A small-world simulation model of a regional innovation system combining the strength of the intersubject relationship of the regional innovation system with the loosely coupled system is constructed. We use a simulation to observe knowledge flow within the regional innovation system under relationships of varying strength. The results show that when the relationship between the subjects of the regional innovation system reaches a certain strength, the system will exhibit high module independence and high network integrity, forming a loosely coupled system. The knowledge flow in the system exhibits the emergence of a fast flow rate, a high mean value and little variance. When relationship strength is at other levels, the emergence of knowledge cannot be identified.
AlbertR., & BarabasiA.L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47–97.
2.
AmonarrizC. A., IturriozC., NarvaizaL., & ParrilliM. D. (2019). The role of social capital in regional innovation systems: Creative social capital and its institutionalization process. Papers in Regional Science, 98(1), 35–51.
3.
ArranzN., ArroyabeC. F., & de ArroyabeJ. C. F. (2019). The effect of regional factors in the development of eco-innovations in the firm. Business Strategy and the Environment, 28(7), 1406–1415.
4.
AsheimB. T., & CoenenL. (2005). Knowledge bases and regional innovation systems: Comparing Nordic clusters. Research Policy, 34(8), 1173–1190.
5.
AsheimB. T., & CoenenL. (2006). Contextualizing regional innovation systems in a globalising learning economy: On knowledge bases and institutional frameworks. The Journal of Technology Transfer, 31, 163–173.
6.
AudrestchD. B., KuratkoD. F., & LinkA. N. (2016). Dynamic entrepreneurship and technology-based innovation. Journal of Evolutionary Economics, 26(3), 603–620.
7.
BermanA., MarinoA., & MudambiR. (2020). The global connectivity of regional innovation systems in Italy: A core-periphery perspective. Regional Studies, 54(5), 677–691.
8.
ChenJ., WangL. J., & LiY. Y. (2020). Natural resources, urbanization and regional innovation capabilities. Resources Policy, 66, 101643.
9.
ChenX. F., LiuZ. Y., & ZhuQ. Y. (2018). Performance evaluation of China’s high-tech innovation process: Analysis based on the innovation value chain. Technovation, 74–75, 42–53.
10.
ChiuS. H., & LinT. Y. (2019). Evaluation of regional knowledge innovation system in China: An economic framework based on dynamic Slacks-based approach. Journal of Asian Finance Economics and Business, 6(3), 141–149.
11.
ChristiansenN., SikerM., & FrostC. T. (2014). What employees dislike about their jobs: Relationship between personality-based fit and work satisfaction. Personality and Individual Differences, 71, 25–29.
12.
CowanR., JonardN., & ZimmermannJ. B. (2006). Evolving networks of inventors. Journal of Evolutionary Economics, 16, 155–174.
13.
FuL. P., & JiangX. D. (2019). Does the multiple-participant innovation improve regional innovation efficiency? A study of China’s regional innovation systems. Sustainability, 11(17), 4658.
14.
GeY. Q., & SunX. M. (2020). The relationship of employees’ strengths use and innovation: Work engagement as a mediator. Social Behavior and Personality, 48(5), e9083.
15.
GuanH. L. (2016). An evolution model for regional collaborative innovation under the perspective of complex network. Journal of Intelligent & Fuzzy Systems, 31(3), 1319–1328.
16.
HuangJ. B., & ChenX. (2020). Domestic R&D activities, technology absorption ability, and energy intensity in China. Energy Policy, 138, 111184.
17.
KleinbergJ. (2004). The small- world phenomenon and decentralized search. SIAM News, 37(3), 1–2.
18.
LaiJ., LuiS. S., & TsangE. W. K. (2016). Intrafirm knowledge transfer and employee innovative behavior: The role of total and balanced knowledge flows. Journal of Product Innovation Management, 33(1), 90–103.
19.
LengyelB., & ErikssonR. H. (2017). Co-worker networks, labour mobility and productivity growth in regions. Journal of Economic Geography, 17(3), 635–660.
20.
LiW. B., WuW. W., LiuY. X., & YuB. (2017). How China’s manufacturers achieve technological catch-up: The periphery-core mode of R&D cooperation. Chinese Management Studies, 11(1), 139–162.
21.
LiangL., WenY. B., & LvY. Y. (2019). Fuzzy intelligent comprehensive evaluation of urban regional innovation system operation based on Bayesian discriminant. Open house international, 44(3), 104–107.
22.
LiljerosF., EdlingC. R., AmaralL. A. N., StanleyH. E., & AbergY. (2001). The web of human sexual contacts. Nature, 411, 907–908.
23.
LiuX. Y., SunR., & ZhaoD. L. (2014). The influence of network structure on cluster knowledge distribution and enterprise innovation. Science and Technology Management Research, 34(22), 141–144.
24.
MinS., KimJ., & SawngY. W. (2020). The effect of innovation network size and public R&D investment on regional innovation efficiency. Technological Forecasting and Social Change, 155, 119998.
25.
MoralesD., & Sariego-KlugeL. (2021). Regional state innovation in peripheral regions: Enabling Lapland’s green policies. Regional Studies Regional Science, 8(1), 54–64.
26.
OpashlT., VernetA., AlnuaimiT., & GeorgeG. (2017) Revisiting the small-world phenomenon: Efficiency variation and classification of small-world networks. Organizational Research Methods, 20(1), 149–173.
27.
OrtonJ. D., & WeickK. E. (1990). Loosely coupled systems: A reconceptualization. The Academy of Management Review, 15(2), 203–223.
28.
OttH., & RondeP. (2019). Inside the regional innovation system black box: Evidence from French data. Papers in Regional Science, 98(5), 1993–2026.
29.
Ozkan-CanbolatE., & BerahaA. (2016). A configurational approach to network topology design for product innovation. Journal of Business Research, 69(11), 5216–5221.
30.
PanX., MingY., LiM. N., GuoS. C., & HanC. C. (2020). Inter-regional innovation correlation effects and influencing factors in China. Business Process Management Journal, 26(4), 925–941.
31.
PapadonikolakiE. (2018). Loosely coupled systems of innovation: Aligning BIM adoption with implementation in Dutch construction. Journal of Management In Engineering, 34(6), 05018009.
32.
PengM., XuH. Z., QuC. F., XuJ. Y., ChenL. R., DuanL. (2021). Understanding China’s largest sustainability experiment: Atmospheric and climate governance in the Yangtze river economic belt as a lens. Journal of Cleaner Production, 290, 125760.
33.
RuanY. H., & LiA. W. (2016). A new small-world network created by cellular automata. Physica A-Statistical Mechanics and Its Applications, 456, 106–111.
34.
ShenJ. P., GaoX. Y., & XiaJ. G. (2017). School as a loosely coupled organization? An empirical examination using national SASS 2003-04 data. Educational Management Administration & Leadership, 45(4), 657–681.
35.
ShiY., & GuanJ. C. (2016). Small-world network effects on innovation: Evidences from nanotechnology patenting. Journal of Nanoparticle Research, 18(11), 329.
36.
SuY., & AnX. L. (2018). Application of threshold regression analysis to study the impact of regional technological innovation level on sustainable development. Renewable & Sustainable Energy Review, 89, 27–32.
37.
SuY., & LiT. C. (2020). Simulation analysis of knowledge transfer in a knowledge alliance based on a circular surface radiator model. Complexity, 2020, 4301489.
38.
SuY., & LiuB. D. (2019). Synergetics of enterprise innovation systems based on a three-variable oscillation reaction. IEEE Access, 7, 150598–150608.
39.
SuY., & YuY. Q. (2020). Spatial agglomeration of new energy industries on the performance of regional pollution control through spatial econometric analysis. Science of the Total Environment, 704, 135261.
40.
SungS. Y., & ChoiJ. N. (2018). Building knowledge stock and facilitating knowledge flow through human resource management practices toward firm innovation. Human Resource Management, 57(6), 1429–1442.
41.
TavassoliS., & KarlssonC. (2021). The role of location on complexity of firms’ innovation outcome. Technological Forecasting and Social Change, 162, 120404.
42.
TripplM., Baumgartinger-SeiringerS., FrangenheimA., IsaksenA., & RypestolJ. O. (2020). Unravelling green regional industrial path development: Regional preconditions, asset modification and agency. Geoforum, 111, 189–197.
43.
WangW. P., & ZhangB. (2009) Small world of knowledge flowing—from a relation strength point of view. Studies in Science of Science, 27(9), 1312–1321.
44.
WangW. P., & ZhangB. (2010) A simulation study on knowledge flowing efficiency of informal knowledge networks based on different interactive policies. Chinese Journal of Management, 7(5), 706–713.
45.
WangW. P., & ZhangB. (2011) Distribution of relation strength and small world of knowledge flowing on informal knowledge networks. Chinese Journal of Management Science, 19(4), 159–166.
46.
WangW. P., & ZhangB. (2013). Emergence characteristics of knowledge flow in knowledge networks under dynamic relationship strengths. Journal of Management Sciences in China, 16(2), 1–11.
47.
WattsD. J., & StrogatzS. H. (1998). Collective dynamics of small-world networks. Nature, 393(4), 440–442.
48.
XiaW. F., LiB. Z., & YinS. (2020). Identification of influencing factors for sustainable development: Evaluation and management of regional innovation performance in Heilongjiang, China. Sustainability, 12(7), 2739.
49.
ZhangJ., XiaF., NingZ. L., BekeleT. M., BaiX. M., SuX. Y., & WangJ. Z. (2016). A hybrid mechanism for innovation diffusion in social networks. IEEE Access, 4, 5408–5416.
50.
ZhangM. L., & LiB. Z. (2020). How to improve regional innovation quality from the perspective of green development? Findings from entropy weight method and fuzzy-set qualitative comparative analysis. IEEE Access, 8, 32575–32586.
51.
ZhangY. Q., FanR. G., & LuoM. (2018). A study on the inner mechanisms of knowledge distribution, depreciation on industrial clusters’ innovation patterns. Chinese Journal of Management Science, 26(12), 186–196.
52.
ZhengJ. J., ShaoX. F., LiuW., KongJ., & ZuoG. S. (2021). The impact of the pilot program on industrial structure upgrading in low-carbon cities. Journal of Cleaner Production, 290, 125868.
53.
ZhouX., YuY., YangF., ShiQ. F. (2021). Spatial-temporal heterogeneity of green innovation in China. Journal of Cleaner Production, 282, 124464.
54.
ZhouY. X. (2014). Role of Institutional Quality in Determining the R&D Investment of Chinese Firms. China & World Economy, 22(4), 60–82.
