Technology Foresight Index to Support Science and Technology Policy-Making in the Field of Pharmacology/Pharmacy: A Scientometric Analysis

Abstract

Foresight methods have been used by governments to reduce the margin of error in decision-making, but there is no golden rule for foresight activity; rather, several methods are combined to support decision-making. This article proposes an index number to support Technology Foresight in the field of Pharmacology/Pharmacy. The index number was formed by the relationship between bibliometric and human resources variables. First, Principal Components Analysis was used to reduce the initial bibliometric variables proposed by literature. Finally, Data Envelopment Analysis was used to calculate the number of Decision-Making Units (DMU), which are the most prolific institutions in the study country. The study examined 12 DMUs with 2,744 human resources (100% with academic degree) and 1,515 with research category (55.2%) from these, 217 granted patents (17.1% cited patents) and 1,017 papers (92.3% cited papers) were obtained. A simple but robust index was obtained to support decision-making in Technology Foresight. The results obtained from DMUs affect the Technology Foresight Index due to some institutions with low levels of scientific and technological activity and others with many highly qualified personnel. Technology foresight should be performed periodically by governments to reduce uncertainty in the innovation process and to develop highly competitive technologies. In this sense, this index is reliable for decision-making in the field of pharmacology/ pharmaceuticals. It proposes a novel index relating bibliometric variables (output indicator) and human resources variables (input indicator) to foresee the scientific and technological development in the field of Pharmacology/Pharmacy at the national level. In addition, this study includes variables representing scientific (paper) and technological (patent) activity, as well as the impact of both at the international level.