Research article Special Issues

Study on the influence diffusion of SMEs in open-source communities from the perspective of complex networks


  • Received: 29 December 2022 Revised: 25 April 2023 Accepted: 07 May 2023 Published: 31 May 2023
  • In the era of digital economy, enterprise research and development (R&D) tends to be open-source. Due to their limited resources, small and medium-sized enterprises (SMEs) can join open-source platforms to get additional creative resources and technical support. In this context, from the perspective of complex networks, the influence diffusion of SMEs after embedding open-source innovation networks is studied in this paper. First, an integrated simulation model including a network model, agent model and innovative diffusion model is constructed. Second, the influence diffusion strategy is proposed considering initial impact, embedding timing and connection mode (same-match and heterogeneous) of the enterprise. Third, the dynamic simulation of the influence diffusion process of SMEs demonstrates that embedding timing has a significant impact. There is no significant difference in the influence diffusion at the early and mature stages in the evolution process of open-source innovation networks. The initial impact of enterprises has a significant influence on the diffusion during the developing period, but the effect on its influence diffusion at the initial and mature stages is not obvious. Finally, in light of experiment results, it is clear that the open-source platform plays an important role on the growth of SMEs as evidenced by the close correlation between the spread of SMEs' influence within the open-source innovation network and the community's stage of development.

    Citation: Yingzi Li, Mingxuan Yang, Shuo Zhang. Study on the influence diffusion of SMEs in open-source communities from the perspective of complex networks[J]. Mathematical Biosciences and Engineering, 2023, 20(7): 12731-12749. doi: 10.3934/mbe.2023568

    Related Papers:

  • In the era of digital economy, enterprise research and development (R&D) tends to be open-source. Due to their limited resources, small and medium-sized enterprises (SMEs) can join open-source platforms to get additional creative resources and technical support. In this context, from the perspective of complex networks, the influence diffusion of SMEs after embedding open-source innovation networks is studied in this paper. First, an integrated simulation model including a network model, agent model and innovative diffusion model is constructed. Second, the influence diffusion strategy is proposed considering initial impact, embedding timing and connection mode (same-match and heterogeneous) of the enterprise. Third, the dynamic simulation of the influence diffusion process of SMEs demonstrates that embedding timing has a significant impact. There is no significant difference in the influence diffusion at the early and mature stages in the evolution process of open-source innovation networks. The initial impact of enterprises has a significant influence on the diffusion during the developing period, but the effect on its influence diffusion at the initial and mature stages is not obvious. Finally, in light of experiment results, it is clear that the open-source platform plays an important role on the growth of SMEs as evidenced by the close correlation between the spread of SMEs' influence within the open-source innovation network and the community's stage of development.



    加载中


    [1] Y. Qi, X. Xiao, Transformation of enterprise management in the era of digital economy, Manage. World, 6 (2020), 135–152.
    [2] K. Crowston, K. Wei, J. Howison, A. Wiggins, Free/libre open source software development: What we know and what we do not know, ACM Comput. Surv., 44 (2012), 1–35. https://doi.org/10.1145/2089125.2089127 doi: 10.1145/2089125.2089127
    [3] C. Terwiesch, Y. Xu, Innovation contests, open innovation, and multiagent problem solving, Manage. Sci., 54 (2008), 1529–1543. https://doi.org/10.1287/mnsc.1080.0884 doi: 10.1287/mnsc.1080.0884
    [4] G. Von Krogh, T. Netland, M. Worter, Winning with open process innovation, MIT Sloan Manage. Rev., 59 (2017), 53–56.
    [5] L. Dahlander, M. Magnusson, How do firms make use of open source communities?, Long Range Plann., 41 (2009), 629–649. https://doi.org/10.1016/j.lrp.2008.09.003 doi: 10.1016/j.lrp.2008.09.003
    [6] M. Schaarschmidt, G. Walsh, H. F. O. V. Kortzfleisch, How do firms influence open source software communities? A framework and empirical analysis of different governance modes, Inf. Organ., 25 (2015), 99–114. https://doi.org/10.1016/j.infoandorg.2015.03.001 doi: 10.1016/j.infoandorg.2015.03.001
    [7] Y. H. Shuk, A. Rai, Continued voluntary participation intention in firm-participating open source software projects, Inf. Syst. Res., 28 (2017), 603–625. https://doi.org/10.1287/isre.2016.0687 doi: 10.1287/isre.2016.0687
    [8] C. Freeman, Networks of innovators: A synthesis of research issues, Res. Policy, 20 (1991), 499–514. https://doi.org/10.1016/0048-7333(91)90072-X doi: 10.1016/0048-7333(91)90072-X
    [9] R. Tang, X. S. Chen, C. C. Wei, Q. Li, W. Wang, H. Wang, et al., Interlayer link prediction based on multiple network structural attributes, Comput. Networks, 203 (2022), 108651. https://doi.org/10.1016/j.comnet.2021.108651 doi: 10.1016/j.comnet.2021.108651
    [10] C. Huang, Y. Wang, Evolution of network relations, enterprise learning, and cluster innovation networks: The case of the Yuyao plastics industry cluster, Technol. Anal. Strategic Manage., 30 (2018), 158–171. https://doi.org/10.1080/09537325.2017.1297786 doi: 10.1080/09537325.2017.1297786
    [11] S. X. Wang, L. Yang, Spatial competition, strategic R&D and the structure of innovation networks, J. Bus. Res., 139 (2022), 13–31. https://doi.org/10.1016/j.jbusres.2021.09.037 doi: 10.1016/j.jbusres.2021.09.037
    [12] M. G. A. Rojas, E. R. R. Solis, J. J. Zhu, Innovation and network multiplexity: R&D and the concurrent effects of two collaboration networks in an emerging economy, Res. Policy, 47 (2018), 1111–1124. https://doi.org/10.1016/j.respol.2018.03.018 doi: 10.1016/j.respol.2018.03.018
    [13] J. Zhang, H. Jiang, R. Wu, J. Li, Reconciling the dilemma of knowledge sharing: A network pluralism framework of firms' R&D alliance network and innovation performance, J. Manage., 45 (2019), 2635–2665. https://doi.org/10.1177/0149206318761575 doi: 10.1177/0149206318761575
    [14] R. Y. Lu, Y. Zhou, Y. W. Ding, Enterprise innovation network: Tracing, evolution and research prospect, Manage. World, 1 (2021), 217–233. https://doi.org/10.19744/j.cnki.11-1235/f.2021.0014 doi: 10.19744/j.cnki.11-1235/f.2021.0014
    [15] T. R. Eikebrokk, N. F. Garmann-Johnsen, D. H. Olsen, Co-creation in networks of SMEs: A conceptual model of the co-creation process, Proc. Comput. Sci., 181 (2021), 360–366. https://doi.org/10.1016/j.procs.2021.01.179 doi: 10.1016/j.procs.2021.01.179
    [16] F. G. Albert, E. Pizzurno, Oops, I did it again! Knowledge leaks in open innovation networks with start-ups, Eur. J. Innovation Manage., 20 (2017), 50–79. https://doi.org/10.1108/ejim-11-2015-0116 doi: 10.1108/ejim-11-2015-0116
    [17] A. Spithoven, W. Vanhaverbeke, N. Rojiakkers, Open innovation practices in SMEs and large enterprises, Small Bus. Econ., 41 (2013), 537–552. https://doi.org/10.1007/s11187-012-9453-9 doi: 10.1007/s11187-012-9453-9
    [18] Z. Y. Xie, J. Wang, Influence of open innovation on enterprises' R&D efficiency: An empirical study based on the panel data from high-tech industries, Sci. Res. Manage., 41 (2020), 22–32.
    [19] M. L. Xie, D. S. Liu, Developmental performance appraisal and technological SMEs' open innovation: A moderated mediating effect model, Manag. Rev., 33 (2021), 142–152.
    [20] W. R. Chen, J. X. Wang, Platform-dependent upgrade: Digital transformation strategy of complementors in platform-based ecosystem, Manage. World, 10 (2021), 195–213.
    [21] L. Benhayoun, M. Dain, C. Dominguez-Péry, A. C. Lyons, SMEs embedded in collaborative innovation networks: How to measure their absorptive capacity?, Technol. Forecast. Soc. Change, 159 (2020), 120196. https://doi.org/10.1016/j.techfore.2020.120196 doi: 10.1016/j.techfore.2020.120196
    [22] M. Granovetter, Economic action and social structure: The problem of embeddedness, Am. J. Sociol., 91 (1985), 481–510. https://doi.org/10.1086/228311 doi: 10.1086/228311
    [23] B. R. Koka, J. E, Prescott, Designing alliance networks: the influence of network position, environmental change, and strategy on firm performance, Strategic Manage. J., 29 (2008), 639–661. https://doi.org/10.1002/smj.679 doi: 10.1002/smj.679
    [24] Y. Lyu, Q. Liu, B. He, J. Nie, Structural embeddedness and innovation diffusion: the moderating role of industrial technology grouping, Scientometrics, 111 (2017), 1–28. https://doi.org/10.1007/s11192-017-2320-3 doi: 10.1007/s11192-017-2320-3
    [25] S. Han, Y. Lyu, R. Ji, Y. Zhu, J. Su, L. Bao, Open innovation, network embeddedness and incremental innovation capability, Manage. Decis., 58 (2020), 2655–2680. https://doi.org/10.1108/MD-08-2019-1038 doi: 10.1108/MD-08-2019-1038
    [26] Y. Lyu, Y. Zhu, S. Han, B. He, L. Bao, Open innovation and innovation radicalness—the moderating effect of network embeddedness, Technol. Soc., 62 (2020), 101292. https://doi.org/10.1016/j.techsoc.2020.101292 doi: 10.1016/j.techsoc.2020.101292
    [27] X. M. Xie, H. W. Wang, The impact mechanism of network embeddedness on firm innovation performance: A moderated mediation model based on non-R&D innovation, J. Manage. Eng., 34 (2020), 13–28. https://doi.org/10.13587/j.cnki.jieem.2020.06.002 doi: 10.13587/j.cnki.jieem.2020.06.002
    [28] E. Mazzola, G. Perrone, D. S. Kamuriwo, Network embeddedness and new product development in the biopharmaceutical industry: The moderating role of open innovation flow, Int. J. Prod. Econ., 160 (2015), 106–119. https://doi.org/10.1016/j.ijpe.2014.10.002 doi: 10.1016/j.ijpe.2014.10.002
    [29] C. Dogbe, H. Tian, W. Pomegbe, S. A. Sarsah, C. O. A. Otoo, Effect of network embeddedness on innovation performance of small and medium-sized enterprises: The moderating role of innovation openness, J. Strategy Manage., 13 (2020), 181–197. https://doi.org/10.1108/JSMA-07-2019-0126 doi: 10.1108/JSMA-07-2019-0126
    [30] L. Liang, A. Alam, G. Sorwar, H. Yazdifar, R. Eskandari, The combined network effect of sparse and interlocked connections in SMEs' innovation, Technol. Forecast. Soc. Change, 163 (2020), 120488. https://doi.org/10.1016/j.techfore.2020.120488 doi: 10.1016/j.techfore.2020.120488
    [31] H. M. Xie, Y. Zhang, C. Cong, C. Ying, The impact of network embedding on technical innovative performance based on the perspective of learning capability, Sci. Res. Manage., 35 (2014), 1–7. https://doi.org/10.19571/j.cnki.1000-2995.2014.12.001 doi: 10.19571/j.cnki.1000-2995.2014.12.001
    [32] Z. H. Sheng, Management: From systematism to complexity, J. Manage. Sci. China, 22 (2019), 2–14.
    [33] J. Tan, H. J. Zhang, R. H. Lin, Modeling and analyzing the evolution mechanism of industrial innovation network, J. Manage. Sci. China, 22 (2019), 1–13.
    [34] E. Kiesling, M. Günther, C. Stummer, L. M, Wakolbinger, Agent-based simulation of innovation diffusion: A review, Central Eur. J. Oper. Res., 20 (2012), 183–230. https://doi.org/10.1007/s10100-011-0210-y doi: 10.1007/s10100-011-0210-y
    [35] J. S. Lin, C. OuYang, Y. C. Juan, Towards a standardized framework for a multi-agent system approach for cooperation in an original design manufacturing company, Int. J. Comput. Integr. Manuf., 22 (2009), 494–514. https://doi.org/10.1080/09511920802537987 doi: 10.1080/09511920802537987
    [36] R. Li, L. Dong, J. Zhang, X. Wang, W. X. Wang, Z. Di, et al., Simple spatial scaling rules behind complex cities, Nat. Commun., 8 (2017), 1841. https://doi.org/10.1038/s41467-017-01882-w doi: 10.1038/s41467-017-01882-w
    [37] F. Shang, B. Chen, P. Expert, L. Lü, A. Yang, H. E. Stanley, et al., Local dominance unveils clusters in networks, preprint, arXiv: 2209.15497. https://doi.org/10.48550/arXiv.2209.1549
    [38] M. Niazi, A. Hussain, Agent-based computing from multi-agent systems to agent-based models: A visual survey, Scientometrics, 89 (2011), 479–499. https://doi.org/10.1007/s11192-011-0468-9 doi: 10.1007/s11192-011-0468-9
    [39] W. Q. Huang, S. Yao, X. T. Zhuang, The agent-based simulation of innovation diffusion based on complex social networks, Stud. Sci. Sci., 31 (2013), 310–320. https://doi.org/10.3969/j.issn.1003-2053.2013.02.018 doi: 10.3969/j.issn.1003-2053.2013.02.018
    [40] X. Wang, B. Li, S. Yin, J. Zeng, Formation mechanism for integrated innovation network among strategic emerging industries: Analytical and simulation approaches, Comput. Ind. Eng., 162 (2021), 107705. https://doi.org/10.1016/j.cie.2021.107705 doi: 10.1016/j.cie.2021.107705
    [41] H. L. Zhou, X. D. Zhang, Dynamic robustness of knowledge collaboration network of open source product development community, Phys. A, 490 (2018), 601–612. https://doi.org/10.1016/j.physa.2017.08.092 doi: 10.1016/j.physa.2017.08.092
    [42] J. H. Panchal, Agent-based modeling of mass-collaborative product development processes, J. Comput. Inf. Sci. Eng., 9 (2009), 296–297. https://doi.org/10.1115/1.3184605 doi: 10.1115/1.3184605
    [43] Y. W. Seo, S. W. Chae, Market dynamics and innovation management on performance in SMEs: Multi-agent simulation approach, Proc. Comput. Sci., 91 (2016), 707–714. https://doi.org/10.1016/j.procs.2016.07.060 doi: 10.1016/j.procs.2016.07.060
    [44] S. Zhang, Y. Z. Li, Modeling and simulation study of two-phase collaborative behaviors oriented to open source design process, Math. Prob. Eng., 8 (2018), 1–15. https://doi.org/10.1155/2018/9347109 doi: 10.1155/2018/9347109
    [45] A. L. Barabasi, R. Albert, Emergence of scaling in random networks, Science, 286 (1999), 509–512. https://doi.org/10.1126/science.286.5439.509 doi: 10.1126/science.286.5439.509
    [46] X. M. Ye, Research on the role and mechanism of the platform economy to promote the innovation of small and medium enterprises, Sci. Manage. Res., 36 (2018), 62–66. https://doi.org/10.19445/j.cnki.15-1103/g3.2018.02.017 doi: 10.19445/j.cnki.15-1103/g3.2018.02.017
    [47] K. Kapoor, A. Z. Bigdeli, Y. K. Dwivedi, A. Schroeder, A. Beltagui, T. Baines, A socio-technical view of platform ecosystems: Systematic review and research agenda, J. Bus. Res., 128 (2021), 94–108. https://doi.org/10.1016/j.jbusres.2021.01.060 doi: 10.1016/j.jbusres.2021.01.060
    [48] G. Parker, V. Alstyne, Innovation, openness, and platform control, Manage. Sci., 64 (2018), 3015–3032. https://doi.org/10.1287/mnsc.2017.2757 doi: 10.1287/mnsc.2017.2757
    [49] D. Cutolo, M. Kenney, Platform-dependent entrepreneurs: Power asymmetries, risks, and strategies in the platform economy, Acad. Manage. Perspectives, 35 (2021), 584–605. https://doi.org/10.5465/amp.2019.0103 doi: 10.5465/amp.2019.0103
    [50] A. Lomi, E. R. Larsen, Dynamics of organizations: Computational Modeling and Organization Theories, MIT Press, 2001. https://doi.org/10.2307/3556626
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1403) PDF downloads(64) Cited by(0)

Article outline

Figures and Tables

Figures(5)  /  Tables(5)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog