A metafrontier and Malmquist productivity index approach for analyzing biased technological and efficiency change in Taiwanese traditional Chinese medicine

Kuan-Chen Chen , Hsiang-An Yu , Ming-Miin Yu
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Abstract

This study assesses changes in resource productivity in traditional Chinese medicine (TCM) system across Taiwanese counties and cities from 2016 to 2019, stratifying the analysis by population densities. Employing a data envelopment analysis (DEA) metafrontier Malmquist productivity index model, this research relaxes Hicks' neutrality assumption of technical change, allowing for the measurement of biased technological change and technical gap ratio changes. The empirical findings reveal a decline in TCM system productivity, primarily attributed to reduced technological advancements. Notably, higher productivity changes were observed in counties and cities with lower population densities, contrasting with those having higher population densities, where productivity changes were limited. The results suggest that areas with lower population densities hold significant potential for technological enhancement, as evidenced by intergroup technology updates and technological leadership indices. Furthermore, the estimates of productivity change and technological bias underscore the inadequacy of assuming Hicks’ neutral technological change for analyzing TCM system productivity in Taiwan. These findings highlight the need for improved TCM system technology and innovation within the healthcare system to address the urban-rural gap effectively.
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台湾中医药偏激技术与效率变迁之超前沿与Malmquist生产力指数分析
本研究评估了2016 - 2019年台湾各县市中医药系统资源生产力的变化,并以人口密度进行分层分析。本文采用数据包络分析(DEA)元前沿Malmquist生产率指数模型,放宽Hicks的技术变革中性假设,允许测量偏倚技术变革和技术差距比变化。实证结果表明,中医系统生产力的下降主要归因于技术进步的减少。值得注意的是,在人口密度较低的县市,生产率变化较大,而在人口密度较高的县市,生产率变化有限。结果表明,人口密度低的地区具有显著的技术提升潜力,体现在群体间技术更新和技术领先指数上。此外,对于生产力变迁与技术偏差的估计,也凸显了假设Hicks中立技术变迁来分析台湾中医系统生产力的不足。这些发现突出了中医系统技术和医疗保健系统创新的必要性,以有效解决城乡差距。
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来源期刊
Healthcare analytics (New York, N.Y.)
Healthcare analytics (New York, N.Y.) Applied Mathematics, Modelling and Simulation, Nursing and Health Professions (General)
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
79 days
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