This study aims to explore the direct effect and spillover effect of innovation policy in the distribution and dynamic evolution of the regional innovation from the perspective of innovation motivation using the spatial econometric model. Substantive innovation and strategic innovation in one region could affect innovation in another region. In addition, the direct effect and spatial spillover effect of innovation policy could significantly affect innovation; however, they exert a higher impact on substantive innovation. Considering different policy tools, we found that government subsidies exert a significant positive impact on substantive innovation and strategic innovation, whereas financial institution loans exert a significant negative impact on substantive innovation and strategic innovation. And for the impact range, the government subsidies are higher than that of financial institution loans. Furthermore, this study reveals the leading environmental factors affecting regional innovation and provide a policy basis to promote the construction of an innovation-oriented country.
Manufacturing is one of the drivers of China’s growth, realizing structural upgrading is vital to achieve high-quality economic development during periods of economic policy uncertainty. Based on firm-level and province-level panel data from 1997 to 2018, this paper used a fixed effect panel data model and panel quantile regression model to investigate the effect of economic policy uncertainty on structural upgrading in manufacturing. The findings indicate that the effect of economic policy uncertainty on structural upgrading in manufacturing is significantly positive and great in regions at advanced stages of manufacturing structure. The discussion about the results suggests that the mechanism of economic policy uncertainty affecting structural upgrading in manufacturing operates through pushing the manufacturing industry to implement service transformation strategies along with vertical integration.
This paper focuses on the coordination and optimization between a manufacturer and multiple retailers in a supply chain. The manufacturer makes product quotes and delivery deadlines for all retailers, and each retailer selects product offers and delivery deadlines based on their own needs. Manufacturers maximize their own total profits by setting optimal quotes and delivery deadlines. This paper constructs the mathematical model of the optimal quotation and delivery deadline and proposes a scheduling algorithm that is different from the general M/M/1 and then studies the production scheduling problem and explores the effective implementation of quotation policy in management practice.
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