Advanced sciences convergence based methods for surveillance of emerging trends in science, technology, and intelligence
Abstract
Purpose
Strategic decision-making is a complex process and encompasses an exhaustive knowledge base, collective guidance, contemporary foresight, analytical capabilities, paradigmatic congruence, and risk assessment and optimization within mission space. Employing advanced sciences convergence and analytical methodologies, the aim of this report is to provide a set of plausible solution trajectories to complex scenarios.
Design/methodology/approach
Three methodologies are reported here which provide policymakers with plausible solution pathways and alternatives. The methodologies, namely: TechFARM, ADAMS, and NESTTS, involve convergence of scientific disciplines, cutting edge technologies, social dynamics, astute extraction, and principles of foresight to support the process of informed decision-making, as comprehensive tools to develop a plausible solution space and future trends.
Findings
The methodologies provided in this report provide scientific basis to trends analysis and foresight. Few selected examples are reported here indicating its practical implications. The methodologies are currently applied to and likely to be used for many applications in trends analysis for government, industry, and even academics. These applications are particularly relevant to policy-making due to their capacity for identification of emerging trends.
Originality/value
Being highly adaptable, these methodologies were initially generated for defense applications, but have since been applied to clean water, cyber-security, the medical sector, and environmental health and safety (EHS) and evaluating eco-toxicity of nanomaterials, to strategically address a variety of global challenges. Additionally, these methodologies support investment recommendations and implementation of policies that promise significant benefit to the public at large.
Keywords
Citation
Vaseashta, A. (2014), "Advanced sciences convergence based methods for surveillance of emerging trends in science, technology, and intelligence", Foresight, Vol. 16 No. 1, pp. 17-36. https://doi.org/10.1108/FS-10-2012-0074
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited