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Introduction
By: Stefano Brusoni, Joachim Henkel, Michael G Jacobides, Samina Karim, Alan MacCormack, Phanish Puranam and Melissa Schilling
In 2000, Carliss Baldwin and Kim Clark published Design Rules: The Power of Modularity, a book that introduced new ways of understanding and explaining the architecture of complex systems. This Special Issue of Industrial and Corporate Change celebrates...
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Keywords:
Complex Systems;
Industry Structure;
Systems Design;
Complexity;
Organizational Design;
Competitive Strategy;
Innovation and Management
Brusoni, Stefano, Joachim Henkel, Michael G Jacobides, Samina Karim, Alan MacCormack, Phanish Puranam, and Melissa Schilling. "Introduction." Special Issue on The Power of Modularity: Twenty Years of Design Rules. Industrial and Corporate Change 32, no. 1 (February 2023): 1–10.
- 2022
- Working Paper
Regulatory Incentives for Innovation: The FDA's Breakthrough Therapy Designation
By: Amitabh Chandra, Jennifer Kao, Kathleen Miller and Ariel D. Stern
Regulators of new products confront a tradeoff between speeding a new product to market and collecting additional product quality information. The FDA’s Breakthrough Therapy Designation (BTD) provides an opportunity to understand if a regulator can use new policy to...
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Chandra, Amitabh, Jennifer Kao, Kathleen Miller, and Ariel D. Stern. "Regulatory Incentives for Innovation: The FDA's Breakthrough Therapy Designation." NBER Working Paper Series, No. 30712, December 2022.
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
AI and Machine Learning;
Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- 2022
- Book
Healthy Buildings: How Indoor Spaces Can Make You Sick—or Keep You Well
By: Joseph G. Allen and John D. Macomber
For too long we’ve designed buildings that haven’t focused on the people inside—their health, their ability to work effectively, and what that means for the bottom line. An authoritative introduction to a movement whose vital importance is now all too clear, Healthy...
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Allen, Joseph G., and John D. Macomber. Healthy Buildings: How Indoor Spaces Can Make You Sick—or Keep You Well. Revised and updated edition, Cambridge, MA: Harvard University Press, 2022.
- 2022
- Working Paper
Are Transformational Ideas Harder to Fund? Resource Allocation to R&D Projects at a Global Pharmaceutical Firm
By: Joshua Krieger and Ramana Nanda
We study resource allocation to early-stage ideas at an internal startup program of one the largest pharmaceutical firms in the world. Our research design enables us to elicit every evaluator's scores across five different attributes, before seeing how would allocate...
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Keywords:
Project Selection;
Pharmaceuticals;
Financing Innovation;
Resource Allocation;
Innovation and Invention;
Research and Development
Krieger, Joshua, and Ramana Nanda. "Are Transformational Ideas Harder to Fund? Resource Allocation to R&D Projects at a Global Pharmaceutical Firm." Harvard Business School Working Paper, No. 23-014, August 2022.
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats...
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Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Special Issue on Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022). Proceedings of Machine Learning Research (PMLR) 180 (2022): 1264–1274.
- 2022
- Book
Purpose + Profit: How Business Can Lift Up the World
By: George Serafeim
The roadmap and best practices to reap the enormous value that can emerge when your business prioritizes social and environmental goals—such as climate change, diversity and inclusion, and sustainability—right alongside the pursuit of profit.
We not only... View Details
We not only... View Details
Keywords:
ESG (Environmental, Social, Governance) Performance;
Profitability;
Business And Society;
Organizations;
Mission and Purpose;
Goals and Objectives;
Social Issues;
Environmental Sustainability;
Value Creation;
Organizational Change and Adaptation
Serafeim, George. Purpose + Profit: How Business Can Lift Up the World. New York: HarperCollins Leadership, 2022.
- July 2022
- Article
A Strategic View of Team Learning in Organizations
By: Jean-François Harvey, Henrik Bresman, Amy C. Edmondson and Gary P. Pisano
Research in strategic management and organizational behavior has increasingly focused on understanding how organizations achieve and sustain performance in fast-changing environments. Strategy research suggests that senior managers, through their decisions, influence...
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Keywords:
Strategic Management;
Organization Behavior;
Teams;
Organizational Capabilities;
Groups and Teams;
Learning;
Management;
Decision Making;
Performance;
Organizational Design
Harvey, Jean-François, Henrik Bresman, Amy C. Edmondson, and Gary P. Pisano. "A Strategic View of Team Learning in Organizations." Academy of Management Annals 16, no. 2 (July 2022): 476–507.
- 2022
- Chapter
Redirecting Rawlsian Reasoning Toward the Greater Good
By: Joshua D. Greene, Karen Huang and Max Bazerman
In A Theory of Justice, John Rawls employed the ‘veil of Ignorance’ as a moral reasoning device designed to promote impartial thinking. By imagining the choices of decision-makers who are blind to biasing information, one might see more clearly the organizing...
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Greene, Joshua D., Karen Huang, and Max Bazerman. "Redirecting Rawlsian Reasoning Toward the Greater Good." Chap. 15 in The Oxford Handbook of Moral Psychology, edited by Manuel Vargas and John M. Doris, 246–261. Oxford, UK: Oxford University Press, 2022.
- June 2022
- Case
Strategic Innovation at the United Nations: A Network of Ecosystems
By: Frank Nagle, Elizabeth J. Altman and Amy Klopfenstein
In 2021, Gina Lucarelli, leader of the United Nations Development Programme (UNDP) Accelerator Labs, prepared for a meeting with UNDP Administrator Achim Steiner. The two planned to discuss the future of the Accelerator Labs, a network of social innovation labs located...
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Keywords:
Change;
Disruption;
Transformation;
Change Management;
Education;
Learning;
Environmental Management;
Climate Change;
Environmental Sustainability;
Geography;
Geographic Scope;
Global Range;
Local Range;
Geopolitical Units;
Country;
Human Resources;
Recruitment;
Retention;
Selection and Staffing;
Employees;
Employee Relationship Management;
Information Technology;
Information Management;
Innovation and Invention;
Collaborative Innovation and Invention;
Disruptive Innovation;
Innovation and Management;
Innovation Leadership;
Innovation Strategy;
Knowledge;
Knowledge Acquisition;
Knowledge Dissemination;
Knowledge Management;
Knowledge Sharing;
Knowledge Use and Leverage;
Organizations;
Mission and Purpose;
Organizational Culture;
Organizational Structure;
Organizational Design;
Organizational Change and Adaptation;
Social Enterprise;
Non-Governmental Organizations;
Social Psychology;
Social and Collaborative Networks;
Society;
Social Issues;
Welfare;
Strategy;
Cooperation;
Adaptation;
Public Administration Industry;
North and Central America
Nagle, Frank, Elizabeth J. Altman, and Amy Klopfenstein. "Strategic Innovation at the United Nations: A Network of Ecosystems." Harvard Business School Case 722-363, June 2022.
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...
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Keywords:
Machine Learning Models;
Counterfactual Explanations;
Adversarial Examples;
Mathematical Methods
Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
- Article
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that...
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Keywords:
Difference In Differences;
Staggered Difference-in-differences Designs;
Generalized Difference-in-differences;
Dynamic Treatment Effects;
Mathematical Methods
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395. (Editor's Choice, May 2022.)
- 2022
- Working Paper
A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure
By: Jesse M. Shapiro and Liyang Sun
Linear panel models featuring unit and time fixed effects appear in many areas of empirical economics. An active literature studies the interpretation of the ordinary least squares estimator of the model, commonly called the two-way fixed effects (TWFE) estimator, in...
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Shapiro, Jesse M., and Liyang Sun. "A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure." NBER Working Paper Series, No. 29976, April 2022.
- 2022
- Article
Social Interactivity in Live Video Experiences Reduces Loneliness
By: Benjamin T. Kaveladze, Robert R. Morris, Rosa Victoria Dimitrova-Gammeltoft, Amit Goldenberg, James J. Gross, Judd Antin, Melissa Sandgren and Melissa C. Thomas-Hunt
Background: Loneliness, especially when chronic, can substantially reduce one's quality of life. However, positive social experiences might help to break cycles of loneliness by promoting more prosocial cognitions and behaviors. Internet-mediated live video...
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Keywords:
Lonelines;
Social Connection;
Internet-mediated Communication;
Experiment;
Emotions;
Well-being;
Interpersonal Communication;
Internet
Kaveladze, Benjamin T., Robert R. Morris, Rosa Victoria Dimitrova-Gammeltoft, Amit Goldenberg, James J. Gross, Judd Antin, Melissa Sandgren, and Melissa C. Thomas-Hunt. "Social Interactivity in Live Video Experiences Reduces Loneliness." Frontiers in Digital Health 4:859849 (2022).
- March 2022
- Article
Sensitivity Analysis of Agent-based Models: A New Protocol
By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such...
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Keywords:
Agent-based Modeling;
Sensitivity Analysis;
Design Of Experiments;
Total Order Sensitivity Indices;
Organizations;
Behavior;
Decision Making;
Mathematical Methods
Borgonovo, Emanuele, Marco Pangallo, Jan Rivkin, Leonardo Rizzo, and Nicolaj Siggelkow. "Sensitivity Analysis of Agent-based Models: A New Protocol." Computational and Mathematical Organization Theory 28, no. 1 (March 2022): 52–94.
- March 2022
- Article
Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field
Identifying high-growth microentrepreneurs in low-income countries remains a challenge due to a scarcity of verifiable information. With a cash grant experiment in India we demonstrate that community knowledge can help target high-growth microentrepreneurs; while the...
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Keywords:
Microentrepreneurs;
Community Information;
Field Experiment;
Loans;
Entrepreneurship;
Developing Countries and Economies;
Financing and Loans;
Information;
Mathematical Methods;
India
Hussam, Reshmaan, Natalia Rigol, and Benjamin N. Roth. "Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field." American Economic Review 112, no. 3 (March 2022): 861–898.
- February 2022 (Revised September 2022)
- Case
InstaDeep: AI Innovation Born in Africa (A)
By: Shikhar Ghosh and Esel Çekin
Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.]....
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Keywords:
AI;
Artificial Intelligence;
Entrepreneurship;
Operations;
Business Subsidiaries;
Brands and Branding;
Innovation and Invention;
Growth and Development Strategy;
AI and Machine Learning;
Technology Industry;
Africa
Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (A)." Harvard Business School Case 822-104, February 2022. (Revised September 2022.)
- February 2022 (Revised July 2022)
- Supplement
InstaDeep: AI Innovation Born in Africa (B)
By: Shikhar Ghosh and Esel Çekin
Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.]....
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Keywords:
AI;
Artificial Intelligence;
Entrepreneurship;
Operations;
Business Subsidiaries;
Brands and Branding;
Innovation and Invention;
Growth and Development Strategy;
AI and Machine Learning;
Technology Industry;
Africa
Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (B)." Harvard Business School Supplement 822-105, February 2022. (Revised July 2022.)
- 2022
- Book
The Role of Innovation and Entrepreneurship in Economic Growth
By: Michael J. Andrews, Aaron Chatterji, Josh Lerner and Scott Stern
We live in an era in which innovation and entrepreneurship seem ubiquitous, particularly in regions like Silicon Valley, Boston, and the Research Triangle Park. But many metrics of economic growth, such as productivity growth and business dynamism, have been at best...
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Keywords:
Productivity Growth;
Production Technologies;
Innovation and Invention;
Entrepreneurship;
Economic Growth;
Competition;
Organizational Design;
Economic Slowdown and Stagnation
Andrews, Michael J., Aaron Chatterji, Josh Lerner, and Scott Stern, eds. The Role of Innovation and Entrepreneurship in Economic Growth. Chicago: University of Chicago Press, 2022.
- 2022
- Working Paper
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh
As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between...
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Keywords:
Natural Language Conversations;
AI and Machine Learning;
Experience and Expertise;
Interactive Communication;
Business and Stakeholder Relations
Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.