New Product Development as a Complex Adaptive System of Decisions

TLDR

New product development has traditionally been modeled linearly, but recent recursive and chaotic frameworks recognize overlapping stages, feedback loops, and non‑linear behaviors that resist reductionist analysis. This article extends those models by treating NPD as a complex adaptive system governed by in‑stage, review, and strategic decision levels and rules, and proposes how agent configuration predicts nonlinearity, self‑organization, and emergence. Comparative case studies show that process adaptability arises from the number and variety of agents, their connections and interactions, and the ordering or disordering effects of decision levels and rules. The resulting CAS framework reconciles descriptive, behavioral, and innovation perspectives, demonstrating that NPD processes can toggle between linear and chaotic modes to generate incremental to radical outputs aligned with market expectations.

Abstract

Early research on new product development (NPD) has produced descriptive frameworks and models that view the process as a linear system with sequential and discrete stages. More recently, recursive and chaotic frameworks of NPD have been developed, both of which acknowledge that NPD progresses through a series of stages, but with overlaps, feedback loops, and resulting behaviors that resist reductionism and linear analysis. This article extends the linear, recursive, and chaotic frameworks by viewing NPD as a complex adaptive system (CAS) governed by three levels of decision making—in‐stage, review, and strategic—and the accompanying decision rules. The research develops and presents propositions that predict how the configuration and organization of NPD decision‐making agents will influence the potential for three mutually dependent CAS phenomena: nonlinearity, self‐organization, and emergence. Together these phenomena underpin the potential for NPD process adaptability and congruence. To support and to verify the propositions, this study uses comparative case studies, which show that NPD process adaptability occurs and that it is dependent on the number and variety of agents, their corresponding connections and interactions, and the ordering or disordering effect of the decision levels and rules. Thus, the CAS framework developed within this article maintains a fit among descriptive stance, system behavior, and innovation type, as it considers individual NPD processes to be capable of switching or toggling between different behaviors—linear to chaotic—to produce corresponding innovation outputs that range from incremental to radical in accord with market expectations.