Externalities in Knowledge Production: Evidence from a Randomized Field Experiment

Hinnosaar, Marit; Hinnosaar, Toomas; Kummer, Michael E.; Slivko, Olga

doi:10.2139/ssrn.3341630

Cited by 2 publications

(1 citation statement)

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“…Another natural question for further research is whether the additional content spurs additional organic content. This question was addressed in a separate paper that uses the data from the same experiment (Hinnosaar et al, 2020). This paper shows that the added material has a relatively small effect on future content growth, suggesting that edits to user-generated content should be undertaken solely based on their value rather than possible externalities.…”

Section: Limitations and Future Researchmentioning

confidence: 99%

Wikipedia matters

Hinnosaar

Kummer

et al. 2021

Economics Manag Strategy

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We document a causal impact of online user-generated information on realworld economic outcomes. In particular, we conduct a randomized field experiment to test whether additional content on Wikipedia pages about cities affects tourists' choices of overnight visits. Our treatment of adding information to Wikipedia increases overnight stays in treated cities compared to nontreated cities. The impact is largely driven by improvements to shorter and relatively incomplete pages on Wikipedia. Our findings highlight the value of digital public goods for informing individual choices. | INTRODUCTIONAsymmetric information can hinder efficient economic activity (Akerlof, 1970). In recent decades, the Internet and new media have enabled greater access to information than ever before. However, the digital divide, language barriers, Internet censorship, and technological constraints still create inequalities in the amount of accessible information (see

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Section: Limitations and Future Researchmentioning

confidence: 99%

Wikipedia matters

Hinnosaar

Kummer

et al. 2021

Economics Manag Strategy

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Information Seeding and Knowledge Production in Online Communities: Evidence from OpenStreetMap

Nagaraj

2021

Management Science

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The wild success of a few online communities (such as Wikipedia) has obscured the fact that most attempts at forming such communities fail. This study evaluates information seeding, an early-stage intervention to bootstrap online communities that enables contributors to build on externally sourced information rather than have them start from scratch. I analyze the effects of information seeding on follow-on contributions using data on more than 350 million contributions made by more than 577,000 contributors to OpenStreetMap, a crowd-sourced map-making community seeded with data from the U.S. Census. I estimate the effect of seeding using a natural experiment in which an oversight caused about 60% of U.S. counties to be seeded with a complete census map, while the rest were seeded with less complete versions. Although access to basic knowledge generally encourages downstream knowledge production, I find that a higher level of information seeding significantly lowered follow-on contributions and contributor activity on OpenStreetMap, and was associated with lower levels of long-term quality. However, seeding did benefit densely populated urban areas and did not discourage more committed users. To explain these patterns, I argue that information seeding can crowd out contributors’ ability to develop ownership over baseline knowledge and thereby disincentivize follow-on contributions. This paper was accepted by Chris Forman, information systems.

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Externalities in Knowledge Production: Evidence from a Randomized Field Experiment

Cited by 2 publications

References 50 publications

Wikipedia matters

Wikipedia matters

Information Seeding and Knowledge Production in Online Communities: Evidence from OpenStreetMap

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