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The Influencing Factors of Industrial Technological Innovation Ability--Using Bayesian Model Averaging

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DOI: 10.25236/emcs.2018.055


Mengni Zhang

Corresponding Author

Mengni Zhang


Capacity for independent innovation is an important factor to measure the economic strength of a country or a region. Taking industrial enterprises as the research object, this paper analyzes the influencing factors of technological innovative ability. Previous studies only focus on a single field and lack of considering the model uncertainty, leading to an unfaithful conclusion. By abandoning the limitations of single model and synthesizing the different theories about the technological innovation ability at home and abroad, this paper treats the influencing factors as random variables themselves and uses the Bayesian model averaging to measure the uncertainty of model selection. This study found that there are six variables, R&D investment, R&D personnel input, value of import and export, export trade dependence, GDP growth and government S&T input in the 15 possible influence factor, had great influence on the technology innovation ability of industrial enterprises.


Bayesian Model Averaging (BMA), Technology innovation ability, Model uncertainty, Industrial enterprises, Learning-by-exporting hypothesis