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The purpose of this paper is to develop a system dynamics approach based on Susceptible, Exposed, Infected, Recovered (SEIR) model to investigate the coronavirus pandemic and the impact of therapeutic and preventive interventions on epidemic disaster.

To model the behavior of COVID-19 disease, a system dynamics model is developed in this paper based on SEIR model. In the proposed model, the impact of people's behavior, contact reduction, isolation of the sick people as well as public quarantine on the spread of diseases is analyzed. In this model, data collected by the Iran Ministry of Health have been used for modeling and verification of the results.

The results show that besides the intervening policies, early application of them is also of utmost priority and makes a significant difference in the result of the system. Also, if the number of patients with extreme conditions passes available hospital intensive care capacity, the death rate increases dramatically. Intervening policies play an important role in reducing the rate of infection, death and consequently control of pandemic. Also, results show that if proposed policies do not work before the violation of the hospital capacity, the best policy is to increase the hospital’s capacity by adding appropriate equipment.

The authors also had some limitations in the study including the lack of access to precise data regarding the epidemic of coronavirus, as well as accurate statistics of death rate and cases in the onset of the virus due to the lack of diagnostic kits in Iran. These parameters are still part of the problem and can negatively influence the effectiveness of intervening policies introduced in this paper.

The contribution of this paper includes the development of SEIR model by adding more policymaking details and considering the constraint of the hospital and public health capacity in the rate of coronavirus infection and death within a system dynamics modeling framework.

The Journal of Intellectual Capital (JIC) celebrated its 20th anniversary in 2020. Therefore, the present study aims to provide a general overview of the history and key trends in this journal during 2000–2019.

Two types of citation and textual data during a 20-year journal period were retrieved from the Scopus database. The citation structures and contents were explored based on a combination of bibliometric analysis, altmetric analysis and text mining. The journal themes and trends of their changes were analyzed through citation bursts, mapping and topic modeling. To make a better comparison, the text mining process for the topic modeling of the IC field was performed in addition to the topic modeling of JIC.

Bibliometric analysis indicated that JIC has experienced a remarkable growth in terms of the number of publications and citations over the last 20 years. The results indicated that JIC plays a significant role among IC researchers. Additionally, a large number of researchers, institutes and countries have made contributions to this journal and cited its research papers. Altmetric analysis showed that JIC has been shared in different social media such as Twitter, Facebook, Wikipedia, Mendeley, Citeulike, news and blogs. Text mining abstract of JIC articles indicated that “measurement,” “financial performance” and “IC reporting” have the relative prevalence with increasing trends over the past 20 years. In addition, “research trends” and “national and international studies” had a stable trend with low thematic share.

The findings have important implications for the JIC editorial team in order to make informed decisions about the further development of JIC as well as for IC researchers and practitioners to make more valuable contributions to the journal.

Using bibliometric analysis, altmetric analysis and text mining, this study provided a systematic and comprehensive analysis of JIC. The simultaneous use of these methods provides an interesting, unique and suitable capacity to analyze the journals by considering their various aspects.