Dominant Design Prediction with Phylogenetic Networks

TL;DR

This paper introduces a machine learning approach combined with phylogenetic networks to predict future dominant product designs, aiding technology forecasting and new product development from an evolutionary perspective.

Contribution

It presents a novel method integrating phylogenetic networks and machine learning to predict dominant designs in technological evolution.

Findings

Effective prediction of future dominant designs.

Successful construction of a Fully Connected Phylogenetic Network dataset.

Improved accuracy in technology development forecasting.

Abstract

This study proposes an effective method to predict technology development from an evolutionary perspective. Product evolution is the result of technological evolution and market selection. A phylogenetic network is the main method to study product evolution. The formation of the dominant design determines the trajectory of technology development. How to predict future dominant design has become a key issue in technology forecasting and new product development. We define the dominant product and use machine learning methods, combined with product evolutionary theory, to construct a Fully Connected Phylogenetic Network dataset to effectively predict the future dominant design.