scholarly journals Impact of Venture Capital in Strategic Emerging Industries on Enterprise Technological Innovation - Based on GEM

2018 ◽  
Author(s):  
Sun-Lei Yang ◽  
Kai-Lun Gao ◽  
Hui-Yun Tang ◽  
Run-Qiu Zhang
Keyword(s):  
Venture Capital ◽  
Technological Innovation ◽  
Emerging Industries

scholarly journals The Legal and Institutional Foundations of Silicon Valley’s Technological Innovation: An Interdisciplinary Literature Review

2021 ◽  
Vol 8 (3) ◽  
pp. 472-484
Author(s):  
S. D. Stone
Keyword(s):  
Venture Capital ◽  
Technological Innovation ◽  
Initial Public Offering ◽  
Silicon Valley ◽  
Business Culture ◽  
Venture Capitalists ◽  
Board Of Director ◽  
Institutional Relations ◽  
Major Factors ◽  
Public Offering

This article reviews interdisciplinary literature to explain how state legislation and the practice of law in California influenced the success of Silicon Valley in creating a startup business culture involving the commercialization of technologies built on venture capital finance. Scholarship has identified four major factors in the rise of Silicon Valley: business culture, symbiotic institutional relations with research universities, California contract and employment law, and Silicon Valley law firm culture. Both law and institutional support have been central to the commercialization of scientific knowledge that is the hallmark of Silicon Valley. Silicon Valley companies have remained leaders in technological innovation for over sixty years, encompassing various technologies from semiconductors to personal computers to the Internet. This entrepreneurial approach to technology continues to this day as exemplified by the successful DoorDash and Airbnb IPOs launched in 2020. The paradigmatic Silicon Valley technology company consists of a small group of entrepreneurs building a start-up technology company funded by a venture capital fund. The venture capitalists (VC) maintain hands-on management of the company and receive seats on the board of director and preferred stock rights. If the business plan is successful, the company offers shares to the public through an initial public offering (IPO), or arranges additional funding from another VC fund. This Silicon Valley model is characterized by a tolerance for failure and high labor mobility. Technology company employees have the freedom to leave established companies to start their own ventures.

scholarly journals The Impact of Innovation Investment Volatility on Technological Innovation of Enterprises in Different Life Cycles

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Miaomiao Li ◽  
Zhaoxing Hao ◽  
Meng Luan ◽  
Haibo Li ◽  
Guikun Cao
Keyword(s):  
Technological Innovation ◽  
Positive Impact ◽  
Punctuated Equilibrium ◽  
Life Cycles ◽  
Moderating Effect ◽  
Mature Stage ◽  
Punctuated Equilibrium Theory ◽  
Emerging Industries ◽  
The Impact ◽  
The Relationship

Empirical findings from the impact of innovation investment volatility on enterprise technological innovation are mixed. Based on the punctuated equilibrium theory, this study explores the impact of innovation investment volatility on enterprise technological innovation in different life cycles and whether innovation subsidy has expected effects on enterprises’ technological innovation. By using the 205 Chinese listed enterprises in strategic emerging industries from 2010 to 2019 as the research sample, the results show that the innovation investment volatility has a positive impact on technological innovation of enterprise in the growing stage, while it has no significant effect on enterprise technological innovation in the mature and declining stages. In addition, the negative moderating effect of innovation subsidy on the relationship between innovation investment volatility and technological innovation is the most significant for enterprises in the growing stage, weakly significant for enterprises in the mature stage, and insignificant for enterprises in the declining stage.

scholarly journals Research on the Technological Innovation Efficiency of China’s Strategic Emerging Industries Based on SBM: NDEA Model and Big Data

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zuchang Zhong ◽  
Fanchao Meng ◽  
Yuanbing Zhu ◽  
Gang Wang
Keyword(s):  
Big Data ◽  
Technological Innovation ◽  
Large Scale ◽  
Scale Efficiency ◽  
Eastern Region ◽  
Network Dea ◽  
Emerging Industries ◽  
Knowledge Innovation ◽  
Technological Efficiency ◽  
Level 2

Characterized by large scale, variety, fast generation, and extremely high value but low density, big data can be used to mine effective information, provide users with auxiliary decision-making, and realize its own value. Based on the nonoriented SBM and the network DEA model, this paper systematically and objectively evaluates the technological innovation efficiency of strategic emerging industries in all provinces of China in 2002–2013. The study found the following. (1) The overall technological efficiency of China’s strategic emerging industries is low. The average of comprehensive efficiency is 0.278; of 26 provinces, only 8 are above the average level. (2) The efficiency in the commercialization stage of scientific and technological achievements of strategic emerging industries in the whole country and most of the provinces is higher than that in the stage of knowledge innovation. The inefficiency of the knowledge innovation stage restricts the efficiency promotion of China’s strategic emerging industries. (3) The overall innovation efficiency of strategic emerging industries has been increasing from 2002 to 2013. In comparison, the growth rate of pure technical efficiency is larger than that of scale efficiency. (4) The overall efficiency, the efficiency in the knowledge innovation stage, and the efficiency in the commercialization stage of scientific and technological achievements of the eastern region are higher than those of the central and western regions.

scholarly journals The Complexity of Technological Innovation Decision-Making in Emerging Industries

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Wenjing Li ◽  
Xue Guo ◽  
Dan Cao
Keyword(s):  
Decision Making ◽  
Economic Policy ◽  
Dynamic System ◽  
Technological Innovation ◽  
Negative Binomial ◽  
Financing Constraints ◽  
Negative Binomial Regression Model ◽  
Investment Activity ◽  
Inhibition Effect ◽  
Emerging Industries

It is well known that innovation-driven emerging industries have gradually become the main driving force of global economic recovery and growth. Technological innovation decision-making is a complex and dynamic system, which is affected by various factors inside and outside an enterprise. In this dynamic system, how to make the optimal technological innovation investment decisions is a key concern for enterprises and governments. As an investment activity, technological innovation largely depends on the amount of external financing obtained by enterprises. However, financial constraints have increasingly become an obstacle to enterprises’ technological innovation. At the same time, technological innovation is also affected by the external political and economic environment, such as changes in economic policy, government subsidy policies, and institutional environmental policies. Can these external environments reduce the negative impact of financing constraints on technological innovation? In this study, based on the data of listed companies in China’s strategic emerging industries, we adopt a panel negative binomial regression model to investigate the complexity of technological innovation decision-making from the perspective of financing constraints. Our main findings include the following. First, financing constraints significantly inhibit the input and output of technological innovation in emerging industries. Second, the inhibition effect on the output of substantive innovations is more pronounced than that on the output of strategic innovations. Third, based on the analysis of enterprise heterogeneity in different dimensions, we show that this inhibition has a selective effect among different industries. Finally, we show that economic policy and marketization can help alleviate the inhibition effect of financing constraints on technological innovation.

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