Tax incentives on R&D.

The long R&D process, the high risk, and the externalities of technological innovation are challenges that enterprises have to meet when making decisions on R&D investment. Governments share this risk with enterprises through preferential tax policies. We summarized China’s preferential tax policies related to enterprises and R&D innovation, and used panel data of listed enterprises from 2013 to 2018 in the Growth Enterprises Market (GEM) of the Shenzhen Stock Exchange to explore the incentive effects of current tax policies on the R&D innovation of enterprises. Through empirical analysis, we found that tax incentives significantly motivate R&D innovation input and promote output. In addition, we found that the income tax incentives are greater than that of the circulation tax, since the profitability of enterprise has a positive correlation with R&D investment. Meanwhile, the size of the enterprise is negatively correlated with the intensity of R&D investment.</div

Income tax policies.

The long R&D process, the high risk, and the externalities of technological innovation are challenges that enterprises have to meet when making decisions on R&D investment. Governments share this risk with enterprises through preferential tax policies. We summarized China’s preferential tax policies related to enterprises and R&D innovation, and used panel data of listed enterprises from 2013 to 2018 in the Growth Enterprises Market (GEM) of the Shenzhen Stock Exchange to explore the incentive effects of current tax policies on the R&D innovation of enterprises. Through empirical analysis, we found that tax incentives significantly motivate R&D innovation input and promote output. In addition, we found that the income tax incentives are greater than that of the circulation tax, since the profitability of enterprise has a positive correlation with R&D investment. Meanwhile, the size of the enterprise is negatively correlated with the intensity of R&D investment.</div

Robustness tests of tax incentives on R&D output performance.

Robustness tests of tax incentives on R&D output performance.</p

Tax incentives on R&D output performance.

The long R&D process, the high risk, and the externalities of technological innovation are challenges that enterprises have to meet when making decisions on R&D investment. Governments share this risk with enterprises through preferential tax policies. We summarized China’s preferential tax policies related to enterprises and R&D innovation, and used panel data of listed enterprises from 2013 to 2018 in the Growth Enterprises Market (GEM) of the Shenzhen Stock Exchange to explore the incentive effects of current tax policies on the R&D innovation of enterprises. Through empirical analysis, we found that tax incentives significantly motivate R&D innovation input and promote output. In addition, we found that the income tax incentives are greater than that of the circulation tax, since the profitability of enterprise has a positive correlation with R&D investment. Meanwhile, the size of the enterprise is negatively correlated with the intensity of R&D investment.</div

Robustness tests of tax incentives on R&D.

The long R&D process, the high risk, and the externalities of technological innovation are challenges that enterprises have to meet when making decisions on R&D investment. Governments share this risk with enterprises through preferential tax policies. We summarized China’s preferential tax policies related to enterprises and R&D innovation, and used panel data of listed enterprises from 2013 to 2018 in the Growth Enterprises Market (GEM) of the Shenzhen Stock Exchange to explore the incentive effects of current tax policies on the R&D innovation of enterprises. Through empirical analysis, we found that tax incentives significantly motivate R&D innovation input and promote output. In addition, we found that the income tax incentives are greater than that of the circulation tax, since the profitability of enterprise has a positive correlation with R&D investment. Meanwhile, the size of the enterprise is negatively correlated with the intensity of R&D investment.</div

Descriptive statistics.

The long R&D process, the high risk, and the externalities of technological innovation are challenges that enterprises have to meet when making decisions on R&D investment. Governments share this risk with enterprises through preferential tax policies. We summarized China’s preferential tax policies related to enterprises and R&D innovation, and used panel data of listed enterprises from 2013 to 2018 in the Growth Enterprises Market (GEM) of the Shenzhen Stock Exchange to explore the incentive effects of current tax policies on the R&D innovation of enterprises. Through empirical analysis, we found that tax incentives significantly motivate R&D innovation input and promote output. In addition, we found that the income tax incentives are greater than that of the circulation tax, since the profitability of enterprise has a positive correlation with R&D investment. Meanwhile, the size of the enterprise is negatively correlated with the intensity of R&D investment.</div

Preferential VAT policies.

The long R&D process, the high risk, and the externalities of technological innovation are challenges that enterprises have to meet when making decisions on R&D investment. Governments share this risk with enterprises through preferential tax policies. We summarized China’s preferential tax policies related to enterprises and R&D innovation, and used panel data of listed enterprises from 2013 to 2018 in the Growth Enterprises Market (GEM) of the Shenzhen Stock Exchange to explore the incentive effects of current tax policies on the R&D innovation of enterprises. Through empirical analysis, we found that tax incentives significantly motivate R&D innovation input and promote output. In addition, we found that the income tax incentives are greater than that of the circulation tax, since the profitability of enterprise has a positive correlation with R&D investment. Meanwhile, the size of the enterprise is negatively correlated with the intensity of R&D investment.</div

Efficient Synthesis of Long-Chain Highly Branched Polymers via One-Pot Tandem Ring-Opening Metathesis Polymerization and Acyclic Diene Metathesis Polymerization

A facile one-pot synthesis of long-chain highly branched polymers (LCHBPs) was accomplished by a tandem ring-opening metathesis polymerization (ROMP) and acyclic diene metathesis (ADMET) polymerization procedure. A telechelic polymer with two terminal allyloxy groups and many pendent acrylates was first prepared through the first generation Grubbs catalyst-mediated chain transfer ROMP of 7-oxanorborn-5-ene-exo,exo-2,3-dicarboxylic acid bis(2-(acryloyloxy)ethyl) ester in the presence of a symmetrical multifunctional olefin 1,4-diallyloxy-cis-2-butene as chain transfer agent (CTA), and then utilized as an A2B2n-type macromonomer in subsequent ADMET polymerization between allyloxy and acrylate triggered by the most activated second generation Grubbs catalyst, yielding LCHBPs as the reacton time prolonged. The CTA, monomer, macromonomer, and the resulting LCHBPs were characterized by mass spectroscopy, elemental analysis, gel permeation chromatography with multiangle laser light scattering, NMR and matrix-assisted laser desorption ionization time-of-flight mass measurements. The LCHBPs have comparatively high molecular weights and relatively moderate polydispersity indices

Descriptive statistics of variables.

The digital economy is a new impetus to promote high-quality economic development. We use the policies of Zhejiang Information Economy Development Demonstration Base (IEDD) and Zhejiang Software and Information Service Industry Base (SISI) established between 2015 and 2017 to design a quasi-natural experiment. By using a panel data from 2005 to 2020 in Zhejiang and the difference-in-differences model, we test the impacts of IEDD and SISI policies on digital economy development. We find that there are significant spatial differences for digital economy in Zhejiang. IEDD and SISI policies improve the digital economy development, that is, the policy advantages can indeed be transformed into industrial advantages. The IEDD policy can promote the digital economy industry development by enhancing the digital infrastructure and financial development; SISI policy can promote the development of the digital economy industry by promoting financial development. The results of quantile regression show that the promotion effect of IEDD and SISI policies increases with the improvement of the industrial basis of regional digital economy. The results of group regression show that the IEDD policy promotes the digital economy development in counties and county-level cities of Zhejiang, and the SISI policy plays a significant role in municipal districts.</div

Mesh-Clustered Gaussian Process Emulator for Partial Differential Equation Boundary Value Problems

Partial differential equations (PDEs) have become an essential tool for modeling complex physical systems. Such equations are typically solved numerically via mesh-based methods, such as finite element methods, with solutions over the spatial domain. However, obtaining these solutions are often prohibitively costly, limiting the feasibility of exploring parameters in PDEs. In this article, we propose an efficient emulator that simultaneously predicts the solutions over the spatial domain, with theoretical justification of its uncertainty quantification. The novelty of the proposed method lies in the incorporation of the mesh node coordinates into the statistical model. In particular, the proposed method segments the mesh nodes into multiple clusters via a Dirichlet process prior and fits Gaussian process models with the same hyperparameters in each of them. Most importantly, by revealing the underlying clustering structures, the proposed method can provide valuable insights into qualitative features of the resulting dynamics that can be used to guide further investigations. Real examples are demonstrated to show that our proposed method has smaller prediction errors than its main competitors, with competitive computation time, and identifies interesting clusters of mesh nodes that possess physical significance, such as satisfying boundary conditions. An R package for the proposed methodology is provided in an open repository.</p