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- November–December 2024
- Article
How to Avoid the Agility Trap
By: Jianwen Liao and Feng Zhu
Agility is all the rage in strategy circles these days. According to conventional wisdom, organizations should rapidly react to technological advances, new market dynamics, and shifting consumer preferences. But in practice this is nearly impossible to pull off,... View Details
Keywords: Organizational Change and Adaptation; Competitive Advantage; Growth and Development Strategy; Business Model
Liao, Jianwen, and Feng Zhu. "How to Avoid the Agility Trap." Harvard Business Review 102, no. 6 (November–December 2024): 126–133.
- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
Keywords: Churn; Churn Management; Churn/retention; Assortment Planning; Retail; Retailing; Retailing Industry; Preference Heterogeneity; Assortment Optimization; Customers; Retention; Consumer Behavior; Forecasting and Prediction; Retail Industry
Anderson, Eric, Chaoqun Chen, Ayelet Israeli, and Duncan Simester. "Canary Categories." Journal of Marketing Research (JMR) 61, no. 5 (October 2024): 872–890.
- 2024
- Working Paper
When Batteries Meet Hydrogen: Dual-Storage Investments for Load-Shifting Purposes
By: Christian Kaps and Simone Marinesi
Power systems account for nearly 40% of global emissions. As the world tries to reduce emissions by increasing renewable penetration, storage technologies are playing an increasingly important role in matching variable renewable supply with demand. Batteries have... View Details
Keywords: Environmental Sustainability; Renewable Energy; Transition; Utilities Industry; Utilities Industry
Kaps, Christian, and Simone Marinesi. "When Batteries Meet Hydrogen: Dual-Storage Investments for Load-Shifting Purposes." Working Paper, October 2024.
- September 2024 (Revised October 2024)
- Case
Anker Innovations (A)
By: Feng Zhu, Jiangyong Lu and Nancy Hua Dai
An Amazon-native brand, Anker is the world’s No. 1 mobile charging brand and a leading consumer electronics company. Over the years, Anker developed an effective model of proving new products online first by leveraging customer insights from its proprietary Voice of... View Details
- September 2024
- Supplement
Anker Innovations (B)
By: Feng Zhu, Jiangyong Lu and Nancy Hua Dai
An Amazon-native brand, Anker is the world’s No. 1 mobile charging brand and a leading consumer electronics company. Over the years, Anker developed an effective model of proving new products online first by leveraging customer insights from its proprietary Voice of... View Details
- 2024
- Working Paper
The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis
By: Shirley Lu and George Serafeim
Leveraging advancements in large language models (LLM), we study the financial characteristics of firms offering climate solutions-products and services aimed at fostering a transition to a low-carbon economy. We use a new measure that applies LLM to 10-K Item 1... View Details
Keywords: Climate; Climate Finance; Innovation; Technology; Financial Statement Analysis; AI and Machine Learning; Climate Change; Environmental Sustainability; Analysis; Financial Statements
Lu, Shirley, and George Serafeim. "The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis." Harvard Business School Working Paper, No. 25-026, August 2024.
- July 2024
- Case
ZEISS: Commercializing Science
By: Maria P. Roche, Carlota Moniz and Daniela Beyersdorfer
Karl Lamprecht, President and CEO of the ZEISS AG Group, mused on how far ZEISS had come in 175 years of being a pioneer in optics, and how the course he had charted since taking the helm of the company could keep it on track. In his role, he oversaw the four core... View Details
Keywords: Business Model; Business Organization; Decisions; Business Strategy; Competition; Business History; Collaborative Innovation and Invention; Independent Innovation and Invention; Disruptive Innovation; Innovation and Management; Innovation Strategy; Technological Innovation; Growth and Development Strategy; Knowledge Sharing; Industry Growth; Monopoly; Organizational Culture; Supply Chain; Supply Chain Management; Relationships; Partners and Partnerships; Risk and Uncertainty; Adaptation; Commercialization; Semiconductor Industry; Technology Industry; Germany; Europe
Roche, Maria P., Carlota Moniz, and Daniela Beyersdorfer. "ZEISS: Commercializing Science." Harvard Business School Case 725-359, July 2024.
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- July 2024
- Article
How Artificial Intelligence Constrains Human Experience
By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
Keywords: Large Language Model; User Experience; AI and Machine Learning; Consumer Behavior; Technology Adoption; Risk and Uncertainty; Cost vs Benefits
Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
- 2024
- Working Paper
How Inflation Expectations De-Anchor: The Role of Selective Memory Cues
By: Nicola Gennaioli, Marta Leva, Raphael Schoenle and Andrei Shleifer
In a model of memory and selective recall, household inflation expectations remain rigid when inflation is anchored but exhibit sharp instability during inflation surges, as similarity prompts retrieval of forgotten high-inflation experiences. Using data from the New... View Details
Gennaioli, Nicola, Marta Leva, Raphael Schoenle, and Andrei Shleifer. "How Inflation Expectations De-Anchor: The Role of Selective Memory Cues." NBER Working Paper Series, No. 32633, June 2024.
- 2024
- Working Paper
Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations
By: Raviv Murciano-Goroff, Ran Zhuo and Shane Greenstein
How prevalent are severe software vulnerabilities, how fast do software users respond to the availability of secure versions, and what determines the variance in the installation distribution? Using the largest dataset ever assembled on user updates, tracking server... View Details
Murciano-Goroff, Raviv, Ran Zhuo, and Shane Greenstein. "Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations." NBER Working Paper Series, No. 32696, July 2024.
- June 2024
- Module Note
Value Creation Potential of New Business Models
By: David J. Collis
A business model is composed of three elements. These describe a generic way of creating value and identify the maximum potential value of that model for customers. The elements of a business model are the “job to be done” for the customer, the asset configuration, or... View Details
- 2024
- Working Paper
AI Companions Reduce Loneliness
By: Julian De Freitas, Ahmet K Uguralp, Zeliha O Uguralp and Puntoni Stefano
Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details
De Freitas, Julian, Ahmet K Uguralp, Zeliha O Uguralp, and Puntoni Stefano. "AI Companions Reduce Loneliness." Harvard Business School Working Paper, No. 24-078, June 2024.
- June 2024 (Revised August 2024)
- Case
Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard
By: Tatiana Sandino and Samuel Grad
Revlon India was founded as a joint venture in 1995, pairing the industrial conglomerate UMG with the global beauty brand Revlon, Inc. to bring international color cosmetics to India. After growing rapidly and pioneering the Beauty Advisor (BA) model in India, the... View Details
Keywords: Balanced Scorecard; Restructuring; Training; Supply Chain Management; Distribution; E-commerce; Business Model; Business Plan; Decision Choices and Conditions; Marketing Strategy; Alignment; Brands and Branding; Negotiation; Joint Ventures; Strategic Planning; Salesforce Management; Competition; Consumer Products Industry; Consumer Products Industry; Consumer Products Industry; India
Sandino, Tatiana, and Samuel Grad. "Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard." Harvard Business School Case 124-107, June 2024. (Revised August 2024.)
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- June 2024
- Article
Information Spillovers in Experience Goods Competition
By: Zhuoqiong Charlie Chen, Christopher Stanton and Catherine Thomas
When experience goods compete, consuming one product can be informative about value for similar untried products. We study a two-period model of duopoly competition in markets that have this feature and where firms can price discriminate between consumers based on... View Details
Chen, Zhuoqiong Charlie, Christopher Stanton, and Catherine Thomas. "Information Spillovers in Experience Goods Competition." Management Science 70, no. 6 (June 2024): 3923–3950.
- 2024
- Working Paper
Personalization and Targeting: How to Experiment, Learn & Optimize
By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details
Keywords: Personalization; Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; AI and Machine Learning
Lemmens, Aurelie, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela, and Oded Netzer. "Personalization and Targeting: How to Experiment, Learn & Optimize." Working Paper, June 2024.
- May 2024
- Article
True Costs of Uterine Artery Embolization: Time-Driven Activity-Based Costing in Interventional Radiology Over a 3-Year Period
By: Julia C. Bulman, Nicole H. Kim, Robert S. Kaplan, Sarah Schroeppel DeBacker, Olga R. Brook and Ammar Sarwar
The study used time-driven activity-based costing (TDABC) to estimate the costs to perform uterine artery embolization (UAE). Utilization times for patients undergoing outpatient UAE for fibroids or adenomyosis were captured from electronic health record timestamps and... View Details
Bulman, Julia C., Nicole H. Kim, Robert S. Kaplan, Sarah Schroeppel DeBacker, Olga R. Brook, and Ammar Sarwar. "True Costs of Uterine Artery Embolization: Time-Driven Activity-Based Costing in Interventional Radiology Over a 3-Year Period." Journal of the American College of Radiology 21, no. 5 (May 2024): 721–728.
- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.