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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

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Published on: January 31, 2014

Role of design complexity in technology improvement.

James McNerney¹, J Doyne Farmer, Sidney Redner

¹Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.

Proceedings of the National Academy of Sciences of the United States of America

|May 18, 2011

Summary

This study models technology evolution, revealing that cost reduction follows a power law related to innovation attempts. Design complexity, influenced by component interactions, dictates the pace of technological improvement.

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Area of Science:

Complexity Science
Technology Management
Innovation Studies

Background:

Technological advancement often exhibits performance improvements over time.
Empirical data frequently shows a power-law relationship between cumulative innovation efforts and cost reduction.
Understanding the factors driving innovation rates is crucial for predicting technological progress.

Purpose of the Study:

To develop a simple model for the evolution of technology cost (performance).
To investigate the relationship between innovation attempts, design complexity, and the rate of improvement.
To connect engineering properties of designs with historical technology improvement patterns.

Main Methods:

A computational model simulating technology evolution through trial-and-error innovation events.
Decomposition of technology into 'n' components, each interacting within a cluster of 'd-1' others.
Analysis of cost reduction dynamics based on random component modifications within clusters.

Main Results:

The relationship between technology cost and innovation attempts asymptotically follows a power law.
The exponent of the power law (α) is determined by component innovation difficulty and design complexity.
Increased design complexity, characterized by component connectivity and bottlenecks, leads to slower improvement rates.

Conclusions:

The model provides a theoretical framework linking engineering design to observed technology improvement trajectories.
Design complexity, quantified by component interactions and bottlenecks, is a key determinant of innovation speed.
The model explains both steady progress and periods of stasis in technological development based on design structure.