Due to the price elasticity of demand for secondhand commodities, it is difficult to establish a quantitative model for the auction. This paper proposes an agent-based multiattribute reverse auction model to support multicommodity combinatorial auction. First, this paper establishes an agent-based reverse auction model and introduces the framework, procedures, and protocols of the model in detail. Second, in light of the multicommodity environment, the targets, protocols, auction strategies, and approaches are identified. Finally, by using the proposed agent-based auction model, both buyers and sellers will reach simultaneous agreements on the details of the commodities to complete the auction. 相似文献
We use topic modeling to study research articles in environmental and resource economics journals in the period 2000–2019. Topic modeling based on machine learning allows us to identify and track latent topics in the literature over time and across journals, and further to study the role of different journals in different topics and the changing emphasis on topics in different journals. The most prevalent topics in environmental and resource economics research in this period are growth and sustainable development and theory and methodology. Topics on climate change and energy economics have emerged with the strongest upward trends. When we look at our results across journals, we see that journals have different topical profiles and that many topics mainly appear in one or a few selected journals. Further investigation reveal latent semantic structures across research themes that only the insider would be aware.
Using a dynamic national computable general equilibrium model, we investigate the impact of carbon tax and energy efficiency improvement on the economy and environment of China. The Chinese social account matrix is presented based upon the latest input–output table (2012 IO table) and other data. The business as usual (BAU) scenario is designed according to several forecasts about China by 2030, followed by six policy scenarios, including different levels of carbon tax and technological progress as well as their combinations. The results show that carbon tax will frustrate the overall economic growth slightly. The CO2 emission will be 13.81% lower in 2030 compared to BAU case if the carbon tax scheme is carried out at a rate of 200 RMB/ton of CO2. Technological progress will stimulate the economic growth, enrich the household and government income, increase total investment and make most sectors prosperous with the exception of energy industries. 相似文献