Computational Management Science

Top Research Topics at Computational Management Science?

The journal explores disciplines such as Mathematical optimization, Stochastic programming, Econometrics, Portfolio and Optimization problem. The work on Mathematical optimization tackled in the journal brings together disciplines like Set (abstract data type), Portfolio optimization and Integer (computer science). Computational Management Science focused on Stochastic programming research but expanded to cover Stochastic optimization.

The majority of Econometrics studies presented zero in on Volatility (finance).

• Mathematical optimization (47.47%)
• Stochastic programming (13.82%)
• Econometrics (12.67%)

What are the most cited papers published in the journal?

• Partitioning procedures for solving mixed-variables programming problems (665 citations)
• ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure (359 citations)
• Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games (350 citations)

Research areas of the most cited articles at Computational Management Science:

The journal publications generally zeroe in on subjects such as Mathematical optimization, Stochastic programming, Optimization problem, Mathematical economics and Nash equilibrium. The journal publications address concerns in Mathematical optimization which are intertwined with other disciplines, such as Algorithm and Portfolio optimization, Portfolio. The journal publications facilitate discussions on Nash equilibrium that incorporate concepts from other fields like Equilibrium selection and Multilevel programming.

What topics the last edition of the journal is best known for?

• Statistics
• Artificial intelligence
• Mathematical optimization

The previous edition focused in particular on these issues:

The journal mainly deals with areas of study such as Mathematical optimization, Econometrics, Stochastic programming, Microeconomics and Portfolio. The journal holds forums on Mathematical optimization that merges themes from other disciplines such as Point (geometry) and State (computer science). Many of the research works in Econometrics, specifically Quantile, closely connected to disciplines like Exponent.

While work presented in Computational Management Science provided substantial information on Stochastic programming, it also covered topics in Electricity market, Bidding, Exploit, Industrial organization and Job shop scheduling. The research on Microeconomics featured in the journal combines topics in other fields like Profitability index, restrict, Loyalty and Multinomial logistic regression. Issues in Portfolio were discussed, taking into consideration concepts from other disciplines like Investment theory, Stochastic dominance, Investment (macroeconomics) and Trading strategy.

The most cited articles from the last journal are:

• Predictive stochastic programming (2 citations)
• A diversified AHP-tree approach for multiple-criteria supplier selection (2 citations)
• Single cut and multicut stochastic dual dynamic programming with cut selection for multistage stochastic linear programs: convergence proof and numerical experiments (2 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Computational Management Science (based on the number of publications) are:

• Anna Nagurney (8 papers) absent at the last edition,
• Theodore B. Trafalis (7 papers) absent at the last edition,
• Panos M. Pardalos (7 papers) absent at the last edition,
• Michal Kaut (7 papers) published 1 paper at the last edition,
• Francesca Maggioni (6 papers) published 1 paper at the last edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Computational Management Science (based on the number of publications) are:

• University of Bergamo (18 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Imperial College London (17 papers) absent at the last edition,
• Norwegian University of Science and Technology (15 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• University of Florida (13 papers) absent at the last edition,
• University of Vienna (11 papers) absent at the last edition.

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.

Publication chance based on affiliation

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, 14.29% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 6.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 23.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 30.00% of all publications and 40.00% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.