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In this paper, a combined TODIM-BSC method with the neutrosophical approach for evaluating the performance of a private insurance company has been proposed. In other words, first, using the BSC technique, and identify the performance evaluation indicators, then evaluate the performance of the insurance company's agencies and rank them with the TODIM decision-making method.

The insurance industry has a special prestige and importance in domestic and foreign trade. The evaluation of insurance companies, in addition to informing the stakeholders, increases competition, industry dynamism, sustainable and balanced development of society. The purpose of this paper is to establish a model for evaluating the performance of private insurance companies by adopting multiple-attribute decision-making and Balanced Scorecard (BSC) with single-values neutrosophic numbers (SVNNs) which will be applied by considering a set of indicators and alternatives deliberated with different viewpoints.

A case study of the private insurance agencies in one of the provinces of Iran based on 26 criteria of agencies is used to confirm the practicality and effectiveness of the proposed model. Finally, there was a discussion about why the results are logical, which shows the strength and robustness of the proposed framework.

To the best of our knowledge, no study has been performed to evaluate the performance of a real-world problem with the integrated TODIM-BSC method in a neutrophilic environment. Therefore, this paper can be effective in bridging the existing research gap and expanding our knowledge of the discussion of evaluating the performance of organizations or companies. Besides, by using these results, the authors can help the planners of these companies as well as similar organizations in attracting satisfaction and retaining target customers.

The purpose of this study is to adopt the perspective of congruence to explore how organizational unlearning facilitates knowledge transfer in cross-border mergers and acquisitions (M&A).

Drawing on the congruence theory, this study built a theoretical model and examined it with survey data from 212 firms in China.

Organizational unlearning has no direct influence on knowledge transfer. In contrast, it promotes knowledge and routine compatibility that facilitate knowledge transfer. Routine and knowledge compatibility have different mechanisms on knowledge transfer. Specifically, the higher routine compatibility, the more effective is knowledge transfer. When knowledge compatibility is at a medium level, the effectiveness of knowledge transfer is optimal.

Firms should regard organizational unlearning as a crucial facilitator to knowledge and routine compatibility that promote knowledge transfer.

This study provides a specific understanding of the relationships between organizational unlearning and knowledge transfer by focusing on knowledge and routine compatibility as the crucial links, and enriches existing literature regarding knowledge transfer.

The purpose of this study is to address the challenge of task allocation in multi-robot systems by getting the minimum overall task completion time and task allocation scheme while also minimizing robot energy consumption. This study aims to move away from traditional centralized methods and validate a more scalable distributed approach.

This paper proposes a distributed algorithm for the multi-robot task allocation problem, aimed at getting the minimum task completion time along with the task allocation scheme. The algorithm operates based on local interaction information rather than global information. By using the Consensus-Based Auction Algorithm (CBAA), it seeks to effectively minimize energy consumption without affecting the minimum completion time required for overall task allocation.

The proposed distributed algorithm successfully reduces robot energy consumption while effectively obtaining the shortest overall task completion time and corresponding task allocation scheme. Numerical simulations conducted using MATLAB software demonstrated its superior performance, and empirical testing on the Turtlebot3-Burger robot platform further substantiated these findings.

The original contribution of this study lies in the development of an enhanced distributed task allocation strategy using CBAA to improve efficiency in multi-robot environments. Its value extends to applications that require rapid and resource-aware coordination, such as automated logistics or search-and-rescue operations.

This study focuses on the context of interactions in online medical-consultation services. It integrates theories of value co-creation and social support, and it introduces customer-perceived doctor’s contribution behaviors (DCBs) as mediators to investigate the impact of customer value co-creation behavior (CVCB) on customer service well-being (CSW). This study also explores the moderating roles of communication and task characteristics of interactive medical interfaces.

A survey of 353 patients with online consultation experience were conducted. Structural equation modeling and PROCESS macro technology were used to test the hypotheses.

CVCB positively affects CSW through the mediating role of DCBs, including cure-based knowledge contribution behavior (KCB) and care-based emotional supportive behavior (ESB). The difference in task-oriented communication styles between customers and doctors weakens the positive effect of CVCB on perceived doctor’s cure-based KCB and care-based ESB. However, task complexity diminishes the positive effect of CVCB on perceived doctor’s cure-based KCB.

Managers of online medical-consultation platforms can optimize service design and enhance positive doctor–patient interactions to improve CSW and promote sustainable platform growth. This can effectively address social equity issues associated with the uneven distribution of medical resources and enhance societal well-being.

There is insufficient attention to the perceived well-being caused by the service context and customer–employee interactions, especially in online environments. This study contributes to value co-creation theory and customer well-being research by exploring factors influencing CSW in online medical care.

This paper aims to explore the relationships between organizational unlearning and knowledge transfer in cross-border mergers and acquisitions (M&As) from a routine-based view. The study also stresses the mediating role that knowledge integration capability plays in this relationship.

In all, 178 samples were collected from Chinese multinational corporations that experienced cross-border M&As. In addition, the bootstrap method was used to test the mediating role of knowledge integration capability.

The empirical results indicate that knowledge integration capability is the crucial link between organizational unlearning and knowledge transfer. Specifically, this capability goes beyond the direct effect of organizational unlearning on knowledge transfer and points to the importance of enhancing knowledge integration capability. In turn, knowledge integration capability has a significant influence on knowledge transfer. The study finds that knowledge integration capability mediates the relationship between organizational unlearning and knowledge transfer.

This study adopts a routine-based view to develop a theoretical model for examining the relationship between organizational unlearning, knowledge integration capability and knowledge transfer in the context of cross-border M&As. This model provides new insights for a routine-based understanding of the important mediating role of knowledge integration capability for knowledge transfer and the effects of this role on the specific knowledge transfer, i.e. technological, marketing and managerial knowledge.

The proposed DHHFLOWLAD is used to design a recommendation system, which aims to provide the most appropriate treatment to the patient under a double hierarchy hesitant fuzzy linguistic environment.

Based on the ordered weighted distance measure and logarithmic aggregation, we first propose a double hierarchy hesitant fuzzy linguistic ordered weighted logarithmic averaging distance (DHHFLOWLAD) measure in this paper.

A case study is presented to illustrate the practicability and efficiency of the proposed approach. The results show that the recommendation system can prioritize TCM treatment plans effectively. Moreover, it can cope with pattern recognition problems efficiently under uncertain information environments.

An expert system is proposed to combat COVID-19 that is an emerging infectious disease causing disruptions globally. Traditional Chinese medicine (TCM) has been proved to relieve symptoms, improve the cure rate, and reduce the death rate in clinical cases of COVID-19.

Credit risk assessment has gained importance in recent years due to global financial crisis and credit crunch. Financial institutions therefore seek the support of credit rating agencies to predict the ability of creditors to meet financial persuasions. The purpose of this paper is to construct neural network (NN) and fuzzy support vector machine (FSVM) classifiers to discriminate good creditors from bad ones and identify a best classifier for credit risk assessment.

This study uses artificial neural network, the most popular AI technique used in the field of financial applications for classification and prediction and the new machine learning classification algorithm, FSVM to differentiate good creditors from bad. As membership value on data points influence the classification problem, this paper presents the new FSVM model. The instances membership is computed using fuzzy c-means by evolving a new membership. The FSVM model is also tested on different kernels and compared and the classifier with highest classification accuracy for a kernel is identified.

The paper identifies a standard AI model by comparing the performances of the NN model and FSVM model for a credit risk data set. This work proves that that FSVM model performs better than back propagation-neural network.

The proposed model can be used by financial institutions to accurately assess the credit risk pattern of customers and make better decisions.

This paper has developed a new membership for data points and has proposed a new FCM-based FSVM model for more accurate predictions.

All those effluent streams having compromised characteristics pose negative effects on the environment either directly or indirectly. Health care facilities and hospitals also generate a large amount of effluent like other industries containing harmful and toxic pharmaceutical residual compounds due to uncontrolled use of drugs, besides others. The occurrence of antibiotic in the environment is of utmost concern due to development of resistant genes. These get mixed up with ground and surface water due to lack of proper treatment of hospital wastewater. The effect of pharmaceutical compounds on human society and ecosystem as a whole is quite obvious. There are no strict laws regarding discharge of hospital effluent in many countries. Contrary to this, the authors do not have appropriate treatment facilities and solution to solve day by day increasing complexity of this problem. Moreover, water discharged from different health facilities having variable concentration often gets mixed with municipal sewage, thus remains partially untreated even after passing from conventional treatment plants. The purpose of this paper is to highlight the occurrences and fate of such harmful compounds, need of proper effluent management system as well as conventionally adopted treatment technologies nowadays all around the globe. This mini-review would introduce the subject, the need of the study, the motivation for the study, aim, objectives of the research and methodology to be adopted for such a study.

Hospital effluents consisting of pathogens, fecal coliforms, Escherichia coli, etc, including phenols, detergents, toxic elements like cyanide and heavy metals such as copper (Cu), iron (Fe), gadolinium (Gd), nickel (Ni), platinum (Pt), among others are commonly detected nowadays. These unwanted compounds along with emerging pollutants are generally not being regulated before getting discharged caused and spread of diseases. Various chemical and biological characteristics of hospital effluents are assessed keeping in the view the threat posed to ecosystem. Several research studies have been done and few are ongoing to explore the different characteristics and compositions of these effluent streams in comparison so as to suggest the suitable conventional treatment techniques and ways to manage the problem. Several antibiotic groups such as ciprofloxacin, ofloxacin, sulfa pyridine, trimethoprim, metronidazole and their metabolites are reported in higher concentration in hospital effluent. The aquatic system also receives a high concentration of pharmaceutical residues more than 14,000 μg/L from treatment plants also and other surface water or even drinking water in Indian cities. Many rivers in southern parts of India receives treated water have detected high concentration drugs and its metabolites. As far as global constraints that need to be discussed, there are only selected pharmaceuticals compounds generally analyzed, issue regarding management and detection based on method of sampling, frequency of analysis and observation, spatial as well as temporal concentration of these concerned micropollutants, accuracy in detecting these compounds, reliability of results and predictions, prioritization and the method of treatment in use for such type of wastewater stream. The complexity of management and treatment as well need to be addressed with following issues at priority: composition and characterization of effluent, compatible and efficient treatment technology that needs to be adopted and the environment risk posed by them. The problem of drugs and its residues was not seen to be reported in latter part of 20th century, but it might be reported locally in some part of globe. This paper covers some aspect about the disposal and regulatory standard around the world toward hospital effluent discharge, its managements and treatment technologies that are adopted and best suitable nowadays various industries and monitoring the efficiencies of existing treatment systems. This mini-review would introduce the subject, the need, the motivation and objectives of the study and methodology can be adopted for such a study.

The compiled review gives a complete view about the types of antibiotics used in different health care facilities, their residue formation, occurrences in different ecosystems, types of regulations or laws available in different counties related to disposal, different type of treatment technologies, innovative combined treatment schemes and future action needed to tackle such type of effluent after its generation. The thesis also highlights the use of certain innovative materials use for the treatment like nanoparticles. It also discusses about the residues impact on the human health as well as their bioaccumulative nature. If the authors relate the past to the current scenario of pharmaceutical compounds (PhACs) in the environment, the authors will certainly notice that many diseases are nowadays not curable by simple previously prescribed Ab. Many research projects have been done in European countries that have shown the risk of such residues like Pills, Sibell, Poseidon, No pills, Neptune, Knappe, Endetech, etc. In the previous section, it was mentioned that there are no stringent laws for hospital wastewater and in many countries, they are mixed with domestic wastewater. Many difficulties are there with this research due to complex analysis, detection of targeted Ab, affecting waterbodies rate of flow, nature of treatment varies with season to season. The way nature is being degraded and harmful effect are being imposed, it is important to take immediate and decisive steps in this area. Wastewater treatment plants (WWTPs) serves as a nursery for antibiotic-resistant systems, hence monitoring with great attention is also needed. Many trials with different treatment process, in combination, were considered. Many countries are paying great attention to this topic by considering the severity of the risk involved in it.

Previous studies by several scientists show that the pharmaceutical residues in the discharged effluent displayed direct toxic effects, and sometimes, detrimental effects in the mixture were also observed. The discharge of untreated effluent from hospitals and pharmaceuticals and personal care products in the natural ecosystem poses a significant threat to human beings. The pharmaceuticals, like antibiotics, in the aquatic environment, accelerate the development of the antibiotic-resistant genes in bacteria, which causes fatal health risks to animals and human beings. Others, like analgesics, are known to affect development in fishes. They also degrade the water quality and may lead to DNA damage, toxicity in lower organisms like daphnia and have the potential to bioaccumulate. A few commonly used nanoadsorbents for water and wastewater treatment along with their specific properties can also be used. The main advantages of them are high adsorption capacity and superior efficiency, their high reusability, synthesis at room temperatures, super magnetism, quantum confinement effect as well as eco-toxicity. This review will focus on the applicability of different nanoscale materials and their uses in treating wastewater polluted by organic and inorganic compounds, heavy metals, bacteria and viruses. Moreover, the use of various nanoadsorbents and nano-based filtration membranes is also examined.

A number of different pharmaceutical residues derived from various activities like production facilities, domestic use and hospitals have been reported earlier to be present in groundwater, effluents and rivers, they include antibiotics, psycho-actives, analgesics, illicit drugs, antihistamine, etc. In past few years environmental scientists are more concerned toward the effluents generated from medical care facilities, community health centers and hospitals. Various chemical and biological characteristics of hospital effluents have been assessed keeping in the view the common threats pose by them to the entire ecosystem. In this study, seven multispecialty hospitals with nonidentical pretreatment were selected for three aspects i.e. conventional wastewater characteristics, high priority pharmaceuticals and microbial analyses. The present work is to evaluate efficacy of advanced wastewater treatment methods with regard to removal of these three aspects from hospital effluents before discharge into a sewage treatment plant (STP). Based on test results, two out of seven treatment technologies, i.e. MBR and CW effectively reducing conventional parameters and pharmaceuticals from secondary and tertiary treatments except regeneration of microbes were observed in tertiary level by these two treatments.

This review has aimed to identify the emerging contaminants, including pharmaceutical residues, highly consumed chemicals that are present in the hospital effluent, along with their physicochemical and biological characteristics. In this, the main objective was to review the occurrences and fate of common drugs and antibiotics present in effluents from hospital wastewaters. As far as global constraints that need to be discussed, there are only selected pharmaceuticals compounds generally analyzed, issue regarding management and detection based on method of sampling, frequency of analysis and observation, spatial as well as temporal concentration of these concerned micropollutants, accuracy in detecting these compounds, reliability of results and predictions, prioritization and the method of treatment in use for such type of wastewater stream are among the major issues (Akter et al., 2012; Ashfaq et al., 2016; García-Mateos et al., 2015; Liu et al., 2014; Mubedi et al., 2013; Prabhasankar et al., 2016; Sun et al., 2016; Suriyanon et al., 2015; Wang et al., 2016; Wen et al., 2004). This paper covers some aspect about the disposal and regulatory standard around the world toward hospital effluent discharge, its managements and treatment technologies that are adopted and best suitable nowadays.

This study many multispecialty hospitals with nonidentical pretreatment were selected for three aspects i.e. conventional wastewater characteristics high priority pharmaceuticals and microbial analyses. The present work is to evaluate efficacy of advanced wastewater treatment methods with regard to removal of these three aspects from hospital effluents before discharge into an STP. Based on test results, two out of different treatment effectively reducing conventional parameters and pharmaceuticals from secondary and tertiary treatments except regeneration of microbes were observed in the tertiary level by these two treatments were studies followed by ozonation and ultraviolet-ray treatment.