Research article Special Issues

A novel evolution model to investigate the collaborative innovation mechanism of green intelligent building materials enterprises for construction 5.0

  • Received: 09 September 2022 Revised: 18 December 2022 Accepted: 26 December 2022 Published: 31 January 2023
  • MSC : 90B70, 91A80

  • Green intelligent building materials is an effective way for building materials industry to reduce carbon. However, a small amount of research and development (R&D, unstable R&D investment and imperfect collaborative innovation mode hinder the development of green intelligent building materials industry. However, few scholars study the development mechanism of green intelligent building materials industry from the perspective of industrial chain considering the above obstacles. In this study, the game models under market mechanism and government regulation were constructed to analyze the income distribution mechanism for the development mechanism of green intelligent building materials industry. Finally, the questionnaire method was used to discuss the game strategy of collaborative innovation behavior among agents. The results are as follows. In the game strategy selection of collaborative innovation behavior among green intelligent building materials, factors such as database marketing maturity, information flow and technology volume generated by collaborative innovation, technical benefit coefficient, social benefit coefficient and profit and loss barrier factors are conducive to the collaborative innovation behavior of green intelligent building materials. When the market mechanism fails, the incentive effect of cost subsidy adopted by the government is more efficient and fast, and the driving force of achievement reward is more lasting. The combination of the two incentives is the best. Moderate supervision and punishment lower than the free rider income can not ensure fair competition among green intelligent building materials enterprises. The punishment above the threshold can effectively restrain the negative impact of free rider income and prospect profit and loss. This study not only theoretically expands the development theory of digital industry from the perspective of industrial chain by considering the maturity factor of database, but also provides policy guidance for the development of green intelligent building materials industry in practice.

    Citation: Chengli Hu, Ping Liu, Hongtao Yang, Shi Yin, Kifayat Ullah. A novel evolution model to investigate the collaborative innovation mechanism of green intelligent building materials enterprises for construction 5.0[J]. AIMS Mathematics, 2023, 8(4): 8117-8143. doi: 10.3934/math.2023410

    Related Papers:

  • Green intelligent building materials is an effective way for building materials industry to reduce carbon. However, a small amount of research and development (R&D, unstable R&D investment and imperfect collaborative innovation mode hinder the development of green intelligent building materials industry. However, few scholars study the development mechanism of green intelligent building materials industry from the perspective of industrial chain considering the above obstacles. In this study, the game models under market mechanism and government regulation were constructed to analyze the income distribution mechanism for the development mechanism of green intelligent building materials industry. Finally, the questionnaire method was used to discuss the game strategy of collaborative innovation behavior among agents. The results are as follows. In the game strategy selection of collaborative innovation behavior among green intelligent building materials, factors such as database marketing maturity, information flow and technology volume generated by collaborative innovation, technical benefit coefficient, social benefit coefficient and profit and loss barrier factors are conducive to the collaborative innovation behavior of green intelligent building materials. When the market mechanism fails, the incentive effect of cost subsidy adopted by the government is more efficient and fast, and the driving force of achievement reward is more lasting. The combination of the two incentives is the best. Moderate supervision and punishment lower than the free rider income can not ensure fair competition among green intelligent building materials enterprises. The punishment above the threshold can effectively restrain the negative impact of free rider income and prospect profit and loss. This study not only theoretically expands the development theory of digital industry from the perspective of industrial chain by considering the maturity factor of database, but also provides policy guidance for the development of green intelligent building materials industry in practice.



    加载中


    [1] C. Debrah, A. P. C. Chan, A. Darko, Artificial intelligence in green building, Autom. Constr., 137 (2022), 104192. https://doi.org/10.1016/j.autcon.2022.104192 doi: 10.1016/j.autcon.2022.104192
    [2] X. Q. Liu, C. A. Wang, X. M. Zhang, L. Gao, J. N. Zhu, Financing constraints change of China's green industries, AIMS Mathematics, 7 (2022), 20873–20890. https://doi.org/10.3934/math.20221144 doi: 10.3934/math.20221144
    [3] Y. Su, H. Y. Cheng, Z. Wang, L. W. Wang, Impacts of the COVID-19 lockdown on building energy consumption and indoor environment: A case study in Dalian, China, Energ. Buildings, 263 (2022), 112055. https://doi.org/10.1016/j.enbuild.2022.112055 doi: 10.1016/j.enbuild.2022.112055
    [4] X. C. Zeng, S. C. Li, S. Yin, Z. Y. Xing, How does the government promote the collaborative innovation of green building projects? An evolutionary game perspective, Buildings, 12 (2022), 1179. https://doi.org/10.3390/buildings12081179 doi: 10.3390/buildings12081179
    [5] P. F. Pereira, N. M. Ramos, M. L. Simões, Data-driven occupant actions prediction to achieve an intelligent building, Build. Res. Inf., 48 (2020), 485–500. https://doi.org/10.1080/09613218.2019.1692648 doi: 10.1080/09613218.2019.1692648
    [6] C. X. Jia, H. Y. Ding, C. J. Zhang, X. Zhang, Design of a dynamic key management plan for intelligent building energy management system based on wireless sensor network and blockchain technology, Alex. Eng. J., 60 (2021), 337–346. https://doi.org/10.1016/j.aej.2020.08.019 doi: 10.1016/j.aej.2020.08.019
    [7] T. D. Shao, Indoor environment intelligent control system of green building based on PMV index, Adv. Civ. Eng., 2021 (2021), 6619401. https://doi.org/10.1155/2021/6619401 doi: 10.1155/2021/6619401
    [8] S. Yin, B. Z. Li, Z. Y. Xing, The governance mechanism of the building material industry (BMI) in transformation to green BMI: The perspective of green building, Sci. Total Environ., 677 (2019), 19–33. https://doi.org/10.1016/j.scitotenv.2019.04.317 doi: 10.1016/j.scitotenv.2019.04.317
    [9] J. Lu, K. Wang, M. L. Qu, Experimental determination on the capillary water absorption coefficient of porous building materials: A comparison between the intermittent and continuous absorption tests, J. Build. Eng., 28 (2020), 101091. https://doi.org/10.1016/j.jobe.2019.101091 doi: 10.1016/j.jobe.2019.101091
    [10] S. Yin, N. Zhang, H. M. Dong, Preventing COVID-19 from the perspective of industrial information integration: Evaluation and continuous improvement of information networks for sustainable epidemic prevention, J. Ind. Inf. Integr., 19 (2020), 100157. https://doi.org/10.1016/j.jii.2020.100157 doi: 10.1016/j.jii.2020.100157
    [11] S. Yin, N. Zhang, K. Ullah, S. Gao, Enhancing digital innovation for the sustainable transformation of manufacturing industry: A pressure-state-response system framework to perceptions of digital green innovation and its performance for green and intelligent manufacturing, Systems, 10 (2022), 72. https://doi.org/10.3390/systems10030072 doi: 10.3390/systems10030072
    [12] M. A. Omer, T. Noguchi, A conceptual framework for understanding the contribution of building materials in the achievement of Sustainable Development Goals (SDGs), Sustain. Cities Soc., 52 (2020), 101869. https://doi.org/10.1016/j.scs.2019.101869 doi: 10.1016/j.scs.2019.101869
    [13] T. Dong, S. Yin, N. Zhang, New energy-driven construction industry: Digital green innovation investment project selection of photovoltaic building materials enterprises using an integrated fuzzy decision approach, Syst., 11 (2023), 11. https://doi.org/10.3390/systems11010011 doi: 10.3390/systems11010011
    [14] F. J. Kong, L. H. He, Impacts of supply-sided and demand-sided policies on innovation in green building technologies: A case study of China, J. Clean. Prod., 294 (2021), 126279. https://doi.org/10.1016/j.jclepro.2021.126279 doi: 10.1016/j.jclepro.2021.126279
    [15] A. K. Kan, N. Zheng, W. B. Zhu, D. Cao, W. Wang, Innovation and development of vacuum insulation panels in China: A state-of-the-art review, J. Build. Eng., 48 (2021), 103937. https://doi.org/10.1016/j.jobe.2021.103937 doi: 10.1016/j.jobe.2021.103937
    [16] W. A. Medeiros, M. de Oliveira Soriani, G. A. Parsekian, Innovation in flat-jack application to evaluate modern high-strength hollow concrete block masonry, Constr. Build. Mater., 255 (2020), 119341. https://doi.org/10.1016/j.conbuildmat.2020.119341 doi: 10.1016/j.conbuildmat.2020.119341
    [17] Y. F. Jiang, W. Y. Zheng, Coupling mechanism of green building industry innovation ecosystem based on blockchain smart city, J. Clean. Prod., 307 (2021), 126766. https://doi.org/10.1016/j.jclepro.2021.126766 doi: 10.1016/j.jclepro.2021.126766
    [18] R. D. Lumpkin, T. W. Horton, V. J. Sinfield, Holistic synergy analysis for building subsystem performance and innovation opportunities, Build. Environ., 178 (2020), 106908. https://doi.org/10.1016/j.buildenv.2020.106908 doi: 10.1016/j.buildenv.2020.106908
    [19] B. Lv, X. G. Qi, Research on partner combination selection of the supply chain collaborative product innovation based on product innovative resources, Comput. Ind. Eng., 128 (2019), 245–253. https://doi.org/10.1016/j.cie.2018.12.041 doi: 10.1016/j.cie.2018.12.041
    [20] H. Y. Guo, C. J. Fan, J. C. Li, L. Wang, H. C. Wu, Y. P. Yang, Study on co-evolution of e-commerce industry and big data industry considering internal and external factors, Oper. Res. Manag., 28 (2019), 191–199. http://www.jorms.net/EN/10.12005/orms.2019.0072
    [21] R. K. P. Maddikunta, V. Q. Pham, B. Prabadevi, N. Deepa, K. Dev, R. T. Gadekallu, et al., Industry 5.0: A survey on enabling technologies and potential applications, J. Ind. Inf. Integr., 26 (2021), 100257. https://doi.org/10.1016/j.jii.2021.100257 doi: 10.1016/j.jii.2021.100257
    [22] A. Mojumder, A. Singh, An exploratory study of the adaptation of green supply chain management in construction industry: the case of Indian Construction Companies, J. Clean. Prod., 295 (2021), 126400. https://doi.org/10.1016/j.jclepro.2021.126400 doi: 10.1016/j.jclepro.2021.126400
    [23] M. M. W. Wijesiri, K. A. K. Devapriya, P. Rathnasiri, L. T. Wickremanayake Karunaratne, A framework to implement green adaptive reuse for existing buildings in Sri Lanka, Intell. Build. Int., 14 (2021), 581–605. https://doi.org/10.1080/17508975.2021.1906204 doi: 10.1080/17508975.2021.1906204
    [24] G. Wang, Y. Li, J. Zuo, W. B. Hu, Q. W. Nie, H. Q. Lei, Who drives green innovations? Characteristics and policy implications for green building collaborative innovation networks in China, Renew. Sust. Energ. Rev., 143 (2021), 110875. https://doi.org/10.1016/j.rser.2021.110875 doi: 10.1016/j.rser.2021.110875
    [25] X. W. Li, R. N. Huang, J. C. Dai, J. R. Li, Q. Shen, Research on the evolutionary game of construction and demolition waste (CDW) recycling units' green behavior, considering remanufacturing capability, Int. J. Environ. Res. Public. Health., 18 (2021), 9268. https://doi.org/10.3390/ijerph18179268 doi: 10.3390/ijerph18179268
    [26] M. Jeihoonian, M. Kazemi Zanjani, M. Gendreau, Dynamic reverse supply chain network design under uncertainty: Mathematical modeling and solution algorithm, Int. T. Oper. Res., 29 (2022), 3161–3189. https://doi.org/10.1111/itor.12865 doi: 10.1111/itor.12865
    [27] S. Yin, B. Z. Li, Academic research institutes-construction enterprises linkages for the development of urban green building: Selecting management of green building technologies innovation partner, Sustain. Cities Soc., 48 (2019), 101555. https://doi.org/10.1016/j.scs.2019.101555 doi: 10.1016/j.scs.2019.101555
    [28] L. H. He, L. Y. Chen, The incentive effects of different government subsidy policies on green buildings, Renew. Sust. Energ. Rev., 135 (2021), 110123. https://doi.org/10.1016/j.rser.2020.110123 doi: 10.1016/j.rser.2020.110123
    [29] A. Karamikli, Y. Bayar, Impact of information and communication technology on CO2 emissions: Evidence from EU transition economies, In: Technological development and impact on economic and environmental sustainability, New York: IGI Global Press, 2022.
    [30] S. Yin, N. Zhang, J. F. Xu, Information fusion for future COVID-19 prevention: Continuous mechanism of big data intelligent innovation for the emergency management of a public epidemic outbreak, J. Manag. Anal., 8 (2021), 391–423. https://doi.org/10.1080/23270012.2021.1945499 doi: 10.1080/23270012.2021.1945499
    [31] S. S. Guo, B. G. Du, L. B. Sun, Y. B. Li, J. Guo, Design and implementation of digital management platform for building materials equipment manufacturing enterprises, CIMS, 21 (2015), 226–234. https://doi.org/10.13196/j.cims.2015.01.025 doi: 10.13196/j.cims.2015.01.025
    [32] M. S. Zhang, Y. Cui, Investigation and research on Shenzhen green building materials market, New Build. Mater., 45 (2018), 143–146.
    [33] L. L. He, H. Yuan, Research on quality perception of recycled building materials enterprises, Ind. Eng. Manag., 24 (2019), 144–151. https://doi.org/10.19495/j.cnki.1007-5429.2019.01.019 doi: 10.19495/j.cnki.1007-5429.2019.01.019
    [34] W. Wang, Z. Tian, W. Xi, Y. R. Tan, Y. Deng, The influencing factors of China's green building development: An analysis using RBF-WINGS method, Build. Environ., 188 (2021), 107425. https://doi.org/10.1016/j.buildenv.2020.107425 doi: 10.1016/j.buildenv.2020.107425
    [35] S. Yin, T. Dong, B. Z. Li, S. Gao, Developing a conceptual partner selection framework: Digital green innovation management of prefabricated construction enterprises for sustainable urban development, Buildings, 12 (2022), 721. https://doi.org/10.3390/buildings12060721 doi: 10.3390/buildings12060721
    [36] Q. Liu, F. H. Gong, Research on e-commerce logistics service upgrading of traditional building materials professional market, Logist. Technol., 2014 (2014), 22–25. https://doi.org/10.3969/j.issn.1005-152X.2014.05.007 doi: 10.3969/j.issn.1005-152X.2014.05.007
    [37] C. Cohen, D. Pearlmutter, M. Schwartz, Promoting green building in Israel: A game theory-based analysis, Build. Environ., 163 (2019), 106227. https://doi.org/10.1016/j.buildenv.2019.106227 doi: 10.1016/j.buildenv.2019.106227
    [38] Y. Liu, J. Zuo, M. Pan, Q. Ge, R. D. Chang, X. T. Feng, et al., The incentive mechanism and decision-making behavior in the green building supply market: A tripartite evolutionary game analysis, Build. Environ., 214 (2022), 108903. https://doi.org/10.1016/j.buildenv.2022.108903 doi: 10.1016/j.buildenv.2022.108903
    [39] H. Lintsen, Stagnation and dynamism in three supply chains: agriculture and foods, building materials and construction, energy, In: Well-being, sustainability and social development, Cham: Springer, 2018. https://doi.org/10.1007/978-3-319-76696-6
    [40] M. Li, M. Lu, H. L. Yu, Research on building materials Information Technology Framework under block chain technology, Build. Econ., 40 (2019), 103–107. https://doi.org/10.14181/j.cnki.1002-851x.201910103 doi: 10.14181/j.cnki.1002-851x.201910103
    [41] M. A. Wibowo, N. U. Handayani, A. Mustikasari, S. A. Wardani, B. Tjahjono, Reverse logistics performance indicators for the construction sector: A building project case, Sustainability, 14 (2022), 963. https://doi.org/10.3390/su14020963 doi: 10.3390/su14020963
    [42] S. M. Khoshnava, R. Rostami, A. Valipour, M. Ismail, A. R. Rahmat, Rank of green building material criteria based on the three pillars of sustainability using the hybrid multi criteria decision making method, J. Clean. Prod., 173 (2018), 82–99. https://doi.org/10.1016/j.jclepro.2016.10.066 doi: 10.1016/j.jclepro.2016.10.066
    [43] A. Darko, A. P. Chan, X. S. Huo, D. G. Owusu-Manu, A scientometric analysis and visualization of global green building research, Build. Environ., 149 (2019), 501–511. https://doi.org/10.1016/j.buildenv.2018.12.059 doi: 10.1016/j.buildenv.2018.12.059
    [44] C. C. Menassa, From BIM to digital twins: A systematic review of the evolution of intelligent building representations in the AEC-FM industry, J. Inf. Technol. Constr., 26 (2021), 58–83. https://doi.org/10.36680/j.itcon.2021.005 doi: 10.36680/j.itcon.2021.005
    [45] Z. H. Mohson, Z. A. Ismael, S. S. Shalal, Comparison between smart and traditional building materials to achieve sustainability, Period. Eng. Nat. Sci., 9 (2021), 808–822. http://doi.org/10.21533/pen.v9i3.2283 doi: 10.21533/pen.v9i3.2283
    [46] S. Yin, Y. Y. Yu, An adoption-implementation framework of digital green knowledge to improve the performance of digital green innovation practices for industry 5.0, J. Clean. Prod., 363 (2022), 132608. https://doi.org/10.1016/j.jclepro.2022.132608 doi: 10.1016/j.jclepro.2022.132608
    [47] M. M. Wang, S. Lian, S. Yin, H. M. Dong, A three-player game model for promoting the diffusion of green technology in manufacturing enterprises from the perspective of supply and demand, Mathematics, 8 (2020), 1585. https://doi.org/10.3390/math8091585 doi: 10.3390/math8091585
  • 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(3700) PDF downloads(117) Cited by(0)

Article outline

Figures and Tables

Figures(5)  /  Tables(5)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog