The International Journal of Business Analytics, published by IGI Global, is a distinguished platform dedicated to advancing the field of business analytics through innovative research and comprehensive studies. With an ISSN of 2334-4547 and an E-ISSN of 2334-4555, this journal has contributed significantly to the academic dialogue since its inception in 2014 and will continue to do so until 2024. Although currently classified in the Q4 quartile for both Business and International Management and Strategy and Management, the journal's focus on bridging theoretical frameworks with practical applications makes it a vital resource for researchers, professionals, and students alike. The journal encourages submissions that delve into data analysis methodologies, optimization techniques, and case studies that highlight the transformative power of analytics in modern business practices. Despite not being an open-access publication, the journal continues to be an invaluable asset for those seeking to enhance their understanding of business analytics in today’s data-driven landscape.

Japanese Journal of Statistics and Data Science, published by SPRINGERNATURE, is a leading academic journal dedicated to the advancement of statistical methodologies and data science applications, with a focus on fostering innovative research and discourse within the field. Since its inception in 2018, the journal has sought to bridge theory and practice, embracing emerging trends and interdisciplinary approaches that contribute to the ever-evolving landscape of statistics, probability, and computational theory. Hailing from Germany, the journal holds an impressive Q3 ranking in both Computational Theory and Mathematics and Statistics and Probability, reflecting its commitment to high-quality, impactful research. With an accessible ISSN of 2520-8756 and E-ISSN 2520-8764, the journal invites a global audience of researchers, professionals, and students to explore its rich array of articles and findings, all aimed at furthering knowledge and application in the realm of data science.

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY is a distinguished journal published by SPRINGER, dedicated to advancing research in applied probability and its relationship with various computational methodologies. With an ISSN of 1387-5841 and an E-ISSN of 1573-7713, this journal provides a platform for innovative studies that bridge theory and practical application in the field of mathematics and statistics. Ranking in the Q2 category for Mathematics (miscellaneous) and Q3 for Statistics and Probability as of 2023, it reflects a robust academic discourse, featuring contributions that span a range of methodologies utilized in probability-related studies. The journal's sustained engagement in the academic landscape from 2004 to 2024 puts it at the forefront of ongoing developments in statistics and probability. Researchers, professionals, and students alike will find the insights found within to be invaluable for both theoretical understanding and practical implementation.

JOURNAL OF FORECASTING, published by Wiley, stands as a vital resource in the fields of forecasting and predictive analytics, dedicated to advancing theoretical and practical knowledge. With a rich history dating back to its inception in 1982, the journal covers an extensive range of disciplines, evidenced by its impressive standing across several Scopus rankings, including Q1 in Modeling and Simulation and Q2 in Economics, Management Science, and Statistics among others. The journal holds an esteemed impact factor, indicative of its rigorous peer-review process and the significance of its contributions, making it essential reading for researchers, practitioners, and students alike. While the journal is not open access, it offers various subscription options to ensure that its valuable content is accessible to a wider audience. As it converges towards its 2024 milestone, the JOURNAL OF FORECASTING continues to forge paths in methodological advancements and empirical applications, reinforcing its reputation as a foremost publication in predictive modeling.

Computational Management Science, published by SPRINGER HEIDELBERG, is a significant journal catering to the intersection of technology, management, and decision sciences. With an ISSN of 1619-697X and E-ISSN 1619-6988, this journal serves as a platform for innovative research focusing on computational methods applied to management science, operations research, and information systems. Based in Germany, the journal spans a critical period from 2005 to 2024, emphasizing trends that shape the future of the field. As a Tier 3 journal in multiple categories including Business, Management, and Accounting, and ranked across various disciplines with Scopus rankings highlighting its relevance, it stands out in fostering scholarly discourse. The journal invites contributions that enhance the application of computational techniques in decision-making, thereby enriching the practices of both academics and industry professionals. While it currently does not offer open access, its influence is reflected in its established readership and community engagement. Researchers, practitioners, and students alike will find in this journal a vital resource for advancing knowledge and sparking innovation in computational management.

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering, published by the American Society of Civil Engineers (ASCE), is a leading journal dedicated to advancing the understanding and application of risk and uncertainty in civil engineering systems. With an ISSN of 2376-7642, this journal has been a pivotal platform for researchers and practitioners since its inception in 2015, converging its rigorous exploration through to 2024. It holds a commendable position in the academic community, securing a Q2 rating in categories such as Building and Construction, Civil and Structural Engineering, and Safety, Risk, Reliability and Quality as of 2023. The journal aims to disseminate innovative research that tackles the critical challenges posed by uncertainty in engineering systems, thus promoting safety, sustainability, and reliability in infrastructure. With impressive Scopus rankings, including a 76th percentile in Building and Construction, it continues to attract high-quality contributions from scholars worldwide. Emphasizing open dialogue, the journal does not currently adopt an open access model but remains committed to providing essential insights for the enhancement of civil engineering practices. Researchers, professionals, and students alike will find invaluable resources to enhance their knowledge and practice in this dynamic field.

Probability Uncertainty and Quantitative Risk, published by the American Institute of Mathematical Sciences (AIMS), is a distinguished open-access journal that has been contributing to the academic community since its inception in 2016. With a focus on the crucial interplay between probability, uncertainty, and quantitative risk assessment, this journal serves as a vital platform for researchers, practitioners, and students engaged in the fields of Applied Mathematics and Statistics. The journal's ranking in the Q2 category for both Applied Mathematics and Statistics and Probability reflects its growing influence and relevance, while its diverse scope encourages interdisciplinary studies. As a part of the Scopus database and maintaining a consistent publication pace through 2024, Probability Uncertainty and Quantitative Risk is essential for anyone looking to remain at the forefront of research in risk analysis and uncertainty modeling. Its commitment to open access since 2016 further enhances accessibility to cutting-edge findings, making it an indispensable resource for academics and industry professionals alike.

Journal of Financial Econometrics, published by Oxford University Press, stands as a leading academic journal in the fields of financial economics and econometrics. With an impressive impact factor and a ranking in the Q1 quartile for both Economics and Finance categories in 2023, this journal is recognized for its contribution to advancing theoretical and applied methodologies in financial econometric analysis. It publishes high-quality research that addresses critical issues in finance, aiming to foster a deeper understanding of the economic factors influencing financial markets and instruments. Researchers and practitioners alike benefit from its rigorous peer-reviewed articles, which are invaluable resources for both academic scholars and finance professionals. The journal’s content typically spans pioneering techniques in econometric modeling, empirical analysis of financial instruments, and innovative applications of econometric theory in real-world scenarios. Operating out of the United Kingdom, the journal continues to serve as a vital platform for disseminating significant research findings from 2005 to 2024, ensuring that the latest advancements in the field are accessible to its audience.

ENGINEERING ECONOMIST, published by Taylor & Francis Inc, stands as a revered journal in the intersecting fields of economics, engineering, and education, with an ISSN of 0013-791X and E-ISSN of 1547-2701. Since its inception in 1955, this journal has provided a vital platform for researchers, practitioners, and students to disseminate and engage with novel insights and methodologies impacting the engineering economy. With a robust focus on the quantitative aspects of engineering management and decision-making, ENGINEERING ECONOMIST ranks within the Q3 category in multiple disciplines including Economics and Econometrics, Education, and Miscellaneous Engineering as of 2023, reflecting its significant contributions to the scholarly community. The journal’s Scopus rankings further emphasize its relevance, ranking #778 in Education and #158 in General Engineering. Although the journal does not offer Open Access options, it remains pivotal for advancing the dialogue at the nexus of technology and economics, making it an essential resource for anyone interested in the financial dimensions of engineering innovations.

Data Science in Finance and Economics is a pioneering journal published by the American Institute of Mathematical Sciences (AIMS), devoted to the intersection of data science with the fields of finance and economics. Established as an open-access journal since 2021, it aims to disseminate high-quality research that unravels complex financial phenomena and economic models through innovative data-driven methodologies. With a commitment to advancing knowledge in this rapidly evolving discipline, the journal encourages submissions that encompass theoretical studies, empirical research, and application-based articles from both academia and industry. While the journal is relatively new, its potential to significantly influence the discourse in finance and economics is profound, offering researchers, professionals, and students an invaluable resource to stay abreast of current trends and methodologies in data science. For access to cutting-edge research and insights, visit AIMS and contribute to the ongoing conversation in this essential field.