Research on coupling coordination level of Sci-tech finance and technology innovation in Jiangsu province

Author(s):  
Qiu Dongfang ◽  
Shao Huayang
2014 ◽  
Vol 4 (1) ◽  
pp. 124-136 ◽  
Author(s):  
Yu Zhang ◽  
Jie Ni ◽  
Jian Liu ◽  
Li-rong Jian

Purpose – This paper aims to investigate the performance of Jiangsu Province industrial technology innovation strategy alliance. Design/methodology/approach – Through a preliminary investigation of 30 Jiangsu industrial technology innovation strategic alliances, this paper analyzed the status and extracted 18 alliances to conduct an in-depth investigation. By grey evaluation method based on center-point triangular whitenization weight function, the paper classified and analyzed alliances. Findings – The results show that university or research institutions-oriented alliance perform better, but the government/enterprise-oriented alliance perform diverse, and majority is rated “general”. Originality/value – The paper succeeds in clustering analysis to Jiangsu Province industrial technology innovation strategy alliance with insufficient data. And according to the result of clustering, it analyzes the causes, which provide value information for the sustainable development of Jiangsu Province industrial technology innovation strategy alliance.


2019 ◽  
Vol 2 (4) ◽  
pp. 260-266
Author(s):  
Haru Purnomo Ipung ◽  
Amin Soetomo

This research proposed a model to assist the design of the associated data architecture and data analytic to support talent forecast in the current accelerating changes in economy, industry and business change due to the accelerating pace of technological change. The emerging and re-emerging economy model were available, such as Industrial revolution 4.0, platform economy, sharing economy and token economy. Those were driven by new business model and technology innovation. An increase capability of technology to automate more jobs will cause a shift in talent pool and workforce. New business model emerge as the availabilityand the cost effective emerging technology, and as a result of emerging or re-emerging economic models. Both, new business model and technology innovation, create new jobs and works that have not been existed decades ago. The future workers will be faced by jobs that may not exist today. A dynamics model of inter-correlation of economy, industry, business model and talent forecast were proposed. A collection of literature review were conducted to initially validate the model.


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