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- February 2024
- Article
Pricing Power in Advertising Markets: Theory and Evidence
By: Matthew Gentzkow, Jesse M. Shapiro, Frank Yang and Ali Yurukoglu
Existing theories of media competition imply that advertisers will pay a lower price in equilibrium to reach consumers who multi-home across competing outlets. We generalize, extend, and test this prediction. We find that television outlets whose viewers watch more... View Details
Gentzkow, Matthew, Jesse M. Shapiro, Frank Yang, and Ali Yurukoglu. "Pricing Power in Advertising Markets: Theory and Evidence." American Economic Review 114, no. 2 (February 2024): 500–533.
- June 2023
- Case
Investing in the Climate Transition at Neuberger Berman
By: George Serafeim and Benjamin Maletta
By mid-2023, Neuberger Berman (NB), an active asset manager, had grown its assets under management to about half a trillion dollars and took pride in its client centricity and innovative spirit. Responding to client demand for investment products that integrated... View Details
Keywords: Carbon Emissions; Sustainability; Decarbonization; Performance; Risk Assessment; Opportunities; Environmental Sustainability; Carbon Footprint; Business Analysis; Investing; Regulation; Asset Management; Investment Strategy; Climate Change; Transition; Analysis; Product Positioning; Strategy; Investment Portfolio; Financial Services Industry; Energy Industry
Serafeim, George, and Benjamin Maletta. "Investing in the Climate Transition at Neuberger Berman." Harvard Business School Case 123-092, June 2023.
- 2023
- Article
Provable Detection of Propagating Sampling Bias in Prediction Models
By: Pavan Ravishankar, Qingyu Mo, Edward McFowland III and Daniel B. Neill
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipeline but also to understand the downstream impacts of bias across stages. Here we consider... View Details
Ravishankar, Pavan, Qingyu Mo, Edward McFowland III, and Daniel B. Neill. "Provable Detection of Propagating Sampling Bias in Prediction Models." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (2023): 9562–9569. (Presented at the 37th AAAI Conference on Artificial Intelligence (2/7/23-2/14/23) in Washington, DC.)
- 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.
- 2022
- Working Paper
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details
Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
- April 2020 (Revised June 2022)
- Technical Note
Quantitative Analysis in Marketing
By: Sunil Gupta
Marketing is a combination of art and science that requires both qualitative and quantitative analysis to arrive at effective decisions. This note highlights how quantitative analysis can help in the following marketing decisions: estimating market size, determining... View Details
Gupta, Sunil. "Quantitative Analysis in Marketing." Harvard Business School Technical Note 520-091, April 2020. (Revised June 2022.)
- 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.)
- June 2018
- Case
Japan: Deficits, Deflation and Debt
By: Richard H.K. Vietor and Haviland Sheldahl-Thomason
In April 2018, Prime Minister Shinzo Abe was again in Washington to petition Donald Trump. After years of rapid, export-led growth, Japan had slumped into recession in 1991 and never really recovered. For the past 27 years, its economy has grown at 1.1% annually,... View Details
Keywords: Deflation; Debt; Country Analysis; Monetary Expansion; Population Growth; Inflation and Deflation; Borrowing and Debt; Economy; Energy; National Security; Japan
Vietor, Richard H.K., and Haviland Sheldahl-Thomason. "Japan: Deficits, Deflation and Debt." Harvard Business School Case 718-063, June 2018.
- June 2018
- Case
Forta Furniture: International Expansion
By: John A. Quelch and Karthik Easwar
The Forta Furniture case highlights the need to consider new market expansion to grow a firm. It demonstrates that simply doing what has always been done is not sustainable when other competitors enter the market with differentiated or potentially superior offerings.... View Details
Keywords: Market Entry and Exit; Global Range; Decision Making; Analysis; Cross-Cultural and Cross-Border Issues; Growth and Development Strategy; Brands and Branding; Expansion
Quelch, John A., and Karthik Easwar. "Forta Furniture: International Expansion." Harvard Business School Brief Case 918-547, June 2018.
- February 2018 (Revised June 2021)
- Case
New Constructs: Disrupting Fundamental Analysis with Robo-Analysts
By: Charles C.Y. Wang and Kyle Thomas
This case highlights the business challenges associated with a financial technology firm, New Constructs, that created a technology that can quickly parse complicated public firm financials to paint a clearer economic picture of firms, remove accounting distortions,... View Details
Keywords: Fundamental Analysis; Machine Learning; Robo-analysts; Financial Statements; Financial Reporting; Analysis; Information Technology; Accounting Industry; Financial Services Industry; Information Technology Industry; North America; Tennessee
Wang, Charles C.Y., and Kyle Thomas. "New Constructs: Disrupting Fundamental Analysis with Robo-Analysts." Harvard Business School Case 118-068, February 2018. (Revised June 2021.)
- November 28, 2017
- Editorial
Active Investing v.2.0
By: Gabriel Karageorgiou and George Serafeim
Keywords: Investment; Investing; Technology; Big Data; Quantitative Analysis; ESG; ESG (Environmental, Social, Governance) Performance; Sustainability; Analytics and Data Science
Karageorgiou, Gabriel, and George Serafeim. "Active Investing v.2.0." Pensions & Investments (online) (November 28, 2017).
- November 2016 (Revised March 2018)
- Module Note
Strategy Execution Module 9: Building a Balanced Scorecard
By: Robert Simons
This module reading explains how to construct a strategy map and build a balanced scorecard. Using an internal value chain model, the module illustrates how a balanced scorecard can support and enable customer management, innovation, operations, and post-sale service... View Details
Keywords: Management Control Systems; Implementing Strategy; Execution; Performance Measurement; Strategy Map; Business Goals; Customer Measures; Strategy; Balanced Scorecard; Business Model
Simons, Robert. "Strategy Execution Module 9: Building a Balanced Scorecard." Harvard Business School Module Note 117-109, November 2016. (Revised March 2018.)
- November 2016 (Revised December 2016)
- Module Note
Strategy Execution Module 7: Designing Asset Allocation Systems
By: Robert Simons
This module reading provides tools and analyses for acquiring and allocating resources. The module begins by reviewing the importance of setting strategic boundaries as a basis for asset acquisitions. Next, a distinction is made between new assets acquired to meet... View Details
Keywords: Management Control Systems; Implementing Strategy; Execution; Asset Allocation Systems; Payback; Discounted Cash Flow; Internal Rate Of Return; Strategic Investments; Analyzing Acquisitions; Strategy; Capital Budgeting
Simons, Robert. "Strategy Execution Module 7: Designing Asset Allocation Systems." Harvard Business School Module Note 117-107, November 2016. (Revised December 2016.)
- October 2016 (Revised December 2016)
- Module Note
Strategy Execution Module 6: Evaluating Strategic Profit Performance
By: Robert Simons
This module reading demonstrates how to calculate and analyze the profit generated by different business strategies. Formulas and examples are provided to calculate profit generated by changes in market share, revenue growth, efficiency improvements, and support costs.... View Details
Keywords: Management Control Systems; Implementing Strategy; Execution; Evaluating Business Performance; Profitability Analysis; Variance Analysis; Measuring Effectiveness; Measuring Efficiency; Activity-Based Costing; Flexible Budget; Accounting; Strategy
Simons, Robert. "Strategy Execution Module 6: Evaluating Strategic Profit Performance." Harvard Business School Module Note 117-106, October 2016. (Revised December 2016.)
- October 2016 (Revised February 2019)
- Module Note
Strategy Execution Module 5: Building a Profit Plan
By: Robert Simons
This module reading describes how to build a profit plan to reflect the strategy of a business in economic terms. After introducing the profit wheel, cash wheel, and ROE wheel, the module illustrates how to use a profit plan to assess the viability of different... View Details
Keywords: Management Control Systems; Implementing Strategy; Execution; Profit Planning; Cash Flow Analysis; Asset Utilization; Return On Equity; Business Planning; Testing Strategy; Analyzing Strategic Alternative; Strategy; Asset Management; Cash Flow; Investment Return; Management Systems; Profit
Simons, Robert. "Strategy Execution Module 5: Building a Profit Plan." Harvard Business School Module Note 117-105, October 2016. (Revised February 2019.)
- September 2016 (Revised January 2018)
- Module Note
Strategy Execution Module 4: Organizing for Performance
By: Robert Simons
This module reading explores the implications of different business models on organization design. After discussing the distinction between units focused on work processes and those devoted to markets, the analysis provides insight as to when to organize businesses by... View Details
Keywords: Management Control Systems; Implementing Strategy; Execution; Customer Focused Organization; Specialization; Span Of Control; Span Of Accountability; Span Of Attention; Strategy; Organizational Design; Organizational Structure
Simons, Robert. "Strategy Execution Module 4: Organizing for Performance." Harvard Business School Module Note 117-104, September 2016. (Revised January 2018.)
- 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
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.)
- August 2016 (Revised December 2016)
- Module Note
Strategy Execution Module 2: Building a Successful Strategy
By: Robert Simons
This module reading describes the basics of building a successful strategy. Topics in this module include a discussion of the distinction between corporate and business strategy; how to conduct a SWOT analysis of market dynamics and internal capabilities; the use of... View Details
Keywords: Management Control Systems; Implementing Strategy; Strategy Execution; Business Strategy; Five Forces; Distinctive Capabilities; Emergent Strategy; Mission Statements; Strategy; SWOT Analysis; Competitive Advantage
Simons, Robert. "Strategy Execution Module 2: Building a Successful Strategy." Harvard Business School Module Note 117-102, August 2016. (Revised December 2016.)
- 2019
- Working Paper
Fiscal Rules and Sovereign Default
By: Laura Alfaro and Fabio Kanczuk
Recurrent concerns over debt sustainability in emerging and developed nations have prompted renewed debate on the role of fiscal rules. Their optimality, however, remains unclear. We provide a quantitative analysis of fiscal rules in a standard model of sovereign debt... View Details
Alfaro, Laura, and Fabio Kanczuk. "Fiscal Rules and Sovereign Default." Harvard Business School Working Paper, No. 16-134, June 2016. (Also NBER Working Paper w23370. Revised January 2019.)