A novel methodology for the assessment or wave energy opions at early stages

276 p.El aumento de la proporción de generación de electricidad a partir de fuentes renovables es clave para garantizar un sistema energético totalmente descarbonizado y luchar contra el cambio climático. La energía undimotriz es un recurso abundante pero, al mismo tiempo, es la menos desarrollada de todas las tecnologías renovables. El marco de evaluación común desarrollado en la tesis se basa en principios sólidos de ingeniería de sistemas y abarca el contexto externo, los requisitos del sistema y los criterios de evaluación. Se puede aplicar a diferentes niveles de madurez tecnológica y capta los aspectos cualitativos relacionados con las expectativas de las partes interesadas. El enfoque novedoso guía las decisiones de diseño a lo largo del proceso de desarrollo para la gestión adecuada del riesgo y la incertidumbre, y facilita la selección y evaluación comparativa de la tecnología undimotriz a diferentes niveles de madurez de manera controlada. Los métodos propuestos en esta investigación brindan información valiosa para enfocar los esfuerzos de innovación en aquellas áreas que tienen la mayor influencia en el desempeño de la tecnología. La incorporación de estrategias de innovación eficaces en el desarrollo de la energía undimotriz ayuda a gestionar la complejidad del sistema y canalizar la innovación hacia mejoras útiles.Tecnali

Quality Function Deployment: Can Improve Innovation Efficiency in the Food Industry?

This paper considers the implementation of the Quality Function Deployment (QFD) as a methodological framework for the development of new food products. This paper focuses on the beef supply chain and develops a horizontal product’s quality deployment as a strategic tool for the implementation of consumer-led product innovation strategies. Difficulties in the prioritisation of parameters and setting of target values for the desired performance level of each parameter would limit the implementation of a complete ‘four-phase’ model in the sector. Thus, the use of complementary management tools, such as SWOT analysis and Failure Mode and Effect Analysis (FMEA) would be necessary to develop more suitable process designs to the specific requirements of the sector.Agribusiness, Research and Development/Tech Change/Emerging Technologies,

Specification of Non-Functional Requirements for Contract Specification in the NGOSS Framework for Quality Management and Product Evaluation

The community of operation support systems (OSS) for telecom applications defined a set of fundamental principles, processes, and architectures for developing the next generation OSS through the TeleManagement Forum TMF. At the heart of NGOSS lies the notion of a contract which embodies the specification of services offered by an OSS component for quality management and product evaluation. However, TMF does not provide any method (or process) for specification of the non-functional part in the NGOSS contract specification. In this paper, we develop a systematic approach for specifying non-functional requirements of telecom OSS applications for contracts in the NGOSS framework for quality management and evaluation. Specifically, two categories of non-functional specification techniques are explored: qualitative and quantitative. Furthermore, we introduce two quantitative non-functional requirements specification methods: crisp and elastic to expand the capability of the current NGOSS contract specification method since only qualitative non-functional specification is currently available from TMF

Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Purpose: Analytics research is increasingly divided by the domains Analytics is applied to. Literature offers little understanding whether aspects such as success factors, barriers and management of Analytics must be investigated domain-specific, while the execution of Analytics initiatives is similar across domains and similar issues occur. This article investigates characteristics of the execution of Analytics initiatives that are distinct in domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management has been recognized as early adopter of Analytics but has retracted to a midfield position comparing different domains. Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured Interviews creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin. Findings: A total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives were identified, which are mapped and explained. As a blueprint for further research, the domain-specifics of Logistics and Supply Chain Management are presented and discussed. Originality/value: The results of this research stimulates cross domain research on Analytics issues and prompt research on the identified characteristics with broader understanding of the impact on Analytics initiatives. The also describe the status-quo of Analytics. Further, results help managers control the environment of initiatives and design more successful initiatives.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

A Decision Process Model to Support Migration to Cloud Computing

Migration to cloud computing is a strategic organisational decision that can affect performance, productivity, growth, as well as increase competitiveness. The decision to migrate is usually complicated and dynamic due to the immaturity and the still evolving nature of the cloud environment. Although there have been many proposed methods for supporting the migration, no systematic decision process exists that clearly identifies the main steps and explicitly describes the tasks to be performed within each step. In this paper, a decision-making process model, based on a two-stage survey, is proposed. The model guides decision makers through a step-by-step approach, aiding them with their decisions for cloud migration. It offers a preliminary structure for developing a cloud knowledge-based decision support system. The model was evaluated by a group of cloud practitioners. The analysis demonstrates a high level of acceptance with regard to the structure, tasks involved and issues addressed by it

Effectiveness of R&D project selection in uncertain environment: An empirical study in the German automotive supplier industry

This paper presents results of an empirical large-scale study on uncertainty reduction of R&D projects and R&D project selection. The empirical field is the German automotive supplier industry. We explore R&D project selection practices in this specific industry and briefly contrast our findings with the academic research and management literature in this field. We concentrate on answering three research questions (with focus on questions no. 1 and 2): I. Which information and related uncertainties are crucial for the product selection decision to the R&D decision makers? II. How do R&D decision makers today cope with typical challenges related to reducing uncertainty? Where do they face major problems and how effective are they? III. What are major implications for managing the Fuzzy Front End (FFE) of innovation process in industry practice and respectively for further academic research in this field? Key findings are that on the one hand certainty about fields of product applications, target markets and production feasibility are most important criteria for initial product selection decisions. On the other hand market and cost related uncertainties (e.g. sales volume, product price, cost per unit) cannot be satisfyingly reduced in practice before project approval for development or definite termination of projects. Although different uncertainty profiles exist within the process of project evaluation, most companies do not systematically choose available product selection methods and tools according to specific uncertainty situations. Intuition still plays a major role in R&D product selection. Some first conclusion drawn from this research are: A sufficient level of resources (including financial and methodological know-how), a systematic use of suitable project selection instruments, and a fit with the company specific as well as the OEMs' product/brand strategies can be potential levers for more effective uncertainty reduction before product decision. --