Alexander Staub, Ph.D.
I am a postdoctoral researcher at the Digital Markets Lab as part of the Data Economy Project at the University of Lausanne, Faculty of Business and Economics (HEC Lausanne). I am also affiliated with the Laboratory for Innovation Science at Harvard & D3 at Harvard Business School, where I am a guest researcher.
I am interested in the economics of digital technology and innovation. My research is driven by the desire to understand the intended and unintended consequences of policy and governance measures in response to technological change.
Before joining HEC Lausanne, I completed my Ph.D. at the WU Vienna University of Economics and Business at the Institute for Strategy, Technology and Organization. I hold a M.Sc. Degree from the University of Manchester,´ and a B.Sc. degree from WU.
Get in touch: alexander.staub [at] unil.ch
Publications
Heavy Medal - The Consequences of Introducing Symbolic Awards on Contribution Behavior in Online Communities
Alexander Staub, Tom Grad (CBS), Christopher Lettl (WU Vienna)
Online communities, like Wikipedia and Stack Overflow, have made a vast knowledge repository available as a public good. However, they suffer from under-contribution in terms of quantity and quality. To tackle this issue, online communities have increasingly been relying on gamification, the use of game elements in non-game settings, to incentivize their members. The consequences of introducing such features on members’ behavior have remained elusive. To address this gap, we take advantage of a natural experiment in which a technical online community introduced gamified rewards, which are awarded contingent on performance thresholds—termed performance contingent symbolic awards. Employing a difference-in-differences design using a comparable online community as a control group, we find that the introduction of performance-contingent symbolic awards harms the contribution behavior overall and that experienced members reduce their contribution quantity while inexperienced members reduce their contribution quality.
Working Papers
Strategic Behavior and AI Training Data
Together with: Florian Abeillon, Jérémie Haese, Franziska Kaiser, and Christian Peukert (all at HEC Lausanne)
Stage: under review at the Review of Economic Studies
intelligence (AI). Strategic behavior can play a major role for AI training datasets, be it in limiting access to existing works or in deciding which types of new works to create or whether to create any at all. We examine creators' behavioral change when their works become training data for AI. Specifically, we focus on contributors on Unsplash, a popular stock image platform with about 6 million high-quality photos and illustrations. In the summer of 2020, Unsplash launched an AI research program by releasing a dataset of 25,000 images for commercial use. We study contributors' reactions, comparing contributors whose works were included in this dataset to contributors whose works were not. Our results suggest that treated contributors left the platform at a higher-than-usual rate and substantially slowed down the rate of new uploads. Professional and more successful photographers had a stronger reaction than amateurs and less successful photographers. We also show that affected users changed the variety and novelty of contributions to the platform, which can potentially lead to lower-quality AI outputs in the long run. Taken together, our findings highlight the trade-off between the interests of rightsholders and promoting innovation at the technological frontier. We discuss implications for copyright and AI policy.
Governance of Firm-Hosted Online Communities: A Natural Experiment with Performance-Contingent Symbolic Awards
Together with: Tom Grad (CBS), Christopher Lettl (WU Vienna)
Stage: under review at the Strategic Management Journal
Extension of the ICIS Proceedings 2022 publication "Heavy Medal - The Consequences of Introducing Symbolic Awards on Contribution Behavior in Online Communities"
Firm-hosted online communities can be a source of competitive advantage but often suffer from members' under-performance in terms of contribution quantity and quality. However, establishing governance mechanisms to steer participants’ behavior towards value-generating activities is challenging. We study how the governance intervention of introducing performance-contingent symbolic awards affects contribution behavior and the role of heterogeneity in members’ experience. Exploiting a natural experiment in a firm-hosted online community, we find that the intervention backfires both in terms of contribution quantity and quality, and that within-community experience of members is an important determinant of how they react. However, we also find positive effects such as a reduction in the response time to questions and an increase in the difficulty of questions that are answered.
Sounds familiar? Investigating the Impact of Transparency in the Creative Industries
Together with: Alessio Delpero (WU Vienna)
Stage: data analysis
Target: Strategic Management Journal
In the creative industries, the power and network dynamics of gatekeepers and producers of creative goods determine consumer choice. Given this cross-influence information, intermediaries reduce information asymmetry and gather and aggregate information, providing a transparent view of consumption preferences for consumers, producers, and gatekeepers. While the drawbacks of information asymmetry for market efficiency are undisputed, the increase in transparency might stifle creativity by imposing stringent rules and reducing ambiguity. Focusing on Billboard’s transparency policy regarding rules around remixing, we investigate how increased transparency imposed by information intermediaries affects the number of artists and songs available on the market and the diversity of songs. We exploit a quasi-natural experiment imposed by Billboard in 2002, employing the entire song portfolio of record labels operating in the U.S. and 5 European countries from 1998 to 2005. We use a difference-in-differences design to study the effects of the policy change on the quantity as well as the variety in output. We find that, while the number of artists releasing songs at record labels decreases, the number of songs and their average diversity remains consistent when increased transparency is imposed. In addition, we find a notable reduction in the variability of song similarity in the U.S., indicating a decline in radically diverse outputs at the extremes of the product distribution. Our findings highlight the need for a carefully balanced approach to transparency policies in creative industries.
Work in Progress
Do Developers Pay to be Open-Source Developers? Field Experimental Evidence from an Online Labor Market
Together with: Karim Lakhani, Frank Nagle, and Manuel Hoffmann (Harvard Business School)
Stage: implementation of field experiment
Target: Management Science
Unintended Consequences of Pulling out: Age Verification Regulation and Online User Behavior
Together with: Gordon Burtch (Boston University) and Benjamin Barraza (Weber State University)
Stage: data analysis
Target: Management Science