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The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

As returns to scale (RTS) describes the long run connection of the changes of outputs relative to increases in the inputs, the purpose of this study is to answer the following questions: If the proportionate changes exist in the inputs, what is the rate of changes in outputs with respect to the inputs’ variations in the two-stage networks over the long term? How can the authors investigate quantitative RTS in the two-stage networks? In other words, the purpose of this research is to introduce a different approach to estimate the performance, RTS and scale economies (SE) in network structures.

This paper proposes a novel non-radial approach based on data envelopment analysis to analyze the performance and to investigate RTS and SE in two-stage processes.

The findings show that the range adjusted measure (RAM)/RTS approach can identify reference sets for overall systems and each stage. In addition, the models presented in this paper can classify decision-making units and determine the increasing/decreasing trends of RTS.

The majority of previous RTS studies have been examined in black-box structures and have been discussed in a radial framework. Therefore, in this study, RTS and SE in the two-stage networks are dealt with using an extended RAM approach. Actually, the efficiency and RTS for each stage and the overall model are calculated using the proposed technique.

The purpose of this study is to evaluate the operational efficiency of 23 four‐ and five‐plum international tourist hotels (ITHs) in Taipei in 2006, paying attention to efficiency improvement using a non‐radial data envelopment analysis (DEA) model.

A non‐radial DEA model is proposed to improve the efficiency of inefficient hotels focusing on the output side by allowing for non‐proportional reductions in each positive input or augmentations in each positive output. The model considers four inputs (total number of rooms, total number of employees, food and beverage (F&B) capacity, and total operating cost) and three outputs (guest room revenues, F&B revenues, and other revenues); variable returns to scale are assumed.

The empirical results show that the radial and non‐radial DEA models provide not only different performance measurements for the corresponding hotels but also different benchmarks from different angles for improving efficiency.

Hoteliers or other service providers should find this alternative DEA model helpful and more flexible in re‐examining their resource utilization and possibly reshuffling their resource pool.

Unlike traditional DEA studies, which focus on measuring efficiency while ignoring differences among input or output variables, this study pays attention to efficiency improvement by considering changes in output with non‐proportional augmentations to improve efficiency.

The aim of this paper is to show current position of domestic airports and provide an improvement scheme through the comparative analysis of efficiency and social efficiency. We used SBM (Slack Based Measure) for efficiency and undesirable output model that is extended from SBM for social efficiency. In addition, window analysis is used for analyzing the trend of the values. For the scope of this study, we analyzed fourteen airports in Korea from 2004 to 2009. In the models, we considered the length of runway, the number of employees and terminal area as input factors, and the number of passengers, the amount of cargo and the number of flights as desirable outputs and directly controllable CO2 emissions from airports as undesirable output. The results show that all of the efficiencies are higher than the social efficiencies and both of them are decreasing by years. To improve social efficiency in 2009, the average amounts of reduced CO2 emissions which account for 48.3% of the total emissions are required.

Mitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.

The study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.

Agriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO₂e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.

The Chinese government should consider expanding its national carbon market to cover agricultural sector.

Existing studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.

This paper introduces the concept of policy efficiency of banks as their efficiency in implementing the government's policies. It further compares the Indian public sector banks (PSBs) and private sector banks (PVBs) on two efficiency paradigms, operational efficiency and policy efficiency.

A three-stage analysis is carried out on data collected for 19 PSBs and 16 PVBs for ten years. Non-radial DEA with slack-based measure (SBM) is used to obtain efficiency scores of the banks for the two efficiency paradigms. The efficiency scores and the changes in efficiency and Malmquist index are further analysed by Tobit regression and seemingly unrelated regression (SUR) models.

PVBs are found to be more operationally efficient than PSBs. On the contrary, PSBs are found to be more policy efficient. Among the PSBs, the older and larger banks performed better in both the paradigms. Though Indian banks have become more operational and policy efficient over the years, the rate of improvement is slowing down.

Results imply that evaluating banks, especially PSBs, only on their operational efficiency is myopic. Their efficacies must also be measured by the roles they play on social and policy front. The loss of efficiency of Indian PSBs in a competitive environment should provoke thoughts of reforms. The study suggests that the proposed merger of PSBs to form large banks might be fruitful.

The study contributes to the literature by introducing the measure of policy efficiency. It shows that the Indian PSBs are indispensable as vehicles of government policy implementation.

This paper uses various Data Envelopment Analysis (SBM-DEA) approaches to study the efficiency of major airlines in Asia-Pacific region. To evaluate the operation efficiency of fourteen major airlines in Asia-Pacific region from 2003-2011, Available Seat Kilometers(ASK), Available Ton Kilometers(ATK), the number of employees are used as input factors, Revenue Passenger Kilometers(RPK), Revenue Ton Kilometers(RTK), the amount of Sales are used as output factors.

The non-radial SBM-DEA (Slacks-based Measure of Efficiency) model was able to provide a more comprehensive efficiency of combining economic performance and regional difference. And it was also able to capture slack values in input excess and output shortage.

The results demonstrate that Korea and Japan airlines are operated efficiently and could be regarded as the benchmarking airlines. On the other hand, most of the China and ASEAN airlines are deemed to be inefficient. Also analyzing slacks may be more suitable way for the evaluation or suggestion of an improvement scheme for the inefficient airlines. The excess of labor is the major cause of the airlines’ inefficiency.

This paper investigates the impact of intellectual capital and its components on slack-based technical efficiency (SBM-TE) of banks.

Data envelopment analysis is used to compute SBM-TE scores and the Value-Added Intellectual Coefficient (VAIC™) model is used to measure intellectual capital. An unbalanced panel of 32 banks that operated from 2000 to 2017 has been used.

Overall, the efficiency scores are averaged at 79%, suggesting that an inefficient bank needs to enhance technical efficiency by 21% to be at par with the best performing banks. Beta-convergence and sigma-convergence exist among banks with faster speed evident among listed and local banks. Intellectual capital has a positive impact on SBM-TE and human capital is the main driver of technical efficiency among banks. This result is specifically evident among non-listed banks and foreign banks. Economies of scale property are also evident among the banks. Competition and asset tangibility inhibit technical efficiency among banks.

Banks are advised to invest in value-adding emerging technologies and their employees so as to enhance their efficiency. The study offers insights for policymakers, practitioners and researchers in emerging markets.

The study is premier in employing the SBM-TE to explain the intellectual capital and efficiency nexus, as well as, testing for both beta-convergence and sigma-convergence.

The purpose of this paper is to benchmark the energy use of Indian iron and steel industry. For this purpose, the authors have estimated a production frontier to know the best performing states. Further, the energy-saving targets are estimated to lie below the benchmark level for those states. Panel data for this purpose are extracted from the Annual Survey of Industry (an official database from the government of India) for 19 major steel-producing states over the period from 2004–2005 to 2013–2014.

The authors employed a radial and non-radial (slack-based measure) variant of the data envelopment analysis (DEA) to estimate the production frontier. Particularly, slack-based measures (SBMs) developed by Tone (2001) are used to get a more comprehensive measure of energy efficiency along with technical efficiency. Variable returns to scale technology is specified to accommodate market imperfection and heterogeneity across states. Four inputs (capital, labour, energy and material) and a single output are conceptualised for the production process to accommodate input substitution. The relative position of each state in terms of the level of energy efficiency is then identified.

The authors started by examining energy-output ratio. The average level of energy intensity shows declining trends over the period of time. States like Bihar, Jharkhand, Gujarat and Uttarakhand remain stagnant in the energy intensity level. SBM of energy efficiency shows an overall average energy saving potential of 8 per cent without reducing average output level. Considerable heterogeneity exists among states in terms of the energy efficiency scores. Further, the authors calculated scale efficiency (SE) which shows the overall average level of SE is 0.91; hence, the scale of operation is not optimal and needs to adjusted to enhance energy efficiency.

The authors demonstrate the empirical application of DEA with SBM to energy use performance. This is the first study that benchmarks Indian states in terms of the consumption of energy input to produce iron and steel by applying DEA.

This chapter evaluates the operational efficiency of major airports in the United States. The airport is defined as a major point of contact in the aviation industry, and on-time operations is regarded as a core service factor. We develop a bounded data envelopment analysis (DEA) model that evaluates the punctuality of airports and proposes a three-stage approach that analyzes not only current operations performance but also efficiency changes over time. We classify airports into several classes according to Federal Aviation Authority (FAA) definitions and compare their class efficiencies through decomposed efficiency scores. We find significant differences in efficiency scores between classifications.