Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs

Data envelopment analysis (DEA) is a well-known non-parametric technique primarily used to estimate radial efficiency under a set of mild assumptions regarding the production possibility set and the production function. The technical efficiency measure can be complemented with a consistent radial metrics for cost, revenue and profit efficiency in DEA, but only for the setting with known input and output prices. In many real applications of performance measurement, such as the evaluation of utilities, banks and supply chain operations, the input and/or output data are often stochastic and linked to exogenous random variables. It is known from standard results in stochastic programming that rankings of stochastic functions are biased if expected values are used for key parameters. In this paper, we propose economic efficiency measures for stochastic data with known input and output prices. We transform the stochastic economic efficiency models into a deterministic equivalent non-linear form that can be simplified to a deterministic programming with quadratic constraints. An application for a cost minimizing planning problem of a state government in the US is presented to illustrate the applicability of the proposed framework

Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkData envelopment analysis (DEA) is a well-known non-parametric technique primarily used to estimate radial efficiency under a set of mild assumptions regarding the production possibility set and the production function. The technical efficiency measure can be complemented with a consistent radial metrics for cost, revenue and profit efficiency in DEA, but only for the setting with known input and output prices. In many real applications of performance measurement, such as the evaluation of utilities, banks and supply chain operations, the input and/or output data are often stochastic and linked to exogenous random variables. It is known from standard results in stochastic programming that rankings of stochastic functions are biased if expected values are used for key parameters. In this paper, we propose economic efficiency measures for stochastic data with known input and output prices. We transform the stochastic economic efficiency models into a deterministic equivalent non-linear form that can be simplified to a deterministic programming with quadratic constraints. An application for a cost minimizing planning problem of a state government in the US is presented to illustrate the applicability of the proposed framework

Celebrating Faculty Achievement 2015

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Benchmarking with network DEA in a fuzzy environment

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Benchmarking is a powerful and thriving tool to enhance the performance and profitabilities of organizations in business engineering. Though performance benchmarking has practically and theoretically developed in distinct fields such as banking, education, health and so on, supply chain benchmarking across multiple echelons that includes certain characteristics such as intermediate measure differs from other fields. In spite of incremental benchmarking activities in practice, there is the dearth of a unified and effective guideline for benchmarking in organizations. Amongst the benchmarking tools, data envelopment analysis (DEA) as a non-parametric technique has been widely used to measure the relative efficiency of firms. However, the conventional DEA models that are bearing out precise input and output data turn out to be incapable of dealing with uncertainty, particularly when the gathered data encompasses natural language expressions and human judgements. In this paper, we present an imprecise network benchmarking for the purpose of reflecting the human judgments with the fuzzy values rather than precise numbers. In doing so, we propose the fuzzy network DEA models to compute the overall system scale and technical efficiency of those organizations whose internal structure is known. A classification scheme is presented based upon their fuzzy efficiencies with the aim of classifying the organizations. We finally provide a case study of the airport and travel sector to elucidate the details of the proposed method in this study

An Integrated Approach of Fuzzy Quality Function Deployment and Fuzzy Multi-Objective Programming Tosustainable Supplier Selection and Order Allocation

The emergence of sustainability paradigm has influenced many research disciplines including supply chain management. It has drawn the attention of manufacturing companies’ CEOs to incorporate sustainability in their supply chain and manufacturing activities. Supplier selection problem, as one of the main problems in supply chain activities, is also combined with sustainable development where traditional procedures are now transformed to sustainable initiatives. Moreover, allocating optimal order quantities to sustainable suppliers has also attracted attention of many scholars and industrial practitioners, which has not been comprehensively addressed. Therefore, a practical model of supplier selection and order allocation based on the sustainability Triple Bottom Line (TBL) approach is presented in this research article. The proposed approach utilizes Fuzzy Analytical Hierarchy Process combined with Quality Function Deployment (FAHP-QFD) for reflecting buyer’s sustainability requirements into the preference weights that are then exerted by an efficient Fuzzy Assessment Method (FAM) to assess the suppliers to obtain their sustainability scores. Thereupon, these scores are utilized in a fuzzy multi-objective mix-integer non-linear programming model (MINLP) for allocating orders to suppliers based on the manufacturer’s sustainability preference. A real-world application of food industry is presented to show the practicality of the proposed approach

An Integrated Approach of Fuzzy Quality Function Deployment and Fuzzy Multi-Objective Programming Tosustainable Supplier Selection and Order Allocation

The emergence of sustainability paradigm has influenced many research disciplines including supply chain management. It has drawn the attention of manufacturing companies’ CEOs to incorporate sustainability in their supply chain and manufacturing activities. Supplier selection problem, as one of the main problems in supply chain activities, is also combined with sustainable development where traditional procedures are now transformed to sustainable initiatives. Moreover, allocating optimal order quantities to sustainable suppliers has also attracted attention of many scholars and industrial practitioners, which has not been comprehensively addressed. Therefore, a practical model of supplier selection and order allocation based on the sustainability Triple Bottom Line (TBL) approach is presented in this research article. The proposed approach utilizes Fuzzy Analytical Hierarchy Process combined with Quality Function Deployment (FAHP-QFD) for reflecting buyer’s sustainability requirements into the preference weights that are then exerted by an efficient Fuzzy Assessment Method (FAM) to assess the suppliers to obtain their sustainability scores. Thereupon, these scores are utilized in a fuzzy multi-objective mix-integer non-linear programming model (MINLP) for allocating orders to suppliers based on the manufacturer’s sustainability preference. A real-world application of food industry is presented to show the practicality of the proposed approach

Análisis de eficiencia de unidades productivas que prestan servicios al público: la opinión del cliente como output

El objetivo de la tesis es presentar un protocolo, eminentemente práctico, basado en herramientas estadísticas y sociológicas, y justificado teóricamente, que permite atender a la incipiente demanda, administrativa, social y empresarial, de evaluar la eficiencia de las unidades productivas que prestan servicios al público utilizando la opinión-satisfacción de sus usuarios, estimada con una muestra. En el primer bloque de la tesis se propone una solución a las cuestiones de a cuantos usuarios o clientes encuestar y cómo encuestarlos, cuando la población de referencia son las personas usuarias de algún servicio de un organismo o entidad pública o privada con unas características espacio-temporales específicas, lo que equivale a una población humana móvil, y se utiliza un cuestionario como herramienta para recoger la opinión del cliente con respecto al servicio del que acaban de hacer uso. El contenido presentado en el segundo bloque de la tesis tiene por objeto atender al problema de determinar la eficiencia de un conjunto homogéneo de unidades de producción que prestan un servicio (el mismo en todas las unidades) a clientes, utilizando, como outputs, la opinión de estos clientes, opinión estimada a partir de una muestra probabilística, y, como inputs, los recursos que pueden influir en esta opinión. Para resolver este problema, se determina la relación entre tamaño de muestra en cada unidad productiva y precisión en la estimación del índice de eficiencia, se da una relación de metodologías de construcción de intervalos de confianza de eficiencia y se encuentra la relación entre tamaño de muestra y región de confianza simultánea para el vector de eficiencias poblacional.Departamento de Estadística e Investigación Operativ