Abstract
Based on the sample data of 40 rural commercial banks in China from 2011 to 2016, the paper empirically tested the influence of ownership structure on the performance of rural commercial banks when loan behavior was used as an intermediary variable. First, the direct influence of ownership structure on the performance of rural commercial banks is tested. The regression results show that ownership concentration, ownership balance and the nature of state-owned ownership have a significant negative influence on the performance of rural commercial banks. Secondly, on the basis of the regression model of the relationship between ownership structure and performance, loan behavior is added as an intermediary variable to test whether ownership structure influences the performance of rural commercial banks through loan behavior. The results of the mediation effect show that the loan concentration plays a partial intermediary role in the influence of ownership concentration and ownership balance on the performance of rural commercial banks, and a complete intermediary role in the influence of ownership nature on the performance of rural commercial banks. The loan scale plays a full intermediary role in the influence of equity nature on the performance of rural commercial banks.
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Acknowledgements
This work was supported by the National Social Science Fund of China Project “Research on the service ability promotion strategy of rural credit cooperatives from the perspective of corporate governance” (Item number 14BJY104) and the Shaanxi Social Science Foundation Project “Study on the evaluation and influencing factors of county Inclusive Finance Development in Shaanxi Province” (Item number 2019D008).
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Wang, W., Dang, X., Zhang, X. (2020). Impact of Ownership Structure and Credit Behavior on Performance of Rural Commercial Banks: Evidence from China. In: Xu, J., Duca, G., Ahmed, S., García Márquez, F., Hajiyev, A. (eds) Proceedings of the Fourteenth International Conference on Management Science and Engineering Management. ICMSEM 2020. Advances in Intelligent Systems and Computing, vol 1190. Springer, Cham. https://doi.org/10.1007/978-3-030-49829-0_4
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