• Journal of the military operations research society of Korea
• /
• v.33 no.2
• /
• pp.61-73
• /
• 2007

We examined technological forecasting of extended TFDEA(Technological Forecasting with Data Envelopment Analysis) and thereby apply the extended method to the technological forecasting problem of main battle tank. The TFDEA has the possibility of using comparatively inefficient DMUs(Decision Making Units) because it is based on DEA(Data Envelopment Analysis), which usually leads to multiple efficient DMUs. Therefore, TFDEA may result in incorrect technological forecasting. Instead of using the simple DEA, we incorporated the concept of Super-efficiency, Cross-efficiency, and CCCA(Constrained Canonical Correlation Analysis) into the TFDEA respectively, and applied each method to the case study of main battle tank using verifiable practical data sets. The comparative analysis shows that the use of CCCA with TFDEA results in very comparable prediction accuracies with respect to MAE(Mean Absolute Error), MSE(Mean Squared Error), and RMSE(Root Mean Squared Error) than using the concept of Super-efficiency and Cross-efficiency.

• Journal of Korea Technology Innovation Society
• /
• v.19 no.4
• /
• pp.799-821
• /
• 2016

Unmanned Aerial Vehicles (UAVs) are essential systems for Intelligence, Surveillance, and Reconnaissance (ISR) operations in current battlespace. And its importance will be getting extended because of complexity and uncertainty of battlespace. In this study, we forecast the advancement of 96 UAVs during the period of 32 years from 1982 to 2014 using TFDEA. TFDEA is a quantitative technology forecasting method which is characterized as non-parametric and non-statistical mathematical programming. Inman et al. (2006) showed that TFDEA is more accurate in forecasting compared with classical econometrics (e.g. regression). This study got 4.06% point of annual technological rate of change (RoC) for UAVs by applying TFDEA. And most UAVs in the period are inefficient according to the global SOA frontiers. That is because the countries which develop UAVs are in the middle class of technological level, so more than 60% of world UAVs markets are shared by North America and Europe which are advanced countries in terms of technological maturity level. This study could give some insights for UAVs development and its advancement. And also can be used for evaluating the adequacy of Required Operational Capability (ROC) of suggested future systems and managing the progress of Research and Development (R&D).

• Journal of Technology Innovation
• /
• v.15 no.2
• /
• pp.83-102
• /
• 2007

This study extends the existing method of Technology Forecasting with Data Envelopment Analysis (TFDEA) by incorporating a ranking method into the model so that we can reduce the required number of DMUs (Decision Making Units). TFDEA estimates technological rate of change with the set of observations identified by DEA(Data Envelopment Analysis) model. It uses an excessive number of efficient DMUs(Decision Making Units), when the number of inputs and outputs is large compare to the number of observations. Hence, we investigated the possibility of incorporating CCCA(Constrained Canonical Correlation Analysis) into TFDEA so that the ranking of DMUs can be made. Using the ranks developed by CCCA(Constrained Canonical Correlation Analysis), we could limit the number of efficient DMUs that are to be used in the technology forecasting process. The proposed hybrid model could establish technology frontiers with the efficient DMUs for each generation of technology with the help of CCCA that uses the common weights. We applied our hybrid model to forecast the technological progress of main battle tank in order to demonstrate its forecasting capability with practical application. It was found that our hybrid model generated statistically more reliable forecasting results than both TFDEA and the regression model.