IDEAS home Printed from https://ideas.repec.org/a/bcp/journl/v9y2025i14p1-13.html
   My bibliography  Save this article

Motivation and Bidding Intention on Crowdsourcing Platforms: A Study of Malaysian Digital Workers

Author

Listed:
  • Ahmad Syahmi Ahmad Fadzil

    (Faculty of Business and Management, Universiti Teknologi MARA(UiTM), Cawangan Johor,Kampus Segamat,85000 Johor, MALAYSIA)

  • Nor Azairiah Fatimah Othman

    (Faculty of Business and Management, Universiti Teknologi MARA(UiTM), Cawangan Johor,Kampus Segamat,85000 Johor, MALAYSIA)

  • Gouri Apasamy

    (Faculty of Business and Management, Universiti Teknologi MARA(UiTM), Cawangan Johor,Kampus Segamat,85000 Johor, MALAYSIA)

  • Luqmanul Hakim Johari

    (Faculty of Business and Management, Universiti Teknologi MARA(UiTM), Cawangan Johor,Kampus Segamat,85000 Johor, MALAYSIA)

  • Norzanah Mat Nor

    (Arshad Ayub Graduate Business School, Universiti Teknologi MARA (UiTM) Shah Alam)

Abstract

Crowdsourcing has been identified as an emerging industry that can serve as a platform to generate additional income and allow businesses to conduct their operations more innovatively. To ensure the platform’s success, the crowdsourcing system heavily relies on the bidding intention of the crowd’s participation. As a result, it is critical to understand the reasons behind digital workers’ crowdsourcing bid intentions. Nevertheless, much research has been conducted on the motivational factors that influence bid intention in crowdsourcing, either intrinsic or extrinsic factors. Regrettably, past research typically isolates intrinsic and extrinsic motivational factors to determine which factors are more significant and impact participation in crowdsourcing. Therefore, this paper aims to provide insight into the relationship’s significance between intrinsic and extrinsic motivational factors. As a result, this paper explains motivational synergy using the stimulus-organisation-response (S-O-R) model. The stimulus-organisation-response (S-O-R) model explains how hedonic pleasure, an intrinsic motivation, affects external motivations (like money and the game-like aspect) and the intention to bid in crowdsourcing. This model explains how the relationship between internal and external motivations can be combined to have the best influence on bidding intention. The model was tested using partial least squares structural equation modeling (PLS-SEM) analysis by taking an online survey from 129 digital workers who participated in eRezeki, LinkedIn, and Freelancer.com. As hypothesised, hedonic pleasure mediates the relationship between monetary reward and gamification elements with bidding intention, which is significant. Furthermore, monetary reward and gamification elements were found to have a non-significant direct relationship with bid intention. Therefore, this result proves that the synergy between internal and external motivations is important in influencing bid intentions in crowdsourcing.

Suggested Citation

  • Ahmad Syahmi Ahmad Fadzil & Nor Azairiah Fatimah Othman & Gouri Apasamy & Luqmanul Hakim Johari & Norzanah Mat Nor, 2025. "Motivation and Bidding Intention on Crowdsourcing Platforms: A Study of Malaysian Digital Workers," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(14), pages 1-13, January.
  • Handle: RePEc:bcp:journl:v:9:y:2025:i:14:p:1-13
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijriss/Digital-Library/volume-9-issue-14/1-13.pdf
    Download Restriction: no

    File URL: https://rsisinternational.org/journals/ijriss/articles/integrating-the-principles-of-federal-constitution-and-rukun-negara-in-ai-laws-of-malaysia/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mei-Teh Goi & Vigneswari Kalidas & Norzita Yunus, 2018. "Mediating roles of emotion and experience in the stimulus-organism-response framework in higher education institutions," Journal of Marketing for Higher Education, Taylor & Francis Journals, vol. 28(1), pages 90-112, January.
    2. Knutson, Brian & Wimmer, G. Elliott & Kuhnen, Camelia & Winkielman, Piotr, 2008. "Nucleus accumbens activation mediates the influence of reward cues on financial risk-taking," MPRA Paper 8013, University Library of Munich, Germany.
    3. 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.
    4. Tuba Bakici, 2020. "Comparison of crowdsourcing platforms from social-psychological and motivational perspectives," Post-Print hal-02966992, HAL.
    5. Garcia Martinez, Marian, 2017. "Inspiring crowdsourcing communities to create novel solutions: Competition design and the mediating role of trust," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 296-304.
    6. Bakici, Tuba, 2020. "Comparison of crowdsourcing platforms from social-psychological and motivational perspectives," International Journal of Information Management, Elsevier, vol. 54(C).
    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. 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).
    2. Skare, Marinko & Gavurova, Beata & Polishchuk, Volodymyr, 2023. "A decision-making support model for financing start-up projects by venture capital funds on a crowdfunding platform," Journal of Business Research, Elsevier, vol. 158(C).
    3. Tekic, Anja & Alfonzo Pacheco, Diana Vilma, 2024. "Contest design and solvers' engagement behaviour in crowdsourcing: The neo-configurational perspective," Technovation, Elsevier, vol. 132(C).
    4. Christian W. Scheiner & Christian V. Baccarella & John Bessant & Kai-Ingo Voigt, 2018. "Participation Motives, Moral Disengagement, And Unethical Behaviour In Idea Competitions," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(06), pages 1-24, August.
    5. Agus Sugiarto & Cheng-Wen Lee & Andrian Dolfriandra Huruta & Christine Dewi & Abbott Po Shun Chen, 2022. "Predictors of Pro-Environmental Intention and Behavior: A Perspective of Stimulus–Organism–Response Theory," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    6. Salgado, Stéphane & Hemonnet-Goujot, Aurelie & Henard, David H. & de Barnier, Virginie, 2020. "The dynamics of innovation contest experience: An integrated framework from the customer’s perspective," Journal of Business Research, Elsevier, vol. 117(C), pages 29-43.
    7. Cary Frydman & Nicholas Barberis & Colin Camerer & Peter Bossaerts & Antonio Rangel, 2014. "Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility," Journal of Finance, American Finance Association, vol. 69(2), pages 907-946, April.
    8. Guiso, Luigi & Sapienza, Paola & Zingales, Luigi, 2018. "Time varying risk aversion," Journal of Financial Economics, Elsevier, vol. 128(3), pages 403-421.
    9. Morone, Andrea & Nemore, Francesco & Schirone, Dario Antonio, 2018. "Sales impact of servicescape's rational stimuli: A natural experiment," Journal of Retailing and Consumer Services, Elsevier, vol. 45(C), pages 256-262.
    10. N. M. Slanevskaya, 2022. "Public Administration Transformation Based on Research in Social Neurosciences in the Context of Sustainable Development (Part 2)," Administrative Consulting, Russian Presidential Academy of National Economy and Public Administration. North-West Institute of Management., issue 5.
    11. 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).
    12. William J. Bazley & Henrik Cronqvist & Milica Mormann, 2021. "Visual Finance: The Pervasive Effects of Red on Investor Behavior," Management Science, INFORMS, vol. 67(9), pages 5616-5641, September.
    13. Anum Khan & Muhammad Shujaat Mubarik, 2022. "Measuring the role of neurotransmitters in investment decision: A proposed constructs," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 258-274, January.
    14. Hytönen, Kaisa & Baltussen, Guido & van den Assem, Martijn J. & Klucharev, Vasily & Sanfey, Alan G. & Smidts, Ale, 2014. "Path dependence in risky choice: Affective and deliberative processes in brain and behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 566-581.
    15. Yin, Xicheng & Wang, Hongwei & Wang, Wei & Zhu, Kevin, 2020. "Task recommendation in crowdsourcing systems: A bibliometric analysis," Technology in Society, Elsevier, vol. 63(C).
    16. Jahedi, Salar & Deck, Cary & Ariely, Dan, 2017. "Arousal and economic decision making," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 165-189.
    17. Feng, Yuanyue & Yi, Zihui & Yang, Congcong & Chen, Ruoyi & Feng, Ye, 2022. "How do gamification mechanics drive solvers’ Knowledge contribution? A study of collaborative knowledge crowdsourcing," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    18. Berrada, Tony & Detemple, Jérôme & Rindisbacher, Marcel, 2018. "Asset pricing with beliefs-dependent risk aversion and learning," Journal of Financial Economics, Elsevier, vol. 128(3), pages 504-534.
    19. Reimann, Martin & Bechara, Antoine, 2010. "The somatic marker framework as a neurological theory of decision-making: Review, conceptual comparisons, and future neuroeconomics research," Journal of Economic Psychology, Elsevier, vol. 31(5), pages 767-776, October.
    20. George I. Christopoulos & Xiao-Xiao Liu & Ying-yi Hong, 2017. "Toward an Understanding of Dynamic Moral Decision Making: Model-Free and Model-Based Learning," Journal of Business Ethics, Springer, vol. 144(4), pages 699-715, September.

    More about this item

    Statistics

    Access and download statistics

    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:bcp:journl:v:9:y:2025:i:14:p:1-13. 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: Dr. Pawan Verma (email available below). General contact details of provider: https://rsisinternational.org/journals/ijriss/ .

    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.