R&amp;D Investment and Corporate Performance of Listed Chinese Medicine Companies Based on Big Data

Liu, Jiaxin

doi:10.1007/978-981-16-0115-6_64

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…A large number of studies have focused on the relationship between R&D capital input and innovation output, but no consistent research conclusions have been obtained. Different studies have concluded that there is a positive , negative (Liu & Xu, 2020), and inverted U-shaped relationship (Zhang, 2018). This paper argues that the reason for the negative impact of R&D capital input on innovation output is that high-tech enterprises have a longer cycle from R&D input to conversion into output, which is characterized by high initial investment costs (Liu & Wang, 2023).…”

Section: Spatial Lag Model Regression Resultsmentioning

confidence: 99%

Analysis of the spatial influences on innovation efficiency of enterprises with different ownership in China: high‐tech industry as an example

Shao,

Chen,

2024

Manage Decis Econ

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Enterprises have different behavioral characteristics depending on their ownership structure and their nature and play different roles in promoting economic development. In order to explore the innovation behavior characteristics of private enterprises, state‐owned enterprises, Hong Kong‐, Macao‐, and Taiwan‐funded enterprises, and foreign‐funded enterprises in China's high‐tech industry, this paper constructs spatial lag models and varying coefficient spatial lag models within the framework of knowledge production functions. It not only evaluates the technological innovation performance of various types of enterprises in high‐tech industries but also comprehensively explores the differences in the impact of external environments such as spatial dependence and business environment on the innovation efficiency of various types of enterprises. The results of the study provide a reference for enterprise managers and investors to efficiently allocate the scarce resources for innovation investment.

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Section: Spatial Lag Model Regression Resultsmentioning

confidence: 99%

Analysis of the spatial influences on innovation efficiency of enterprises with different ownership in China: high‐tech industry as an example

Shao,

Chen,

2024

Manage Decis Econ

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“…R&D investment primarily comprises capital expenditure and manpower investment. Therefore, when studying enterprise's R&D investment, key indicators encompass R&D capital investment and R&D personnel investment [44]. As a result, this paper designates (c) R&D capital investment and (d) R&D personnel investment as the conditional variables at this level.…”

Section: Enterprises' Randd Inputs (Resource Layer)mentioning

confidence: 99%

How does digital transformation improve new product development performance from the perspective of resource orchestration?—Analysis based on configuration

Zhang,

Hou,

Guo

2023

PLoS ONE

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The new product development (NPD) activities of enterprises serve as a critical source of competitiveness. To effectively harness the opportunities presented by digital transformation and enhance the performance of NPD in organizations amidst the digital revolution is an area of concern that warrants attention. In this context, we conducted research using data from the annual reports of 35 listed mainboard enterprises in 2021. This research used the resource arrangement theory and the resource-structure-capability research framework. In addition, we utilized the quantitative comparative analysis (QCA) method to investigate how digital transformation capability, R&D investment capability, and heterogeneity synergies impact the performance of NPD. The findings indicate that: (1) Four distinct paths (i.e., digital innovation-driven, large-scale multi-talent, mature and robust, and digital start-up) drive improvements in NPD performance. Notably, there exists an asymmetric causal relationship between these four paths and the performance; (2) Digital transformation capability, firm R&D investment, and firm heterogeneity all contribute to enhancing NPD performance. However, they do not individually guarantee high performance. A synergistic effect of at least two factors is required to yield notable NPD performance; (3) Enterprise heterogeneity plays a pivotal role. Companies with different characteristics must opt for distinct digital transformation paths to improve their NPD performance; (4) In the initial stage of digital transformation, enterprises can enhance NPD performance by augmenting their investment in R&D personnel.

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R&D Investment and Corporate Performance of Listed Chinese Medicine Companies Based on Big Data

Cited by 2 publications

References 5 publications

Analysis of the spatial influences on innovation efficiency of enterprises with different ownership in China: high‐tech industry as an example

Analysis of the spatial influences on innovation efficiency of enterprises with different ownership in China: high‐tech industry as an example

How does digital transformation improve new product development performance from the perspective of resource orchestration?—Analysis based on configuration

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