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Open Access

Empirical Evidence of Idea Generation in Open Innovation Community

Zhengfa Yang1Qian Liu2( )Xin Zhao3Yang Zhao2
School of Information, Central University of Finance and Economics, Beijing 100081, China
China Center for Internet Economy Research, Central University of Finance and Economics, Beijing 100081, China
School of Economics and Management, Xi’an University of Technology, Xi’an 710048, China
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Abstract

Organizations need to develop effective engagement strategies to engage individuals to contribute and sustain their involvement with innovative ideas. We investigate how feedback can encourage and promote more ideas by considering the source and valence of in-process feedback, user characteristics, and the moderating effect of the aforementioned variables. Our model is tested using a panel linear model and data from the MIUI Forum. We discovered that individuals who received unfavorable peer evaluation reduced subsequent idea generation, with the effect lessening as ideators gained success experience. Whereas receiving positive peer feedback cannot stimulate users’ ideation. Experienced contributors are more motivated (less demotivated) to come up with ideas after receiving positive feedback (negative feedback) from firms. We complement extant research related to feedback by investigating its synergetic effects on ideation and exploring which feedback is more important and their boundary conditions.

References

[1]

M. Modaresnezhad, L. Iyer, P. Palvia, and V. Taras, Information technology (IT) enabled crowdsourcing: A conceptual framework, Information Processing & Management, vol. 57, no. 2, p. 102135, 2020.

[2]

P. M. D. Gangi and M. Wasko, Steal my idea! Organizational adoption of user innovations from a user innovation community: A case study of dell ideastorm, Decision Support Systems, vol. 48, no. 1, pp. 303–312, 2009.

[3]

Y. Liu and J. Feng, Does money talk? The impact of monetary incentives on user-generated content contributions, Information Systems Research, vol. 32, no. 2, pp. 394–409, 2021.

[4]

J. West and M. Bogers, Leveraging external sources of innovation: A review of research on open innovation, Journal of Product Innovation Management, vol. 31, no. 4, pp. 814–831, 2014.

[5]

J. Yan, D. E. Leidner, and H. Benbya, Differential innovativeness outcomes of user and employee participation in an online user innovation community, Journal of Management Information Systems, vol. 35, no. 3, pp. 900–933, 2018.

[6]

M. Qin and S. Liang, User recognition mechanism and user contribution behavior in enterprise-hosted online product innovation communities: Based on prosocial behavior theory, Nankai Business Review International, vol. 10, no. 1, pp. 17–41, 2019.

[7]

L. B. Jeppesen and L. Frederiksen, Why do users contribute to firm-hosted user communities? The case of computer-controlled music instruments, Organization Science, vol. 17, no. 1, pp. 45–63, 2006.

[8]

N. Luo, Y. Wang, C. Jin, Y. Ni, and M. Zhang, Effects of socialization interactions on customer engagement in online travel communities, Internet Research, vol. 29, no. 6, pp. 1509–1525, 2019.

[9]

K. W. Chan, S. Y. Li, and J. J. Zhu, Fostering customer ideation in crowdsourcing community: The role of peer-to-peer and peer-to-firm interactions, Journal of Interactive Marketing, vol. 31, no. 3, pp. 42–62, 2015.

[10]

K. W. Chan, S. Y. Li, J. Ni, and J. J. Zhu, What feedback matters? The role of experience in motivating crowdsourcing innovation, Production and Operations Management, vol. 30, no. 1, pp. 103–126, 2021.

[11]

J. Liao, J. Chen, and J. Mou, Examining the antecedents of idea contribution in online innovation communities: A perspective of creative self-efficacy, Technology in Society, vol. 66, p. 101644, 2021.

[12]

S. Stieglitz and L. Dang-Xuan, Emotions and information diffusion in social media—Sentiment of microblogs and sharing behavior, Journal of Management Information Systems, vol. 29, no. 4, pp. 217–248, 2013.

[13]

R. Hofstetter, J. Z. Zhang, and A. Herrmann, Successive open innovation contests and incentives: Winner-take-all or multiple prizes, Journal of Product Innovation Management, vol. 35, no. 4, pp. 492–517, 2018.

[14]

B. L. Bayus, Crowdsourcing new product ideas over time: An analysis of the dell ideastorm community, Management Science, vol. 59, no. 1, pp. 226–244, 2013.

[15]

J. Zhou, Feedback valence, feedback style, task autonomy, and achievement orientation: Interactive effects on creative performance, Journal of Applied Psychology, vol. 83, no. 2, pp. 261–276, 1998.

[16]

T. S. Sindlinger, Crowdsourcing: Why the power of the crowd is driving the future of business, American Journal of Health-System Pharmacy, vol. 67, no. 18, pp. 1565–1566, 2010.

[17]

D. C. Brabham, Crowdsourcing the public participation process for planning projects, Planning Theory, vol. 8, no. 3, pp. 242–262, 2009.

[18]

J. O. Wooten and K. T. Ulrich, Idea generation and the role of feedback: Evidence from field experiments with innovation tournaments, Production and Operations Management, vol. 26, no. 1, pp. 80–99, 2017.

[19]

D. V. Dijk and A. N. Kluger, Feedback sign effect on motivation: Is it moderated by regulatory focus, Applied Psychology, vol. 53, no. 1, pp. 113–135, 2004.

[20]

J. Jin, Y. Li, X. Zhong, and L. Zhai, Why users contribute knowledge to online communities? An empirical study of an online social Q&A community, Information & Management, vol. 52, no. 7, pp. 840–849, 2015.

[21]

Q. Liu, Q. Du, Y. Hong, W. Fan, and S. Wu, User idea implementation in open innovation communities: Evidence from a new product development crowdsourcing community, Information Systems Journal, vol. 30, no. 5, pp. 899–927, 2020.

[22]

R. Mehta, D. W. Dahl, and R. J. Zhu, Social-recognition versus financial incentives? Exploring the effects of creativity-contingent external rewards on creative performance, Journal of Consumer Research, vol. 44, no. 3, pp. 536–553, 2017.

[23]

R. B. L. Sijbom, F. Anseel, M. Crommelinck, and A. D. Beuckelaer, Why seeking feedback from diverse sources may not be sufficient for stimulating creativity: The role of performance dynamism and creative time pressure, Journal of Organizational Behavior, vol. 39, no. 3, pp. 355–368, 2017.

[24]

L. Chen, J. R. Marsden, and Z. Zhang, Theory and analysis of company-sponsored value co-creation, Journal of Management Information Systems, vol. 29, no. 2, pp. 141–172, 2012.

[25]

N. Camacho, H. Nam, P. Kannan, and S. Stremersch, Tournaments to crowdsource innovation: The role of moderator feedback and participation intensity, Journal of Marketing, vol. 83, no. 2, pp. 138–157, 2019.

[26]

L. J. Kornish and J. Hutchison-Krupat, Research on idea generation and selection: Implications for management of technology, Production and Operations Management, vol. 26, no. 4, pp. 633–651, 2017.

[27]

D. D. Keum and K. E. See, The influence of hierarchy on idea generation and selection in the innovation process, Organization Science, vol. 28, no. 4, pp. 597–780, 2017.

[28]
A. Bandura and R. H. Walters, Social Learning Theory. Englewood Cliffs, NJ, USA: Prentice-Hall, 1977.
[29]

C. E. Porter and N. Donthu, Cultivating trust and harvesting value in virtual communities, Management Science, vol. 54, no. 1, pp. 113–128, 2008.

[30]

J. Liao, M. Huang, and B. Xiao, Promoting continual member participation in firm-hosted online brand communities: An organizational socialization approach, Journal of Business Research, vol. 71, pp. 92–101, 2017.

International Journal of Crowd Science
Pages 40-45
Cite this article:
Yang Z, Liu Q, Zhao X, et al. Empirical Evidence of Idea Generation in Open Innovation Community. International Journal of Crowd Science, 2023, 7(1): 40-45. https://doi.org/10.26599/IJCS.2022.9100030

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Received: 10 April 2022
Revised: 30 September 2022
Accepted: 04 October 2022
Published: 31 March 2023
© The author(s) 2023

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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