A reasonable benchmarking frontier using DEA : an incentive scheme to improve efficiency in public hospitals

There exists research relating management concepts with productivity measurement methods that offers useful solutions for improving management control in the public sector. Within this sphere, we connect agency theory with efficiency analysis and describe how to define an incentives scheme that can be applied in the public sector to monitor the efficiency and productivity of managers. To fulfill the main objective of this research, we propose an iterative process for determining what we define as a ‘reasonable frontier’, a concept that provides the foundation required to establish the incentive scheme for the managers. Our ‘reasonable frontier’ has the following properties: i) it detects the presence of outliers, ii) it proposes a procedure to establish the influence introduced by extreme observations, and iii) it sorts out the problem of data masking. The proposed method is applied to a sample of hospitals taken from the public network of the Spanish health service. The results obtained confirm the applicability of the proposal made. Summing up, we define and apply a useful method, combining aspects of agency theory and efficiency analysis, which is of interest to those public authorities trying to design effective incentive schemes which influence the decision making of the public managers

A reasonable benchmarking frontier using DEA : an incentive scheme to improve efficiency in public hospitals

There exists research relating management concepts with productivity measurement methods that offers useful solutions for improving management control in the public sector. Within this sphere, we connect agency theory with efficiency analysis and describe how to define an incentives scheme that can be applied in the public sector to monitor the efficiency and productivity of managers. To fulfill the main objective of this research, we propose an iterative process for determining what we define as a ‘reasonable frontier’, a concept that provides the foundation required to establish the incentive scheme for the managers. Our ‘reasonable frontier’ has the following properties: i) it detects the presence of outliers, ii) it proposes a procedure to establish the influence introduced by extreme observations, and iii) it sorts out the problem of data masking. The proposed method is applied to a sample of hospitals taken from the public network of the Spanish health service. The results obtained confirm the applicability of the proposal made. Summing up, we define and apply a useful method, combining aspects of agency theory and efficiency analysis, which is of interest to those public authorities trying to design effective incentive schemes which influence the decision making of the public managers.

A nonparametric analysis of the Greek renewable energy sector

This paper applies a bootstrapped Data Envelopment Analysis (DEA) formulation aiming to evaluate the financial performance of the firms operating in the Greek renewable energy sector. With the use of financial ratios in a DEA setting, efficiency ratios are constructed in order to analyse firms’ financial performance. The results reveal that firms’ performances are positively influenced by the high levels of return on assets and equity and by lower levels of debt to equity. In addition it appears that there are not significant differences of firms’ efficiency levels indicating high competitiveness between firms. Finally, firms producing wind energy appear to perform better than firms producing hydropower energy. It emerges that the majority of firms are operating in the wind and hydropower energy production making the Greek market of solar energy production being an emerging segment of the Greek renewable energy sector.Renewable energy market; Data Envelopment Analysis; Financial ratios; Greece

Determinants of health sector efficiency: evidence from a two-step analysis on 30 OECD countries

This study aims to assess the efficiency of expenditure on health in 30 OECD countries over the period 2005-2015 by regressing Data Envelopment Analysis (DEA) output efficiency scores on discretionary and non-discretionary variables, with a two-stage DEA/Tobit and bootstrap procedure. We show that health inefficiency in OECD countries is related to per capita GDP, vaccine coverage and tobacco consumption, also controlling for geographical and institutional variables (i.e., bureaucratic red tape and weather temperature)

Performance and Congestion Analysis of the Portuguese Hospital Services

The health care services have been characterised by a growing demand by the citizens leading to the need of more and more resources. Population aging, new pathologies and drugs as well as new treatments are some of the major factors for this. However, in hospitals, for example, consumption of a large number of inputs frequently has not corresponded to the production of the same or more proportion of outputs. Sometimes, the outputs even decline with the increase of inputs due to the influence of the congestion effect on efficiency. The heavy burden of the health sector on the state budget brings about the interest of research over its efficiency. This paper aims to assess the performance of the Portuguese hospitals and particularly the contribution of the congestion effect. We use the non-parametric technique of data envelopment analysis (DEA) for this purpose and a double-bootstrap procedure to take into account the influence of operational environment on efficiency. Afterwards, by comparing three different approaches we determine the importance of congestion in efficiency measurement and discuss its computation methodologically. The results suggest significant levels of inefficiency in 68 major Portuguese hospitals for the year 2005 and more than half of them were found to be congested.Hospitals; congestion; efficiency; DEA; Portugal

Comparison of Healthcare Performance and its Determinants in European Countries Using the TOPSIS Approach

The paper provides a comparison of European countries with respect to their healthcare. Two dimensions were taken into account. The first set of criteria contains the resources provided by the healthcare sector to the inhabitants, such as the number of practising physicians and the number of hospital beds per one hundred thousand inhabitants, and the resources provided to the sector by financing entities, such as health care expenditures. The second dimension reflects the output sphere which results from the quality of healthcare system performance; this set of criteria includes life expectancy, the share of people with good or very good perceived health, and the infant mortality rate. Countries were ranked using the TOPSIS method. Results reveal that resources are crucial to the assessment

A new perspective on the competitiveness of nations

The capability of firms to survive and to have a competitive advantage in global markets depends on, amongst other things, the efficiency of public institutions, the excellence of educational, health and communications infrastructures, as well as on the political and economic stability of their home country. The measurement of competitiveness and strategy development is thus an important issue for policy-makers. Despite many attempts to provide objectivity in the development of measures of national competitiveness, there are inherently subjective judgments that involve, for example, how data sets are aggregated and importance weights are applied. Generally, either equal weighting is assumed in calculating a final index, or subjective weights are specified. The same problem also occurs in the subjective assignment of countries to different clusters. Developed as such, the value of these type indices may be questioned by users. The aim of this paper is to explore methodological transparency as a viable solution to problems created by existing aggregated indices. For this purpose, a methodology composed of three steps is proposed. To start, a hierarchical clustering analysis is used to assign countries to appropriate clusters. In current methods, country clustering is generally based on GDP. However, we suggest that GDP alone is insufficient for purposes of country clustering. In the proposed methodology, 178 criteria are used for this purpose. Next, relationships between the criteria and classification of the countries are determined using artificial neural networks (ANNs). ANN provides an objective method for determining the attribute/criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, in our third step, the countries of interest are ranked based on weights generated in the previous step. Beyond the ranking of countries, the proposed methodology can also be used to identify those attributes that a given country should focus on in order to improve its position relative to other countries, i.e., to transition from its current cluster to the next higher one

Sustainable Assessment in Supply Chain and Infrastructure Management

In the competitive business environment or public domain, the sustainability assessment in supply chain and infrastructure management are important for any organization. Organizations are currently striving to improve their sustainable strategies through preparedness, response, and recovery because of increasing competitiveness, community, and regulatory pressure. Thus, it is necessary to develop a meaningful and more focused understanding of sustainability in supply chain management and infrastructure management practices. In the context of a supply chain, sustainability implies that companies identify, assess, and manage impacts and risks in all the echelons of the supply chain, considering downstream and upstream activities. Similarly, the sustainable infrastructure management indicates the ability of infrastructure to meet the requirements of the present without sacrificing the ability of future generations to address their needs. The complexities regarding sustainable supply chain and infrastructure management have driven managers and professionals to seek different solutions. This Special Issue aims to provide readers with the most recent research results on the aforementioned subjects. In addition, it offers some solutions and also raises some questions for further research and development toward sustainable supply chain and infrastructure management

How 'one-size-fits-all' public works contract does it better? An assessment of infrastructure provision in Italy

Public infrastructure procurement is crucial as a prerequisite for public and private investments and for economic and social capital growth. However, low performance in execution severely hinders infrastructure provision and benefits delivery. One of the most sensitive phases in public infrastructure procurement is the design because of the strategic relationship that it potentially creates between procurers and contractors in the execution stage, affecting the costs and the duration of the contract. In this paper, using recent developments in non-parametric frontiers and propensity score matching, we evaluate the performance in the execution of public works in Italy. The analysis provides robust evidence of significant improvement of performance where procurers opt for a design and build contracts, which lead to lower transaction costs, allowing contractors to better accommodate the project in the execution. Our findings bear considerable policy implications