Complexity science: Implications for forecasting

The Curious Behavior of Complex Systems The most exciting development in the systems area in recent years is that of complexity science, focusing on nonlinear, dynamic, complex adaptive systems (CAS), which has clearly recognized the move beyond the constraints of traditional analysis.

Abstract

How to evaluate or measure the emergence degree or level for a specific technology is rarely discussed in the prior studies, and it should be a valuable issue for the relevant areas on technology forecasting, foresight, and technological strategies for macro and micro economies, particularly for those emerging economies who are chasing the technology advances in the developed countries. A conceptual framework inspired by swarm intelligence theory is introduced to measure the emergence degree or level for a specific technology. Swarm intelligence belongs to complex systems theory, and has evolved into a helpful tool for heuristic algorithms and optimization computation, and brought forward an insightful perspective on the evolution and emergence of natural or social systems in the past decades. To verify the proposed framework for measuring emergence degree of a specific technology based on the basic philosophy of swarm intelligence, a case study analyzes an annual set of emerging technologies of the World Economic Forum. The theoretical and empirical analyses could present a fresh vision to investigate the essence of technology emergence, and provide some supplemental thoughts for the policy-making on those emerging or new technologies.