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    • All HBS Web  (267)
      • Faculty Publications  (123)

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      • Article

      Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

      By: Eva Ascarza and Ayelet Israeli

      An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

      Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
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      Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
      • March 2022
      • Supplement

      Allianz Customer Centricity: Is Simplicity the Way Forward?

      By: Eva Ascarza
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      Ascarza, Eva. "Allianz Customer Centricity: Is Simplicity the Way Forward?" Harvard Business School PowerPoint Supplement 522-086, March 2022.
      • March 2022
      • Supplement

      Allianz Customer Centricity: Is Simplicity the Way Forward?

      By: Eva Ascarza
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      Ascarza, Eva. "Allianz Customer Centricity: Is Simplicity the Way Forward?" Harvard Business School Spreadsheet Supplement 522-713, March 2022.
      • March 2022
      • Teaching Note

      Allianz Customer Centricity: Is Simplicity the Way Forward?

      By: Eva Ascarza
      Teaching Note for HBS Case No. 522-008. View Details
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      Ascarza, Eva. "Allianz Customer Centricity: Is Simplicity the Way Forward?" Harvard Business School Teaching Note 522-060, March 2022.
      • February 2022
      • Teaching Note

      Introducing EVA at ISS: A Better Way to Evaluate CEO Performance and Compensation?

      By: Jonas Heese and Charles C.Y. Wang
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      Heese, Jonas, and Charles C.Y. Wang. "Introducing EVA at ISS: A Better Way to Evaluate CEO Performance and Compensation?" Harvard Business School Teaching Note 122-062, February 2022.
      • February 2022 (Revised February 2024)
      • Supplement

      ISS EVA Instructor Template

      By: Jonas Heese and Charles C.Y. Wang
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      Heese, Jonas, and Charles C.Y. Wang. "ISS EVA Instructor Template." Harvard Business School Spreadsheet Supplement 122-708, February 2022. (Revised February 2024.)
      • February 2022 (Revised February 2024)
      • Supplement

      ISS EVA Student Template

      By: Jonas Heese and Charles C.Y. Wang
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      Heese, Jonas, and Charles C.Y. Wang. "ISS EVA Student Template." Harvard Business School Spreadsheet Supplement 122-707, February 2022. (Revised February 2024.)
      • January 2022 (Revised February 2022)
      • Case

      Introducing EVA at ISS: A Better Way to Evaluate CEO Performance and Compensation?

      By: Jonas Heese, Charles C.Y. Wang and James Weber
      In early 2019, Anthony Campagna, the global director of fundamental research at ISS EVA, a unit of the proxy advisory firm Institutional Shareholder Services (ISS), was preparing to release ISS's analyses of public company performance and CEO compensation ahead of Say... View Details
      Keywords: Jobs and Positions; Compensation and Benefits; Performance; Performance Productivity; Measurement and Metrics; Analytics and Data Science; Value; Business or Company Management; Performance Evaluation; Business and Shareholder Relations
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      Heese, Jonas, Charles C.Y. Wang, and James Weber. "Introducing EVA at ISS: A Better Way to Evaluate CEO Performance and Compensation?" Harvard Business School Case 122-061, January 2022. (Revised February 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.
      • September 2021
      • Supplement

      Interview with Julio Bruno (Time Out)

      By: Eva Ascarza
      Video supplement for HBS Case No. 520-128. View Details
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      Ascarza, Eva. "Interview with Julio Bruno (Time Out)." Harvard Business School Multimedia/Video Supplement 522-707, September 2021.
      • 2021
      • White Paper

      Hidden Workers: Untapped Talent

      By: Joseph B. Fuller, Manjari Raman, Eva Sage-Gavin and Kristen Hines

      Companies are increasingly desperate for workers. As they continue to struggle to find people with the skills they need, their competitiveness and growth prospects are put at risk.

      At the same time, an enormous and growing group of people are unemployed or... View Details

      Keywords: Hiring; Talent; Skills Gap; Selection and Staffing; Diversity; Talent and Talent Management; Competency and Skills
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      Fuller, Joseph B., Manjari Raman, Eva Sage-Gavin, and Kristen Hines. "Hidden Workers: Untapped Talent." White Paper, Harvard Business School Project on Managing the Future of Work, Boston, MA, September 2021. (Published by Harvard Business School Project on Managing the Future of Work and Accenture.)
      • August 2021
      • Teaching Note

      Time Out: The Evolution from Media to Markets

      By: Eva Ascarza
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      Ascarza, Eva. "Time Out: The Evolution from Media to Markets." Harvard Business School Teaching Note 522-036, August 2021.
      • August 2021 (Revised February 2022)
      • Supplement

      Melissa Wood Health: How to Win in the Creator Economy

      By: Eva Ascarza
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      Ascarza, Eva. "Melissa Wood Health: How to Win in the Creator Economy." Harvard Business School PowerPoint Supplement 522-029, August 2021. (Revised February 2022.)
      • August 2021 (Revised February 2022)
      • Supplement

      Melissa Wood Health: How to Win in the Creator Economy

      By: Eva Ascarza
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      Ascarza, Eva. "Melissa Wood Health: How to Win in the Creator Economy." Harvard Business School Spreadsheet Supplement 522-704, August 2021. (Revised February 2022.)
      • August 2021 (Revised January 2024)
      • Teaching Note

      Melissa Wood Health: How to Win in the Creator Economy

      By: Eva Ascarza
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      Ascarza, Eva. "Melissa Wood Health: How to Win in the Creator Economy." Harvard Business School Teaching Note 522-024, August 2021. (Revised January 2024.)
      • July 2021 (Revised January 2022)
      • Teaching Note

      Amazon Shopper Panel: Paying Customers for Their Data

      By: Eva Ascarza and Ayelet Israeli
      Teaching Note for HBS Case No. 521-058. View Details
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      Ascarza, Eva, and Ayelet Israeli. "Amazon Shopper Panel: Paying Customers for Their Data." Harvard Business School Teaching Note 522-011, July 2021. (Revised January 2022.)
      • July 2021 (Revised October 2021)
      • Case

      Allianz Customer Centricity: Is Simplicity the Way Forward?

      By: Eva Ascarza and Emilie Billaud
      This case explores the tradeoffs between product personalization and simplicity as companies grow. The case presents an opportunity to understand whether and how each of these approaches enables and/or limits companies’ abilities to provide customer satisfaction while... View Details
      Keywords: Simplicity; Customer Focus and Relationships; Customization and Personalization; Customer Satisfaction; Performance Efficiency; Strategy; Insurance Industry; Europe; Germany
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      Ascarza, Eva, and Emilie Billaud. "Allianz Customer Centricity: Is Simplicity the Way Forward?" Harvard Business School Case 522-008, July 2021. (Revised October 2021.)
      • June 23, 2021
      • Article

      Research: When A/B Testing Doesn't Tell You the Whole Story

      By: Eva Ascarza
      When it comes to churn prevention, marketers traditionally start by identifying which customers are most likely to churn, and then running A/B tests to determine whether a proposed retention intervention will be effective at retaining those high-risk customers. While... View Details
      Keywords: Customer Retention; Churn; Targeting; Market Research; Marketing; Investment Return; Customers; Retention; Research
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      Ascarza, Eva. "Research: When A/B Testing Doesn't Tell You the Whole Story." Harvard Business Review Digital Articles (June 23, 2021).
      • June 2021
      • Article

      Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?

      By: Jacqueline N. Lane, Ina Ganguli, Patrick Gaule, Eva C. Guinan and Karim R. Lakhani
      We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a natural field experiment at a medical research symposium, where we exogenously... View Details
      Keywords: Cognitive Similarity; Innovation; Knowledge Production; Natural Field Experiment; Knowledge Acquisition; Knowledge Sharing; Relationships
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      Lane, Jacqueline N., Ina Ganguli, Patrick Gaule, Eva C. Guinan, and Karim R. Lakhani. "Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?" Strategic Management Journal 42, no. 6 (June 2021).
      • July–August 2021
      • Article

      Why You Aren't Getting More from Your Marketing AI

      By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie
      Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of... View Details
      Keywords: Artificial Intelligence; Marketing; Decision Making; Communication; Framework; AI and Machine Learning
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      Ascarza, Eva, Michael Ross, and Bruce G.S. Hardie. "Why You Aren't Getting More from Your Marketing AI." Harvard Business Review 99, no. 4 (July–August 2021): 48–54.
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