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Publications
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- April 2025
- Article
Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile
By: Shunyuan Zhang, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar and Xupin Zhang
Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling... View Details
- January–February 2025
- Article
Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing
By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley
For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details
- 2024
- Other Teaching and Training Material
Earth
By: Barry Nalebuff and Max Bazerman
Earth was created to provide participants with the opportunity to negotiate a solution to the most important environmental challenge that faces humanity — climate change. Just as finding solutions to climate change is challenging, students will be challenged to find a... View Details
- November 2024 (Revised January 2025)
- Case
MiDAS: Automating Unemployment Benefits
By: Shikhar Ghosh and Shweta Bagai
In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details
Keywords: Artificial Intelligence; AI; Machine Learning Models; Algorithmic Data; Automation; Benefits; Compensation; Cost Reduction; Government; Fraud; Government Technology; Public Sector; Systems; Systems Integration; Unemployment Insurance; Waste Heat Recovery; AI and Machine Learning; Government Administration; Insurance; Decision Making; Digital Transformation; Employment; Public Administration Industry; United States; Michigan
- November–December 2024
- Article
Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing
By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment... View Details
- October 2024
- Case
Reed Group and Succession in a Family Business: An Impossible Job to Fill?
By: Lauren H. Cohen and Tonia Labruyere
James Reed had taken over Reed Group, the recruitment and career services company his father had founded and built, in 1994. He was now reflecting on succession planning and other challenges that lay ahead: with no obvious choice among his family members, he needed to... View Details
- 2024
- Working Paper
Learning to Cover: Online Learning and Optimization with Irreversible Decisions
By: Alexander Jacquillat and Michael Lingzhi Li
- 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; Retail Industry; Consumer Products Industry; Beauty and Cosmetics Industry; India
- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
- March 2024 (Revised August 2024)
- Case
Darktrace: Scaling Cybersecurity and AI (A)
By: Jeffrey F. Rayport and Alexis Lefort
In 2023, Darktrace CEO Poppy Gustafsson was contemplating her growth strategy at a leading U.K.-based cybersecurity venture, launched in 2013 by a group of anti-terror cyber specialists, University of Cambridge mathematicians, and artificial intelligence (AI) experts.... View Details
Keywords: Technology; Talent; Scaling; Entrepreneurship; Cybersecurity; Leadership; Business Growth and Maturation; Recruitment; Resignation and Termination; AI and Machine Learning; Growth and Development Strategy; Organizational Culture; Going Public; Technology Industry; United Kingdom; Europe; United States
- February 2024 (Revised July 2024)
- Case
Taffi: Entrepreneurship in Saudi Arabia
By: Paul A. Gompers and Fares Khrais
Taffi was a tech-enabled fashion styling startup founded by Shahad Geoffrey in Saudi Arabia in 2020. Within three years of operating, Geoffrey had pivoted the business multiple times. In 2023, Geoffrey was attempting the business’s most ambitious pivot yet, shifting... View Details
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
- 2023
- Working Paper
The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks
By: Isamar Troncoso, Minkyung Kim, Ishita Chakraborty and SooHyun Kim
The US has seen a rise in union movements, but their effects on service industry marketing outcomes like customer satisfaction and perceptions of service quality remain understudied. In this paper, we empirically study the impact on customer satisfaction and... View Details
- October 2023 (Revised January 2024)
- Case
SEK: Reimagining Spanish Higher Education at Universidad Camilo José Cela (UCJC)
By: John J-H Kim, Mary C. Sauer and Emilie Billaud
In 2023, Nieves Segovia, President of the SEK Education Group in Spain, contemplates the future of her family's for-profit education company, which includes K-12 schools and the newly established UCJC university. Renowned for its innovation in education, SEK faces... View Details
- 2023
- Working Paper
The Customer Journey as a Source of Information
By: Nicolas Padilla, Eva Ascarza and Oded Netzer
In the face of heightened data privacy concerns and diminishing third-party data access,
firms are placing increased emphasis on first-party data (1PD) for marketing decisions.
However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details
- September 2023 (Revised June 2024)
- Case
Kaspi.kz: Building Trust through Innovation
By: Sandra J. Sucher, Fares Khrais and Marilyn Morgan Westner
This case is written to help students explore how companies can maintain and develop trust while innovating, how to identify and respond effectively to warning signs that they may not be as trusted as they believe, and how being trusted can aid in expanding and growing... View Details
- 2023
- Working Paper
Learning to Use: Stack Overflow and Technology Adoption
By: Daniel Jay Brown and Maria P. Roche
In this paper, we examine the potential impact of Q&A websites on the adoption of technologies.
Using data from Stack Overflow – one of the most popular Q&A websites worldwide
– and implementing an instrumental-variable approach, we find that users whose questions... View Details
- June 2023 (Revised July 2023)
- Case
Social Media Background Screening at Fama Technologies
By: Joseph Pacelli, Jillian Grennan and Alexis Lefort
Fama Technologies is an online screening company that uses AI to analyze job applicants' publicly available online content for signs of risk and culture fit. The case opens with Ben Mones, founder and CEO, looking to secure funding from venture firms. He is running... View Details
- 2022
- Article
A Human-Centric Take on Model Monitoring
By: Murtuza Shergadwala, Himabindu Lakkaraju and Krishnaram Kenthapadi
Predictive models are increasingly used to make various consequential decisions in high-stakes domains such as healthcare, finance, and policy. It becomes critical to ensure that these models make accurate predictions, are robust to shifts in the data, do not rely on... View Details