National Technological Innovation Output Capacity Forecast and its Influence Factors Analyses in China

2011 ◽  
Vol 65 ◽  
pp. 568-573
Author(s):  
Xiao Hong Li
Keyword(s):  
Public Education ◽  
Technological Innovation ◽  
Statistical Data ◽  
Influence Factors ◽  
External Environment ◽  
Total Degree ◽  
Output Capacity ◽  
Innovation Activities ◽  
Dependent Variables ◽  
Innovation Output

This paper aims to measure nation technological innovation output capacity and its developing tendency of China. The influence factors that impact the output of national innovation mainly come from three aspects. They are technological innovation activities, innovation external environment, and potential technological innovation resources. We finally adopt four factors (Expenditure for R&D (X1), Governmental capitals for R&D with percentage of GDP (X2), R&D persons per million labors (X3), Expenses of public education with percentage of GDP (X4)) to estimate the innovation output (measure by number of patents application accepted). Results of regression model that uses statistical data from 1989 to 2009 indicate total degree of correlation between them is 99.9%. All Variables play significant linear actions to dependent variables Y except X4. The number of patents application accepted per million persons is 9.518 (1276 thousand pieces in total) in 2010, with an error of 4.42%. This study may be useful for innovation output prediction and relevant decision making of China.

Study on Prediction of the Peasants’ Income Based on SVM

2014 ◽  
Vol 687-691 ◽  
pp. 5169-5172
Author(s):  
Li Na Zhang ◽  
Bo Yang
Keyword(s):  
Social Factors ◽  
Index System ◽  
Statistical Data ◽  
Influence Factors ◽  
Prediction Method ◽  
Svm Model ◽  
The Index System ◽  
Relationship Of ◽  
System Designs ◽  
Computing Speed

China is a big agricultural country, effective prediction of peasants’ income is very important. This study mainly uses the SVM theory to predict the peasants’ income. By analyzing the influence factors of peasants’ income, establishes the index system, that is corresponding relationship of peasants’ income and factors of social influence, According to this index system, designs the prediction method of peasants’ income based on SVM. Bases on the statistical data of social factors and peasants’ income between 1990-2012 in china, to train the SVM model, at the same time, the kernel function and parameters of SVM used were setting and compared. The experimental results show that the accuracy of RBF function is 90.7%, the time is 98ms, has higher accuracy and faster computing speed.

She-E-Os and innovation: do female CEOs influence firm innovation?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hafiz Mustansar Javaid ◽  
Qurat Ul Ain ◽  
Antonio Renzi
Keyword(s):  
Financial Constraints ◽  
Ordinary Least Squares ◽  
State Ownership ◽  
Corporate Environment ◽  
Firm Innovation ◽  
Content Type ◽  
Innovation Activities ◽  
Female Ceos ◽  
Innovation Output ◽  
The Impact

PurposeThis paper empirically investigates whether female CEOs (She-E-Os) have an effect on firm innovation among Chinese listed firms based on patent data. This study also delved further by looking at whether the internal corporate environment moderates the effect of female CEOs on innovation, that is, state ownership. Finally, this study investigates an additional test of financial constraints to examine whether financial constraints also moderate the impact of female CEOs on firm innovation.Design/methodology/approachThis study used the data of all A-share listed companies on the Shanghai and Shenzhen stock exchanges for the period from 2008 to 2017. The authors use ordinary least squares regression as a baseline methodology, along with firm-fixed effect, lagged measure of female CEOs, alternative measures of innovation, Heckman two-step model and negative binomial regression to check and control the possible issue of endogeneity.FindingsThe authors’ findings show that CEO gender plays an important role in producing higher levels of innovation output by improving the governance structure. However, female CEOs have no effect on state-owned enterprises' (SOEs) innovation activities, which suggests that the main goal of SOEs is achieving sociopolitical objectives. Furthermore, female CEOs' influence on innovation output is weaker in firms with financial constraints.Social implicationsThis study adds to the emerging global discussion on gender diversity. Many legislative bodies require a quota for women on corporate boards due to gender inequality. This study's findings reinforce such guidelines by emphasizing the economic benefits of including women in top management positions.Originality/valueThis study provides new insights by highlighting the role of female CEOs in increasing firms' innovation activities. Additionally, this study provides evidence on whether the internal corporate environment (state ownership and financial constraints) moderates female CEOs' effect on innovation.

THE ROLE OF WOMEN IN THE PUBLIC EDUCATION OF THE SURKHAN OASIS(ON EXAMPLE IN THEYEARS OF INDEPENDENCE)

2021 ◽  
Vol 4 (6) ◽  
pp. 62-66
Author(s):  
Sabohat B. Radjabova ◽  
Keyword(s):  
Public Education ◽  
Education System ◽  
Statistical Data ◽  
The State ◽  
Work Activities ◽  
The Public ◽  
Role Of Women

It is scientifically analyzed information about the activity of women in the education system of Surkhandarya region in the period of independence years and their achievements in this field through statistical data with examples over the years in this article. It is emphasized that the state pays attention to the work activities of selfless women, who have been awarded many medals and medals in this region, such as the Medal of “Shukhrat”, the Order of “Saglom avlod uchun”, the title of "Xalk ta`limi a`lochisi", is also mentioned separately

Technological Innovation in Family Firms

2020 ◽  
pp. 168-190
Author(s):  
Mario Ossorio
Keyword(s):  
Technological Innovation ◽  
Family Firms ◽  
Innovation Management ◽  
Innovation Process ◽  
Family Ownership ◽  
The Third ◽  
The Family ◽  
Innovation Output ◽  
Innovation Strategies ◽  
External Actors

This chapter illustrates the main issues with respect to innovation process within family firms. In the first part, it describes the main theories underlying the innovation process of family firms (agency theory, altruism, portfolio theory, stewardship theory, socioemotional wealth perspective). In the second part, it exposes the R&D underinvestment problem in large companies with a focus on the effect of the family ownership on the R&D investments. In the third part, it describes the effect of family ownership on the innovation output with a focus on the kind of innovation (radical vs. incremental). In the fourth section, studies exploring the innovation strategies of family firms (prospectors, analysers, defenders, reactors) are examined. In the fifth section, it sheds light on the innovation management process of family firms. In this part, it explores the issues of internal innovation process (functional vs. cross-functional structure) and of the partnerships with external actors aimed to generate innovation.

scholarly journals Analysis of the Effect of R&D Planning Support for SMEs Using Latent Growth Modeling

2020 ◽  
Vol 12 (3) ◽  
pp. 1018
Author(s):  
Ju Hwan Seo ◽  
Daemyeong Cho
Keyword(s):  
Technological Innovation ◽  
Growth Modeling ◽  
Latent Growth Modeling ◽  
Sustainable Growth ◽  
Policy Support ◽  
Technology Commercialization ◽  
Latent Growth ◽  
Planning Stage ◽  
Planning Support ◽  
Innovation Activities

Small and medium enterprises (SMEs) in Korea play a pivotal role in the national economy. However, due to scale limitations, the resources available to SMEs for innovation activities are limited. Therefore, as a means to compensate for the market failure of SMEs, which can be caused by resource limitations, and to ensure sustainable growth, the government supports the SMEs for innovation activities. Korea has fulfilled SME R&D planning support projects since 2002 to efficiently support SMEs’ technology commercialization activities through systematic support in the early stages of the technology commercialization cycle. In order to analyze the effectiveness of SME R&D planning support program, this study conducted latent growth modeling analysis using financial data of three years of SMEs participating in the program. According to the analysis results, SMEs receiving R&D planning support funds have an increase in sales compared to those that do not. In particular, it was analyzed that the sales increase effect of companies supported by R&D funds continuously appeared more clearly. The result of this analysis is that policy support for SMEs can help technological innovation activities necessary for R&D planning, which is an early stage of SME technological innovation. This study is meaningful in that it quantitatively analyzes using latent growth model and the contribution of government support at the R&D planning stage to SMEs’ innovation capabilities and their contribution to performance. However, it has a limitation that it does not address the specific impact path of the planning stage support on innovation capacity and innovation performance.

scholarly journals Influence Factors of Spatial Distribution of Urban Innovation Activities Based on Ensemble Learning: A Case Study in Hangzhou, China

2020 ◽  
Vol 12 (3) ◽  
pp. 1016 ◽  
Author(s):  
Jiwu Wang ◽  
Nina Liu ◽  
Yichen Ruan
Keyword(s):  
Spatial Distribution ◽  
Public Transportation ◽  
Influence Factors ◽  
Impact Mechanism ◽  
Location Selection ◽  
Innovation Activities ◽  
Innovation Space ◽  
Ensemble Algorithms ◽  
The Impact

Innovation is an inevitable way for cities to achieve sustainable development. The occurrence of innovation activities is a complex systemic behavior. Its spatial distribution has some location selection laws, which are the result of interaction and feedback between various spatial influence factors. We explain the impact mechanism from the microscale using a street unit in a city. Hangzhou was selected as a case study. First, we systematically selected factors influencing the spatial distribution of innovation activities as the independent variable based on the demands of innovation subjects. Patents were used as the dependent variable to represent the spatial distribution of innovation activities. Second, ensemble algorithms (Boosting) were used to analyze the influence contribution of independent variables to dependent variables. Then, based on the aspects of innovation driving force, which are innovation resources and innovation environments, relevant factors were divided into the following seven categories: innovation industry concentration, knowledge intensity, innovative talent resources, service facilities, external transportation convenience, public transportation convenience, and ecological environment. We interpreted the impact mechanism and made corresponding suggestions for urban innovation space planning.

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