Modeling the technological landscape: directed search and the technology life cycle

Steven Callander

Chapter 2 in Elgar Companion to Technology Life Cycles, 2026, pp 28-49 from Edward Elgar Publishing

Abstract: The evolution of technology can be understood as a search process in which each firm builds upon the achievements of its predecessors, learning from past experiences to deliberately select the next technological innovation to explore. In this chapter, I describe an economic framework that formalizes the search for new technologies. In this framework, the technological landscape is modeled as the realized path of a stochastic process, most commonly represented by Brownian motion. Search over this path matches the evolution of technological development in practice. The search dynamic is path-dependent, mixing successes with failures, and exhibits changes in the speed as well as the novelty of innovations. The search path often reverses direction as the lessons of early technological developments shape future decisions. In particular, the search process matches features of the technological life cycle (TLC). I develop the points of contact between the theory and practice, highlighting areas of alignment and suggesting promising avenues for future research.

Keywords: Technology; Search; Innovation; Trial-and-error learning; Market evolution (search for similar items in EconPapers)
Date: 2026
ISBN: 9781035355488
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