Measuring efficiencies of multi-period and multi-division systems associated with DEA: An application to OECD countries’ national innovation systems |
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| Affiliation: | 1. School of Business, Shanxi Datong University, Datong 037009, PR China;2. Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, PR China;3. Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, PR China;4. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China\n;1. Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Avda. de la Universidad, 30, Leganés Madrid, 28911, Spain;2. Facultad de Ingeniería y Computación, Universidad Católica San Pablo, Campus Campiña Paisajista s/n Quinta Vivanco, Barrio de San Lázaro, Arequipa, Peru;1. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, R.O.C.;2. Control System Laboratory, Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan, R.O.C.;1. School of Statistics, Southwestern University of Finance & Economics, Chengdu 611130, China;2. Department of Mathematics, University of Ioannina, Greece;3. Cotsakos College of Business, The William Paterson University of New Jersey, Wayne, NJ 07470, USA |
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| Abstract: | The efficiency-oriented performance evaluation of multi-period and multi-division systems (MPMDS) becomes increasingly important for complex investment and management decisions. This paper proposes a new formulation approach for dynamic network DEA (DN–DEA) models based on system thinking to measure and decompose the overall efficiency of MPMDS. The proposed approach is general and maintains the objective property of DEA evaluation, which not only does not need the pre-specified weights to subjectively combine component efficiencies into overall efficiency, but also is applicable to both radial and non-radial measures. More attracting, it presents a weighted average decomposition of the overall efficiency score into component ones by a set of endogenous weight sets which are most favorable for the overall efficiency of the tested entire MPMDS and ensures consistency in the comparison between overall and component efficiency scores. This study makes two contributions to the existing literature. First, it not only makes the structured decision making of MPMDS possible but also helps us realize semi- and non-structural decision making from an expert and intelligent systems point of view. Second, it evaluated the innovation efficiency of OECD countries in the multi-period and multi-division context, which presents an analytical technique and some systemic evidence for national innovation investment decisions in the long run. |
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