Performance evaluation of China's innovation during the industry-university-research collaboration process—an analysis basis on the dynamic network slacks-based measurement model

Bai, Xuejie; Li, Zhenyang; Zeng, Jin

doi:10.1016/j.techsoc.2020.101310

Cited by 29 publications

(19 citation statements)

References 44 publications

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“…(2021) confirmed that measuring the effectiveness of collaboration would strengthen innovation creation. In conclusion, measuring effectiveness also results in building a collective understanding to strengthen the creation of innovation in the industry in general (Bai et al. , 2020).…”

Section: Discussionmentioning

confidence: 99%

Examining the role of measuring impact in higher education innovation creation

Prihandono

Wijaya

Wiratama

et al. 2022

JARHE

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PurposeThis study responds to the need for further research to examine determinants that impact innovation creation in higher education institutions.Design/methodology/approachThe study is a quantitative analysis; it uses 133 responses derived from respondents from several universities in Indonesia. The data are analyzed by using SEM-PLS. In the analysis, after having the inner model, then, the outer model is calculated. The research establishes a 95% confidence interval and conducts 500 bootstraps.FindingsThe results of this study indicate, firstly, the business and university partnerships, entrepreneurship orientation, and information technology facilities significantly influence innovation creation; secondly, measuring the impact in universities will strengthen the business and university partnerships, entrepreneurship orientation, and information technology facilities on the innovation creation.Research limitations/implicationsThis research implies that universities need to measure the impact and develop a proper measurement to enhance innovation through their relationship with their industrial partnerships and information technology facilities. However, the research has a limitation; the study is only conducted in state universities.Practical implicationsThe research measures the impact of the university–business partnership, entrepreneurship orientation, and IT facility. These determinants' effectiveness needs a measurement scheme to improve the innovation creation outputs, quantity, and quality.Originality/valueUniversities have an essential role in developing entrepreneurship competence for students and staff by nurturing innovation creation. It will benefit the staff in managing tasks and the students after they graduate to create businesses. This study aims to provide an in-depth analysis of determinants that affect innovation creation in higher education institutions in Indonesia.

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Section: Discussionmentioning

confidence: 99%

Examining the role of measuring impact in higher education innovation creation

Prihandono

Wijaya

Wiratama

et al. 2022

JARHE

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“…Using the DNSBM model, the overall efficiency, divisional efficiency, and period efficiency can be obtained. The DNSBM model has been used for efficiency measurements in several fields, such as the efficiency of electric power systems, the efficiency of banks, China's innovation during industry-university-research institute's collaboration process [31][32][33].…”

Section: Research On Innovation Efficiency Methodsmentioning

confidence: 99%

Measurement of Innovation Efficiency in China’s Electronics and Communication Equipment Manufacturing Industry-Based on Dynamic Network SBM Model

2022

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In recent years, China’s electronics and communication equipment manufacturing (ECEM) industry has overgrown, and the government should assess the innovation performance of the industry for its sustainable development. However, most previous studies on the innovation efficiency of the ECEM industry have ignored the link and carry-over variables. This paper uses the number of patent applications as a link variable to consider the stage of innovation activities. It divides the innovation activities of the electronics industry into two stages: technology development and results in transformation. To consider the dynamics of innovation activities, this paper uses capital stock as a period carry-over variable and evaluates the change of innovation efficiency over time. In this paper, the DNSBM model is used to measure the innovation efficiency of the ECEM industry in 26 Chinese provinces from 2013–2019. This model includes both stage link variables and period carry-over variables, thus allowing for overall efficiency and stage efficiency and period efficiency. The results show that the overall innovation efficiency values in the Chinese ECEM industry are low, there are considerable differences between the two-stage efficiency values in the east, central and western regions, and the overall efficiency values show a slow upward trend.

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“…Industry-university-research cooperation refers to collaborative technological innovation and commercialization of enterprises, universities, and scientific research institutions (Bai et al, 2020;Song et al, 2020). External knowledge from universities and scientific research institutions is considered to have a positive influence on environmental innovation (De Marchi and Grandinetti, 2013).…”

Section: The Impact Of Iurc On Eementioning

confidence: 99%

Does industry-university-research cooperation promote the environmental efficiency of China’s high-tech manufacturing?

Feng

Zhang

2023

Front. Ecol. Evol.

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As one of the important strategic measures to increase the international competitiveness of high-tech manufacturing (HTM), industry-university-research cooperation (IURC) has received increasing attention in China. However, there is little literature to explore the links between IURC and the environmental efficiency (EE) of HTM. To incorporate a variety of environmental pollution indicators into the efficiency analysis framework and reduce the adverse effects of random errors on the estimation results, this article combined the projection pursuit model with the stochastic frontier analysis (SFA) method and proposed a translog stochastic frontier model considering undesirable outputs to analyze the multiple impacts of IURC on the EE of HTM. The results show that IURC has both a significant negative direct effect and a significant positive indirect effect on HTM’s EE. Although IURC cannot directly promote EE, it has a positive impact on EE of HTM through its complementary effect with research and development (R&D) investment. The results also confirm that the average EE of the whole country is only 0.346, while that of the eastern area is 0.595, and that of the central and western areas are 0.199 and 0.171, respectively. Therefore, it is particularly urgent to improve the EE of China’s HTM industry through a variety of measures, such as promoting IURC and increasing R&D investment in environmental technology. This study not only provides an improved SFA method for measuring EE, but also deepens research on the mechanism of the impact of IURC on HTM’s EE.

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Performance evaluation of China's innovation during the industry-university-research collaboration process—an analysis basis on the dynamic network slacks-based measurement model

Cited by 29 publications

References 44 publications

Examining the role of measuring impact in higher education innovation creation

Examining the role of measuring impact in higher education innovation creation

Measurement of Innovation Efficiency in China’s Electronics and Communication Equipment Manufacturing Industry-Based on Dynamic Network SBM Model

Does industry-university-research cooperation promote the environmental efficiency of China’s high-tech manufacturing?

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