scholarly journals The Impact of Venture Capital Expenditures on Innovation in Europe

2021 ◽  
Author(s):  
Angelo Leogrande ◽  
ALBERTO COSTANTIELLO ◽  
LUCIO LAURETI
Keyword(s):  
Panel Data ◽  
Venture Capital ◽  
Fixed Effects ◽  
Government Procurement ◽  
Advanced Technology ◽  
Capital Expenditures ◽  
High Tech ◽  
Technology Products ◽  
The Impact ◽  
The Relationship

Abstract We investigate the relationship between “Venture Capital Expenditures” and innovation in Europe. Data are collected from the European Innovation Scoreboard for 36 countries in the period 2010-2019. We perform Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS, Dynamic Panel. Results show that the level of Venture Capitalist Expenditure is positively associated to “Foreign Doctorate Students” and “Innovation Index” and negatively related to “Government Procurement of Advanced Technology Products”, “Innovators”, “Medium and High-Tech Products Exports”, “Public-Private Co-Publications”. In adjunct, cluster analysis is realized with the algorithm k-Means and the Silhouette coefficient, and we found the presence of four different clusters for the level of “Venture Capital Expenditures”. Finally, we propose a confrontation among 8 different algorithms of machine learning to predict the level of “Venture Capital Expenditures” and we find that the linear regression generates the best results in terms of minimization of MAE, MSE, RMSE.

scholarly journals The SMEs Innovation in Europe

2021 ◽  
Author(s):  
Alberto Costantiello ◽  
Laureti Lucio ◽  
Leogrande Angelo
Keyword(s):  
Panel Data ◽  
Population Density ◽  
Fixed Effects ◽  
Government Procurement ◽  
Advanced Technology ◽  
High Tech ◽  
Dynamic Panel ◽  
Technology Products ◽  
Firm Investments ◽  
Intellectual Assets

Abstract In this article we investigate the determinants of SMEs Innovation in Europe. We use data from the European Innovation Scoreboard of the European Commission in the period 2000-2019 for 36 countries. Data are analyzed through Panel Data with Fixed Effects, Random Effects, Dynamic Panel at 1 Stage and WLS. Results show that the presence of Innovators is positively associated with “Enterprise births”, “Government Procurement of Advanced Technology Products”, “Firm Investments”, “Intellectual Assets”, “Sales Impacts”, “Share High and Medium High-Tech Manufacturing” and negatively associated to “FDI Net Inflows” and “Population Density”.

scholarly journals Human Resources in Europe. Estimation, Clusterization, Machine Learning and Prediction

2021 ◽  
Author(s):  
ANGELO LEOGRANDE ◽  
ALBERTO COSTANTIELLO
Keyword(s):  
Machine Learning ◽  
Human Resources ◽  
Fixed Effects ◽  
Tertiary Education ◽  
Government Procurement ◽  
Machine Learning Algorithms ◽  
Advanced Technology ◽  
High Tech ◽  
Technology Products ◽  
Using Data

Abstract We estimate the relationships between innovation and human resources in Europe using the European Innovation Scoreboard of the European Commission for 36 countries for the period 2010-2019. We perform Panel Data with Fixed Effects, Random Effects, Pooled OLS, Dynamic Panel and WLS. We found that Human resources is positively associated to “Basic-school entrepreneurial education and training”, “Employment MHT manufacturing KIS services”, “Employment share Manufacturing (SD)”, “Lifelong learning”, “New doctorate graduates”, “R&D expenditure business sector”, “R&D expenditure public sector”, “Tertiary education”. Our results also show that “Human Resources” is negatively associated to “Government procurement of advanced technology products”, “Medium and high-tech product exports”, “SMEs innovating in-house”, “Venture capital”. In adjunct we perform a clusterization with k-Means algorithm and we find the presence of three clusters. Clusterization shows the presence of Central and Northern European countries that has higher levels of Human Resources, while Southern and Eastern Europe has very low degree of Human Resources. Finally, we use seven machine learning algorithms to predict the value of Human Resources in Europe Countries using data in the period 2014-2021 and we show that the linear regression algorithm performs at the highest level.

scholarly journals The Broadband Penetration in Europe

2021 ◽  
Author(s):  
Angelo Leogrande ◽  
ALBERTO COSTANTIELLO ◽  
LUCIO LAURETI
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Polynomial Regression ◽  
Government Procurement ◽  
Machine Learning Algorithms ◽  
Advanced Technology ◽  
Technology Products ◽  
Firm Investments ◽  
Intellectual Assets ◽  
Knowledge Intensive

Abstract In this article we estimate the determinants of broadband penetration in Europe. We use data from the European Innovation Scoreboard of the European Commission for 37 countries in the period 2010-2019. We apply Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, OLS and Dynamic Panel. We found that the level of “Broadband Penetration” in Europe is positively associated to “Enterprises Providing ICT Training”, “Innovative Sales Share”, “Intellectual Assets”, “Knowledge-Intensive Service Exports”, “Turnover Share SMEs”, “Innovation Friendly Environment” and negatively associated with “Government procurement of advanced technology products”, “Sales Impact”, “Firm Investments”, “Opportunity-Driven Entrepreneurship”, “Most Cited Publications”, “Rule of Law”. In adjunct we perform a clusterization with k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of three different clusters. Finally, we apply eight machine learning algorithms to predict the level of “Broadband Penetration” in Europe and we find that the Polynomial Regression algorithm is the best predictor and that the level of the variable is expected to increase of 10,4%.

scholarly journals The Intellectual Assets in Europe

2021 ◽  
Author(s):  
Costantiello Alberto ◽  
Laureti Lucio ◽  
Leogrande Angelo
Keyword(s):  
Fixed Effects ◽  
Government Procurement ◽  
Advanced Technology ◽  
High Tech ◽  
Dynamic Panel ◽  
Research Systems ◽  
Technology Products ◽  
Employment Share ◽  
Intellectual Assets ◽  
Knowledge Intensive

Abstract In this article we investigate the determinants of the Intellectual Assets in Europe. We use data from the European Innovation Scoreboard of the European Commission in the period 2000-2019 for 36 countries. Data are analyzed using Panel with Fixed Effects, Random Effects, WLS, Pooled OLS, Dynamic Panel at 1 Stage. Results show that the presence of Intellectual Assets in Europe is positively associated with “Enterprise Births”, “Top R&D Spending Enterprises per 10 mln Population”, “Employment Share Manufacturing”, “Share High and Medium high-tech Manufacturing”, “Attractive Research Systems”, “Finance and Support”, “Innovators”, “Sales Impact” and is negatively associated to “Government Procurement of Advanced Technology Products” and “Share Knowledge-Intensive Services”

scholarly journals The impact of technological innovation on carbon emissions

2021 ◽  
Vol 275 ◽  
pp. 02039
Author(s):  
Jing Niu
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Technological Innovation ◽  
Carbon Emissions ◽  
Fixed Effects ◽  
Low Carbon ◽  
Fixed Effects Models ◽  
Low Carbon Technologies ◽  
The Impact ◽  
The Relationship

Environmental problems caused by carbon emissions have received widespread attention, and technological innovation has an important impact on carbon emissions. This paper uses data from 30 provinces (excluding Tibet) in China from 2009 to 2018 as a sample, and empirically analyzes the relationship between technological innovation and carbon emissions by constructing panel data and fixed effects models. The results show that technological innovation can curb carbon emissions. Therefore, China should increase research and application of low-carbon technologies to promote sustainable economic development.

Retrospective analysis of the resilience of Russian regions as socio-economic systems

2019 ◽  
pp. 46-64 ◽  
Author(s):  
Vladimir V. Klimanov ◽  
Sofiya М. Kazakova ◽  
Anna A. Mikhaylova
Keyword(s):  
Panel Data ◽  
Economic Systems ◽  
Financial Indicators ◽  
Russian Regions ◽  
Integral Index ◽  
Negative Effects ◽  
Economic Resilience ◽  
Correlation Dependence ◽  
The Impact ◽  
The Relationship

The article examines the impact of various socio-economic and financial indicators on the resilience of Russian regions. For each region, the integral index of resilience is calculated, and its correlation dependence with the selected indicators is revealed. The study confirms the relationship between fiscal resilience and socio-economic resilience of the regions. The analysis of panel data for 75 regions from 2007 to 2016 shows that there are significant differences in the dynamics of indicators in different periods. In particular, the degree of exposure to the negative effects of the crises of 2008—2009 and 2014—2015 in non-resilient regions is higher than in resilient ones.

scholarly journals Environmental Management, Green Innovation, and Social–Open Innovation

2021 ◽  
Vol 7 (1) ◽  
pp. 89
Author(s):  
Pham Thu Huong ◽  
Jacob Cherian ◽  
Nguyen Thi Hien ◽  
Muhammad Safdar Sial ◽  
Sarminah Samad ◽  
...  
Keyword(s):  
Environmental Management ◽  
Stock Exchange ◽  
Advanced Technology ◽  
Green Innovation ◽  
Social Image ◽  
Whole Process ◽  
Corporate Environmental Management ◽  
The Impact ◽  
The Relationship

The present study aims to determine the impact of green innovation (GI) on the overall performance of an organization while keeping the variable of environmental management (EM) as a moderator. We used a dataset consisting of four data years, from 2014 to 2017, of A-share companies listed on the Shanghai Stock Exchange (SSE). The concept of green innovation refers to the use of advancements in technology that enable savings in energy, along with the recycling of waste material. When advanced technology is utilized in the production process, the products are referred to as green products and the whole process of adopting such technologies and product design is referred to as “Corporate Environmental Management”. Such innovations improve the overall financial performance of companies as it enables them to improve their social image by reducing their carbon footprint and ensures their long-term sustainability. The main issue is the limited focus and attention given to the topic, from the perspective of companies. This research focuses on the impact of green innovation and the importance of environmental management for the sustainability of companies. Our findings suggest that the relationship between green innovation and the performance of the company is positive and verifies the existence of moderating effects of environmental management on the relationship between green innovation and firm performance. Implications are given to academia and practitioners.

Managers' and auditors' narcissism on the management team's stability and relative corporate performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Salehi ◽  
Safoura Rouhi ◽  
Mohana Usefi Moghadam ◽  
Faezeh Faramarzi
Keyword(s):  
Significant Relationship ◽  
Fixed Effects ◽  
Corporate Performance ◽  
Stock Exchange ◽  
Relative Performance ◽  
Psychological Characteristics ◽  
Content Type ◽  
The Impact ◽  
The Relationship ◽  
Performance Research

PurposeSuccess in corporate relative performance is one of the factors for the growth and durability of firms. Since the relative performance is a function of managers' decisions and such decisions are under the influence of behavioral and psychological characteristics, this paper aims to assess the managers’ and auditors’ narcissism's effect on the management team's stability relative to corporate performance.Design/methodology/approachThis paper has used the signature magnitude for examining narcissism and the regression model of Jenter and Kanaan (2015) for assessing relative corporate performance. The logistic regression is used to test the model of the management team's stability, and the multivariate regression is used to test the model of relative corporate performance. Research hypotheses were also examined using a sample of 768 listed year-companies on the Tehran Stock Exchange during 2012–2017 and by employing a panel data approach and fixed effects method.FindingsThe obtained results show a negative and significant relationship between managers' and auditors' narcissism and the management team's stability. The relationship between the narcissism of managers and auditors and relative corporate performance is positive and significant. Moreover, managers' narcissism positively and significantly impacts the relationship between auditors' narcissism and team management stability. A negative and significant relationship is evident between auditors’ narcissism and relative corporate performance.Originality/valueThis study's results can identify the effect of psychological components such as narcissism on people's performance by directing and influencing their decisions. Many studies have been conducted on narcissism, but none of them have examined the impact auditors’ and managers' narcissism has on the management team's stability and the corporate relative performance. Therefore, considering the importance of success in the corporate relative performance and benefits of the management team's stability, this study's results can reveal the importance of such features in accounting research. Also, the results of this research can make it important to know more about financial behavioral theory.

Assessing the Impact of the Factors in the Digital Transformation on the Regional Economic Growth

REGIONOLOGY ◽  
2021 ◽  
Vol 29 (3) ◽  
pp. 486-510
Author(s):  
Tatyana V. Mirolyubova ◽  
Marina V. Radionova
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Digital Transformation ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
The Russian Federation ◽  
Regional Product ◽  
The Impact ◽  
Regions Of Russia

Introduction. The scientific problem under consideration is of particular relevance due to the need to assess the impact of the factors in the digital transformation of the regional economy and in the economic growth on the economic development of the regions of the Russian Federation. Based on the research conducted, the article presents an econometric assessment of the dependence of the level of the gross regional product per capita in the regions of Russia on such factors as digital labor and digital capital. Materials and Methods. The authors analyzed panel data from the Federal State Statistics Service covering 87 regions of Russia for the period from 2010 to 2018. The research methodology is based on the use of the Cobb–Douglas production function, statistical and correlation data analysis, as well as on econometric methods for studying panel data. Results. To analyze the impact of the digital transformation of the economy on the regional economic growth of the regions of Russia, various models based on panel data have been considered, such as the pooled model, fixed effects models, random effects models, as well as time-varying effects models using dummy variables. Based on statistical criteria, the best model has been chosen and conclusions have been drawn about the nature of the impact of the digital transformation indicators on the gross regional product per capita in the regions of Russia. Discussion and Conclusion. The results of econometric modeling have demonstrated that digital factors in economic growth (digital labor, digital capital), along with common factors in economic growth (labor and capital), affect the regional economic growth. According to the regional data for the period from 2010 to 2018, the time fixed effects model has proved to be the best model of the impact of the factors in economic growth and digital transformation on the economic development of the regions of the Russian Federation. The research results can be used when developing a public policy aimed at stimulating the digital transformation of the regional economy.

scholarly journals Malpractice Environment vs Direct Litigation: What Drives Nursing Home Exit?

2018 ◽  
Vol 55 ◽  
pp. 004695801878799
Author(s):  
R. Tamara Konetzka ◽  
Hari Sharma ◽  
Jeongyoung Park
Keyword(s):  
Nursing Home ◽  
Nursing Homes ◽  
Fixed Effects ◽  
Online Survey ◽  
Market Competition ◽  
Consumer Welfare ◽  
Data Sets ◽  
For Profit ◽  
The Impact ◽  
The Relationship

An ongoing concern about medical malpractice litigation is that it may induce provider exit, potentially affecting consumer welfare. The nursing home sector is subject to substantial litigation activity but remains generally understudied in terms of the effects of litigation, due perhaps to a paucity of readily available data. In this article, we estimate the association between litigation and nursing home exit (closure or change in ownership), separating the impact of malpractice environment from direct litigation. We use 2 main data sources for this study: Westlaw’s Adverse Filings database (1997-2005) and Online Survey, Certification and Reporting data sets (1997-2005). We use probit models with state and year fixed effects to examine the relationship between litigation and the probability of nursing home closure or change in ownership with and without adjustment for malpractice environment. We examine the relationship on average and also stratify by profit status, chain membership, and market competition. We find that direct litigation against a nursing home has a nonsignificant effect on the probability of closure or change in ownership within the subsequent 2 years. In contrast, the broader malpractice environment has a significant effect on change in ownership, even for nursing homes that have not been sued, but not on closure. Effects are stronger among for-profit and chain facilities and those in more competitive markets. A high-risk malpractice environment is associated with change of ownership of nursing homes regardless of whether they have been directly sued, indicating that it is too blunt an instrument for weeding out low-quality nursing homes.

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