| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Business and Management | 473 | 10 | 11 | 6 |
| Computer Science | 942 | 7 | 6 | 4 |
| Engineering and Technology | 1222 | 11 | 16 | 5 |
The concepts of Operations research, Mathematical optimization, Management science, Multiple-criteria decision analysis and Decision analysis are tackled in the journal. The presented studies in Analytic hierarchy process, Goal programming and Multicriteria decision fall within the purview of Operations research but it also intertwines with topics in Decision maker. The study on Analytic hierarchy process presented is investigated in conjunction with research in Pairwise comparison.
It addresses concerns in Mathematical optimization which are intertwined with other disciplines, such as Mathematical economics and Preference (economics). Decision support system, Decision problem and Process (engineering) are some topics wherein Management science research discussed in the journal have an impact. The Decision analysis works featured in Journal of Multi-criteria Decision Analysis incorporate elements from Decision rule and Optimal decision.
The most cited publications mainly deal with areas of study such as Management science, Operations research, Multiple-criteria decision analysis, Decision analysis and Mathematical optimization. The most cited publications explore issues in Management science which can be linked to other research areas like Decision support system, Business decision mapping, Structuring, Decision problem and Process (engineering). In addition to Mathematical optimization research, the published articles aim to explore topics under Analytic hierarchy process, Preference (economics) and Fuzzy logic.
Journal of Multi-criteria Decision Analysis was organized to reinforce research efforts on Multiple-criteria decision analysis, Analytic hierarchy process, Artificial intelligence, Sorting and Mathematical optimization. Some problems in Multiple-criteria decision analysis that were presented in it overlapped with concepts under Health technology, Health informatics, Risk analysis (engineering) and Family medicine. In the journal, Decision analysis and Algebra are investigated in conjunction with one another to address concerns in Analytic hierarchy process research.
The featured Artificial intelligence studies mainly concentrate on Machine learning but also cover areas of interest in Preference learning, Entropy (energy dispersal) and Multicriteria decision. Journal of Multi-criteria Decision Analysis aims to bridge the gap between the study of Mathematical optimization and Cost improvement. The concepts on Operations research presented in Journal of Multi-criteria Decision Analysis can also apply to other research fields, including Credit rating and Supply chain network.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Multi-criteria Decision Analysis (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Multi-criteria Decision Analysis (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 2.86% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 5.88% were posted by at least one author from the top 10 institutions publishing in the journal. Another 2.94% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.65% of all publications and 73.53% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Several students and researchers reading the Journal of Multi-criteria Decision Analysis might be interested to know how the research topics align with career opportunities in their areas of interest. Understanding this relationship can be a crucial factor in selecting which topics to delve deeper into for gaining a competitive edge in the job market or in pursuing a career in academia.
For instance, students who have shown interest in topics such as Operations research and Management Science may find that many top-tier organizations value these skills for making critical business decisions. Similarly, those versed in Artificial Intelligence research can find opportunities within technology firms, where AI is becoming an integral part of product development and customer experience enhancement.
Additionally, these research topics can also point students towards advanced study opportunities. For example, the topics of Operations Research and Management Science are often key components in the curriculum of some of the best business schools in Florida. By aligning their research focus with these areas, students not only expand their knowledge but also increase their chances of getting admitted to these prestigious institutions.
As we can see, the connection between research areas and career opportunities is a significant one. It is highly recommended that students and researchers remain aware of the practical implications of their work in a societal and professional context.
Miguel Ortiz‐Barrios;Chris Nugent;Ian Cleland;Mark Donnelly
(2020)Ali Hosseini;Ahmad Pourahmad;Athareh Ayashi;Gwo-Hshiung Tzeng
(2021)Bosko Blagojevic;Dimitris Athanassiadis;Raffaele Spinelli;Jyrki Raitila
(2020)Bhaskar B. Gardas;Nilesh P. Ghongade;Annasaheb H. Jagtap
(2021)Bhaskar B. Gardas
(2021)Joana A. T. Abrantes;Fernando A. F. Ferreira;Fernando A. F. Ferreira;Constantin Zopounidis;Leandro F. Pereira
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