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Changes in technological innovation efficiency and influencing factors of listed textile and apparel companies research--Based on three-stage DEA with Tobit modeling.

ABSTRACT: The key to high-quality development in the textile and apparel industry lies in enhancing technological innovation and optimizing the efficiency of technological innovation. Based on data from 60 A-share listed companies in the textile and apparel sector in China from 2013 to 2022, this study employs a three-stage DEA model and the Malmquist index model to measure changes in technological innovation efficiency from static and dynamic perspectives. Additionally, it uses a Tobit model to analyze the impact and mechanisms of management and financial factors on technological innovation efficiency. The results indicate that: (1) Compared to the manufacturing industry and its sub-sectors, the overall technological innovation efficiency of listed textile and apparel companies was relatively low and showed a declining trend between 2013 and 2022; (2) Over the decade, the average total factor productivity of these listed companies increased by 1.7%, exhibiting a "W" shaped fluctuation, with technological progress, pure technical efficiency, and scale efficiency all showing weak improvement; (3) Management and financial factors significantly influence technological innovation efficiency. Specifically, employee quality, profitability, and operational capability are positively correlated with technological innovation efficiency and have long-term effectiveness, while firm age, management costs, equity concentration, development ability, and debt repayment capacity are negatively correlated with technological innovation efficiency; (4) Different types of enterprises show differences in the significance of management factors, while whether the same person holds both managerial positions significantly affects financial factors.

SUBMITTER: Chen G

PROVIDER: S-EPMC11309499 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Changes in technological innovation efficiency and influencing factors of listed textile and apparel companies research--Based on three-stage DEA with Tobit modeling.

Chen Guang G Chen Fei F

PloS one 20240808 8

The key to high-quality development in the textile and apparel industry lies in enhancing technological innovation and optimizing the efficiency of technological innovation. Based on data from 60 A-share listed companies in the textile and apparel sector in China from 2013 to 2022, this study employs a three-stage DEA model and the Malmquist index model to measure changes in technological innovation efficiency from static and dynamic perspectives. Additionally, it uses a Tobit model to analyze t ...[more]

PMID: 39116077

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Project description:Facing the intensification of global carbon emissions and the increasingly severe pressure of environmental pollution, listed companies urgently need to promote green innovation, achieve green transformation, and alleviate environmental problems. Green finance policy has played a significant role as a financial strategy for environmental governance in affecting green innovation level over the years. In this context, taking the green finance reform and innovation pilot zone (GFRIPZ) implemented in 2017 in China as a quasi-natural experiment, this paper analyzes the impact of green finance policy on green innovation level of listed companies by the difference-in-difference model. Based on the data of Chinese A-share listed companies from 2008 to 2020, the results of empirical analysis show that green finance significantly promotes green innovation of listed companies. The effect is profound on green utility model patents, but less pronounced on green invention patents. Among all these pilot zones, the policy effects of GFRIPZ ranked in descending order are Zhejiang, Guangdong, Jiangxi, Guizhou, and Xinjiang. In addition, green finance has a more significant impact on heavy-polluting industries, large and state-owned enterprises, and listed companies located in the eastern region. Furthermore, the effects of industry heterogeneity ranked in descending order are energy, manufacturing, processing, and engineering industry, while it is not obvious in the service industry. Mechanism analysis suggests that the effect is driven by a reduction in the cost of debt financing and an increase in the long-term debt ratio. The findings provide implications for policymakers to promote the level of green innovation and environmental governance. Therefore, policymakers should support the long-term creative development of green invention patents by reducing the cost of debt financing and increasing the long-term debt ratio and consider the heterogeneous characteristics of listed companies when formulating green finance policies.

Dataset Information

Changes in technological innovation efficiency and influencing factors of listed textile and apparel companies research--Based on three-stage DEA with Tobit modeling.

Publications

Changes in technological innovation efficiency and influencing factors of listed textile and apparel companies research--Based on three-stage DEA with Tobit modeling.

Similar Datasets

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