数智化转型对中国纺织服装企业全要素生产率的影响研究OA

As a traditional manufacturing industry in China,the textile and apparel industry is facing multiple difficulties such as rising costs,efficiency bottlenecks and intensified market competition.With the deep penetration of artificial intelligence,industrial Internet and big data analysis technology into manufacturing scenarios,the transformation of digital intelligence has evolved from a simple innovation of production tools to a systematic project of reshaping the whole value chain of enterprises,which is regarded as a key path to break through the real dilemma and reshape total factor productivity.In order to explore the effect of digital intelligence transformation on the total factor productivity of China's textile and apparel enterprises,this paper takes the A-share listed enterprises in China's textile and apparel industry from 2010 to 2024 as the research sample,depicts the level of digital intelligence transformation from three dimensions of cognition,investment and application,and uses the fixed effect model and the intermediary effect model to empirically test the direction,conduction path and boundary conditions of digital intelligence transformation on total factor productivity. The results show that the digital intelligence transformation can significantly improve the total factor productivity of China's textile and apparel enterprises,and this positive impact has both lag effect and cumulative effect characteristics.Through enabling management,production and marketing links,the transformation of digital intelligence effectively reduces financing costs and transaction costs,while improving management efficiency,capacity utilization and marketing efficiency,and jointly drives the growth of total factor productivity of enterprises;heterogeneity analysis shows that the promotion effect is more prominent in large-scale enterprises,non-state-owned enterprises,enterprises with high human capital level,enterprises with low financing constraints,enterprises in the downstream of the industrial chain and enterprises in the eastern region.The above findings provide a micro basis for the precise formulation of industry digital intelligence support policies. The marginal contribution of this paper is mainly reflected in the following three aspects.First,it focuses on the traditional manufacturing sector of textile and apparel,and deepens the research on the micro-economic effects of digital intelligence transformation in sub-sectors.Secondly,it reveals that the digital intelligence transformation forms a dual transmission mechanism of cost saving and efficiency improvement through the three links of empowerment management,production and marketing,and expands the theoretical interpretation framework of the impact of digital intelligence transformation on the total factor productivity of enterprises.Third,it comprehensively examines the heterogeneity of the above-mentioned promotion effects in the dimensions of enterprise scale,property rights,human capital level,financing constraints,industrial chain position and geographical location,and provides a micro-level decision-making basis for the textile and apparel industry to accurately formulate classified and intelligent support policies. Although this paper makes a systematic investigation on the productivity effect of digital intelligence transformation of textile and apparel enterprises,there are still some shortcomings due to data availability and research design.Future research can further reveal the dynamic evolution mechanism in the process of digital intelligence transformation by means of event research method,dynamic panel model or simulation method.In addition,this paper takes China's textile and apparel A-share listed companies as research samples.Whether the research conclusions have the same applicability to the large number of non-listed companies with different characteristics of digital intelligence transformation still needs to be verified and expanded.