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

Victoria Banken ()
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Victoria Banken: University of Innsbruck

A chapter in Innovation Through Information Systems, 2021, pp 437-453 from Springer

Abstract: 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.

Keywords: Open Innovation; Crowdsourcing; Crowd types; Amazon Mechanical Turk; Student sample; Attention (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-86800-0_30

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DOI: 10.1007/978-3-030-86800-0_30

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