Efficiency and exogenous factors: evidence from Spanish tourism regions

2017 ◽  
Vol 30 (1) ◽  
pp. 108-123 ◽  
Author(s):  
José Solana Ibáñez ◽  
Lorena Para González ◽  
Carmen de Nieves Nieto
Keyword(s):  
Statistical Significance ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Strategic Decisions ◽  
Content Type ◽  
Dea Models ◽  
World Tourism Organization ◽  
Scale Test ◽  
Exogenous Factors ◽  
Tourism Organization

Purpose The purpose of this paper is to analyse the performance of Spanish tourism regions for the 2008-2011 period, to obtain a ranking of efficiency and to examine the hypothesis that the efficiency of these regions is determined by a group of contextual variables. Design/methodology/approach In contrast with monitoring reports based on descriptive methods, this paper uses data envelopment analysis (DEA) methodology and bootstrap semiparametric procedures to correct inherent bias. The significance of a group of exogenous factors is investigated and the importance of each determinant is ordered by its elasticity. Findings The ranking obtained by radial DEA models and by bias-corrected ones describes two remarkably different settings. The exogenous variables influence hypothesis and confirmed: that estimated coefficients are of the correct sign and statistically significant at 5 per cent. Originality/value The statistical significance of the potential attractors can offer an interesting tool for strategic decisions. The two-stage procedure employed has supposed a turning point in the methodology and there are only a handful of very recent studies of this type in the literature on tourism destination performance. In this sense, no previous work has considered the returns to scale test or the separability assumption. Following United Nations of World Tourism Organization recommendations, it is essential to move towards responsible tourism in all aspects. Some final considerations about the link between performance and sustainability of the Spanish tourist model are addressed in this study.

Analyzing technical and super efficiency of aluminium firms in India

2017 ◽  
Vol 24 (6) ◽  
pp. 1729-1741 ◽  
Author(s):  
Mini Kundi ◽  
Seema Sharma
Keyword(s):  
Large Scale ◽  
Returns To Scale ◽  
Foreign Firms ◽  
Data Envelopment ◽  
Content Type ◽  
Super Efficiency ◽  
Young Firms ◽  
Dea Models ◽  
Dea Analysis ◽  
Practical Implications

Purpose The purpose of this paper is to evaluate the efficiency of aluminium firms in India. Design/methodology/approach Different data envelopment analysis (DEA) models have been employed to calculate the various efficiency scores of aluminium firms in India. Findings The major findings of the DEA analysis suggest that 62 per cent firms are found to be technically efficient. Overall, the industry shows good performance with mean technical efficiency levels of 0.936 and 0.911 for VRS and CRS frameworks, respectively. Further, five firms show decreasing returns to scale, signifying the overutilization of plant capacities. Six firms exhibit increasing returns to scale implying underutilization of plants. The results show that domestic firms are more efficient than the foreign firms, young firms are more efficient than young firms and small- and medium-scale firms are more efficient than large-scale firms. Practical implications The results of this study would help the aluminium firms to formulate an appropriate strategy to cautiously use their resources to increase their efficiency levels. Originality/value To the best of authors’ knowledge, no earlier studies seem to have ranked the aluminium firms based on their super-efficiency scores. Further, no previous studies seem to have examined the efficiency differences among aluminium firms across different size, age and ownership groups.

Rationality, accounting and benchmarking water businesses

2018 ◽  
Vol 31 (3) ◽  
pp. 290-315 ◽  
Author(s):  
Nicholas Pawsey ◽  
Jayanath Ananda ◽  
Zahirul Hoque
Keyword(s):  
Economic Efficiency ◽  
Fair Value ◽  
Water Utilities ◽  
Future Research ◽  
Data Envelopment ◽  
Water Utility ◽  
Capital Input ◽  
Content Type ◽  
Dea Models ◽  
Future Work

Purpose The purpose of this paper is to explore the sensitivity of economic efficiency rankings of water businesses to the choice of alternative physical and accounting capital input measures. Design/methodology/approach Data envelopment analysis (DEA) was used to compute efficiency rankings for government-owned water businesses from the state of Victoria, Australia, over the period 2005/2006 through 2012/2013. Differences between DEA models when capital inputs were measured using either: statutory accounting values (historic cost and fair value), physical measures, or regulatory accounting values, were scrutinised. Findings Depending on the choice of capital input, significant variation in efficiency scores and the ranking of the top (worst) performing firms was observed. Research limitations/implications Future research may explore the generalisability of findings to a wider sample of water utilities globally. Future work can also consider the most reliable treatment of capital inputs in efficiency analysis. Practical implications Regulators should be cautious when using economic efficiency data in benchmarking exercises. A consistent approach to account for the capital stock is needed in the determination of price caps and designing incentives for poor performers. Originality/value DEA has been widely used to explore the role of ownership structure, firm size and regulation on water utility efficiency. This is the first study of its kind to explore the sensitivity of DEA to alternative physical and accounting capital input measures. This research also improves the conventional performance measurement in water utilities by using a bootstrap procedure to address the deterministic nature of the DEA approach.

scholarly journals The Efficiency of Waste Sector in Italy: An Application by Data Envelopment Analysis

2020 ◽  
Vol 24 (3) ◽  
pp. 225-238
Author(s):  
Massimo Gastaldi ◽  
Ginevra Virginia Lombardi ◽  
Agnese Rapposelli ◽  
Giulia Romano
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Performance ◽  
Returns To Scale ◽  
Sustainable Growth ◽  
Waste Reduction ◽  
Data Envelopment ◽  
Environmental Legislation ◽  
Dea Models ◽  
Developed Nations ◽  
Variable Returns To Scale

AbstractWith growing environmental legislation and mounting popular concern for the need to pursuing a sustainable growth, there has been an increasing recognition in developed nations of the importance of waste reduction, recycling and reuse maximization. This empirical study investigates both ecological and economic performances of urban waste systems in 78 major Italian towns for the years 2015 and 2016. To this purpose the study employs the non-parametric approach to efficiency measurement, represented by Data Envelopment Analysis (DEA) technique. More specifically, in the context of environmental performance we implement two output-oriented DEA models in order to consider both constant and variable returns to scale. In addition, we include an undesirable output – the total amount of waste collected – in the two models considered. The results show that there is variability among the municipalities analysed: Northern and Central major towns show higher efficiency scores than Southern and Islands ones.

An application of data envelopment analysis for Korean banks with negative data

2017 ◽  
Vol 24 (4) ◽  
pp. 1052-1064 ◽  
Author(s):  
Yong Joo Lee ◽  
Seong-Jong Joo ◽  
Hong Gyun Park
Keyword(s):  
Data Envelopment Analysis ◽  
Data Sets ◽  
Data Envelopment ◽  
Negative Data ◽  
Ownership Type ◽  
Data Set ◽  
Translation Invariant ◽  
Content Type ◽  
Dea Models ◽  
Regional Banks

Purpose The purpose of this paper is to measure the comparative efficiency of 18 Korean commercial banks under the presence of negative observations and examine performance differences among them by grouping them according to their market conditions. Design/methodology/approach The authors employ two data envelopment analysis (DEA) models such as a Banker, Charnes, and Cooper (BCC) model and a modified slacks-based measure of efficiency (MSBM) model, which can handle negative data. The BCC model is proven to be translation invariant for inputs or outputs depending on output or input orientation. Meanwhile, the MSBM model is unit invariant in addition to translation invariant. The authors compare results from both models and choose one for interpreting results. Findings Most Korean banks recovered from the worst performance in 2011 and showed similar performance in recent years. Among three groups such as national banks, regional banks, and special banks, the most special banks demonstrated superb performance across models and years. Especially, the performance difference between the special banks and the regional banks was statistically significant. The authors concluded that the high performance of the special banks was due to their nationwide market access and ownership type. Practical implications This study demonstrates how to analyze and measure the efficiency of entities when variables contain negative observations using a data set for Korean banks. The authors have tried two major DEA models that are able to handle negative data and proposed a practical direction for future studies. Originality/value Although there are research papers for measuring the performance of banks in Korea, all of the papers in the topic have studied efficiency or productivity using positive data sets. However, variables such as net incomes and growth rates frequently include negative observations in bank data sets. This is the first paper to investigate the efficiency of bank operations in the presence of negative data in Korea.

scholarly journals A Comparison of Ensemble and Dimensionality Reduction DEA Models Based on Entropy Criterion

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 232
Author(s):  
Parag C. Pendharkar
Keyword(s):  
Dimensionality Reduction ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Objective Functions ◽  
High Entropy ◽  
Selection Of Variables ◽  
Dea Models ◽  
Entropy Criterion ◽  
Selection Of ◽  
Normally Distributed

Dimensionality reduction research in data envelopment analysis (DEA) has focused on subjective approaches to reduce dimensionality. Such approaches are less useful or attractive in practice because a subjective selection of variables introduces bias. A competing unbiased approach would be to use ensemble DEA scores. This paper illustrates that in addition to unbiased evaluations, the ensemble DEA scores result in unique rankings that have high entropy. Under restrictive assumptions, it is also shown that the ensemble DEA scores are normally distributed. Ensemble models do not require any new modifications to existing DEA objective functions or constraints, and when ensemble scores are normally distributed, returns-to-scale hypothesis testing can be carried out using traditional parametric statistical techniques.

A review of the literature on DEA models under common set of weights

2020 ◽  
Vol 15 (4) ◽  
pp. 1277-1300
Author(s):  
Ignacio Contreras
Keyword(s):  
Future Research ◽  
Data Envelopment ◽  
Systematic Revision ◽  
Systematic Classification ◽  
Content Type ◽  
Dea Models ◽  
Common Set Of Weights ◽  
The Individual ◽  
Selection Of

Purpose Data envelopment analysis (DEA) is a mathematical method for the evaluation of the relative efficiency of a set of alternatives, which produces multiple outputs by consuming multiple inputs. Each unit is evaluated on the basis of the weighted output over the weighted input ratio with a free selection of weights and is allowed to select its own weighting scheme for both inputs and outputs so that the individual evaluation is optimized. However, several situations can be found in which the variability between weighting profiles is unsuitable. In those cases, it seems more appropriate to consider a common vector of weights. The purpose of this paper is to include a systematic revision of the existing literature regarding the procedures to determine a common set of weights (CSW) in the DEA context. The contributions are classified with respect to the methodology and to the main aim of the procedure. The discussion and findings of this paper provide insights into future research on the topic. Design/methodology/approach This paper includes a systematic revision of the existing literature about the procedures to determine a CSW in the DEA context. The contributions are classified with respect to the methodology and to the main aim of the procedure. Findings The discussion and findings of the literature review might insights into future research on the topic. Originality/value This papers revise the state of the art on the topic of models with CSW in DEA methodology and propose a systematic classification of the contributions with respect to several criteria. The paper would be useful for both theoretical and practical future research on the topic.

Environmental efficiency of Xiangjiang River in China: a data envelopment analysis cross-efficiency approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qingxian An ◽  
Zhaokun Cheng ◽  
Shasha Shi ◽  
Fenfen Li
Keyword(s):  
Information Technology ◽  
Data Envelopment Analysis ◽  
Environmental Performance ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Efficiency Measure ◽  
Tobit Regression ◽  
Xiangjiang River ◽  
Content Type ◽  
Exogenous Factors

PurposeEnvironmental performance becomes a key issue for the sustainable development. Recently, incremental information technology is adopted to collect environmental data and improve environmental performance. Previous environmental efficiency measures mainly focus on individual decision-making units (DMUs). Benefited from the information technology, this paper develops a new environmental efficiency measure to explore the implicit alliances among DMUs and applies it to Xiangjiang River.Design/methodology/approachThis study formulates a new data envelopment analysis (DEA) environmental cross-efficiency measure that considers DMUs' alliances. Each DMUs' alliance is formulated by the DMUs who are supervised by the same manager. In cross-efficiency evaluation context, this paper adopts DMUs' alliances rather than individual DMUs to derive the environmental cross-efficiency measure considering undesirable outputs. Furthermore, the Tobit regression is conducted to analyze the influence of exogenous factors about the environmental cross-efficiency.FindingsThe findings show that (1) Chenzhou performs the best while Xiangtan performed the worst along Xiangjiang River. (2) The environmental efficiency of cities in Xiangjiang River is generally low. Increasing public budgetary expenditure can improve environmental efficiency of cities. (3) The larger the alliance size, the higher environmental efficiency. (4) The income level is negatively correlated with environmental efficiency, indicating that the economy is at the expense of the environment in Xiangjiang River.Originality/valueThis paper contributes to developing a new environmental DEA cross-efficiency measure considering DMUs' alliance, and combining DEA cross-efficiency and Tobit regression in environmental performance measurement of Xiangjiang River. This paper examines the exogenous factors that have influences on environmental efficiency of Xiangjiang River and derive policy implications to improve the sustainable operation.

Eco-innovation analysis of OECD countries with common weight analysis in data envelopment analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Kiani Mavi ◽  
Neda Kiani Mavi ◽  
Reza Farzipoor Saen ◽  
Mark Goh
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Oecd Countries ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Environmental Research ◽  
Data Envelopment ◽  
Discrimination Power ◽  
Content Type ◽  
Dea Models

PurposeDespite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW). Design/methodology/approachUsing goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018. FindingsAchieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018. Practical implicationsMore investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions. Originality/valueIn addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.

A MONTE CARLO EVALUATION OF SEVERAL TESTS FOR THE SELECTION OF VARIABLES IN DEA MODELS

2005 ◽  
Vol 04 (03) ◽  
pp. 325-343 ◽  
Author(s):  
INMACULADA SIRVENT ◽  
JOSÉ L. RUIZ ◽  
FERNANDO BORRÁS ◽  
JESÚS T. PASTOR
Keyword(s):  
Statistical Tests ◽  
Returns To Scale ◽  
Nonparametric Tests ◽  
Model Specification ◽  
Data Envelopment ◽  
Selection Of Variables ◽  
Dea Models ◽  
Observed Behaviour ◽  
Monte Carlo Evaluation ◽  
Selection Of

Data Envelopment Analysis (DEA) is a recently developed methodology that is widely used for estimating relative efficiency scores of Decision Making Units (DMUs) that use several inputs to produce several outputs. Model specification in DEA includes aspects such as the choice of inputs and outputs or the adoption of a returns to scale assumption. As pointed out by many authors, it is obvious that the specification of a model is the key to having reliable efficiency scores. In this paper, we are particularly concerned with the selection of variables in DEA models. To be specific, we investigate the performance of several statistical tests existing in the literature that can be used for the selection of variables. In particular, the behaviour of the well-known tests proposed by Banker2 and the nonparametric tests recently developed by Pastor et al.13 is analyzed in relation to several factors such as sample size, model size, the specification of returns to scale and the type and level of inefficiency. We have drawn some conclusions that will be of help for practical uses, since the observed behaviour of the tests in the different scenarios determined by the specifications of the mentioned factors may provide some useful insight into the choice of an adequate statistical test in the particular context of a given DEA application.

International performance benchmarking in winemaking

2017 ◽  
Vol 24 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Anatoliy G. Goncharuk ◽  
Natalia Lazareva
Keyword(s):  
Wine Industry ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
International Performance ◽  
Performance Benchmarking ◽  
Capital Productivity ◽  
Product Service ◽  
Study Results ◽  
Dea Models

Purpose The purpose of this paper is to study winemaking efficiency with the help of international performance benchmarking and to finding ways for its improvement. Design/methodology/approach In this research, three models of data envelopment analysis (DEA) and other tools of international performance benchmarking are used to analyse the efficiency of wine companies. Return to scale (RTS) and scale efficiency, labour and capital productivity and some other indicators are examined. The research is based on a sample of 36 wine companies from 15 countries. Findings International benchmarking expands performance improvement for domestic companies. The most efficient wine companies are originated from Germany, USA and New Zeeland. Scale inefficiency and increasing RTS for most of the wine companies was identified. Only three wine companies have decreasing RTS (those from UK, Australia and France). To increase relative efficiency, these companies need to reduce the output and sales as their costs are growing faster than the revenues. A huge potential for cost reduction and efficiency growth within Ukrainian wine companies was revealed. Research limitations/implications The research is limited to a single industry. This is explained by the requirement of technology (product, service) homogeneity while using DEA tools. Practical implications Study results include the data and recommendations to develop winemaking. These results can be used by wine companies’ management, present and potential investors and proprietors, regulative public authority, e.g. to improve efficiency in winemaking. Originality/value This is the first paper that adapts various DEA models to measure efficiency in the wine industry of Ukraine and the tools of international performance benchmarking for wine companies around the world.

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