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Motivations and solution appropriateness in crowdsourcing challenges for innovation

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  • 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
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    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. 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).
    3. Stanko, Michael A. & Allen, B.J., 2022. "Disentangling the collective motivations for user innovation in a 3D printing community," Technovation, Elsevier, vol. 111(C).
    4. Liu, Yang & Dong, Jiuyu & Mei, Liang & Shen, Rui, 2023. "Digital innovation and performance of manufacturing firms: An affordance perspective," Technovation, Elsevier, vol. 119(C).
    5. 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).
    6. 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).
    7. 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.
    8. Stefan Stremersch & Elke Cabooter & Ivan Guitart & Nuno Camacho, 2024. "Customer insights for innovation : A framework and research agenda for marketing," Post-Print hal-04731671, HAL.
    9. 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.
    10. Mindel, Vitali & Overstreet, Robert E. & Sternberg, Henrik & Mathiassen, Lars & Phillips, Nelson, 2024. "Digital activism to achieve meaningful institutional change: A bricolage of crowdsourcing, social media, and data analytics," Research Policy, Elsevier, vol. 53(3).
    11. 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).
    12. 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.
    13. 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).
    14. 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.
    15. 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.
    16. Tekic, Anja & Alfonzo Pacheco, Diana Vilma, 2024. "Contest design and solvers' engagement behaviour in crowdsourcing: The neo-configurational perspective," Technovation, Elsevier, vol. 132(C).
    17. Yin, Xicheng & Wang, Hongwei & Wang, Wei & Zhu, Kevin, 2020. "Task recommendation in crowdsourcing systems: A bibliometric analysis," Technology in Society, Elsevier, vol. 63(C).
    18. 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).
    19. 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).
    20. 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).
    21. 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).

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