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Academic Journal of Business & Management, 2022, 4(19); doi: 10.25236/AJBM.2022.041917.

Social network analysis based on collaborative innovation performance impact factors of assembled construction industrial park

Author(s)

Yuqing Bai

Corresponding Author:
Yuqing Bai
Affiliation(s)

Hebei University of Engineering, Handan, Hebei, 056107, China

Abstract

In order to improve the current situation that innovation in the construction industry is relatively lagging behind, this paper investigates the key influencing factors that affect the collaborative innovation performance of the assembly construction industrial park. Based on the research of previous literature, this paper sorts out the factors affecting the collaborative innovation among innovation subjects in the assembly construction industry, and lists the influencing factors affecting the innovation performance of the industrial park by combining the characteristics of the assembly construction industry, constructs a social network analysis model among the influencing factors through the obtained data, and finally analyzes them by UCINET 6.0 software. The research results show that six factors, namely innovation resource investment, willingness to cooperate, knowledge conversion rate, participants' ability and quality, standardization degree and alliance organization management, are the key factors influencing the collaborative innovation performance of the assembly construction industrial park.

Keywords

assembly building; collaborative innovation performance; social network analysis

Cite This Paper

Yuqing Bai. Social network analysis based on collaborative innovation performance impact factors of assembled construction industrial park. Academic Journal of Business & Management (2022) Vol. 4, Issue 19: 138-146. https://doi.org/10.25236/AJBM.2022.041917.

References

[1] Wang J, Zhao Kida, Hu Zongyu. Current situation and reflection on the development of construction industrialization in China[J]. Journal of Civil Engineering,2016,49(05):1-8. 

[2] Ji Xun. Construction industry modernization and construction industry development of new industry, new mode of exploration [N]. China Construction News,2015-09-25(006).

[3] Ma Hui, Wang Suzhen, Huang Mengjiao. Analysis of influencing factors of collaborative innovation of construction industry alliance based on social network analysis - taking Beijing-Tianjin-Hebei region as an example [J]. Science and Technology Management Research,2018,38(15):170-176.

[4] Yang, C. and Wang, W.. Research on wisdom construction promotion strategy based on the evolution of construction industry modernization technology[J]. China Soft Science,2018(08):18-30.

[5] Ma Zhiliang. Technological innovation thinking on the synergistic development of intelligent construction and building industrialization [J]. China Survey and Design, 2020(09):28-30.

[6] Liu Qian. Digital architecture: constructing a new engine for digital transformation of industry[J]. Software and integrated circuits,2020(09):28-29.

[7] He Weiyi, Zhai Yinan, Wang Jing. Green science and technology innovation and pushing synergistic mechanism:A key customer perspective[J]. Journal of Dalian University of Technology (Social Science Edition),2018,39(03):17-23.

[8] Zheng Jun, Zhang Fan, Wang Bingfu. Global pipeline, knowledge gatekeepers and strategic emerging industry cluster development--a case from IC industry cluster in Suzhou High-tech Zone[J]. Enterprise Economics,2021,40(03):24-32.

[9] Zhou Dasen, Shi Pengfei, Geng Biao, Li Xingming. Research on the collaborative innovation path of science and technology-based micro and small enterprises--based on the perspective of strategic alliance [J]. Resource Development and Market,2021,37(10):1200-1208.

[10] He XJ, Li N, Wang YAO. System dynamics analysis of innovation performance enhancement of alliance firms--based on knowledge synergy perspective [J]. Journal of System Science, 2021, 29(03): 125-130. System dynamics analysis of innovation performance enhancement of alliance enterprises--based on knowledge synergy perspective

[11] Wu Weihong, Zhao Kun, Zhang Aimi. A study on the path of the role of corporate collaborative innovation risk on innovation performance[J]. Scientific Research Management, 2021,42(05):124-132.

[12] Lv Pu, Ma Kexin. Research on the benefit distribution mechanism of cluster supply chain collaborative innovation based on relative risk sharing[J]. Operations Research and Management,2 020, 29(09): 115-123. 

[13] Li L, Attack Y. Research on the design and application of collaborative innovation performance evaluation index system for research projects[J]. Science and Technology Progress and Countermeasures, 2014, 31(01):123-129.

[14] Zhao Bingyuan. Analysis of factors influencing the collaborative innovation performance of Beijing, Tianjin and Hebei--based on the spatial Durbin model [J]. Business and Economic Research, 2021(01): 162-166.

[15] Wu, C. Chao. Network structure, innovation infrastructure and regional innovation performance - an analysis based on network DEA multiplier model [J]. Journal of Beijing Jiaotong University (Social Science Edition), 2021,20(02):79-89. 

[16] Jingjing Bai, Junfeng Li. An empirical study on the correlation between innovation network and innovation performance of enterprises within industrial clusters--An example of Anhui Gogou cable industry cluster [J]. World Geography Research,2021,30(01):157-166.

[17] Yu L. P., Fang J. X., Wang Zuogong. Factors influencing the depth of collaborative innovation in high-tech industries and its industry comparison--Aerospace and computer and office industries as an example [J]. Journal of Guangdong University of Finance and Economics,2017,32(05):12-21.

[18] Jiang, X. H.. Research on the factors influencing the performance of collaborative innovation in higher education [J]. Research and Development Management,2018,30(06):138-143.

[19] Xie Weiqun, Huangfu Yang, Yu Liying. Factors influencing the performance of collaborative innovation in universities from the perspective of value co-creation [J]. China University Technology, 2020(04): 22-26.

[20] Li Y, Ye Q. Study on the evolution of inter-city collaborative innovation network in Zhejiang Province and its influencing factors--based on the perspective of innovation network [J]. Lanzhou Journal, 2021(10): 49-64.

[21] Zheng R, Sun X. Han, Wei M. Zhu, Chang Z. Yu. A study on the factors influencing the operation of industrial think tank alliance based on rooting theory [J]. Intelligence Science,2020,38(12):51-56.

[22] Ruan, Ping-Nan, Wei, Yun-Feng, Zhang, Guo-Hong. Research on the factors influencing innovation synergy in corporate innovation networks [J]. Science and Technology Management Research, 2016, 36(21): 1-5+11.

[23] Cao Xiaoju, Guo Guangfeng, Zhang Lei. Research on optimization measures of modern construction engineering management from the perspective of informationization [J]. China Management Informatization, 2020, 23(22):83-84.

[24] Liu Jun. Lecture Notes on Holistic Network Analysis: A Practical Guide to UCINET Software [M]. Shanghai: Gezhi Press, 2009.