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Color matching design simulation platform based on collaborative collective intelligence

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Abstract

With the rise of high-speed networks and remote collaboration platforms, it has become a trend for companies to form group collaboration teams based on open innovation, but there is still a lack of research and mechanism design for group collaboration practices. This research attempts to transfer the open innovation group collaboration model to the design team collaboration environment, and investigates the designer's behaviour model, including originality, profitability and output, based on the task of product colour matching design. The modelling method and the colour-matching design simulation platform proposed in this paper provide a real design platform that can be evaluated, enabling the strategic optimisation of combinations of design subjects with multiple behavioural characteristics, and finding a relatively optimal teamwork model by adjusting the team structure, providing a theoretical and practical basis for the personalised design of design team operation models.

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References

  • Axelrod, R., Hamilton, W.D.: The evolution of cooperation. Science 211(4489), 1390–1396 (1981)

    Article  MathSciNet  Google Scholar 

  • Buchanan, J.T., Daellenbach, H.G.: A comparative evaluation of interactive solution methods for multiple objective decision models. Eur. J. Oper. Res. 29(3), 353–359 (2007)

    Article  Google Scholar 

  • Chan, J., Dow, Steven. P., Schunn, C. Conceptual distance matters when building on others' ides in crowd-collaborative innovation platforms. cscw 2014, Blatimore, Maryland, USA, February 15–19. 2014.

  • Chesbrough, H.W.: The era of open innovation. MIT Sloan Manag. Rev. 44(3), 35–41 (2003a)

    Google Scholar 

  • Chesbrough, H.: The logic of open innovation: managing intellectual property. Calif. Manage. Rev. 45(3), 33–58 (2003b)

    Google Scholar 

  • Dellermann, D., Lipusch, N., Ebel, P., et al.: The potential of collective intelligence and crowdsourcing for opportunity creation. Int. J. Entrep. Ventur. 12(2), 183–207 (2020)

    Article  Google Scholar 

  • Galton, F.: Vox populi. Nature 75(5), 450–451 (1907)

    Article  Google Scholar 

  • Gill, Z. User-driven collaborative intelligence: social networks as crowdsourcing ecosystems. CHI 2012, May 5-10, Austin, Texas, USA 2012: 161-170

  • Howe, J.: Crowdsourcing: why the power of the crowd is driving the future of business. Am. J. Health Syst. Pharm. 67(18), 1565–1566 (2010)

    Article  Google Scholar 

  • Iacuzzi, S., Massaro, M., Garlatti, A.: Value creation through collective intelligence: managing intellectual capital. Electron. J. Knowl. Manage. 18(1), 68–79 (2020)

    Google Scholar 

  • Kohn, N.W., Paulus, P.B., Choi, Y.H.: Building on the ideas of others: an examination of the idea combination process. J. Exp. Soc. Psychol. 47(3), 554–561 (2011)

    Article  Google Scholar 

  • Leimeister, J.M.: Collective intelligence. Bus. Inf. Syst. Eng. 2(4), 245–248 (2010)

    Article  Google Scholar 

  • Leydesdorff, L.: Synergy in knowledge-based innovation systems at national and regional levels: the triple-helix model and the fourth industrial. J. Open Innov. Technol. Market Compl. 4(2), 1–13 (2018)

    Article  Google Scholar 

  • Liu, X., Wu, J., Lyu, C., Sun, Y.: Technology development and experimental study on the open group collaborative innovation design. Pack. Eng. 39(22), 111–118 (2018)

    Google Scholar 

  • Malone, T.W., Laubacher, R., Dellarocas, C.: Harnessing crowds: mapping the genome of collective intelligence. MIT Slogan Res. Pap. 2, 1–3 (2009)

    Google Scholar 

  • Malone, T.W., Laubacher, R., Dellarocas, C.: The collective intelligence genome. IEEE Eng. Manage. Rev. 38(3), 38–52 (2010)

    Article  Google Scholar 

  • Mann, R.P., Helbing, D.: Optimal incentives for collective intelligence. Proc. Natl. Acad. Sci. 114(20), 5077–5082 (2017)

    Article  MathSciNet  Google Scholar 

  • Mathieu, J., Maynard, T.M., Rapp, T., et al.: Team effectiveness 1997–2007: a review of recent advancements and a glimpse into the future. J. Manag. 34(3), 410–476 (2008)

    Google Scholar 

  • McAfee, A., Brynjolfsson, E.: Machine, platform, crowd: harnessing our digital future. Norton 2017, 2 (2017)

    Google Scholar 

  • Meslec, N., Aggarwal, I., Curseu, P.L.: The insensitive ruins it all: compositional and compilational influences of social sensitivity on collective intelligence in groups. Front. Psychol. 7(5), 1–7 (2016)

    Google Scholar 

  • Mladenow, A., Bauer, C., Strauss, C.: Social crowd integration in new product development: crowdsourcing communities nourish the open innovation. Glob. J. Flex. Syst. Manag. 15(1), 77–86 (2014)

    Article  Google Scholar 

  • Nowak, M.: Five rules for the evolution of cooperation. Science 314(8), 1560–1563 (2006)

    Article  Google Scholar 

  • Osborn, A.F.: Applied Imagination: Principles and Procedures of Creative Problem-Solving, 3rd edn. Scribner, New York (1963)

    Google Scholar 

  • Poetz, M.K., Schreier, M.: The value of crowdsourcing: can users really compete with professionals in generating new product ideas? J. Prod. Innov. Manag. 29, 245–256 (2012)

    Article  Google Scholar 

  • Riedl, C., Kim, Y.J., Gupta, P., et al.: Quantifying collective intelligence in human groups. Proc. Natl. Acad. Sci. 118(21), e2005737118 (2021)

    Article  Google Scholar 

  • Sun, Y., Liu, X., Wang, W., Ji, S., Shiwei, C., Wu, J.: Experiment on open group collaborative innovation method in product design. Comput. Integr. Manuf. Syst. 21(2), 392–400 (2015)

    Google Scholar 

  • Sun, Y., Liu, X., Zhao, Y.: Asynchronous collaboration in product design teams and its influence to outcome. Comput. Integr. Manuf. Syst. 24(12), 3121–3128 (2018)

    Google Scholar 

  • Surowiecki, J.: The Wisdom of Crowds: Why the Many are Smarter than the Few, pp. 10–20. Little Brown, New York (2004)

    Google Scholar 

  • Woolley, A.W.: Means vs. ends: implications of process and outcome focus for team adaptation and performance. Org. Sci. 20(3), 500–515 (2009)

    Article  Google Scholar 

  • Xu, B., Sun, S.Y., Liu, X., Lu, C., Tao, H., Zhu, Y.: Simulation research for influence of design team structure on asynchronous. Comput. Integr. Manuf. Syst. 26(2), 496–507 (2020)

    Google Scholar 

  • Yu, L., Nikerson, J.V.: Cooks or cobblers? Crowd creativity through combination. In: 2011 SIGCHI conference on human factors in computing systems (CHI 2011), Vancouver, BC, Canada, pp. 1393–1402 (2011)

  • Yu, C., Chai, Y., Liu, Y.: Literature review on collective intelligence: a crowd science perspective. Int. J. Crowd Sci. 2(1), 64–73 (2018)

    Article  Google Scholar 

  • Zhang, H., Xi, Y., Zeng, X.: The research on the effect of network structure and actor learning strategy on organizational performance. J. Manag. Sci. 22(2), 64–72 (2009)

    Google Scholar 

  • Zhou, Y., Sheng, Z., Chen, X.: Research on evolutionary simulation of self-organizing team based on multi-agent. Modern Manag. Sci. 2, 8–11 (2009)

    Google Scholar 

  • Zhou, J., Yin, X., Xu, F.: Simulation of domestic hot water using behavior of college students based on group characteristics. J. Syst. Simul. 31(1), 145–150 (2019)

    Google Scholar 

Download references

Acknowledgements

This research was funded by the Natural Science Foundation of Zhejiang Province of China (LQ20F020023) and the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (19YJA850012).

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Authors and Affiliations

  1. Zhejiang University of Technology, Hangzhou, 310000, China

    Lekai Zhang, Ming Li, Xiaojian Liu, Boqun Xu & Lingyan Zhang

  2. Zhejiang University, Hangzhou, 310000, China

    Lekai Zhang

  3. Zhejiang A&F University, Hangzhou, 310000, China

    Yan Sun

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  1. Lekai Zhang
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  2. Ming Li
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  3. Yan Sun
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  4. Xiaojian Liu
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  6. Lingyan Zhang
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Correspondence to Lekai Zhang.

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Zhang, L., Li, M., Sun, Y. et al. Color matching design simulation platform based on collaborative collective intelligence. CCF Trans. Pervasive Comp. Interact. 4, 61–75 (2022). https://doi.org/10.1007/s42486-022-00088-4

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  • DOI: https://doi.org/10.1007/s42486-022-00088-4

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