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      • October 2023
      • Technical Note

      Design and Evaluation of Targeted Interventions

      By: Eva Ascarza and Ta-Wei (David) Huang
      Targeted interventions serve as a pivotal tool in business strategy, streamlining decisions for enhanced efficiency and effectiveness. This note delves into two central facets of such interventions: first, the design of potent decision guidelines, or targeting...  View Details
      Keywords: Marketing; Customer Relationship Management; Retail Industry; Apparel and Accessories Industry; Technology Industry; Financial Services Industry; Telecommunications Industry
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      Ascarza, Eva, and Ta-Wei (David) Huang. "Design and Evaluation of Targeted Interventions." Harvard Business School Technical Note 524-034, October 2023.
      • June 2023
      • Simulation

      Artea Dashboard and Targeting Policy Evaluation

      By: Ayelet Israeli and Eva Ascarza
      Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea...  View Details
      Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Artea Dashboard and Targeting Policy Evaluation." Harvard Business School Simulation 523-707, June 2023.
      • 2023
      • Working Paper

      Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation

      By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
      Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to...  View Details
      Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior
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      Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.
      • June 2023
      • Article

      National Customer Orientation: An Empirical Test across 112 Countries

      By: Ofer Mintz, Imran S. Currim and Rohit Deshpandé
      Customer orientation is a central tenet of marketing. However, less is known about how customer orientation varies across countries and time. Mintz, Currim, and Deshpandé (Eur. J. Mark., 56: 1014–1041, 2022) propose a country-level construct, national customer...  View Details
      Keywords: Global Range; Customer Focus and Relationships
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      Mintz, Ofer, Imran S. Currim, and Rohit Deshpandé. "National Customer Orientation: An Empirical Test across 112 Countries." Marketing Letters 34, no. 2 (June 2023): 189–204.
      • April, 2023
      • Article

      Reducing Information Barriers to Solar Adoption: Experimental Evidence from India

      By: Meera Mahadevan, Robyn C. Meeks and Takashi Yamano
      Off-grid solar technologies hold promise for unelectrified and low-quality electricity settings; however, their adoption remains low. Important barriers to adoption, such as incomplete information remain relatively unexplored in developing countries. In collaboration...  View Details
      Keywords: Technology Adoption; Renewable Energy; Knowledge Sharing; Developing Countries and Economies; India
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      Mahadevan, Meera, Robyn C. Meeks, and Takashi Yamano. "Reducing Information Barriers to Solar Adoption: Experimental Evidence from India." Energy Economics 120 (April, 2023).
      • January–February 2023
      • Article

      External Interfaces and Internal Processes: Market Positioning and Divergent Professionalization Paths in Young Ventures

      By: Alicia DeSantola, Ranjay Gulati and Pavel Zhelyazkov
      We explore how the initial market positioning of entrepreneurial ventures shapes how they professionalize over time, focusing specifically on the development of functional roles. In contrast to existing literature, which has presumed a uniform march toward...  View Details
      Keywords: Market Positioning; Professionalization; Scaling; Entrepreneurship; Strategy; Business Startups; Growth and Development; Organizational Structure
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      DeSantola, Alicia, Ranjay Gulati, and Pavel Zhelyazkov. "External Interfaces and Internal Processes: Market Positioning and Divergent Professionalization Paths in Young Ventures." Organization Science 34, no. 1 (January–February 2023): 1–23.
      • December 2022
      • Article

      I Don't 'Recall': The Decision to Delay Innovation Launch to Avoid Costly Product Failure

      By: Byungyeon Kim, Oded Koenigsberg and Elie Ofek
      Innovations embody novel features or cutting-edge components aimed at delivering desired customer benefits. Oftentimes, however, we observe the need to recall new products shortly after their introduction. Indeed, a firm may rush an innovation to market in an attempt...  View Details
      Keywords: Innovation Management; Innovation And Strategy; Product Development Strategy; Product Introduction; Quality Control; Product Recalls; Game Theory; Market Timing; Innovation Strategy; Product Launch; Product Development
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      Kim, Byungyeon, Oded Koenigsberg, and Elie Ofek. "I Don't 'Recall': The Decision to Delay Innovation Launch to Avoid Costly Product Failure." Management Science 68, no. 12 (December 2022): 8889–8908.
      • April 2022
      • Article

      National Customer Orientation: A Framework, Propositions and Agenda for Future Research

      By: Ofer Mintz, Imran S. Currim and Rohit Deshpandé
      Purpose: This paper aims to propose a new country-level construct, national customer orientation, to provide a benchmark for global headquartered managers’ decisions and scholars investigating cross-national research.
      Design/methodology/approach: A conceptual...  View Details
      Keywords: International Marketing; Macro-marketing; Marketing; Financial Crisis; Customer Focus and Relationships; Economic Growth; Economic Slowdown and Stagnation
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      Mintz, Ofer, Imran S. Currim, and Rohit Deshpandé. "National Customer Orientation: A Framework, Propositions and Agenda for Future Research." European Journal of Marketing 56, no. 4 (April 2022): 1014–1041.
      • August 2021
      • Case

      Orchadio’s First Two Split Experiments

      By: Iavor I. Bojinov, Marco Iansiti and David Lane
      Orchadio, a direct-to-consumer grocery business, needs to conduct its first two A/B tests—one to evaluate the effectiveness and functioning of its newly redesigned website, and one to market-test four versions of a new banner for the website. To do so, it will rely on...  View Details
      Keywords: Information Management; Technological Innovation; Knowledge Use and Leverage; Resource Allocation; Marketing; Measurement and Metrics; Customization and Personalization; Information Technology; Internet and the Web; Digital Platforms; Information Technology Industry; Food and Beverage Industry
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      Bojinov, Iavor I., Marco Iansiti, and David Lane. "Orchadio’s First Two Split Experiments." Harvard Business School Case 622-015, August 2021.
      • July 2021 (Revised July 2022)
      • Case

      Brigham & Women's Hospital: Using Patient Reported Outcomes to Improve Breast Cancer Care

      By: Robert S. Kaplan, Navraj S. Nagra and Syed S. Shehab
      Dr. Andrea Pusic, breast cancer reconstruction surgeon, wants to extend outcomes measurement beyond traditional surgical metrics of infections, complications, and survival rates. The case describes her development of a new mobile phone app, which collects patients’...  View Details
      Keywords: Health Care and Treatment; Outcome or Result; Cost Management; Activity Based Costing and Management; Mobile and Wireless Technology; Health Testing and Trials; Surveys; Health Industry; Boston
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      Kaplan, Robert S., Navraj S. Nagra, and Syed S. Shehab. "Brigham & Women's Hospital: Using Patient Reported Outcomes to Improve Breast Cancer Care." Harvard Business School Case 122-010, July 2021. (Revised July 2022.)
      • 2021
      • Working Paper

      Dirty Money: How Banks Influence Financial Crime

      By: Joseph Pacelli, Janet Gao, Jan Schneemeier and Yufeng Wu
      On September 21st, 2020, a consortium of international journalists leaked nearly 2,500 suspicious activity reports (SAR) obtained from the U.S. Financial Crimes Enforcement Network, exposing nearly $2 trillion of money laundering activity. The event raises important...  View Details
      Keywords: Financial Institutions; Crime and Corruption; Policy
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      Pacelli, Joseph, Janet Gao, Jan Schneemeier, and Yufeng Wu. "Dirty Money: How Banks Influence Financial Crime." Working Paper, July 2021.
      • July 2021
      • Article

      Information Transparency, Multihoming, and Platform Competition: A Natural Experiment in the Daily Deals Market

      By: Hui Li and Feng Zhu
      Platform competition is shaped by the likelihood of multi-homing (i.e., complementors or consumers adopt more than one platform). To take advantage of multi-homing, platform firms often attempt to motivate their rivals’ high-performing complementors to adopt their own...  View Details
      Keywords: Platform Competition; Multi-homing; Information Transparency; Daily Deals; Groupon; LivingSocial; Digital Platforms; Information; Competition
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      Li, Hui, and Feng Zhu. "Information Transparency, Multihoming, and Platform Competition: A Natural Experiment in the Daily Deals Market." Management Science 67, no. 7 (July 2021): 4384–4407.
      • 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).
      • May–June 2021
      • Article

      Why Start-ups Fail

      By: Thomas R. Eisenmann
      If you’re launching a business, the odds are against you: Two-thirds of start-ups never show a positive return. Unnerved by that statistic, a professor of entrepreneurship at Harvard Business School set out to discover why. Based on interviews and surveys with hundreds...  View Details
      Keywords: Entrepreneurship; Business Startups; Problems and Challenges; Failure
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      Eisenmann, Thomas R. "Why Start-ups Fail." Harvard Business Review 99, no. 3 (May–June 2021): 76–85.
      • March 2021
      • Supplement

      Artea (A), (B), (C), and (D): Designing Targeting Strategies

      By: Eva Ascarza and Ayelet Israeli
      Power Point Supplement to Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on...  View Details
      Keywords: Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School PowerPoint Supplement 521-719, March 2021.
      • March 2021
      • Case

      VideaHealth: Building the AI Factory

      By: Karim R. Lakhani and Amy Klopfenstein
      Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new...  View Details
      Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
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      Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.
      • September 2020 (Revised June 2023)
      • Teaching Note

      Artea (A), (B), (C), and (D): Designing Targeting Strategies

      By: Eva Ascarza and Ayelet Israeli
      Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and...  View Details
      Keywords: Targeted Advertising; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School Teaching Note 521-041, September 2020. (Revised June 2023.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (B): Including Customer-level Demographic Data

      By: Eva Ascarza and Ayelet Israeli
      This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The...  View Details
      Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (C): Potential Discrimination through Algorithmic Targeting

      By: Eva Ascarza and Ayelet Israeli
      This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The...  View Details
      Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (C): Potential Discrimination through Algorithmic Targeting." Harvard Business School Exercise 521-037, September 2020. (Revised July 2022.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (D): Discrimination through Algorithmic Bias in Targeting

      By: Eva Ascarza and Ayelet Israeli
      This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The...  View Details
      Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
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