IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v48y2019i812.html
   My bibliography  Save this article

Motivations and solution appropriateness in crowdsourcing challenges for innovation

Author

Listed:
  • Acar, Oguz A.

Abstract

Crowdsourcing challenges are fast emerging as an effective tool for solving complex innovation problems. The main strength of the crowdsourcing model is that it brings together a large number of diverse people from all over the world to focus on solving a problem. This openness, however, results in a large number of solutions that are not appropriate, and this inhibits organizations from leveraging the value of crowdsourcing efficiently and effectively. It is therefore essential to identify ways to increase the appropriateness of solutions generated in a crowdsourcing challenge. This paper takes a step towards that by exploring what motivates the crowd to participate in these challenges and how these motivations relate to solution appropriateness. Drawing on data from InnoCentive, one of the largest crowdsourcing platforms for innovation problems, this paper shows that the various types of motivation driving crowd members to participate were related in different ways to the appropriateness of the solutions generated. In particular, intrinsic and extrinsic motivation were positively related to appropriateness whereas for learning and prosocial motivation the relationship was negative. The association between social motivation and appropriateness was not significant. The results have important implications for how to better design crowdsourcing challenges.

Suggested Citation

  • Acar, Oguz A., 2019. "Motivations and solution appropriateness in crowdsourcing challenges for innovation," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    • Handle: RePEc:eee:respol:v:48:y:2019:i:8:12
    DOI: 10.1016/j.respol.2018.11.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048733318302889
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.respol.2018.11.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Suhada, Thontowi A. & Ford, Jerad A. & Verreynne, Martie-Louise & Indulska, Marta, 2021. "Motivating individuals to contribute to firms’ non-pecuniary open innovation goals," Technovation, Elsevier, vol. 102(C).
    2. Stanko, Michael A. & Allen, B.J., 2022. "Disentangling the collective motivations for user innovation in a 3D printing community," Technovation, Elsevier, vol. 111(C).
    3. Deichmann, Dirk & Gillier, Thomas & Tonellato, Marco, 2021. "Getting on board with new ideas: An analysis of idea commitments on a crowdsourcing platform," Research Policy, Elsevier, vol. 50(9).
    4. Piazza, Mariangela & Mazzola, Erica & Perrone, Giovanni, 2022. "How can I signal my quality to emerge from the crowd? A study in the crowdsourcing context," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    5. Livio Cricelli & Michele Grimaldi & Silvia Vermicelli, 2022. "Crowdsourcing and open innovation: a systematic literature review, an integrated framework and a research agenda," Review of Managerial Science, Springer, vol. 16(5), pages 1269-1310, July.
    6. Nambisan, Satish & Wright, Mike & Feldman, Maryann, 2019. "The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    7. Palacios-Marqués, Daniel & Gallego-Nicholls, José Fernando & Guijarro-García, María, 2021. "A recipe for success: Crowdsourcing, online social networks, and their impact on organizational performance," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    8. Naudé, Wim & Bray, Amy & Lee, Celina, 2021. "Crowdsourcing Artificial Intelligence in Africa: Findings from a Machine Learning Contest," IZA Discussion Papers 14545, Institute of Labor Economics (IZA).
    9. Xu, Hui & Wu, Yang & Hamari, Juho, 2022. "What determines the successfulness of a crowdsourcing campaign: A study on the relationships between indicators of trustworthiness, popularity, and success," Journal of Business Research, Elsevier, vol. 139(C), pages 484-495.
    10. Peter Konhäusner & Marius Thielmann & Veronica Câmpian & Dan-Cristian Dabija, 2021. "Crowdfunding for Independent Print Media: E-Commerce, Marketing, and Business Development," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    11. Yin, Xicheng & Wang, Hongwei & Wang, Wei & Zhu, Kevin, 2020. "Task recommendation in crowdsourcing systems: A bibliometric analysis," Technology in Society, Elsevier, vol. 63(C).
    12. Moghaddam, Ehsan Noorzad & Aliahmadi, Alireza & Bagherzadeh, Mehdi & Markovic, Stefan & Micevski, Milena & Saghafi, Fatemeh, 2023. "Let me choose what I want: The influence of incentive choice flexibility on the quality of crowdsourcing solutions to innovation problems," Technovation, Elsevier, vol. 120(C).
    13. Liu, Jialing & Wei, Jiang & Liu, Yang & Jin, Duo, 2022. "How to channel knowledge coproduction behavior in an online community: Combining machine learning and narrative analysis," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    14. Jiao, Yuanyuan & Wu, Yepeng & Lu, Steven, 2021. "The role of crowdsourcing in product design: The moderating effect of user expertise and network connectivity," Technology in Society, Elsevier, vol. 64(C).
    15. Ren, Jie & Han, Yue & Genc, Yegin & Yeoh, William & Popovič, Aleš, 2021. "The boundary of crowdsourcing in the domain of creativity✰," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    16. Liu, Yang & Dong, Jiuyu & Mei, Liang & Shen, Rui, 2023. "Digital innovation and performance of manufacturing firms: An affordance perspective," Technovation, Elsevier, vol. 119(C).
    17. Pankaj Kumar & Swanand J. Deodhar & Srilata Zaheer, 2023. "Cognitive sources of liability of foreignness in crowdsourcing creative work," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(4), pages 686-716, June.
    18. Patel, Chirag & Ahmad Husairi, Mariyani & Haon, Christophe & Oberoi, Poonam, 2023. "Monetary rewards and self-selection in design crowdsourcing contests: Managing participation, contribution appropriateness, and winning trade-offs," Technological Forecasting and Social Change, Elsevier, vol. 191(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:respol:v:48:y:2019:i:8:12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/respol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.