A novel hybrid multi-criteria group decision-making approach with intuitionistic fuzzy sets to design reverse supply chains for COVID-19 medical waste recycling channels

Intermodal travel planning and decision support integrated with transportation and energy systems

The fast urbanization in China makes it all the more important to find sustainable solutions that are both comprehensive and energy-efficient. Because of its important role in lowering logistical expenses and pollutant emissions, intermodal transport is generally seen as an effective method of coordinating transportation operations, helping to address the growing economic and environmental issues. Considering the characteristics of a growing city, this article lays out a multi-criteria method for selecting which new initiatives for China's public transportation system should be prioritized. "Electric municipality bus," "light rail system," and "modernization to the current fleet and optimization" are the three enhancement initiatives that are outlined. Using transportation-related economic, social, and environmental sub-criteria, this research applies TOPSIS, an analytic hierarchy method and fuzzy approach for order preference by resemblance to ideal circumstance application, to prioritize transportation projects. The study aims to improve city life in Chongqing, China, by identifying the most environmentally friendly development projects. Applying the analytical hierarchy method (AHP), the relative importance of several sustainability criteria was established for use in making strategic decisions. The alternative projects for the given city have been ranked using the fuzzy TOPSIS approach. However, the investigated results show the supportive response of hybrid to environmental sustainability and vice versa for non-hybrid vehicles. However, the energy consumption in public transport remains a leading hurdle in sustainability across the three modes of transport: taxis, rail transit and buses. Finally, computer trains in public transport also surprisingly deal with environmental sustainability to keep the current & forthcoming generation from ecological harm. However, theoretical and empirical policy suggestions have been proposed to become clean & green shortly.

Risk Management for Whole-Process Safe Disposal of Medical Waste: Progress and Challenges

Over the past decade, the global outbreaks of SARS, influenza A (H1N1), COVID-19, and other major infectious diseases have exposed the insufficient capacity for emergency disposal of medical waste in numerous countries and regions. Particularly during epidemics of major infectious diseases, medical waste exhibits new characteristics such as accelerated growth rate, heightened risk level, and more stringent disposal requirements. Consequently, there is an urgent need for advanced theoretical approaches that can perceive, predict, evaluate, and control risks associated with safe disposal throughout the entire process in a timely, accurate, efficient, and comprehensive manner. This article provides a systematic review of relevant research on collection, storage, transportation, and disposal of medical waste throughout its entirety to illustrate the current state of safe disposal practices. Building upon this foundation and leveraging emerging information technologies like Internet of Things (IoT), cloud computing, big data analytics, and artificial intelligence (AI), we deeply contemplate future research directions with an aim to minimize risks across all stages of medical waste disposal while offering valuable references and decision support to further advance safe disposal practices.

Linking to the development of economic growth with digital financial inclusion and supply chain management in China

Much research demonstrates the positive effects of financial inclusion and digital finance on expansion. Supply chains that can be relied upon are essential to national productivity and economic development. This study uses panel data from 2007 to 2022 covering 27 provinces in China to study the results of widespread access to digital financial services and supply chain management on regional economic growth using the instrumental variable approach (fixed effect model). In contrast to earlier research, this study employs an alternative measure of access to digital financial services utilization and digitalization. The data demonstrates that digital financial inclusion and supply chain management have a major impact on the development of the provincial economies in China. Based on the results of this research, we suggest increasing digital financial inclusion and bolstering human capital development to stimulate economic expansion. This essay makes a theoretical advancement in studying digital technology's widespread adoption of financial services by providing a comprehensive critical review and a fresh angle on the nuts and bolts of digital money and universal banking. Boosting institutional quality and governance are two more paths that authorities can take to stimulate economic expansion in the China area, and the results show how important these measures are for achieving this goal.

An application of BWM for risk control in reverse logistics of medical waste

The pollution posed by medical waste complicate the procedures of medical waste logistics (MWL), and the increasingly frequent occurrence of public health emergencies has magnified the risks posed by it. In this study, the authors established an index of the factors influencing the risks posed by MWL along five dimensions: the logistics business, emergency capacity, equipment, personnel, and management. The best-worst case method was used to identify the critical risk-related factors and rank them by importance. Following this, we assessed the risk posed by MWL in four major cities in China as an example and propose the corresponding measures of risk control. The results showed that the linking of business processes was the most important factor influencing the risk posed by MWL. The other critical risk-related factors included the location of the storage site, the capacity for emergency transportation, measures to manage emergencies, and the safety of packaging. Of the cities considered, Beijing was found to be a high-risk city, and its MWL needed to be improved as soon as possible in light of the relevant critical risks. Shanghai, Guangzhou, and Shenzhen were evaluated as general-risk cities, which meant that the risks of MWL were not a priority in these areas, and the other goals of urban development should be comprehensively considered during the long-term planning for MWL in these municipalities.

Land evaluation approaches comparing TOPSIS and SAW with parametric methods for rice cultivation

Population growth has resulted in an increase in land exploitation on a large scale. Therefore, to increase crop yield and sustainable use of soil, it is necessary to exploit the land according to its potential. Due to land suitability assessment's multifactor nature, it needs a method for evaluating the factors simultaneously; in this case, multi-criteria decision models can be used. Therefore, this study aimed to compare the efficiency of the parametric method (square root) with multi-criteria decision-making approaches (technique for order of preference by similarity to ideal solution (TOPSIS) and simple additive weighting (SAW)) for evaluating land suitability in some rice cultivated areas in Khuzestan province, southwest Iran. A total of 28 rice farms were selected in the study area, and a pedon was dug, examined, and sampled in each. Several physicochemical land characteristics were used for the evaluation process, such as soil, climate, and topographical factors. According to the results, soil texture is the main limiting factor for rice farming in the study region, and organic carbon, salinity, and alkalinity ranked next. The range of land index for rice cultivation calculated by the square root method was from 19.3 to 70.9, from 49 to 95.3 by TOPSIS, and from 3.57 to 74.7 by SAW. The calculated explanatory coefficients between the actual yield and land indices for rice products estimated by the square root method, the TOPSIS approach, and the SAW method were 0.44, 0.63, and 0.60, respectively. This result confirms the high accuracy of TOPSIS method compared to SAW and square root methods. TOPSIS is therefore the ideal method for prioritizing options based on the simulation of the ideal answer because it is highly technical and robust in its decision-making approach. Furthermore, it uses the standardization method, equations, mathematical matrices, and suitable weights. Overall, it can be recommended as a suitable efficiency approach for land suitability evaluation.

The effect of COVID-19 on nuclear medicine and radiopharmacy activities: A global survey

Globally, COVID-19 affected radiopharmaceutical laboratories. This study sought to determine the economic, service, and research impacts of COVID-19 on radiopharmacy. This online survey was conducted with the participation of employees from nuclear medicine and radiopharmaceutical companies. The socioeconomic status of the individuals was collected. The study was participated by 145 medical professionals from 25 different countries. From this work, it is evident that 2-deoxy-2-[18F]fluoro-D-glucose (2-[18F]FDG), and 99mTc-labeled macro aggregated albumin 99mTc-MAA were necessary radiopharmaceuticals used by 57% (83/145and 34% (49/145;) respondents, respectively for determining how COVID infections affect a patient's body. The normal scheduling procedure for the radiopharmacy laboratory was reduced by more than half (65%; 94/145). In COVID-19, 70% (102/145) of respondents followed the regulations established by the local departments. Throughout the pandemic, there was a 97% (141/145) decrease in all staffing recruitment efforts. The field of nuclear medicine research, as well as the radiopharmaceutical industry, were both adversely affected by COVID-19.

Assessment of sustainable waste management alternatives using the extensions of the base criterion method and combined compromise solution based on the fuzzy Z-numbers

A number of factors have contributed to the increase in waste production and diversity of waste, such as the increase in population, alterations in consumption patterns, economic development, income changes, urbanization, and industrialization. The production of different types of waste, such as electronic, urban, hospital, and industrial waste, makes it necessary to classify waste accurately and recognize effective criteria for waste management. To design and operate waste management systems, it is necessary to understand the sources and types of waste, as well as information about their composition and rate of production. As a result, this study aims to rank 21 types of waste according to Iran's economic, social, and environmental criteria, as well as 13 sub-criteria related to those criteria. For this aim, proposed a novel decision-making approach based on the extension of the base criterion method (BCM) and combined compromise solution (CoCoSo) methods under fuzzy Z-numbers. Additionally, sensitivity analysis and comprehensive analysis are conducted on the results of the criteria and alternatives of sustainable waste management. Based on the results of this study, direct profit and reduced landfill are the most important criteria for assessing sustainable waste management alternatives. According to the results of this study, the sub-alternative of industrial metal waste is the most important waste management option. Examining the next sub-alternative ranks under sustainable waste management options (mobile, communication equipment, and battery) shows that electronic waste requires more attention for recycling and sustainable waste management.

Selection of plastic solid waste treatment technology based on cumulative prospect theory and fuzzy DEMATEL

Under the global implementation of a low-carbon economy, the treatment of municipal plastic solid waste (PSW) has become an important task to be solved urgently. In the actual decision-making process of PSW treatment, the evaluation information is usually fuzzy, and the decision-makers (DMs) are bounded rational. For selecting the most appropriate PSW treatment technology, we propose a multi-criteria decision-making (MCDM) method based on cumulative prospect theory and fuzzy decision-making trail and evaluation laboratory (DEMATEL). Firstly, we construct the criteria system of PSW treatment that consists of 9 sub-criteria from the perspectives of environment, economy, society, and technology. Then, considering the interdependences and interactions between these evaluation criteria and allowing multiple stakeholders to participate in decision-making, we propose a fuzzy DEMATEL method to deal with the fuzziness of evaluation in the decision-making process and determine the weights of the evaluation criteria. Subsequently, taking into account the different opinions of different stakeholders and psychological factors such as risk preference and loss aversion of stakeholders, we aggregate the evaluation information of different stakeholders and develop the PSW treatment alternatives to rank the orders by using the proposed multi-actor cumulative prospect theory (CPT) method. We study seven alternative processes for PSW treatment by the developed model, including landfill, recycling, pyrolysis, incineration, and the combination of landfilling and recycling, landfill and incineration, and recycling and pyrolysis. According to the ranking results, we find the combination of recycling and incineration is the best treatment alternative. We take the seven PSW treatment technologies in Shanghai as the case study to verify the effectiveness and feasibility of the proposed method. Through the sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method, we illustrate the effectiveness and superiority of the proposed method. This research provides significant references for the PSW treatment technology selection problems under uncertain environments and extends the methods in the decision-making field.

Assessing the nexus between COVID-19 pandemic-driven economic crisis and economic policy: lesson learned and challenges

This study examines China's budgetary policy during the COVID-19 pandemic as a result of China's insufficient ability to deal with a new crisis when the epidemic struck in March 2020 and as a result of the economic crisis that began in China in March 2020. In order to better comprehend China's economic status during COVID-19, the study relies on secondary data. The fiscal response of emerging market economies like India is less than in advanced economies. However, it is generally considered to be in line with the average for emerging market economies. As a result of the Disaster Management authority imposing a rigorous lockdown, unemployment rose, the trade cycle was interrupted, and manufacturing and service activities were affected. According to the study's findings, China's economic policies, namely its fiscal policy, responded in the years leading up to 2019 by increasing health expenditure, income transfer, welfare payments, subsidies, and reducing short-term unemployment. As a result of the COVID-19 pandemic, China's government has adopted a number of measures to minimize the damage to the economy. This article also focuses on China's numerous budgetary actions with COVID-19.

Does COVID-19 impact on financial markets of China-evidence from during and pre-COVID-19 outbreak

During the outbreak of COVID-19, concern significantly influenced our financial system. This new paper's primary assessment of the COVID-19 virus affects the world's major economies and financial markets. This paper utilizes an event analysis approach and a data model to investigate the influence of COVID-19 on the financial market system from three viewpoints: (1) supply chain finance and titles, (2) processing system, and (3) the financial system of the organization. According to data analysis, the model built in this work may properly depict the influence of COVID-19 on the financial market system. The results indicated that the low age coefficient (p-value (p 0.05)) and a higher blocking condition (p-value (p > 0.05)) impact city tourism market system with p-values of 0.002 and 0.004, respectively. Other results show the impact of the Chinese New Year vacations. Since then, the government has slowly stabilized its recovery, with many measures taken to limit the epidemic in February and a series of regulatory measures enacted to stabilize financial markets. These findings show a small but statistically significant degree of stabilization in international financial markets in response to stay-at-home government policies and social distancing measures, which is encouraging for political actors concerned about economic performance during the coronavirus 2019 pandemic response.

Modeling analysis of the correlation between duality innovation and multinational enterprise performance

In this study, we investigate how the influence of dual innovation affects the productivity of multinational enterprises (MNEs). Because of the rise of the knowledge-based economy, the capacity of multinational corporations (MNCs) to innovate technologically has become an increasingly important component in determining the extent to which they can compete in the global market. Models of Duality Innovation and Multinational Enterprise Performance with a Measurement of Corporate Risks from 2000 to 2015 were developed using corporate finance literature and data. The models show positive relationships between duality innovations and multinational enterprise performance. Furthermore, there has been an increasing level of corporate risks over the years when measured by both the duality innovation and multinational enterprise performance metrics. This article discusses the findings of this research project. It explains how they can help understand international enterprise performance while also explaining how to determine a potential risk profile for an individual or multiple companies. This knowledge is valuable because it helps us understand why some corporations succeed while others fail.

Digital supply chain transformation: effect of firm’s knowledge creation capabilities under COVID-19 supply chain disruption risk

Digital supply chain (SC) transformation has emerged as a way to improve information sharing, better manage demand, and reduce costs in supply chain management. However, the majority of firms are unable to transform their supply chains into digital models. Thus, this study aims to identify the key drivers of digital SC transformation and provide empirical evidence on the extent to which firms’ knowledge creation capabilities could impact firms’ level of digital supply chain transformation. Based on a knowledge-based view, this study proposes that firms’ knowledge creation capabilities – which consist of the capacity to absorb external knowledge and the intent to learn with partners within the SC – are crucial to the successful knowledge transfer required to digitially transform, particularly under the effects of COVID-19 supply chain disruption risks. Survey data collected from 923 Vietnamese firms participating in cross-border trades were analyzed using partial least squares structural equation modeling (PLS-SEM). This study finds that firms’ absorptive capacity and learning intent are critical drivers of their digital supply chain transformation. Moreover, the high uncertainties in external environments are found to substantially accelerate the digital transformation processes and influence the effectiveness of firms’ knowledge creation capabilities in digital SC transformation. Significantly, firms are more inclined toward external knowledge sources to cope with disruption risks in the supply chain. This study contributes a novel approach to better understanding the role of knowledge creation capabilities in responding to supply chain disruption risks and fills a gap in research on drivers of successful digital SC transformation.

A comprehensive and bibliometric review on the blockchain-enabled IoT technology for designing a secure supply chain management system

Blockchain is a well-known prominent technology that has gotten a lot of interest beyond the financial industry, attracting researchers and practitioners from numerous businesses and fields. Specific uses of blockchain in supply chain management (SCM) are addressed in business practice. By combining two perspectives on blockchain in SCM, this study provides comprehensive knowledge in this field using a bibliometric approach. We will explore the worldwide research trend in related topic areas. By collecting data from the Web of Science, we collected 400 articles related to our research topic from 2016 until early 2021. We eliminated research in the form of technical reports, editorials, comments, and consultancy articles to maintain the quality of the data gathering. VOSviewer is used to create visualization maps based on text and bibliographic information. The examination uncovered helpful information, such as annual publishing and citation patterns, the top research topic, the top authors, and the most supporting funding organizations in this field.

Application of Capital Asset Pricing Model Based on BP Neural Network in E-commerce Financing

The study explores the risks and benefits of investors in e-commerce financing under the background of "double carbon" to maximize investors' interests and reduce investment losses. The Back Propagation Neural Network (BPNN) algorithm model of e-commerce enterprise financing based on the Capital Asset Pricing Model (CAPM) is mainly studied. First, according to the worldwide literature, the theoretical concept and principle of the CAPM are deeply studied and analyzed. Then, from the perspective of "double carbon," with the financing risk characteristics of listed companies responding to the "double carbon" policy as samples, the CAPM model of e-commerce financing under the BPNN algorithm is established. Next, the BPNN is used to input the financing samples of e-commerce enterprises and train the model. The verification experiment of the capital asset financing model of e-commerce enterprises is further conducted. The experimental results show that the model error is the smallest when the number of neurons in the hidden layer reaches about 20. Therefore, the number of neurons in the hidden layer of the model is set to 20. When the number of iterations in training reaches 3000, the financing risk model begins to show a convergence trend. Finally, it can be determined that the number of adaptive iterations of the model is 3000. When the learning rate is 0.03, the oscillation of the model is smaller and stabler, so the model learning rate is 0.03, and the final model error is only 9.96 × 10-8. Based on this, e-commerce enterprises can achieve the purpose using this model to adjust the coefficient in financing in the future. The results have certain reference significance for e-commerce financing risk assessment under a "double carbon" background.

A comparative analysis of three multi-criteria decision-making methods for land suitability assessment

Natural resource management relies on identifying the ecological constraints, assessing land suitability, and considering the socio-economic demands in the region. However, in many developing countries, natural resources are extensively overused in favor of economic growth. This is due to the fact that conservation and natural constraints are not always taken into consideration during the planning phase, especially when the decision-making process is mainly influenced by political or economical views. To avoid these subjective plannings, environmental planners are encouraged to consider quantitative planning approaches that can integrate environmental, social, economic, and political matters through a non-bias procedure. The present study, therefore, examines the application of three multi-criteria decision-making methods (MCDM), namely, analytic hierarchical process (AHP), fuzzy analytic hierarchical process (fuzzy AHP), and technique for order of preference by similarity to ideal solution (TOPSIS), for the assessment of land suitability afforestation. Siahpoosh Watershed, in Iran, is used as a case study to compare three MCDM methods. To achieve this, a set of land suitability criteria (i.e., slope, elevation, aspect, soil texture, soil depth, drainage, erosion, temperature, rainfall, and vegetation type and cover) was defined and weighted using the AHP and fuzzy AHP methods. TOPSIS was then used to prioritize and rank the suitability of different sections of the study area for afforestation. The study demonstrates that the fuzzy AHP method combined with TOPSIS generates more reliable outcomes than the AHP method. The results could be useful for making more informed decisions about afforestation in the region.

Theorem Verification of the Quantifier-Guided Dominance Degree with the Mean Operator for Additive Preference Relations

Deciding which film is the best or which portfolio is the best for investment are examples of decisions made by people every day. Decision-making systems aim to help people make such choices. In general, a decision-making system processes and analyses the available information to arrive at the best alternative solution of the problem of interest. In the preference modelling framework, decision-making systems select the best alternative(s) by maximising a score or choice function defined by the decision makers’ expressed preferences on the set of feasible alternatives. Nevertheless, decision-making systems may have logical errors that cannot be appreciated by developers. The main contribution of this paper is the provision of a verification theorem of the score function based on the quantifier-guided dominance degree (QGDD) with the mean operator in the context of additive preference relations. The provided theorem has several benefits because it can be applied to verify that the result obtained is correct and that there are no problems in the programming of the corresponding decision-making systems, thus improving their reliability. Moreover, this theorem acts on different parts of such systems, since not only does the theorem verify that the order of alternatives is correct, but it also verifies that the creation of the global preference relation is correct.