Efficiency in European football teams using WindowDEA: analysis and evolution

Purpose The purpose of this paper is to analyze efficiency and its evolution in teams that played in the UEFA Champions League during nine seasons. The aim is to present a research procedure for determining the most accurate data envelopment analysis to estimate and compare the efficiency. Design/methodology/approach First, the authors analyzed the existence of a temporal trend using the S-statistic. The authors calculated the Kruskal–Wallis statistic to verify if there is stability in relative ranks. The results of the aforementioned tests have indicated that window analysis is an accurate methodology to apply to the sample. The authors analyzed 94 clubs with a sample of 288 observations, obtaining 768 efficiency ratios. They have been calculated using super-efficiency which enables to discriminate efficient units. Findings Results indicate that there is a low efficiency level in the nine seasons observed. There is a strong correlation between sports results and the efficiency of semifinalists. The authors conclude that improvement in a club’s efficiency could enhance its sports results. Finally, as practical implications, the authors highlight benchmark teams and alternative sports tactics to help clubs become more efficient and achieve better sports results. Originality/value This paper contributes to sports efficiency literature by presenting a research procedure to identify the most accurate methodology to be applied to panel data. To the best of the authors’ knowledge, this paper is the first empirical study on international football competitions applying WindowDEA to incomplete panel data

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Riveting two-dimensional materials: exploring strain physics in atomically thin crystals with microelectromechanical systems

Two dimensional (2D) materials can withstand an order of magnitude more strain than their bulk counterparts, which results in dramatic changes to electrical, thermal and optical properties. These changes can be harnessed for technological applications such as tunable light emitting diodes or field effect transistors, or utilized to explore novel physics like exciton confinement, pseudo-magnetic fields (PMFs), and even quantum gravity. However, current techniques for straining atomically thin materials offer limited control over the strain field, and require bulky pressure chambers or large beam bending equipment. This dissertation describes the development of micro-electromechanical systems (MEMS) as a platform for precisely controlling the magnitude and orientation of the strain field in 2D materials. MEMS are a versatile platform for studying strain physics. Mechanical, electrical, thermal and optical probes can all be easily incorporated into their design. Further, because of their small size and compatibility with electronics manufacturing methods, there is an achievable pathway from the laboratory bench to real-world application. Nevertheless, the incorporation of atomically thin crystals with MEMS has been hampered by fragile, non-planer structures and low friction interfaces. We have innovated two techniques to overcome these critical obstacles: micro-structure assisted transfer to place the 2D materials on the MEMS gently and precisely, and micro-riveting to create a slip-free interface between the 2D materials and MEMS. With these advancements, we were able to strain monolayer molybdenum disulfide (MoS2) to greater than 1\% strain with a MEMS for the first time. The dissertation develops the theoretical underpinnings of this result including original work on the theory of operation of MEMS chevron actuators, and strain generated PMFs in transition metal dichalcogenides, a large class of 2D materials. We conclude the dissertation with a roadmap to guide and inspire future physicists and engineers exploring strain in 2D systems and their applications. The roadmap contains ideas for next-generation fabrication techniques to improve yield, sample quality, and add capabilities. We have also included in the roadmap proposals for experiments such as a speculative technique for realizing topological quantum field theories that mimics recent theoretical wire construction methods

Defining A Stakeholder-relative Model To Measure Academic Department Efficiency At Achieving Quality In Higher Education

In a time of strained resources and dynamic environments, the importance of effective and efficient systems is critical. This dissertation was developed to address the need to use feedback from multiple stakeholder groups to define quality and assess an entity’s efficiency at achieving such quality. A decision support model with applicability to diverse domains was introduced to outline the approach. Three phases, (1) quality model development, (2) input-output selection and (3) relative efficiency assessment, captured the essence of the process which also delineates the approach per tool applied. This decision support model was adapted in higher education to assess academic departmental efficiency at achieving stakeholder-relative quality. Phase 1 was accomplished through a three round, Delphi-like study which involved user group refinement. Those results were compared to the criteria of an engineering accreditation body (ABET) to support the model’s validity to capture quality in the College of Engineering & Computer Science, its departments and programs. In Phase 2 the Analytic Hierarchy Process (AHP) was applied to the validated model to quantify the perspective of students, administrators, faculty and employers (SAFE). Using the composite preferences for the collective group (n=74), the model was limited to the top 7 attributes which accounted for about 55% of total preferences. Data corresponding to the resulting variables, referred to as key performance indicators, was collected using various information sources and infused in the data envelopment analysis (DEA) methodology (Phase 3). This process revealed both efficient and inefficient departments while offering transparency of opportunities to maximize quality outputs. Findings validate the potential of the ii Delphi-like, analytic hierarchical, data envelopment analysis approach for administrative decision-making in higher education. However, the availability of more meaningful metrics and data is required to adapt the model for decision making purposes. Several recommendations were included to improve the usability of the decision support model and future research opportunities were identified to extend the analyses inherent and apply the model to alternative areas

Life cycle sustainability assessment for selecting construction materials in the preliminary design phase of road construction projects

Road construction project activities cause severe harm to the environment as they consume a tremendous volume of materials and release pollutants into the environment. Besides, an increasing number of researchers is participating in work related to sustainability in the construction industry as well as road construction projects. Similar to other life cycles, a strong influence on sustainability is exerted in the early phases of road construction projects, especially in the preliminary design phase. Especially selecting materials is one of the most critical tasks in this phase because it contributes considerably to the achievement of sustainability targets. For enabling a conscious and systematic selection of materials, a significant evaluation of materials with regard to the three dimensions of sustainability is necessary. However, a well-elaborated and mature instrument supporting such an evaluation has not been developed and presented in literature until now. In the contrary, several studies revealed that the material-dependent activities and the life cycle analysis have been neglected so far. Moreover, selecting materials in the preliminary design phase is mainly based on designers’ experience and not on the application of analytic methods. Such selection is highly error-prone. In this thesis, current material selection methods for sustainable development in the preliminary design phase were analyzed. Initially, material selection studies conducted in the early design phase were analyzed to determine the relevant issues. The result emphasized that the integration of sustainability into material selection in the preliminary design phase encountered many obstacles, such as unavailable information and databases. Then, the most important sustainability criteria for selecting road construction materials were identified, covering the economic, environmental, and social dimensions of sustainability. Next, approaches which suggest the application of LCC, LCA, Social LCA, MCDM, and LCSA in road construction material selection are discussed in order to identify their limitations. Accordingly, this thesis developed an instrument based on the LCC, LCA, Social LCA, MCDM methods, and LCSA for assessing the sustainability performance of road construction materials in the preliminary design phase. The instrument is intended to help designers select the most sustainable materials by addressing the issues that emerge in the preliminary design phase. Firstly, a procedure model for evaluating the sustainability performance of road construction materials is suggested. It is based on two existing procedure models. One is a decision theory-based procedure model for sustainability-oriented evaluations. The model is divided into two levels, with the overall sustainability performance evaluation at the first level and the evaluation of the economic, environmental, and social performances at the second level. Although this procedure model demonstrates some benefits and has been utilized in some cases, the four-step LCA procedure, according to ISO 14044, appears to be more prevalent and well-established. Therefore, it is suggested here to integrate both approaches. This procedure model contributes to integrating the LCC, LCA, and Social LCA). Secondly, this instrument for assessing the sustainable performance of materials is further developed based on the step-by-step models of three pillars of sustainability. This allows for employing numerical methods from the LCC, LCA and Social LCA and thereby reducing the mistakes from the experience-based selection of designers. The proposed instrument also addresses the specific challenges of material selection in the preliminary design phase. The LCC could refine all material-dependent costs incurred during the life cycle and evaluate the material alternatives' total cost. Besides, it defines long-term outcomes by dividing the material life cycle into many consecutive phases and applying the time value of money into the calculation. For the LCA, two scenarios are proposed to solve the problems concerning the lack of available information in the preliminary design phase. Besides, the environmental performance of material-dependent activities, such as the usage of equipment and labor, is also considered in the method. The Social LCA is developed based on the Performance Preference Point (PPR) approach and the Subcategory Assessment Method (SAM) to assess the social performance of road construction materials. The method also shows the potential to support the designers in selecting the most social-friendly material by considering the material-dependent activities and stakeholders. The LCC, LCA, and Social LCA analyses integrated into the LCSA to come up with the general perspective of sustainable level. From the perspective of decision-makers, the importance level of sustainability dimensions might be different. The study suggests applying the AHP method and Likert Scale to evaluate the weightings and then integrating them into the LCSA model to assess the general sustainability performance of road construction materials. After that, a ternary diagram can be drawn to provide a comprehensive picture of the road construction material selection in dependence on these weightings. The assessment of two alternatives, “concrete bricks” and “baked bricks”, was conducted as a case study to illustrate and demonstrate the procedure model

Medidas de productividad en los proyectos de desarrollo de software: una aproximación por puestos de trabajo

La productividad es una medida, principalmente económica, creada a finales del siglo XVIII. Desde entonces, numerosas modificaciones se han realizado sobre la definición inicial y se han incorporando a diversas áreas de conocimiento. Dentro de la Ingeniería del Software (IS), la productividad comenzó a ser objeto de estudio a finales de los años 70, casi de forma paralela a la concepción de la misma y al inicio del estudio de conceptos relacionados, tales como la estimación de esfuerzo. La medición de la productividad en IS ha sido ampliamente analizada a nivel de proyecto y organización, sin embargo a nivel de puesto de trabajo no ha sido tan investigada. En estos escasos estudios, las medidas utilizadas suelen ser las mismas medidas que las empleadas en niveles superiores de medición. En concreto, las medidas empleadas suelen ser ratios entre una medida de tamaño de producto (p. ej., líneas de código o puntos función) y una medida de esfuerzo o tiempo (p. ej., horas-hombre u horas). Este tipo de medidas son muy específicas y no reflejan la realidad del trabajo desempeñado en todo el proceso de desarrollo, ya que no tienen en cuenta las características inherentes a cada puesto de trabajo. Así pues, la eficacia de estas medidas, en este nivel de medición, parece estar en entredicho y la realización de estudios que aporten nuevas medidas de productividad en IS a nivel de puesto de trabajo cobra sentido. En la presente tesis doctoral se ha analizado la situación actual de la medición de la productividad en IS a nivel de puesto de trabajo con el objetivo de crear nuevas medidas. Para conseguir este objetivo se ha realizado un estudio del estado de la cuestión utilizando una metodología clásica de revisión de referencias junto con una revisión sistemática de la literatura. Una vez analizado el estado de la cuestión se ha planteado un conjunto de hipótesis relacionadas con la construcción de nuevas medidas de productividad: Hipótesis 1. En los puestos de trabajo involucrados en la ejecución de proyectos de desarrollo de software se emplean otras entradas, además del tiempo y el esfuerzo. Hipótesis 2. Las entradas utilizadas son distintas para cada puesto de trabajo involucrado en la ejecución de proyectos de desarrollo de software. Hipótesis 3. En los puestos de trabajo involucrados en la ejecución de proyectos de desarrollo de software se producen otras salidas, además de líneas de código y funcionalidad. Hipótesis 4. Las salidas producidas son distintas para cada puesto de trabajo involucrado en la ejecución de proyectos de desarrollo de software. Hipótesis 5. Las medidas de productividad más utilizadas a nivel de puesto de trabajo en los proyectos de desarrollo de software tienen una eficacia limitada para medir la productividad real de los trabajadores. Hipótesis 6. Es posible medir de forma más eficaz la productividad de los puestos de trabajo en los proyectos de desarrollo de software con nuevas medidas que combinen varios elementos: entradas, salidas y factores. Tras el análisis del estado de la cuestión, se ha realizado una fase de investigación cualitativa mediante el empleo de entrevistas a trabajadores de IS y un posterior análisis de contenido, con el fin de obtener información suficiente para: (1) contrastar las cuatro primeras hipótesis con información cualitativa, y (2) construir el medio de recogida de información para la siguiente fase de la investigación. Con respecto al primer objetivo, ha sido posible contrastar dos hipótesis (H1 y H3). En la segunda fase, mediante una metodología cuantitativa, se han contrastado las cuatro primeras hipótesis planteadas. Para la recogida de información se ha utilizado un formulario construido a partir de los resultados de la fase cualitativa. Los resultados de esta fase indican que en los puestos de trabajo analizados (programador, analista, consultor, y jefe de proyecto): se utilizan otros recursos además del tiempo, se producen otras salidas además del código fuente y la funcionalidad entregada al cliente. Además, se han encontrado diferencias en el grado de uso de las entradas y en la producción de las salidas, por lo que el uso de una misma medida de productividad para todos los puestos bajo estudio es, en principio, ilógico. Para contrastar las dos, y últimas, hipótesis se han construido nuevas medidas de productividad, teniendo en cuenta los resultados previos. En concreto, se ha utilizado Data Envelopment Analysis (DEA) como metodología personalizable para medir la productividad; y se han realizado cuatro casos de estudio empleando dicha metodología. Los resultados tras los casos de estudio indican que mediante DEA es posible medir la productividad de los puestos de trabajo vinculados con los proyectos de desarrollo y mantenimiento de software de forma más eficaz que con las medidas más utilizadas. Además, esta metodología permite conocer los puntos de mejora para que los trabajadores menos productivos aumenten su productividad, lo que supone una gran ventaja frente a otras medidas de productividad si el objetivo de medir, como es lógico suponer, es mejorar la productividad, y no simplemente evaluarla. Así pues, se contrastan las dos últimas hipótesis y se insta, entre otras futuras líneas de investigación, a continuar con nuevos estudios que comparen el uso de DEA con otras medidas de productividad. Finalmente, se concluye que la medición de la productividad en los puestos de trabajo vinculados con los proyectos de desarrollo y mantenimiento de software continua siendo un reto. Para reducir la dificultad de éste, la presente tesis doctoral arroja luz aportando un marco de trabajo para analizar y plantear nuevas medidas de productividad, tanto en estos puestos de trabajo como en otros. ------------------------------Productivity is mainly an economic measure, created in the late eighteenth century. Since then, many changes have been made on its initial definition and have been incorporated into various areas of knowledge. Within Software Engineering (SE), productivity began to be studied in the late '70s. These efforts ran parallel to SE developments, such as effort estimation. Measuring productivity in SE has been extensively analyzed at the project and organization level; however job level has not been investigated with the same depth. In these few studies, the measures used are often the same ones than those used in higher levels of measurement. Specifically, the measures employed are usually ratios between a measure of product size (e.g., lines of code or function points) and a measure of effort or time (e.g., man-hours or hours). Such measures do not reflect the reality of the work performed throughout the development process because they do not take into account the inherent characteristics of each job. Thus, the effectiveness of these measures, in this measurement level, seems to be in question and studies that provide new measures of productivity at job level make sense. In this thesis we have analyzed the current state of productivity measurement at job level within SE with the goal of creating new measures. In order to achieve this objective a study of the state of the art has been carried out with a classical methodology along with a systematic review of the literature. After analyzing the state of the art, a number of hypotheses related to the construction of new productivity measures have been stated: Hypothesis 1. In the jobs involved in the implementation of software development projects other inputs are used in addition to time and effort. Hypothesis 2. The inputs used are different for every job involved in software development projects. Hypothesis 3. In the jobs involved in the implementation of software development projects other outputs are produced in addition to source code lines and functionality. Hypothesis 4. The outputs produced are different for every job involved in software development projects. Hypothesis 5. The most used productivity measures at job level in software development projects have limited effectiveness for measuring real productivity of workers. Hypothesis 6. It is possible to measure more effectively the productivity of jobs in software development projects with new measures that combine several elements: inputs, outputs and factors. After analyzing the state of the art, a qualitative phase has been performed using interviews with SE workers and a subsequent content analysis of them in order to obtain pertinent information: (1) to test the first four hypotheses with qualitative information, and (2) to build the information gathering instrument for the next phase of research. Regarding the first objective, it has been possible to test two hypotheses (H1 and H3). In the second phase, using a quantitative method, the first four hypotheses have been contrasted and accepted. For the information gathering a form constructed from the results of the qualitative phase has been used. The results of this phase indicate that the analyzed job positions (programmer, analyst, consultant, and project manager): use other resources in addition to time, and deliver other outputs in addition to source code and functionality delivered to the client. Also some differences in the degree of use of inputs and production of outputs have been found. Therefore, the use of the same measure of productivity for all positions under study is, in principle, illogical. To contrast the last two hypotheses new productivity measures have been built taking into account the previous results. Specifically, a customizable methodology for measuring productivity such as Data Envelopment Analysis (DEA) was used in four case studies. The results after these studies indicate that using DEA is a mean to measure the productivity of job level for job positions related to the development and maintenance of software projects in a more effectively way. Furthermore, this methodology allows knowing the points for improvement for the least productive workers in order to increase their productivity. This knowledge is a great advantage over other productivity measures if the goal of measuring, as is logical to assume, is to improve productivity, not simply to evaluate it. So the last two hypotheses has been supported. Consequently we call, among other future research, to continue with further studies comparing the use of DEA with other measures of productivity. Finally, it is concluded that the measurement of productivity in job positions related with software development and maintenance projects remains a challenge. To reduce this difficulty, this thesis sheds some light on the topic by providing a framework to analyze and propose new measures of productivity for SE job roles.Presidente: María Belén Ruiz Mezcua; Vocal: Rafael Valencia García; Secretario: Edmundo Tovar Car

Modelo de medición de la productividad para fábricas de software

La productividad en las fábricas de software es dado por el esfuerzo realizado para la producción del software, siendo muy importante porque permite que las organizaciones logren una mayor eficiencia y eficacia en sus actividades. Uno de los pilares de la competitividad es la productividad, la cual está relacionada al esfuerzo requerido para cumplir con las tareas asignadas, sin embargo, no existe una forma estándar de medirla. En este trabajo, se presenta un modelo basado en Análisis Envoltorio de Datos (DEA, por las siglas del inglés Data Envelopment Analysis) para evaluar la eficiencia relativa de las fábricas de software y sus proyectos, a fin de medir la productividad en la Componente de Producción de Software de la Fábrica de Software a través de las actividades que se realizan en sus diferentes unidades de trabajo. El modelo propuesto consta de dos fases, en la cual se evalúa, respectivamente, la productividad de la fábrica de software y la productividad de los proyectos que esta realiza. Pruebas numéricas sobre 6 fábricas de software con 160 proyectos implementados en el Perú muestran que el modelo propuesto permite determinar las fábricas de software y los proyectos más eficientes.Tesi

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii