Article
Environmental Studies
Ying He, Yuantong Xing, Xiancheng Zeng, Yijun Ji, Huimin Hou, Yang Zhang, Zhe Zhu
Summary: This study examines the influential factors of China's carbon emissions from the electricity industry (CEEI) and proposes targeted provincial strategies to control carbon emissions and promote low-carbon transformation.
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Yi-Cheng Chen, Yen-Liang Chen, Jyun-Yun Lu
Summary: K-Means algorithm is one of the most famous and popular clustering algorithms in the world, known for its simple structure, easy implementation, high efficiency, and fast convergence speed. This article introduces an improvement to past variants of K-Means used in evolutionary clustering, considering both past and future clustering results, and extending K-Means to multiple cycles, resulting in more consistent, stable, and smooth clustering results.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Environmental Sciences
Ran Li, Tao Sun
Summary: This paper analyzes the energy consumption data of the logistics industry in China and finds that the total carbon emissions of the industry are increasing significantly, with the eastern region having higher emissions and growth rates compared to the central and western regions. Intra-regional differences are the main reason for the overall differences in carbon emissions in China's logistics industry, with inter-regional differences having a smaller impact on the overall differences.
POLISH JOURNAL OF ENVIRONMENTAL STUDIES
(2021)
Article
Geosciences, Multidisciplinary
Quande Qin, Huimin Yan, Baixun Li, Wei Lv, Muhammad Wasif Zafar
Summary: This study proposes a novel temporal-spatial decomposition method to investigate the drivers of China's carbon emissions, considering investment efficiency, resource allocation, and labor. The results indicate that energy intensity and investment efficiency are the two most significant factors affecting carbon emissions. In the new normal period, carbon emissions in eastern, central, and northeast China are decreasing. Furthermore, the distribution of carbon emissions among provinces and regions in China is unbalanced due to disparities in energy intensity, resource allocation, and labor. The research emphasizes insights to reduce carbon dioxide emissions and narrow regional differences in carbon emissions.
Article
Green & Sustainable Science & Technology
Tianping Bi, Mei Zhang
Summary: Based on the estimation data and models, this study analyzed the temporal and spatial changes and driving mechanism of carbon emissions in Shenyang. The results showed an upward trend in energy carbon emissions, with the growth rate peaking before decreasing and the carbon peak not yet reached. The spatial distribution exhibited a radiative pattern, with higher concentration in the central region and lower concentration in the peripheral regions. Economic development, population size, and energy efficiency were identified as significant carbon-increasing factors, while industrial structure and energy structure were significant carbon-reducing factors.
Article
Green & Sustainable Science & Technology
Guoyin Xu, Tong Zhao, Rong Wang
Summary: This paper measures the carbon emissions of the logistics industry in different regions of China from 2010 to 2020 and decomposes the influencing factors of carbon emissions in China's logistics industry. The study finds significant regional variations in carbon emission levels and highlights the impact of economic development and logistics industry on carbon emissions. The effects of energy intensity and energy structure on carbon emissions also show volatility. The decoupling analysis reveals that only a few provinces have achieved strong decoupling, while most provinces are weakly decoupled.
Article
Physics, Multidisciplinary
Nick James, Max Menzies
Summary: We introduce new frameworks to study spatio-temporal patterns in carbon dioxide emissions, demographic trends, and economic patterns across 50 countries over the past 50 years. Our analysis is divided into four sections, focusing on emissions classes, carbon dioxide trajectories, spatial propagation of emissions, and country grouping based on similarity in real and carbon economies.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Environmental Sciences
Haonan Zhang, Xingping Zhang, Jiahai Yuan
Summary: China, the largest carbon dioxide emitter in the world, has made great efforts to retard carbon emission growth over the past decades. Economic growth was the major contributing factor to provincial carbon emissions increase during 2007-2012, while energy intensity effect replaced it during 2012-2017. Upgrading industrial structure and expanding renewable energy can help mitigate provincial carbon growth, with the power sector continuing to contribute to national decarbonization.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Environmental Sciences
Han Hu, Tiangui Lv, Xinmin Zhang, Hualin Xie, Shufei Fu, Can Geng, Zeying Li
Summary: The objective of this study is to identify the spatiotemporal change law and the leading factors of industrial carbon emission decoupling. The study analyzed the industrial carbon emission level of the Yangtze River Delta urban agglomeration from 2006 to 2020 and explored the spatiotemporal heterogeneity using spatial Markov chain. The findings provide insights for industrial carbon emission reduction in megalopolises.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Energy & Fuels
Yanfeng Li, Yongping Li, Guohe Huang, Rubing Zheng
Summary: This study explored the impact of electricity trading on carbon emissions in China using various models and algorithms. The results showed that inter-provincial electricity imports offset carbon emissions, while exports increased carbon emissions. Additionally, the abundant hydropower resources in certain provinces reduced the impact of electricity exports on carbon emissions. Moreover, emission reductions were only observed when electricity trading was generated from renewable sources or if the exporting province had a lower carbon intensity than the importing province at the national level.
Article
Computer Science, Artificial Intelligence
Carlo Baldassi
Summary: We introduce an evolutionary algorithm called recombinator-k-means for optimizing the highly nonconvex kmeans problem. Its defining feature is that its crossover step involves all the members of the current generation, stochastically recombining them with a repurposed variant of the k-means++ seeding algorithm. The recombination also uses a reweighting mechanism that realizes a progressively sharper stochastic selection policy and ensures that the population eventually coalesces into a single solution. We compare this scheme with a state-of-the-art alternative, a more standard genetic algorithm with deterministic pairwise-nearest-neighbor crossover and an elitist selection policy, of which we also provide an augmented and efficient implementation. Extensive tests on large and challenging datasets (both synthetic and real word) show that for fixed population sizes recombinator-k-means is generally superior in terms of the optimization objective, at the cost of a more expensive crossover step. When adjusting the population sizes of the two algorithms to match their running times, we find that for short times the (augmented) pairwise-nearest-neighbor method is always superior, while at longer times recombinator-k-means will match it and, on the most difficult examples, take over. We conclude that the reweighted whole-population recombination is more costly but generally better at escaping local minima Moreover, it is algorithmically simpler and more general (it could be applied even to k-medians or k-medoids, for example).
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Biotechnology & Applied Microbiology
Jiankun Jing, Shizhen Ke, Tianjiang Li, Tian Wang
Summary: This study investigates the classification of lithology using the K-means dynamic clustering analysis method, and the results show that this method is feasible and effective, but the misjudgment rate increases when the number of samples decreases.
ENVIRONMENTAL TECHNOLOGY & INNOVATION
(2021)
Article
Automation & Control Systems
Uri Stemmer
Summary: This research presents a new algorithm operating in the local model of differential privacy for solving the Euclidean k-means problem, significantly reducing additive error while maintaining multiplicative error. The study shows that the obtained additive error in handling the k-means objective is almost optimal in terms of its dependency on the database size.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Ahmed Fahim
Summary: The k-means method divides N objects into k clusters based on mean values, with linear time complexity and dependence on knowing the number of clusters and initial centers. This research introduces a method able to detect near-optimal values for k and initial centers without prior knowledge, resulting in improved final result quality. The proposed method combines DBSCAN and k-means to converge to global minima and has a time complexity of o(n log n).
JOURNAL OF COMPUTATIONAL SCIENCE
(2021)
Article
Energy & Fuels
Mengxin Shao, Minggao Xue
Summary: This research investigates carbon dioxide emissions in China at different phases from 2000 to 2016, using the logarithmic mean Divisia index (LMDI) technique to study four drivers: population, economic development level, energy intensity, and carbon emission intensity. The results show a decrease in the rate of increase in CO2 emissions in recent years, with declining energy intensity being the largest contributor to carbon reduction in China.
Article
Engineering, Environmental
Da Liu, Jin Chen Liu, Han Huang, Kun Sun
RESOURCES CONSERVATION AND RECYCLING
(2019)
Article
Thermodynamics
Guowei Zhang, Da Liu
ENERGY CONVERSION AND MANAGEMENT
(2020)
Article
Computer Science, Cybernetics
Da Liu, Wenbo Wang, Yinchuan Zhao
Summary: This study utilized web crawler techniques to gather takeaway food ordering data from Meituan, the world's largest GMV platform, and employed statistical models and time series regression models to analyze the impact of weather on online orders. Findings showed that temperature, air quality, and rainfall have significant effects on most category takeaway orders.
Article
Environmental Sciences
Da Liu, Linlin Xu, Umma Habiba Sadia, Hui Wang
Summary: This paper evaluated the CO2 emission reduction effects after the promotion of battery electric vehicles (BEVs) by the Chinese government, using the Well-to-Wheel (WTW) approach. The results showed that the CO2 emission reductions of BEVs are mainly influenced by the number of BEVs and the Renewable Portfolio Standard (RPS).
ATMOSPHERIC POLLUTION RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Bilal Ahmad, Liu Da, Mirza Huzaifa Asif, Muhammad Irfan, Shahid Ali, Muhammad Imad Ud Din Akbar
Summary: The research shows that charismatic leadership has a positive and significant impact on salespeople's service-sales ambidextrous behavior, which in turn affects service recovery performance. Similarly, adaptive selling behavior also has a significant impact on service recovery performance. Therefore, training programs that offer opportunities for salespeople to understand and implement selling strategies while providing customer service are necessary.
Article
Thermodynamics
Dongxiao Niu, Zhengsen Ji, Wanying Li, Xiaomin Xu, Da Liu
Summary: This paper proposes a secondary decomposition model to reduce the complexity of power demand sequences, combines different models for prediction, and further improves prediction accuracy through the Markov chain model. The case study in Zhejiang Province demonstrates that the proposed model can effectively extract the characteristics of changes in electricity demand and improve forecast accuracy.
Article
Green & Sustainable Science & Technology
Da Liu, Yumeng Liu, Kun Sun
Summary: Renewable energy, particularly wind power and photovoltaic power generation industries, is rapidly developing globally with the stimulation of subsidies. However, China's wind power and PV power generation industries, as the largest renewable energy generation country, are facing subsidy gaps. The cancellation of subsidies has brought challenges and opportunities to power generation companies, prompting the exploration of its impact on wind power, PV power, and coal-fired power generation companies in this study.
Article
Business
Bilal Ahmad, Da Liu, Naeem Akhtar, Muhammad Imad-ud-Din Akbar
Summary: The research explores how sales managers' aggression affects salespeople's performance in B2B sales organizations, with a focus on surface acting, deep acting, and service recovery. It finds that sales managers' aggression negatively impacts service recovery performance, while also positively correlating with surface acting and negatively correlating with deep acting. Additionally, ethical sales leadership moderates the relationship between sales managers' aggression and service recovery performance positively.
ASIA PACIFIC JOURNAL OF MARKETING AND LOGISTICS
(2022)
Article
Environmental Sciences
Naila Nureen, Da Liu, Bilal Ahmad, Muhammad Irfan
Summary: Based on socio-technical systems and institutional theory, this study examines the mediating effect of behavioral GSCM practices and the moderating effect of institutional pressure on the relationship between technical GSCM practices and organizational performance. The results show that behavioral practices mediate the relationship between technical practices and organizational performance, and that institutional pressure positively moderates this relationship.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Business
Bilal Ahmad, Da Liu, Naeem Akhtar, Umar Iqbal Siddiqi
Summary: This research investigates service-sales ambidexterity and its impact on service innovation and service recovery performance. The study found that behavior-based control has a negative effect on service-sales ambidexterity, while outcome-based control has a significant positive impact. Additionally, manager trust in salesperson and resistance to change play significant moderating roles between antecedents and outcomes.
INDUSTRIAL MARKETING MANAGEMENT
(2022)
Article
Social Sciences, Interdisciplinary
Bilal Ahmad, Da Liu, Mirza Huzaifa Asif, Muhammad Ashfaq, Muhammad Irfan
Summary: The study highlights the significant association between opening leader behavior and service recovery performance, while closing leader behavior is not significantly related to service recovery performance. Both opening and closing leader behaviors play a positive and significant role in service innovation capability, which in turn is positively related to value-based selling, adaptive selling, and service recovery performance. The study also contributes to existing research by exploring the mediation effect of service innovation capability between opening leader behavior and service recovery performance linkage.
Article
Psychology, Multidisciplinary
Bilal Ahmad, Da Liu, Muhammad Irfan, Jose alvarez-Garcia
Summary: This study investigates the impact of the salesforce control system on salesforce ambidexterity and finds that behavior-based control has a negative influence while outcome-based control is positively associated with salesforce ambidexterity. It also reveals that salesforce ambidexterity is positively linked with emotional exhaustion, which in turn has a negative impact on service innovation implementation and service recovery performance.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Naila Nureen, Da Liu, Muhammad Irfan, Maida Malik, Usama Awan
Summary: The increasing pressures from various stakeholders have urged manufacturing firms to adopt environmentally friendly production methods and pursue green innovation in developing countries. However, little research has been conducted on the relationship between green supply chain management (GSCM), green human capital (GHC), green innovation (GIN), managerial environmental knowledge (MEK), and firm performance (FPR). This study fills this research gap by providing empirical evidence that implementing GSCM, GHC, GIN, and MEK can substantially enhance FPR. The findings suggest that GIN mediates the link between GHC, GSCM, and FPR, while MEK directly affects FPR and moderates the relationship between GIN and FPR. The study has both theoretical and managerial implications, and the results can benefit practitioners, policymakers, and stakeholders seeking to improve FPR.
Article
Green & Sustainable Science & Technology
Da Liu, Xiaomei Zeng, Bin Su, Wenbo Wang, Kun Sun, Umma Habiba Sadia
JOURNAL OF CLEANER PRODUCTION
(2020)