Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

An MCDA cause-effect factors model for the implementation of Greenstone digital library soft-ware

The selection of an effective library software plays an important role not only for students, academic staff, and the library staff but it also helps an institution by having the library management system more centralized. Therefore, the aim of this study is to develop a Multiple- Criteria Decision Analysis (MCDA) cause and effect factor model for the implementation of the Greenstone digital library (GSDL) software. A thorough review of the literature is conducted to develop an initial list of the appropriate evaluation factors that play a significant role in the implementation of GSDL software. The data was collected from a domain of experts in the library sciences field. A combined approach of Delphi-DEMATEL methods is employed for the definition of these factors and to construct an MCDA cause-effect model which represent their relationships. The DEMATEL analysis resulted in the division of all factors into two groups, i.e., causes and effects. The results show that content management, having a user-friendly interface and usability, information search and retrieval, authentication and authorization fall into the cause group. These factors directly affect the remaining factors. Content acquisition, classification, access, control and privacy management, plus metadata submission and support fall into the effect group. The research findings can help library professionals to make effective decisions to facilitate the successful implementation of GSDL software in a library and the enhancement of library technology. The results of this study can be useful for library professionals and decision-makers to select the most appropriate software for the implementation of library technology. The study analysis shows that for GSDL, having a user-friendly interface and usability, information search and retrieval plus authentication, and authorization factors have seven positive relationships with other factors. Secondly, content management and classification have six relationships with other factors. Thirdly, access control plus privacy and management have two relationships. Content acquisition has only one relationship with other factors. It is recommended that the user-friendly interface and usability, information search and retrieval, as well as authentication and authorization should be the initial areas of focus if GSDL is to be implemented successfully in digital libraries. The proposed MCDA cause-effect model can be useful for library professionals or decision-makers in the context of selecting software to be implemented in a library and to minimize implementation costs.N/

Technical Conception and Implementation of an IT-System supporting the flexible Distribution of Documents within a large scale Sales Organization

This thesis aims to discuss and present an IT system to distribute documents within a large scale sales organization. Therefore, different sales applications on the market are analyzed and described. Based on this analysis, requirements for the IT system are defined. The requirements are divided into client-side and server-side requirements. The server application is realized using an existing ECM system to support the content throughout the enterprise content life cycle. Therefore, an evaluation of existing ECM systems is performed with a criteria catalog based on the requirements. Afterwards, the conception and architecture of the IT system is described, followed by further insights into the technical implementation of the mobile application. Finally, the features of the overall IT system are discussed and an outlook on how to extend the IT system is presented

The selection of an entry-level music librarian: The analytic hierarchy process (AHP) as a new model

This paper aims to present how to select the best entry-level music librarian by using the Analytic Hierarchy Process technique. The reason why we used this technique is due to the fact that it helps the decision makers easily calculate ‘the importance weights of professional criteria’ and ‘the extent to which the candidates meet the professional criteria’ to come to a final decision on each candidate. With this purpose, we firstly described 7 professional criteria (a1, a2, a3,…, a7) that must be met by 3 entry-level music librarian candidates. Secondly, we decided each candidate’s performance score representing the extent to which each candidate meets these criteria. For this, we used both a 9-point scale for pairwise comparisons and Saaty’s eigenvector method. Thirdly, we assigned the importance weights to the required criteria. Fourthly, we performed the consistency test to measure the consistencies of our calculations with the aid of the consistency ratio (CR). Fifthly, we obtained the final performance scores of each candidate as the candidate 1= 0,464, the candidate 2= 0, 296, and the candidate 3= 0, 240. Finally, we selected the candidate 1 who earned the highest score (0,464) in total as the best entry-level music libraria

Un enfoque de toma de decisiones multicriterio aplicado a la estrategia de transformación digital de las organizaciones por medio de la inteligencia artificial responsable en la nube de las organizaciones. Estudio de caso en el sector de salud

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Estudios Estadísticos, leída el 08-02-2023Organisations are committed to understanding both the needs of their customers and the capabilities and plans of their competitors and partners, through the processes of acquiring and evaluating market information in a systematic and anticipatory manner. On the other hand, most organisations in the last few years have defined that one of their main strategic objectives for the next few years is to become a truly data-driven organisation in the current Big Data and Artificial Intelligence (AI) context (Moreno et al., 2019). They are willing to invest heavily in Data and AI Strategy and build enterprise data and AI platforms that will enable this Market-Oriented vision (Moreno et al., 2019). In this thesis, it is presented a Multicriteria Decision Making (MCDM) model (Saaty, 1988), an AI Digital Cloud Transformation Strategy and a cloud conceptual architecture to help AI leaders and organisations with their Responsible AI journey, capable of helping global organisations to move from the use of data from descriptive to prescriptive and leveraging existing cloud services to deliver true Market-Oriented in a much shorter time (compared with traditional approaches)...Las organizaciones se comprometen a comprender tanto las necesidades de sus clientes como las capacidades y planes de sus competidores y socios, a través de procesos de adquisición y evaluación de información de mercado de manera sistemática y anticipatoria. Por otro lado, la mayoría de las organizaciones en los últimos años han definido que uno de sus principales objetivos estratégicos para los próximos años es convertirse en una organización verdaderamente orientada a los datos (data-driven) en el contexto actual de Big Data e Inteligencia Artificial (IA) (Moreno et al. al., 2019). Están dispuestos a invertir fuertemente en datos y estrategia de inteligencia artificial y construir plataformas de datos empresariales e inteligencia artificial que permitan esta visión orientada al mercado (Moreno et al., 2019). En esta tesis, se presenta un modelo de toma de decisiones multicriterio (MCDM) (Saaty, 1988), una estrategia de transformación digital de IA de la nube y una arquitectura conceptual de nube para ayudar a los líderes y organizaciones de IA en su viaje de IA responsable, capaz de ayudar a las organizaciones globales a pasar del uso de datos descriptivos a prescriptivos y aprovechar los servicios en la nube existentes para ofrecer una verdadera orientación al mercado en un tiempo mucho más corto (en comparación con los enfoques tradicionales)...Fac. de Estudios EstadísticosTRUEunpu

Praxis Market Drift

Over the last decade, digital data has been growing exponentially. Unstructured data is rapidly outgrowing structured data, and so managing unstructured data is increasing as a challenge for many organisations. Consequently, text mining has been gaining traction as a way to deal with unstructured data. Text mining is a form of data mining that deals with text and is the process of transforming unstructured text into meaningful and actionable information. Praxis is a platform that implements a virtual market for project/internship offers. organisations submit their project/internship offers that become available for search, and students search the platform using keywords that express their interest. Praxis has loads of unexplored data from which they can extract useful information to obtain more insights on their internships market. This dissertation proposes a solution based on text mining techniques, that displays the necessary information to analyse the evolution of users’ interests and internship offers submitted in Praxis, over time.Durante a última década, a quantidade de dados digitais tem vindo a crescer exponencialmente. A quantidade de dados não estruturados está rapidamente a superar a quantidade de dados estruturados, e portanto, a gerência de dados não estruturados está a crescer como um desafio para várias organizações. Consequentemente, text mining tem vindo a ganhar tração como forma de lidar com dados não estruturados. Text mining é uma forma de data mining que trabalha com texto e é o processo the transformar dados não estruturados em informação significativa. O Praxis é uma plataforma que implementa um mercado virtual para ofertas de projetos/estágios. Organizações submetem as suas propostas de projeto/estágio que ficam disponíveis para pesquisa, e os estudantes pesquisam na plataforma, com recurso a palavraschave que expressam os seus interesses. O Praxis tem muitos dados inexplorados dos quais eles podem extrair informações úteis para obter uma melhor perceção do seu mercado de estágios académicos. Esta dissertação propõe uma solução baseada em técnicas de text mining, que apresenta a informação necessária para analisar a evolução dos interesses dos utilizadores e das ofertas de estágio no Praxis, ao longo do tempo