Lecture notes in business information processing

432 papers and 3.0k indexed citations i.

About

The 432 papers published in Lecture notes in business information processing in the last decades have received a total of 3.0k indexed citations. Papers published in Lecture notes in business information processing usually cover Management Information Systems (147 papers), Information Systems (67 papers) and Artificial Intelligence (35 papers) specifically the topics of Business Process Modeling and Analysis (89 papers), Big Data and Business Intelligence (53 papers) and Software Engineering Techniques and Practices (35 papers). The most active scholars publishing in Lecture notes in business information processing are Jan Mendling, Witold Abramowicz, Remco Dijkman, Ewa Ziemba, Jana Koehler, Pnina Soffer, Selmin Nurcan, Marco Montali, Joaquim Filipe and Claes Wohlin.

In The Last Decade

Fields of papers published in Lecture notes in business information processing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Lecture notes in business information processing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Lecture notes in business information processing.

Countries where authors publish in Lecture notes in business information processing

Since Specialization
Citations

This map shows the geographic impact of research published in Lecture notes in business information processing. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Lecture notes in business information processing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lecture notes in business information processing more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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