The impact of intrapreneurship on operators’ performance of Jordanian Telecom organizations

The creation and growth of new enterprises and, on the other hand, their decline and market exit are crucial factors of business dynamism and economic growth. Thus, business dynamism is an important aspect in the market chain and productivity of an economy, as well as a trigger for market reforms. The aim is to analyze business dynamism using Global Competitiveness Index 4.0 and its variables worldwide and to verify the relationship between business dynamism in the EU states and economic characteristics such as Valued added at factor cost, Enterprise Birth Rate and Enterprise Death Rate. Data were collected from the 2019 Global Competitiveness Report and from the EUROSTAT database, using the most recently updated source for each indicator. The 11th pillar of the Global Competitiveness Index, focused on business dynamics, and a set of indicators were analyzed using PCA to verify if all the variables are effective representatives of the concept. It was found out that the pillar does not effectively represent the concept of business dynamism in case of the EU countries; therefore the new pillar was constructed. A strong and statistically significant correlation between business dynamism and Value Added was confirmed. A relationship between business dynamism and other economic indicators was not proven. From a territorial point of view, Oceania achieved the best overall result in the analyzed field. The process of starting a new business is the most challenging in terms of start-up costs in South America. By contrast, the EU has reached the best result in this process.

The study aims to identify the financial performance measures used as a proxy of the firm-level competitiveness dimensions of small and medium-sized enterprises and their competitiveness. By investigating the factors that affect competitiveness in general, those areas will be introduced, related to an identified competitiveness dimension. Financial and non-financial performance indicators will assess these areas. The paper considers competitiveness as an outcome variable, suggests a relationship between financial performance and the identified areas, and searches for the financial performance measures drivers.
A panel data model was tested on Hungarian small and medium-sized enterprises (SMEs) and US SMEs. The collected data cover the period between 2013 and 2017. As a result of the applied panel regression, those variables were successfully identified that drive and could predict financial performance measures related to competitiveness. The research found a significant difference between the two-sample dataset results, which differences can be connected to country, industry, and, in general, to economic development characteristics.
The results provide decision-making support and hint about the managerial tools and techniques aiming to control the firm characteristics, performance, and, eventually, firm-level competitiveness. Based on the results, further research can be dedicated to the development characteristics of firm-level competitiveness and the analysis of the relationship between the competitiveness dimensions and competitiveness itself.

Acknowledgment
The research was financed by the Higher Education Institutional Excellence Programme of the Ministry for Innovation and Technology in Hungary, within the framework of the 4th thematic programme „Enhancing the Role of Domestic Companies in the Reindustrialization of Hungary” of the University of Pécs.

Integration or segmentation of markets determines whether substantial advantages in risk reduction can be attained through portfolio diversification in foreign securities. In an integrated market, investors face risk from country-specific factors and factors, which are common to all countries, but price only the later, as country-specific risk is diversifiable. The aim of this study is two-fold, firstly, investigating the superiority of the Fama-French three-factor model over Capital Asset Pricing Model (CAPM) and later using the superior model to test for integration of Indian and US equity markets (a proxy for global markets). Based on a sample of Bombay Stock Exchange 500 non-financial companies for the period 2003–2019, the data suggest the superiority of Fama-French three-factor model over CAPM. Using the Non-Linear Seemingly Unrelated Regression technique, the first half of the sample period (2003–2010) shows evidence of market segmentation; however, the second sub-period (2011–2019) shows weak signs of market integration, which is supported by the Johansen test of cointegration, suggesting that Indian market is gradually getting integrated with global markets.