A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach

The insurance industry worldwide has become less fragmented through liberalization reforms. Yet, following the transformational changes, there is little empirical evidence on identifying the determinants of managerial efficiency. This paper employs a truncated regression analysis to determine the factors driving managerial efficiency of Malaysian insurers. Overall and divisional efficiencies are derived using data envelopment analysis. The decomposition analysis reveals that the observed inefficiency is mainly caused by investment capability division. The regression findings reveal that determinants of efficiency have dissimilar impacts on overall and divisional efficiencies. This study broadly supports financial liberalization as a means of promoting managerial efficiency.     

基于数据包络分析法的涉农金融机构经营效率分析

文章以2012年246家涉农金融机构的4项投入因素(员工人数、总利息支出、非利息费用与净值)与3项产出因素(贷款收入、非贷款收入与逾期贷款比率)为研究对象,利用非预期因素数据包络分析法,分析涉农金融机构经营效率的评估,并提出达到相对有效率应改善的方向。研究发现:舍弃逾期贷款比率与不舍弃逾期贷款比率的产出导向BCC模型间,占总体样本的8.54%,显现两种方法有其差异性。这是因为涉农金融逾期贷款比率愈高,需要付出更多的人力去催讨与处理抵押品的损失,皆会影响涉农金融机构经营效率。此外,投入或产出项需要调整的涉农金融机构占80.89%。涉农金融机构经营效率低下的主要原因是资源分配不当,如何降低经营成本与开拓业务实属当务之急。     

Firm performance and ownership structure: Dynamic network data envelopment analysis approach

This paper applies dynamic network slacks-based data envelopment analysis to measure financial performance based on the interrelationship among investment, financing, and dividend decisions. The empirical results show that financial performance is determined simultaneously by the efficiency of decisions, and sample firms have good performance in investment stage, but need to improve their financing and dividend policies. The proposal financial performance measure explains the multicriteria of decision-making rather than the single financial ratios. Besides, the research contributes a novel on the significant relationship between firm's ownership structure in the form of managers, government and foreign shareholders, and the firm's financial performance.     

Distance optimization approach to ratio-form efficiency measures in data envelopment analysis

This paper examines the development pattern of the DEA (Data Envelopment Analysis) research field using Social Network Analysis. Nine stylized facts are verified: it is shown that the distribution of research performance is highly skewed, satisfying a power law, and that collaborative research activity is concentrated achieving higher performance. Moreover, economics and OR (operations research)/MS (management science) groups developed without collaboration until the 1980s; however, the merger of the two groups began in 1994 with the collaboration of frontier researchers. Now the two groups have merged significantly, but they are still identifiable. Finally, research hubs and the emergence of new groups are examined. Nine stylized facts show that DEA has developed with unique attributes. Although it shares common characteristics with other academic fields, including a highly skewed distribution of publications and expansion of the network over time, the DEA field has had a pattern of development that is different from those of other academic fields. Independent development and interrelated evolution between economics and OR/MS contributed to the exchange of knowledge of these two separate fields.     

A data envelopment analysis of gas utilities' efficiency

This study examines the Natural Gas Policy Act of 1978 and Federal Energy Regulatory Commission (FERC) policies that culminated in Order 636 in 1992. The regulatory environment in which natural gas distribution utilities operate was altered. FERC policies forced local gas distribution utilities into an increasingly competitive environment. Restructuring of the industry may affect economic efficiency. Data Envelopment Analysis is used to examine the economic efficiency of gas distributors during 1975–94. Federal policy appears to lead to a reduction in scale due to restructuring and more competition. Reduced scale economies have not altered the economic efficiency of the utilities.     

Productive efficiency of English football teams—a data envelopment analysis approach

This paper investigates how close to their potential English Premier League Clubs play. Using a deterministic Data Envelopment Analysis Approach, the productive efficiency of 20 teams in the 2000/2001 season is measured and weaknesses of individual teams are disclosed. The sensitivity of results is analyzed with regard to different model specifications and variable combinations. Copyright © 2003 John Wiley & Sons, Ltd.     

Measurement of technical efficiency in farrow-to-finish swine production using multi-activity network data envelopment analysis: evidence from Taiwan

This study aims to propose a dynamic multi-activity network data development analysis (DMNDEA) model to measure the technical efficiency of farrow-to-finish swine production in Taiwan. Production phases are explicitly divided into two activities; namely, the breed-to-farrow phase and the wean-to-finish phase. By using this model, the problem of shared inputs and dynamic intermediates among activities that characterize pig production are taken into account in an integrated framework, simultaneously with the consideration of non-zero slack, allowing us to examine aspects of production in a more comprehensive and factual manner. For the empirical results based on sample data from 2006 to 2007, it is shown that the overall technical inefficiencies obtained from DMNDEA are not obviously different from those obtained using a traditional one-stage model. However, the DMNDEA results explicitly show us that the sources of inefficiency for each farm are different. Furthermore, second-stage bootstrapping regression results reveal that the determinants of efficiency for each production phase are not the same, indicating the need to identify the influential factors for each production phase separately.     

Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis

This paper analyses the regional technical efficiency of Chinese iron and steel industry from 1996 to 2010 by a network DEA procedure, and provides the smoothed bootstrap network DEA strategy for the sensitivity analysis of the efficiency measure to sampling variation of the estimated frontier. Furthermore, the evolution and convergence characteristics of regional technical efficiency are examined by a dynamic regression model based on different regional divisions of China. The empirical results show that there exist significant geographical differences in the technical efficiency of Chinese iron and steel industry. On the one hand, the technical efficiency of the eastern area, the central area and the western area is unbalanced, with a lower efficiency in the west and a higher one in the east. On the other hand, technical efficiency of Central Bohai, Yangtze River Delta and Pearl River Delta economic zones is higher than that of the other economic zones. In addition, the technical efficiency has a significant improvement during the period of the Eleventh Five-Year Plan. Following the convergence notation in economic growth theory, this paper also gives some convergence evidence of the technical efficiency towards the efficient frontier due to the catching-up effect. Finally, this paper explores the determinants of the technical efficiency, and discusses policy implications for Chinese iron and steel industry.     

Using data envelopment analysis to measure the efficiency of non-profit organizations: A critical evaluation

This study examines the potential effects of variable set expansion and data variations upon the efficiency scores generated using the Data Envelopment Analysis (DEA) model. It was found that variable set expansion (either through disaggregation of existing variables or addition of new factors) should produce an upward trend in efficiency scores. In addition, ample opportunity exists for ‘decision-making units’ to increase their efficiency scores through manipulation of reported data. In real-world applications of DEA, these problems must be resolved as much as possible (e.g. increased audit of data) in order to improve DEA's practical usefulness and reliability.     

An application of data envelopment analysis to evaluate the efficiency level of the operational cost of Brazilian electricity distribution utilities

This paper shows efficiency indices for 60 Brazilian electricity distribution utilities. The efficiency scores are gauged by three DEA models. For both models, these quantities are evaluated under different contexts. One treats with respect to the regulator perspective. The others examine an alternative approach based on cluster analysis and restrictions on factor weights. It is worth pointing out that these developments can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental in incentive regulation schemes.     

Efficiency evaluation of China's high-tech industry with a multi-activity network data envelopment analysis approach

This paper employs a Russell multi-activity network DEA model and divides the overall innovation process into the upstream Research and Development (R&D) process and the downstream commercialization process to appraise the innovation performance of China's high-tech industries from 2009 to 2013. This model can deal with the problems of intermediates, shared inputs and slack-based measure in a unified framework, and the result can provide policy makers with process-specific information on how to improve the innovation performance of China's high-tech industries. The main findings are presented as follows. First, the overall efficiency of China's high-tech industries still remains at a low level, which has its roots mainly in commercialization inefficiencies other than R&D inefficiencies. Second, for most provinces, their R&D efficiencies do not match up with their commercialization efficiencies. Finally, the innovative activities of China's high-tech industries should be driven by the market demand -oriented for the improvement of innovation efficiency.     

Performance evaluation using data envelopment analysis in the presence of time lags

Data Envelopment Analysis (DEA) is a methodology that computes efficiency values for decision making units (DMU) in a given period by comparing the outputs with the inputs. In many applications, inputs and outputs of DMUs are monitored over time. There might be a time lag between the consumption of inputs and the production of outputs. We develop an approach that aims to capture the time lag between the outputs and the inputs in assigning the efficiency values to DMUs. We propose using weight restrictions in conjunction with the model. Our computational results on randomly generated problems demonstrate that the developed approach works well under a large variety of experimental conditions. We also apply our approach on a real data set to evaluate research institutions.     

Production frontier estimation to measure efficiency: A critical evaluation in light of data envelopment analysis

The ranking and measurement of efficiency of decision-making units by two methods—data envelopment analysis and frontier production function—may not always lead to identical results. In this framework we attempt here a critical evaluation of the frontier production function theory in terms of theoretical and empirical implications. It is shown that under certain conditions the two approaches to effciency measurement may lead to identical results.     

A two-stage double-bootstrap data envelopment analysis of efficiency differences of New Zealand secondary schools

We conduct a two-stage (DEA and regression) analysis of the efficiency of New Zealand secondary schools. Unlike previous applications of two-stage semi-parametric modelling of the school “production process”, we use Simar and Wilson’s double bootstrap procedure, which permits valid inference in the presence of unknown serial correlation in the efficiency scores. We are therefore able to draw robust conclusions about a system that has undergone extensive reforms with respect to ideas high on the educational agenda such as decentralised school management and parental choice. Most importantly, we find that school type affects school efficiency and so too does teacher quality.     

Using data envelopment analysis to measure the efficiency of not-for-profit organizations: A critical evaluation—comment

This note responds to Nunamaker (1985) who supposedly deals with deficiencies in Data Envelopment Analysis (DEA) as an approach for (1) measuring efficiencies of not-for-profit entities identified as Decision Making Units (DMUs) and (2) locating sources and amounts of inefficiencies in each of the inputs used and in each of the outputs produced by each DMU. Corrections and comments are offered with references supplied for interested readers who wish to examine more detailed treatments of the topics covered.     

Using data envelopment analysis to evaluate efficiency in the economic performance of Chinese cities

This paper studies the use of DEA (data envelopment analysis) as a tool for possible use in evaluating and planning the economic performance of China's cities (28 in all) which play a critical role in the government's program of economic development. DEA promises advantages which include the absence of any need for the assignment of weights on an a priori basis (to reflect the supposed relative importance of various outputs or inputs) when evaluating technical efficiency. It is also unnecessary to explicitly specify underlying functions that are intended to prescribe the analytical form of the relations between inputs and outputs. Finally, as is illustrated in the paper, DEA can be used to identify sources, and estimate amounts of inefficiencies in each city's performance as well as to identify returns-to-scale possibilities in ways that seem well-suited to the mixture of centralized and decentralized planning and performance that China is currently trying to use.     

Changes in hospital efficiency and size: An integrated propensity score matching with data envelopment analysis

Turkey has made huge investments in city hospitals. The distinguishing feature of these hospitals is that they are physically large. Although many studies have investigated the efficiency of public hospitals, there are a few studies on the effect of hospital size on efficiency. This study examines the effect of hospital size on changes in public hospital efficiencies. The analysis is made up of three steps. First, using a bootstrap data envelopment analysis (DEA), the pure efficiency scores of each hospital were calculated. Second, propensity score matching (PSM) was used to ensure that any differences could be attributed to a particular class of hospital size, and not be due to differences in sample characteristics between the intervention and control groups. To highlight a potential time difference between small and large hospitals, the efficiencies of hospitals were examined from 2014 to 2017. Third, the Mann–Whitney U test was used to conduct a robustness check of the DEA and PSM results. Fourth, logistic regression was used on balanced data to examine the determinants of the efficiency of public hospitals. There are remarkable differences in the results obtained before and after matching the groups based on the bed-occupancy rate. Additionally, urban location is a key predictor of efficient and inefficient hospitals. This study also highlights that integrating DEA and PSM is a useful strategy in accurately identifying predictors of efficiencies of hospitals by creating balanced groups. Health policymakers should consider the efficiency advantages of high workload and service burden in the planning of public hospitals.     

Decomposition of technical efficiency under fixed proportion technologies: an application of data envelopment analysis

In this paper, we extend the four-component stochastic frontier model to allow for global spatial dependence via the endogenous spatial autoregressive variable. Our proposed model is more general than the model considered by (Glass et al., 2016) in the sense that we include a random effect as well as a permanent efficiency component. With the spatial autoregressive specification, our model is able to capture the asymmetric efficiency spillovers and also decompose the persistent/transient inefficiencies into direct and indirect efficiencies. Moreover, we also investigate the marginal effects of the exogenous variables on the persistent/transient efficiency. We suggest a maximum simulated likelihood method to estimate the frontier parameters of the model, and we predict the efficiencies using the simulated estimator. Monte Carlo simulations reveal that the suggested estimator performs well in finite samples. An empirical application is considered to illustrate the usefulness of our proposed model and method.

     

Eco-efficiency changes of the electricity and gas sectors across 28 European countries: A value-based data envelopment analysis productivity approach

This paper assesses the relative eco-efficiency changes in the electricity and gas sector (E&G)' production and consumption chains in 28 European countries. We propose a novel robustness assessment for the productivity index, specifically adjusted to value-based data envelopment analysis. Overall, results indicate that total factor productivity gains have been mainly driven by the catch-up effect across all chains of the E&G sector. When a more demanding perspective concerning negative environmental externalities is adopted, we find that the number of European countries that achieved productivity gains across all chains decreases. Besides, results depict the existence of lower productivity gains for the direct production chain when compared with the direct and indirect supply chains of the E&G sector. Germany, Luxembourg, and Belgium were consistently viewed as innovators across all chains, according to the environmental perspective. Several Eastern Europe countries usually viewed as policy laggards that resisted adopting the ambitious European decarbonization targets, showed total factor productivity gains in the supply chain of the E&G sector under a more environmental demanding perspective. Czechia was the only country with productivity losses across all chains, due to increasing coal-fired electricity generation in the time horizon assessed. The current partial return to coal as a source of electricity, due to the geopolitical tensions between Russia and Europe, brings additional challenges to the enhancement of the eco-efficiency of the European E&G sector.