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The purpose of this paper is to propose a site selection method using grey system theory for a desalination plant in Libya.

In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best site. Therefore, a real case study of a selection problem of a site selection of desalination plant in Libya was used to illustrate the proposed approach.

Site selection in a desalination plant can be one of the most important decisions in planning a desalination project. The decision affects both the project cost and potentially the project schedule. Based on the results of grey model, a clear order of these sites and the degree of preference are obtained. This paper presents a way to improve a site selection by using a grey model, especially in a complex environment like Libya.

To the best knowledge of the authors, there is no literature for site selection using grey system theory in a desalination plant in Libya. This attempt may well enhance and facilitate the decision-making process of the best site in the country involved in this research.

The purpose of this paper is to produce an intelligent technique for modelling machine tool errors caused by the thermal distortion of Computer Numerical Control (CNC) machine tools. A new metaheuristic method, the cuckoo search (CS) algorithm, based on the life of a bird family is proposed to optimize the GMC(1, N) coefficients. It is then used to predict thermal error on a small vertical milling centre based on selected sensors.

A Grey model with convolution integral GMC(1, N) is used to design a thermal prediction model. To enhance the accuracy of the proposed model, the generation coefficients of GMC(1, N) are optimized using a new metaheuristic method, called the CS algorithm.

The results demonstrate good agreement between the experimental and predicted thermal error. It can therefore be concluded that it is possible to optimize a Grey model using the CS algorithm, which can be used to predict the thermal error of a CNC machine tool.

An attempt has been made for the first time to apply CS algorithm for calibrating the GMC(1, N) model. The proposed CS-based Grey model has been validated and compared with particle swarm optimization (PSO) based Grey model. Simulations and comparison show that the CS algorithm outperforms PSO and can act as an alternative optmization algorithm for Grey models that can be used for thermal error compensation.

The purpose of this paper is to propose a supplier selection method using grey system theory for a steelmaking company in Libya.

In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best supplier. Therefore, an example of a selection problem of a steelmaking company in Libya was used to illustrate the proposed approach.

Supplier selection in a supply chain is a critical strategic decision for company’s success and has attracted much attention of both academic scholars and decision makers. The authors have found that the Grey model can play an important role in improving supplier selection strategy, especially when it is in a situation where complex sustainability environments (i.e. Libya) exist.

No literature has been found till date for selection of supplier using grey system theory in a steelmaking company in Libya. An attempt in this regard could enhance a decision-making technique for selecting the best suppliers for the selected case company.

Performance evaluation of airports or any other organisation is paramount for improving performance. The purpose of this paper is to evaluate and compare the performance of the three international airports in Libya (MJI, MRA, and LAQ airports) by considering five aspects of performance.

The considered aspects are airport service quality, airport operations, airport economy, safety and security, and environmental. The paper uses the grey system theory to assess these airports by summarizing the opinions of experts.

The finding of this study provides directions of the evaluated airports to take the correct actions to improve overall performance.

No literature has been found till date is to evaluate and compare the performance of the international airports in Libya.

The coronavirus disease 2019 (COVID-19) pandemic has subjected a considerable strain on the healthcare (HC) systems around the world. The most affected countries are developing countries because of their weak HC infrastructure and meagre resources. Hence, building the resilience of the HC system of such countries becomes essential. Therefore, this study aims to build a resilience-based model on the HC sector of Pakistan to combat the COVID-19 and future pandemics in the country.

The study uses a novel hybrid approach to formulate a model based on resilient attributes (RAs) and resilient strategies (RSs). In the first step, the multi-criteria decision-making (MCDM) technique, i.e. full consistency method (FUCOM) is used to prioritize the RAs. Whereas, the fuzzy quality function deployment (QFD) is used to rank the RSs.

The findings suggest “leadership and governance capacity” to be the topmost RA. Whereas “building the operational capacity of the management”, “resilience education” and “Strengthening laboratories and diagnostic systems” are ranked to be the top three RSs, respectively.

The model developed in this study and the prioritization RAs and RSs will help build resilience in the HC sector of Pakistan. The policymakers and the government can take help from the prioritized RAs and RSs developed in this study to help make the current HC system more resilient towards the current COVID-19 and future pandemics in the country.

A new model has been developed to present a sound mathematical model for building resilience in the HC sector consisting of FUCOM and fuzzy QFD methods. The main contribution of the paper is the presentation of a comprehensive and more robust model that will help to make the current HC system of Pakistan more resilient.

The study responds to the common concerns of authors, reviewers, and editors on writing and publishing high-quality literature review (LR) studies. First, we evolved the background and decision elements on the five parameters of a quality LR paper: Planning, Operationalizing, Writing, Embedding, and Reflecting (POWER), from the editorials and guiding literature. Statistical procedure and refinement of 256 responses from writers, reviewers, and editors revealed 37 decision elements. Finally, a multicriteria-decision-making approach was applied to the detailed responses from the lead editors of ABDC, Scopus, ABS, and WoS journals, and 31 decision elements were found strong enough to represent these five parameters on the quality of LR studies. All five parameters are found important to be considered. However, a high priority is suggested for embedding (the results coming out of the review) and operationalizing (the process of conducting the review), whereas reflection, writing, and planning of LR papers still remain important. The purpose of the POWER framework is to overcome the challenges and decision dilemmas faced by writers and decision-makers. The POWER framework acts as a guiding tool to conduct LR studies in general and business management scholars in specific ways. In addition, this study provides a checklist (Table 6) and template (Appendix A1) of a quality LR study to its stakeholders.

Educational policies, integrated practices, obliged strategies and notable benchmarks are always required by the higher educational institutions (HEIs) for operating business ventures into competent boundaries and to preside toward the overall new business density. The same are needed to be evaluated based on student's concerns for road-mapping sustainability. Accordingly, authors conducted present study to identify crucial quality characteristics (measures) under the origins of HEIs based on student's concerns using qualitative medium under Indian economy. The study is presenting critical dimensions and quality characteristics, which are seeking by the students for selecting HEIs for their studies.

Kano integrated-Grey-VIKOR approach is utilized in present study for road-mapping sustainability based on the determination of priority index and ranking. The study utilized three segments of methodology, where in the first segment, Kano technique is implicated to define priority index of quality characteristics. In the second segment, grey sets theory is implicated to capture the perceptions of the respondents. In the third segment, VIKOR technique is implicate to rank the HEIs.

The findings of the study will assist administrators in planning the prominent strategies that can embrace performance traits under HEI, which in turn will participate in growth and development of an economy. The findings have revealed “PPCS, ICMC, TSTR, PICM, AFEP, IMIS as Attractive performance characteristics,” “IEAF, OIAR, INET as One dimensional performance characteristics,” “QTCS, PORE, SIRD as Must-be performance characteristics” and “PQPE, PCTM as Indifferent performance characteristics.” Additionally, “Professional and placement characteristics of institute” is found as the most significant measure inspiring students for admiring engineering institutes. It is found that “Observance of institutional affiliation and recognition” and “Infrastructure, classroom management and control methods” are found as the second significant measures. “Patterns of question papers and evaluation medium” and “Personal characteristics of teacher and management” are found as the least competent characteristics admiring stakeholders for selecting HEI.

The present study can assist administrators in drafting refined policies and strategies for practising quality outputs by HEI. The study suggested critical quality characteristics, which in respond will aid in attracting more number of students toward educational institutes. A study under Indian context is demonstrated for presenting critical facts and attaining higher student's enrolment rates.

As the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.

Using the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.

Many grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.

The present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

The present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.

Grey Systems: Theory and Application (GSTA) journal started publication in 2011 and completed a decade in 2021. The purpose of this study is to provide a detailed bibliometric analysis of the articles published in GSTA and their content primary trends and themes.

This study uses the Web of Science (WoS) database to analyze the content of published articles. A range of bibliometric analyses and indicators are applied to analyze the GSTA article content using science mapping tools of the Bibliometrix package in the R environment.

The GSTA publishes around 28 articles each year with citations of this work steadily growing over time. The impact of these publications is measured as total mean citations which increased from 0 to 11. The journal has attracted contributors from around the globe, most often affiliated with China, India and Europe. Thematic evolution of the journal's themes reveals that it has expanded its scope to include topics such as relational analysis, decision making, incidence analysis, and forecasting, hybrid grey-fuzzy or grey-rough modeling, etc.

The study is majorly based on GSTA data available on the WoS database.

This study provides the first overview of GSTA's publication and citation trends as well as the evolution of its thematic structure. It also suggests future directions that the journal might take to strengthen its position.