Slacks-based Measure Data Envelopment Analysis Research Articles

Environmental efficiency of ports: a Data Envelopment Analysis approach

Numerous studies have analyzed the productivity, efficiency, and competitiveness of ports. However, empirical studies on the environmental efficiency of ports have not yet been carried out, since all previous studies have not considered the undesirable outputs that ports generate, for instance, CO2 emissions. To fill the gap in the literature, the objective of this study is to estimate environmental efficiency of ports. More specifically, this paper intends to analyze environmental efficiency of ports in Korea and to estimate the potential CO2 emission reduction by ports in the country. The main methodology is a Slacks-Based Measure Data Envelopment Analysis (SBM-DEA) model. Data, on labor, capital, and energy used as major inputs of the port sector; on cargo tonnage and vessel tonnage handled as desirable outputs; and on CO2 emissions as an undesirable output, were collected and estimated. The SBM-DEA model was able to provide us with a more comprehensive efficiency of combining economic performance and environmental performance and was also able to capture slack values of input excess and undesirable output excess (CO2) as well as desirable output shortage. Using the model and the data, it was found that Korean ports are deemed to be economically inefficient, but environmentally efficient when considering economic and environmental performances simultaneously.

Using fuzzy super-efficiency slack-based measure data envelopment analysis to evaluate Taiwan’s commercial bank efficiency

Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production function in microeconomics. The input and output of decision making units (DMUs) are projected into the attributes to evaluate or measure their performance. However, if the inputs and outputs are linguistically termed or are fuzzy-numbered, conventional DEA can not easily measure the performance. Therefore, we propose the use of a fuzzy super-efficiency slack-based measure DEA to analyze the operational performance of 24 commercial banks facing problems on loan and investment parameters with vague characteristics. After our analysis, we find that the fuzzy slack-based measure of efficiency (Fuzzy SBM)/fuzzy super-efficiency slack-based measure of efficiency (Fuzzy Super SBM) can not only effectively characterize uncertainty, but also have a higher capability to evaluate bank efficiency than the conventional Fuzzy DEA approach.