Analysis of citation impact of ORMS journals by DEA models

Performance and citation impact of scientific journals are measured by traditional metrics such as impact factor, article influence score, journal citation indicator, and others. While the impact factor is based on the total number of citations and does not reflect the quality of journals cited, the article influence score considers the past importance of the citing journals. This paper aims the analyze the possibility of measuring the performance of journals by data envelopment analysis (DEA) models and propose a new DEA based citation performance metrics for ranking of a set of journals. We applied traditional radial and slack-based measure DEA models with weight restrictions where the outputs of the models are the citation counts from Q1 to Q4 categories, and other journals. This basic model is extended by considering the impact factor of the journals from the previous year as one of the inputs of the model. The results of the study are illustrated in the set of 80 journals from the Web of Science category Operations Research and Management Science (ORMS). The dataset for the study was obtained from the Journal Citation Reports in the period from 2017 until 2022. The relative efficiency scores and the ranking of journals obtained by the models are compared with traditional metrics, Academic Journal Guide 2021 classification and the results of the study (Chen et al., Journal of Informetrics, 15(3), 2021) that applies DEA models for the classification of ORMS journals in the same year as our study.