Electronic Equipment Manufacturing Industry Research Articles

Intrafirm collaboration network dynamics, external cooperation network embeddedness, and firm knowledge search

ABSTRACT In the context of open innovation, firms urgently expand knowledge search and acquisition externally, forming complex interactions between internal networks and their knowledge exploration behaviours. However, prior research has overlooked network dynamics and treated internal networks as static. Drawing upon social network theory and the knowledge-based view, our study constructs a theoretical model that links intrafirm collaboration network dynamics with knowledge search within firms. We also investigated external contextual mechanisms such as the relationship strength, relationship breadth, and network centrality of corporate external networks. These moderate the relationship between intrafirm collaboration network dynamics and firms’ knowledge search. We empirically test the hypotheses using data from listed firms in the Chinese computer, communication, and electronic equipment manufacturing industry (C39) between 2014 and 2021. The results indicate that the intrafirm collaboration network dynamic has an inverted U-shaped effect on firms’ knowledge search breadth and depth. Relationship strength and network centrality weaken these effects.

Influencing factors and improvement paths of manufacturing innovation performance: Configuration analysis based on TOE framework.

Innovation is the first driving force to lead development, how to improve manufacturing innovation performance has become a hot topic. Based on 47 listed companies in the computer, communication and other electronic equipment manufacturing industry in the A-share market, this paper adopted the Fuzzy set qualitative comparative analysis (fsQCA) to explore the influencing factors of technology, organization and environment on the innovation performance of manufacturing industry and the improvement path. The findings are as follows: (1) A single condition is not a necessary condition for high innovation performance in manufacturing industry, but government support plays a key role in improving innovation performance in manufacturing industry. (2) There are two improvement paths for high innovation performance in manufacturing industry, which are specifically explained as "technology-environment dual improvement path" and "technology-organization-environment collaborative improvement path". (3) The improvement of innovation performance in the manufacturing industry is the result of multiple factors, showing the characteristics of "all paths lead to the same destination". Different manufacturing enterprises have different paths to improve innovation performance based on their actual conditions. Based on these findings, this study may provide some implications for the effective improvement of manufacturing innovation performance.

The impact of green finance on the optimization of industrial structure: Evidence from China.

Green finance promotes the optimization of industrial structure and continuous improvement of ecological environment by supporting the development of green industries. Based on the panel data of 30 provinces in China from 2012 to 2020, this paper uses the entropy weight TOPSIS method to measure the development level of green finance and the level of industrial structure optimization in China, and constructs a panel data model to empirically test the impact of green finance on the upgrading of China's industrial structure. The study finds that there is still an imbalance and insufficiency in the development of green finance and industrial structure optimization in China. From 2012 to 2020, the development level of green finance and the level of industrial structure optimization in China have been continuously rising, but there is obvious heterogeneity, showing an eastern>central>western spatial pattern. Empirical analysis results show that at the significance level of 1‰, the development of green finance has a significant promoting effect on the rationalization and upgrading of the industrial structure. However, there is significant heterogeneity in the impact of green finance on industrial structure optimization. In terms of regional heterogeneity, at the significance level of 1‰, the role of green finance in promoting the optimization of industrial structure in central and western China is higher than that in eastern China, and the impact of green finance on China's industrial structure shows a spatial pattern of western>central>eastern China. In terms of industry heterogeneity, at the significance level of 1‰, green finance has a significant promoting effect on the development of green industries, and a significant inhibiting effect on the development of high-energy-consuming industries. Specifically, in the green industry, green finance has the greatest promoting effect on the communication and other electronic equipment manufacturing industry; in the high-energy-consuming industry, green finance has the greatest inhibiting effect on the black metal smelting and rolling processing industry, and the smallest impact on the petroleum, coal and other fuel processing industry. Finally, based on this, policy suggestions for green finance to support the optimization of industrial structure are proposed from two dimensions: government and financial institutions.

A Study on the Economic Effects of U.S. Export Controls on Semiconductors to China

Purpose – This study addresses the development of China’s semiconductor industry in the context of the U.S.-China trade conflict, and analyzes the impact on other industries. Design/Methodology/Approach – Based on the multi-regional input-output table industry splitting method, the electrical and electronic equipment manufacturing industry in the Asian Development Bank’s multi-regional input-output table (ADB-MRIO, 2019) is split into semiconductor and non-semiconductor industries, and the impact of U.S. export controls on China’s semiconductor exports on domestic and foreign economies is simulated and analyzed using the hypothesis extraction and hypothesis expansion methods. Findings – The United States has suffered more than China from US export controls on semiconductors to China, and the impact of U.S. export controls on U.S. GDP decreasing by at most 0.0124‰, and China’s GDP decreasing by at most 0.00089‰. Since Japan, Korea, and European countries have become China’s semiconductor import substitutes, they all benefit from U.S. export controls on China. Second, the most affected industries in China are the chemical products, metal products, wholesale, financial, and non-semiconductor industries in the electrical and electronic equipment manufacturing industry. Research Implications – China should adopt coping strategies such as deepening international exchanges, enhancing communication between China and the U.S., and strengthening its scientific and technological strength.

Study on the factors of industrial electricity consumption behavior in Hunan Province based on multiple regression analysis

In recent years, Hunan province has gradually accelerated the adjustment of industrial structure, and has achieved a rapid industrial growth, thereupon the total amount of industrial electricity has increased greatly. There is an internal correlation between the industrial growth and electricity consumption. Therefore, based on this background, this paper established multiple linear regression models to study the influencing factors on the electricity consumption behavior of the three industries with the most electricity consumption in Hunan Province. The regression results show that the iron and steel output, raw coal price index and Mylpic mine price index can significantly affect the electricity consumption of ferrous metal industry. Cement output, cement price and real estate development investment can significantly affect the electricity consumption of non-metal industry. Automobile output, integrated circuit output and per capita disposable monthly income can significantly affect the electricity consumption of transportation and electrical and electronic equipment manufacturing industry in Hunan Province.

Evaluation of technological innovation efficiency in equipment manufacturing industry based on input orientation – Panel data analysis based on data envelopment model

By using CCR model, BCC model and scale efficiency method, this paper mainly analyzes the dynamic development trend of technological innovation efficiency in equipment manufacturing industry and its sub-sectors in 2010-2014 from input orientation, and finds out the change trend of technological innovation efficiency in equipment manufacturing industry and each sub-sector under the condition of certain output. It is found that technological innovation efficiency in computer and communications and other electronic equipment manufacturing industry, equipment manufacturing industry, electrical machinery and equipment manufacturing industry, metal products industry and transportation equipment manufacturing industry is relatively high, and that in the general equipment manufacturing, special equipment manufacturing industry, instrumentation and cultural and office machinery manufacturing industry ranks relatively backward which should be further improved. It is pointed out that in improving the efficiency of technological innovation, electrical, mechanical and equipment manufacturing industry and equipment manufacturing industry as a whole can only improve the efficiency of pure technology, and other sub sectors can improve their technological innovation efficiency by improving the efficiency of pure technology and scale efficiency.

An Input-Output Analysis of Financial Industry in China - Focusing on 2008 Financial Crisis -

본 연구의 연구결과를 살펴보면 다음과 같다. 중국 금융산업의 영향력 계수를 살펴보면, 2007년은 물 생산 및 공급제조업이 1.170069, 전력생산 및 공급제조업이 1.115053, 통신설비·컴퓨터 및 기타 전자설비제조업이 1.080031로 1.080031-1.170069에 분포되어 있었고, 이에 반해 2012년은 전문설비제조업이 3.780887, 물 생산 및 공급업이 2.623895, 계량/계측기 제조업이 1.340107을 알 수 있었다. 종합적으로 2007년에 비해 전반적으로 감응도계수 역시 변화 폭이 증가되었음을 알 수 있었다. 중국금융산업의 감응도 계수를 살펴보면, 2007년은 금융업이 1.957427, 임대서비스업이 1.359269, 제지인쇄 및 문방용품 제조업이 1.261815로, 1.261815-1.957427에 분포되어 있었고, 이에 반해 2012년은 화학공업이 3.451570, 금속제련 및 압연가공업이 2.891365, 전력/난방생산 및 공급이 1.932049을 알 수 있었다. 결론적으로 2007년에 비해 전반적으로 감응도계수 역시 변화 폭이 증가되었음을 알 수 있었다.This study looking at the results are as follows. First, Looking at the Impact Factor of China’s financial industry, 2007 was a water production and supply manufacturing is 1.170069, electricity production and supply manufacturing is 1.115053, communications equipment, computers and other electronic equipment manufacturing industry is 1.080031, that distributed from 1.080031 to 1.170069. A general increase in the change in the width of the impact factor compared to 2007. Second Looking at the sensitive Factor of China’s financial industry, 2007 was the financial industry is 1.957427, rental service industry is 1.359269, paper and printing supplies manufacturers munbang is 1.261815, that distributed from 1.261815 to 1.957427. Whereas in 2012, it can be seen that the overall sensitivity factor also increases the width change compared to 2007.

Unionisation and Firm Performance in China’s Manufacturing Industries

Using firm level data, this paper examines the link between unionisation and firm performance in China’s manufacturing industries. The empirical results suggest that unionisation has not greatly benefitted workers in China’s textile industry but it has contributed to much larger increase in average wages in both domestic and foreign invested firms in communication equipment, computer and other electronic equipment manufacturing industry. In the case of the general equipment manufacturing industry, unionised domestic firms pay higher average wages but there is no link between unionisation and average wage in foreign invested firms.