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Data envelopment analysis (DEA) and window analysis are used to follow the changes in Australian trading banks' pure technical efficiency, scale efficiency, and the nature of returns to scale. The main findings indicate declining average efficiency scores until 1991, followed by a steady rise thereafter. Pure technical inefficiency emerges as a greater source of inefficiency than scale inefficiency. Overall, regional banks exhibit increasing returns to scale and major trading banks exhibit decreasing returns to scale. Also worthy of note is the mixed size of banks operating at optimal returns to scale.

This chapter proposes a new technique based on the data envelopment analysis (DEA) method to evaluate the scale efficiency with considering the environmental influences. Using this method, we can get the pure scale efficiency which has eliminated the environmental factors and random errors that might influence the production process. Our approach extends the three-stage-DEA model by Fried, Lovell, Schmidt, and Yaisawarng (2002) to the five-stage DEA model. Afterward, in order to measure the scale efficiency of the China’s universities more accurately, this chapter gives an empirical study on the scale efficiency of the top universities in China by applying the five-stage DEA model. The results show that the efficiency levels of many universities are indeed affected by external environmental variables and random factors. According to the levels of pure technical efficiency and scale efficiency, we divide China’s universities into four types, and we also propose some suggestions for the inefficient universities to improve their scale efficiency.

Organizational performance improves through several channels, including changes in efficiency, innovation and technological change. Most of the extant research has focused on overall performance, often measured by partial measures of productivity, with little attention given to the components of performance. The aim of this paper is to analyze the impact of HR practices and unionization on one important channel – organization efficiency - as measured by technical and scale efficiency. Using French industry survey data, the paper shows that HR practices do influence efficiency, but this is moderated by the existence of unions. The results show a rather complex set of associations. We find robust results that show that in France, HR practices have a positive effect on scale efficiency but this effect is dampened in the presence of unions. On their own, HR practices have no effect on technical efficiency. However, some of the results suggest that HR practices can exert a positive influence when combined with unions.

The purpose of this paper is to identify the structural problem in the Chinese dairy sector. There exists a large number of low‐efficiency, small‐scale farms, and productivity inequality between small and large farms keeps increasing, which is a possible driving force behind the Melamine scandal in 2008.

Using the stochastic frontier production function, this paper estimates and compares the changes in technology and technical efficiency between backyard, small‐scale, medium‐scale and large‐scale dairy farms in China over the period between 2004 and 2008.

There are compensating effects between technology and technical efficiency. However, low yield for backyard farms is mainly caused by traditional low‐yield varieties, even though the technical efficiency is very high, which cannot compensate for the low technology.

The author put the assumption of constant return to scale mainly due to the data availability. Such an assumption implies that there are no scale‐effects between the different scales in productivity, and the productivity difference is explained by technology and technical efficiency.

In order to solve the structural problems, Chinese governments should help small‐scale farmers to adopt new high‐yield varieties, to subsidize small‐scale farmers, and to train farmers to master the complicated skills for raising high‐yield varieties.

The paper gives another possible explanation for the Melamine scandal of milk powder in 2008. If the structural problem cannot be solved, similar food safety scandals could happen once again.

The purpose of this paper is to examine the relative production efficiency of state‐wise clusters in the registered small‐scale sector in India.

For this, data envelopment analysis under the assumption of variable returns to scale is used. Using BCC model, technical and scale efficiencies for 23 states and three union territories are estimated.

Seven states namely, Delhi, Meghalaya, Uttranchal, Haryana, Punjab, Andaman and Nicobar and Tamilnadu are found to be technically efficient whereas Delhi and Meghalaya came out to be the only scale efficient states. Most of the states are found to be operating at decreasing returns to scale, which signifies the scope for investment and further employment generation.

Since the results indicate massive scope for expansion and employment generation in small industries in India, therefore, policy makers can use it as a tool to achieve the goal of inclusive and sustainable growth.

Originality lies in providing, for the first time, an inter state technical and scale efficiency analysis for small scale industries in India which in turn reflects the performance efficiency of the state level policies for the small scale industries.

The purpose of this paper is to examine the long‐term trend in the efficiency of the Singapore banking sector.

The paper utilises the data envelopment analysis (DEA) window analysis methodology, which allows us to distinguish between three different types of efficiency namely, technical, pure technical and scale efficiencies. Given that the sample population is small, the DEA window analysis allows for a greater degree of freedom to the sample. The paper further examines whether the Singapore banking groups were drawn from the same environment during two sub‐periods by performing a series of parametric and non‐parametric tests. Finally, the paper attempts to investigate the consistency of the estimated DEA efficiency scores by examining its relationship with the traditional measures of banks’ performance.

During the period of study, the results suggest that the Singapore banking groups have exhibited mean overall or technical efficiency of 88.4 per cent. It was found that the Singapore banking groups’ overall efficiency was on a declining trend during the earlier part of the studies, before increasing dramatically during the later period.

The paper could be extended to consider the production approach along with the intermediation approach, which has been applied in this paper. Investigation of changes in productivity over time as a result of technical change or technological progress or regress by employing the Malmquist Total Factor Productivity Index, could be another extension to the paper.

This paper provides new empirical evidence on the long‐term trends in the efficiency of the Singapore banking groups.

This paper aims to endeavour to assess revenue efficiency (RE) scores of Scheduled Commercial Banks operating in India. Differences in RE are studied across varying ownership as well. The study also determines the nature of return to scale of Indian SCBs as whole as well as classified across ownership. Number of banks operating as leaders and laggards has also been calculated.

RE of banks is calculated by using the non-parametric approach, namely, data envelopment analysis (DEA). Further, the differences in the efficiency scores are examined by applying Panel Tobit Regression.

The results of DEA suggest that none of the banks has ever achieved full RE score of 1 in any of the years under study. An inconsistent pattern of RE is seen. Private sector banks have performed better than their counterparts in public and foreign sector. Maximum number of banks operating on decreasing return to scale are from public sector, and the highest number of banks operating on constant return to scale belong to Foreign Sector. More number of banks operates as laggards in the Indian financial system. Thus, there still exists room for improvement for banks in all sectors.

With specific reference to India, less empirical work has been carried out with respect to RE. As only two studies so far from the literature are available that consider RE exclusively, namely, Ram Mohan and Ray (2004) and Bhatia and Mahendru (2015). However, Ram Mohan and Ray (2004) considered only the reformatory phase, whereas Bhatia and Mahendru (2015) analyzed the performance for specific points of time only. None of the study has been able to give any concrete findings according to sector-wise performance of banks in terms of RE parameters.

This study explores the applicability of the resource‐based view at the organizational unit level by investigating why resource utilization, as measured by efficiency, might differ within a firm. Using a downstream petroleum firm as the context for this study, the data envelopment analysis framework is applied to examine resource input congestion of its DCs (i.e. distribution centers). The study also provides a more granular analysis by decomposing distribution efficiency into managerial, scale, and programmatic efficiency, and examines the impact of corporate‐level decision making by including non‐discretionary variables. The analysis identifies opportunities to improve efficiency at the organizational unit level, using alternative views of the operational problem. The approach also provides practicing managers with an objective means to evaluate performance at the level of the organizational unit. Both the efficiency view and the managerial performance view are discussed simultaneously from a strategic view of firm resources.

The purpose of this paper is to investigate the productivity of rice production by decomposing the growth of total factor productivity (TFP) into four components: technological change, scale effects, technical and allocative efficiencies.

This study employed an econometric approach to decompose TFP growth into four components: technological change, technical efficiency, allocative efficiency and scale effect. Unbalanced panel data used in this study were surveyed in 1994, 2004 and 2014 from 360 rice farming operations. The model used the stochastic frontier transcendental logarithm production technology to estimate the technology parameters.

The results indicate that the primary sources of TFP growth were technological change and allocative efficiency effects. The contribution of technical efficiency was low because it grew sluggishly.

This study has several shortcomings, such as very low R² and the insignificant elasticity of labour presented in the findings. Another limitation is the limited time period panel covering long interval, which resulted in unbalanced data.

The government should improve productivity growth by allocating more areas for rice production, which enhances the scale and efficiency effects and adjusting the use of capital and material inputs. Extension services should be strengthened to provide farmers with training on improved agronomic technologies. This action will enhance technical efficiency performance and lead to technological progress.

As Indonesian population is still growing at a significant rate and the fact that rice is the primary staple food for Indonesian people, the productivity of rice production should increase continually to ensure social security at a national level.

The productivity growth is decomposed into four components using the transcendental logarithm production technology based on farm-level data. The measure has not been conducted previously in Indonesia, even in rice-producing countries.

The purpose of this paper is to evaluate and compare bank efficiency between the two Maghreb countries, Tunisia and Morocco, over the period 2005–2014.

The authors follow the stochastic frontier analysis, where the preferred cost model is determined via various hypothesis tests based on the maximum likelihood estimation. Then, the first and the second derivates of the cost function are employed to determine scale elasticities, scale inefficiencies and technological progress.

Specification tests indicate that the Fourier Flexible form provides better fit to the data set. Further, the estimated model shows that Tunisian and Moroccan banks’ efficiency is positively affected by banking service quality, but negatively influenced by both bank capitalization and GDP growth. Overall, Moroccan banks are found to be the most efficient despite the decrease of efficiency levels in both countries. Additionally, foreign banks have a higher scale inefficiency and, therefore, a lower cost efficiency. Equally, the technical progress raises banking costs in both countries, providing a decrease in efficiency scores.

The findings of this study provide novel insights to Tunisian and Moroccan policy makers on the relevance of the smaller banks’ consolidation to improve bank efficiency by achieving unrealized economies of scale. Also, more reforms should be implemented in Tunisia to reduce non-performing loans.

To the best of the authors’ knowledge, this study is the first which offers a comparison between Tunisian and Moroccan banks to clarify the sources of inefficiency and to make strategic decisions.