Economics at your fingertips  

The effects of task instructions in crowdsourcing innovative ideas

Thomas Gillier, Cédric Chaffois, Mustapha Belkhouja, Yannig Roth and Barry L. Bayus

Technological Forecasting and Social Change, 2018, vol. 134, issue C, 35-44

Abstract: The existing literature offers conflicting advice regarding the types of task instructions that increase the quality of ideas during idea generation. Our research examines three types of task instructions: unbounded (participants are asked to generate any ideas they want), suggestive (participants are asked to propose ideas that improve current product benefits), and prohibitive (participants are asked to propose ideas that do not involve current product benefits). We explore the effectiveness of these three types of task instructions in a field study involving 6406 ideas from eYeka, a global crowdsourcing platform. As compared to unbounded task instructions, we find that suggestive task instructions are significantly related to lower idea originality, feasibility, and value. In addition, we find that idea originality and value are statistically equivalent for unbounded and prohibitive task instructions. Together, our results suggest that either unbounded or prohibitive task instructions should be used when crowdsourcing innovative ideas.

Keywords: Problem formulation; Idea generation; Crowdsourcing; Creativity; Fixation (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2018-11-10
Handle: RePEc:eee:tefoso:v:134:y:2018:i:c:p:35-44