Article
Mathematics, Interdisciplinary Applications
Ming Qi, Danyang Shi, Congcong Li, Jialu Wu, Pei Wang
Summary: China and India have great potential to enhance their oil supply security by reducing imports from certain countries and increasing imports from others. The Middle East plays a crucial role in their oil import strategies, while African countries and North America can provide alternative choices for diversifying energy supply risks. Both countries should adjust their oil import strategies by 2030 and 2040 to ensure a more stable and secure energy supply.
DISCRETE DYNAMICS IN NATURE AND SOCIETY
(2021)
Article
Mathematics, Interdisciplinary Applications
Jiepeng Wang, Hong Zhou, Xiaodan Jin
Summary: By using epidemic model to study supply chain risk transmission, we found the risk transmission in a supply chain network has a threshold and is influenced by multiple factors. The heterogeneity of network affects the risk transmission threshold and scale, which is of significant importance for supply chain risk management.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Environmental Studies
Simona Bigerna, Carlo Andrea Bollino, Paolo Polinori
Summary: The paper discusses how economic convenience of energy supplies can be obtained from a portfolio of partner countries to ensure energy security. By analyzing the oil imports structure of four major Asian energy importers, it is found that the composition of oil imports affects risk levels, and simulations of related shocks are conducted.
Article
Green & Sustainable Science & Technology
Alhanouf Abdulrahman Alsuwailem, Emad Salem, Abdul Khader Jilani Saudagar, Abdullah AlTameem, Mohammed AlKhathami, Muhammad Badruddin Khan, Mozaherul Hoque Abul Hasanat
Summary: This study examines the impact of the COVID-19 pandemic on the food supply chain in Saudi Arabia. The results indicate significant effects on the number of items shipped and countries that supplied these items, as well as notable differences in the mean values of certain item groups and countries. However, the impact on other countries is negligible.
Article
Engineering, Manufacturing
Sheridan Titman
Summary: Firms along a supply chain are exposed to risks depending on production technologies and supply and demand elasticities, and cannot rely on historical covariance or industry practices to determine hedging strategies for commodity price exposures.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Business, Finance
Yichu Huang, Yaoyao Fan
Summary: This study examines the impact of supplier-customer geographic proximity on corporate risk taking and finds that it reduces risk taking for supplier firms. The effect is more pronounced when suppliers have lower bargaining power and higher information asymmetry. The findings suggest that monitoring and information sharing are possible mechanisms through which geographic proximity influences suppliers' risk taking.
FINANCE RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Kazi Safowan Shahed, Abdullahil Azeem, Syed Mithun Ali, Md Abdul Moktadir
Summary: This study develops a mathematical model to mitigate disruptions in a three-stage supply chain network subject to natural disasters like COVID-19 pandemic. By providing appropriate inventory policies, manufacturers can maximize profits while considering potential disruptions.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
C. J. Axon, R. C. Darton
Summary: Managing risk is crucial for achieving energy security, and a methodology for identifying and assessing risks in the energy system has been developed. The study identified 34 distinct generic causes of risk and constructed a risk matrix for the UK's energy supply chains. Lack of access to capital, changing policy or regulatory frameworks, and significant public concern were among the most significant risks identified, indicating potential systemic issues.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Environmental Studies
Yuanchun Zhang, Carlos Enrique Montenegro-Marin, Vicente Garcia Diaz
Summary: Supply chain management is crucial for businesses, and this study proposes a holistic cognitive conflict chain management framework (HCCCMF) to enhance customer service quality and efficiency in supply chain management. The method utilizes behavioral monitoring analysis and policy matrix analysis to effectively manage disruptions and reduce costs in the supply chain.
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
(2021)
Article
Environmental Sciences
Sourena Rahmani, Alireza Goli
Summary: The excessive consumption of fossil fuels has led to environmental damage, prompting the global community to search for a suitable alternative. Biodiesel, a clean and eco-friendly fuel, has emerged as one viable option. To promote mass-level production of biodiesel, a sustainable supply chain network is necessary. This study proposes a mathematical model and scenario-based robust optimization approach to design such a network, resulting in achievable and efficient production and distribution of biodiesel fuel.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Business
Joao Henrique Lopes Guerra, Fernando Bernardi de Souza, Silvio Roberto Ignacio Pires, Anderson Luiz Ribeiro de Sa
Summary: Supply chains are important and complex systems that require effective risk management. This study provides a maturity model to guide companies in improving their supply chain risk management process. The proposed model addresses critical issues and offers practical implications for strengthening and implementing risk management practices.
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL
(2023)
Article
Business
Ruilei Qiao, Lindu Zhao
Summary: This paper explores the important role of supply chain risk management (SCRM) capabilities on improving supply chain financing performance (SCFP) for SMEs, incorporating supply chain integration (SCI) as well. By combining SCRM with supply chain financing management, the study proposed hypotheses to discuss the impact of SCRM capabilities on SCFP and the role of SCI. The research model was validated using structural equation modeling on survey data from 286 Chinese SMEs. The findings confirm that SCRM capabilities have a significant positive effect on SCFP and that SCI plays a promoting role. SMEs should establish SCRM capabilities and consider SCI for superior SCFP.
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL
(2023)
Editorial Material
Engineering, Manufacturing
Peter Ritchken
Summary: This commentary reflects on Titman's research on risk transmission across supply chains in Production and Operations Management, 2021.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Food Science & Technology
Nicole Tichenor Blackstone, Edgar Rodriguez-Huerta, Kyra Battaglia, Bethany Jackson, Erin Jackson, Catherine Benoit Norris, Jessica Decker L. Sparks
Summary: Social risk assessments and case studies on labour conditions in food production have focused on specific subpopulations, regions and commodities. This study aims to quantitatively assess the risk of forced labour in the US land-based food supply by combining data on production, trade, labour intensity and qualitative risk coding. The findings reveal that animal-based proteins, processed fruits and vegetables, and discretionary foods are major contributors to forced labour risk, with 62% of the risk stemming from domestic production or processing. Collaborative action across all countries is needed to eliminate reliance on labour exploitation and ensure the sustainability of food systems.
Article
Green & Sustainable Science & Technology
Ayberk Soyer, Erhan Bozdag, Cigdem Kadaifci, Umut Asan, Seyda Serdarasan
Summary: Supply chains are vulnerable to disruptive events, posing risks to all parties involved. This study proposes a new approach to examine the structure of sustainable supply chain risks and their impact on performance. The findings reveal that risks linked to economic, social, and environmental sustainability have a negative impact on supply chain performance.
JOURNAL OF CLEANER PRODUCTION
(2023)
Review
Computer Science, Information Systems
Jin Li, Yulan Zhang, Jianping Li, Jiangze Du
Summary: Online reviews play a crucial role in the decision-making process of purchasing experience products. This study analyzes a dataset of automobile reviews and quantifies the sentiment tendency expressed in textual reviews. The research empirically examines the nonlinear relationship between customer satisfaction and sentiment tendency, as well as the nonlinear effects of review sentiment and depth on helpfulness. The study also investigates how numerical ratings and sentiments expressed in text contents contribute to review helpfulness. The findings suggest the importance of neutral reviews, moderate depth, and complementarity between sentiment tendency and numerical ratings in increasing review helpfulness.
INFORMATION SYSTEMS FRONTIERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Lulu Shen, Jianping Li, Weilan Suo
Summary: This study proposes a scenario-based extended case-based reasoning approach to promptly generate effective response strategies for critical infrastructures with multiple interdependent risks. By combining risk network and ontological modeling, the approach considers the risk loss severity and interdependencies among risks, leading to more suitable and effective risk response in reality.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Hospitality, Leisure, Sport & Tourism
Xin Long Xu, Ying Zi Lin, Shun Jia Liu, Dengsheng Wu, Jianping Li
Summary: The research gap in the literature lies in the identification of spatial spillover effects and pollution risk transfer in cross-border tourism. This study develops a new tourism-induced environmental spatial hyperbolic model by incorporating disembodied technology communications into the classical environmental Kuznets curve to distinguish these two opposing effects. The study finds that disembodied technology communications resulting from cross-border tourism reduce pollution emissions in both local and adjacent regions. The relationship between pollution emissions and economic growth in local and adjacent areas follows an inverted U-shaped curve and a U-shaped curve, respectively. These findings emphasize the need for governments to improve the quality of cross-border tourism consumption to facilitate disembodied technology communications from developed countries.
CURRENT ISSUES IN TOURISM
(2023)
Article
Energy & Fuels
Ling Liu, Jujie Wang, Jianping Li, Lu Wei
Summary: A novel system-wide update online transfer learning model is proposed in this study to accurately predict wind turbine power. It applies various methods such as time trend quantification, convolutional neural network multi-source data fusion, and Hilbert spatial feature construction to improve data accuracy and reduce dimension. The model achieved high prediction accuracy of over 92.5%.
Article
Thermodynamics
Ling Liu, Jujie Wang, Jianping Li, Lu Wei
Summary: This article proposes a novel dual-meta pool model to improve the prediction accuracy of power in new wind farms with small data. The model learns the data knowledge contained in relevant wind farms to achieve multi-step prediction.
Article
Public, Environmental & Occupational Health
Shun Jia Liu, Jianping Li, Dengsheng Wu, Xiaoqian Zhu, Xin Long Xu
Summary: This study clarifies the causal relationship between risk communication and risk transfer based on multistakeholder engagement processes and constructs a spatial environmental hyperbolic model with a bidirectional correlation between pollution emissions and economic growth. The results show that agricultural watershed pollution and economic growth exhibit a U-shaped relationship and an inverted U-shaped relationship in different regions, respectively. The pollution reduction assessment in the classical EKC model can be largely attributed to pollution risk transfer behavior. This study expands the theoretical connotation of the classical EKC hypothesis and provides insights for pollution reduction scenarios in developing countries.
Article
Business, Finance
Yiran Shen, Chang Liu, Xiaolei Sun, Kun Guo
Summary: This paper proposes a Chinese investor sentiment index based on the LSTM deep learning method and investigates its impact on new energy stock returns and VaR behavior before and during COVID-19. The results show that investor sentiment significantly affects stock returns and VaR for both new and traditional energy companies, with a stronger effect in the new energy industry. The effects of investor sentiment have increased during COVID-19, and investors prioritize risk over returns. These findings provide guidance for Chinese small and medium-sized investors to optimize their investment strategies and mitigate losses associated with extreme risks.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2023)
Article
Social Sciences, Interdisciplinary
Jun Hao, Jianping Li, Dengsheng Wu
Summary: Risk science is a disciplinary system that predicts, assesses, and manages risks. This study performs a scientometric analysis of risk science using 10,950 papers from 1996 to 2021. The analysis provides insights into publishing trends, leading contributors, and research focus questions, aiming to improve the understanding and development of the risk science field.
JOURNAL OF RISK RESEARCH
(2023)
Article
Economics
Shigang Wen, Jianping Li, Chuangxia Huang, Xiaoqian Zhu
Summary: This paper applies complex network analysis methods to investigate the extreme risk spillovers among U.S. traditional financial and FinTech institutions. Dynamic extreme risk spillover networks are constructed using the GARCH-Copula-CoVaR approach for 91 public companies from January 2011 to August 2020. Empirical analyses reveal that the global efficiency sharply increases prior to and during financial crises and rapidly decreases afterward. Additionally, the insurance sector shows higher sector risk spillover indices in crisis periods, while the FinTech sector demonstrates higher indices in common periods, indicating their importance as recipients of extreme risk spillovers. Furthermore, large diversified financials are influential senders of extreme risk spillovers, and banking institutions play crucial roles in transmitting extreme risks.
QUARTERLY REVIEW OF ECONOMICS AND FINANCE
(2023)
Article
Business, Finance
Xu Zhang, Xian Yang, Jianping Li, Jun Hao
Summary: This paper proposes a new network topology approach to identify the contemporaneous and noncontemporaneous idiosyncratic spillovers of lower-moment and higher-moment risks in commodity futures markets using high-frequency data. The results suggest that contemporaneous information is more important in constructing the networks, especially for higher-moment risk spillover networks. Different commodities play different roles in the networks, with gold, silver, and wheat being the main transmitters of volatility and kurtosis risks, and corn and silver being the main transmitters of skewness spillovers. Crisis events can amplify the idiosyncratic volatility spillovers in commodity markets and the total spillover effects of higher-moment risk are stronger than those of lower-moment risk.
JOURNAL OF FUTURES MARKETS
(2023)
Article
Economics
Jun Hao, Qian Qian Feng, Jianping Li, Xiaolei Sun
Summary: This paper proposes a bi-level ensemble learning approach to improve the accuracy and robustness of complex time series forecasting. The approach combines decomposition-ensemble forecasting, resample strategies, and ensemble strategies. Experimental results on exchange rate time series demonstrate that the proposed model outperforms other benchmarks, indicating its effectiveness as a tool for complex time series forecasting.
JOURNAL OF FORECASTING
(2023)
Article
Automation & Control Systems
Jiaxin Yuan, Jianping Li, Jun Hao
Summary: In this study, a dynamic ensemble forecasting method using clustering approaches is proposed for nonstationary oil prices. Clustering is employed to classify historical observations into clusters, providing a targeted evaluation of individual forecasting models. The proposed model includes a clustering-based weight assignment strategy to balance competitiveness and robustness. Results show that the proposed model outperforms benchmarks and state-of-the-art methods, indicating its competitiveness and robustness. The effectiveness of the proposed model is validated through parameter variation and data missing scenarios, highlighting its potential in improving oil price prediction performance.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Geosciences, Multidisciplinary
Jianping Li, Jiaxin Yuan, Weilan Suo
Summary: National resilience is a crucial benchmark for evaluating a country's ability to withstand disasters. This study develops a three-dimensional assessment model using multi-source data to accurately depict national resilience, involving diversity of losses, fusion utilization of disaster and macro-indicator data, and refined elements. Results show that the national resilience of countries along the Belt and Road is generally not optimistic, with synchronized dimensional resilience, significant individual differences, and limited resilience growth over time. To address this, a coefficient-adjusted stepwise regression model with 20 macro-indicator regressors is proposed as a solution. This study provides quantified model support and guidance for assessing and improving national resilience, contributing to the high-quality development of the Belt and Road Initiative.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Business, Finance
Kun Guo, Fengqi Liu, Xiaolei Sun, Dayong Zhang, Qiang Ji
Summary: In this paper, the authors investigate the impact of climate policy uncertainty (CPU) and climate-related disasters on the price volatility of natural gas futures. Using the GARCH-MIDAS model, they find that disaster frequency has a robust predictive relationship with natural gas price volatility, while incorporating the CPU index with other predictors does not improve forecasting performance. These findings provide insights for traders and market regulators.
FINANCE RESEARCH LETTERS
(2023)
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
