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    • All HBS Web  (1,041)
      • Faculty Publications  (160)

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      • 2022
      • White Paper

      The American Opportunity Index: A Corporate Scorecard of Worker Advancement

      By: Matt Sigelman, Joseph Fuller, Nik Dawson and Gad Levanon
      The American Opportunity Index: A Corporate Scorecard of Worker Advancement is a new effort to give companies and other stakeholders a set of robust tools that measure how well major employers are doing in fostering economic mobility for workers and how they could do... View Details
      Keywords: Upward Mobility; Career Advancement; Personal Development and Career; Compensation and Benefits; Employees; Wages; Human Capital; Recruitment
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      Sigelman, Matt, Joseph Fuller, Nik Dawson, and Gad Levanon. "The American Opportunity Index: A Corporate Scorecard of Worker Advancement." White Paper, Burning Glass Institute, October 2022 (A joint project with Harvard Business School Project on Managing the Future of Work and Schultz Family Foundation.)
      • August, 2022
      • Article

      Billing and Insurance-Related Administrative Costs: A Cross-National Analysis

      By: Barak D. Richman, Robert S. Kaplan, Japees Kohli, Dennis Purcell, Mahek Shah, Igna Bonfrer, Brian Golden, Rosemary Hannam, Will Mitchell, Daniel Cehic, Garry Crispin and Kevin A. Schulman
      Billing and insurance-related costs are a significant source of wasteful health care spending in Organization for Economic Cooperation and Development nations, but these administrative burdens vary across national systems. We executed a microlevel accounting of these... View Details
      Keywords: Health Care Costs; Administrative Costs; Cost; Health Care and Treatment; Health Industry
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      Richman, Barak D., Robert S. Kaplan, Japees Kohli, Dennis Purcell, Mahek Shah, Igna Bonfrer, Brian Golden, Rosemary Hannam, Will Mitchell, Daniel Cehic, Garry Crispin, and Kevin A. Schulman. "Billing and Insurance-Related Administrative Costs: A Cross-National Analysis." Health Affairs 41, no. 8 (August, 2022): 1098–1106.
      • June 2022
      • Case

      Business Implications from Regulating Carbon Emissions in the EU

      By: George Serafeim and Benjamin Maletta
      In the beginning of the 21st century, the European Union (the EU) had led the global fight against climate change with a wide array of policy measures. The EU’s primary approach to climate policy had been taxation via the European Union Emissions Trading System (EU... View Details
      Keywords: Regulation; Carbon Emissions; Trade; Sustainability; Decarbonization; Performance; Climate Change; Analysis; Strategy; Taxation; Policy; Environmental Regulation; Industry Structures; European Union
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      Serafeim, George, and Benjamin Maletta. "Business Implications from Regulating Carbon Emissions in the EU." Harvard Business School Case 122-106, June 2022.
      • 2022
      • Working Paper

      Measuring the Tolerance of the State: Theory and Application to Protest

      By: Veli Andirin, Yusuf Neggers, Mehdi Shadmehr and Jesse M. Shapiro
      We develop a measure of a regime's tolerance for an action by its citizens. We ground our measure in an economic model and apply it to the setting of political protest. In the model, a regime anticipating a protest can take a costly action to repress it. We define the... View Details
      Keywords: Political Protests; Modeling And Analysis; Government and Politics; Conflict and Resolution
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      Andirin, Veli, Yusuf Neggers, Mehdi Shadmehr, and Jesse M. Shapiro. "Measuring the Tolerance of the State: Theory and Application to Protest." NBER Working Paper Series, No. 30167, June 2022.
      • Article

      A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

      By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
      We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
      Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
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      McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
      • December 2021
      • Article

      Employee Responses to Compensation Changes: Evidence from a Sales Firm

      By: Jason Sandvik, Richard Saouma, Nathan Seegert and Christopher Stanton
      What are the long-term consequences of compensation changes? Using data from an inbound sales call center, we study employee responses to a compensation change that ultimately reduced take-home pay by 7% for the average affected worker. The change caused a significant... View Details
      Keywords: Employees; Wages; Compensation and Benefits; Change; Performance; Resignation and Termination; Retention; Analysis
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      Sandvik, Jason, Richard Saouma, Nathan Seegert, and Christopher Stanton. "Employee Responses to Compensation Changes: Evidence from a Sales Firm." Management Science 67, no. 12 (December 2021): 7687–7707.
      • Article

      Behavioral and Neural Representations en route to Intuitive Action Understanding

      By: Leyla Tarhan, Julian De Freitas and Talia Konkle
      When we observe another person’s actions, we process many kinds of information—from how their body moves to the intention behind their movements. What kinds of information underlie our intuitive understanding about how similar actions are to each other? To address this... View Details
      Keywords: Action Perception; Intuitive Similarity; Multi-arrangement; fMRI; Representational Similarity Analysis; Behavior; Perception
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      Tarhan, Leyla, Julian De Freitas, and Talia Konkle. "Behavioral and Neural Representations en route to Intuitive Action Understanding." Neuropsychologia 163 (December 2021).
      • May 2021
      • Simulation

      Customer Compatibility Exercise Application

      By: Ryan W. Buell
      Customers impose considerable variability on the operating systems of service organizations. They show up when they wish (arrival variability), they ask for different things (request variability), they vary in their willingness and ability to help themselves (effort... View Details
      Keywords: Customer Compatibility; Customer Relationship Management; Strategy; Service Operations; Service Delivery; Performance Efficiency; Analysis; Consumer Behavior; Analytics and Data Science
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      Buell, Ryan W. "Customer Compatibility Exercise Application." Harvard Business School Simulation 620-707, May 2021.
      • 2021
      • Working Paper

      How Much Should We Trust Staggered Difference-In-Differences Estimates?

      By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
      Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the... View Details
      Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
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      Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" European Corporate Governance Institute Finance Working Paper, No. 736/2021, February 2021. (Harvard Business School Working Paper, No. 21-112, April 2021.)
      • March 2021
      • Article

      The Customer May Not Always Be Right: Customer Compatibility and Service Performance

      By: Ryan W. Buell, Dennis Campbell and Frances X. Frei
      This paper investigates the impact of customer compatibility – the degree of fit between the needs of customers and the capabilities of the operations serving them – on customer experiences and firm performance. We use a variance decomposition analysis to quantify the... View Details
      Keywords: Customer Compatibility; Satisfaction; Profitability; Service Operations; Customer Relationship Management; Customer Satisfaction; Performance
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      Buell, Ryan W., Dennis Campbell, and Frances X. Frei. "The Customer May Not Always Be Right: Customer Compatibility and Service Performance." Management Science 67, no. 3 (March 2021): 1468–1488.
      • February 2021 (Revised May 2021)
      • Case

      SafeGraph: Selling Data as a Service

      By: Ramana Nanda, Abhishek Nagaraj and Allison Ciechanover
      Set in January 2021, the CEO of SafeGraph, a four-year-old startup that sold Data as a Service, looked to the future. His aim was to become the most trusted source for data about a physical place. The company provided points of interest (POI) and foot traffic data on... View Details
      Keywords: Data As A Service; Monetization; Pricing; Business Startups; Analytics and Data Science; Consumer Behavior; Analysis; Business Model; Health Pandemics; Information Industry; United States
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      Nanda, Ramana, Abhishek Nagaraj, and Allison Ciechanover. "SafeGraph: Selling Data as a Service." Harvard Business School Case 821-082, February 2021. (Revised May 2021.)
      • February 2021
      • Tutorial

      Getting Started in RStudio Cloud

      By: Chiara Farronato and Caleb Kwon
      This video provides an introduction to the free programming language R using an online cloud version of RStudio, which is the most popular editor and interface for writing and executing R code. The video begins by providing a brief background of R and RStudio and... View Details
      Keywords: Data Analysis; Data Analytics; Experiment; Experimental Design; Analytics and Data Science; Analysis; Applications and Software
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      Farronato, Chiara, and Caleb Kwon. Getting Started in RStudio Cloud. Harvard Business School Tutorial 621-708, February 2021.
      • 2021
      • Article

      Fair Algorithms for Infinite and Contextual Bandits

      By: Matthew Joseph, Michael J Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
      We study fairness in linear bandit problems. Starting from the notion of meritocratic fairness introduced in Joseph et al. [2016], we carry out a more refined analysis of a more general problem, achieving better performance guarantees with fewer modelling assumptions... View Details
      Keywords: Algorithms; Bandit Problems; Fairness; Mathematical Methods
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      Joseph, Matthew, Michael J Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Fair Algorithms for Infinite and Contextual Bandits." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
      • Winter 2021
      • Editorial

      Introduction

      By: Michael A. Wheeler
      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
      Keywords: Artificial Intelligence; Information Technology; Negotiation; AI and Machine Learning
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      Wheeler, Michael A. "Introduction." Special Issue on Artificial Intelligence, Technology, and Negotiation. Negotiation Journal 37, no. 1 (Winter 2021): 5–12.
      • 2022
      • Working Paper

      Where the Cloud Rests: The Location Strategies of Data Centers

      By: Shane Greenstein and Tommy Pan Fang
      This study provides an analysis of the entry strategies of third-party data centers in the United States. We examine the market before the pandemic in 2018 and 2019, when supply and demand for data services were geographically stable. We compare with the entry... View Details
      Keywords: Cloud Computing; Location Strategies; Data Centers; Information Infrastructure
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      Greenstein, Shane, and Tommy Pan Fang. "Where the Cloud Rests: The Location Strategies of Data Centers." Harvard Business School Working Paper, No. 21-042, September 2020. (Revised June 2022.)
      • 2020
      • Working Paper

      Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 7 The Value Structure of Technologies, Part 2: Strategy without Numbers

      By: Carliss Y. Baldwin
      Functional analysis as set forth in the last chapter decomposes a technical system into functional components that do things to advance the system’s purpose and the goals of its designers. Functional analysis in turn can be used to construct value structure maps... View Details
      Keywords: Modularity; Value Structure Mapping; Value Capture; Information Technology; Organizations; Strategy; Value Creation
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      Baldwin, Carliss Y. "Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 7 The Value Structure of Technologies, Part 2: Strategy without Numbers." Harvard Business School Working Paper, No. 21-040, September 2020.
      • 2020
      • Working Paper

      Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 2 Transactions in a Task Network

      By: Carliss Y. Baldwin
      From the 1930s through today, many economists have conceived of large technical systems for the production of goods and services as a series of transactions. This point of view has led eminent economists to assert that transactions are the fundamental unit of analysis... View Details
      Keywords: Modularity; Information Technology; Organizations
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      Baldwin, Carliss Y. "Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 2 Transactions in a Task Network." Harvard Business School Working Paper, No. 21-030, August 2020.
      • July 2020
      • Case

      Applying Data Science and Analytics at P&G

      By: Srikant M. Datar, Sarah Mehta and Paul Hamilton
      Set in December 2019, this case explores how P&G has applied data science and analytics to cut costs and improve outcomes across its business units. The case provides an overview of P&G’s approach to data management and governance, and reviews the challenges associated... View Details
      Keywords: Data Science; Analytics; Analysis; Information; Information Management; Information Types; Innovation and Invention; Strategy; Analytics and Data Science; Consumer Products Industry; United States; Ohio
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      Datar, Srikant M., Sarah Mehta, and Paul Hamilton. "Applying Data Science and Analytics at P&G." Harvard Business School Case 121-006, July 2020.
      • June 2020
      • Article

      The Isolated Choice Effect and Its Implications for Gender Diversity in Organizations

      By: Edward H. Chang, Erika L. Kirgios, Aneesh Rai and Katherine L. Milkman
      We highlight a feature of personnel selection decisions that can influence the gender diversity of groups and teams. Specifically, we show that people are less likely to choose candidates whose gender would increase group diversity when making personnel selections in... View Details
      Keywords: Behavior And Behavioral Decision Making; Organizational Studies; Decision Analysis; Economics; Decision Making; Behavior; Analysis; Organizations; Diversity; Gender
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      Chang, Edward H., Erika L. Kirgios, Aneesh Rai, and Katherine L. Milkman. "The Isolated Choice Effect and Its Implications for Gender Diversity in Organizations." Management Science 66, no. 6 (June 2020): 2752–2761.
      • March 2020
      • Article

      Diagnosing Missing Always at Random in Multivariate Data

      By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
      Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
      Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
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      Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
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