Suchergebnisse

The Chinese government is going to &ldquo ; push ahead the revolution of energy production and consumption, and establish a clean, low-carbon, secure, and efficient energy system&rdquo ; which points out a direction for the energy industry in the new era. Using the analytic hierarchy process of the system analysis method, we constructed an indicator system of the modern Chinese energy system, and by determining the weighting of each indicator, we obtained the composite index of the modern Chinese energy system, as well as four sub-indexes of clean, low-carbon, secure, and efficient. Then, we investigated policy changes and energy development characteristics of important periods, and performed historical trend analysis. Finally, we forecasted the composite index and four sub-indexes by 2050, and proposed an energy development path and policy suggestions to achieve a modern Chinese energy system as soon as possible.

This paper introduces a new composite index - the financial supply index (FSI), which measures the level of supply of foreign capital to 11 EU new member states (NMS). We aim to fill the gap in the literature, which has so far focused on creating indices that measure the financial conditions only, while the economic factors, also important determinants of capital flows, have been overlooked. FSI includes both the financial and economic determinants of capital flows and is estimated using Kalman filtering, principal components and variance-equal weights approach. Three financial supply cycles in NMS could be extracted based on the analysis of FSI dynamics. The results indicated that the main drivers of financial supply to NMS are externally determined, with economic sentiment and business climate in the Eurozone carrying the highest weight. In addition, we create a new indicator - the Refinancing Risk Ratio (RRR), which relates the supply and demand for foreign capital, to quantify the external refinancing conditions and risk faced by the government. We are able to distinguish between two main episodes of high refinancing risk faced recently by the EU NMS - one during the global financial crisis, and the other during the European sovereign debt crisis, but the episodes significantly differ in nature.

Convergence study is related to several crucial issues. One of those problems is an individual character of every region in the selected area, as the regions established accordingly to the European classification system NUTS-2 are not homogeneous. Therefore, while analysing convergence in the European Union, regions with extremely dissimilar characteristics (for example GDP per capita) are taken under consideration. Absolute β-convergence means that all of the investigated regions tend to the same level of economic growth. Thus, among the regions with highly differential amounts of the examined variables the convergence hypothesis can be rejected. Due to the heterogeneity in the conducted investigation a classification based on the composite index will be used so that the convergence clubs could be established. Several approaches to convergence will be used according to those regimes. Moreover, there will be an attempt to indicate the determinants that differentiate the selected regions, such as: expenditure on R&D, HRST, quantity of patents, employment, participation of people in tertiary education among all employees. This will allow the analysis of conditional β-convergence to be conducted. In the investigation some methods and models offered by the spatial statistics and econometrics will be used. There are empirical proofs that geographical location has a great impact on the processes of economic growth. Consequently, spatial dependencies will be analysed as well.

This paper aims to assess the profitability and employees' productivity of Italian innovative start-ups with a new composite index: the Start-ups Performance score (SP-score). In recent years, the Italian government has made several efforts to foster the economy, establishment, and growth of start-ups. Specifically, the issuing of the Italian Start-up Act in 2012 offers a unique opportunity to examine the Italian setting, given the special conditions that the government granted to the start-ups. The latter obtain generic benefits, tax reductions and hiring facilitations if they meet specific criteria granting the status (label) of "innovative" by law. Based on a sample of Italian start-ups firms (ISPs) and financial statement data for the period 2016–2020, we test whether the performance of the Italian start-ups which are granted the status of "innovative" is higher compared to start-ups without the mentioned status (NISPs). We measure the firm's performance by building a composite index which synthesizes both profitability and employees' productivity (controlling for the firms' size), and find that the ISPs report higher SP-score compared to the NISPs. In addition, we examine whether the SP-score is higher (or lower) among Innovative start-ups located in different regional areas. The derivation of the composite indicator (SP-score) allows a clear and effective evaluation of several characteristics, permitting a more comprehensive understanding of the data that support the strategic choices of management and localization entrepreneurship policies. In addition, our study highlights a certain homogeneity of innovative start-ups' performance among the Italian territories, which overcomes the classic dualistic division between Northern and Southern regions.

AbstractThe main objective of this research is to propose the best aggregate index of corporate social responsibility practice at the organisational level. To achieve this, we analyse the consistency of the different aggregated measures that researchers use in their analyses through a robust statistical technique, the CUR matrix, framed in the big data environment for selecting individuals. Accordingly, we use an international sample of 2,675 large listed companies. The results show that the CUR leverage identifies greater consistency of the different aggregate measures of CSR, confirming its coherence with a correlation analysis. In this sense, it is possible to affirm that the composite indexes used in academia do not introduce any bias into the analysis of CSR practices. In addition, we demonstrate the utility of this technique to identify the most powerful companies, analysing their CSR commitment at the country and industry levels, namely, Norsk Hydro in the metal and mining industry in Norway, Stora Enso in forestry and paper in Finland, Akzo Nobel in chemical products in the Netherlands, BMW in automobiles and parts in Germany, Generali in finance in Italy, Novartis in pharmaceuticals in Switzerland, the BT Group in telecommunications in the United Kingdom and Inditex in textiles in Spain. Moreover, the results of the CUR study confirm that companies adapt to the demands or pressures from the stakeholders in different areas of interest, which are specific to each country and industry. The availability of these data allows the identification of the structural drivers of their growth and the establishment of priorities that allow the design of more effective sustainable development momentum policies.

[EN] In recent years, a body of scientists has dedicated themselves to measuring and explaining the negative impacts on the environment. Some propositions have emerged through the use of different variables and methods. However, the conclusions about ecological damage are still controversial and a subject of current debate. The present study focuses on this agenda. The starting point is the development of an environmental composite index called Composite Index of Environmental Performance (CIEP), used to measure ecological quality within countries. It is developed using 19 single variables grouped into 5 dimensions according to the driving force¿pressure¿state¿exposure¿effect¿action (DPSEEA) model framework. Moreover, the robustness test is performed in order to check the level of information quality and the rate of the score variation if further methodologies were used. Based on this tool, a ranking is created with 152 analyzed countries over a period 6 years, and then, it is compared with another composite index, the Environmental Performance Index (EPI). Through the comparative analysis, it is observed that the CIEP and EPI used around 20% of the same single variables, and that the rate of ranking variation between both indexes was 21%. Furthermore, an econometric model is developed to analyze the correlation between economic development and environmental performance. The outputs do not support the EKC hypothesis. To conclude, an exploratory model is run in order to explain the ecological quality of the countries studied. Some highlights are found with the produced outputs. It is observed that, in general, the best and the worst environmental performances remain in the same rank during the analyzed period. At the top are the richer, democratic countries, localized in Europe. On the other hand, the worst environmental performances are achieved by the non-democratic and poorest countries, localized in Africa. Furthermore, a positive effect is observed regarding the socio-political aspects on the environmental performance.

The purpose of this contribution is to develop a Circular Economy Composite indicator to benchmark EU countries performance. Europe is at the forefront of the global transition towards a sustainable and circular economy. To this end, the European Commission has launched in 2015 a Circular Economy Action Plan including a monitoring framework to measure progress and to assess the effectiveness of initiatives towards the circular economy in the European Union (EU) and Member States. Still, this monitoring framework lacks a composite indicator at the national level to aggregate the circular economy dimensions into a single summary indicator. Although there is a wide range of sustainability composite indicators, no aggregate circular economy index exits to this date. We use a multi-criteria approach to construct a circular economy composite index based on TOPSIS (Technique for Order Preferences by Similarity to Ideal Solutions) methodology. In addition, we introduce a novel aggregation methodology for building a composite indicator where different levels of compensability for the distances to the ideal and anti-ideal (or negative-ideal) values of each indicator are considered. In order to illustrate the advantages of this proposal, we have applied it to evaluate the Circular Economy performance of EU Member States for the year 2016. This proposal can be a valuable tool for identifying areas in which the countries need to concentrate their efforts to boost their circular economy performance.