Computer Assisted Technology Intelligence: An Introduction

Abstract

Technology depends on innovation — but innovative developments are hard to predict. In addition to existing approaches for Technology Forecasting, the use of data envelopment analysis (DEA) provides valuable insights and prediction data. DEA offers a method to evaluate the relative efficiency of analyzed entities. Using the efficiency analysis features of DEA in Technology Forecasting enables predictions for future developments based on historic data. This paper introduces the Computer Assisted Technology Intelligence (CaTI) system. CaTI implements the Technology Forecasting using DEA method by Oliver Inman, while modifying and expanding the method with the dynamization of the technological Rate of Change calculation using regression analysis, neural network and system Dynamics. CaTI is an interactive system that processes data from a variety of sources and provides a comprehensive set of calculation methods. The results of the calculations are graphically provided to the forecaster. CaTI implements new approaches to the use of Network Data Envelopment Analysis in Technology forecasting to examine the efficient interdependency of subcomponents of a technology. The system supports new functionalities such as collaboration of several forecasters in different locations. The paper describes the individual calculation modules that make up CaTI, their interaction and implementation as software system.