The Total Factor Productivity of China’s Software Industry and its Promotion Path

Lixiang Zhao,Songling Wu,Xiaoxiang Wang

doi:10.1109/access.2021.3094267

Lixiang Zhao, Songling Wu + Show 1 more

Open Access

https://doi.org/10.1109/access.2021.3094267

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Abstract

To reasonably guide and promote the high-quality development of China's software industry through policies, and to improve the total factor productivity (TFP) of China's software industry are the inevitable requirements of the conjunctive development. Previous research mainly used econometric methods to explore the impact of specific variables or factors in different regions on the TFP of the software industry. Here we provide a solution for the path selection to improve the TFP of the software industry. The DEA-Malmquist index analysis method to measure the TFP of the software industry and the fuzzy set qualitative comparative analysis method (fsQCA) are adopted to explore the different promotion paths of provinces based on the relevant data of 29 provinces in China. The results show that 5 path configurations achieve high TFP. Specifically, regions with high TFP in the software industry tend to be those with high enterprise scale, high R&D investment, and high R&D personnel investment. When the scale of enterprises is high, the region should fully consider the degree of R&D investment and the degree of higher education. When the investment of R&D personnel is high, the high education level of human factors and the investment intensity of fixed assets of capital factors should be brought into full play. When the investment in fixed assets and R&D investment are high, the region should fully consider the investment of R&D personnel and the scale of the enterprise.

Highlights

The development of China's software industry has gone through more than 40 years
In the third path H3 (~Fixed asset intensity (FAI)*~R&D intensity (RD)*R&D personnel intensity (RDP)*~SCAL*~HE), the solution points to the fact that the combination of (a) Absence of Fixed asset investment intensity, (b) Absence of research and development (R&D) investment intensity, (c) R&D personnel input intensity, (d) Absence of Enterprise scale, and (e) Absence of Higher education brings about a high level of total factor productivity (TFP) of software industry
In the fifth path H5 (FAI*RD*RDP*~SCAL*~HE), the solution points to the fact that the combination of (a) Fixed asset investment intensity, (b) R&D investment intensity, (c) R&D personnel input intensity, (d) Absence of Enterprise scale, and (e) Absence of Higher education brings about a high level of TFP of software industry

Summary

INTRODUCTION

The development of China's software industry has gone through more than 40 years. Today, it has become a continuous driving force for China to build a well-off society in an all-round way in the new era, and it is a solid foundation for China's future high-quality development. The main contributions of this study are reflected in the following aspects [14] First of all, this is the first study on using fsQCA to improve TFP in China's software industry. The relationship between factors and outcome is analyzed from a systematic perspective, and the fsQCA considers that there can be multiple different path configuration combinations to achieve the outcome. In this way, our research outcome is more consistent with what logic might imply,and more instructive for improving the China's software industry [15].

LITERATURE REVIEW AND METHODS

CASE STUDY

APPLICATION THE FSQCA TO PROMOTION PATH

Findings

CONCLUSION