Bootstrap Data Envelopment Analysis Approach Research Articles

Efficiencies of Faith and Secular Microfinance Institutions in Regions of Asia, Africa, and Latin America: A Two-Stage Dual Efficiency Bootstrap DEA Approach

Purpose: the objective is to measure the financial and social performance of 127 microfinance institutions (MFIs) and observe the effects with explanatory factors such as “type”, “geography region”, and “secular and faith” variables. Design/methodology/approach: The time-series performance analysis of microfinance institutions is determined in two stages. In the first stage, both the social and financial efficiencies are measured with Data Envelopment Analysis (DEA) approach. The two explanatory factors along with faith and secular variables show the effect on these determined efficiencies by the second stage of the Tobit regression Random effect Model. Findings: Financial performance is greater than the social performance from the first stage analysis. When considering the explanatory variables, the social performances are not significant with religious factors. When the regression is performed in a group, the financial score is more significant with religious and other explanatory variables. Faith-based and secular-based microfinance institutions are strongly significant if the performances (efficiencies) are highly maintained. Originality/Value: faith and secular variables are identified based on the background/history information of each microfinance institution (MFI).

Assessing rice production efficiency for food security policy planning in Malaysia: A non-parametric bootstrap data envelopment analysis approach

The 2007–2008 international food crisis triggered national food security policies of several countries worldwide, creating a problematic situation in the global food landscape and led to a drastic shift in the national food security policy (NFSP) approaches undertaken by affected countries. In this context, agricultural policies were reformulated to focus on achieving a certain degree of self-sufficiency while obtaining agricultural efficiency and sustainable agricultural development. This study empirically evaluated Malaysian rice self-sufficiency (RSS) approach, focusing on production efficiency closely related to maximizing production approach and minimizing environmental impact. We utilized non‑parametric bootstrap data envelopment analysis (DEA), input- and output specifications to estimate the relative technical efficiency scores of decision‑making units (DMUs) by constructing confidence intervals and correcting efficiency estimations. Our finding reveals that the Malaysian RSS policy approach demonstrates a better orientation toward output maximization than resource saving. However, the average annual change of the efficiency scores in both specifications was found to deteriorate during the analyzed period. Based on regional analysis, an improved RSS strategic approach could help the nation attain rice production maximization, minimize the environmental impacts, and obtain production efficiency mainly through modernizing the irrigation systems, efficient agrochemical inputs usage, adopting best agricultural practices, and implementing soil treatments programs.

Analysing drivers of efficiency in the leather industry: a two-stage double bootstrap DEA approach

PurposeThe Indian leather industry contributes to economic growth at a significant environmental cost. Due to the rising global demand for sustainable leather products, promoting efficient input utilisation has become vital. This study measures input efficiency and its determinants for leather industry in order for it to improve its future performance.Design/methodology/approachIn the first stage, bootstrap data envelopment analysis (DEA) approach is used for measuring efficiency and analysing firms' differences based on their geographical location, organisational structures, urban-rural location and sub-industrial groups. A second stage regression examines efficiency determinants using size, age, skill and capital-labour intensity as the explanatory variables.FindingsEfficiency result shows a significant potential of minimising inputs by 47% provided the firms adopt best practices. West Bengal firms, urban located firms, individual and proprietorship owned firms and leather consumer goods firms are found to be relatively efficient to their counterparts. Size, skilled managerial staff and labour-intensive firms positively affect efficiency.Practical implicationsConstruction of well-connected roads for accessing urban retail markets and provision of reliable electricity would improve efficiency of rural firms. Small-scale enterprises have a larger share in Indian leather industry; therefore, policy should focus on enhancing the firms' scale and investing in training facilities to skill employed labour for ensuring optimal use of inputs.Originality/valuePrevious studies on the leather industry have used the conventional DEA efficiency measurement approach. This study uses DEA bootstrapping model for robust efficiency estimates and provides consistent inferences about the determinants.

Analyzing factors affecting the technical efficiency of small-scale seaweed farms using a two-stage double bootstrap DEA approach

ABSTRACT Low productivity in seaweed farms in the Philippines is due to issues ranging from lack of training, weather damage, and prevalence of pest and diseases. This study sampled 63 small-scale seaweed farmers in Ipil, Zamboanga Sibugay, as part of a development project. Technical Efficiency (TE) scores were calculated using the two-stage double bootstrap Data Envelopment Analysis (DEA) approach to investigate the causes of inefficiencies and external factors affecting small-scale production. Bias-corrected TE scores reveal that input use can be reduced by 55% to produce the same level of output, suggesting significant efficiency gaps. Factors such as primary occupation, number of farms, access to credit, farm location, and type of product sold had significant effect on technical efficiency. Extending government loan facilities to include seaweed farmers can lead to a reduction in inefficiency. Government initiatives to encourage seaweed farming, choosing the right farm location, and providing information can positively impact efficiency.

Structural and operational management of Turkish airports: a bootstrap data envelopment analysis of efficiency

This paper explores the structural and operational dimensions of the efficiencies of airports. The two-stage procedure is suggested to assess the efficiencies of airports in this study. In the first-stage, Classification and Regression Tree, which is one of the machine-learning approaches used to divide the airports into homogeneous and thus comparable sub-groups. In the second stage, the bootstrap data envelopment analysis approach obtains more precise structural and operational efficiency scores. To illustrate the proposed framework use, we applied it to a real case associated with Turkish airports. The results demonstrate that this framework presents a more comprehensive assessment of airport performance rather than conventional data envelopment analysis models. Moreover, it provides to show the deficiencies of the structural and operational management of airports. The findings can help anywhere airport authorities as well as Turkish airport authorities.

Environmental efficiency of disaggregated energy R&D expenditures in OECD: a bootstrap DEA approach.

Two essential topics of Sustainable Development Goals (SDGs) are accessible which are clean energy (SDG-7) and climate change action (SDG-13). Developments and innovations in energy technologies play an essential role in achieving these goals. Therefore, any country should use energy R&D expenditures, which are the primary source of energy innovation, most optimally. This paper aims to investigate the environmental efficiency of R&D expenditures for energy efficiency, renewable energy, hydro and fuel cells, fossil energy, nuclear energy, and other power and storage technologies in OECD countries using data envelopment analysis (DEA) and bootstrap DEA. Estimation findings indicate that only the USA ensures the environmental efficiency in energy R&D expenditures among OECD countries. Although Japan, Canada, France, Germany, and Italy cannot provide environmental efficiency in energy R&D, their scores are very close to the efficiency frontier. Portugal, Hungary, and Slovak Republic are the countries with the lowest environmental efficiency in energy R&D expenditures. At the end of the investigation, this paper also provides an empirical estimation of the extent to which inefficient countries should change their R&D spending to achieve efficiency.

Efficiency of microfinance institutions of South Asia: a bootstrap DEA approach

The microfinance institutions (MFIs) operate with the dual goals; financial sustainability and social outreach. Therefore, the present paper aims to assess the twin objectives of MFIs operating in the selected four South Asian countries (i.e., Bangladesh, India, Nepal and Pakistan) during the financial year 2010 to 2015. First, we remove the outliers from the dataset by following Banker and Gifford (1988) and Banker and Chang (2006) guidelines. Thereafter, the study use bootstrap data envelopment analysis (DEA) by designing two separate models to measure bias-corrected financial and social efficiency estimates. The empirical results confirm that the South Asian MFIs remain more financially efficient than socially during the study period. Further, the Indian MFIs outperform in terms of both the aspects followed by Nepali and Bangladeshi MFIs, respectively. However, the Pakistani MFIs are the least performers in terms of both social outreach and financial sustainability.

Efficiency of microfinance institutions of South Asia: a bootstrap DEA approach

The microfinance institutions (MFIs) operate with the dual goals; financial sustainability and social outreach. Therefore, the present paper aims to assess the twin objectives of MFIs operating in the selected four South Asian countries (i.e., Bangladesh, India, Nepal and Pakistan) during the financial year 2010 to 2015. First, we remove the outliers from the dataset by following Banker and Gifford (1988) and Banker and Chang (2006) guidelines. Thereafter, the study use bootstrap data envelopment analysis (DEA) by designing two separate models to measure bias-corrected financial and social efficiency estimates. The empirical results confirm that the South Asian MFIs remain more financially efficient than socially during the study period. Further, the Indian MFIs outperform in terms of both the aspects followed by Nepali and Bangladeshi MFIs, respectively. However, the Pakistani MFIs are the least performers in terms of both social outreach and financial sustainability.

Investigating the link between medical urgency and hospital efficiency \u2013 Insights from the German hospital market

With hospital budgets remaining tight and healthcare expenditure rising due to demographic change and advances in technology, hospitals continue to face calls to contain costs and allocate their resources more efficiently. In this context, efficiency has emerged as an increasingly important way for hospitals to withstand competitive pressures in the hospital market. Doing so, however, can be challenging given unpredictable fluctuations in demand, a prime example of which are emergencies, i.e. urgent medical cases. The link between medical urgency and hospitals’ efficiency, however, has been neglected in the literature to date. This study therefore aims to investigate the relationship between hospitals’ urgency characteristics and their efficiency. Our analyses are based on 4094 observations from 1428 hospitals throughout Germany for the years 2015, 2016, and 2017. We calculate an average urgency score for each hospital based on all cases treated in that hospital per year and also investigate the within-hospital dispersion of medical urgency. To analyze the association of these urgency measures with hospitals’ efficiency we use a two-stage double bootstrap data envelopment analysis approach with truncated regression. We find a negative relationship between the urgency score and hospital efficiency. When testing for non-linear effects, the results reveal a u-shaped association, indicating that having either a high or low overall urgency score is beneficial in terms of efficiency. Finally, our results reveal that higher within-hospital urgency dispersion is negatively related to efficiency.

Analyzing the variations in cost-efficiency of marine cage lobster aquaculture in Vietnam: A two-stage bootstrap DEA approach

ABSTRACTThis study measures cost-efficiency and its determinants for 353 marine cage lobster farms in Vietnam using a two-stage bootstrap data envelopment analysis (DEA). In the first stage, the bootstrap DEA approach was used to obtain bias-corrected technical, allocative cost-efficiencies for the farms. Then, the bias-corrected cost-efficiency scores were regressed on a set of explanatory variables using a bootstrapped truncated regression. The results show that substantial cost-inefficiency occurs in lobster aquaculture due to the overuse of inputs, which, given the prevailing input prices, are also used in inappropriate ratios. Cost-efficiency is shown to be significantly impacted by the age of the farmer, total cage volume and by variables affecting the production environment such as the cage cleaning, distance to the nearest farms and the presence of other discharges into the marine environment.

A non-parametric bootstrap-data envelopment analysis approach for environmental policy planning and management of agricultural efficiency in EU countries

Globally, agriculture is a dominant form of human use of land with agro-ecosystems covering about 40% of the terrestrial surface of the Earth. In this context, the European Union considers agriculture a key sector of the economy, recognizing, however, the related environmental implications. The aim of this paper is to examine the agricultural efficiency of EU countries, through a bootstrap-Data Envelopment Analysis (DEA) approach, an effective nonparametric method for evaluating the relative efficiency of the decision-making units. European datasets, suitable for policies and focused on the integration between agricultural productivity and ecosystem services (ESs) conservation, have been used to support planners and managers. Data related to five inputs (labor, land, capital, fertilizers, and irrigation area) and to one output connected to the economic value of agricultural production were collected from 1993 to 2013. The results show that the majority of EU countries have been experiencing increasing or decreasing returns to scale, highlighting their potential to increase their production efficiency by modifying their input use. Both for the output-oriented approach and the input-oriented approach, the majority of EU countries could better rationalize their input use obtaining more outputs and achieving production efficiency. DEA, a non-parametric methodology has been applied, using the concept of a reference group of efficient decision-making units that produce a similar output (peer group). Input-oriented and output-oriented DEA results and comparison indicate that most of the oldest EU countries have a more efficient and optimized crop production process in terms of resource savings and output maximization. This is probably due to the application of the Common Agricultural Policy. Therefore, in policy planning but also in management decisions, attention should always be paid not only to the maximization of agricultural production, but also to the environmental resource overexploitation. In this sense, best agricultural practices could represent a model to follow because they can maintain ESs without depressing production by using practices like conservation tillage, crop diversification, legume intensification and biological control perform giving the same results as intensive, high-input systems.

Efficiency Analysis of Islamic Banks in the Middle East and North Africa Region: A Bootstrap DEA Approach

This paper measures and analyzes the technical efficiency of Islamic banks in the Middle East and North Africa (MENA) region during the period 2007–2012. To do this, the bootstrap Data Envelopment Analysis (DEA) approach was employed in order to provide a robust estimation of the overall technical efficiency and its components: pure technical efficiency and scale efficiency in the case of MENA Islamic banks. The main results show that over the period of study, pure technical inefficiency was the main source of overall technical inefficiency instead of scale inefficiency. This finding was confirmed for all MENA Islamic banks as well as for the two subsamples: Gulf Cooperation Council (GCC) and non-GCC Islamic banks. Furthermore, our results show that GCC Islamic banks had stable efficiency scores during the global financial crisis (2007–2008) and in the early post-crisis period (2009–2010). However, a decline in overall technical efficiency of all panels of MENA Islamic banks was recorded in the last two years of the study period (2011–2012). Thus, we recommend that MENA Islamic bank managers focus more on improving their management practices rather than increasing their sizes. We also recommend that financial authorities in MENA countries implement several regulatory and financial measures in order to ensure the development of MENA Islamic banking.

Technical and scale efficiency in public and private Irish nursing homes – a bootstrap DEA approach

This article provides methodological and empirical insights into the estimation of technical efficiency in the nursing home sector. Focusing on long-stay care and using primary data, we examine technical and scale efficiency in 39 public and 73 private Irish nursing homes by applying an input-oriented data envelopment analysis (DEA). We employ robust bootstrap methods to validate our nonparametric DEA scores and to integrate the effects of potential determinants in estimating the efficiencies. Both the homogenous and two-stage double bootstrap procedures are used to obtain confidence intervals for the bias-corrected DEA scores. Importantly, the application of the double bootstrap approach affords true DEA technical efficiency scores after adjusting for the effects of ownership, size, case-mix, and other determinants such as location, and quality. Based on our DEA results for variable returns to scale technology, the average technical efficiency score is 62%, and the mean scale efficiency is 88%, with nearly all units operating on the increasing returns to scale part of the production frontier. Moreover, based on the double bootstrap results, Irish nursing homes are less technically efficient, and more scale efficient than the conventional DEA estimates suggest. Regarding the efficiency determinants, in terms of ownership, we find that private facilities are less efficient than the public units. Furthermore, the size of the nursing home has a positive effect, and this reinforces our finding that Irish homes produce at increasing returns to scale. Also, notably, we find that a tendency towards quality improvements can lead to poorer technical efficiency performance.

Impact of informal groundwater markets on efficiency of irrigated farms in India: a bootstrap data envelopment analysis approach

In recent years, the proliferation of private well irrigation systems in South Asia, especially in the hard rock areas of India, has stimulated the growth of informal groundwater markets. These markets allow water-buying farmers, who are unable to invest in wells, to benefit from irrigation while enhancing the economic benefits of water-selling farmers. In this way, they have a positive impact on farm income. On the other hand, they are believed to have contributed to the problem of overexploitation of groundwater aquifers. This study examines the role of groundwater markets in determining the efficiency of irrigated farms. Technical, allocative and economic efficiency of groundwater-irrigated farms is determined, using a bootstrapped data envelopment analysis, and the determinants of the efficiency are explored using a bootstrapped truncated regression. For this purpose, data were collected from three different groups of groundwater-irrigated farmers: (i) a control group of 30 farmers who are neither selling nor buying groundwater; (ii) a group of 30 water-selling farmers; and (iii) a group of 30 water-buying farmers. The results demonstrate that there is substantial technical, allocative and economic inefficiency in the irrigated production due to overuse of inputs and that this inefficiency is higher among the control group farmers followed by water sellers and water buyers. Also in the second-stage regression, participation in the water markets is revealed as an important factor positively affecting efficiency scores. This shows that it is relevant for the government to make appropriate institutional policy interventions to capitalize on the benefits associated with the water markets, while at the same time, ensuring that the negative external effects are avoided.

Determinants of Technical Efficiency in Chinese Banking: A Double Bootstrap Data Envelopment Analysis Approach

The main objective of this study is to measure the technical efficiency level of the Chinese banking industry. It uses a double bootstrap data envelopment analysis approach to compute bias-corrected efficiency scores and investigate the determinants of bank efficiency in China between 2003 and 2010. We observe that Chinese commercial banks regardless of ownership have shown improved efficiency from 2003 to 2010. Our results show a significant difference in the performance between state-owned banks and joint-stock banks over the period analyzed. Moreover, the equity-to-asset ratio also significantly explains variations in inefficiency across Chinese commercial banks. Initial public offering is considered one of the effective ways to improve bank efficiency in China. Overall, the present study provides valuable empirical information that can be used to help guide deliberations regarding future reform policies.

Efficiency of microfinance institutions in Sri Lanka: a two-stage double bootstrap DEA approach

This study examines technical efficiency and its determinants of 36 microfinance institutions (MFIs) in Sri Lanka using a two-stage double bootstrap approach. In the first-stage, bias-corrected Data Envelopment Analysis (DEA) efficiency estimates for the individual MFI are obtained by means of the smoothed homogeneous bootstrapped procedure (Simar and Wilson, 2000) and then they are regressed on a set of explanatory variables employing the double bootstrap truncated regression approach (Simar and Wilson, 2007). Two different DEA models are designed to obtain DEA scores along financial and social perspectives. According to the results from the first stage, many MFIs in Sri Lanka do not escape criticism of financial and social inefficiency. Second stage regression reveals that age and capital-to-assets are significant determinants on financial efficiency whereas age, type of the institution and return-on-assets are the crucial determinants of social efficiency.

Measuring and Benchmarking Technical Efficiency of Public Hospitals in Tianjin, China: A Bootstrap-Data Envelopment Analysis Approach.

China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application of this method for benchmarking and inter-organizational learning. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional Banker, Charnes, and Cooper (BCC) model, which means that Chinese researchers need to update their DEA models for more scientific calculation of hospital efficiency scores. Our research has helped shorten the gap between China and the international world in relative efficiency measurement and improvement of hospitals. It is suggested that Bootstrap-DEA be widely applied into afterward research to measure relative efficiency and productivity of Chinese hospitals so as to better serve for efficiency improvement and related decision making.

Evaluating efficiency of international container shipping lines: A bootstrap DEA approach

In this article, a non-parametric analysis of the efficiency of major international container shipping lines (CSLs) is conducted in order to evaluate the effects of the recent profound global economic crisis on such a crucial sector in seaborne trade. Data Envelopment Analysis (DEA) is applied to highlight the efficiency status of top CSLs using a bias-corrected efficiency estimator. In the first stage, hypotheses regarding the underlying production frontier of major international CSLs are tested. In the second stage, an output-oriented, non-increasing returns to scale DEA model is used to compute efficiency scores estimates of the different CSLs. The model considers labour, number of ships and fleet capacity as inputs, and container throughput handled and turnover as outputs. Confidence interval estimates of efficiency and returns to scale for each CSL are reported. The results of the analysis indicate that none of the CSLs assessed operates under constant returns to scale and that average efficiency is 0.74, finding considerable waste in the production of CSLs for the year 2009. In addition, the major international CSLs in 2009 have oversized operations that exceed the most productive scale size. The evidence suggests that strategic alliance membership is not a guarantee for efficient practices in operations. There must be other reasons, purportedly of a strategic nature, for CSLs to join such alliances.

Examining the relation between intangible assets and technical efficiency in the international textile and clothing industry

The resource-based view of the firm suggests that intangible assets have a positive impact on firm performance. This study examined the relation between intangible assets and technical efficiency of textile and clothing firms. A double bootstrap data envelopment analysis approach was used to measure and explain technical efficiency. The empirical application used a data-set of the textile and clothing industry over the period 1995–2004 with a worldwide coverage. The results show that intangible assets had a positive relation with technical efficiency of the textile and clothing firms. Debt and membership of EU had a negative relation, whereas size, membership of NAFTA, and GDP per capita were positively related with technical efficiency.

How efficient are Greek hospitals? A case study using a double bootstrap DEA approach

The purpose of this study was to measure Greek hospital performance using different input-output combinations, and to identify the factors that influence their efficiency thus providing policy makers with valuable input for the decision-making process. Using a unique dataset, we estimated the productive efficiency of each hospital through a bootstrapped data envelopment analysis (DEA) approach. In a second stage, we explored, using a bootstrapped truncated regression, the impact of environmental factors on hospitals' technical and scale efficiency. Our results reveal that over 80% of the examined hospitals appear to have a technical efficiency lower than 0.8, while the majority appear to be scale efficient. Moreover, efficiency performance differed with inclusion of medical examinations as an additional variable. On the other hand, bed occupancy ratio appeared to affect both technical and scale efficiency in a rather interesting way, while the adoption of advanced medical equipment and the type of hospital improves scale and technical efficiency, correspondingly. The findings of this study on Greek hospitals' performance are not encouraging. Furthermore, our results raise questions regarding the number of hospitals that should operate, and which type of hospital is more efficient. Finally, the results indicate the role of medical equipment in performance, confirming its misallocation in healthcare expenditure.