Biomass is viewed as one of the critical renewable energies and it widely exists in nature. Developing bioenergy has been promoted as a viable mean of dealing with environment issues that are related to the utilization of fossil fuel. However, due to many obstacles, the biomass and bioenergy technology has not won widespread support in developing countries, like China, with vast land area, particularly in rural area. Furthermore, most existing researches just focused on the description of the influence factors, along with the solution to the technical problems, while many social factors are overlooked. In fact, the process of developing biomass is indeed complicated due to the need for consensus and active participation of the various stakeholders, such as the government, the industry, and the local residents. Therefore, while integrating the intuitionistic fuzzy logic and fuzzy cognitive map, this study constructs an intuitionistic fuzzy cognitive map (IFCM) that is in line with experts’ suggestions and the current literature to investigate how to promote the development of biomass through enhancing public acceptance. We conduct several simulations from the perspective of different stakeholders, according to the IFCM. The analysis results reveal the influence mechanism in the system and illustrate the effect of various factors that are stressed by every stakeholder. The research design also provides a reference for future studies.

Most of the existing methodologies for evaluating heterogeneity in zero-inflated Poisson (ZIP) models are often assuming that the Poisson mean is a function of nuisance parameters. However, these nuisance parameters can be misspecified when performing these methodologies, the validity and the power of the test may be affected. In this article, we primarily focus on investigating the impact of misspecification on the performance of score test for homogeneity in ZIP models. Through an intensive simulation study, we find that: 1) under misspecification, the limiting distribution of the score test statistic under the null no longer follows a ${\chi }^2$ distribution. A parametric bootstrap methodology is suggested to use to find the true null limiting distribution of the score test statistic; 2) the power of the test decreases as the number of covariates in the Poisson mean increases. The test with a constant Poisson mean has the highest power, even compared to the test with a well-specified mean. At last, simulation results are applied to the Wuhan Inpatient Care Insurance data which contain excess zeros.

Megacities in the Yangtze River Economic Belt (YREB) are facing severe challenges and unbalanced development. Combating megacity syndrome is crucial for achieving modernization. This study developed a Development-Autonomy-Inclusiveness governance framework to characterize megacity governance capacity modernization (MGCM). The integrated model is employed to evaluate the MGCM for nine megacities along the YREB in China from 2013 to 2022. The key determinants are identified by Geo-detector. The configuration pathways and synergistic mechanisms for high MGCM are depicted using fsQCA. The empirical study indicates that: (1) The MGCM is at a low level but displays a slight upward trend, with development capacity > autonomy capacity > inclusiveness capacity. The MGCMs of three urban agglomerations manifest as being development-driven, autonomy-constrained, and autonomy-promoted. (2) The synergistic interaction among determinants is greater than any single factor. (3) Megacities exhibited distinct pathways to achieve high MGCM: tri-capacity synergy pattern in the Yangtze River Delta, development dominant pattern in Chengdu-Chongqing, autonomy weakness pattern in the Mid-Yangtze River, and adversity survival pattern during extraordinary periods. A novel theoretical framework and practical examples are proposed for boosting the modernization of governance capacity in China’s megacities, offering valuable insights for advancing the governance modernization of megacities worldwide.