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Protected areas play an important role in biodiversity conservation and tourism. Significant efforts have been made to increase the amount of protected lands. A problem of increasing the amount of public protected areas is that governments and other institutions face difficulties in providing the necessary resources for effective management. Accordingly, managers must be as efficient as possible but the lack of comparative methods makes the evaluation of efficiency difficult. Using Data Envelopment Analysis, a non-stochastic and non-parametric approach, information from 29 protected areas in 5 countries was analyzed to compare management efficiency amongst them. The first result found is the level of management efficiency that each park has in comparison with the others parks. The other important result is a prediction of the changes in the outputs if there is a hypothetical budget change. These results allow the generation of information for decision making. Objectius de Desenvolupament Sostenible::14 - Vida Submarina Objectius de Desenvolupament Sostenible::15 - Vida d'Ecosistemes Terrestres

We evaluate the co-innovation trajectory of firms adopting different collaborative innovation networks (i.e., vertical, horizontal, and institutional). The results of the empirical applications are obtained from a multilevel regression, and a Nash bargaining model estimated via data envelopment analysis on a sample of 734 enterprises from seven OECD countries form Europe and Latin America. Findings point to important national and firm-level distinctions across the optimal co-innovation configurations: whereas vertical co-innovation strategies are characteristic of firms with the highest innovation efficiency, institutions are frequently found to be optimal for co-innovation success in less developed innovation systems that may be faced with structural deficiencies. However, digital competency is found to disrupt co-innovation configurations for successful innovation, facilitating the development of efficient vertical and horizontal co-innovation trajectories.

Purpose: Airport management is influenced by several related critical decisions on financial and technical operations. Optimum utilization of resources, including assets and personnel, is critical to achieve better service quality for the passengers and an efficient airport. Due to its importance, this paper aims to assess the performance of airports based on security, safety, and possible work-related health problems by considering the uncertain and unclear number of passengers and their baggage. Design/methodology/approach: The efficiency of 30 airports in Turkey is evaluated with a basic Data Envelopment Analysis (DEA) model with two inputs and five outputs. Then, the model is redefined with an undesired output. High, medium, and low seasons are defined in the second DEA model to estimate the number of passenger baggage. The third model utilizes the principles of Fuzzy DEA (F-DEA) that aims to handle the uncertainty for the undesired output data.Findings: The results of three models confirm that the number and weight of baggage and consequently health and safety issues in airports should not be overlooked when optimizing airport efficiency. Utilizing the fuzzy theory has the potential to help managers to improve the operational efficiency of airports when dealing with an uncertain number of passengers and estimating the workload of baggage handlers.Research limitations/implications: No permission was given to make interviews with the ground handling personnel and gather real-life data to analyze task durations and workers’ body movements.Practical implications: Inputs, outputs, and undesired output defined in this study can be used to assess the airports in any other country.Social implications: The importance of health and safety issues for passengers, airport personnel, baggage handlers, and the residents who live close to the airports is considered.Originality/value: This study contributes to the airport performance assessment literature by considering the uncertain and dynamic data related to health and safety issues. This pioneering study, up-to-best knowledge, is the first to assess the airports in Turkey by DEA with the defined undesired output (baggage handler workload) and also utilizing the fuzzy model for the uncertain data.

This study analyzes the efficiency of Spanish provinces in a model that incorporates occupational health and safety (OHS) policy controls and work accidents into the analysis. Building on productivity models rooted in nonparametric frontier methods, namely Data Envelopment Analysis, the proposed approach allows the development of a production function that accurately models the joint production of desirable (GDP) and undesirable (work accidents) outputs. The efficiency analysis of the 50 Spanish provinces during 2003–2012 reveals that territories that drastically cut resources dedicated to OHS controls—in our case, safety inspections and economic sanctions for safety violations—show higher inefficiency levels. Nevertheless, the changes in OHS policies introduced by Spanish provinces after the change in the state of the economy in 2008 had a heterogeneous impact on their efficiency level. Effective OHS policy is not necessarily linked to merely implementing more OHS policy controls, but rather to the capacity of territories to efficiently allocate their available OHS resources and monitor business activity. Policy implications and future research avenues are discussed.

Building on the Resource Based View (RBV) theory of the firm, this study proposes an analysis of business competitiveness and competitive efficiency based on the configuration of different competitive pillars that shape competitiveness. The empirical application uses non-parametric frontier methods (Data Envelopment Analysis, DEA) on a unique sample of 171 Catalan businesses.The results show that different strategies adopted by businesses impact their competitiveness level. Also, it was found that competitive efficiency is conditioned by the heterogeneous configuration of competitive pillars, and that this effect varies across industries, in our case manufacturing, construction, retail, knowledge-intensive business services (KIBS), and consumer services. The findings at industry level reveal that competitiveness and competitive efficiency are two inter-connected construct that not always follow the same trajectory.Additionally, the findings indicate that the optimal configurations of competitive pillars (measured via the weights assigned to competitive pillars) are heterogeneous across industries, which suggests that competitive strengths and weaknesses also vary across industries. For example, ‘innovation’ and ‘human capital’ are the most relevant competitive pillars among KIBS firms, while for retail firms the pillars related to ‘markets’ and ‘human capital’ are more decisive to shape competitiveness.

Purpose: Representative correlational study of Spanish Ports Authorities (PA), based on analysis of PA economic efficiency, measured using DEA Data Envelopment Analysis, and PA environmental disclosure. Data employed: environmental reports of 20 PAs examined to gain understanding of Environmental Disclosures; economic management reports of individual ports to obtain the economic variables analyzed. The purpose to identify correlations among variables of environmental disclosure and economic efficiency of port management, with consideration of port overheads and profit focused structure. Design/methodology: A three-stage study, comprised of: 1st Classification of PAs efficiency; 2nd Analysis of environmental information disclosed, for which an Environmental Disclosure Assessment was defined; 3rd Cluster Analysis to determine correlations of the economic efficiency findings of stage 1 cross-referenced with environmental disclosures of stage 2. Findings: The results obtained from the study are: classification of all Spanish PAs, although only 20 PAs are analyzed in stages 2nd and 3rd; snapshot of 2012 information contained in the Environmental Disclosure Assessment defined, and DEA with results of correlations between the PAs´ environmental disclosures and economic efficiency ratings. Among relevant findings, the study shows that Efficient and Marginally Efficient PAs provide best environmental disclosures, as defined by type/frequency of reporting and environmental impact management information disclosed. Note: Efficient PAs provide more detailed information on water and energy management. Research limitations/implications: 8 PAs not supplying environmental reports were excluded from stages 2-3, due to which final results do not include 100% of PAs of the Spanish port system. Originality/value: The analysis allows to identify correlations among variables of environmental disclosure and economic efficiency of port management in Spanish Ports Authorities.

DOI: 10.1039/c6gc01696k URL: http://pubs.rsc.org/en/Content/ArticleLanding/2016/GC/C6GC01696K#!divAbstract Filiació URV: SI Inclòs a la memòria: SI Paraules en blanc With the growing trend of incorporating sustainability principles in the chemical industry, there is a clear need to develop decision-making tools to quantify and optimise the sustainability level of chemical products and processes. In this study, we propose a systematic approach based on Data Envelopment Analysis (DEA) for the multi-criteria screening of molecules according to techno-economic and environmental aspects. The main advantage of our method is that it does not require any articulation of preferences via subjective weighting of the assessment criteria. Furthermore, our approach identifies the most efficient chemicals (according to some sustainability criteria) and for the ones found to be inefficient it establishes in turn improvement targets that can be used to guide research efforts in green chemistry. Our method was applied to the screening of 125 amine-based solvents for CO2 capture considering 10 different performance indicators, which are relevant to technical, health, safety and environmental aspects, including CO2 solubility, molar volume, surface tension, heat capacity, viscosity, vapour pressure, mobility, fire & explosion, acute toxicity and Eco-indicator 99. Our approach eliminates 36% of the solvents (as they are found to be inefficient), identifies the main sources of inefficiency (e.g., properties displaying poor values that should be improved) and ranks the best chemicals according to an objective criterion that does not rely on weights. Overall, our proposed DEA-based framework offers insightful guidance to make chemicals more sustainable.

DOI: 10.1016/j.jclepro.2016.06.085 URL: http://www.sciencedirect.com/science/article/pii/S0959652616307624 Filiació URV: SI Inclòs a la memòria: SI A considerable amount of food is wasted every year around the world. This makes it necessary to manage and treat such food waste while trying to minimize impacts to the environment. The most common options for treating food waste include anaerobic digestion, composting, incineration and landfilling. The aims of this paper are (1) to develop a 3-stage methodology which capitalizes on the DEA + LCA framework proposed recently in the literature and combines data envelopment analysis, life cycle assessment and process retrofit into a single consistent framework; and (2) the application of this methodology to the assessment and retrofit of a number of technological options for food waste management. In essence, it starts by assessing the management options with respect to 12 environmental indicators (recommended in the European Commission Product Environmental Footprint method). With this information at hand, data envelopment analysis is applied to identify efficient and inefficient options. For the latter group, improvement targets are calculated, which are then used in the last stage of the methodology to guide retrofit actions to be implemented in the inefficient options so as to improve them. The capabilities of this methodology are illustrated by means of a case study that analyses 6 management options in an average European context. Results show that 4 of the 6 options are deemed efficient, while the other 2 are considered inefficient. A contribution analysis of the life cycle assessment results in the inefficient options is finally used to link the estimated reduction targets in every impact category with the specific proc

Quantifying the level of sustainability attained by a system is a challenging task due to the need to consider a wide range of economic, environmental and social aspects simultaneously. This work explores the application of data envelopment analysis (DEA) to evaluate the sustainability ‘efficiency’ of a system. We propose an enhanced DEA methodology that uses the concept of ‘order of efficiency’ to compare and rank alternatives according to the extent to which they adhere to sustainability principles. The capabilities of the proposed approach are illustrated through a sustainability assessment of different technologies for electricity generation in United Kingdom. In addition to screening the alternatives based on sustainability principles, enhanced DEA provides improvement targets for the least sustainable alternatives that, if achieved, would make them more sustainable. The enhanced DEA shows clearly the ultimate distance to sustainability, helping industry and policy makers to improve the efficiency of technologies, products and policies.

Quantifying the level of sustainability attained by a system is a challenging task due to the need to consider a wide range of economic, environmental and social aspects simultaneously. This work explores the application of data envelopment analysis (DEA) to evaluate the sustainability ‘efficiency’ of a system. We propose an enhanced DEA methodology that uses the concept of ‘order of efficiency’ to compare and rank alternatives according to the extent to which they adhere to sustainability principles. The capabilities of the proposed approach are illustrated through a sustainability assessment of different technologies for electricity generation in United Kingdom. In addition to screening the alternatives based on sustainability principles, enhanced DEA provides improvement targets for the least sustainable alternatives that, if achieved, would make them more sustainable. The enhanced DEA shows clearly the ultimate distance to sustainability, helping industry and policy makers to improve the efficiency of technologies, products and policies., Computers & Chemical Engineering, 90, ISSN:0098-1354, ISSN:1873-4375

Purpose: Evaluation and selection of efficient suppliers is one of the key issues in supply chain management which depends on wide range of qualitative and quantitative criteria. The aim of this research is to develop a mathematical model for evaluating and selecting efficient suppliers when faced with supply and demand uncertainties. Design/methodology/approach: In this research Grey Relational Analysis (GRA) and Data Envelopment Analysis (DEA) are used to evaluate and select efficient suppliers under uncertainties. Furthermore, a novel ranking method is introduced for the units that their efficiencies are obtained in the form of interval grey numbers. Findings: The study indicates that the proposed model in addition to providing satisfactory and acceptable results avoids time-consuming computations and consequently reduces the solution time. To name another advantage of the proposed model, we can point out that it enables us to make decision based on different levels of risk. Originality/value: The paper presents a mathematical model for evaluating and selecting efficient suppliers in a stochastic environment so that companies can use in order to make better decisions.

Globalisation and the knowledge-based society have driven universities to an intense competition for the best professors, researchers and students. Yet, rankings and reports measuring how universities perform are available in abundance. Among these assessment tools it is worth highlighting those based on Data Envelopment Analysis (DEA), which since the 1980s have risen considerably. However, there is a lack of consensus when selecting the indicators that best represent the inputs and outputs of such institutions. Aiming to clarify how these proxies are chosen, this paper does an exhaustive review of the indicators used in DEA empirical studies in the last decade, classifying them according to their nature and use.

En este trabajo se realiza un análisis comparado de dos métodos no paramétricos de medida de productividad total de los factores con datos de panel basados en programación: índices de Malmquist y un modelo DEA intertemporal que permite acotar las medidas de eficiencia y progreso técnico, suponiendo cambio técnico no regresivo. La aplicación se realiza sobre las agriculturas de los países de la Unión Europea, encontrándose algunas diferencias importantes entre ambos enfoques. Los resultados sugieren menor crecimiento de productividad agraria y, sobre todo, una ordenación distinta de países en relación con dichos crecimientos que los encontrados en otros trabajos. Palabras clave: Productividad, DEA, Agricultura, Europa, Datos de panel. SUMMARY This paper compares two non-parametric programming techniques for the measurement of total factor productivity using panel data: Malmquist indices and an intertemporal-DEA model that allows the calculation of technology and efficiency levels bounds, assuming non-regressive technical change. Both methodologies are applied to the analysis of agricultural productivity in the European Union countries, and several important divergences between models are found. The results suggest lower productivity increases in agriculture than those found in recent literature, with different country ranking concerning productivity growth.

The paper investigates the productivity level of technology transfer offices (TTOs) affiliated to Spanish public universities. The proposed approach allows the development of a framework that matches universities’ technology transfer concerns with the need to accurately analyze the role of the outcome configuration of TTOs. We analyze the productivity of Spanish TTOs during 2006–2011 by computing total factor productivity models rooted in non-parametric techniques, namely the Malmquist index. The results confirm that technology transfer productivity is affected by changes in the configuration of the TTO’s outcome portfolio that result from benchmarking own and market peers’ performance levels. While benchmarking own performance levels facilitates the exploitation of internal resources and yields superior productivity results, changes in TTO’s portfolio based on comparisons with market peers might generate greater operational costs that negatively impact productivity. info:eu-repo/semantics/acceptedVersion