Two-stage Data Envelopment Analysis Approach Research Articles

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.

Sustainability and interactivity between cities and ports: a two-stage data envelopment analysis (DEA) approach

ABSTRACTPorts and cities are intrinsically linked. Port city, which serves as a link between the local and global economy, is an integration of both urban and port systems. Constrained by different regional structures, port cities have developed various formulations over time. Using a two-stage data envelopment analysis (DEA) approach, this paper proposes a new method for measuring the sustainable development of different port city systems. While the previous empirical studies often separate the port system and the urban system, this paper assesses the two systems in an integrated way. Moreover, this paper develops a systematic methodology for measurement of sustainability. Twenty world-leading container port cities are selected for this study using contemporary data. The DEA results display their relative differences in levels of sustainable development, which reveal the effectiveness of the prevailing policies in them. Eventually, recommendations are drawn for other port cities by referring to the best practices.

A two-stage DEA approach to analyse the efficiency of the hospitality sector

This article explores the performance of the hospitality sector in Sardinia (Italy) using empirical data collected from company balance sheets (from 2004 to 2013). A standard data envelopment analysis (DEA) is run using sales revenue as an output and the monetary value of all tangible and intangible assets as well as labour costs as inputs. Following the Simar–Wilson approach, a post-DEA is also carried out to investigate the factors that influence hotels’ economic efficiency. The empirical results show that business default and the cost of money negatively influence hotels’ performance and that firms located in highly specialized areas with a strong seasonality are relatively inefficient. Furthermore, the short-run debt index and the long-term debt index positively impact efficiency.

Can Foreign Capital Participation Enhance Commercial Banks’ Market Efficiency?

Banks’ efficiency can be decomposed into their ability in expanding their business with given inputs and ability in making maximum profits with given business scale. The former is defined as the operational efficiency while the latter is defined as the market efficiency. This paper tries to test impacts of foreign capital participation on the Chinese listed commercial banks’ market efficiency with two-stage Data Envelopment Analysis (DEA) approach and Tobit model. The results indicate that more foreign capital participation can help to improve the largest banks’ market efficiency, while weak foreign capital participation cannot help. These findings are important not only for China but also for the other transitional economies and developing economies. DOI: http://dx.doi.org/10.5755/j01.ee.29.1.5444

Are public state libraries efficient? An empirical assessment using network Data Envelopment Analysis

In Italy, public state libraries are multi-product organizations preserving ancient books of great historical relevance for future generations, and providing divisible services to the public. Hence, they may undertake different activities for conservation and use, which together constitute a network. This paper shows the importance of considering multi-process interactions in evaluating the overall performance of public state libraries and focuses on library operations and their sub-processes. It uses a network two-stage Data Envelopment Analysis (DEA) approach to examine the relationship between the libraries' basic inputs, intermediate outputs and final outputs. The main result is that Italian public state libraries generally perform better in the first stage of conservation, but score poorly in the second stage of use. Some policy advice to improve the decision-making process follow

Data envelopment analysis, truncated regression and double-bootstrap for panel data with application to Chinese banking

We investigate the impact of earning asset diversification on Chinese bank efficiency from 2006 to 2011. We do this by adapting the current two-stage data envelopment analysis approach to a panel data setting so that we can account for technology change over time. Our Monte Carlo experiments illustrate the advantages and disadvantages of the proposed new algorithm over the conventional approach. When applied to Chinese banking data, the regression results reveal that increasing the asset share of other earning assets (including securities and derivatives) is positively associated with bank efficiency. Decreasing the share of nonearning assets in total assets or increasing total equity has a similar impact. Our results also suggest that financial reforms currently being undertaken in China, including removing the regulatory requirement concerning the ratio of loans to deposits (a draft amendment to the existing commercial banking law) and interest rate liberalization (a proposed draft amendment), are likely to have a positive effect on bank efficiency in China.

A two-stage DEA approach for quantifying and analysing the inefficiency of conventional and organic rain-fed cereals in Spain

This paper assesses the efficiency of rain-fed cereals crops grown in Southern Spain. The proposed approach uses a two-stage Data Envelopment Analysis (DEA) plus regression approach. In the first stage a Slacks-based Inefficiency (SBI) DEA model is used to project conventional and organic cropping systems onto the efficient frontier. The results of the efficiency analysis show that conventional production is more inefficient than organic production and that the main sources of inefficiency in the case of conventional production correspond to excessive input consumption and GHG emissions. In the case of organic production, the inefficiency comes from output shortfalls. It is shown that reducing inefficiency would reduce the amount of GHG emitted per unit of fresh matter yielded. This potential gain is more pronounced in the case of conventional production but also occurs for organic production. In the second stage, the crops efficiency scores are regressed against some exogenous variables using a fractional regression model. The regression results confirm that organic production significantly decreases inefficiency and they also indicate that the larger the farm, the larger the inefficiency and that growing barley is more inefficient than wheat.

Determinan Tingkat Efisiensi Perbankan Syariah Di Indonesia: Two Stages Data Envelopment Analysis

Efficiency is an important indicator to observe the banks’ ability in resisting and facing the tight rivalry at banking industry. The study aims to evaluate the efficiency and to analyze the determinants of efficiency of Islamic bank in Indonesia on 2010 – 2013 with Two-Stage Data Envelopment Analysis approach. The objects of the study are 11 Islamic banks (BUS). The first phase of testing uses the Data Envelopment Analysis (DEA) method showed that the efficiency of Islamic bank is inefficient on managing the resources and small Islamic banks are more efficient than the larger. The second phase of testing uses Tobit model showed that Capital Adequacy Ratio (CAR), Return on Asset (ROA), Non Performing Financing (NPF), Financing to Deposit Ratio (FDR), and Net Interest Margin (NIM) have positive significant effect on the efficiency of Islamic banks, while Good Corporate Governance (GCG) has a negative significant effect. Moreover, the macroeconomic variables, such as GDP growth and inflation have no significant effect on efficiency of Islamic banks. It suggests that to realize the optimum level of Islamic banks’ efficiency is only related with bank-specific, while the volatility of macroeconomics condition contributes nothing

Closing oil palm yield gaps among Indonesian smallholders through industry schemes, pruning, weeding and improved seeds.

Oil palm production has led to large losses of valuable habitats for tropical biodiversity. Sparing of land for nature could in theory be attained if oil palm yields increased. The efficiency of oil palm smallholders is below its potential capacity, but the factors determining efficiency are poorly understood. We employed a two-stage data envelopment analysis approach to assess the influence of agronomic, supply chain and management factors on oil palm production efficiency in 190 smallholders in six villages in Indonesia. The results show that, on average, yield increases of 65% were possible and that fertilizer and herbicide use was excessive and inefficient. Adopting industry-supported scheme management practices, use of high-quality seeds and higher pruning and weeding rates were found to improve efficiency. Smallholder oil palm production intensification in Indonesia has the capacity to increase production by 26%, an equivalent of 1.75 million hectares of land.

What About the Social Efficiency in Credit Cooperatives? Evidence from Spain (2008–2014)

Credit cooperatives are financial intermediaries that pay attention to social criteria. Thus, if such entities want to survive and thrive in the new international context, they cannot ignore their inefficiencies in both the financial and social dimensions of their activity. However, previous research on efficiency in credit cooperatives is very limited and only considers their financial activity. To date, no study has been published giving evidence through indicators on whether these banking institutions are socially efficient. This paper therefore constructs a social efficiency index of Spanish credit cooperatives during the period 2008–2014 and examines its main explanatory factors. After applying a two-stage Data Envelopment Analysis approach, the results from the first stage indicate that, on average, the social efficiency of Spanish credit cooperatives reaches an acceptable level of 66.42 %. Second-stage truncated regression reveals that entities with a greater proportion of branches in urban areas are socially less efficient, whereas both their size and the number of service points have a positive effect. Interestingly, social efficiency also varies significantly depending on the regional location of credit cooperatives in Spain. As a result, our findings enable these Social Economy financial institutions to both know their performance relative to their social activity and use this information to improve their competitiveness in the future.

Measuring efficiency of working capital management: a two-stage data envelopment analysis approach

Measuring efficiency of working capital management: a two-stage data envelopment analysis approach

Measuring efficiency of working capital management: a two-stage data envelopment analysis approach

The purpose of this paper is to analyse the efficiency of working capital management (WCM) in Indian manufacturing firms during the period 2004-2013. The paper describes and uses a new approach based on data envelopment analysis (DEA) to measure the WCM efficiency of firms. Two-stage bootstrapped DEA is employed to first calculate the efficiency and then analyse the effect of exogenous variables on it. We find that the average WCM efficiency over the last ten years was around 40% and majority of the firms were on the lower side of the average. Firm-specific factors like firm's age, proportion of fixed assets, return on asset and sales growth are found to have significant effect on efficiency, whereas macroeconomic factors have a somewhat inconsistent effect. The paper further suggests that the DEA-based measure is not only able to overcome the limitations of traditional measures like mathematical incorrectness and assignment of fixed weights to constituents but also offers several additional advantages.

Evaluating contextual factors affecting the technical efficiency of freshwater pond culture systems in Peninsular Malaysia: A two-stage DEA approach

The demand for animal protein, especially fish, is growing fast, perhaps due to the rapid expansion of populations, increases in income and changes in eating habits and life styles. Capture fisheries, which supply over 70% of the fish for human consumption in Malaysia, are over-exploited or depleted. Their yields have become stagnant over the last few decades and in some cases have even declined. Nevertheless, aquaculture has the potential to meet these challenges if practised well. This study therefore aims to estimate the technical efficiency of pond culture systems using data envelopment analysis (DEA). In addition, it investigates the determinants of technical efficiency by employing an ordinary least squares (OLS) regression model. The estimated technical efficiency of pond culture was found to be 0.86, which means that the fish farmers in our sample could reach full technical efficiency through reducing their input usage by 14% with the current level of technology to produce the same output levels. The results of the OLS regression indicate that farmers’ age, experience, extension training and water management have positive and statistically significant impacts on technical efficiency. Information on water management practices could be passed on by extension agents to inefficient farms to assist them in catching up with the farms demonstrating best practice.

Efficiency of the implementation of cardiovascular risk management in primary care practices: an observational study.

BackgroundThis study aimed to document the variation in technical efficiency of primary care (PC) practices in delivering evidence-based cardiovascular risk management (CVRM) and to identify associated factors.MethodsThis observational study was based on the follow-up measurements in a cluster randomized trial. Patients were recruited from 41 general practices in the Netherlands, involving 106 GPs and 1671 patients. Data on clinical performance were collected from patient records. The analysis focused on PC practices and used a two-stage data envelopment analysis (DEA) approach. Bias-corrected DEA technical efficiency scores for each PC practice were generated, followed by regression analysis with practice efficiency as outcomes and organizational features of general practice as predictors.ResultsNot all PC practices delivered recommended CVRM with the same technical efficiency; a significant difference from the efficient frontier was found (p < .000; 95 % CI 1.018–1.041). The variation in technical efficiency between PC practices was associated with training practice status (p = .026). Whether CVRM clinical tasks were performed by a practice nurse or a GP did not influence technical efficiency in a statistical significant way neither did practice size.ConclusionsTechnical efficiency in delivering evidence-based CVRM increased with having a training practice status. Nurse involvement and practice size showed no statistical impact.

A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.

Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output

Bank industry plays a critical role in the economic development of China. In this paper, we develop a new two-stage data envelopment analysis approach for measuring the slacks-based efficiency of Chinese commercial banks during years 2008–2012, where the banking operation process of each bank is divided into a deposit-generation stage (division) and a deposit-utilization stage (division). In the approach, the increase of desirable outputs and the decrease of undesirable outputs are simultaneously considered in order to identify the inefficiency of a bank. Three efficiency statuses are first defined for such a system to investigate its input-output performance and divisional performances, and a full efficiency status is then defined based on these statuses. The empirical results show that the improvement of the banks’ performances during this period was mainly contributed by the improvement of deposit-utilization stage. Besides, the results also show that our approach can provide a benchmark for the intermediate measures of the two stages of an inefficient bank.

Measuring the efficiency of wastewater services through Data Envelopment Analysis.

Efficient water management is a priority in the European Union, since the operational efficiency of many water utilities is very low compared to best practice. Several countries are restructuring the water industry to save costs. Larger-scale operations and vertical integration are promoted to achieve scale and scope economies; however, the literature is not unanimous that such economies exist. There is also little evidence of the effect of customer density on costs. This article offers some insights into this matter, analysing the Danish water industry by a two-stage Data Envelopment Analysis approach to investigate the effects of size, scope and density in the wastewater industry. The results show that the Danish wastewater industry is positively affected by vertical integration and higher population density: firms that serve more than 100 person per km of sewer and combine water and wastewater services achieve better efficiency. Size does not have any significant influence on global efficiency, although technical pure efficiency decreases statistically with firm size.

A new look at measuring sustainability of industrial parks: a two-stage data envelopment analysis approach

An industrial park is a community of manufacturing and service businesses located together in a specific area. The sustainable industrial park is strategically significant for sustainable development of countries. In this paper, a gradual efficiency improvement data envelopment analysis (DEA) model is proposed to (i) measure sustainability of industrial parks, (ii) classify follower and pioneer industrial parks regarding the environmental performance, and (iii) direct the followers toward pioneers to gradually (not at once) improve their performance and make feasible improvement plans. The proposed method identifies decision-making units (DMUs) on most productive scale size (MPSS) region, and then projects other DMUs onto this region. The proposed model is extended to evaluate performance of a two-stage network structures where outputs from the first stage become inputs to second stage in addition to inputs of first stage and outputs of second stage. The proposed approach is applied to measure the sustainability of 31 Iranian industrial parks. Despite traditional DEA methods, the results indicate that inputs (outputs) should not be necessarily decreased (increased) to project the industrial parks onto the MPSS region.

Environment and economic performance evaluation of 30 provinces and municipalities in China based on a two-stage multiplier DEA approach

Data envelopment analysis (DEA) has been widely applied in the performance evaluation of environment or economy recently. If economic and environmental systems exist simultaneously in a decision making unit (DMU), conventional DEA models generally treat the DMU as a black box, and the internal relationship of DMU is often ignored. Thus, the performance of DMUs may be overestimated. In order to solve this problem, a new two-stage multiplier DEA approach is proposed in this paper. The new model can not only obtain the efficiency score of each system, but also consider the intermediate outputs when assessing the overall efficiency of the two systems. In order to test the effectiveness of this approach, a numerical example of 30 provinces in China is illustrated.

The Sources of Efficiency in the Nigerian Banking Industry

The paper employed a two-stage Data Envelopment Analysis (DEA) approach to examine the sources of technical efficiency in the Nigerian banking sub-sector. Using a cross section of commercial and merchant banks, the study showed that the Nigerian banking industry was not efficient both in the pre-and-post-liberalization era. The study further revealed that market share was the strongest determinant of technical efficiency in the Nigerian banking Industry. Thus, appropriate macroeconomic policy, institutional development and structural reforms must accompany financial liberalization to create the stable environment required for it to succeed. Hence, the present bank consolidation and reforms by the Central Bank of Nigeria, which started with Soludo and continued with Sanusi, are considered necessary, especially in the areas of e banking and reorganizing the management of banks.