Why and How Firms Implement Internal Crowdsourcing Platforms

Michela Beretta, Lars Frederiksen, Martin Wallin, Viktorija Kulikovskaja

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

9 Citations (Scopus)

Abstract

Internal crowdsourcing platforms enable firms to involve a wider crowd of employees beyond the R&D department in the generation and development of ideas for innovation. Prior studies emphasize firm-level functional benefits, e.g., accessing larger and more diverse sets of ideas, competences, and expertise as well as reducing the costs for innovation. Inspired by the behavioral theory of the firm, we depart from such functionalist approach and develop a model that explains why and how managers in large organizations implement and design internal crowdsourcing. Drawing on a qualitative, multiple case study of five large organizations, we identify three key motives that underpin managers' decision to implement an internal crowdsourcing platform: problem-stimulated, opportunity-driven, and legitimacy-seeking. Next, we discuss how such different motives drive managers' decisions regarding their design of the internal crowdsourcing initiative. Broadly, our results help explain why firms continue to invest in crowdsourcing initiatives despite meager results and how managers' cognitive frameworks impact heterogeneity in the design and implementation of crowdsourcing initiatives. This article contributes to the crowdsourcing literature by providing a more multifaceted picture of internal crowdsourcing than previous research has suggested. From a practitioners' perspective, awareness and recognition by managers of the potential pitfalls in implementing and designing these platforms stand out as an important first step toward improving the effectiveness of internal crowdsourcing.

Original languageEnglish
JournalIEEE Transactions on Engineering Management
Volume70
Issue9
Pages (from-to)3036-3049
Number of pages14
ISSN0018-9391
DOIs
Publication statusPublished - Sept 2023

Keywords

  • Crowdsourcing
  • Decision making
  • Industries
  • Interviews
  • Organizations
  • Search problems
  • Technological innovation
  • decision making
  • innovation management
  • organizational aspects
  • technology management

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