Journals in Decision sciences

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Machine Learning with Applications

ISSN: 2666-8270

Machine Learning with Applications (MLWA) is a peer reviewed, open access journal focused on research related to machine learning. The journal encompasses all aspects of research and development in ML, including but not limited to data mining, computer vision, natural language processing (NLP), intelligent systems, neural networks, AI-based software engineering, bioinformatics and their applications in the areas of engineering, medicine, biology, education, business and social sciences. It covers a broad spectrum of applications in the community, from industry, government, and academia. The journal publishes research results in addition to new approaches to ML, with a focus on value and effectiveness. Application papers should demonstrate how ML can be used to solve important practical problems. Research methodology papers should demonstrate an improvement to the way in which existing ML research is conducted. Submissions must be novel, technically sound, and clearly presented. MLWA accepts both regular papers and technical notes (technical notes are limited to a maximum of 10 pages). In addition, survey articles and discussion papers on ML are welcome. Submissions meeting journal criteria will undergo a single-blind review process, utilizing a minimum of two (2) external referees. Our dedicated editorial team, together with active researchers from all areas of ML, ensure that papers move through the evaluation and review as fast as possible without compromising on the quality of the process. The journal audience comprises academia, industry, and practitioners. Authors are strongly encouraged to make their datasets publicly accessible via a repository of their choosing. Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center. Reproducibility Badge Initiative and Software Publication Reproducibility Badge Initiative (RBI) is a collaboration with Code Ocean (CO), a cloud based computational reproducibility platform that helps the community by enabling sharing of code and data as a resource for non-commercial use. CO verifies the submitted code (and data) and certifies its reproducibility. Code submission will be verified by the Code Ocean team for computational reproducibility by making sure it runs, delivers results and it is self-contained. For more information please visit this help article. Note that an accepted paper will be published independently of the CO application outcome. However, if the paper receives the Reproducibility badge, it will be given additional exposure by having an attached R Badge, and by being citable at the CO website with a DOI. We invite you to convert your open source software into an additional journal publication in Software Impacts, a multi-disciplinary open access journal. Software Impacts provides a scholarly reference to software that has been used to address a research challenge. The journal disseminates impactful and re-usable scientific software through Original Software Publications which describe the application of the software to research and the published outputs. For more information contact us at: [email protected]

Multimodal Transportation

ISSN: 2772-5863

MULTRA provides a forum for high quality, cutting-edge research in transportation science and technology. MULTRA covers all modes - road, rail, air, maritime - and the integration of multimodal transport. Papers concerning multimodal integration or emerging transportation technologies are particularly welcome, as is work focusing on Intelligent Transportation Systems, Smart Transportation, or Big Data, as applied to transport planning, network modelling or traffic safety. MULTRA is an interdisciplinary journal and embraces work from a wide range of disciplines, including, but not limited to, transportation, logistics, economics, operations research, and urban planning. MULTRA publishes papers in two categories: Theory and Methodology: Papers in this category employ mathematical modeling, optimization theory, etc., to develop new concepts and technologies, rather than the refinement of established theories. Empirical Research: Papers in this category can either employ quantitative techniques from statistics, AI, machine learning etc., or qualitative research methods such as one-on-one interviews, focus groups, case study research etc., to obtain new insights into specific aspects of transportation science. Regardless of the category, MULTRA papers are expected to clearly articulate their expected impact on the practice of transportation science.

New Techno-Humanities

ISSN: 2664-3294

The Article Publishing Charge (APC) fee will be covered by Shanghai Jiao Tong University for articles submitted by 31st December 2025 The journal targets at the creative aspect of the humanities that has not been fully recognized in the established classification and methodology of disciplines. By embracing the practical extension of the latest scientific and technological methods, the journal aims to provide a forum for the discussion and in-depth analysis on the nature and development in the field of humanities, as well as the latter's interface with other disciplines. The traditional fields of research in humanities, such as literature, arts, history and philosophy, will be covered from a trans-disciplinary approach. First, the journal welcomes contributions in the fields of humanities from the pragmatic and experimental approaches by employing new technological methodologies, such as computational methods, visualization, data archives, processing and interaction, or surveys. Second, the journal also welcomes the philosophical, hermeneutic, critical, rhetorical, and historical approaches to interpretations of scientific and technological phenomena, focusing on their ontologies, nature, histories, methodologies and prospect of development. The journal publishes original research articles, review articles and book reviews on the topics including, but not limited to Methodology Literature and technology (science fiction studies, Internet literature) Critical theory (posthumanism, eco-criticism) Video games, gamification New media studies, media and technology Philosophy of science and technology Quantitative history Authorship attribution/ stylometry/ stylistics Modelling, digital visualization Techno humanities- culture, nature and history Digital cultural heritage Data visualization, statistical analysis, big data Translation studies with technological methods Corpus analysis Textual analysis Artificial intelligence and education/ language/ translation

Next Research

ISSN: 3050-4759

Next Research is a peer-reviewed multidisciplinary journal, publishing research spanning all scientific technical and medical communities. The journal is part of the Next family, a new suite of multidisciplinary journals from Elsevier spanning all branches of science. Managed by our dedicated team of in-house Editors, Next Research offers authors speed, consistency, innovation, flexibility, and ease of submission. Next Research is an inclusive venue for scientifically accurate manuscripts that meet the ethical and scientific publishing standards. It publishes all research topics across the fields of health sciences, physical sciences, life sciences and social sciences. Next Research publishes experimental, computational, and theoretical work, in traditional formats such as Original Research Articles, Communications and Reviews, as well as novel formats and video content. The journal provides authors with rigorous peer review ensuring articles adhere to a high technical standard, with rapid decisions and a highly visible platform for scientists to share their research. We believe that all rigorous research should be shared.

Omega

ISSN: 0305-0483
5 Year impact factor: 7.8
Impact factor: 6.9

The International Journal of Management Science Omega reports on developments in management, including the latest research results and applications. Original contributions and review articles describe the state of the art in specific fields or functions of management, while there are shorter critical assessments of particular management techniques. Other features of the journal are the "Memoranda" section for short communications and "Feedback", a correspondence column. Omega is both stimulating reading and an important source for practising managers, specialists in management services, operational research workers and management scientists, management consultants, academics, students and research personnel throughout the world. The material published is of high quality and relevance, written in a manner which makes it accessible to all of this wide-ranging readership. Preference will be given to papers with implications to the practice of management. Submissions of purely theoretical papers are discouraged. The review of material for publication in the journal reflects this aim. Now Incorporating Optimization and Business Analytics Applications We seek submissions related to the use of optimization and Business Analytics models and techniques to address practical optimization and Business Analytics challenges. Of particular interest are papers that present effective and contemporary modeling and solution approaches for a novel application area, as well as those papers that contain breakthroughs on solving established problems in application domains of considerable interest. Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services. Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

Operations Research Letters

ISSN: 0167-6377
5 Year impact factor: 1.2
Impact factor: 1.1

Operations Research Letters (ORL) promises the rapid review of short articles on all aspects of operations research. ORL welcomes pure methodological papers and applied papers with firm methodological grounding. Click the button below for the full description of the areas the journal covers. Area Editors Approximation & Heuristics Area Editor: Leah Epstein Associate Editors: M. Feldman, J. Hurink, N. Olver, J. Sgall, J. Verschae, K. Elbassioni, M. Chrobak The area covers all issues relevant to the development of efficient approximate solutions to computationally difficult problems. Examples are heuristic approaches like local search, worst case analysis or competitive analysis of approximation algorithms, complexity theoretic results, and computational investigations of heuristic approaches. Computational Social Science Area Editor: Vianney Perchet Associate Editors: P. Mertikopoulos, A. Drutsa, R. Smorodinsky This area publishes papers focusing on data-driven procedures, either from a theoretical or an applied perspective, in operation research, games, economics and other social science. The scope includes: sample/computational complexity of mechanisms, learning in games/OR/social science, empirical solutions with AI algorithms (such as, but not limited to, deep learning techniques) of complex problems, etc. Continuous Optimization Area Editor: Hector Ramirez Associate Editors: D. Jiang, M.F. Anjos, G. Eichfelder, F. Schoen, D. Orban, L.M. Briceno, D. Dadush Papers in all fields of continuous optimization that are relevant to operations research are welcome. These areas include, but are not restricted to, linear programming, nonlinear programming (constrained or unconstrained, convex or nonconvex, smooth or nonsmooth, finite or infinite-dimensional), complementarity problems, variational inequalities, bilevel programming, and mathematical programs with equilibrium constraints. Financial Engineering Area Editor: Ning Cai Associate Editors: D.Mitchell, X. He Financial engineering utilizes methodologies of optimization, simulation, decision analysis and stochastic control to analyse the effectiveness and efficiency of financial markets. This area is interested in papers that innovate in terms of methods or that develop new models which guide financial practices. Examples include but are not limited to Fintech, financial networks, market microstructure, derivative pricing and hedging, credit and systemic risk, energy markets, portfolio selection. Game Theory Area Editor: Tristan Tomala Associate Editors: S. Beal, D.W.K. Yeung, G. Zaccour, V. Ihele This area publishes papers which use game theory to analyze operations research models or make theoretical contributions to the theory of games. The scope includes (but is not limited to): cooperative and non-cooperative games, dynamic games, mechanism and market design, algorithmic game theory, games on networks, games of incomplete information. Graphs & Networks Area Editor: Gianpaolo Oriolo Associate Editors: F. Bonomo, Z. Friggstad, L. Sanita, Y. Faenza The area seeks papers that apply, in original and insightful ways, discrete mathematics to advance the theory and practice of operations research, as well as those reporting theoretical or algorithmic advances for the area. Of particular, but not exclusive, interest are papers devoted to novel applications, telecommunications and transportation networks, graphs and web models and algorithms. Inventory and Supply Chain Optimization Area Editor: Sean Zhou Associate Editors: G.J van Houtum, X. Gong, H. Abouee Mehrizi, J. Yang, A. Burnetas, Q. Li The area welcomes innovative papers focused on inventory control and supply management. Examples of topics include, but are not limited to, optimal sourcing, inventory and assortment selection, pricing and inventory optimization, capacity planning, multi-item/echelon systems, algorithms and bounds, near-optimal or asymptotic optimal solutions, and incentive design. Mixed Integer Optimization Area Editor: Marc Pfetsch Associate Editors: L. Liberti, G. Zambelli, J.P. Vielma, R. Fukasawa All submissions advancing the theory and practice of mixed integer (linear or nonlinear) programming like novel techniques and algorithmic approaches in convex relaxations, branch and cut, polyhedral combinatorics and theory driven heuristics are welcome. Case studies may be considered if they contribute to the general methodology. Operations Management Area Editor: Mahesh Nagarajan Associate Editors: T. Huh, C. Shi, L. Chu, N. Golrezaei, R. Roet-Green, D. Saban, Y. Ding The OM department aims to publish short, focused high quality research in the area of operations management, broadly the field of operations research applied to management problems. We welcome papers that use a wide variety of methodologies, both descriptive as well as prescriptive in nature including optimization, applied probability, simulation, and game theory. Scheduling Area Editor: Marc Uetz Associate Editors: E. Pesch, B. Moseley, R. Van Stee We seek original and significant contributions to the analysis and solution of sequencing and scheduling problems. This includes structural and algorithmic results, in particular optimization, approximation and online algorithms, as well as game theoretic modeling. Alll results are welcome as long as the relevance of a problem and significance of the contribution is made compellingly clear. Stochastic Models and Data Science Area Editor: Henry Lam Associate Editors: H. Bastani, J. Dong, K. Murthy, I. Ryzhov, Y. Zhou The area seeks papers broadly on the interplay between operations research and machine learning and statistics where stochastic variability and uncertainty play a crucial role. The area values both papers that develop or utilize stochastic analysis and computation in data science problems, including but not limited to reinforcement learning, stochastic iterative algorithms for model estimation or training, probabilistic analysis of statistical and machine learning tools, sampling and Monte Carlo methods, and also papers that integrate learning or statistical techniques into stochastic modeling to enhance prediction or decision-making for a wide variety of systems. Stochastic Networks and Queues Area Editor: Jamol Pender Associate Editors: H. Honnappa, W. Wang, Y. Zhao, E. Ozkan The area seeks papers that contribute to the modeling, analysis or innovative application of stochastic networks or queues. Work submitted should propose original models and develop novel analytical or computational methods more than incremental extensions. Examples of relevant application areas include but are not limited to supply chain management, manufacturing, financial engineering, healthcare, revenue management, service operations, telecommunications, sharing economy, online markets and public sector operations research. Application-oriented papers should demonstrate direct practical impact and have a strong methodological component as well. Stochastic Optimization and Machine Learning Area Editor: Angelos Georghiou Associate Editors:, M. Claus, E. Feinberg, P. Vayanos, G. Yi Ban, M. Bodur The Stochastic Optimization and Machine Learning area of Operations Research Letters solicits original articles that generate novel insights into problems that arise in optimization under uncertainty and in machine learning. The focus is broad and encompasses, among others, stochastic (dynamic) programming, (distributionally) robust optimization, data-driven optimization as well as the interface of machine learning with traditional areas of operations research. Successful submissions in this area are expected to make a clear and meaningful academic contribution, which may be through the study of new problems, models, solution techniques, performance analysis and convincing and reproducible numerical evaluations. Advisory Board: Jan Karel Lenstra, Nimrod Megiddo, Peter Glynn

Operations Research Perspectives

ISSN: 2214-7160
5 Year impact factor: 3.2
Impact factor: 2.5

Operations Research PerspectivesOperations Research Perspectives is an exciting new open access journal in the field of Operations Research and Management Science. It provides a dedicated and safe environment for open access research, with fast online publication on ScienceDirect for all accepted papers. Operations Research and Management Science has matured over the last 60 years. Nowadays it is a truly interdisciplinary field, intermixing theories and methodologies from mathematics, management science, computer science, operations management, economics, engineering, decision support, soft computing and many more, even reaching into psychology, ergonomics, knowledge management, education, quality management and biology. Rather than disseminating the different scholarly papers among a large number of journals, or focusing on specialized topics in niche publications, Operations Research Perspectives aims to bring together high-quality papers and original contributions with a potentially far-reaching impact in the field, inside the same journal. As a result, the interfaces between the different disciplines and the richness of the field are bolstered, facilitating new and interesting approaches. Operations Research Perspectives is aimed at a wide audience, ranging from management scientists, industrial engineers, computer scientists, mathematicians, practitioners and scientists working in the operations research field, understood in a wide sense. Similarly, all kinds of submissions, from short notes and technical letters to longer-length research papers, case studies and applications are welcomed. There is no page limit imposed and supplementary materials, including multimedia, are also welcomed. Operations Research Perspectives operates a rigorous single blind review process, with all accepted papers having at least 2 quality referee reports from prominent researchers in the field. Benefits to authors Operations Research Perspectives is an open access journal. The journal and the editorial workflow have been fine-tuned in order to speed up the revision process as much as possible. As a result of these two key benefits, authors' research results are disseminated quickly and openly to the field, which significantly increases their visibility and potential impact. Another key benefit is a series of cross-editorial agreements with other major operations research journals, namely Omega - The International Journal of Management Science, Decision Support Systems, European Journal of Operational Research, International Journal of Production Economics, Computers & Operations Research and Computers & Industrial Engineering. Under these agreements, selected high-quality papers that have already been peer reviewed might be accepted in a quick editorial decision for Operations Research Perspectives. We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.

Operations Research for Health Care

ISSN: 2211-6923
5 Year impact factor: 3
Impact factor: 2.1

Operations Research for Health Care (ORHC) focuses on the development and use of operations research and analytics in health and health care. The journal publishes high-quality operations research and/or analytics approaches to problems in health care from researchers and practitioners. ORHC encourages contributions related to typical problem areas of health care such as: hospitals, practices, care (including home care and long-term care), emergency management systems, as well as blood and organ logistics or population health policy and economic analysis. Typical OR/Analytics topics are therefore: forecasting, capacity planning, layout planning, transport and logistics, scheduling, and appointment planning among others - using methods such as: heuristics, machine learning, stochastic modelling, mathematical optimization, and simulation. Case studies or numerical experiments should be based on real world data. In addition to original research articles, ORHC publishes: Review Papers: The content and presentation of this international journal is such as to provide maximum utility to researchers, teachers and practitioners who have an interest in operations research techniques for good health care delivery. Review papers will be presented from time to time, as deemed suitable. Emphasis will be given to those areas in which significant advances are being made. Review Papers are by invitation only. Focused Issue Papers: ORHC also publishes focused issues on topics of interest related to its editorial mission. Such issues typically contain between six and twelve articles. They are put together under the responsibility of one or several guest editors. However, the final decision on all papers will be made by the Editor-in-Chief. Prospective guest editors should provide a call for papers as well as an informative CV for each guest editor. Prospective review authors or guest editors of focused issues are encouraged to contact the Editor-in-Chief, Professor Stefan Nickel.

Organizational Behavior and Human Decision Processes

ISSN: 0749-5978
5 Year impact factor: 6
Impact factor: 4.6

Organizational Behavior and Human Decision Processes publishes fundamental research in organizational behavior, organizational psychology, and human cognition, judgment, and decision-making. The journal features articles that present original empirical research, theory development, meta-analysis, and methodological advancements relevant to the substantive domains served by the journal. Topics covered by the journal include perception, cognition, judgment, attitudes, emotion, well-being, motivation, choice, and performance. We are interested in articles that investigate these topics as they pertain to individuals, dyads, groups, and other social collectives. For each topic, we place a premium on articles that make fundamental and substantial contributions to understanding psychological processes relevant to human attitudes, cognitions, and behavior in organizations. In order to be considered for publication in OBHDP a manuscript has to include the following: Demonstrate an interesting behavioral/psychological phenomenon Make a significant theoretical and empirical contribution to the existing literature Identify and test the underlying psychological mechanism for the newly discovered behavioral/psychological phenomenon Have practical implications in organizational context Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services. Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

Project Leadership and Society

ISSN: 2666-7215

The Journal of the International Project Management Association (IPMA) Project Leadership and Society (PLAS) is an academic and gold open access journal. As a sister open access journal of the International Journal of Project Management, the leading journal in the field of Project Management. PLAS opens up for novel approaches that study projects and relate them to society. Society is considered in a broad sense, including policy, leadership and managerial practice. PLAS articles study the interaction between projects, project leadership, project management on the one hand, and economic, social, political and organizational processes, on the other. Project leadership and management are seen in a broad sense including project based management, project-oriented management and Project Management Office (PMO) Management. All papers are expected to yield findings that have implications for policy or practice. We are especially interested in leadership in a project society that includes all types of projects, programs, project portfolios, project-oriented organizations, project networks, project industries. Interesting topics to study projects from a broader perspective include; vertical leadership, shared leadership, change, projectification, resilience, sustainable development, responsibility, career, stakeholder engagement, novel perceptions on value creation and project success. Project leadership and project leaders, teams and individuals in specific situations like crisis, extreme situations, disaster are of interest to the journal. PLAS welcomes papers that enhance our understanding of theory and practice of Project Leadership, but also papers on education and novel research practices are welcome to disrupt the development of future project leaders and the way research is organized in a project society. PLAS article formats include Empirical research: A PLAS empirical research article identifies a research gap in literature, takes a clear theoretical stance, follows a transparent and rigorous (qualitative and quantitative) methodology, makes a clear contribution to the field of project studies and provides practice or policy implications for a project society. Discoveries: A PLAS discovery starts with rich descriptions of a phenomenon observed in practice, uses theory for explanation, identifies gaps in theory, contributes to theory development and provides practice or policy implications for a project society. Reviews: A PLAS review article is based on a transparent methodology, goes beyond describing the review findings, but brings forward a conceptual theoretical contribution and provides practice or policy implications for a project society. Next Practices: A PLAS next practice article discusses the development of a next practice, including case studies that applied a novel method or approach. The article needs to be linked to theory and needs to make clear what the practice innovation is. Practices should be novel and disruptive, question our existing knowledge of leading or managing projects. The article provides practice or policy implications for a project society. Theoretical Insights: A PLAS theoretical insight article is a theory piece, that brings forward new thoughts and ideas based on theory. It should open up a new research stream or bring a disruption to a current debate relevant to actors in a project society. Enable: A PLAS enable article discusses the development of education and learning for project leadership and their application in a project society to enable future project leaders. The article needs to be linked to theory and needs to make clear what the innovation in education is. Approaches and practices should be novel and disruptive, question our existing knowledge on developing project leaders. The article provides practice or policy implications for a project society. Novel Research Practices: A PLAS novel research practice article discusses the development of and application of a novel research practice in the field of project leadership and project management. The article needs to be linked to theory and needs to make clear what the research practice innovation is. Practices should be novel and disruptive, question our existing knowledge and provide practice or policy implications for research in a project society.