Abstract
Sustainable development has become the biggest concern of the semiconductor industry, which plays a vital role not only in technology breakthroughs, but also by serving as an enabler for sustainability. This study combines Analytic Hierarchy Process (AHP) and additive network Data Envelopment Analysis (DEA) to measure the sustainable performance which are derived from business growth stage and energy utilization stage through the parametric linear program. Meanwhile, this method makes up the disadvantage of the weighting technique used additive decomposition approach to the two-stage network and avoids biasing toward the second stage. The findings demonstrate that Taiwan’s semiconductor manufacturing sector has exhibited a steady increase in its overall trend of sustainability performance. According to the stage-level performance results, the performance of business growth is better than energy utilization. However, the changing trend of overall sustainability performance is through a steady increase from environmental efficiency and not from economic efficiency.
Highlights
With the dynamic evolution of the information and communications technology (ICT) industry, in which products such as computers, and integrated circuits (ICs) are playing a more vital role
This issue can be addressed by the Data Envelopment Analysis (DEA) technique, because DEA applies to problems with multiple inputs and multiple outputs [11], while considering undesirable outputs
This section describes the evaluation of the efficiencies of 15 companies in Taiwan’s semiconductor manufacturing sector
Summary
With the dynamic evolution of the information and communications technology (ICT) industry, in which products such as computers, and integrated circuits (ICs) are playing a more vital role. Proponents of environmental protection worry about pollution, while opponents argue that controlling the pollution can reduce the pace of economic growth [10] by limiting the operations of manufacturing industries This issue can be addressed by the Data Envelopment Analysis (DEA) technique, because DEA applies to problems with multiple inputs and multiple outputs [11], while considering undesirable outputs. Hatami–Marbini et al [16] developed a flexible cross-efficiency evaluation methodology based on DEA for identifying supplier performance Motivated by those findings, this study presents a sustainability measurement framework in Taiwan’s semiconductor industry through the additive efficiency decomposition approach for measuring the efficiency of networks. The paper provides a comprehensive view of the relationship between overall efficiency and stage efficiencies under varying weights This extension is essential in the DEA field.
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