In this paper, the slacks-based measure of super efficiency (super-SBM) is employed to evaluate the rankings and identify the best performers among 18 chosen EMS providers. Both profitability and marketability efficiency are concerned in order to give a comprehensive view in performance of these companies. Besides, Non-radial Malmquist is also applied to analyze the inter-temporal efficiency change which is decomposed into “catch-up” and “frontier-shift” effects. In addition, GM (1, 1) will be utilized for forecasting the future variables which give the managers a further look on the development potential and situation of these EMSs in near future. The results found that the number of efficient companies and the order of ranking change every year. Hon Hai seems to keep its highest best rankings among 18 DMUs most of the time regarding performance scores. In recent years and next few years, the efficiency of profitability stage is higher than in marketability when considering each separate year with super SBM model. However, there are more companies showing efficient score on marketability model than on profitability in cross - period performance with Malmquist index, which means that the increasing market value productivity of EMSs have been being more and more improved. Finally, a decision-making matrix will be designed to help EMS authorities identify their status and position in the industry. Some recommendations for EMSs in how to enhance precisely its performance to create company value and success are also suggested here. The integration of Data Envelopment Analysis (DEA) and Grey model this research is expect to contribute a better insights into performance evaluation of EMSs in recent years and next few years. (C) 2016 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
CITATION STYLE
Tran, T.-T. (2016). Evaluating and forecasting performance using past data of an industry: An analysis of electronic manufacturing services industry. International Journal of ADVANCED AND APPLIED SCIENCES, 3(12), 5–20. https://doi.org/10.21833/ijaas.2016.12.002
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