A reassessment of the human development index via data envelopment analysis

Despotis, Dimitris K.

doi:10.1057/palgrave.jors.2601927

Cited by 287 publications

(136 citation statements)

References 17 publications

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“…Since the first DEA-based CI model proposed by Melyn and Moesen (1991), various indexes have been developed by using the DEA technique. The environmental performance index [Färe et al, 2004], the human development index [Despotis, 2005], the macroeconomic performance index [Ramanathan, 2006], the sustainable energy index [Zhou et al, 2007], the internal market index [Cherchye et al, 2007], the technology achievement index [Cherchye et al, 2008], and the road safety performance index [Hermans, 2009], are examples among others. Furthermore, as a valuable extension of the basic DEA-based CI model, Shen et al (2011; proposed a generalized multiple layer DEA model (MLDEA) and a MLDEA-based CI model, which took the layered hierarchy of indicators into account.…”

Section: Methodsmentioning

confidence: 99%

Investigating Individual Driver Performance: Applying DEA on Simulator Data

Babaee

Shen

Hermans

et al. 2014

Advances in Intelligent Systems and Computing

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The main purpose of the present study is to investigate individual driver's behavior by using the data from a driving simulator, in order to distinguish the best drivers and identify the problematic behavior of 'underperforming' drivers. To this end, 129 participants with different age and gender were enrolled to take part in a particular simulator scenario (i.e., curve taking) and their speed, acceleration and lateral position, the three most important driving performance indicators based on literature review, were monitored at various points (before, during and after the curve) while driving a STISIM simulator. As a widely accepted tool for performance monitoring, benchmarking and policy analysis, the concept of composite indicators (CIs), i.e., combining single indicators into one index score, was employed, and the technique of data envelopment analysis -an optimization model for measuring the relative performance of a set of decision making units, or drivers in this studywas used for the index construction. Based on the results from the model, all drivers were ranked, and valuable insight were gained by comparing the relative performance of each driver. Finally, the sensitivity of the results was examined.

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Section: Methodsmentioning

confidence: 99%

Investigating Individual Driver Performance: Applying DEA on Simulator Data

Babaee

Shen

Hermans

et al. 2014

Advances in Intelligent Systems and Computing

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“…The efficiency of a unit is defined as the weighted sum of its outputs divided by a weighted sum of its inputs. As Despotis (2005) [40] underlines, the weights for inputs and outputs are estimated by a linear programming so as to maximize the relative efficiency of each unit. Farrell (1957) [41] introduced the concept of "best practice frontier", which delineates the technological limits of what a country can achieve with a given level of resources.…”

Section: Dea Studies In the Air Transportmentioning

confidence: 99%

Measuring and Explaining Airport Efficiency and Sustainability: Evidence from Italy

2018

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Abstract:From an environmental point of view, it is widely recognized in economic literature that an efficient management of regional airports produces positive effects both for congestion reduction in the larger airports and for better use of existing infrastructures. Regional airports generally suffer from economic vulnerabilities because of scarcity of traffic volume; besides, their small catchment areas often determine low cash flow levels. As a result, significant problems of economic sustainability arise. In this context, airport infrastructure providers have the incentive to hide failures in their strategic decisions, justifying the low share of cost recovery through market characteristics. By means of the DEA (Data Envelopment Analysis) method this paper analyses overall technical, pure technical, and scale efficiency of 34 Italian airports in the period 2006-2016 in order to investigate how a number of factors impact on the efficiency and economic sustainability of regional airports. Our findings reveal that airport size, presence of low-cost carriers and cargo traffic have a significant influence on the technical and scale efficiency of Italian airports. In other words, air transport privatization and deregulation can positively affect regional airport efficiency and sustainability. This is to say that the market mechanism is a useful tool in achieving regional airport sustainability even if the empirical analysis of the effects of privatization and deregulation is recommended for evaluating such political programs.

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“…the CI values are independent of the units in which the constituent sub-indicator values are measured [4]. The DEA was already applied in the field of CI providing alternative weighting systems ( [11], [8], [3], [4], [22]). It was reported that the use of DEA overcomes some key limitations, the undesirable dependence of final results from the preliminary normalization of sub-indicators, and from subjectivity in weighting [4].…”

Section: Composite Indicatorsmentioning

confidence: 99%

“…Two types of sub-indicator share restrictions were imposed: a proportional sub-indicator share restrictions (8) and restrictions pertaining to category shares (9). When applying the min-max normalization and the general normalization (7), it is possible to set only the upper bound for each proportional sub-indicator share (8). This upper bound was set to 50% higher than the weights determined by the government decree, .…”

Section: The Benefit-of-the-doubt Approach and Simple Linear Optimizamentioning

confidence: 99%

Data-driven weights and restrictions in the construction of composite indicators

Perišić

2015

Croat. Oper. Res. Rev.

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Abstract. Composite indicators are increasingly recognized as a useful tool in policy analysis and public communication. However, if poorly constructed, they can send misleading policy messages. Perhaps the most difficult aspect of constructing a composite indicator is choosing weights for the components. The categorization of Croatian territorial units for development policy is based on the value of the composite indicator called the development index. The main goal of this paper is to propose an empirical approach for weight selection. In order to generate the set of non-subjective weights, principal component analysis and linear programming methods have been applied. An application of data envelopment analysis to the field of composite indicators, known as the Benefit-of-the-Doubt approach, has been demonstrated subject to proportional subindicator share restrictions. Additionally, the Monte Carlo simulation of weights was conducted, and confidence intervals for the values of the development index were estimated. Owing to the fact that the examined weighting schemes have resulted in the different categorization of territorial units, use of unit-specific weights and incorporating uncertainty in the construction of a composite indicator looks promising for further work.

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A reassessment of the human development index via data envelopment analysis

Cited by 287 publications

References 17 publications

Investigating Individual Driver Performance: Applying DEA on Simulator Data

Investigating Individual Driver Performance: Applying DEA on Simulator Data

Measuring and Explaining Airport Efficiency and Sustainability: Evidence from Italy

Data-driven weights and restrictions in the construction of composite indicators

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