IDEAS home Printed from https://ideas.repec.org/a/eee/techno/v132y2024ics0166497224000191.html
   My bibliography  Save this article

Crowd mining as a strategic resource for innovation seekers

Author

Listed:
  • Bonazzi, Riccardo
  • Viscusi, Gianluigi
  • Solidoro, Adriano

Abstract

This article explores how to help people who organize crowdsourcing events (called “seekers”) choose the best ideas from those submitted by participants (called “solvers'). To this end, we created a method using techniques like topic modeling and text analysis to sort and group ideas. Then, we tested this method on data from crowdsourcing contests in Italy in 2021. In particular, considering the literature on intermediaries, we focus on intermediation in crowdsourcing to improve the decision-making processes in those initiatives where searching activities are intermediated by digital platforms, besides other human intermediaries. This method makes it easier for seekers to handle multiple ideas, and it also helps them find better-quality ideas. Moreover, from a theoretical point of view, our method could lead to better results in crowdsourcing challenges because it groups ideas based on their content without being influenced by the organizers' pre-existing knowledge or biases. This means that seekers might discover new and unexpected topics or solutions they hadn't thought of before. From a practical standpoint, for managers organizing crowdsourcing events, this method is valuable because it not only saves time and effort but also potentially uncovers innovative and diverse ideas. Additionally, the method includes a feature that shows how much participants interact and share knowledge, thus implementing the concept of “transactivity”, which, to the best of our knowledge, hasn't been used in crowdsourcing studies before. This can help crowdsourcing organizers better understand which contests are more effective at encouraging collaboration and knowledge sharing among participants.

Suggested Citation

  • Bonazzi, Riccardo & Viscusi, Gianluigi & Solidoro, Adriano, 2024. "Crowd mining as a strategic resource for innovation seekers," Technovation, Elsevier, vol. 132(C).
  • Handle: RePEc:eee:techno:v:132:y:2024:i:c:s0166497224000191
    DOI: 10.1016/j.technovation.2024.102969
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0166497224000191
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.technovation.2024.102969?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.

    References listed on IDEAS

    as
    1. De Silva, Muthu & Howells, Jeremy & Meyer, Martin, 2018. "Innovation intermediaries and collaboration: Knowledge–based practices and internal value creation," Research Policy, Elsevier, vol. 47(1), pages 70-87.
    2. Tat Koon Koh & Muller Y. M. Cheung, 2022. "Seeker Exemplars and Quantitative Ideation Outcomes in Crowdsourcing Contests," Information Systems Research, INFORMS, vol. 33(1), pages 265-284, March.
    3. Cappa, Francesco & Oriani, Raffaele & Pinelli, Michele & De Massis, Alfredo, 2019. "When does crowdsourcing benefit firm stock market performance?," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    4. Shilpi Jain & Swanand J. Deodhar, 2022. "Social mechanisms in crowdsourcing contests: a literature review," Behaviour and Information Technology, Taylor & Francis Journals, vol. 41(5), pages 1080-1114, April.
    5. Douglas P. Hannah & Ron Tidhar & Kathleen M. Eisenhardt, 2021. "Analytic models in strategy, organizations, and management research: A guide for consumers," Strategic Management Journal, Wiley Blackwell, vol. 42(2), pages 329-360, February.
    6. Hong, Lu & Page, Scott E., 2001. "Problem Solving by Heterogeneous Agents," Journal of Economic Theory, Elsevier, vol. 97(1), pages 123-163, March.
    7. 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).
    8. Jie Yan & Renjing Liu & Guangjun Zhang, 2018. "Task Structure, Individual Bounded Rationality and Crowdsourcing Performance: An Agent-Based Simulation Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(4), pages 1-12.
    9. Füller, Johann & Hutter, Katja & Wahl, Julian & Bilgram, Volker & Tekic, Zeljko, 2022. "How AI revolutionizes innovation management – Perceptions and implementation preferences of AI-based innovators," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    10. Lars Bo Jeppesen & Karim R. Lakhani, 2010. "Marginality and Problem-Solving Effectiveness in Broadcast Search," Organization Science, INFORMS, vol. 21(5), pages 1016-1033, October.
    11. Linus Dahlander & Henning Piezunka, 2020. "Why crowdsourcing fails," Journal of Organization Design, Springer;Organizational Design Community, vol. 9(1), pages 1-9, December.
    12. Barbara Aquilani & Tindara Abbate & Anna Codini, 2017. "Overcoming cultural barriers in open innovation processes through intermediaries: a theoretical framework," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 15(3), pages 447-459, August.
    13. Caloffi, Annalisa & Colovic, Ana & Rizzoli, Valentina & Rossi, Federica, 2023. "Innovation intermediaries' types and functions: A computational analysis of the literature," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    14. Herbert A. Simon, 1991. "Bounded Rationality and Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 125-134, February.
    15. Katsagounos, Ilias & Thomakos, Dimitrios D. & Litsiou, Konstantia & Nikolopoulos, Konstantinos, 2021. "Superforecasting reality check: Evidence from a small pool of experts and expedited identification," European Journal of Operational Research, Elsevier, vol. 289(1), pages 107-117.
    16. Anne-Laure Fayard & Emmanouil Gkeredakis & Natalia Levina, 2016. "Framing Innovation Opportunities While Staying Committed to an Organizational Epistemic Stance," Information Systems Research, INFORMS, vol. 27(2), pages 302-323, June.
    17. David P. Brandon & Andrea B. Hollingshead, 2004. "Transactive Memory Systems in Organizations: Matching Tasks, Expertise, and People," Organization Science, INFORMS, vol. 15(6), pages 633-644, December.
    18. Nicholas Berente & Stefan Seidel & Hani Safadi, 2019. "Research Commentary—Data-Driven Computationally Intensive Theory Development," Service Science, INFORMS, vol. 30(1), pages 50-64, March.
    19. Telmo N Santos & José G Dias & Sandro Mendonça, 2023. "University–industry cooperation: a taxonomy of intermediaries," Science and Public Policy, Oxford University Press, vol. 50(3), pages 457-490.
    20. Boons, Mark & Stam, Daan, 2019. "Crowdsourcing for innovation: How related and unrelated perspectives interact to increase creative performance," Research Policy, Elsevier, vol. 48(7), pages 1758-1770.
    21. Clintin P. Davis-Stober & David V. Budescu & Stephen B. Broomell & Jason Dana, 2015. "The Composition of Optimally Wise Crowds," Decision Analysis, INFORMS, vol. 12(3), pages 130-143.
    22. Kathleen R. Conner & C. K. Prahalad, 1996. "A Resource-Based Theory of the Firm: Knowledge Versus Opportunism," Organization Science, INFORMS, vol. 7(5), pages 477-501, October.
    23. Karl E. Weick & Kathleen M. Sutcliffe & David Obstfeld, 2005. "Organizing and the Process of Sensemaking," Organization Science, INFORMS, vol. 16(4), pages 409-421, August.
    24. Gurca, Andrei & Bagherzadeh, Mehdi & Velayati, Rezvan, 2023. "Aligning the crowdsourcing type with the problem attributes to improve solution search efficacy," Technovation, Elsevier, vol. 119(C).
    25. Karan Girotra & Christian Terwiesch & Karl T. Ulrich, 2010. "Idea Generation and the Quality of the Best Idea," Management Science, INFORMS, vol. 56(4), pages 591-605, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mahotra, Arvind & Majchrzak, Ann, 2024. "Digital innovations in crowdsourcing using AI tools," Technovation, Elsevier, vol. 133(C).
    2. 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).
    3. Conroy, Kieran M. & Jacobs, Simon & Liu, Yang, 2023. "The dual knowledge role of open innovation intermediaries: Internal weaving and external filtering for MNE subsidiaries," Technovation, Elsevier, vol. 123(C).
    4. Gurca, Andrei & Bagherzadeh, Mehdi & Velayati, Rezvan, 2023. "Aligning the crowdsourcing type with the problem attributes to improve solution search efficacy," Technovation, Elsevier, vol. 119(C).
    5. Martina Linnenluecke & Andrew Griffiths & Peter Mumby, 2015. "Executives’ engagement with climate science and perceived need for business adaptation to climate change," Climatic Change, Springer, vol. 131(2), pages 321-333, July.
    6. Tongyu Meng & Jamie Newth & Christine Woods, 2022. "Ethical Sensemaking in Impact Investing: Reasons and Motives in the Chinese Renewable Energy Sector," Journal of Business Ethics, Springer, vol. 179(4), pages 1091-1117, September.
    7. Barry L. Bayus, 2013. "Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community," Management Science, INFORMS, vol. 59(1), pages 226-244, June.
    8. Jakob Pohlisch, 2020. "Internal Open Innovation—Lessons Learned from Internal Crowdsourcing at SAP," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    9. Kyle J. Mayer & Deepak Somaya & Ian O. Williamson, 2012. "Firm-Specific, Industry-Specific, and Occupational Human Capital and the Sourcing of Knowledge Work," Organization Science, INFORMS, vol. 23(5), pages 1311-1329, October.
    10. Cricelli, Livio & Mauriello, Roberto & Strazzullo, Serena, 2023. "Preventing open innovation failures: A managerial framework," Technovation, Elsevier, vol. 127(C).
    11. Anne Kokkonen & Pauli Alin, 2015. "Practice-based learning in construction projects: a literature review," Construction Management and Economics, Taylor & Francis Journals, vol. 33(7), pages 513-530, July.
    12. Jacqueline N. Lane & Ina Ganguli & Patrick Gaule & Eva Guinan & Karim R. Lakhani, 2021. "Engineering serendipity: When does knowledge sharing lead to knowledge production?," Strategic Management Journal, Wiley Blackwell, vol. 42(6), pages 1215-1244, June.
    13. Roberts, Deborah L. & Candi, Marina, 2024. "Artificial intelligence and innovation management: Charting the evolving landscape," Technovation, Elsevier, vol. 136(C).
    14. Leckel, Anja & Veilleux, Sophie & Dana, Leo Paul, 2020. "Local Open Innovation: A means for public policy to increase collaboration for innovation in SMEs," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    15. Kathleen Diener & Dirk Luettgens & Frank Thomas Piller, 2019. "Intermediation For Open Innovation: Comparing Direct Versus Delegated Search Strategies Of Innovation Intermediaries," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(04), pages 1-20, June.
    16. Lisa Blix Germundsson & Sören Augustinsson & Alina Lidén, 2020. "Collaboration in the Making—Towards a Practice-Based Approach to University Innovation Intermediary Organisations," Sustainability, MDPI, vol. 12(12), pages 1-14, June.
    17. Josephine Bremer & Martina K. Linnenluecke, 2017. "Determinants of the perceived importance of organisational adaptation to climate change in the Australian energy industry," Australian Journal of Management, Australian School of Business, vol. 42(3), pages 502-521, August.
    18. Vipul Aggarwal & Elina H. Hwang & Yong Tan, 2021. "Learning to Be Creative: A Mutually Exciting Spatiotemporal Point Process Model for Idea Generation in Open Innovation," Information Systems Research, INFORMS, vol. 32(4), pages 1214-1235, December.
    19. Tino T. Herden, 2020. "Explaining the competitive advantage generated from Analytics with the knowledge-based view: the example of Logistics and Supply Chain Management," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 163-214, April.
    20. Gillier, Thomas & Chaffois, Cédric & Belkhouja, Mustapha & Roth, Yannig & Bayus, Barry L., 2018. "The effects of task instructions in crowdsourcing innovative ideas," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 35-44.

    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:techno:v:132:y:2024:i:c:s0166497224000191. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.sciencedirect.com/science/journal/01664972 .

    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.