Article
Engineering, Chemical
Chia-Nan Wang, Chien-Chang Chou, Thanh-Tuan Dang, Hoang-Phu Nguyen, Ngoc-Ai-Thy Nguyen
Summary: Due to increased awareness of environmental preservation and strict regulations, adopting sustainable practices has become crucial for corporate organizations in their supply chains. This research proposes a methodology based on multi-criteria decision making (MCDM) to evaluate and select sustainable suppliers in the chemical industry. Spherical fuzzy analytical hierarchy process (SF-AHP) and combined compromise solution (CoCoSo) methods are used, employing the novel spherical fuzzy sets theory to capture the ambiguous preferences of experts. The proposed approach is demonstrated through a case study in the chemical industry in Vietnam and shows the effectiveness of the method in determining the best alternative supplier. The findings from SF-AHP and CoCoSo analysis highlight the importance of various criteria and identify the Vietnam National Chemical Group as the top sustainable supplier.
Article
Green & Sustainable Science & Technology
Marina V. Vasiljeva, Vadim V. Ponkratov, Larisa A. Vatutina, Maria V. Volkova, Marina I. Ivleva, Elena Romanenko, Nikolay Kuznetsov, Nadezhda N. Semenova, Elena F. Kireeva, Dmitrii K. Goncharov, Izabella D. Elyakova
Summary: This article aims to substantiate the factors by which the oil industry influences the sustainable development of OPEC++-participating countries under conditions of uncertainty. Through panel regression analysis, it is found that the sustainable development of these countries is directly correlated with their socio-economic development level. Additionally, financial investors' panic factor is identified as influencing the imbalance of oil prices in the market.
Article
Computer Science, Artificial Intelligence
Biqin Yang, Yu Deng
Summary: Due to the increasing importance of finance in modern economic development, research on regional financial competitiveness in the study of regional economic competitiveness has become crucial. In the case of China, finance is experiencing rapid development and has permeated all aspects of social and economic life. Evaluating and analyzing financial competitiveness comprehensively is of significant importance for understanding China's national conditions, strength, and international competitiveness, as well as promoting long-term growth and sustainable development of the financial industry. This paper proposes a MADM methodology based on CoCoSo method under interval-valued intuitionistic fuzzy sets (IVIFSs) for evaluating the sustainable competitiveness of regional financial centers, and compares it with other existing methods to verify its effectiveness.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Rui Cheng, Jianping Fan, Meiqin Wu
Summary: This paper proposes an R-numbers Dynamic Multi-Attribute Group Decision-Making (DMAGDM) method, which accurately captures risks. It introduces the properties of the R-numbers Einstein Weighted Averaging (RNEWA) operator and R-numbers Weighted Einstein Geometric (RNEWG) operator. Additionally, the paper constructs an expert weight determination model and an attribute weight determination model, and builds static and dynamic rating calculation models. The applicability and effectiveness of the R-numbers DMAGDM method are demonstrated through a case study on supply chain risk assessment of manufacturing enterprises.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Sheng-Hau Lin, Danyang Wang, Xianjin Huang, Xiaofeng Zhao, Jing-Chzi Hsieh, Gwo-Hshiung Tzeng, Jia-Hsuan Li, Jia-Tsong Chen
Summary: This study introduces an evaluation framework for the causes of inefficient urban industrial parks, based on a novel hybrid modified multi-attribute decision-making model, and analyzes two cases of industrial parks in Taiwan. The results indicate that the parcel dimension and policy dimension have significant influence on causing inefficiency, with criteria such as property rights, size and shape, location, planning and development mechanisms, management mechanisms, and spatial planning policy for industry playing key roles. The study suggests that addressing policy dimension is critical for improving the efficiency of industrial parks.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Environmental Sciences
Mehdi Soltanifar, Madjid Tavana, Francisco J. Santos-Arteaga, Hamid Sharafi
Summary: This study proposes an integrated framework of multi-attribute decision-making (MADM) and data envelopment analysis (DEA) to solve problems with heterogeneous attributes. The proposed model classifies attributes into desirable and undesirable categories and provides a method for aggregating weights and scores. The model was applied to European countries based on their fulfillment of Sustainable Development Goals (SDGs) and showed improved computational efficiency and decision-maker satisfaction compared to standard MADM techniques.
ENVIRONMENTAL SCIENCE & POLICY
(2023)
Article
Environmental Sciences
Jaroslaw Brodny, Magdalena Tutak
Summary: The growing social awareness of environmental protection has led to the increasing implementation of sustainable development ideas in various economic sectors. The power industry, in particular, is now a priority for many countries' economic policies. This study developed methodology to assess the level of sustainable energy development in Central and Eastern European Countries, using four multi-criteria data analysis methods. Results showed differences in sustainable energy development levels among CEE countries, with Latvia and Croatia ranking the highest, and Poland and Bulgaria ranking the lowest.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Computer Science, Artificial Intelligence
Binyu Luo, Yicheng Ye, Nan Yao, Qihu Wang
Summary: This study mined information of interval numbers, including non-positive ones, in a rectangular coordinate system to define a ranking method and validate its feasibility and effectiveness through examples. The method can rank interval numbers intuitively and represent decision-makers’ multiple attitudes with different risk appetites.
Article
Computer Science, Artificial Intelligence
Lin Wei
Summary: Blended teaching, combining face-to-face teaching and online learning, is an important breakthrough in higher education teaching reform. Constructing a blended teaching quality evaluation system for college English courses is significant for ensuring sustainable development.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Social Sciences, Interdisciplinary
Bo-Wei Zhu, Ying He Xiao, Wei-Quan Zheng, Lei Xiong, Xia Yun He, Jian-Yi Zheng, Yen-Ching Chuang
Summary: This study evaluated the aesthetic expression of environmental design schemes in China and proposed a hybrid decision analysis model. By constructing a framework consisting of 5 dimensions and 18 evaluation elements, the key design elements and their influence relationships were identified.
Article
Energy & Fuels
Bogdan Wlodarczyk, Daniela Firoiu, George H. Ionescu, Florin Ghiocel, Marek Szturo, Leslaw Markowski
Summary: This study examines the relationship between sustainable development and renewable energy sources in EU countries through hierarchical clustering analysis, revealing high-performing groups and countries in need of additional support to achieve their goals.
Article
Environmental Sciences
Yizhong Huan, Tao Liang, Haitao Li, Chaosheng Zhang
Summary: In 2015, 193 countries committed to achieving 17 sustainable development goals (SDGs). A lack of methods for quantitative assessment of regional progress in achieving SDGs prompted the development of the Composite SDG Index, which categorized the goals into four dimensions and introduced a Coupling Coordinated SDG subindex for the first time to measure coordination between dimensions. The framework, used to assess 15 countries along the Belt and Road, aims to enhance mutual understanding among global stakeholders and support coordinated planning and decision-making at the national level.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Engineering, Civil
Annette Dietmaier, Thomas Baumann
Summary: Deep groundwater aquifers are important resources for emergencies and pre-industrial water supply. The EU Water Framework Directive (WFD) ensures their protection. Fluctuations in hydrochemical state of Upper Jurassic wells in Bavaria and Austria indicate potential unsustainability due to new exploitation activities. A new workflow using clustering algorithms provides a novel method to assess these fluctuations and establish thresholds for sustainable development.
WATER RESOURCES MANAGEMENT
(2023)
Article
Environmental Sciences
Dong Yan, Hongda Liu, Pinbo Yao
Summary: The study aims to estimate the energy-saving intensities of nations in the European Union using various DEA analysis equations from 2010 to 2018. Different dynamic envelope evaluations were formulated to analyze the efficiency changes in energy usage among EU nations. Germany, Sweden, and Austria were found to have strong ecological safeguard performance and be more energy-efficient compared to other countries like Denmark, Belgium, Spain, France, and Ireland. On the other hand, some Eastern EU nations showed reduced efficiency marks due to lower technological implementation in key manufacturing sectors.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2021)
Article
Environmental Sciences
Dragana Ostic, Angelina Kissiwaa Twum, Andrew Osei Agyemang, Helena Adu Boahen
Summary: This study assesses the impact of oil and gas trading, foreign direct investment inflows, and economic growth on carbon emissions for OPEC member countries. The findings show that there is not a significant relationship between oil and gas export and carbon emissions, while foreign direct investment inflows have a negative relationship and economic growth has a positive relationship with carbon emissions.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Operations Research & Management Science
Sema Kayapinar Kaya, Ejder Aycin, Dragan Pamucar
Summary: The circular economy is a rapidly growing theme in the European Union that encourages responsible and circular use of resources for long-term development. This study evaluates the social impact of the circular economy paradigm in EU countries using clustering methods and multi-criteria decision making. The results show the best-performing countries in each cluster based on social indicators.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Bisera Andric Gusavac, Selman Karagoz, Milena Popovic, Dragan Pamucar, Muhammet Deveci
Summary: This study identifies and connects the elements of the supply chain and environmental chain through an operations research process. A framework is developed to incorporate these chains into economic and natural systems and their performance. The study proposes a causal relationship between the two chains and begins to bridge the gap using operations research methods. Uncertainties are dealt with through a multi-period stochastic model and an interactive fuzzy multi-objective method.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Computer Science, Cybernetics
Ahmet Aytekin, Omer Faruk Gorcun, Fatih Ecer, Dragan Pamucar, Caglar Karamasa
Summary: This study proposes a novel decision-making approach to evaluate the investability of countries in global supply chains, providing practitioners with a practical and robust assessment technique. The findings indicate that only 22% of the 95 countries analyzed are investable, highlighting the need for robust decision-making tools for country selection.
Article
Computer Science, Cybernetics
Ahmet Aytekin, Omer Faruk Gorcun, Fatih Ecer, Dragan Pamucar, Caglar Karama
Summary: A well-operating logistics system is crucial for pharmaceutical supply chains to store and distribute medicines. However, there is an inverse correlation between medicine stock level and logistics service level. Therefore, a robust methodological frame is required to solve the complex evaluation problems in selecting logistics service providers.
Article
Computer Science, Artificial Intelligence
Indranil Ghosh, Manas K. Sanyal, Dragan Pamucar
Summary: This research focuses on developing an integrated predictive modeling framework to estimate Airbnb rental prices based on descriptions and utilities. The study found variations in predictability of rental prices across different cities, with amenity offerings playing a significant role.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
Indranil Ghosh, Pamucar Dragan
Summary: Global financial stress is a critical variable reflecting key macroeconomic indicators and financial markets, but there is limited focus on predictive analytics in the literature. This research uses two predictive frameworks to discover patterns of financial stress across variables and geography, utilizing EEMD for time series decomposition and LSTM and Prophet algorithms for prediction. Findings show accurate prediction of financial stress in short and long-run horizons, even during the COVID-19 pandemic. The frameworks are statistically significant but require Explainable AI methods for model interpretation.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Operations Research & Management Science
Pratibha Rani, Dragan Pamucar, Arunodaya Raj Mishra, Ibrahim M. Hezam, Jabir Ali, S. K. Hasane Ahammad
Summary: This study aims to develop a new decision-making framework for identifying the drivers of Industry 4.0 (I4.0) to achieve digital transformation in the photovoltaic supply chain (PVSC) from a sustainable development perspective. The framework combines generalized Dombi operators, an integrated objective-subjective weighting model, and the weighted sum product method under an interval-valued Pythagorean fuzzy (IVPF) environment. The empirical results show that, from a sustainability perspective, the significance of the social, environmental, and economic dimensions are 0.2258, 0.4947, and 0.2795, respectively, and data analytics and big data should be chosen as the most suitable options among others for the given data.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
K. Venkatachalam, Pavel Trojovsky, Dragan Pamucar, Nebojsa Bacanin, Vladimir Simic
Summary: Weather forecasting plays a crucial role in various aspects of modern society, and this study proposes a deep learning model called LSTM and T-LSTM for accurate weather prediction. Evaluation metrics demonstrate the effectiveness and reliability of the T-LSTM method.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Qiaohong Zheng, Xinwang Liu, Weizhong Wang, Qun Wu, Muhammet Deveci, Dragan Pamucar
Summary: This paper proposes an integrated method that combines prospect theory with a consensus model to address the problem of HFACS-based human error factors risk analysis. The integrated method can yield highly acceptable risk analysis results by considering experts' heterogeneous risk preferences.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Sarah Qahtan, Hassan A. Alsattar, Aws Alaa, Muhammet Deveci, Dragan Pamucar, Luis Martinez
Summary: Recent research has focused on developing real-time sign language recognition systems (SLRSs) using gesture recognition, but no comprehensive system with all desired features has been presented. To address this, researchers have compared and evaluated multiple recognition systems using multicriteria decision-making methods. However, no comparative study has examined the use of multiple Likert scales. Therefore, this paper extends the fuzzy decision by opinion score method (FDOSM) into Pythagorean fuzzy sets (PFSs) and evaluates the three Likert scales (five-, seven-, and ten-point) to benchmark the real-time SLRS.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Cybernetics
Ibrahim M. Hezam, Anand Kumar Mishra, Dragan Pamucar, Pratibha Rani, Arunodaya Raj Mishra
Summary: This paper develops a decision-analysis model to prioritize and select a new hospital site based on various indicators. It introduces the IF-SD-RS model to obtain combined weights and the IF-MARCOS model for prioritization. The study uses a case study to implement the developed model and compares it with existing models.
Correction
Computer Science, Artificial Intelligence
Zeeshan Ali, Tahir Mahmood, Hanen Karamti, Kifayat Ullah, Lemnaouar Zedam, Dragan Pamucar, Mohsen Ahmadi
Article
Computer Science, Information Systems
Hadi Badri Ahmadi, Dragan Pamucar, Pourya Pourhejazy, Sema Kayapinar Kaya, James J. H. Liou
Summary: Innovation is crucial for improving corporate sustainability performance. This study focuses on the economic aspect of sustainable innovation in the context of supplier evaluation from emerging economies. A criteria decision framework is proposed using fuzzy Full Consistency Method (FFUCOM) and Improved Combinative Distance-based Assessment (ICODAS). The framework is validated through a case study in the manufacturing sector. The findings identify financial resumption of products as the most critical economic innovation criterion for supplier evaluation. This article provides valuable insights for decision-makers and practitioners in understanding the economic dimension of sustainable innovation and assessing suppliers.
Article
Computer Science, Artificial Intelligence
Ismail Onden, Dragan Pamucar, Muhammet Deveci, Yakup As, Batin Birol, Feride Suheda Yildiz
Summary: This study aims to analyze the decision-making process in strategic positioning of railway stations and introduces a novel model that can consider Geographic Information System (GIS) outputs and capacity calculations together. The study finds that geographical locations, ease of integration to the existing transportation system, and complementary sectors in the neighborhood play important roles in strategic positioning.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Peng Wang, Yingxin Fu, Peide Liu, Baoying Zhu, Fubin Wang, Dragan Pamucar
Summary: This study explores the ecological governance of the Yellow River and proposes a multi-perspective evaluation method. By using BWM and IGR methods to calculate the weights of the indicators and combining multiple methods for comprehensive evaluation, policy recommendations for the ecological governance of the Yellow River Basin are obtained.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)
