Digital transformation plays a crucial role in improving the quality development of companies in this era of digital economy with ever-changing technologies. This paper empirically investigates the impact of corporate digital transformation on total factor productivity and the mechanism of action, using A-share listed companies in Shanghai and Shenzhen from 2011–2021 as the research sample, and found that the digital transformation of companies significantly improves total factor productivity, with the plausibility of the findings being verified by a series of robustness tests. Based on the heterogeneity study, it is found that such effect is stronger for private companies, non-high-tech companies, and companies with a high degree of industry competition. The mechanism test indicates that digital transformation facilitates total factor productivity through four ways: strengthening company technological innovation, reducing operational costs, increasing resource allocation efficiency, and improving human capital structure. The findings of this paper support a better understanding of the micro effects of digital transformation and provide empirical evidence for policy formulation and adjustment.

Objectives The pharmacoeconomic studies of traditional Chinese medicine (TCM) are still in its infancy. Assessing the quality of pharmacoeconomic studies of TCM to improve the efficiency of health resource allocation and guide the rational use of medicine. Methods Four databases were searched from inception to January 2018. The Consolidated Health Economic Evaluation Reporting Standards statement (CHEERS) and the Quality of Health Economic Studies (QHES) were used to assess the reporting quality and methodological quality. STATA 12.0 and Meta analyst 3.13 were used to analyze the related data. Results A total of 178 studies were included. The methodological evaluation of the study found that the total score of QHES was 47.85 +/- 8.09. The report quality evaluation results found that many studies did not report comprehensive information, such as lack of detailed reports on abstracts, study perspectives, time frames, discount rates, model selection, but the titles, study background and location, and health results, resource and cost estimates, analysis methods, and heterogeneity analysis are reported in more detail. Six of the ten stratification factors have statistically significant differences. Conclusion The overall quality of pharmacoeconomic studies of TCM is low, and further standardization and improvement are needed to obtain reliable study results.

文章立足于循证科学的视角和方法,以"基于当前可得的最佳证据"为基本原则,沿着从理论驱动到数据驱动的经济学方法演化路径,对从前古典时期到现代经济学各个理论发展时期的经济学证据演化进行了梳理,构建了主要包括证据来源、证据生产、证据评价等环节的循证经济学全证据链框架。研究发现,循证科学的理念始终贯穿于经济学证据的演化历史之中;大数据时代的经济学"最佳证据"是一个广义、多源的各种最佳证据集合;大数据时代,经济学证据从理论驱动走向数据驱动,证据链得到优化升级,最终助推经济学研究范式的转变与循证经济学的发展。