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Predicting the research output/growth of selected countries: application of Even GM (1, 1) and NDGM models


  • Saad Ahmed Javed

    () (Nanjing University of Aeronautics and Astronautics)

  • Sifeng Liu

    () (Nanjing University of Aeronautics and Astronautics)


The study aims to forecast the research output of four selected countries (USA, China, India and Pakistan) using two models of Grey System Theory—Even Model GM (1, 1) and Nonhomogeneous Discrete Grey Model (NDGM). The study also conducts publication growth analysis using relative growth rate (RGR) and the doubling time (D t). The linear and exponential regression analyses were also performed for comparison. The study also proposes and successfully tests two novel synthetic models for RGR and D t that facilities the comparison of the countries’ performance when actual data and forecasted data produce different sequences of performance in the given period of time. The data of documents published by the four countries from 2005 to 2016 was collected from SJR/Scopus website. Performance criterion was Mean Absolute Percentage Error. The study confirms that NDGM is a better model for forecasting research output as its accuracy level is higher than that of the Even Model GM (1, 1) and statistical regression models. The results revealed that USA is likely to continue leading in research output at least till 2025 however the research output difference between USA and China is likely to reduce. The study reveals that the less developed countries tend to possess higher relative growth rate in publications whereas the more developed countries tend to possess lower relative growth rate. Further, the more developed countries need more time for publications to double in numbers for a given relative growth rate and less developed countries need less time to do so. The study is original in term of its analysis of the problem using the models involved in the study. The study suggests that the strategies of USA and China to enhance the research output of their respective countries seem productive for the time being however in long run less developed countries have greater competitive advantage over the more developed countries because of their publication growth rate and time required to double the number of publications. The study reported nearly linear trend of growth in research output among the countries. The study is primarily important for the academic policy makers and encourages them to take corrective measures if the growth rate of their academic/publishing sector is not reasonable.

Suggested Citation

  • Saad Ahmed Javed & Sifeng Liu, 2018. "Predicting the research output/growth of selected countries: application of Even GM (1, 1) and NDGM models," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 395-413, April.
  • Handle: RePEc:spr:scient:v:115:y:2018:i:1:d:10.1007_s11192-017-2586-5
    DOI: 10.1007/s11192-017-2586-5

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    References listed on IDEAS

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    1. Ikram, M. & Sroufe, Robert & Rehman, E. & Shah, S.Z.A. & Mahmoudi, A., 2020. "Do Quality, Environmental, and Social (QES) Certifications Improve International Trade? A Comparative Grey Relation Analysis of Developing vs. Developed Countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2019. "Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model," Renewable Energy, Elsevier, vol. 140(C), pages 70-87.
    3. Henry Laverde-Rojas & Juan C. Correa, 2019. "Can scientific productivity impact the economic complexity of countries?," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 267-282, July.
    4. Ofosu-Adarkwa, Jeffrey & Xie, Naiming & Javed, Saad Ahmed, 2020. "Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).


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