INFOR Taylor & Francis Journal Impact Factor

INFOR - Taylor and Francis | 2024 Impact Factor:1.6 | Cite Score:2.4 | Q3

Cite Score and Journal Rank of INFOR

About: INFOR: Information Systems and Operational Research is a peer-reviewed journal that publishes high-quality research in the fields of information systems and operational research. The journal covers a broad spectrum of topics including optimization, decision analysis, data analytics, operations management, artificial intelligence, machine learning, and the application of these methodologies in various industries. INFOR aims to advance the theoretical and practical aspects of information systems and operational research by providing a platform for innovative research and applications.
Objective:
The primary objective of INFOR is to promote the development and application of information systems and operational research methodologies. The journal seeks to offer a comprehensive resource for researchers, practitioners, and policymakers to explore new theories, models, and applications. INFOR aims to support the advancement of knowledge and the development of effective solutions that address complex problems in information systems and operational research.
Interdisciplinary Approach:
INFOR adopts an interdisciplinary approach, encouraging contributions from various fields such as computer science, operations research, industrial engineering, management science, and applied mathematics. This approach ensures a broad exploration of topics related to information systems and operational research, integrating different perspectives and methodologies. By promoting interdisciplinary research, the journal addresses multifaceted challenges and fosters the development of integrated solutions that advance the state of knowledge in these fields.
Impact:
The journal has a significant impact on both academic research and practical applications in information systems and operational research. It is widely cited by researchers, practitioners, and industry professionals interested in the latest developments in these fields. The research published in INFOR contributes to the advancement of new technologies, methodologies, and applications that enhance the capabilities and effectiveness of information systems and operational research. The journal serves as a valuable resource for those involved in research, development, and implementation in these areas.
Significance:
INFOR plays a crucial role in advancing the study and application of information systems and operational research by providing a platform for high-quality research and practical insights. Its contributions support the development of innovative solutions and technologies that address current and emerging challenges in these fields. The journals commitment to excellence and its interdisciplinary focus make it an essential resource for anyone involved in research, development, and application in information systems and operational research. Through its rigorous scholarship and broad coverage, INFOR helps shape the future of these disciplines.

Journal Home: Journal Homepage

Editor-in-Chief: Joe Naoum-Sawaya

Scope: The INFOR: Information Systems and Operational Research journal publishes high-quality research articles, reviews, and case studies in the fields of information systems and operational research. Its scope includes, but is not limited to:
Operational Research (OR): Research on the development and application of analytical methods to improve decision-making, including optimization, simulation, and stochastic models.
Information Systems (IS): Studies on the design, implementation, and evaluation of information systems, including database management, information retrieval, and data mining.
Decision Analysis: Exploration of methodologies and tools for decision analysis, including multi-criteria decision-making, risk analysis, and decision support systems.
Supply Chain Management: Research on the optimization and management of supply chains, including logistics, inventory management, and supply chain network design.
Data Analytics and Big Data: Studies on techniques and applications of data analytics and big data in various domains, including predictive analytics, data visualization, and machine learning.
Optimization Methods: Research on mathematical and computational optimization methods, including linear programming, nonlinear programming, integer programming, and heuristic algorithms.
Simulation: Exploration of simulation techniques and their applications in modeling and analyzing complex systems, including discrete-event simulation, Monte Carlo simulation, and agent-based simulation.
Game Theory: Research on the application of game theory in strategic decision-making, including cooperative and non-cooperative games, bargaining theory, and auction design.
Queueing Systems: Studies on the modeling and analysis of queueing systems, including performance evaluation, capacity planning, and service optimization.
Healthcare Operations: Research on the application of OR and IS in healthcare, including hospital management, patient flow optimization, and healthcare logistics.
Financial Engineering: Exploration of quantitative methods and models in finance, including portfolio optimization, risk management, and financial derivatives.
Project Management: Research on the application of OR and IS in project management, including project scheduling, resource allocation, and risk assessment.
Transportation and Logistics: Studies on the optimization and management of transportation and logistics systems, including routing, scheduling, and traffic management.