ABSTRACT
First, this paper explores Main Battle Tank (MBT) data set with different statistical methods in order to decide the most appropriate variables as reliable yardsticks in applying technology forecasting (TF) using data envelopment analysis (TFDEA) technique. It then applies TF using DEA method to forecast MBT technologies. This article attempts to predict technology development year of MBT commercialised from 1941 to 1994. This article presents the processes of TFDEA in detail and identifies some issues to search for appropriate input and output variables to forecast MBT technologies. The purpose of this study is to address some issues and identify an appropriate data to predict future trends of MBT technologies when using TFDEA and multiple linear regression tools. Finally, the study provides an understanding of the technological advances being sought in MBT technologies and information for use in making decisions regarding development strategy.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Yonghee Cho is a Ph.D. candidate at the Department of Engineering and Technology Management at Portland State University, Oregon, USA. He holds two MS degrees in Engineering and Technology Management from Portland State University as well as in Urban Economics from Hanyang University and a Bachelor’s degree in Urban Engineering from Hanyang University. Before joining the Ph.D. program of ETM, he previously worked at the KIAT (Korea Institute for the Advancement of Technology) under the Ministry of Industry, Commerce and Energy for about eight years in Seoul, South Korea as a senior researcher. Mr Cho has a research interest in technology forecasting, technology roadmapping, strategic decision-making and technology policy. Recent journal articles have been published in Technological Forecasting and Social Change, Foresight, and Technology Analysis & Strategic Management.
Timothy R. Anderson is Chair and Associate Professor of Engineering and Technology Management at Portland State University. He received an Electrical Engineering degree from the University of Minnesota and MSc. and Ph.D. degrees in Industrial and Systems Engineering from Georgia Institute of Technology. He has worked with and consulted for a range of companies including the US Postal Service, Oki Electric Corporation, Honeywell, and Nike. Dr Anderson’s current research focus is on applications of productivity analysis, technology forecasting, quantitative benchmarking, data mining, and new product development.
ORCiD
Yonghee Cho http://orcid.org/0000-0002-4972-1680