In this paper, Data Envelopment Analysis (DEA) and super efficient DEA (SE-DEA) are employed to measure the efficiency of Chinese commercial banks. Incorporating Tobit regression analysis, the determinants of banking efficiency are investigated based on Panel data. Overall, the DEA results show relatively low average efficiency levels and state-owned banks are more inefficient than that of join...

This paper presents a simplified version of Data Envelopment Analysis (DEA) a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object the one having greatest outputs and smal...

There exist many different ranking methods for ranking efficient Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). However, since each of these methods considers a certain theory for ranking, they may give different ranks. In practice, choosing a ranking method, the results of which the Decision Maker (DM) would be able to trust is an important issue. In this paper, we consider s...

Although investment is regarded as a key force of China’s economic growth, little study has been done to measure China’s investment efficiency. The present paper applies the data envelopment analysis (DEA) to Chinese provincial panel data from the year 2003 to 2008 for measuring the investment efficiencies and identifying their trends of Chinese 30 provinces and autonomous regions. A cross-effi...

This study evaluates operation performances of 67 international tourist hotels in Taiwan by using the Context-dependent DEA model of Date Envelopment Analysis (DEA) in order to find out the performance of these hotels and their competitive advantages. This study differentiates the levels of efficient frontier with the efficiency of each international tourist hotel. Based on the efficiency, the ...

Frontier analysis methods, such as Data Envelopment Analysis (DEA), seek to investigate the technical efficiency of productive systems which employ input factors to deliver outcomes. In economic literature one can find extreme opinions about the role of input/output systems in assessing performance. For instance, it has been argued that if all inputs and outputs are included in assessing the ef...

This paper adopts two mathematical approaches, data envelopment analysis (DEA) and grey relation analysis (GRA) to measure DEA efficiency using the sample of 69 listed US internet companies. A total of 40 indicators were initially selected for the efficiency evaluation, with 21 related to DEA-input indicators and 19 to DEAoutput indicators. Eight representative indicators selected using GRA are...

this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

Data envelopment analysis (DEA) is a non-parametric approach to evaluate a set of decision making units (DMUs) consuming multiple inputs to produce multiple outputs. Formally, DEA use to estimate the efficiency score into the empirical efficient frontier. Also, DEA can be used to allocate resources and set targets for future forecast. The data are continuous in the standard DEA model whereas th...