A Comprehensive Dea Approach for the Resource Allocation Problem based on Scale Economies Classification

Abstract

This paper is concerned with the resource allocation problem based on data envelopment analysis (DEA) which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers: central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs' scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.Key words Common weights analysis (CWA), date envelopment analysis (DEA), decision making unit (DMU), efficiency score, inverse DEA model, multiple-objective linear programming (MOLP), resource allocation problem, returns to scale (RTS).

Evaluation of Regional Efficiency Disparities by Efficient Frontier Analysis

“…A more differentiated funding scheme for the regional infrastructure in respect to both structural and spatial factors was suggested in the paper. Li and Cui (2008) constructed an algorithm by using data envelopment analysis tools in various model forms and extensions, such as a variable return to scale, an inverse form of data envelopment analysis techniques, and an extra resource allocation algorithm, to provide recommendations for resource allocation and to propose possible alternatives for achieving an effective equality-efficient target. Halkos, Tzeremes (2013) analysed regional productivity effects on the countries' environment according to the Kyoto protocol by applying conditional data envelopment analysis and the free disposal hull method.…”

“…In the time of economic recession and the period of recovery when there is a lack of funds, effective allocation of funds among different territories and the analysis of regional disparities are among the main issues of the European Union regional policy for the programming period 2014-2020 and also for scientific research literature. Different methods for decision support of regional allocation of financial funds are evaluated; for instance, Li and Cui (2008) provided insights for resource allocation by applying an inverse form of data envelopment analysis and an extra resource allocation algorithm, Castells and Sole-Olle (2005) analysed the efficiency-oriented distribution of public investments among regions, which revealed the elasticity of infrastructure investments into regions' income according to government insights.…”

Employing post-DEA method in budget management of health care sectors

“…In [10], a common algorithm is provided to solve the inverse DEA problem. In [11], a comprehensive resource allocation framework is built. In [12], resource allocation model based on DEA and game theory are combined together to design the water resource allocation mechanism.…”

“…In [13], an improved inverse DEA model allowing the efficiency score being changed is put up with. Besides, post-DEA models is assumed not only to consider models in DEA field, but also to include models of optimization [11], stochastic regression [6] and game theory [12], etc.…”

Resource allocation and target setting based on virtual profit improvement

“…Xiaoya and Jinchuan [32] suggested a framework for resource allocation combining the concept of return to scale, inverse DEA and common weights. Wu et al [31] presented an approach for resource allocation considering environmental factors i.e., undesirable inputs and outputs.…”