Publications
Publications
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(4,045)
- Faculty Publications (1,261)
- Winter 2021
- Article
Dealmaking Disrupted: The Unexplored Power of Social Media in Negotiation
By: James K. Sebenius, Ben Cook, David A. Lax, Isaac Silberberg and Paul Levy
While social media has had profound effects in many realms, the theory and practice of negotiation have remained relatively untouched by this potent phenomenon. In this article, we survey existing research in this area and develop a broader framework for understanding... View Details
- June 2021
- Article
From Predictions to Prescriptions: A Data-driven Response to COVID-19
By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details
- 2021
- Article
Helping and Happiness: A Review and Guide for Public Policy
By: Lara B. Aknin and Ashley V. Whillans
Perhaps one of the most reaffirming findings to emerge over the past several decades is that humans not only engage in generous behavior, they also appear to experience pleasure from doing so. Yet not all acts of helping lead to greater happiness. Here, we review the... View Details
- 2021
- Chapter
International Business History and the Strategy of Multinational Enterprises: How History Matters
By: Geoffrey Jones and Teresa da Silva Lopes
This chapter provides an overview of the evolution of international business over the long-run as well as the strategies of MNEs. It highlights how strategies became more complex over time with MNEs moving from being coordinators of resources and managers of... View Details
- Winter 2021
- Editorial
Introduction
This issue of Negotiation Journal is dedicated to the theme of artificial intelligence, technology, and negotiation. It arose from a Program on Negotiation (PON) working conference on that important topic held virtually on May 17–18. The conference was not the... View Details
- 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
- 2021
- Working Paper
No-fault Default, Chapter 11 Bankruptcy, and Financial Institutions
By: Robert C. Merton and Richard T. Thakor
This paper analyzes the costs and benefits of a no-fault-default debt structure as an alternative to the typical bankruptcy process. We show that the deadweight costs of bankruptcy can be avoided or substantially reduced through no-fault-default debt, which permits a... View Details
- Article
Reflections: Toward a Normative and Actionable Theory of Planned Organizational Change and Development
By: Michael Beer
A normative and actionable theory of planned organizational change and development is proposed based on fifty years of engagement by the author as a scholar-consultant. Five principles are central features of the theory and practice proposed: 1) Organizations are... View Details
- Article
Towards Robust and Reliable Algorithmic Recourse
By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan
approvals), there has been growing interest in post-hoc techniques which provide recourse to affected
individuals. These techniques generate recourses under the assumption... View Details
- 2020
- Working Paper
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing... View Details
- December 2020 (Revised April 2021)
- Case
IBM Watson at MD Anderson Cancer Center
By: Shane Greenstein, Mel Martin and Sarkis Agaian
After discovering that their cancer diagnostic tool, designed to leverage the cloud computing power of IBM Watson, needed greater integration into the clinical processes at the MD Anderson Cancer Center, the development team had difficult choices to make. The Oncology... View Details
Keywords: Decision Making; Innovation Strategy; Knowledge Management; Knowledge Use and Leverage; Operations; Failure; Information Technology; Applications and Software; Health Care and Treatment; Product Development; Health Industry; Information Technology Industry; Technology Industry; United States; Houston; Texas
- December 2020
- Case
VIA Science (A)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
- December 2020
- Supplement
VIA Science (B)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
- December 2020 (Revised December 2022)
- Case
The Dance of Dharma: On the Difficulty of Being Good
By: Arthur I. Segel and Tyler M. Richard
When deciding how to be good and act well, we often seek outside help. Many of our oldest and most frequently consulted sources of ethical guidance are our religious traditions. Just as one might consult a thoughtful friend, countless people seek direction from their... View Details
- Article
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
By: Wanqian Yang, Lars Lorch, Moritz Graule, Himabindu Lakkaraju and Finale Doshi-Velez
Domains where supervised models are deployed often come with task-specific constraints, such as prior expert knowledge on the ground-truth function, or desiderata like safety and fairness. We introduce a novel probabilistic framework for reasoning with such constraints... View Details
- Article
Making a Difference: Developing Actionable Knowledge for Practice and Theory
By: Michael Beer
There is a widely acknowledged gap between academic research and practice. While the field of organizational studies and development has had an impact on management practice in some organizations, it has had only a modest impact on widely accepted management practice... View Details
- 2020
- Working Paper
Prioritarianism and Optimal Taxation
By: Matti Tuomala and Matthew C. Weinzierl
Prioritarianism has been at the center of the formal approach to optimal tax theory since its modern starting point in Mirrlees (1971), but most theorists’ use of it is motivated by tractability rather than explicit normative reasoning. We characterize analytically and... View Details
Keywords: Prioritarianism; Optimal Taxation; Utilitarianism; Redistribution; Inverse-optimum; Taxation; Theory
- Article
Robust and Stable Black Box Explanations
By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani
As machine learning black boxes are increasingly being deployed in real-world applications, there
has been a growing interest in developing post hoc explanations that summarize the behaviors
of these black boxes. However, existing algorithms for generating such... View Details
- Article
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to... View Details
- 2023
- Working Paper
The Market for Healthcare in Low Income Countries
By: Abhijit Banerjee, Abhijit Chowdhury, Jishnu Das, Jeffrey Hammer, Reshmaan Hussam and Aakash Mohpal
Patient trust is an important driver of the demand for healthcare. But it may also impact supply:
doctors who realize that patients may not trust them may adjust their behavior in response. We
assemble a large dataset that assesses clinical performance using... View Details