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A Comparison of Crowd Types: Idea Selection Performance of Students and Amazon Mechanical Turks

In: Innovation Through Information Systems

Author

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  • Victoria Banken

    (University of Innsbruck)

Abstract

Crowdsourcing is an effective means to generate a multitude of ideas in a very short amount of time. Therefore, companies and researchers increasingly tap into the power of the crowd for the evaluation of these ideas. However, not all types of crowds are the equally capable for complex decision-making tasks, which might result in poor selection performance. This research aims to evaluate differences in anonymous crowds and student crowds regarding their information processing, attention and selection performance. A web-experiment with 339 participants was conducted to reveal that 1) undergraduate Information Systems students perform better in idea selection than crowd workers recruited from Amazon Mechanical Turk, 2) attention checks increase selection performance and 3) while crowd workers indicate to process information more systematically, students acquire more information for evaluation than crowd workers.

Suggested Citation

  • Victoria Banken, 2021. "A Comparison of Crowd Types: Idea Selection Performance of Students and Amazon Mechanical Turks," Lecture Notes in Information Systems and Organization, in: Frederik Ahlemann & Reinhard Schütte & Stefan Stieglitz (ed.), Innovation Through Information Systems, pages 437-453, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-86800-0_30
    DOI: 10.1007/978-3-030-86800-0_30
    as

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