Sustainability-oriented management of retail stores through the combination of life cycle assessment and dynamic data envelopment analysis

A sound management of retail stores is a crucial aspect in the path towards a sustainable commercial sector, with a lack of research studies in the field of joint efficiency and sustainability assessment within this sector. In this sense, this work delves into the role of operational efficiency in the sustainability-oriented management of retail stores through the case study of 30 groceries in Spain over the period 2015-2017. With this purpose, and given the current knowledge gap in period-oriented sustainability benchmarking for management plans, for the first time a five-step methodological framework based on the combination of Life Cycle Assessment (LCA) and dynamic Data Envelopment Analysis (DEA) was proposed and applied to a case study within the service sector. The overall- and term-efficiency scores calculated through this method led to the general conclusion of a relatively good performance of the set of grocery stores over the evaluated period, which is associated with the centralised management strategy followed by the retail company. Furthermore, operational, socio-economic and environmental benchmarks were calculated as target values that could assist decision-makers at the retail company level in setting the path for a sustainable operation of the company's stores. Overall, the proposed period-oriented LCA + DEA method proved to be a feasible and valuable tool for sustainability management of retail stores, being preferred over the static (i.e., single term) alternative provided that time-series data are available at the company level.publishe

Performance Measurement in the Australian Water Supply Industry

Various government-owned businesses provide water supply services to Australian residents. With the advent of recent competition and regulatory reforms in infrastructure industries in Australia, more and more of these businesses are now facing new types of incentive-based regulatory regimes. This has led to a desire for more information on the performance of these businesses, both relative to each other and over time. In this study we use panel data on the 18 largest Australian water services businesses, observed over an eight-year period from 1995/6 to 2002/3, to measure the relative efficiency and productivity growth of these businesses. Data envelopment analysis (DEA) methods are used to obtain estimates of the multi-input, multi-output production technology. The potential use of these performance measures in price-cap regulation is discussed, where the effects of variable selection and data quality upon empirical results is emphasised.

Combined use of Data Envelopment Analysis and Life Cycle Assessment for operational and environmental benchmarking in the service sector: a case study of grocery stores

Ensuring sustainable production patterns doing more and better with less is a key sustainable development goal. In this sense, the joint use of Life Cycle Assessment and Data Envelopment Analysis (i.e., the LCA+DEA methodology) arises as a quantitative tool for the eco-efficiency assessment of multiple similar entities. To date, the LCA+DEA methodology has been widely applied to case studies within the primary and secondary sectors. However, the applicability of this combined methodology to case studies within the tertiary (service) sector is still unexplored, which constitutes a current knowledge gap in this field. This work contributes to filling this gap by benchmarking the operational and environmental performance of a sample of 30 groceries located in Spain. All the evaluated groceries were found to involve relative efficiency scores above 0.60, with one third of the groceries deemed fully efficient. Average reductions of 3-26% in the consumption of operational inputs were calculated, leading to average reductions of 9% in the carbon footprint and 10% in the energy footprint. Furthermore, economic savings of up to 3% of the annual turnover were estimated. These results were further enriched through the application of a super-efficiency DEA model for a refined identification of the best-performers, as well as through the novel use of a specific model for the gradual operational and environmental benchmarking of the sample. Overall, a high applicability of the LCA+DEA methodology for eco-efficiency assessment within the service sector is concluded, facilitating the identification and quantification of sustainable operational patterns.publishe

Valuing Environmental Factors in Cost-Benefit Analysis Using Data Envelopment Analysis

Environmental cost-benefit analysis (ECBA) refers to social evaluation of investment projects and policies that involve significant environmental impacts. Valuation of the environmental impacts in monetary terms forms one of the critical steps in ECBA. We propose a new approach for environmental valuation within ECBA framework that is based on data envelopment analysis (DEA) and does not demand any price estimation for environmental impacts using traditional revealed or stated preference methods. We show that DEA can be modified to the context of CBA by using absolute shadow prices instead of traditionally used relative prices. We also discuss how the approach can be used for sensitive analysis which is an important part of ECBA. We illustrate the application of the DEA approach to ECBA by means of a hypothetical numerical example where a household considers investment to a new sport utility vehicle.Cost-Benefit Analysis, Data Envelopment Analysis, Eco-Efficiency, Environmental Valuation, Environmental Performance, Performance Measurement

Supplier Selection by the Pair of Nondiscretionary Factors-Imprecise Data Envelopment Analysis Models

Discretionary models for evaluating the efficiency of suppliers assume that all criteria are discretionary, that is, controlled by the management of each supplier and varied at its discretion. These models do not assume supplier selection in the conditions that some factors are nondiscretionary. The objective of this paper is to propose a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-IDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. A numerical example demonstrates the application of the proposed method.Full Tex

Multiperiod modelling planning and productivity and energy efficient assessment of an industrial gases facility

El creixement de la demanda energètica i el continu desenvolupament tecnològic de la societat estan sobrepassant els límits mediambientals del nostre planeta. Sense les mesures adequades, aquesta situació podria derivar en importants problemes mediambientals que causarien danys irreversibles al medi ambient i al benestar de la humanitat. El sector industrial és el principal consumidor energètic, amb una demanda al voltant d’un terç de la global, un aspecte que té un evident efecte negatiu amb l’impacte mediambiental. Per tant, el repte de mitigar el canvi climàtic implicarà millores en l’ús de la energia a la industria, generant grans oportunitats d’estalvi energètic i reduint el seu impacte mediambiental. En aquest sentit, es essencial obtenir informació derivada de la investigació i l’anàlisi científic que permeti desenvolupar solucions focalitzades en la reducció de costos energètics. Aquesta tesis ha tractat les necessitats particulars de la producció de gasos industrials, creant eines basades en l’optimització matemàtica que permeten una presa de decisions operatives més àgil i efectiva i detectant àrees per la millora energètica. Aquestes eines fomenten i avancen cap a una industria més eficient que permeti un futur més sostenible. Aquesta tesis té dos contribucions principals. D’una banda, s’ha desenvolupat una eina d’optimització multiperiod que permet obtenir la configuració d’operació òptima (des del punt de vista econòmic i energètic) d’un procés de producció de gasos industrials, tenint en compte totes les seves variables. Per altra banda, s’utilitza la metodologia de Data Envelopment Analisis per a comparar diferents unitats de producció de gasos industrials, identificant els focus d’ineficiència i fent recomanacions per a resoldre’ls.El crecimiento de la demanda energética y el continuo desarrollo tecnológico de la sociedad están sobrepasando los límites medioambientales de nuestro planeta. Sin las medidas adecuadas, esta situación puede derivar en importantes problemas medioambientales que podrían causar daños irreversibles al medioambiente y al bienestar de la humanidad. El sector industrial es el principal consumidor energético, consumiendo alrededor de un tercio de la demanda energética global, lo que tiene una evidente relación negativa con el impacto ambiental. Por lo tanto, el reto de mitigar el cambio climático implicará mejoras del uso de la energía en la industria, creando grandes oportunidades de ahorro energético y reduciendo su impacto ambiental. Para ello, es esencial obtener información derivada de la investigación y el análisis científico que permita desarrollar soluciones enfocadas a la reducción de costes energéticos. Esta tesis ha tratado las necesidades particulares de la producción de gases industriales, creando herramientas basadas en la optimización matemática que permiten una toma de decisiones operativas más ágil y efectiva y detectando áreas para la mejora energética. Estas herramientas fomentan y avanzan hacia una industria más eficiente que permita un futuro más sostenible. Esta tesis tiene dos contribuciones principales. Por un lado, se crea una herramienta de optimización multiperiodo que permite obtener la configuración de operación óptima (desde el punto de vista económico y energético) de un proceso de producción de gases industriales, teniendo en cuenta todas sus variables. Por otro lado, se usa la metodología de Data Envelopment Analysis para comparar diferentes unidades de producción de gases industriales, identificando los focos de ineficiencia y haciendo recomendaciones para resolverlos. En definitiva, esta tesis ofrece un conjunto de herramientas prácticas y efectivas que apoyan el proceso de toma de decisiones en actividades industriales y permiten la identificación de oportunidades de mejora energética.The growth of energy demand and the continuous technological development of society are surpassing the environmental limits of our planet. Without adequate measures, this situation can lead to serious environmental problems that could cause irreversible damage to the environment and the well-being of humanity. The industrial sector is the largest energy consumer, with about one-third of global energy demand, which has an evident negative relationship with environmental impact. Therefore, the challenge of mitigating climate change will imply improvements in the energy use in industry, creating great opportunities for energy savings and reducing its environmental impact. In this sense, it is essential to obtain information derived from research and scientific analysis that allows developing solutions focused on the reduction of energy costs. This thesis has dealt with the particular needs of the production of industrial gases, by creating tools based on mathematical optimization models that allow much more agile and effective operational decision-making as well as the detection of areas for energy improvement. These tools encourage and move towards a more efficient industry that allow a more sustainable future. Two main contributions are derived from this thesis. On the one hand, it creates a multiperiod optimization tool that allows obtaining the optimal operational configuration (from the economic and energetic points of view) of an industrial gas manufacturing process, taking into account all the variables that affect the system. On the other hand, the Data Envelopment Analysis methodology is used to compare different industrial gas production units, identifying inefficiency sources and making recommendations to adopt the best practices to solve them. Summarizing, this thesis offers a set of practical and effective tools that support the decision making process in industrial activities and allows the identification of opportunities for energy improvement

Benchmarking the performance of UK electricity distribution network operators: a study of quality, efficiency and productivity using data envelopment analysis

The aim of this thesis is twofold. The first is to develop a comprehensive methodology for assessing performance and then to apply it to the UK electricity distribution network operators (DNOs) to analyse the impact of the regulatory reforms and privatisation introduced in 1990-91 on their quality, efficiency and productivity developments. The models and methods developed will not only be useful in the electricity distribution context but also to other organisations that need to assess and monitor both their efficiency and quality. These objectives are realised through the use of the Data Envelopment Analysis (DEA) method, the main subject area of this thesis. This method has recently become very popular in the empirical literature due to the minimal assumptions underlying it, the case of handling multiple inputs and outputs, and its usefulness in the measurement of productivity. Performance measurement needs to keep pace with the changes in the industry. With the developments in energy and regulatory policy, and the enactment of the Utilities Act 2000, the focus of regulation has broadened from a narrow economic focus towards a wider one of protecting the interests of consumers. The latter includes not only price but also quality of service. Given this broadening focus, it is essential that performance measurement takes into account these aspects. This thesis incorporates new dimensions into efficiency and productivity measurement of electricity distribution network operators by taking into account the quality characteristics of electricity distribution operations. The dimensions of quality of service in electricity distribution were defined in this study, namely the quality of supply dimension and the quality of customer service dimension. Plausible measures of service quality were suggested. In order to provide a more balanced performance assessment, the new DEA model that incorporates the quantity as well as the quality of the services that distribution network operators provide their customers was used. In this study, only the quality of supply dimension was used in the analysis. (The quality of customer service dimension was omitted due to lack of data). Besides this, in order to achieve a more comprehensive assessment, both the operating and capital costs of distribution operations were included as inputs. The technological realities of the electricity distribution production process were captured in this study by taking into account the production trade-offs that exist between inputs and outputs. When trade-offs occur, the reduction in one factor can lead to increases in another, thereby reducing the overall reduction. The reflection of production trade-offs provides more reliable results than can be utilised in management and policy making. The production trade-offs were accounted by developing an enhanced DEA model using weight restrictions that are constructed on the basis of production trade-offs. The enhanced DEA model thus was referred to as the ‘weight-restricted’ model. This model developed was used to evaluate the DNOs efficiencies in 1999/00. A new productivity index called the ‘weight-restricted’ Malmquist productivity index was also developed in order to evaluate the quality and productivity changes of the DNOs since 1990/91. This new index is similar in spirit to the Malmquist productivity index but it reflects production trade-offs and service quality rather than just quantities per se. In this regard, the index is more appropriate to evaluate the DNOs. The index was decomposed in this study into its root components of efficiency change and technological change