Forecasting research trends using population dynamics model with Burgers’ type interaction

Matylda Jabłońska-Sabuka, Robert Sitarz and Andrzej Kraslawski

Journal of Informetrics, 2014, vol. 8, issue 1, 111-122

Abstract: The increasing costs of research and the decreasing lifetime of products and processes make the decisions on allocation of R&D funds strategically important. Therefore, ability to predict research trends is crucial in minimizing risks of R&D expenditure planning. The purpose of this paper is to propose a model for efficient prediction of research trends in a chosen branch of science. The approach is based on population dynamics with Burgers’ type global interaction and selective neighborhood. The model is estimated based on a training set. Then, an out-of-sample forecast is performed. The research trends of filtration and rectification processes were analyzed in this paper. The simulation results show that the model is able to predict the trends with a considerable accuracy and should, therefore, be tested on a wider range of research fields.

Keywords: Research trends; Population dynamics; Momentum; Burgers’ equation (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157713001041
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:8:y:2014:i:1:p:111-122

DOI: 10.1016/j.joi.2013.11.003

Access Statistics for this article

Journal of Informetrics is currently edited by Leo Egghe

More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().