Collaboration and Locality in Crowdsourcing

Andreas Mladenow; Christine Bauer; Christine Strauss; Michal Gregus

doi:10.1109/INCoS.2015.74

Collaboration and Locality in Crowdsourcing

Andreas Mladenow
, Christine Bauer
, Christine Strauss
, Michal Gregus

Institute for Information Systems and Society

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

Abstract

As novel forms of crowdsourcing emerge on the market, we emphasize that the important aspect of location- dependency is more complex than assumed and, thus, suggest a typology along two dimensions of locality: the first dimension refers to whether or not the crowdsourcees interact while being collocated or dispersed; the second dimension refers to the locality of the crowdsourcees in relation to the crowdsourcer's locality (local vs. remote crowd). The resulting four types of crowdsourcing are underpinned by real-world examples. Potential advantages and challenges of the four types are discussed, particularly with respect to motivation and value. The suggested categorization shall provide the necessary basis for future research, as a systematic approach is essential to enable, yield and foster sustainability in a novel interdisciplinary research field like location-based crowdsourcing.

Original language	English
Title of host publication	7th International Conference on Intelligent Networking and Collaborative Systems (INCoS 2015)
Editors	IEEE
Place of Publication	Taipei, Taiwan
Publisher	IEEE
Pages	1 - 6
ISBN (Print)	978-1-4673-7695-2
DOIs	https://doi.org/10.1109/INCoS.2015.74
Publication status	Published - 1 Oct 2015

Austrian Classification of Fields of Science and Technology (ÖFOS)

102015 Information systems
102013 Human-computer interaction
502050 Business informatics

Access to Document

10.1109/INCoS.2015.74Licence: Unspecified

Cite this

@inproceedings{2ded5673e5d243629bb2e943a5dea570,

title = "Collaboration and Locality in Crowdsourcing",

abstract = "As novel forms of crowdsourcing emerge on the market, we emphasize that the important aspect of location- dependency is more complex than assumed and, thus, suggest a typology along two dimensions of locality: the first dimension refers to whether or not the crowdsourcees interact while being collocated or dispersed; the second dimension refers to the locality of the crowdsourcees in relation to the crowdsourcer's locality (local vs. remote crowd). The resulting four types of crowdsourcing are underpinned by real-world examples. Potential advantages and challenges of the four types are discussed, particularly with respect to motivation and value. The suggested categorization shall provide the necessary basis for future research, as a systematic approach is essential to enable, yield and foster sustainability in a novel interdisciplinary research field like location-based crowdsourcing.",

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T1 - Collaboration and Locality in Crowdsourcing

AU - Mladenow, Andreas

AU - Bauer, Christine

AU - Strauss, Christine

AU - Gregus, Michal

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N2 - As novel forms of crowdsourcing emerge on the market, we emphasize that the important aspect of location- dependency is more complex than assumed and, thus, suggest a typology along two dimensions of locality: the first dimension refers to whether or not the crowdsourcees interact while being collocated or dispersed; the second dimension refers to the locality of the crowdsourcees in relation to the crowdsourcer's locality (local vs. remote crowd). The resulting four types of crowdsourcing are underpinned by real-world examples. Potential advantages and challenges of the four types are discussed, particularly with respect to motivation and value. The suggested categorization shall provide the necessary basis for future research, as a systematic approach is essential to enable, yield and foster sustainability in a novel interdisciplinary research field like location-based crowdsourcing.

AB - As novel forms of crowdsourcing emerge on the market, we emphasize that the important aspect of location- dependency is more complex than assumed and, thus, suggest a typology along two dimensions of locality: the first dimension refers to whether or not the crowdsourcees interact while being collocated or dispersed; the second dimension refers to the locality of the crowdsourcees in relation to the crowdsourcer's locality (local vs. remote crowd). The resulting four types of crowdsourcing are underpinned by real-world examples. Potential advantages and challenges of the four types are discussed, particularly with respect to motivation and value. The suggested categorization shall provide the necessary basis for future research, as a systematic approach is essential to enable, yield and foster sustainability in a novel interdisciplinary research field like location-based crowdsourcing.

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