The widespread application of quantitative measurements in evaluating research, though very attractive for its supposed objectivity and expediency, has on the other hand given rise to an intricate web of ethical issues and biases in the system. The current review not only critiques but strategically moves through a thorough system analysis revealing the limitations of metrics and their sociotechnical implications. Our first step is to map out the ethics involved and thereby set up rules for the proper use of metrics. The next stage is to look into the bias aspect of metrics and the various forms of bias such as issues of location and language, unfairness among different fields, and the ongoing divide between the genders. The whole matter of metric malpractice—gaming, manipulation, and the detrimental over-optimization of research integrity—are some of the things that we have extensively discussed in this paper. Likewise, we have raised the emerging trend's ethical implications, namely, altmetrics, visualization, and algorithmic evaluation, taking into account their capability of both widening influence and introducing additional types of bias. Alongside this, we provide a picture of recent empirical findings about the status of research ethics and the level of support from institutions. Lastly, we bring together a progressive agenda for change, which includes institutional accountability, the shaping of reflexive evaluation methodologies, and the essential incorporation of qualitative, expert opinion. We express that a major change in mentality is necessary—one that will place metrics in a supportive role in a holistic, qualitative, and ethically-grounded research evaluation ecosystem.

Supplier selection can be described as a very important problem that is not only multi-faceted but also takes into consideration the different choice making methods (MCDM). Supplier selection directly influences an entity's competitiveness, resilience, and sustainability. The main aim of this paper is to present the integration of the three most widely used MCDM methods -The Analytic Hierarchy Process (AHP), Best-Worst Method (BWM), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) -in supplier selection research in a systematic way. A bibliometric analysis of Scopus database shows a peculiar trend of geographical and journal-based variations. The search for "Supplier Selection" along with AHP yields a total of 521 articles, with India, China, and Turkey being the top three contributors, and Expert Systems with Applications and International Journal of Production Research being the main areas for publishing the findings. If one makes the same search with BWM one gets a total of 123 papers, where Iran and China take the lead, and the two areas with the highest representation are Journal of Cleaner Production and Sustainability. The integrated search consisting of supplier selection and one of the three MCDM methods mentioned above yields another 123 articles with India and Turkey as the leading contributors. The review goes into the detailed methodology of AHP, BWM, and TOPSIS explaining their specific advantages and disadvantages. Moreover, it brings together the results from more than 20 key studies to demonstrate the various ways of applying these methods in the area of green, resilient, and sustainable supply chains. The paper wraps up with a discussion on the emerging trends, challenges like methodological redundancy and geographical concentration, and future research directions which call for, among others, more hybrid models and the application of uncertainty handling techniques like fuzzy and rough sets.

The worldwide quest for sources of energy that are both sustainable and renewable has made algal biofuel a strong candidate to take over fossil fuels. Here, for the first time, a scientific study offers an in-depth analysis based on citation of the top 100 articles in the field of algae and biofuel and the Scopus database has been used for drawing the citation map of this fast-developing research area. Various quantitative bibliometric indicators are used in this paper to show and explain the development of the field through publication growth, citation analysis, geographical distribution, author and institutional productivity, journal performance, and keyword co-occurrence networks. It was 2010 when there was an exploding point of research output and citation impact and all this was due to the global energy crisis and climate change imposing a greater need for research believers. Also, the cutting-edge themes have kept on changing from the primary dependence of the choice of the best strain for lipid induction and isolation to complications in downstream processing, techno-economic assessment, life cycle analysis (LCA), integrated biorefinery systems, and co-products valorization. Mapping of geographical distribution clearly points out U.S., China, and India as the top three countries contributing to research along with their noteworthy international collaboration. Also, the views of Pugazhendhi Arivalagan, Wei-Hsin Chen, and Mohamed F. A. Hossain are among those that have most impacted the discourse. The keyword co-occurrence network revealed four major clusters of themes which were: "Lipid extraction and transesterification," "Biorefinery and sustainability," "Cultivation and photobioreactors," and "Hydrothermal liquefaction." In conclusion, the field is growing from the basic laboratory research to the entire, large-scale, and economically viable systems, with future trends in the direction of the application of genetic engineering, AI-driven optimization, and integration with the circular bio-economy. The results were a great help for researchers, policymakers, and industry players in determining the past, present, and future of algal biofuel research.

The blood supply chain (BSC) is a crucial and intricate system in the healthcare sector, which is marked by perishable products, fluctuating supply and demand, and a major impact of inefficiency. This paper showcases a detailed scientific review of BSC literature from 2010 to 2025 through scientometric methods, thereby mapping out its intellectual structure and development. By scrutinizing both foundational and recent publications, the authors are able to point out the research streams, methodological trends and main scholars. The scrutiny brings forward three leading research paradigms: (1) robust and resilient network design for disaster response, with Jawad as the leading scholar; (2) green and sustainable BSC modeling under uncertainty, where Pishvaee and his team are the main contributors; and (3) integrated inventory-routing problems for perishables, with Ramezanian as the pivotal author. This discipline is moving away from deterministic, single-objective models to the development of intricate multi-objective frameworks under hybrid uncertainties (robust, fuzzy, stochastic) which are being solved increasingly with metaheuristics and supported by case studies from real applications. The new trends include the combination of AI/ML for forecasting and decision-making, blockchain for transparency, and drones for the delivery part. The present review collects all these advancements and gives a succinct direction for both researchers and practitioners.

Facility Layout Planning (FLP) is one of the most important strategic decisions that have a very big effect on the operational efficiency and therefore also the productivity and cost-effectiveness of manufacturing and service systems. The uncertainty which is inherent to the parameters like product demand, material flow, and processing times makes the FLP problem very complicated and dynamic. This paper exhibits a detailed review of the works done so far on FLP under uncertainty which has been based on an analysis of 163 articles from the Scopus database. The review organizes and evaluates systematically the main methodologies used, among them mathematical programming, heuristics and metaheuristics, simulation, and Multi-Criteria Decision-Making (MCDM) methods. The different types of uncertainty—fuzzy, stochastic, robust, and fuzzy-random—being modeled and integrated into solution approaches is one of the main areas of focus. It turned out from the analysis that hybrid metaheuristics, especially when combined with fuzzy MCDM techniques, are the most common and effective means of dealing with fluoroscope FLP issues today. Moreover, the paper contains a bibliometric analysis that underlines the main contributors, geographical patterns, and the trend of shifting research emphasis toward topics like construction site layout, sustainable logistics, and digital twin-supported planning. The review not only presents the gaps in the current literature but also points to further research implications including more integrated use of AI and dealing with the problem of real-time dynamic layout reconfiguration.

This article introduces a scientometric investigation regarding the use of Multi-Criteria Decision-Making (MCDM) techniques in the area of portfolio optimization. The study, which employs a carefully selected dataset of 108 scholarly articles that are drawn from the Scopus database, covers the period 2003 to 2026, and maps the intellectual landscape, identifies the leading methodologies, and tracks the trends of migration. We perform a systematic analysis of the occurrence, impact, and application domains of 20 different MCDM methods, which include Data Envelopment Analysis (DEA), the Analytic Hierarchy Process (AHP), TOPSIS and PROMETHEE, among others. The study employs key indicators such as the number of publications, the number of citations, the geographical distribution of authors, as well as the dispersion of journals, to assess the impact and uptake of the various techniques. The analysis demonstrates the dominance of DEA as a method, which is often combined with other MCDM methods and metaheuristics. A trend towards hybridization, which includes the combination of MCDM with fuzzy set theory, machine learning, and evolutionary algorithms, has been recognized as one of the main factors contributing to the innovation of recent techniques. In addition, the study points out the increasing adoption of Environmental, Social, and Governance (ESG) factors and big data analytics into the portfolio selection process. The survey presents a quantitative picture of the domain and provides researchers and practitioners with valuable insights through the identification of the established pillars, the emerging hotspots, and the future research trajectories in the field of MCDM-based portfolio optimization.