores

By: Liran Einav, Amy Finkelstein, Raymond Kluender and Paul Schrimpf
"Big data" and statistical techniques to score potential transactions have transformed insurance and credit markets. In this paper, we observe that these widely-used statistical scores summarize a much richer heterogeneity, and may be endogenous to the context in which... View Details
Keywords: Analytics and Data Science; Risk and Uncertainty; Insurance Industry
Citation
Find at Harvard
Read Now
Related
Einav, Liran, Amy Finkelstein, Raymond Kluender, and Paul Schrimpf. "Beyond Statistics: The Economic Content of Risk Scores." American Economic Journal: Applied Economics 8, no. 2 (April 2016): 195–224.
  • February 25, 2016
  • Article

The Hodgepodge Principle in U.S. Privacy Policy

By: John A. Deighton
Data, says Professor Lawrence Summers, is the new oil, "a hugely valuable asset essential to economic life." Personal data, the kind of data that invites thoughts of privacy, is a big part of that. The European Union saw this economic fuel source coming long ago and... View Details
Keywords: Data; Privacy; Technology; Big Data; Personal Data; Marketing; Information Technology; Analytics and Data Science
Citation
Read Now
Deighton, John A. "The Hodgepodge Principle in U.S. Privacy Policy." Harvard Law and Policy Review Blog (March 2, 2016). http://harvardlpr.com/2016/03/02/the-hodgepodge-principle-in-us-privacy-policy/.
  • Web

Cookie Information | HBS Online

optout.networkadvertising.org We may use third party analytics such as Google Analytics or similar analytics services. For information on how Google processes and collects... View Details
  • 01 Sep 2010
  • News

Faculty Books

The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance by Marshall Fisher and Ananth Raman (Harvard Business Press) Professor Raman and his coauthor explain how to use View Details
Keywords: Retail Trade; Water Transportation; Transportation
  • 25 Aug 2017
  • Blog Post

HBS Interns: Summer Takeovers

in technology at the Sephora Innovation Lab. Jenn researched the impacts of artificial intelligence on the retail industry and participated in idea hackathons to brainstorm creative new ways for the brand to innovate. Adam Behrens, View Details
Keywords: All Industries
  • November 2016 (Revised April 2017)
  • Case

Basecamp: Pricing

By: Frank Cespedes and Robb Fitzsimmons
A data analyst at Basecamp is evaluating the results of pricing research and its potential implications for the venture’s latest version of its project management software product. View Details
Keywords: Pricing; Entrepreneurial Management; Data Analysis; Marketing; Customer Acquisition; Customer Retention; Value Proposition; Sales Management; Product Management; Market Research; Life Time Value; Testing; Entrepreneurship; Analytics and Data Science; Customers; Value; Sales; Product Marketing; United States
Citation
Educators
Purchase
Related
Cespedes, Frank, and Robb Fitzsimmons. "Basecamp: Pricing." Harvard Business School Case 817-067, November 2016. (Revised April 2017.)
  • December 1998
  • Case

Origins of National Income Accounting

By: David A. Moss and Joseph P Gownder
Set in the Great Depression, this case explores the origins of national income accounting in the United States. Highlights Senator La Follette's 1932 proposal for the federal government to begin collecting national income statistics. View Details
Keywords: Accounting; Financial Crisis; Analytics and Data Science; Mathematical Methods; United States
Citation
Educators
Purchase
Related
Moss, David A., and Joseph P Gownder. "Origins of National Income Accounting." Harvard Business School Case 799-080, December 1998.
  • ←
  • 42
  • 43
  • …
  • 85
  • 86
  • →
ǁ
Campus Map
Harvard Business School
Soldiers Field
Boston, MA 02163
→Map & Directions
→More Contact Information
  • Make a Gift
  • Site Map
  • Jobs
  • Harvard University
  • Trademarks
  • Policies
  • Accessibility
  • Digital Accessibility
Copyright © President & Fellows of Harvard College.