• Energy Research

The aim of this study is to evaluate different renewable energy investments alternatives. Within this framework, six different criteria are chosen to represent financial and non-financial dimensions. Additionally, five renewable energy investment alternatives (biomass, hydropower, geothermal, wind and solar) are selected. Fuzzy AHP and fuzzy DEMATEL methods are considered to weight these criteria whereas alternatives are ranked by using fuzzy TOPSIS and fuzzy VIKOR approaches. The findings show that fuzzy AHP and fuzzy DEMATEL methods also give coherent results. It is concluded that environmental effects and earnings are the most significant criteria. Moreover, wind and solar are the most attractive renewable energy investment alternatives. Therefore, it is recommended that governmental incentives should be widely used for effective location selection of both energy alternatives. This situation could be also attractive for foreign investors in renewable energy market. In addition, large-scale investments should be handled by merger and acquisition to increase overall performance. Hence, it can be possible to raise earnings, improve capital adequacy and enhance organizational capacity with the extensive investments. Furthermore, easy access to the sources and good contract conditions should also be provided for this purpose so that it can be much easier to attract the attention of these investors. Also, customer expectations should be understood effectively with a detailed analysis. With the help of this issue, appropriate products can be presented according to customer needs and it significantly contributes to the success in renewable energy investment.

This paper proves that the development of the digital economy has become a new vector to promote the upgrading of China’s industrial structure. In addition, heterogeneous technological innovation plays an intermediary role in the promotion of the industrial structure by the digital economy. This study aims to solve the following: whether the development level of the digital economy is positively promoting the upgrading of the industrial structure; whether technological innovation can promote the upgrading of the industrial structure; the path of the digital economy through which to promote the upgrading of the industrial structure and the heterogeneity of this path. The purpose of this study was to verify the digital economy and scientific and technological innovation to promote the upgrading of the industrial structure and the reality of the realization path; and to solve the problem of insufficient power for upgrading China’s regional industrial structure against the background of the impact of the new generation of information technology. This study mainly adopted comprehensive evaluation and multivariate statistical analysis methods. The statistical basis for the study was data from 30 Chinese provinces from 2013 to 2018. The results confirm the hypothesis that the development of the digital economy and scientific and technological innovation have a positive role in promoting the upgrading of the industrial structure, and also prove that the intermediary role of heterogeneous technological innovation is crucial in the process of the digital economy promoting industrial upgrading. This conclusion can further give play to the role of the digital economy in promoting industrial structure upgrading, build a clean and intelligent industrial chain, solve the root cause of the lack of new drivers for China’s industrial upgrading, and help to form a new development pattern of domestic and international double circulation, so as to achieve the high-quality and sustainable development of China’s economy.

While previous study has confirmed significant correlation between infrastructure construction and air quality, little is known about the nature of the relationship. In this paper, we intend to fill this gap by using the Panel Smooth Transition Regression (PSTR) model to discuss the nonlinear relationship between transportation infrastructure construction and air quality. The panel data includes 280 cities in China for the period 2000-2017. We find that the transportation infrastructure investment is positively correlated to the air quality when the GDP per capita is below RMB 7151 or the number of motor vehicle population per capita is below 37 (vehicles per 10,000 persons) where the model is in the lower regime, and that the transportation infrastructure investment is negatively correlated to the air quality when the GDP per capita is greater than RMB 7151 or the number of motor vehicle population per capita is larger than 37 (vehicles per 10,000 persons) where the model is in the upper regime. The empirical results of the three sub-samples, including eastern, western and central regions, are similar to that of the national level. Furthermore, increasing transportation infrastructure investment is conducive to improving air quality. Urban bus services, green area, population density, wind speed and rainfall are also conducive to reducing air pollution, but the role of environmental regulation is not significant. After adding the instrumental variable (urban built-up area), the conclusions are further supported. Finally, relevant policy recommendations for reducing air pollution are proposed based on the empirical results.

This study aims to identify the factors affecting economic inequality in emerging seven (E7) countries. Within this framework, first, a wide literature review has been made and 12 different criteria which are thought to affect economic inequality have been determined. These criteria were weighted according to their importance with the help of interval type-2 (IT2) fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. Then, by using these weighted criteria, the E7 countries were ranked according to economic equality performance with IT2 fuzzy Multi-Objective Optimization by Ratio Analysis (MOORA) and IT2 fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The findings show that fair taxation, the equality of education provided by the state, and the uncontrolled growth of financial markets have a significant effect on the economic inequality. On the other side, Russia and China are the most successful countries in terms of economic equality, whereas India and Brazil have the worst performances. While considering these results, it can be said that the taxation system must be fair to eliminate the economic inequality. For this purpose, E7 countries should implement direct taxes, such as wealth tax to transfer funds from the rich to middle- and low-income groups. In addition, these countries should offer equal education opportunities to all citizens which affects their future income level. Finally, legal authorities should make the necessary arrangements and prevent excessive risk of financial system in the country so that the financial system in the country can be maintained in a healthy manner.

This study aimed to evaluate the energy policies and investments in renewable energy resources. In this context, developing energy policy and investing in energy were defined as two different factors for renewable energy. Additionally, eight different criteria were also selected based on these two different factors. In the first stage of the analysis, these criteria were evaluated by using a correlation coefficient based on interval type-2 fuzzy sets. The findings show that five criteria have a relationship with policy factors, whereas seven criteria are related to the investment factor. After that, the fuzzy DEMATEL approach based on interval type-2 fuzzy sets were used to weight these criteria. It was identified that policy returns, policy facilities, and policy technology were the most important criteria. Additionally, a performance evaluation of renewable energy investment alternatives was made with a fuzzy TOPSIS approach based on interval type-2 fuzzy sets. It was concluded that wind and solar are the most significant renewable energy investment alternatives. Therefore, it is recommended that there should be government supports for wind and solar energy investments. Within this context, corporate tax discounts for these companies, customs duty decrease for the items used in the investments, and providing qualified personnel in this area can attract the attention of these investors.

In this paper, petroleum product (mainly petrol and diesel) consumption in the transportation sector of China is analyzed. This was based on the Bayesian linear regression theory and Markov Chain Monte Carlo method (MCMC), establishing a demand-forecast model of petrol and diesel consumption introduced into the analytical framework with explanatory variables of urbanization level, per capita GDP, turnover of passengers (freight) in aggregate (TPA, TFA), and civilian vehicle number (CVN) and explained variables of petrol and diesel consumption. Furthermore, we forecast the future consumer demand for oil products during “The 12th Five Year Plan” (2011–2015) based on the historical data covering from 1985 to 2009, finding that urbanization is the most sensitive factor, with a strong marginal effect on petrol and diesel consumption in this sector. From the viewpoint of prediction interval value, urbanization expresses the lower limit of the predicted results, and CVN the upper limit of the predicted results. Predicted value from other independent variables is in the range of predicted values which display a validation range and reference standard being much more credible for policy makers. Finally, a comparison between the predicted results from autoregressive integrated moving average models (ARIMA) and others is made to assess our task.