Mathematical Methods in Skills-based Workforce Scheduling: A Comprehensive Review

The aim of this study is to obtain an overview of the literature on multi‐criteria decision‐making (MCDM) methods in educational research, to map the literature, to identify existing knowledge and application areas, to reveal the methods used and their purposes of use, and to reveal the thematic structure of the field. This study followed a systematic review methodology covering 328 studies obtained from Web of Science, Scopus and ERIC databases. According to the findings of the study, the related literature has shown a significant growth trend in the last two decades. Although journals from various disciplines contribute to the literature, journals in the field of operations research and management science dominate the literature. Established methods such as AHP, TOPSIS and fuzzy AHP are the most commonly used. However, methods such as fuzzy DEMATEL, BWM, Delphi and fuzzy Delphi have been included in educational research in the last decade. Although crisp methods dominate the educational literature, fuzzy methods have been on the rise in recent years. In addition, hybrid approaches using more than one method have shown an increasing trend in recent years. The most common decision problematics in the literature are ranking, choice, description and sorting. While more than half of the literature focuses on higher education‐level problems, the highest diversity of topics is seen in higher education. This study reveals 13 educational themes in the literature and performance evaluation is the leading topic. In addition, this study also reveals periodical changes of theme.

Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators

This paper provides a bibliometric analysis of the articles in the field of operations research or management science (OR/MS) published in the years 1980–2018 by European researchers. The analysis’s objective is to identify and examine the current state of OR/MS studies in Europe, which publishes about 38% of the papers published worldwide. The analysis was based on the data from the Web of Science (WoS) databases. We found a total of 65,352 papers in 148 different journals in the OR/MS field. The results provide a general picture of the studies, which are classified according to the most influential authors, institutions, papers, and journals. The study revealed that the ratio of OR/MS studies having at least one European author has steadily increased over the decades from 28.27% in the 1980 s to 41.29% in the 2010 s. The analysis also provides citation statistics of the European OR/MS articles. The study concluded that the impact of European publications is less than the impact of U.S. publications. The bibliometric analysis of the studies showed that only a small portion of the countries/regions, institutions, and even authors published a substantial portion of the papers, as indicated by the Pareto rule. The research trends have been identified through an analysis of keyword usage over the years. In keyword analysis, which subcategories are studied together is also identified. In the paper, collaboration among countries and institutions is also identified and depicted by using VOS viewer.

A state-of-the-art review on D number (2012-2022): A scientometric analysis

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Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, and countable subadditivity axioms. The goal of uncertainty theory is to study the behavior of uncertain phenomena such as fuzziness and randomness. The main topics include probability theory, credibility theory, and chance theory. For this new edition the entire text has been totally rewritten. More importantly, the chapters on chance theory and uncertainty theory are completely new. This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, and management science will find this work a stimulating and useful reference. (orig.)

This book introduces readers to the basic concepts of and latest findings in the area of differential equations with uncertain factors. It covers the analytic method and numerical method for solving uncertain differential equations, as well as their applications in the field of finance. Furthermore, the book provides a number of new potential research directions for uncertain differential equation. It will be of interest to researchers, engineers and students in the fields of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, automation, economics, and management science.

Background: The 1998 book "Carrots, Sticks & Sermons: Policy Instruments and Their Evaluation" introduced a seminal typology categorizing policy tools by their mechanisms of influence. Despite its potential to shape policy theory and practice, its broader disciplinary impact and citation patterns remain underexplored. This article evaluates the book's legacy in public policy literature while testing bibliometric methods, including emerging generative artificial intelligence (GAI) tools for research synthesis. Purpose: The study aims to (1) assess the influence of the book on the discourse in the public policy literature and (2) explore the utility and limits of AI-driven tools for tracing scholarly impact. It addresses four questions: the book's citation trends, its presence in major disciplinary texts, citation intent, and GAI's ability to reference the work accurately. Setting: Not applicable. Intervention: Not applicable. Research Design: A mixed-methods approach consisted of: (i) quantitative bibliometrics (citation counts, trends, and keyword analysis), (ii) qualitative content analysis by human researchers (major disciplinary handbooks/textbooks and articles), and (iii) generative AI semantic search and analysis. Data Collection and Analysis: The quantitative analysis covered a corpus of interdisciplinary public policy literature from 1998 to 2024, extracted from citation databases (Scopus, Web of Science, Google Scholar). Qualitative analysis focused on 20 major handbooks and textbooks from public policy discipline (occurrence of references to book and policy instruments typology) and coding of 20 highly cited articles (classification of citation types in terms of intent). Work with GAI focused on semantic search and analysis with various AI platforms. Findings: The findings underscore the typology's enduring relevance while advocating for methodological rigor in impact assessments and GAI-aided research. The book has achieved "classic" status in public policy, evidenced by 1,369 citations on Google Scholar, 924 citations on Scopus, 627 citations on Web of Science, as well as presence in 16 out of 20 major disciplinary handbooks/textbooks. Its typology is foundational but often superficially referenced; only 7 of 20 top articles applied it directly. GAI tools also referred to the book, although frequently misattributed or diluted the source, highlighting risks in automated literature reviews. The authors propose updating the typology of policy instruments to include behavioral tools (e.g., nudges) and stress the need for human verification of GAI outputs.

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The measurement of profit, profitability, cost and revenue efficiency through data envelopment analysis: A comparison of models using BenchmarkingEconomicEfficiency.jl

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Many universities around the World have made important contributions in the field of operations research and management science. This article presents the most productive and influential universities between 1991 and 2015. For doing so, we use the Web of Science database in order to search for the information which is usually regarded as the most relevant for scientific research. The results show the country of origin of the leading universities being mainly from North America and Asia and especially from USA and China. The Centre National de la Recherche Scientifique (CNRS) of France is the most productive university while the Massachusetts Institute of Technology (MIT) of USA is the most influential one. The temporal evolution shows that USA is trailing its dominancy while China progressing quickly. The evaluation also reveals that Asian universities outperform North American universities during the last 5 years.

This article was downloaded by: [128.97.27.20] On: 25 May 2016, At: 09:44 Publisher: Institute for Operations Research and the Management Sciences (INFORMS) INFORMS is located in Maryland, USA Marketing Science Publication details, including instructions for authors and subscription information: http://pubsonline.informs.org Editorial—Marketing Science and Big Data Pradeep Chintagunta, Dominique M. Hanssens, John R. Hauser To cite this article: Pradeep Chintagunta, Dominique M. Hanssens, John R. Hauser (2016) Editorial—Marketing Science and Big Data. Marketing Science 35(3):341-342. http://dx.doi.org/10.1287/mksc.2016.0996 Full terms and conditions of use: http://pubsonline.informs.org/page/terms-and-conditions This article may be used only for the purposes of research, teaching, and/or private study. Commercial use or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publisher approval, unless otherwise noted. For more information, contact permissions@informs.org. The Publisher does not warrant or guarantee the article’s accuracy, completeness, merchantability, fitness for a particular purpose, or non-infringement. Descriptions of, or references to, products or publications, or inclusion of an advertisement in this article, neither constitutes nor implies a guarantee, endorsement, or support of claims made of that product, publication, or service. Copyright © 2016, INFORMS Please scroll down for article—it is on subsequent pages INFORMS is the largest professional society in the world for professionals in the fields of operations research, management science, and analytics. For more information on INFORMS, its publications, membership, or meetings visit http://www.informs.org

A novel approach for assessing academic journals: Application of integer DEA model for management science and operations research field