A companion title to the International Journal of Information Management, IJIM Data Insights is a peer reviewed gold open access journal focusing on information management using data science methods.
Data science is an emerging research area in information management that is enriched through the influence of methods from computer science, operations research and statistics. It attempts to extract knowledge and inferences by using a variety of methods, processes, algorithms and perspectives to provide actionable insights into a context or problem. The source of data could be structured, semi-structured or unstructured (or a mix of these). The applications of such algorithms and methods could be undertaken in firms, government, education and societal contexts. The units of analysis could be individual, society, firms or even a context in such studies.
IJIM Data Insights is interested in publishing state-of-the-art articles which address one or more the following themes and contexts:
- Empirical studies which use a data-driven approach for information management.
- Data science studies surrounding unstructured data analysis methods like opinion mining, sentiment analysis, text mining, image mining, video analytics and network science.
- Studies which analyze user-generated and machine-generated content and other unstructured data for innovative contributions surrounding usage of platforms by individuals, groups, communities and firms.
- Studies which demonstrate applications of machine learning, bio-inspired computing and artificial intelligence algorithms based on primary and secondary datasets for improving information management. In case of studies utilizing secondary datasets, peer reviewed datasets in platforms like Data in Brief are preferred.
- Case studies on information management which demonstrate value creation through the application of data science algorithms at the individual, firm, government or societal level based on empirical data.
- Domains could be in financial management, social media, cyber security, operations management, supply chain management, marketing management, technology management, human resources management, entrepreneurship, healthcare and public policy.
- Studies may be characterized by interesting analysis and visualization of big data along with possible statistical analysis to support information management for decision makers.
- Studies surrounding emerging technologies like blockchain, IoT and others which use machine learning and data science are also welcome, as long as they are connected with information management systems.
- Case studies which demonstrate a practical application of the methods and practices of projects using data science would also be welcome.
|Issue volume||Issue year||Planned ship date||Actual ship date|
|1/1||2021||Apr 19, 2021||Apr 09, 2021|
|1/2||2021||Nov 10, 2021|
|2/1||2022||Apr 18, 2022|
|2/2||2022||Nov 10, 2022|