The development of input-monitoring system on biofuel economics and social welfare analysis

Abstract

Biofuel production relies on stable supply of biomass which would be significantly influenced by climate-induced impacts. Since the actual agricultural outputs are relatively unpredictable in the face of uncertain environmental conditions and can only be realized in the harvest season, providing useful information regarding the stability of biomass supply to the downstream biofuel industry is crucial. This study firstly illustrates a theoretical framework to explore the resultant market equilibrium and optimal conditions of agricultural and bioenergy production in the face of highly uncertain environmental risks and then employs a two-stage stochastic programming model to investigate the optimal biofuel development and associated economic and environmental effects. The results show that total welfare may not always increase because the loss of other agricultural commodities induced by climate impacts may be greater than the gains received by biofuel production and emission reduction. This study provides insights into the area where artificial intelligence monitoring system can be implemented to analyze the input data associated with agricultural activities and help the biofuel industry to improve its production possibilities.

What drives horizontal logistics collaboration? A grounded theory analysis of Chinese logistics service providers

“…On the other hand, the results indicate that innovations are the driving forces of HLC in China and point out some differences between Chinese LSPs in terms of driving forces, 1,2,4,8,9,12,17,19,21,32 labor utilization, 1,2,[7][8][9]21,32 cross-institutional collaboration, and AI technology integration and learning, 1,2,[24][25][26][27]40 which is an in-depth interpretation of China's phenomenon.…”

“…The application of AI in logistics is still being explored, 1 and Chinese LSPs' understanding of AI mostly comes from government policies to promote intelligent supply chains. [24][25][26][27]40 AI technology in the Chinese logistics industry can be roughly divided into two types. One is the replacement of labor by intelligent devices.…”

“…Currently, the development of AI technology requires greater cooperation to complete deep learning and technology upgrading. 1,4,24,39,40 Meanwhile, exogenous driving forces, such as the division of labor, the business environment, and competitive pressure, create a business atmosphere. The division of labor is the premise and basis of cooperation.…”

Green-production transitions and hazardous industrial discharge: A regional case study from China

“…To identify the research gap in the EKC, this study reviews recent studies that test the Kuznets Curve hypothesis at the country level, which will indicate a need for more attention to regional disparities in developing countries. 2,9 As the focus is to find an additional driving force of the EKC, the latest environmental solutions, such as the monitoring system in material flows and the waste recycling system, 10,11 are not included in the scope of this research. Sequentially, to factor in regional heterogeneity, the section on regional disparities explains how industrialization varies in China and identifies administrative ranking as Hou a significant factor in green transformation.…”

“…Which type of industrial hazard has been reduced the most through green innovation? To identify the research gap in the EKC, this study reviews recent studies that test the Kuznets Curve hypothesis at the country level, which will indicate a need for more attention to regional disparities in developing countries. 2,9 As the focus is to find an additional driving force of the EKC, the latest environmental solutions, such as the monitoring system in material flows and the waste recycling system, 10,11 are not included in the scope of this research.…”