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      • Faculty Publications  (81)

      Forecasting Models Remove Forecasting Models →

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      • April 12, 2023
      • Article

      Using AI to Adjust Your Marketing and Sales in a Volatile World

      By: Das Narayandas and Arijit Sengupta
      Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer...  View Details
      Keywords: Forecasting and Prediction; AI and Machine Learning; Consumer Behavior; Technology Adoption; Competitive Advantage
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      Narayandas, Das, and Arijit Sengupta. "Using AI to Adjust Your Marketing and Sales in a Volatile World." Harvard Business Review Digital Articles (April 12, 2023).
      • March–April 2023
      • Article

      Market Segmentation Trees

      By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
      Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market...  View Details
      Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
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      Aouad, Ali, Adam Elmachtoub, Kris J. Ferreira, and Ryan McNellis. "Market Segmentation Trees." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 648–667.
      • February 2023
      • Supplement

      Coats Dyehouse Management

      By: Willy C. Shih
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour...  View Details
      Keywords: Inventory Management; Supply Chain; Inventory; Supply Chain Management; Operations; Apparel and Accessories Industry; Asia
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      Shih, Willy C. "Coats Dyehouse Management." Harvard Business School Multimedia/Video Supplement 622-703, February 2023.
      • October–December 2022
      • Article

      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; AI and Machine Learning; Forecasting and Prediction
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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." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
      • 2022
      • Working Paper

      Perceptions about Monetary Policy

      By: Michael D. Bauer, Carolin Pflueger and Adi Sunderam
      We estimate perceptions about the Fed's monetary policy rule from micro data on professional forecasters. The perceived rule varies significantly over time, with important consequences for monetary policy and bond markets. Over the monetary policy cycle, easings are...  View Details
      Keywords: Monetary Policy; Central Banking; Forecasting and Prediction; Policy; Interest Rates
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      Bauer, Michael D., Carolin Pflueger, and Adi Sunderam. "Perceptions about Monetary Policy." NBER Working Paper Series, No. 30480, September 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.
      • February 2022 (Revised September 2022)
      • Case

      Lilium: Preparing for Takeoff

      By: Navid Mojir, Vincent Dessain, Mette Fuglsang Hjortshoej and Emer Moloney
      Lilium is a German company focused on developing electric vertical takeoff and landing vehicles (eVTOLs) that can be used to offer air taxi services. The company went public in September 2021 through a special purpose acquisition company (SPAC) deal, raising more than...  View Details
      Keywords: SPACs; Business Model; Forecasting and Prediction; Green Technology; Capital Markets; Venture Capital; Initial Public Offering; Rural Scope; Urban Scope; City; Disruptive Innovation; Growth and Development Strategy; Technological Innovation; Demand and Consumers; Market Timing; Industry Growth; Infrastructure; Logistics; Product Design; Product Development; Production; Service Delivery; Service Operations; Strategic Planning; Partners and Partnerships; Risk and Uncertainty; Urban Development; Sustainable Cities; Business Strategy; Competitive Strategy; Competitive Advantage; Air Transportation; Aerospace Industry; Air Transportation Industry; Green Technology Industry; Transportation Industry; Travel Industry; Germany; Munich; Brazil; United States; Florida
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      Mojir, Navid, Vincent Dessain, Mette Fuglsang Hjortshoej, and Emer Moloney. "Lilium: Preparing for Takeoff." Harvard Business School Case 522-084, February 2022. (Revised September 2022.)
      • January 2022
      • Background Note

      Residual Income Valuation Model

      By: Charles C.Y. Wang and Albert Shin
      This note explains the residual income valuation model (RIM), how it relates to "traditional" valuation models, the intuition behind its use, and empirical research related to its value relevance. RIM is theoretically equivalent to the dividend discount model and the...  View Details
      Keywords: Residual Income Valuation; Valuation; Research; Theory; Measurement and Metrics; Performance; Financial Management; Business Strategy
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      Wang, Charles C.Y., and Albert Shin. "Residual Income Valuation Model." Harvard Business School Background Note 122-070, January 2022.
      • August 2021
      • Supplement

      Coats: Supply Chain Challenges

      By: Willy C. Shih
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour...  View Details
      Keywords: Inventory Management; Supply Chain; Inventory; Supply Chain Management; Operations; Apparel and Accessories Industry; Asia
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      Shih, Willy C. "Coats: Supply Chain Challenges." Harvard Business School PowerPoint Supplement 622-041, August 2021.
      • August 2021
      • Supplement

      Coats: Supply Chain Challenges: Spreadsheet Supplement

      By: Willy C. Shih
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour...  View Details
      Keywords: Inventory Management; Supply Chain; Inventory; Supply Chain Management; Operations; Growth and Development Strategy; Forecasting and Prediction; Demand and Consumers; Consolidation; Apparel and Accessories Industry; Asia
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      Shih, Willy C. "Coats: Supply Chain Challenges: Spreadsheet Supplement." Harvard Business School Spreadsheet Supplement 622-702, August 2021.
      • June 2021
      • Technical Note

      Introduction to Linear Regression

      By: Michael Parzen and Paul Hamilton
      This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...  View Details
      Keywords: Linear Regression; Regression; Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory; Compensation and Benefits; Mathematical Methods; Analytics and Data Science
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      Parzen, Michael, and Paul Hamilton. "Introduction to Linear Regression." Harvard Business School Technical Note 621-086, June 2021.
      • May 2021 (Revised July 2021)
      • Case

      Coats: Supply Chain Challenges

      By: Willy C. Shih and Adina Wong
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour...  View Details
      Keywords: Inventory Management; Supply Chains; Digital; Operations; Supply Chain Management; Apparel and Accessories Industry; Asia
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      Shih, Willy C., and Adina Wong. "Coats: Supply Chain Challenges." Harvard Business School Case 621-115, May 2021. (Revised July 2021.)
      • 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; Analytics and Data Science
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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.
      • February 2021
      • Tutorial

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael Toffel and Natalie Epstein
      This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and...  View Details
      Keywords: Machine Learning; Statistics; Experiments; Forecasting and Prediction; Performance Evaluation
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      Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021.
      • 2021
      • Working Paper

      Real Credit Cycles

      By: Pedro Bordalo, Nicola Gennaioli, Andrei Shleifer and Stephen J. Terry
      We incorporate diagnostic expectations, a psychologically founded model of overreaction to news, into a workhorse business cycle model with heterogeneous firms and risky debt. A realistic degree of diagnosticity, estimated from the forecast errors of managers of U.S....  View Details
      Keywords: Econometric Models; Business Cycles; Credit
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      Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. "Real Credit Cycles." NBER Working Paper Series, No. 28416, January 2021.
      • 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
      Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
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      Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • January 2021
      • Article

      Using Models to Persuade

      By: Joshua Schwartzstein and Adi Sunderam
      We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model...  View Details
      Keywords: Model Persuasion; Analytics and Data Science; Forecasting and Prediction; Mathematical Methods; Framework
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      Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
      • October 2020 (Revised March 2021)
      • Supplement

      Migros Turkey: Scaling Online Operations During COVID-19 (C)

      By: Antonio Moreno and Gamze Yucaoglu
      The case opens in August 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are navigating Migros through COVID-19 and the unprecedented...  View Details
      Keywords: Business Model; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Competition; Expansion; Logistics; Profit; Resource Allocation; Diversification; Corporate Strategy; Crisis Management; Health Pandemics; Strategic Planning; Food and Beverage Industry; Turkey
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      Moreno, Antonio, and Gamze Yucaoglu. "Migros Turkey: Scaling Online Operations During COVID-19 (C)." Harvard Business School Supplement 621-062, October 2020. (Revised March 2021.)
      • August 2020 (Revised September 2020)
      • Technical Note

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools...  View Details
      Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
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      Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
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