Most Cited Paper Award 2020

2024-04-10

The Most Cited Paper Award for Journal of Construction (Revista de la Construcción) 2020 aims to honor and acknowledge the effort of the author(s) of outstanding papers (shall not exceed two papers) in both categories civil engineering and construction and building technology research, indexed in the Web of Science (WoS)/Science Citation Index Expanded.

Papers selected by the Editorial Board must provide a significant contribution in the state-of-the-art or understanding in a particular field, originality, clarity and accuracy in writing, and overall impact (amount of citations/date of publication). The winner will be announced within the last week of April, 2024. 

Nomination and selection procedures

The eligible papers could be either from (i) volume 19, issue (1), year 2020; (ii) volume 19, issue (2), year 2020; or (iii) volume 19, issue (3), year 2020. Understanding that age/time of publication should be considered for normalization due to older papers usually tend to accrue more citations (Dunaiski et al., 2019), a normalization score has been calculated depending on the time that the issue (i.e., 1, 2, 3) for volume 19, was released in 2022. 

The preselected papers are:

  • Aksoylu, C., Mobark, A., Hakan Arslan, M., & Hakkı Erkan, İ. (2020). A comparative study on ASCE 7-16, TBEC-2018 and TEC-2007 for reinforced concrete buildings. Revista de la Construcción, 19(2), 282-305.
  • Farouk Ghazy, M. (2020). Optimization of recycled concrete aggregate geopolymer bricks by Taguchi Method. Revista de la construcción, 19(2), 244-254.
  • Muthusamy Kavitha, S., Venkatesan, G., Avudaiappan, S., & Saavedra Flores, E. I. (2020). Mechanical and flexural performance of self compacting concrete with natural fiber. Revista de la construcción, 19(2), 370-380.
  • Kara, İ. B., & Arslan, M. (2020). Effects of plasticizer and antifreeze on concrete at elevated temperatures and different cooling regimes. Revista de la construcción, 19(3), 347-357.
  • Nagarajan, D., Rajagopal, T., & Meyappan, N. (2020). A comparative study on prediction models for strength properties of LWA concrete using artificial neural network. Revista de la construcción, 19(1), 103-111.