## 2 Technology Forecasting Methodology  
### Concepts of Technology Forecast  
Technological forecasting is premised on a certain orderliness of the innovation process [18]. Technological forecasting is the study of new trends, technologies, or new forces that arise due to policies, social changes, or scientific inventions. [PERSON] [19] defines it as: \"A prediction of the future characteristics of useful machines, procedures or techniques\". The classification of technology forecasting methods varies according to experts. According to [PERSON] and [PERSON] [20], technology forecasting methods could be traditionally categorized into three groups: exploratory, normative, and combined (normative/experimental) methods. Exploratory methods try to predict future technological state of the art (SOA) from the present by extrapolating past technological trends. Trend extrapolation, Growth Curve, Bibliometrics, and Cross impact analysis are kinds of experimental methods. Normative methods set up a possible future that ought to be or needs to be, then suggest a strategy to achieve this future. Morphological analysis, Relevance tree, Analytic Hierarchy Process (AHP), and Backcasting are normative methods. Combined (normative/exploratory) methods use two different methods, normative and experimental, in forecasting. Delphi, Scenario Planning, Trend impact analysis, and Technology roadmapping could be categorized as these methods. [PERSON] et al. [21] introduced a new exploratory forecasting methodology, Technology Forecasting using Data Envelopment Analysis (TFDEA), at the PICMET 01 Conference for assessing the change of database market. TFDEA extends the traditional Data Envelopment Analysis (DEA) for technology forecasting, so it has inherited DEA's nonparametric and non-statistic characteristics. Technological SOA frontiers are estimated using DEA and measuring the rate of change (ROC) by observing the evolution of SOA frontiers. After being introduced in 2001, TFDEA has been used in a variety of sectors including jet fighter aircraft, wireless communications, microprocessors, hybrid electric vehicles (HEV), Research and Development (R & D) target-setting, etc. [21; 22; 23; 24; 25; 26; 27; 28; 29]. The TFDEA methodology can be said to be a technology prediction centered on SOA technology in that it predicts future technology by considering the degree of change in the technology frontier. TFDEA provides better forecasting results than regression when forecasting technological SOA because it chooses SOA based observation and predicts future SOA according to ROC [21; 22; 23; 24; 25; 26; 27; 28; 29]. Because TFDEA is modeled based on DEA, it retains the strengths and limitations of DEA's methodology. There is another reason to consider TFDEA as a research methodology because it has the advantage of being able to make technology predictions for multiple inputs and multiple outputs that regression models cannot handle. Smartphone technology, the subject of this study, had characteristics such as enlarged screen size, increased battery capacity, applied next-generation data communication, sensors, applied advanced camera technology, and expanded applications. On the other hand, discussions about the prospect of sixth generation communication technology applicable to smartphones, expansion of IoT technology, and application of artificial intelligence technology are revealing the limitations of predicting future smartphone technology due to technological changes in the past. In addition, the equipment required to achieve a strategic advantage militarily in the new battlefield environment in the future requires a new technology that is different from the past. Therefore, despite the advantages of TFDEA as a technology prediction methodology, an approach to supplement the limitations of TFDEA classified as an exploratory methodology is needed.