Getting inside your employees' heads: Navigating barriers to internalcrowdsourcing for product and service innovation

Lee B. Erickson, Irene Petrick, Eileen M. Trauth

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

Organizations are beginning to experiment with the use of the "crowd" to complete tasks commonly performed by employees or designated agents. While "crowdsourcing" is growing, we know little about common uses of the crowd and the challenges such initiatives present. Findings from a grounded theory study reveal four common uses by established organizations: productivity, product/service innovation, knowledge capture, and marketing/branding. Further, leveraging internal crowds for product/service innovation may present unique challenges. Based on findings, an Internal-Crowdsourcing Acceptance Model illustrates the role of proactive executive leadership in breaking through organizational structure and processes that act as barriers to acceptance and use of internal-crowdsourcing platforms. The anticipated theoretical contribution of this research is the finding that internal-crowdsourcing presents many of the same challenges to organizations as faced in open innovation initiatives. Its anticipated contribution to practice is the identification of the role proactive executive leadership plays in reducing barriers to successful outcomes.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems, ICIS 2012
Pages3628-3638
Number of pages11
StatePublished - 2012
EventInternational Conference on Information Systems, ICIS 2012 - Orlando, FL, United States
Duration: Dec 16 2012Dec 19 2012

Publication series

NameInternational Conference on Information Systems, ICIS 2012
Volume4

Other

OtherInternational Conference on Information Systems, ICIS 2012
Country/TerritoryUnited States
CityOrlando, FL
Period12/16/1212/19/12

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Library and Information Sciences

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