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    • All HBS Web  (323)
      • Faculty Publications  (52)

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      • July 2022
      • Article

      What Do I Make of the Rest of My Life? Global and Quotidian Life Construal across the Retirement Transition

      By: Jeff Steiner and Teresa M. Amabile
      Retirement means relinquishing the daily structure that work provides and the career-dependent meanings that it offers life narratives. The retirement transition can therefore involve contemplating both how to spend newly-freed daily time and the implications of...  View Details
      Keywords: Retirement Transition; Life Narrative; Construal Level Theory; Global Construal; Quotidian Construal; Meanings Of Work And Retirement; Retirement; Transition; Perspective
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      Steiner, Jeff, and Teresa M. Amabile. "What Do I Make of the Rest of My Life? Global and Quotidian Life Construal across the Retirement Transition." Organizational Behavior and Human Decision Processes 171 (July 2022).
      • March 2022 (Revised March 2022)
      • Module Note

      Linear Regression

      By: Iavor I. Bojinov, Michael Parzen and Paul J. Hamilton
      This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to...  View Details
      Keywords: Data Science; Mathematical Methods; Analytics and Data Science
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      Bojinov, Iavor I., Michael Parzen, and Paul J. Hamilton. "Linear Regression." Harvard Business School Module Note 622-100, March 2022. (Revised March 2022.)
      • March 2022 (Revised May 2022)
      • Case

      Winning Business at Russell Reynolds (A)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and...  View Details
      Keywords: Compensation; Collaboration; Executive Search Firms; Consulting Firms; Compensation and Benefits; Restructuring; Human Resources; Human Capital; Management Practices and Processes; Organizational Culture; Organizational Change and Adaptation; Social and Collaborative Networks; Recruitment; Selection and Staffing; Talent and Talent Management; Consulting Industry; Employment Industry; Asia; Europe; Latin America; Middle East; North and Central America; South America; Oceania
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      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (A)." Harvard Business School Case 422-045, March 2022. (Revised May 2022.)
      • March 2022
      • Supplement

      Winning Business at Russell Reynolds (B)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and...  View Details
      Keywords: Compensation; Collaboration; Executive Search Firms; Consulting Firms; Compensation and Benefits; Restructuring; Human Resources; Human Capital; Management Practices and Processes; Organizational Culture; Organizational Change and Adaptation; Social and Collaborative Networks; Recruitment; Selection and Staffing; Talent and Talent Management; Consulting Industry; Employment Industry; Asia; Europe; Latin America; Middle East; North and Central America; South America; Oceania
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      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (B)." Harvard Business School Supplement 422-046, March 2022.
      • October 2021
      • Article

      Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

      By: Nicolas Padilla and Eva Ascarza
      The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...  View Details
      Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis
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      Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
      • August 2021
      • Article

      Multiple Imputation Using Gaussian Copulas

      By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
      Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use...  View Details
      Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation
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      Hollenbach, F.M., I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward, and A. Volfovsky. "Multiple Imputation Using Gaussian Copulas." Special Issue on New Quantitative Approaches to Studying Social Inequality. Sociological Methods & Research 50, no. 3 (August 2021): 1259–1283. (0049124118799381.)
      • 2020
      • Working Paper

      Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective

      By: Srikant Datar, Apurv Jain, Charles C.Y. Wang and Siyu Zhang
      We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the...  View Details
      Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction
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      Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
      • April 2021
      • Article

      A Model of Multi-Pass Search: Price Search Across Stores and Time

      By: Navid Mojir and K. Sudhir
      In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across...  View Details
      Keywords: Consumer Search; Multi-pass Search; Price Search; Store Search; Spatial Search; Temporal Search; Spatiotemporal Search; Dynamic Structural Models; MPEC; Price Promotions; Store Loyalty; Consumer Behavior; Price; Spending; Marketing; Mathematical Methods
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      Mojir, Navid, and K. Sudhir. "A Model of Multi-Pass Search: Price Search Across Stores and Time." Management Science 67, no. 4 (April 2021): 2126–2150.
      • March 2021
      • Article

      Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment

      By: Yang Xiang, Thomas Graeber, Benjamin Enke and Samuel Gershman
      This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the...  View Details
      Keywords: Visual Perception; Bayesian Modeling; Perception; Judgments
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      Xiang, Yang, Thomas Graeber, Benjamin Enke, and Samuel Gershman. "Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment." Attention, Perception, & Psychophysics (March 2021): 1–11.
      • February 2021
      • Case

      Digital Manufacturing at Amgen

      By: Shane Greenstein, Kyle R. Myers and Sarah Mehta
      This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is...  View Details
      Keywords: Digital Technologies; Change; Change Management; Decision Making; Cost vs Benefits; Decisions; Information; Analytics and Data Science; Innovation and Invention; Innovation and Management; Innovation Leadership; Innovation Strategy; Technological Innovation; Jobs and Positions; Knowledge; Leadership; Organizational Culture; Science; Strategy; Information Technology; Technology Adoption; Biotechnology Industry; Pharmaceutical Industry; United States; California; Puerto Rico; Rhode Island
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      Greenstein, Shane, Kyle R. Myers, and Sarah Mehta. "Digital Manufacturing at Amgen." Harvard Business School Case 621-008, February 2021.
      • 2021
      • Working Paper

      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...  View Details
      Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; Analysis; Theory; Measurement and Metrics; Performance Consistency
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      Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." Working Paper, 2021. (3rd Round Revision.)
      • 2022
      • Working Paper

      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 someone’s effort from their observable performance may require accounting for the otherwise irrelevant role of...  View Details
      Keywords: Belief Formation; Attention; Bounded Rationality; Values and Beliefs; Information; Mathematical Methods
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      Graeber, Thomas. "Inattentive Inference." Working Paper, January 2022. (R&R at Journal of the European Economic Association.)
      • 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
      Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
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      Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
      • November 2020
      • Article

      Disrupting the Disruptors or Enhancing Them? How Blockchain Re‐Shapes Two‐Sided Platforms

      By: Daniel Trabucchi, Antonella Moretto, Tommaso Buganza and Alan MacCormack
      The importance of platform‐based businesses in the modern economy is growing continuously and becoming increasingly relevant. Specifically, the deployment of digital technologies has enhanced the applicability of two‐sided business models, enabling companies to act not...  View Details
      Keywords: Blockchain; Two-Sided Platforms; Business Model; Innovation and Invention; Technological Innovation
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      Trabucchi, Daniel, Antonella Moretto, Tommaso Buganza, and Alan MacCormack. "Disrupting the Disruptors or Enhancing Them? How Blockchain Re‐Shapes Two‐Sided Platforms." Journal of Product Innovation Management 37, no. 6 (November 2020): 552–574.
      • September–October 2020
      • Article

      The Air War Versus the Ground Game: An Analysis of Multi-Channel Marketing in U.S. Presidential Elections

      By: Lingling Zhang and Doug J. Chung
      This study jointly examines the effects of television advertising and field operations in U.S. presidential elections, with the former referred to as the “air war” and the latter as the “ground game.” Specifically, the study focuses on how different campaign...  View Details
      Keywords: Multi-channel Marketing; Ground Campaigning; Political Campaigns; Discrete-choice Model; Instrumental Variables; Political Elections; Marketing Channels; Advertising; United States
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      Zhang, Lingling, and Doug J. Chung. "The Air War Versus the Ground Game: An Analysis of Multi-Channel Marketing in U.S. Presidential Elections." Marketing Science 39, no. 5 (September–October 2020): 872–892.
      • 2020
      • Working Paper

      Conflicting Interests and the Effect of Fiduciary Duty—Evidence from Variable Annuities

      By: Mark Egan, Shan Ge and Johnny Tang
      We examine the drivers of variable annuity sales and the impact of a proposed regulatory change. Variable annuities are popular retirement products with over $2 trillion in assets in the United States. Insurers typically pay brokers a commission for selling variable...  View Details
      Keywords: Variable Annuity; Brokers; Fiduciary Duty; Finance; Investment; Insurance; Conflict of Interests; Financial Services Industry; Insurance Industry; United States
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      Egan, Mark, Shan Ge, and Johnny Tang. "Conflicting Interests and the Effect of Fiduciary Duty—Evidence from Variable Annuities." Harvard Business School Working Paper, No. 21-018, August 2020. (Conditionally Accepted at the Review of Financial Studies. Revised August 2020. NBER Working Paper Series, No. 27577, July 2020)
      • June 2020 (Revised May 2022)
      • Case

      Vanguard Retail Operations (A)

      By: Willy C. Shih and Antonio Moreno
      The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or...  View Details
      Keywords: Pooling; Generalist Model; Specialist Model; Operations; Service Operations; Management; Job Design and Levels; Financial Services Industry; United States
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      Shih, Willy C., and Antonio Moreno. "Vanguard Retail Operations (A)." Harvard Business School Case 620-104, June 2020. (Revised May 2022.)
      • June 2020 (Revised August 2020)
      • Supplement

      Vanguard Retail Operations (B)

      By: Willy C. Shih and Antonio Moreno
      The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or...  View Details
      Keywords: Pooling; Generalist Model; Specialist Model; Service Operations; Management; Financial Services Industry; United States
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      Shih, Willy C., and Antonio Moreno. "Vanguard Retail Operations (B)." Harvard Business School Supplement 620-105, June 2020. (Revised August 2020.)
      • 26 Apr 2020
      • Other Presentation

      Towards Modeling the Variability of Human Attention

      By: Kuno Kim, Megumi Sano, Julian De Freitas, Daniel Yamins and Nick Haber
      Children exhibit extraordinary exploratory behaviors hypothesized to contribute to the building of models of their world. Harnessing this capacity in artificial systems promises not only more flexible technology but also cognitive models of the developmental processes...  View Details
      Keywords: Exploratory Learning Behaviors; Modeling; Artificial Intelligence; AI and Machine Learning
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      Kim, Kuno, Megumi Sano, Julian De Freitas, Daniel Yamins, and Nick Haber. "Towards Modeling the Variability of Human Attention." In Bridging AI and Cognitive Science (BAICS) Workshop. 8th International Conference on Learning Representations (ICLR), April 26, 2020.
      • 2020
      • Conference Presentation

      Towards Modeling the Developmental Variability of Human Attention

      By: K-H Kim, M. Sano, J. De Freitas, N. Haber and D. L. K. Yamins
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      Kim, K-H, M. Sano, J. De Freitas, N. Haber, and D. L. K. Yamins. "Towards Modeling the Developmental Variability of Human Attention." Paper presented at the 8th International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia, 2020.
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