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- Research (51)
- Faculty Publications (19)
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- 2023
- Article
Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.
By: Edward McFowland III and Cosma Rohilla Shalizi
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its... View Details
Keywords: Causal Inference; Homophily; Social Networks; Peer Influence; Social and Collaborative Networks; Power and Influence; Mathematical Methods
McFowland III, Edward, and Cosma Rohilla Shalizi. "Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations." Journal of the American Statistical Association 118, no. 541 (2023): 707–718.
- April 2020
- Article
Designs for Estimating the Treatment Effect in Networks with Interference
By: Ravi Jagadeesan, Natesh S. Pillai and Alexander Volfovsky
In this paper, we introduce new, easily implementable designs for drawing causal inference from randomized experiments on networks with interference. Inspired by the idea of matching in observational studies, we introduce the notion of considering a treatment... View Details
Keywords: Experimental Design; Network Inference; Neyman Estimator; Symmetric Interference Model; Homophily
Jagadeesan, Ravi, Natesh S. Pillai, and Alexander Volfovsky. "Designs for Estimating the Treatment Effect in Networks with Interference." Annals of Statistics 48, no. 2 (April 2020): 679–712.
Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore... View Details
- Article
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
By: Wanqian Yang, Lars Lorch, Moritz Graule, Himabindu Lakkaraju and Finale Doshi-Velez
Domains where supervised models are deployed often come with task-specific constraints, such as prior expert knowledge on the ground-truth function, or desiderata like safety and fairness. We introduce a novel probabilistic framework for reasoning with such constraints... View Details
Yang, Wanqian, Lars Lorch, Moritz Graule, Himabindu Lakkaraju, and Finale Doshi-Velez. "Incorporating Interpretable Output Constraints in Bayesian Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
- 2023
- Working Paper
Black-box Training Data Identification in GANs via Detector Networks
By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
- 11 AM – 12 PM EST, 25 Jan 2018
- Webinars: Trending@HBS
Becoming Effective Change Makers: The Power of Networks
Instituting change in an organization or in a sector of society has always been the bane of leaders. However, some leaders do succeed--often spectacularly--at transforming their organizations and even whole sectors of society. What makes some change makers triumph in a... View Details
- February 2016
- Article
After The Break-Up: The Relational and Reputational Consequences of Withdrawals from Venture Capital Syndicates
By: Pavel Zhelyazkov and Ranjay Gulati
Traditional research has long treated reputation as an egocentric attribute, typically described as an intangible asset directly shaped by the focal actor's track record. We argue, however, that reputation is dyadic: that an actor can have different reputations with... View Details
Zhelyazkov, Pavel, and Ranjay Gulati. "After The Break-Up: The Relational and Reputational Consequences of Withdrawals from Venture Capital Syndicates." Academy of Management Journal 59, no. 1 (February 2016): 277–301.
- June 2015
- Case
The Coca-Cola Company's Case for Creative Transformation
By: Thales S. Teixeira and Elizabeth Anne Watkins
In 2013, the Coca-Cola Company was awarded Creative Marketer of the Year by the Cannes Lions Festival (known as the "Oscar of Advertising") for the first time ever in history and nearly 50 years after the Festival's inception. Just one year before that, Jonathan... View Details
Keywords: Attention Economics; Creating Connections; Digital Marketing; Marketing Innovations; Social Networks; Advertising Content; Networked Brand; Beverage Industry; Coca-Cola; Digital Innovation; Digital Transition; Marketing; Marketing Communications; Innovation Strategy; Social and Collaborative Networks; Advertising; Creativity; Consumer Products Industry
Teixeira, Thales S., and Elizabeth Anne Watkins. "The Coca-Cola Company's Case for Creative Transformation." Harvard Business School Multimedia/Video Case 815-714, June 2015.
- March 2018
- Case
TrustSphere: Building a Market for Relationship Analytics
By: Boris Groysberg and Katherine Connolly Baden
Manish Goel was the CEO of TrustSphere, a seven-year-old company in the data analytics industry that focused squarely on relationship analytics, a space in which TrustSphere was pioneering a unique technology and solutions in the areas of sales, risk, and people... View Details
Keywords: Data Analytics; People Analytics; Talent Management; Human Resources; Networks; Relationships; Analysis; Employee Relationship Management; Core Relationships; Applications and Software; Communication; Technology Industry; Singapore
Groysberg, Boris, and Katherine Connolly Baden. "TrustSphere: Building a Market for Relationship Analytics." Harvard Business School Case 418-070, March 2018.
- Research Summary
Statistical Methodology
William Simpson is developing methods of inference to use when assumptions of standard models are not met. He has created a hypothesis test to use for ipsative variables that adjusts for the non-zero correlations among variables expected under the null hypothesis. ... View Details
- March 2021
- Article
The Impact of the General Data Protection Regulation on Internet Interconnection
By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on... View Details
Keywords: Personal Data; Privacy Regulation; GDPR; Interconnection Agreements; Internet and the Web; Governing Rules, Regulations, and Reforms
Zhuo, Ran, Bradley Huffaker, KC Claffy, and Shane Greenstein. "The Impact of the General Data Protection Regulation on Internet Interconnection." Telecommunications Policy 45, no. 2 (March 2021).
- 2019
- Working Paper
The Impact of the General Data Protection Regulation on Internet Interconnection
By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on... View Details
Keywords: Personal Data; Privacy Regulation; GDPR; Interconnection Agreements; Internet and the Web; Governing Rules, Regulations, and Reforms; European Union
Zhuo, Ran, Bradley Huffaker, KC Claffy, and Shane Greenstein. "The Impact of the General Data Protection Regulation on Internet Interconnection." NBER Working Paper Series, No. 26481, November 2019.
- 2017
- Working Paper
The Right Mix: Angels, Venture Capitalists, and the Assembly of Entrepreneurial Resources
By: Benjamin Hallen and Rory McDonald
New ventures rely on external relationships for capital, knowledge, and networks. We examine how ventures assemble these resources—and whether they are all accessible from the same sources—in relationships with two types of investors: venture capital firms and angels.... View Details
- 2019
- Article
Structural Balance Emerges and Explains Performance in Risky Decision-Making
By: Omid Askarisichani, Jacqueline N. Lane, Francesco Bullo, Noah E. Friedkin, Ambuj K. Singh and Brian Uzzi
Polarization affects many forms of social organization. A key issue focuses on which affective relationships are prone to change and how their change relates to performance. In this study,
we analyze a financial institutional over a two-year period that employed 66... View Details
Keywords: Polarization; Structural Balance; Performance; Groups and Teams; Risk and Uncertainty; Decision Making
Askarisichani, Omid, Jacqueline N. Lane, Francesco Bullo, Noah E. Friedkin, Ambuj K. Singh, and Brian Uzzi. "Structural Balance Emerges and Explains Performance in Risky Decision-Making." Art. 2648. Nature Communications 10 (2019): 1–10.
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- Research Summary
Overview
By: Eva Ascarza
Professor Ascarza’s research primarily focuses on providing researchers and marketers a better understanding of how to manage customer retention so as to reduce churn and increase firm’s profitability. She addresses these issues by building empirical models of customer... View Details
- 30 Apr 2019
- First Look
New Research and Ideas, April 30, 2019
platform businesses. We have five major themes in the book: 1) The world’s most valuable companies are all platforms, in part because platforms have network effects, with the potential for a winner-take-all or winner-take-most outcome. 2)... View Details
Keywords: Dina Gerdeman
- 06 Mar 2018
- First Look
First Look at Research and Ideas, March 6, 2018
likely to make aggressive offers in distributive negotiations than those who interacted with counterparts expressing neutral emotion. In Study 2, we find that inferences of the tendency to forgive mediates the relationship between... View Details
Keywords: Sean Silverthorne
- June 2017 (Revised May 2019)
- Supplement
Kjell and Company: Motivating Salespeople with Incentive Compensation (B)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain founded in 1988 by brothers Marcus, Mikael and Fredrik Dahnelius. The company operated 84 stores, all company-owned, located mainly in the metropolitan areas of Sweden’s most popular cities: Stockholm, Gothemburg... View Details
Keywords: Salesforce Management; Compensation and Benefits; Motivation and Incentives; Change Management; Behavior; Electronics Industry; Sweden
Chung, Doug J. "Kjell and Company: Motivating Salespeople with Incentive Compensation (B)." Harvard Business School Supplement 517-133, June 2017. (Revised May 2019.)
- 24 Feb 2015
- First Look
First Look: February 24
rates persist through the three weeks of available data following the initial intervention. Download working paper: http://people.hbs.edu/mluca/ALERT.pdf Thick as Thieves? Dishonest Behavior and Egocentric Social Networks By: Lee, Jooa... View Details
Keywords: Sean Silverthorne