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Multi-directional efficiency analysis (MEA) is an alternative methodology to data envelopment analysis (DEA) that investigates the improvement potentials in each input and output dimension and identifies a benchmark proportional to these potential improvements. This results in a more nuanced picture of the sources of the inefficiency providing opportunities for additional conclusions about which variables the inefficiency is mainly located on. MEA provides insights into not only the level of the inefficiency but also the patterns within the inefficiency, i.e. its sources and location. This paper applies this methodology to Bangladeshi banks to understand the differences in the inefficiency patterns between different subgroups.

This paper analyses the difference in the pattern of inefficiency between the older family-dominated banks and the newer non-family-owned banks in Bangladesh using the recently developed MEAs technology, which enables analysis of patterns within inefficiencies rather than only levels of (in)efficiency. The empirical results show that whilst there are few significant differences in the levels of variable-specific efficiency scores between the two subgroups, there are clearer differences on the inefficiency contributions from particular outputs in most of the study period and also on most variables in the time window of 2007–2009. This finding provides clues to differences in business models and management practice between the two types of banks in Bangladesh.

The empirical results show that whilst there are few significant differences in the levels of variable-specific efficiency scores between the two subgroups (older family-dominated banks and the newer non-family-owned banks), there are clearer differences on the inefficiency contributions from particular outputs in most of the study period and also on most variables in the time window of 2007–2009, during the Global Financial Crisis (GFCs). This finding provides clues to differences in business models and management practice between the two types of banks in Bangladesh.

DEA is a conventional tool for benchmarking in management science. However, conventional benchmarking exercises based on DEA do not reveal significant differences in the sources of inefficiency that show differences in business models. While DEA remains the most utilized technique in the efficiency literature, we think that a more flexible and deeper analysis requires something like MEA.

The contribution is twofold. First, examination of performances of family-owned firms is a well-established but analysis of performances of family-dominated banks is relative scarce. Secondly, isolating the sources of inefficiency which differs between types of banks even if there is no difference in inefficiency levels is absolutely new for a complete data set of conventional banks in Bangladesh. It turns out that there are few (significant) differences between the groups in terms of the inefficiency levels, whereas clear patterns emerge in terms of differences in inefficiency contributions between family-dominated and non-family-owned banks, during the Global Financial Crisis

The purpose of this study is to compare the production efficiencies and frontiers differences of oil-producing countries (OPCs) in four inter-governmental organizations (IGOs) in the international petroleum industry with the aim of providing such countries understanding of group characteristics that help maximize their supply interests.

The empirical analysis is based on 14 years of panel data covering the period from 2000 to 2013. In all 46 unique countries who are members of four IGOs relevant to the international petroleum industry are examined on individual and group bases. The authors use both metafrontier analysis and global frontier difference in examining the group average and group frontiers, respectively.

Groups with high inter and intra-group collaborations which ensure exchange of information, organizational learning and innovation tend to do better than groups with even higher hydro-carbon endowment. Additionally, hydro-carbon resource endowment may not be the solution to group inefficiency without higher endowment in human capital, economic stability, technology and infrastructure.

Choice of inter-governmental organizational membership should be based on the level of inter- and intra-group collaborations, human capital endowment among others and not mere historic links or even resource endowment.

This is among the few studies to compare and rank IGOs. Specifically, it is among the first studies to analyze the petroleum production efficiencies of IGOs involved in the international petroleum industry. This study assesses the performance differences among OPCs with the aim of identifying for OPCs the characteristics of inter-governmental groups that are beneficial to efficiency in upstream petroleum activities.

The development of digital inclusive finance appears to be able to solve the difficulty of traditional finance, which cannot completely cover agriculture and farmers and provides better financial services and products to Chinese farmers. Thus, it improves the farmers' enthusiasm for agricultural production. The purpose of this paper is to clarify whether this goal is indeed being achieved.

This paper theoretically analyzes the mechanism that influences the effect of digital inclusive finance on rural households' agricultural production decisions and conducts an empirical study based on a sample from the Chinese family database (CFD).

First, the development of digital financial inclusion in general can encourage rural households to reduce agricultural production. Second, the negative effect of digital inclusive finance on households' agricultural output is realized by widening the gap between the efficiency of non-agricultural economic activities and the efficiency of agricultural production. The wider the gap is, the lower the enthusiasm of households for agricultural production. Third, the mediating effect of “digital financial inclusion – difference in efficiency – agricultural output” has a significant negative effect on households with low agricultural production efficiency, but not households with high agricultural production efficiency. Digital inclusive finance has no significant effect on the difference in efficiency between the two economic activities of high-efficiency households, but a greater difference in efficiency between the two economic activities corresponds to higher enthusiasm of households for agricultural production.

To the best of our knowledge, this paper is the first to analyze the impact of digital financial inclusion on Chinese farmers' agricultural production. The findings of this study can provide policy-related insights to help local governments promote the development of digital finance in China's agricultural economy.

The issue of mounting non-performing assets (NPAs) in Indian banking industry is serious and attracting attention of academia and policy planners. Thus, the purpose of this paper is to test the hypothesis whether NPAs in Indian commercial banking have reached at alarming state where they start affecting the technical efficiency levels adversely or not.

The efficiency score have been computed using case model (model with NPAs as bad/undesirable output) vs control model (model without NPAs as bad/undesirable output) methodology under meta-frontier data envelopment analysis framework.

It has been noticed that the effect of NPAs on overall technical efficiency and its various components is insignificant. The comparison of the case models (i.e. model with NPAs as bad output) with the control models (i.e. model without NPAs) reveals insignificant difference in average efficiency scores and rank distribution of commercial banks. The major source of inefficiency is technology gap (i.e. structure, setup and objectives of banking) among public, domestic private and foreign private categories of banks.

Though NPAs are increasing in Indian banking industry and specifically in Indian public sector banks because of their compulsory lending to priority sector yet the banks have huge scope to extend credit to priority sector as the NPAs have not reached at alarming stage where they start affecting adversely the efficiency performance.

Given the fact that the banking penetrations, structure and objectives differ significantly across ownership, separate frontiers for each ownership (public, private and foreign banks) category has been used to evaluate the technical efficiency levels of 81 commercial banks operating in India over the period 2005 to 2013.

The purpose of this paper is to analyze the effect of environmental policy China’s national program to address climate change on carbon emission efficiency.

Based on the directional distance function, the provincial total factor carbon emission efficiency was measured. Then, the authors analyzed the effect of environmental policy on carbon emission efficiency based on a difference in difference model.

Carbon emission efficiency has been significantly improved since the environmental policy China’s national program to address climate change was put forwarded, but the positive impact in different periods and regions is different. In addition, the environmental policy improves the carbon emission efficiency through the reduction of energy intensity and adjustment of the industrial structure.

This is the first time to use difference in difference model to use a difference in difference model to quantitatively assess the influence of environmental policy China’s national program to address climate change on carbon emission efficiency.

The purpose of this paper is to identify cross-country differences in socio-economic sustainability, which are operationalized as relative efficiency of economic and social impacts of hyperconnectivity (usage intensity of information and communication technologies (ICT) devices). The authors have a particular interest in the emerging economies because they enjoy outstanding growth rates and prospects for market expansion, and have undertaken significant economic reforms and, thus, should be expected to lead other two groups in the efficiency of transforming hyperconnectivity into sustainable growth.

The authors use canonical correlation analysis (CCA) to confirm the existence of a strong and significant relationship between hyperconnectivity drivers and socio-economic outcomes on a country level. The authors test the difference in efficiency of transforming hyperconnectivity into socio-economic sustainability among three groups of countries: advanced, emerging and developing nations using data envelopment analysis (DEA).

The findings indicate that indeed emerging economies were the most effective ones to use infrastructure and digital content followed by developing and advanced countries, respectively. However, relatively better affordability of technologies in the emerging countries did not produce as much socio-economic impact as compared with developing nations. Favorable legislative conditions and high individual ICT usage in advanced economies did not contribute much to socio-economic sustainability either.

One of the limitations of this study stems from the classification of the countries. World Economy Forum and International Monetary Fund resources are utilized for the economy categories, but their basis for classification of counties is rather subjective. Lack of existing comparative efficiency studies on a country level prevents effective benchmarking of the results.

Since the key vehicles of transforming technology into socio-economic impact are organizations, they should design and implement an appropriate organizational architecture which would facilitate this transformation in the emerging markets more effectively.

In a climate of increasing public accountability, governments have been increasingly urged to introduce good administrative practices and performance standards to enable efficient utilization of their resources and enhance social implications within and across countries.

Although the impact of ICT on macro-economic development has been previously studied, the efficiency of this impact was not. Using CCA as a complementary tool for DEA approach in this study constitutes a methodological contribution to existing DEA research, mostly done in the area of operations management. Using DEA on a country level is a novel approach which contributes to the realm of application of this methodology.

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.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

The use of public-private partnerships (P3s) for infrastructure delivery, particularly for highway projects, has been increasing in the USA. The purpose of this paper is to empirically evaluate the difference of P3s and non-P3 highway projects, in terms of their costs and efficiency.

An empirical model of highway construction costs was estimated using a linear regression model that explicitly accounts for the cost differential between the contracts. The differences between efficiencies was also evaluated through a two-stage analysis, where projects’-specific technical efficiencies were first estimated using stochastic frontier analysis and data envelopment analysis, and then the difference in technical efficiencies between the two groups were evaluated through non-parametric tests of means.

Controlling for various project characteristics, the P3 highway projects in the USA showed higher initial costs than non-P3 projects. However, the efficiency scores showed no significant difference between the two groups. This inconsistency between initial costs and technical efficiency scores suggests the complexity involved in P3 projects, which are not captured in the efficiency analysis.

Limited availability of P3 project data due to their immaturity (in cases of P3 projects that include operation and management) and their complex engineering specifications may have caused biased results. Importantly, the study analyzed project costs as of financial close; post-financial close variations, such as change orders during construction, cost/schedule overruns, and renegotiation of contract terms, are beyond the scope of the analysis in this study.

The present study contributes to the literature as one of the earliest empirical analyses of the performance of highway P3s in the USA. Also, this is one of the first studies to employ frontier analysis methods that focus on the efficiency of highway project delivery.

We examine whether loan securitization has an impact on bank efficiency. Using a sample of large US commercial banks from 2002 to 2012, we find that bank loan securitization has a significant and positive impact on bank efficiency, and this relationship is stronger for banks with higher capital ratios, higher default risk, and lower level of liquidity and diversification. Our results are robust to Heckman self-selection correction and difference-in-difference (DID) analysis. In addition, these results are found mainly in non-mortgage loan securitizations but not in mortgage loan securitizations. Finally, we show that loan sales also have a positive impact on bank efficiency.