Optimal path selection of innovation resource allocation in China’s regions with shared inputs

As an effective form of interaction between innovation subjects and resources, the regional innovation network’s optimal allocation of resources is the key to improving national innovation capacity. According to the innovation value chain, the process of resource allocation in innovation can be divided into two correlative sub-systems: the knowledge innovation stage (KIS) and the achievements commercialisation stage (ACS). To evaluate regional innovation efficiency, a two-stage network data envelopment analysis model with shared inputs is used, with fuzzy set qualitative comparative analysis to analyse the improvement path of resource allocation efficiency from the dimensions of regional environment and network structure. The results show that efficiency in the KIS is higher than in the ACS, and the efficiency scores for most regions in China are better under the model with shared inputs. The efficiency of innovative resource allocation is affected by the cross-action of seven factors: regional economic development, infrastructure, policy system, social culture, network scale, network openness, and network centrality. To achieve highefficiency resource allocation, regions should build an innovation network that matches their environmental characteristics. These findings provide theoretical guidance for formulating innovative resource allocation policies suitable for different regions

Energy and performance-aware scheduling and shut-down models for efficient cloud-computing data centers.

This Doctoral Dissertation, presented as a set of research contributions, focuses on resource efficiency in data centers. This topic has been faced mainly by the development of several energy-efficiency, resource managing and scheduling policies, as well as the simulation tools required to test them in realistic cloud computing environments. Several models have been implemented in order to minimize energy consumption in Cloud Computing environments. Among them: a) Fifteen probabilistic and deterministic energy-policies which shut-down idle machines; b) Five energy-aware scheduling algorithms, including several genetic algorithm models; c) A Stackelberg game-based strategy which models the concurrency between opposite requirements of Cloud-Computing systems in order to dynamically apply the most optimal scheduling algorithms and energy-efficiency policies depending on the environment; and d) A productive analysis on the resource efficiency of several realistic cloud–computing environments. A novel simulation tool called SCORE, able to simulate several data-center sizes, machine heterogeneity, security levels, workload composition and patterns, scheduling strategies and energy-efficiency strategies, was developed in order to test these strategies in large-scale cloud-computing clusters. As results, more than fifty Key Performance Indicators (KPI) show that more than 20% of energy consumption can be reduced in realistic high-utilization environments when proper policies are employed.Esta Tesis Doctoral, que se presenta como compendio de artículos de investigación, se centra en la eficiencia en la utilización de los recursos en centros de datos de internet. Este problema ha sido abordado esencialmente desarrollando diferentes estrategias de eficiencia energética, gestión y distribución de recursos, así como todas las herramientas de simulación y análisis necesarias para su validación en entornos realistas de Cloud Computing. Numerosas estrategias han sido desarrolladas para minimizar el consumo energético en entornos de Cloud Computing. Entre ellos: 1. Quince políticas de eficiencia energética, tanto probabilísticas como deterministas, que apagan máquinas en estado de espera siempre que sea posible; 2. Cinco algoritmos de distribución de tareas que tienen en cuenta el consumo energético, incluyendo varios modelos de algoritmos genéticos; 3. Una estrategia basada en la teoría de juegos de Stackelberg que modela la competición entre diferentes partes de los centros de datos que tienen objetivos encontrados. Este modelo aplica dinámicamente las estrategias de distribución de tareas y las políticas de eficiencia energética dependiendo de las características del entorno; y 4. Un análisis productivo sobre la eficiencia en la utilización de recursos en numerosos escenarios de Cloud Computing. Una nueva herramienta de simulación llamada SCORE se ha desarrollado para analizar las estrategias antes mencionadas en clústers de Cloud Computing de grandes dimensiones. Los resultados obtenidos muestran que se puede conseguir un ahorro de energía superior al 20% en entornos realistas de alta utilización si se emplean las estrategias de eficiencia energética adecuadas. SCORE es open source y puede simular diferentes centros de datos con, entre otros muchos, los siguientes parámetros: Tamaño del centro de datos; heterogeneidad de los servidores; tipo, composición y patrones de carga de trabajo, estrategias de distribución de tareas y políticas de eficiencia energética, así como tres gestores de recursos centralizados: Monolítico, Two-level y Shared-state. Como resultados, esta herramienta de simulación arroja más de 50 Key Performance Indicators (KPI) de rendimiento general, de distribucin de tareas y de energía.Premio Extraordinario de Doctorado U

Organisational Design factors and efficiency of Spanisg First Division football teams

The activity carried out by football players during games can be considered as an example of the characteristics of a team as understood by Organizational Economics. In this study, the Spanish First Division football teams were taken as a sample to evaluate the implemented organisational design. Data Envelopment Analysis was used to calculate the efficiency and the variables representing the degree of coordination achieved in the games were determined by factor analysis. It can be concluded that there are efficient Spanish First Division football teams that have implemented organizational designs leading to good team coordination

Improving the management of an IT department by using a new developed computer application

This work has been developed outside of office hours, in combination with the work of IT Analyst and Project Manager in Philip Morris SA (Switzerland). The dissertation seeks solutions to real-life problems, specifically associated with the daily challenges faced by the managers and team members of the Information Technology department. It was acknowledged the need to enhance the management and assignment of tasks and projects to the team members, where the major issue resided on the understanding of the constraints affecting the work allocation and workload management. To solve the mentioned hurdles, it was needed to develop an appropriate tool, matching the specific needs while being economically efficient and easy to operate. The management was involved in various sharing sessions, allowing the work to be developed in line with the genuine pain-points and to be built accordingly to the needs and expectations of the end-users. The SWOT analysis and the Ishikawa diagram played an important role in the delimitation of the challenges and on documenting the improvement possibilities. Firstly, the problem assessment was done, then it was time to review the literature, searching for the core values and best practices in Project Management. Later, there was an extensive review of the Resources Allocation subject, by concept and objectives, and as a tool to efficiently merging the specificities of the resources and activities while considering an extensive group of constraints. Then, it was done a broad attempt to combine the concepts of the Manager as a human and a servant leader with a focus on team success, with the usage of Resources Allocation tools as indispensable instruments for the success of any Project. Later, the work arrives at its core, with the development of the Allocation Algorithm and the MS Excel® program that allows the Managers to properly register and assign the Projects and Tasks, considering the specificities and constraints in place. The developed tools have been validated and utilized by Managers while performing their daily management routines. The most relevant improvements indicated by the end-users have been, the centralization and availability of the information, the rapidity of new activities’ assignment, and the benefit of having a unified status tool that takes into consideration the team specificities. In the literature, there are different approaches related to the resources’ allocation and project management issues and challenges. However, many of the Researchers never left the concept development stage and several of them have only proposed theoretical approaches. In this work, more than build an algorithm and a program with a straightforward approach to the management challenges, it was prioritized the practicality of the model and the development of a purposeful tool – allowing the ideas to get off paper, implementing the tool and as result, effectively improving the management of activities and the human resources allocation.Este trabalho foi desenvolvido fora do horário de trabalho, em harmonia com o trabalho de Analista IT e Gestor de Projeto na Philip Morris SA (Suíça). Esta dissertação procura encontrar soluções para problemas de gestão, especificamente para os desafios relativos ao trabalho diário dos gestores e membros de equipa do Departamento de Tecnologias da Informação. Assim, foi considerada a necessidade de melhorar o sistema de gestão de tarefas e projetos. Um dos desafios foi compreender as restrições que afetam uma boa gestão e alocação de tarefas, sendo necessário desenvolver uma ferramenta que seja economicamente eficiente e fácil de utilizar. Os gestores foram envolvidos em várias sessões de partilha, permitindo que o trabalho fosse desenvolvido em linha com as necessidades reais e tendo em conta as expetativas dos utilizadores finais da ferramenta. A utilização da análise SWOT e do diagrama de Ishikawa foram muito importantes para delimitar o problema e para definir as oportunidades de melhoria. Primeiramente foi definido o problema, depois foi feita uma revisão da literatura, investigando os valores e os bons princípios da Gestão de Projetos. Seguidamente, foi feita uma revisão sobre a Alocação de Recursos, considerando a base teórica e a aplicabilidade na gestão e alocação de tarefas e de recursos humanos. Paralelamente foi feita uma análise sobre como conjugar o conceito do gestor como humano e líder, e o seu papel no sucesso dos projetos. Foi também analisada a importância das ferramentas na gestão de qualquer projeto. Mais tarde, o trabalho chega ao seu âmago, com o desenvolvimento do Algoritmo de Alocação e do programa MS Excel®, ambos permitindo uma fácil e eficiente alocação de projetos e tarefas por parte dos responsáveis, considerando as restrições e as necessidades da empresa. O desenvolvimento do algoritmo e do programa foi feito em concordância com a gestão, garantindo dessa forma o alinhamento ideal entre o desenvolvimento e as necessidades reais. Os gestores indicaram como benefícios, a forma correta e fácil de associar atividades aos colaboradores, a centralização e qualidade da informação disponibilizada, e ainda a garantia de usar uma ferramenta que considera as especificidades da equipa e os projetos do departamento. Na literatura existem várias abordagens relativas aos desafios da alocação de recursos e da gestão de projetos. Contudo, muitos dos investigadores ficam apenas pela fase do conceito, e muitos apresentam apenas hipóteses e soluções teóricas. Neste trabalho, procurou-se desenvolver um algoritmo e um programa de utilização simples, colocando o funcionalismo e aplicabilidade como prioridades – permitindo que as ideias saíssem do papel, garantindo a implementação da solução e criando melhorias reais em termos de gestão de atividades e gestão de recursos humanos

Estimating the Efficiency of Four-year Public Master\u27s Universities in Arkansas Using Data Envelopment Analysis

For the fourth time in the past 20 years, the state of Arkansas has implemented a performance-funding program. Although directly referenced in the title of Act 1203 of 2011, the implemented performance-funding program does not include a measure of how efficiently institutions are converting their inputs into outputs. The purpose of this study was two-fold: (1) to examine, through the conceptual framework of agency theory, why the state of Arkansas adopted performance funding policy after experiencing three adopt-implement-abandon cycles in the past 20 years, and (2) to estimate the efficiency of four-year public Master\u27s universities in Arkansas in achieving one of the mandatory measures in the performance-funding program: number of bachelor\u27s degrees awarded. The institutions included in this study were Arkansas State University, Arkansas Tech University, and University of Central Arkansas in the larger group, and Henderson State University, Southern Arkansas University, and University of Arkansas at Monticello in the medium/smaller group. The analytical technique utilized in this study was based on Simar and Wilson\u27s (2007) double bootstrap truncated regression approach. This study found that the six Arkansas institutions were inefficient in the production of bachelor\u27s degrees during the 2011-2012 academic year, given the inputs included in the model and in relationship to the national sample of Master\u27s Colleges and Universities. Through the second-stage regression analysis, this study also found that a state\u27s per capita real gross domestic product (GDP) was a positive and statistically significant determinant of estimated efficiency for both groups of institutions (larger and medium/smaller). For the medium/smaller group, higher education\u27s share of total state expenditures was a negative and statistically significant determinant of estimated efficiency, while the share of operating revenues based on net tuition was a positive and statistically significant determinant of estimated efficiency for the larger group institutions. The existence of a performance-funding program was found to not be a significant determinant of institutional efficiency through the second-stage regression analysis. Using Eisenhardt\u27s (1989) taxonomy of behavior- versus outcome-based contracts, this study also found that agency theory served as a viable conceptualization of why the state of Arkansas chose to adopt performance-funding policy for the fourth time since its initial adoption in 1995

Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209

Enterprise, project and workforce selection models for industry 4.0.

Abstract Enterprise, project, and workforce selection models for Industry 4.0. Rupinder Kaur The German federal government first coined industry 4.0 in 2011. Industry 4.0 involves the use of advanced technologies such as cyber-physical system, internet of things, cloud computing, and cognitive computing with the aim to revolutionize the current manufacturing practices. Automation and exchange of big data and key characteristics of Industry 4.0. Due to its numerous benefits, industries are readily investing in Industry 4.0, but this implementation is an uphill struggle. In this thesis, we address three key problems related to Industry 4.0 implementation namely Enterprise selection, Project selection and Workforce selection. The first problem involves identification of enterprises suitable for Industry 4.0 implementation. The second problem involves prioritization and selection of Industry 4.0 projects for the chosen digital enterprises. The third and last problem involves workforce selection and assignment for execution of the identified Industry 4.0 projects. Multicriteria solution approaches based on TOPSIS and Genetic Algorithms are proposed to address these problems. Industry experts are involved to prioritize the criteria used for enterprise, project and workforce selection. Numerical applications are provided. The proposed work is innovative and can be useful to manufacturing and service organizations interested in implementing Industry 4.0 projects for performance improvement