Sueyoshi and Sekitani in 2007 presented a paper that explores the measurement of Returns to Scale under a possible occurrence of multiple solution in a reference set and a supporting hyperplane. The occurrence of multiple solutions is classified into Type I and Type II. Type I is an occurrence of multiple solutions in a reference set. Type II is an occurrence of multiple solutions on a supporti...

For more than twenty years, the cost structure of transport industries in general, and the airline industry in particular, has been analyzed through the calculation of two indices: returns to density (RTD) and returns to scale (RTS), which were originally proposed by Caves et al. (1984). During this period, there have been many observations, amendments, caveats and corrections about their calcu...

abstract present study used translog cost function for determining break point of paddy farms. requested data set include inputs’ prices and quantities, and production amounts had been acquired from 500 rice farmers of guilan province at 2009. model used in this study is seemingly unrelated regressions (sur). the results showed that labor and pesticides had the highest and lowest share of produ...

This paper discusses returns to scale (RTS) in data envelopment analysis (DEA) for each of the presently available types of models. The BCC and CCR models are treated in input oriented forms while the multiplicative model is treated in output oriented form. (This distinction is not pertinent for the additive model which simultaneously maximizes outputs and minimizes inputs in the sense of a vec...

Transport network expansions have been usually analyzed calculating returns to scale with variable network size (RTS), which has been shown to suffer from a number of shortcomings because, in the end, it attempts to capture as a scale property what in fact is related with scope, namely the addition of new products when a transport network expands. In this paper we develop a method to calculate ...

Robust measurement of scale elasticity (SE) in data envelopment analysis (DEA) models remains elusive, primarily reflecting the computational challenges brought about by the piecewise linear nature of the DEA technology. SE is meaningfully defined only at frontier points or at the projection of interior points to the frontier but not for the inefficient unit itself. A long held issue of concern...