Estimating outputs using an inverse non-radial model with non-discretionary measures: An application for restaurants

Few inverse data envelopment analysis (DEA) models have incorporated non-discretionary measures based on radial efficiency values. However, the efficiency may be miscounted in radial approaches when some non-zero slacks appear. Furthermore, there is scant research on inverse DEA to estimate performance measures in the restaurant industry. Accordingly, this research proposes models based on non-radial DEA to analyze the efficiency and output changes of some Iranian restaurants while also presenting non-discretionary measures. Actually, in the company of non-discretionary factors, a non-radial DEA approach and its inverse problem are introduced to assess the performance and estimate the outputs for the modifications of inputs, respectively, while the inefficiency levels are maintained (and when they are preserved or decreased). The inefficiency of each discretionary input and output is specified using the presented non-radial DEA approach, and output targets are determined through inverse non-radial DEA with non-discretionary inputs. The results show containing non-discretionary data leads to more rational determinations through non-radial DEA-founded problems. This research presents analytic insights into the resources of inefficiency and output targets of entities with non-discretionary data, such as restaurants.

Using slacks-based model to solve inverse DEA with integer intervals for input estimation

This paper deals with an inverse data envelopment analysis (DEA) based on the non-radial slacks-based model in the presence of uncertainty employing both integer and continuous interval data. To this matter, suitable technology and formulation for the DEA are proposed using arithmetic and partial orders for interval numbers. The inverse DEA is discussed from the following question: if the output of DMUo increases from Y-o to /beta(o), such the new DMU is given by (alpha(o)& lowast;, /3) belongs to the technology, and its inefficiency score is not less than t-percent, how much should the inputs of the DMU increase? A new model of inverse DEA is offered to respond to the previous question, whose interval Pareto solutions are characterized using the Pareto solution of a related multiple-objective nonlinear programming (MONLP). Necessary and sufficient conditions for input estimation are proposed when output is increased. A functional example is presented on data to illustrate the new model and methodology, with continuous and integer interval variables

Eco‑efficiency assessment under natural and managerial disposability : an empirical application for Chilean water companies

Getting a good understanding regarding the economic and environmental performance of water utilities is of great importance to achieve the goal of an efcient and sustainable industry. In this study, we apply the range adjusted measure (RAM) data envelopment analysis (DEA) model to evaluate the integrated (production and environmental) efciency of several water utilities located in Chile. Integrated efciency is evaluated using the concepts of natural and managerial disposability. This approach further allows us to quantify the contribution of each input and undesirable product on efciency scores. The results highlighted that the Chilean water industry showed high levels of production and environmental efciency over time. Under natural disposability, water utilities could control production costs to reduce water leakage and unplanned water supply interruptions by 3.3% on average. Under managerial disposability, water utilities could further cut down undesirable outputs by 1.4% on average by adopting best managerial practices. On average, potential savings in operating costs, employment, water leakage, and unplanned water supply interruptions were higher for concessionary utilities as they showed slightly lower efciency scores than full private utilities

Circular economy in plastic waste - Analysis of resource and energy productivity

The massive increase in plastic waste, gas emissions as well as the overexploitation of natural resources have a negative influence on the ecosystem. The European Union, as a pioneer in the circular economy, is confronting this problem by implementing strategies to change this trend. Decreasing the use of resources and energy in industry while being able to sustainably manage plastic waste, use renewable energy, increase jobs and contribute to economic development can accelerate the circular process. This investigation analyses the transition to a circular economy through resource and energy productivity in relation to EU countries between 2004 and 2018. The method applied is the Autoregressive Distributed Lag (ARDL) Model, with the help of the Estimator Driscool Kraay. The results obtained confirm a positive relationship between recycling and valorisation of plastic and resource productivity. However, high energy taxation, low investment in research and development, and fewer job opportunities stand out as barriers to circular development.A economia circular destaca-se nos países da União Europeia, através da implementação de medidas que pretendem alterar a degração ambiental sentida ao longo dos últimos séculos, permitindo atingir um bem estar ambiental, social e económico. Considerando este propósito, este estudo analisa a transição para uma economia circular com foco no plástico, considerando a produtividade dos recursos e energética como soluções ambientalmente sustentáveis. O sucesso na implementação da produtividade nestes setores, poderão nutrir benefícios através de uma melhor gestão dos resíduos, menores níveis de poluição, escassez dos recursos e uma promoção do crescimento económico. Este estudo utilizada uma abordagem de dados em painel para 20 países da União Europeia, com um horizonte temporal de 15 anos, mais especificamente, de 2004 a 2018. Para esta análise foi utilizado o modelo ARDL, através do estimador Driscoll-Kray, de forma a analisar os efeitos de curto e longo prazo. Após a análise, as principais conclusões confirmam uma relação positiva entre a reciclagem e recuperação de resíduos plásticos com a produtividade dos recursos. Outros resultados de destaque, implicam uma elevada taxação no setor energético, fraco investimento em pesquisa e desenvolvimento e fracas oportunidades de emprego. Suscitando que, aumentar a produtividade revela ser um bom contributo circular, contudo a capacidade de adaptação a alternativas mais sustentáveis decorre de forma lenta. Como robustez foi efetuada a conceção de dois modelos de consumo do material e energia, de forma a validar as escolhas das variáveis em estudo. A análise destas variáveis avalia a intensidade da utilização do material e energia, consolidando a eficência da sua utilização, os resultados apresentam-se distintos dos modelos de produtividade pela diferente forma de interpretação, contudo apoiam que o aumento da produtividade beneficia a transição circular. Estes resultados revelam que as medidas de implementação de uma economia circular são viáveis e refletem os efeitos desejados, contudo, deverão ser tomadas medidas governamentais e não governamentais que incidam na aceleração da transição circular sem repercurtir efeitos indesejados ao meio envolvente

Integrating Inverse Data Envelopment Analysis and Machine Learning for Enhanced Road Transport Safety in Iran

The purpose of this research is to present a new method for considering accidents according to the environmental, traffic and geometrical conditions of the road, which considers accidents according to the interaction of the components that lead to them. In order to enter the physical characteristics, this approach divides the road into units or parts with homogeneous physical characteristics, and as a result, the decision about the safety status of the road is made for a length of road with specific characteristics instead of a single point. This approach has been carried out using the Data Envelopment Analysis (DEA) method, which, unlike regression methods, does not require obtaining the distribution function and considering hypotheses about it. This method gives scores (inefficiencies) that allow road segments to be appropriately ranked and prioritized in terms of accident proneness. In the current research, a case study was conducted on routes with a length of 144.4 kilometers, which resulted in the identification of 154 road sections with different relative risk scores, thus the accident sections were identified and prioritized with the proposed method, which in terms of the definition of entry indicators and the output based on the data coverage analysis method is considered as a new experience for the priority of road sections. Furthermore, this study focuses on the application of artificial neural networks (ANNs) in analyzing road safety. An idealized ANN model is developed using a database of various input parameters related to road segments, and the weighted index of accidents as the target variable. The results reveal the relative importance of different parameters on the weighted index, with the Ratio of curvature, Length of the segment, and Condition of the pavement identified as the most influential factors. These findings highlight the significance of road curvature, segment length, and pavement condition in determining accident severity. The study underscores the potential of ANNs for assessing road safety and informs targeted interventions to mitigate accidents

Eficiencia de los sistemas productivos de las pequeñas y medianas empresas

This research aims to evaluate the efficiency in the productive systems of goods and services of small and medium-sized enterprises (SMEs) in the Department of Bolívar-Colombia. For this purpose, the Data Enveloping Analysis (DEA) technique was used, in which the technical efficiencies of the 120 SMEs formally registered with the Cartagena Chamber of Commerce for the years 2017 to 2020 were determined. It is contrasted with other studies whose non-parametric technique was applied in similar productive sectors that, the group of small and medium-sized enterprises evaluated showed similar results in their operational processes. It is concluded that the SMEs evaluated presented a meager productive performance in their operational activities due to factors related to low financial appeasement and poor innovation management.Esta investigación tiene como objetivo evaluar la eficiencia en los sistemas productivos de bienes y servicios de las pequeñas y medianas empresas (Pymes) en el Departamento de Bolívar-Colombia. Para este propósito se utilizó la técnica de Análisis Envolvente de Datos (DEA), en la cual se determinó las eficiencias técnicas de las 120 Pymes formalmente registradas en la Cámara de Comercio de Cartagena para los años 2017 a 2020. Se contrasta con otros estudios cuya técnica no paramétrica fue aplicada en sectores productivos similares que, el grupo de pequeñas y medianas empresas evaluadas mostraron resultados análogos en sus procesos operacionales. Se concluye que las Pymes evaluadas presentaron un desempeño productivo exiguo en sus actividades operacionales debido a factores relacionados con el bajo aplacamiento financiero y deficiente gestión de la innovación

Interval and fuzzy optimization. Applications to data envelopment analysis

Enhancing concern in the efficiency assessment of a set of peer entities termed Decision Making Units (DMUs) in many fields from industry to healthcare has led to the development of efficiency assessment models and tools. Data Envelopment Analysis (DEA) is one of the most important methodologies to measure efficiency assessment through the comparison of a group of DMUs. It permits the use of multiple inputs/outputs without any functional form. It is vastly applied to production theory in Economics and benchmarking in Operations Research. In conventional DEA models, the observed inputs and outputs possess precise and realvalued data. However, in the real world, some problems consider imprecise and integer data. For example, the number of defect-free lamps, the fleet size, the number of hospital beds or the number of staff can be represented in some cases as imprecise and integer data. This thesis considers several novel approaches for measuring the efficiency assessment of DMUs where the inputs and outputs are interval and fuzzy data. First, an axiomatic derivation of the fuzzy production possibility set is presented and a fuzzy enhanced Russell graph measure is formulated using a fuzzy arithmetic approach. The proposed approach uses polygonal fuzzy sets and LU-fuzzy partial orders and provides crisp efficiency measures (and associated efficiency ranking) as well as fuzzy efficient targets. The second approach is a new integer interval DEA, with the extension of the corresponding arithmetic and LU-partial orders to integer intervals. Also, a new fuzzy integer DEA approach for efficiency assessment is presented. The proposed approach considers a hybrid scenario involving trapezoidal fuzzy integer numbers and trapezoidal fuzzy numbers. Fuzzy integer arithmetic and partial orders are introduced. Then, using appropriate axioms, a fuzzy integer DEA technology can be derived. Finally, an inverse DEA based on the non-radial slacks-based model in the presence of uncertainty, employing both integer and continuous interval data is presented