The Ecuadorian electricity sector encompasses generation, transmission, distribution and sales. Since the change of the Constitution in Ecuador in 2008, the sector has opted to employ a centralized model. The present research aims to measure the efficiency level of the Ecuadorian electricity sector during the period 2012–2021, using a DEA-NETWORK methodology, which allows examining and integrating each of the phases defined above through intermediate inputs, which are inputs in subsequent phases and outputs of some other phases. These intermediate inputs are essential for analyzing efficiency from a global view of the system. For research purposes, the Ecuadorian electricity sector was divided into 9 planning zones. The results revealed that the efficiency of zones 6 and 8 had the greatest impact on the overall efficiency of the Ecuadorian electricity sector during the period 2012–2015. On the other hand, the distribution phase is the most efficient with an index of 0.9605, followed by sales with an index of 0.6251. It is also concluded that the most inefficient phases are generation and transmission, thus verifying the problems caused by the use of a centralized model.

Energy systems face serious difficulties due to economic policy uncertainty, which affects consumption trends and makes the shift to sustainability more difficult. While adjusting for economic growth and carbon emissions, this study examines the dynamic relationship between economic policy uncertainty and energy consumption (including renewable and nonrenewable) in China from 1985Q1 to 2023Q4. The research reveals the frequency-specific and time-varying relationships between these variables by employing sophisticated techniques such as Wavelet Cross-Quantile Correlation (WCQC) and Partial WCQC (PWCQC). Economic policy uncertainty and energy consumption do not significantly correlate in the short term; however, over the long term, economic policy uncertainty positively correlates with renewable energy consumption at medium-to-upper quantiles, indicating that it may play a role in encouraging investments in sustainable energy. On the other hand, EPU has a negative correlation with nonrenewable energy usage at lower quantiles, indicating a slow move away from fossil fuels. These results are confirmed by robustness testing with Spearman-based WCQC techniques. The study ends with policy recommendations to maximize economic policy uncertainty’s long-term impacts on renewable energy, reduce dependency on fossil fuels, and attain environmental and energy sustainability in China.

This study is based on the theory of planned behaviour, and its aim is to understand the impact of doctoral pursuit intention on the doctoral preparatory behaviour of female teachers in independent colleges in China, as well as to determine the moderating effect of perceived risk between doctoral pursuit intention and doctoral preparatory behaviour. The participants in the study were female teachers from independent colleges in China, who were recruited between February and March 2024 based on convenience sampling. 776 valid questionnaires were obtained, and the data were analyzed using a hierarchical regression method. According to the results, a doctoral pursuit intention has a significant and positive predictive effect on doctoral preparatory behaviour, while the perceived risk has a significant and negative moderating effect between doctoral pursuit intention and doctoral preparatory behaviour. This indicates that female teachers with high doctoral pursuit intention more actively prepare to pursue a doctoral degree when the perceived risk is low, whereas the doctoral preparatory behaviour of those with high perceived risk shows a limited increase as their doctoral pursuit intention increases. Therefore, female teachers’ pursuit of a doctoral degree should be supported on an individual basis and analysed within the broader context of the transformation of independent colleges.

The objective of the study was to determine the relationship between open government and municipal effectiveness State a region of the Peruvian jungle. The research followed a quantitative approach with a non-experimental, cross-sectional, and correlational design. The population comprised citizens of State in a region of the Peruvian jungle, with a sample of 625 individuals. A structured survey was employed as the data collection technique, using a validated questionnaire as the instrument. The results revealed a positive, high, and significant correlation between governance and municipal effectiveness (Spearman’s Rho = 0.813, p < 0.01). Furthermore, the dimensions of transparency, integrity, accountability, and citizen participation showed moderate to high correlations with municipal effectiveness, with accountability (Rho = 0.779) emerging as the most influential dimension. It was concluded that the principles of open government play a crucial role in shaping the perception of effective municipal management. This underscores the need to strengthen transparency, integrity, and citizen participation policies to enhance public services and foster trust in local authorities.

Improving the competitiveness of tourism destinations is crucial for driving local economies and achieving income growth. In light of this evidence, numerous government departments strive to assess specific factors that impact the competitiveness of tourism destinations, enabling them to issue appropriate new tourism policies that promote more effective forms of tourism business. Therefore, the primary objective of this paper is to investigate how various elements such as tourism resources, tourism support, tourism management, location conditions, and tourism demand influence regional competitiveness in the Northern Bay region of Guangxi Province in China. To accomplish this goal, an online survey was conducted to collect data from 420 visitors who had experienced North Gulf Tourism; yielding an impressive response rate of 95 percent. The findings reveal that all aforementioned factors—namely: Tourism resources, tourism support, tourism management, location conditions and tourist demand—significantly impact destination competitiveness. Notably though, it was found that among these factors influencing destination competitiveness; it is primarily determined by effective local-level management (β = 0.345). Following closely behind are tourist demand (β = 0.133) as the second most influential factor affecting destination competitiveness; followed by location conditions (β = 0.116) ranking third; then comes tourist support (β = 0.03) as fourth in line impacting destination competitiveness; finally with least impact being exerted by available tourist resources (β = 0.016). Consequently, highlighting that regional competitiveness within Guangxi’s Northern Bay area predominantly hinges on efficient local-level management practices thus strongly recommending relevant authorities formulate novel work policies aimed at enhancing levels of local-level competitive advantage within the realm of regional touristic offerings.