A New Marketing Channel Management Strategy Based on Frequent Subtree Mining

For most manufacturers, success or failure is determined by how effectively and efficiently their products are sold through their marketing channel members, so the management of marketing channels plays an important role in market competition. Most existing work studies the problem of marketing channel management in a qualitative way. Recently, with the increase of amount of sales data, how to enhance the marketing channel quantitatively is significant. As the marketing channel can be viewed as a tree, in this paper, a new marketing channel management strategy based on frequent subtree mining is proposed. The proposed method is illustrated under the real-world sales data in ERDOS group. Firstly, the tree transaction is formed monthly. For each monthly transaction, only those channel members that pass the basic sales plan will be included. Secondly, we use the TreeMiner algorithm to discover embedded frequent subtrees. Finally, different management strategies are used for different kinds of discovered patterns. We show that our method can correspond to the seven decision areas in traditional marketing channel management

Data Mining In Oil Price Time Series Analysis

This paper sums up the applications of statistic models such as ARCH-family models, cointegration theory and Granger causality etc in oil price time series analysis and introduces the method of data mining combined with statistic knowledge to analysis oil price time series. In addition, the paper also explains advantages, functions, relevant technologies of this method and its potential applications in hedging the oil shock risk

Digitalization and Climate Change Adaptation in China

The effects of climate change are increasingly transforming natural environments, threatening human living and socioeconomic developments. While mitigation action remains a priority, government efforts must also focus on helping people adapt to today’s climate impacts. Emerging digital technologies, which provide more efficient, rapid, and reliable risk monitoring and forecasting and enable better decision-making, can play a critical role to this end. This study develops policy recommendations for the utilization of digital tools to enhance climate change adaptation in China. This article first identifies China's primary climate change adaptation challenges, followed by an examination of successful digital solutions from countries outside of China. Successful application cases include using advanced machine learning models to develop more accurate rainfall predictions and applying digital twin systems to manage urban sewers in real time. These solutions are then evaluated in the Chinese context, leading to the formation of policy recommendations to advance similar initiatives

Temporal change in India’s imbalance of carbon emissions embodied in international trade

In India, rapid industrialization and reorganization of the global supply chain are driving economic growth, accompanied by increasing exports and carbon emissions. India is poised to succeed China as the next world manufactory, which will lead to huge emissions in the country. To formulate appropriate emission mitigation measures, it is necessary to further understand the temporal change in India’s emissions at the sectoral level from both the production and consumption perspectives. However, existing studies that have estimated emissions in India have paid less attention to the link among original emitters, final producers and final consumers and to its temporal change. Based on an emission inventory compiled in this study, we trace emission flows from original emitters to final producers and then to final consumers through the international supply chain by using an environmentally extended multi-regional input-output model. This study finds that both production-based and consumption-based emissions in India increased constantly from 2000 to 2014, and production-based emissions had higher growth rates due to the increased coal share. The major receivers of India’s exported emissions were developed countries (e.g., the European Union and the United States), while the main sources of India’s imported emissions were developing countries (e.g., China and Russia). From 2011 to 2014, India’s net exported emissions increased by 29.2% because of the decrease of imported emissions. Moreover, intermediate products (63% and 73.7%) were the major contributors to exported and imported emissions, most of which were embodied in manufacturing products (48.8% and 65.7%, respectively). Therefore, international cooperation to optimize the energy and trade structure and to improve energy efficiency can be effective in mitigating carbon emissions in India

The governance-production nexus of eco-efficiency in Chinese resource-based cities:A two-stage network DEA approach

For decades, resource-based cities in China have significantly contributed to China's socio-economic development. The heavy resource dependence of resource-based cities inevitably leads to a series of environmental problems. Mitigating environmental impacts in an unthinking manner might be disruptive for economic development. Improving eco-efficiency has been a crucial solution for protecting the environment while mitigating its negative economic impact. However, the method commonly used to evaluate the eco-efficiency – that is, the black-box data envelopment analysis (DEA) – cannot examine the inefficiencies of the internal structure, and as a result, the underlying management defects are unclear. To open the black box, this study presents a two-stage network DEA framework incorporating government and industrial sectors and measures the eco-efficiency of 84 resource-based cities during the post-financial crisis period (2007–2015). The results indicate that the average eco-efficiency of China's resource-based cities shows a promising increase, and there is a positive relationship between governance efficiency and production efficiency. The decreasing trend of governance efficiency in the Central, Western, and Northeast regions after 2014 shows the low quality of the government sector in the usage of fiscal income. Proactive disclosure of how the government sector conducts public business and spends taxpayers' money should be made to increase transparency, attract more entrepreneurial resources to carry out production activities, and further improve sustainability. The two-stage network DEA framework helps obtain more insights into the internal management defects of the government and industrial sectors and enhance their cooperation to improve the eco-efficiency precisely

CO₂ emission reduction potential in China from combined effects of structural adjustment of economy and efficiency improvement

China has committed to decreasing its emission intensity by 60% to 65% by 2030 compared to 2005 levels and achieving carbon neutrality by 2060. It is of great importance to evaluate the CO2 emission reduction potential to quantify the amount of CO2 emissions that can be less generated and the amount that should be balanced out. Economic structure adjustment and CO2 emission efficiency improvement will contribute to mitigating CO2 emissions, which always happen simultaneously in the real world. However, few studies consider these issues simultaneously, which can lead to inaccurate estimation. A scenario analysis framework is proposed to estimate their combined effects, and an indicator is proposed to measure the technical feasibility of achieving the reduction potential. A set of scenarios are designed based on this framework and we find that: (1) to achieve carbon neutrality, 6161.16 Mt of CO2 emissions of China can be less generated compared to 2017 levels by significantly increasing its tertiary industry share to high-income entities’ level and adopting the most advanced technology to improve emission efficiency; the remaining 2732.40 Mt of CO2 emissions should be removed by carbon offsetting. Regarding emission intensity, 81.39% can be reduced compared with the 2005 level; and (2) Technical feasibility analysis shows Sichuan, Chongqing, and Anhui have the largest technical barriers in achieving the reduction potential. The proposed scenario analysis framework can provide a reference not only for China to achieve the emission mitigation pledges, but for countries with significant technological differences and structure adjustment to formulate mitigation strategies.</p

Comparisons of CO₂ emission performance between secondary and service industries in Yangtze River Delta cities

To put the brakes on global climate change, China, the world's top emitter, has established ambitious CO2 emissions reduction targets. Industry-level emissions analysis can help policymakers determine better ways to achieve mitigation targets. This study is the first to target the total-factor carbon emission performance (TCPI) of secondary and service industries. We first compile industry-level CO2 emission inventories of 25 Yangtze River Delta cities during 2007–2016. The TCPI of secondary and service industries is then estimated by the non-radial directional distance function. We then compare the TCPI of the two industries across levels, dynamics, and inequalities using a global metafrontier approach. The results show the TCPI of the service industry (0.563 in 2016) was significantly higher than that of secondary industry (0.256 in 2016), suggesting that the service industry was more carbon-friendly. The TCPI gap between the secondary and service industries narrowed over the study period. The TCPI of secondary industry showed a promising increase during 2007–2016 with an annual growth rate of 2.30%, reflecting the positive effects of the government's reforms and environmental regulations. By contrast, the service industry saw a downward trend in TCPI, decreasing by 1.68% annually, primarily because it is a newcomer to low-carbon development. TCPI inequality in secondary industry was much larger than in the service industry, suggesting that significant heterogeneity exists in secondary industry. Therefore, policymakers should implement targeted mitigation policies for secondary industry, and place decarbonising the service industry on the agenda to reverse its decreasing TCPI

Assessing the economic impacts of a perfect storm of extreme weather, pandemic control, and export restrictions: A methodological construct

This article investigates the economic impacts of a multi-disaster mix comprising extreme weather, such as flooding, pandemic control, and export restrictions, dubbed a "perfect storm." We develop a compound-hazard impact model that improves on the ARIO model by considering the economic interplay between different types of hazardous events. The model considers simultaneously cross-regional substitution and production specialization, which can influence the resilience of the economy to multiple shocks. We build scenarios to investigate economic impacts when a flood and a pandemic lockdown collide and how these are affected by the timing, duration, and intensity/strictness of each shock. In addition, we examine how export restrictions during a pandemic impact the economic losses and recovery, especially when there is the specialization of production of key sectors. The results suggest that an immediate, stricter but shorter pandemic control policy would help to reduce the economic costs inflicted by a perfect storm, and regional or global cooperation is needed to address the spillover effects of such compound events, especially in the context of the risks from deglobalization