Evaluating e-Government services from a citizens' prespective: A reference process model

Evaluating and optimizing e-government services is imperative for governments especially due to the capacity of e-services to transform public administrations and assist the interactions of governments with citizens, businesses and other government agencies. Existing widely applied evaluation approaches neglect to incorporate citizens’ satisfaction measures. Several citizen satisfaction models and indicators have been suggested in academia; however a reference process model that can assist practitioners to apply these performance measures is missing. In this paper we draw upon the evaluation approach proposed by the EU funded project CEES and propose a reference process model that captures re-usable practices for e-government evaluation from a citizens’ perspective. The novelty of the proposed approach is that using DEA for evaluating the e-services the assessment results in suggestions for strategic improvement of the e-services.EU FP7 Marie Curie People Project “CEES - Citizen oriented Evaluation of E-Government Systems” (reference IAPP-2008-230658

Nonparametric approach to evaluation of economic and social development in the EU28 member states by DEA efficiency

Data envelopment analysis (DEA) methodology is used in this study for a comparison of the dynamic efficiency of European countries over the last decade. Moreover, efficiency analysis is used to determine where resources are distributed efficiently and/or were used efficiently/inefficiently under factors of competitiveness extracted from factor analysis. DEA measures numerical grades of the efficiency of economic processes within evaluated countries and, therefore, it becomes a suitable tool for setting an efficient/inefficient position of each country. Most importantly, the DEA technique is applied to all (28) European Union (EU) countries to evaluate their technical and technological efficiency within the selected factors of competitiveness based on country competitiveness index in the 2000-2017 reference period. The main aim of the paper is to measure efficiency changes over the reference period and to analyze the level of productivity in individual countries based on the Malmquist productivity index (MPI). Empirical results confirm significant disparities among European countries and selected periods 2000-2007, 2008-2011, and 2012-2017. Finally, the study offers a comprehensive comparison and discussion of results obtained by MPI that indicate the EU countries in which policy-making authorities should aim to stimulate national development and provide more quality of life to the EU citizens.Web of Science122art. no. 7

Monitoring bank performance in the presence of risk

This paper proposes a managerial control tool that integrates risk in efficiency measures. Building on existing efficiency specifications, our proposal reflects the real banking technology and accurately models the relationship between desirable and undesirable outputs. Specifically, the undesirable output is defined as nonperforming loans to capture credit risk, and is linked only to the relevant dimension of the output set. We empirically illustrate how our efficiency measure functions for managerial control purposes. The application considers a unique dataset of Costa Rican banks during 1998–2012. Results’ implications are mostly discussed at bank-level, and their interpretations are enhanced by using accounting ratios. We also show the usefulness of our tool for corporate governance by examining performance changes around executive turnover. Our findings confirm that appointing CEOs from outside the bank is associated with significantly higher performance ex post executive turnover, thus suggesting the potential benefits of new organisational practices.Peer ReviewedPostprint (author’s final draft

Sustainable R&D portfolio assessment.

Research and development portfolio management is traditionally technologically and financially dominated, with little or no attention to the sustainable focus, which represents the triple bottom line: not only financial (and technical) issues but also human and environmental values. This is mainly due to the lack of quantified and reliable data on the human aspects of product/service development: usability, ecology, ethics, product experience, perceived quality etc. Even if these data are available, then consistent decision support tools are not ready available. Based on the findings from an industry review, we developed a DEA model that permits to support strategic R&D portfolio management. We underscore the usability of this approach with real life examples from two different industries: consumables and materials manufacturing (polymers).R&D portfolio management; Data envelopment analysis; Sustainable R&D;

A Data Envelopment Analysis Approach to the Assessment of Natural Parks’ Economic Efficiency and Sustainability. The Case of Italian National Parks

Wilderness protection is a growing necessity for modern societies, and this is particularly true for areas where population density is extremely high, as for example Europe. Conservation, however, implies very high opportunity costs. It is thus crucial to create incentives to efficient management practices, to promote benchmarking and to improve conservation management. In the present paper we propose a methodology based on Data Envelopment Analysis, DEA, a non parametric benchmarking technique specifically developed to assess the relative efficiency of decision-making units. In particular, the objective of the discussed methodology is to assess the relative efficiency of the management units of the protected area and to indicate how it could be improved, by providing a set of guidelines. The main advantage of this methodology is that it allows to assess the efficiency of natural parks’ management not only internally (comparing the performance of the park to itself in time) but also by external benchmarking, thus providing new and different perspectives on potential improvements. Although the proposed methodology is fairly general, we have applied it to the context of Italian National Parks in order to produce a representative case study. Specifically, the choice of adequate cost and benefit indicators is a very important and delicate phase of any benchmark analysis. For this purpose, a questionnaire was used to investigate the opinions of Italian National Parks managers and stakeholders and to define the relevant indicators for the analysis. Finally, relevant policy implications for the case study are given.Data envelopment analysis, Natural park management

Using Data Envelopment Analysis to Assess the Relative Efficiency of Different Climate Policy Portfolios

Within the political, scientific and economic debate on climate change, the process of evaluating climate policies ex-ante, during and/or ex-post their lifetime, is receiving increasing attention from international institutions and organisations. The task becomes particularly challenging when the aim is to evaluate strategies or policies from a sustainability perspective. The three pillars of sustainability should then be jointly considered in the evaluation process, thus enabling a comparison of the social, the environmental and the economic dimensions of the policy’s impact. This is commonly done in a qualitative manner and is often based on subjective procedures. The present paper discusses a data-based, quantitative methodology to assess the relative performances of different climate policies, when long term economic, social and environmental impacts of the policy are considered. The methodology computes competitive advantages as well as relative efficiencies of climate policies and is here presented through an application to a sample of eleven global climate policies, considered as plausible for the near future. The proposed procedure is based on Data Envelopment Analysis (DEA), a technique commonly employed in evaluating the relative efficiency of a set of decision making units. We consider here two possible applications of DEA. In the first, DEA is applied coupled with Cost-Benefit Analysis (CBA) in order to evaluate the comparative advantages of policies when accounting for social and environmental impacts, as well as net economic benefits. In the second, DEA is applied to compute a relative efficiency score, which accounts for environmental and social benefits and costs interpreted as outputs and inputs. Although the choice of the model used to simulate future economic and environmental implications of each policy (in the present paper we use the FEEM RICE model), as well as the choice of indicators for costs and benefits, represent both arbitrary decisions, the methodology presented is shown to represent a practical tool to be flexibly adopted by decision makers in the phase of policy design.Climate, Policy, Valuation, Data envelopment analysis, Sustainability

Reference Models and Incentive Regulation of Electricity Distribution Networks: An Evaluation of Sweden’s Network Performance Assessment Model (NPAM)

The world-wide electricity sector reforms have led to a search for alternative and innovative approaches to regulation to promote efficiency improvement in the natural monopoly electricity networks. A number of countries have used incentive regulation models based on efficiency benchmarking of the electricity network utilities. While most regulators have opted adopted parametric and non-parametric frontier-based methods of benchmarking some have used engineering designed ‘reference firm’ or ‘norm’ models for the purpose. This paper examines the incentive properties and other related aspects of the norm model NPAM used in regulation of distribution networks in Sweden and compares these with those of frontier-based benchmarking methods. We identify a number of important differences between the two approaches to regulation benchmarking that are not readily apparent and discuss their ramifications for the regulatory objectives and process

Regulatory and Environmental Effects on Public Transit Efficiency. A Mixed DEA-SFA Approach

The aim of this paper is to account for the impact of statistical noise and exogenous regulatory and environmental factors on the efficiency of public transit systems in a DEA-based framework. To this end, we implement a three-stage DEA-SFA mixed approach based on Fried et al. (2002) using a 1993-1999 panel of 42 Italian public transit companies. This allows us to decompose input-specific DEA inefficiency measures into three components: exogenous effects, pure managerial inefficiency, and statistical noise. First, the initial evaluation of producer performance is carried out using conventional variable returns to scale DEA (Banker et al., 1984). Second, a SFA approach (Battese and Coelli, 1992) is used to regress single input slacks on subsidies regulation (cost-plus versus fixed-price contracts) and a set of environmental variables including network speed and user density. Finally, third stage re-runs DEA on inputs purged of both exogenous effects and statistical noise. Results are such that adjusting for the type of regulatory scheme, environmental conditions, and statistical noise increases average efficiency in the industry and reduces dispersion among firms. Furthermore, the implementation of fixed-price subsidies is found to enhance efficiency in the usage of “drivers” and “materials and services” inputs. Such a result sheds some light on the determinants of input-specific efficiency differentials in the industry, improving the existing evidence on mean overall cost efficiency (e.g. Gagnepain e Ivaldi, 2002; Piacenza, 2006). As a policy implication, it is confirmed the relevance of regula tion aimed at replacing cost-plus subsidization mechanisms with high-powered incentive contracts as well as improving operating conditions of public transport networks.Public transit systems, Regulation, Environmental effects, Statistical noise, Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA)

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework