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  • May 2021
  • Article

Ideology and Composition Among an Online Crowd: Evidence From Wikipedians
By: Shane Greenstein, Grace Gu and Feng Zhu
Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that...  View Details
Keywords: User Segregation; Online Community; Contested Knowledge; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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  • May 19, 2021
  • Article

Measuring the Impact of #MeToo on Gender Equity in Hollywood
By: Hong Luo and Laurina Zhang
The #MeToo movement has brought issues of sexual harassment and gender inequities to the forefront around the world. But how much of a tangible impact has it had on the experiences of women in the workplace? In this piece, the authors discuss their research that...  View Details
Keywords: #MeToo Movement; Gender Equity; Creative Industries; Impact; Gender; Equality and Inequality; Film Entertainment; Social Issues
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  • 2021
  • Working Paper

Population Interference in Panel Experiments
By: Iavor I Bojinov, Kevin Wu Han and Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in...  View Details
Keywords: Finite Population; Potential Outcomes; Dynamic Causal Effects; Mathematical Methods
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  • 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; Governing Rules, Regulations, and Reforms
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  • 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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  • 2021
  • Article

Consumer Disclosure
By: Tami Kim, Kate Barasz and Leslie John
As technological advances enable consumers to share more information in unprecedented ways, today’s disclosure takes on a variety of new forms, triggering a paradigm shift in what “disclosure” entails. This review introduces two factors to conceptualize consumer...  View Details
Keywords: Disclosure; Passive Disclosure; Information; Online Technology; Consumer Behavior; Situation or Environment
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  • 2021
  • 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
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  • 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
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  • October 2020
  • Article

Overcoming Resource Scarcity: Consumers' Response to Gifts Intending to Save Time and Money
By: Alice Lee-Yoon, Grant Donnelly and A.V. Whillans
Consumers feel increasingly pressed for time and money. Gifts have the potential to reduce scarcity in recipients’ lives, yet little is known about how recipients perceive gifts given with the intention of saving them time or money. Across four studies (N=1,403), we...  View Details
Keywords: Scarcity; Status; Time; Gift Giving; Status and Position; Money; Attitudes; Emotions
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  • 2020
  • Working Paper

Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted...  View Details
Keywords: Switchback Experiments; Design; Analysis; Mathematical Methods
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  • Article

The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments....  View Details
Keywords: Causal Inference; Observational Studies; Cross-sectional Studies; Panel Studies; Interrupted Time-series; Instrumental Variables
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  • June 2020
  • Article

In Generous Offers I Trust: The Effect of First-offer Value on Economically Vulnerable Behaviors
By: M. Jeong, J. Minson and F. Gino
Negotiation scholarship espouses the importance of opening a bargaining situation with an aggressive offer, given the power of first offers to shape concessionary behavior and outcomes. In our research, we identify a surprising consequence to this common prescription....  View Details
Keywords: Attribution; Interpersonal Interaction; Judgment; Social Interaction; Inference; Open Data; Open Materials; Preregistered; Negotiation Offer; Strategy; Behavior; Interpersonal Communication; Trust; Outcome or Result
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  • 2020
  • Working Paper

Research Subsidy Spillovers, Two Ways
By: Kyle Myers and Lauren Lanahan
We study how the outputs of research spill over technological and geographic space in the context of the U.S. Small Business Innovation Research program. We infer input-output links using text analyses and identify the marginal costs of producing patents using...  View Details
Keywords: Innovation; Small Business; Innovation and Invention; Patents
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  • April 2020
  • Article

Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning
By: Ariel Dora Stern and W. Nicholson Price, II
In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has been engaging...  View Details
Keywords: Machine Learning; Causal Inference; Health Care and Treatment; Safety; Governing Rules, Regulations, and Reforms
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  • November 2019
  • Article

Procedural Justice and the Risks of Consumer Voting
By: Tami Kim, Leslie John, Todd Rogers and Michael I. Norton
Firms are increasingly giving consumers the vote. Eight studies demonstrate that when firms empower consumers to vote, consumers infer a series of implicit promises—even in the absence of explicit promises. We identify three implicit promises to which consumers react...  View Details
Keywords: Consumer Empowerment; Procedural Justice; Promises; Customer Relationship Management; Voting; Perception; Fairness; Risk Management
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  • 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; Governing Rules, Regulations, and Reforms; European Union
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  • Article

Reverse the Curse of the Top-5
By: Robert S. Kaplan
The past 40 years has seen a large increase in the number of articles submitted to journals ranked in the top-5 of their discipline. This increase is the rational response, by faculty, to the overweighting of publications in these journals by university promotions and...  View Details
Keywords: Information Publishing; Journals and Magazines; Power and Influence; Research
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  • May 2019
  • Supplement

Kjell and Company: Motivating Salespeople with Incentive Compensation (C)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain. The company’s products consisted of home electronics and accessories. The company was noted for its excellent customer service and a fair “one-for-all” HR policy. Historically, the salespeople had been compensated...  View Details
Keywords: Salesforce Management; Compensation and Benefits; Change Management; Behavior; Electronics Industry; Sweden
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  • May 2019
  • Supplement

Kjell and Company: Motivating Salespeople with Incentive Compensation (D)
By: Doug J. Chung
Kjell & Company was a Swedish retail electronics chain. The company’s products consisted of home electronics and accessories. The company was noted for its excellent customer service and a fair “one-for-all” HR policy. Historically, the salespeople had been compensated...  View Details
Keywords: Salesforce Management; Compensation and Benefits; Motivation and Incentives; Change Management; Behavior; Electronics Industry; Sweden
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  • 2020
  • Working Paper

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; Customer Value and Value Chain; Consumer Behavior; Data and Data Sets; Mathematical Methods; Retail Industry
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