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

The technical efficiency of Public Libraries in the Czech Republic

The purpose of this article is to define and evaluate the development of the aggregated technical efficiency of public libraries in the Czech Republic from 1993 to 2014. To simulate technical efficiency, the Data Envelopment Analysis Model (The BCC model) was chosen. To evaluate the production units (the unit of the Czech Republic from 1993 to 2014 and its production is given by the sum of real homogenous units, i.e. the public libraries operating in a given area and in a given time), two input variables (the recalculated number of employees and the library collection) and two output variables (the number of registered readers and the number of loans) were analysed. Two basic models were simulated – the M1 model oriented to inputs and the M2 model oriented to outputs. Correlation between the input and output variables was researched using Pearson’s coefficient. Within the range of the M1 and M2 basic models, partial models were simulated. All of the basic and partial models identically showed eight efficient periods of public libraries in the Czech Republic (1995, 1997, 1999–2000, 2002–2005). Public libraries were, according to the chosen variables, inefficient in the remaining 16 observed years

Assessing the Efficiency of Mass Transit Systems in the United States

Frustrated with increased parking problems, unstable gasoline prices, and stifling traffic congestion, a growing number of metropolitan city dwellers consider utilizing the mass transit system. Reflecting this sentiment, a ridership of the mass transit system across the United States has been on the rise for the past several years. A growing demand for the mass transit system, however, necessitates the expansion of service offerings, the improvement of basic infrastructure/routes, and the additional employment of mass transit workers, including drivers and maintenance crews. Such a need requires the optimal allocation of financial and human resources to the mass transit system in times of shrinking budgets and government downsizing. Thus, the public transit authority is faced with the dilemma of “doing more with less.” That is to say, the public transit authority needs to develop a “lean” strategy which can maximize transit services with the minimum expenses. To help the public transit authority develop such a lean strategy, this report identifies the best-in-class practices in the U.S. transit service sector and proposes transit policy guidelines that can best exploit lean principles built upon best-in-class practices

Assessing The Impact Of Economies Of Scale And Uncontrollable Factors On The Performance Of U.S. Cities.

Despite the increased interest among local governments in collecting data on performance measurement, empirical evidence is still limited regarding the extent to which these data are utilized to assess the impact on efficiency of economies of scale and uncontrollable factors. Data envelopment analysis (DEA) is a linear programming method designed to estimate the relative efficiency of decision-making units. In addition to assessing relative efficiency, DEA can estimate scale efficiency and incorporate the impact of uncontrollable factors. Using data from the International City/County Association (ICMA), this study utilized DEA to evaluate the impact of economies of scale and uncontrollable factors on the relative efficiency of municipal service delivery in the United States. The findings from this doctoral dissertation show that uncontrollable variables such as population density, unemployment, and household income suppress the relative efficiency of local governments. Moreover, the findings imply that the prevalence of economies of scale in city governments depends on the types of services these governments provide

Insights into the efficiencies of on-shore wind turbines: a data-centric analysis

Literature on renewable energy alternative of wind turbines does not include a multidimensional benchmarking studythat can help investment decisions as well as design processes. This paper presents a data-centric analysis of commercial on-shore wind turbines and provides actionable insights through analytical benchmarking through Data Envelopment Analysis (DEA), visual data analysis, and statistical hypothesis testing. The paper also introduces a novel visualization approach for the understanding and the interpretation of reference sets, the set of efficient wind turbines that should be taken as benchmark by inefficient ones

Creating Composite Indicators with DEA and Robustness Analysis: the case of the Technology Achievement Index

Composite indicators are regularly used for benchmarking countries’ performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final results from the preliminary normalization of sub-indicators, and, more cogently, from the subjective nature of the weights used for aggregating. Still, subjective decisions remain, and such modelling uncertainty propagates onto countries’ composite indicator values and relative rankings. Uncertainty and sensitivity analysis are therefore needed to assess robustness of final results and to analyze how much each individual source of uncertainty contributes to the output variance. The current paper reports on these issues, using the Technology Achievement Index as an illustration.factor is more important in explaining the observed progress.composite indicators, aggregation, weighting, Internal Market

Creating composite indicators with DEA and robustness analysis: The case of the technology achievement index.

Composite indicators are regularly used for benchmarking countries’ performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final results from the preliminary normalization of sub-indicators, and, more cogently, from the subjective nature of the weights used for aggregating. Still, subjective decisions remain, and such modelling uncertainty propagates onto countries’ composite indicator values and relative rankings. Uncertainty and sensitivity analysis are therefore needed to assess robustness of final results and to analyze how much each individual source of uncertainty contributes to the output variance. The current paper reports on these issues, using the Technology Achievement Index as an illustration.Indexes; Indicators; Robustness; Technology;