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- May–June 2023
- Article
Analytics for Marketers: When to Rely on Algorithms and When to Trust Your Gut
By: Fabrizio Fantini and Das Narayandas
Advanced analytics can help companies solve a host of management problems, including those related to marketing, sales, and supply-chain operations, which can lead to a sustainable competitive advantage. But as more data becomes available and advanced analytics are...
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- 2023
- Working Paper
El Dorado Lost: Local Elites, Real Estate and the Education Business in China
By: Geoffrey Jones and Yuhai Wu
This working paper examines the evolving, complex and multifaceted relationship between the real estate industry and the education sector in China. The current crises in the private education and real estate sectors caused by policy shifts reflect the inter-meshing of...
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- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer...
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- April 6, 2023
- Article
A New NFT Launch Strategy: The Wave Mint
By: Scott Duke Kominers and 1337 Skulls Sers
In an NFT project, the mint—the process by which tokens are initially allocated—largely determines who your community is and how they and the broader market view the project going forward. In this piece, we review a new minting strategy recently introduced by 1337...
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- 2023
- Article
Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.
By: Edward McFowland III and Cosma Rohilla Shalizi
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its...
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- April 2023
- Article
Inattentive Inference
By: Thomas Graeber
This paper studies how people infer a state of the world from information structures that include additional, payoff-irrelevant states. For example, learning from a customer review about a product’s quality requires accounting for the reviewer’s otherwise irrelevant...
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- March 2023
- Case
Patagonia: 'Earth Is Now Our Only Shareholder'
By: Brian Trelstad, Nien-hê Hsieh, Michael Norris and Susan Pinckney
Patagonia’s change of ownership from a privately held company to a perpetual purpose trust and 501(c)(4) nonprofit in order to use the company’s profit to fight the environmental crisis and be a model for future businesses.
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Keywords:
Trusts;
Business Ventures;
Business Organization;
Family Business;
Restructuring;
Change;
Disruption;
Transition;
Decision Making;
Ethics;
Values and Beliefs;
Finance;
Financial Management;
Governance;
Corporate Governance;
Investment Activism;
Leadership;
Labor;
Law;
Common Law;
Management;
Goals and Objectives;
Organizations;
Corporate Social Responsibility and Impact;
Mission and Purpose;
Organizational Change and Adaptation;
Organizational Culture;
Ownership;
Ownership Type;
Family Ownership;
Private Ownership;
Social Enterprise;
Nonprofit Organizations;
Society;
Social Issues;
Wealth and Poverty;
Value;
Value Creation;
Apparel and Accessories Industry;
United States
- March 2023
- Background Note
A Primer on OKRs
By: Suraj Srinivasan and Li-Kuan (Jason) Ni
The OKR framework is a popular goal-setting and strategy execution tool that uses goal setting through “Objectives” and measuring performance using “Key Results” on a periodic basis to measure and drive performance. The OKR framework has been adopted and practiced at...
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Keywords:
Business Organization;
Talent and Talent Management;
Framework;
Corporate Governance;
Goals and Objectives;
Growth and Development;
Growth and Development Strategy;
Growth Management;
Management Analysis, Tools, and Techniques;
Management Practices and Processes;
Management Skills;
Management Systems;
Measurement and Metrics;
Outcome or Result;
Performance Effectiveness;
Performance Evaluation;
Performance Expectations;
Performance Productivity;
Performance Efficiency
- March 2023
- Case
FinTunes, Inc., Board of Directors
By: Lynn S. Paine and Jennifer Fonstad
The board of FinTunes, Inc., a start-up aimed at helping musicians distribute their work and manage their finances, must decide among three candidates to serve as the company’s first independent director. The terms of FinTunes’ last round of financing provided that the...
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- March 2023
- Case
Woven Planet - Designing Software for the Car of the Future
By: Gary P. Pisano and Catherine Piner
Founded in 2021, Woven Planet Holdings—a subsidiary of Toyota Motor Corporation—was developing Arene, an automotive software platform consisting of an operating system, development and simulation tools, and a cloud-based service that could store and analyze vehicle...
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- 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...
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- January–February 2023
- Article
External Interfaces and Internal Processes: Market Positioning and Divergent Professionalization Paths in Young Ventures
By: Alicia DeSantola, Ranjay Gulati and Pavel Zhelyazkov
We explore how the initial market positioning of entrepreneurial ventures shapes how they professionalize over time, focusing specifically on the development of functional roles. In contrast to existing literature, which has presumed a uniform march toward...
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- 2022
- Article
Efficiently Training Low-Curvature Neural Networks
By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often...
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Keywords:
AI and Machine Learning
- 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...
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- October 2022
- Background Note
Note on Cyberattacks and Regulatory Regimes
Describes common types of cyberattacks on enterprises and their costs, as well as the fragmentary regulatory regimes through which U.S. states and regulatory agencies at the start of 2021 attempted to encourage disclosure of cyberattacks and to pursue enforcement...
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- 2022
- Working Paper
When Do Individuals Give Up Agency? The Role of Decision Avoidance
By: Holly Dykstra, Christine L. Exley and Muriel Niederle
A common policy problem is that individuals reject recommended options and insist on making their own choices. Via a large-scale experiment, we document and investigate what factors contribute to this preference for agency. Our main results show that individuals’...
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- 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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- September 2022
- Background Note
On CUE: The Quest for Optimal Customer Unit Economics
By: Elie Ofek, Barak Libai and Eitan Muller
Startups are often evaluated by how well they perform on unit economics, defined as the ratio of a customer’s lifetime value (LTV) to acquisition costs (CAC). A common target for unit economics, advocated by many VCs and analysts, is 3:1 (i.e., LTV/CAC=3). While there...
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- 2022
- Chapter
Coordinating Marketing and Sales in B2B Organizations
This Handbook is targeted at academics and graduate students who want an overview of the academic state of the business-to-business marketing domain and at B2B practitioners who want to be aware of the current state of knowledge in their domains. This chapter examines...
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- September–October 2022
- Article
Seeking Purity, Avoiding Pollution: Strategies for Moral Career Building
By: Erin Reid and Lakshmi Ramarajan
This study builds theory on how people construct moral careers. Analyzing interviews with 102 journalists, we show how people build moral careers by seeking jobs that allow them to fulfill both the institution’s moral obligations and their own material aims. We...
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