Magister Commercii (Information Management) - MCom(IM) / Companies are putting in place systems that might assist in attaining their business goals and vision to improve the running of their business processes. Companies are looking at Business Intelligence (BI) as a means to attain a competitive edge over competitors, predict future trends, improve strategic decision making, facilitate quick and reliable decision making, or make the day-to-day running of business easier. The study looks at the perspective of middle to top management on the context of BI, with main focus on the technical capabilities of BI within medium to large companies in South Africa. To obtain factors relevant to the South African business context, an online survey was conducted with various sectors of South African industry. The study is part of research conducted collaboratively by the University of the Western Cape and Neu-Ulm University of Applied Sciences in Germany. It focuses on exploring usage of Business Intelligence Systems (BIS) together with Corporate Performance. Online surveys were conducted that targeted medium to large companies in Germany and South Africa by questioning middle to top management on issues surrounding BIS and Corporate Performance. On this basis online survey approach was taken to ensure required number of participants would be covered and approached. Therefore, the research adopted stratified sample method for the online survey. Stratified sampling enabled the expansion of the research by gathering and collaborating participants responses on the research question and eliminate the possibilities of unreliable sample from large population.

Les normes de construction pour des bâtiments de plus en plus économes en énergie (BBC) nécessitent une attention particulière. Ces normes reposent sur l’amélioration des performances thermiques de l’enveloppe du bâtiment associé à un effet capacitif des murs augmentant la constante de temps du bâtiment. La prévision de la demande en énergie de bâtiments BBC est plutôt complexe. Ce travail aborde cette question par la mise en œuvre d’intelligence artificielle(IA). Deux approches de mise en œuvre ont été proposées : « all data » et « relevant data ». L’approche « all data » utilise la totalité de la base de données. L’approche « relevant data » consiste à extraire de la base de données un jeu de données représentant le mieux possible les prévisions météorologiques en incluant les phénomènes inertiels. Pour cette extraction, quatre modes de sélection ont été étudiés : le degré jour (HDD), une modification du degré jour (mHDD) et des techniques de reconnaissance de chemin : distance de Fréchet (FD) et déformation temporelle dynamique (DTW). Quatre techniques IA sont mises en œuvre : réseau de neurones (ANN), machine à support de vecteurs (SVM), arbre de décision (DT) et technique de forêt aléatoire (RF). Dans un premier temps, six bâtiments ont été numériquement simulés (de consommation entre 86 kWh/m².an à 25 kWh/m².an) : l’approche « relevant data » reposant sur le couple (DTW, SVM) donne les prévisions avec le moins d’erreur. L’approche « relevant data » (DTW, SVM) sur les mesures du bâtiment de l’Ecole des Mines de Nantes reste performante. / High-energy efficiency building standards (as Low energy building LEB) to improve building consumption have drawn significant attention. Building standards is basically focused on improving thermal performance of envelope and high heat capacity thus creating a higher thermal inertia. However, LEB concept introduces alarge time constant as well as large heat capacity resulting in a slower rate of heat transfer between interior of building and outdoor environment. Therefore, it is challenging to estimate and predict thermal energy demand for such LEBs. This work focuses on artificial intelligence (AI) models to predict energy consumptionof LEBs. We consider two kinds of AI modeling approaches: “all data” and “relevant data”. The “all data” uses all available data and “relevant data” uses a small representative day dataset and addresses the complexity of building non-linear dynamics by introducing past day climatic impacts behavior. This extraction is based on either simple physical understanding: Heating Degree Day (HDD), modified HDD or pattern recognition methods: Frechet Distance and Dynamic Time Warping (DTW). Four AI techniques have been considered: Artificial Neural Network (ANN), Support Vector Machine (SVM), Boosted Ensemble Decision Tree (BEDT) and Random forest (RF). In a first part, numerical simulations for six buildings (heat demand in the range [25 – 85 kWh/m².yr]) have been performed. The approach “relevant data” with (DTW, SVM) shows the best results. Real data of the building “Ecole des Mines de Nantes” proves the approach is still relevant.

La complexité et l'ampleur des scénarios de l'Intelligence Ambiante impliquent que des attributs tels que l'expressivité de modelisation, la flexibilité de representation et de deploiement et la facilité de configuration et de developpement deviennent des caracteristiques centrales pour les systèmes de gestion de contexte. Cependant, les ouvrages existants semblent explorer ces attributs orientés-developpement a un faible degré.Notre objectif est de créer un intergiciel de gestion de contexte flexible et bien configurable, capable de répondre aux différents scenarios. A cette fin, notre solution est construite a base de techniques et principes du Web Semantique (WS) et des systèmes multi-agents (SMA).Nous utilisons le WS pour proposer un noveau meta-modèle de contexte, permettant une modelisation expressive et extensible du contenu, des meta-proprietés (e.g. validité temporelle, parametres de qualité) et des dépendances (e.g. les contraintes d'integrité) du contexte.De plus, une architecture a base de SMA et des composants logiciels, ou chaque agent encapsule un aspect fonctionnel du processus de gestion de contexte (acquisition, coordination, diffusion, utilisation) est developpée.Nous introduisons un nouveau moyen de structurer le deploiement d'agents selon les dimensions du modèle de contexte de l'application et nous elaborons des politiques déclaratives gouvernant le comportement d'adaptation du provisionnement contextuel des agents. Des simulations d'un scenario d'université intelligente montrent que un bon outillage construit autour de notre intergiciel peut apporter des avantages significatifs dans la génie des applications sensibles au contexte. / The complexity and magnitude of Ambient Intelligence scenarios imply that attributes such as modeling expressiveness, flexibility of representation and deployment, as well as ease of configuration and development become central features for context management systems.However, existing works in the literature seem to explore these development-oriented attributes at a low degree.Our goal is to create a flexible and well configurable context management middleware, able to respond to different scenarios. To this end, our solution is built on the basis of principles and techniques of the Semantic Web and Multi-Agent Systems.We use the Semantic Web to provide a new context meta-model, allowing for an expressive and extensible modeling of content, meta-properties (e.g. temporal validity, quality parameters) and dependencies (e.g. integrity constraints).In addition, we develop a middleware architecture that relies on Multi-Agent Systems and a service component based design. Each agent of the system encapsulates a functional aspect of the context provisioning processes (acquisition, coordination, distribution, use).We introduce a new way to structure the deployment of agents depending on the multi-dimensionality aspects of the application's context model. Furthermore, we develop declarative policies governing the adaptation behavior of the agents managing the provisioning of context information.Simulations of an intelligent university scenario show that appropriate tooling built around our middleware can provide significant advantages in the engineering of context-aware applications.

L’objectif fixé à travers ce travail, est de rechercher si l’IE existe dans le secteur des industries agroalimentaires en Algérie, et, le cas échéant, d’en déterminer les pratiques adoptées par l’entreprise, et d’étudier le mécanisme d’intervention de celles-ci dans le processus d’innovation. L’étude exploratoire des pratiques d’intelligence économique et du processus d’innovation a été effectuée dans dix entreprises agroalimentaires algériennes ; elle s’est appuyée sur l’approche qualitative et a été effectuée suivant la stratégie d’étude de cas en combinant l’observation non participante et les entretiens semi-directifs ainsi que la consultation documentaire. L’un des principaux résultats obtenus à travers notre étude est que les principaux acteurs des entreprises observées ne possèdent pas de méthodologie particulière pour l’IE formelle et structurée, mais que tous se fixent des objectifs de surveillance et de collecte d’informations. A de rares exceptions près, ce n’est qu’en situation de crise, que leurs efforts d’IE se concentrent sur le court terme, et que l’information nécessaire à la solution adéquate est recherchée dans l’urgence. En nous basant sur les apports théoriques de la littérature, nous avons défendu la thèse selon laquelle dans les processus de prise de décision et d’innovation de l’entreprise, il serait plus judicieux de prendre en considération aussi bien les pratiques d’IE formelles (systèmes, cellule de veille, …) qu’informelles (réseaux, associations, relations,…) pour une meilleure performance du processus d’innovation. Un modèle qualifié d’ « intelligence innovatrice » a été proposé et qui consiste à innover grâce à un SIE global, recouvrant toutes les pratiques d’IE et rassemblant toutes les sources d’information (formelles et informelles). Une démarche d’anticipation dictée vraisemblablement par l’évolution de l’environnement économique et social du pays suite aux effets du dernier « choc pétrolier » sur le paysage économique, a été toutefois constatée chez quelques entreprises, ce qui semble être un signe susceptible de préfigurer la mise en place, à plus grande échelle, de la pratique d’IE formelle et structurée, et son appropriation effective au sein des entreprises du secteur AA. De plus, des facteurs influençant le choix des pratiques d’IE entre formelles et/ou informelles ont été constatés dans les entreprises étudiées, à savoir : la culture de l’entreprise, la présence à l’international (l’exportation) et le niveau de la concurrence dans la filière. / This work goal is to investigate whether the Business intelligence exists in the agri-food companies sector in Algeria, and, if appropriate, to determine the practices adopted by the company, and to study their mechanism of intervention in the innovation process. The exploratory study of business intelligence practices and innovation process was carried out in ten algerian agribusiness companies; it relied on the qualitative approach and was performed according to the case study strategy by combining non-participant observation and semi-directive interviews and documentary consultation.One of the main results obtained through our study is that the main actors of the companies surveyed do not have a particular methodology for formal and structured Business Intelligence, but that all set goals for monitoring and collecting information. With rare exceptions, it is only in crisis situations, that their Business Intelligence efforts are focused on the short term, and the information required for the proper solution is sought urgently.Based on the theoretical contributions of the literature, we defended the thesis that in the processes of decision making and innovation of the company, it would be wiser to consider both formal Business Intelligence practices (systems, monitoring unit, ...) and informal (networks, associations, relationships, ...) for better performance of the innovation process. A qualified model "innovative intelligence" was proposed, which is to innovate through a comprehensive Business Intelligence system covering all Business intelligence practices and bringing together all sources of information (formal and informal).A proactive approach probably dictated by the changing economic and social environment of the country due to the effects of the last "oil shock" on the economic landscape, however, was observed in some companies, this seems to be a sign capable of foreshadow the establishment, on a larger scale, the practice of formal and structured Business intelligence, and its effective ownership in Agri-Food sector companies. In addition, factors influencing the choice of formal and / or informal Business intelligence practices were found in the companies studied: corporate culture, international presence (export), and level of competition in the sector.

Les progrès récents des technologies de l'information et de la communication (TIC) ont joué un rôle déterminant dans la transformation de la plupart des pratiques de travail traditionnelles et les structures organisationnelles. Le travail d'équipe équipes virtuelles mondiales/internationales (EVI) est un exemple. Les précédentes recherches sur les (EVI) identifient comme limite les différences culturelles et cette question doit être traitée pour une meilleure efficience de l’équipe virtuelle. Prenant appui sur l'étude de la théorie de la discontinuité de l'organisation (TDO), nous proposons l'intelligence culturelle (IC) comme l'une des modalités à travers lesquelles les discontinuités culturelles dans les EVI pourraient éventuellement être comblées. En situant le débat dans le modèle transactionnel du stress et de l'adaptation (MTSA), nous développons un réseau nomologique d’IC décrivant les interrelations et les mécanismes à travers lesquels différentes dimensions d’IC influencent la performance des EVI. En outre, tirant parti de la théorie de l'adaptation compensatoire (TAC) le rôle important de l'adaptation structurelle (IC d'adaptation) est l'hypothèse, en plus de l'adaptation comportementale (comportement d’IC), dans le cadre de l’IC proposée pour le contexte de l’EVI. Pour tester le modèle conceptuel « théorisé », l'étude utilise une conception séquentielle de la recherche reposant sur les méthodes mixtes. / Recent advances in information and communication technologies (ICTs) have been instrumental in transforming many of the traditional work practices and organizational structures. Global virtual teams (GVTs) are one such example.  Prior research on GVT identifies ‘cultural discontinuity’ as a salient boundary that needs to be bridged for better performance. Grounding the study in organizational discontinuity theory (ODT), in this research, we propose cultural intelligence (CQ) as one of the modalities through which cultural discontinuities in GVTs could possibly be bridged. Situating the discussion, in transactional model of stress and coping (TMSC), we develop a CQ nomological network describing the inter-relationships and mechanisms through which different CQ dimensions influence GVT performance. Further, leveraging compensatory adaptation theory (CAT) the significant role of structural adaptation (role structure adaptation) is hypothesized, in addition to behavioral adaptation (CQ behavior), in the proposed CQ framework for the GVT context. For testing the theorized conceptual model, the study uses a sequential mixed methods research design comprising a quantitative study followed by a qualitative The integrated findings enable us to propose a 'substantive theory of CQ for GVT performance' thereby making significant contributions to both theory and practice.

Les technologies du numérique s’invitent de plus en plus dans l’enseignement. Les nouvelles pratiques pédagogiques révolutionnent également les standards de la formation. La « gamification » des cursus est, par exemple, devenue une tendance actuelle. Elle permet, par le jeu, d’exercer les apprenants différemment. Les simulations de gestion d’entreprise entrent dans ce cadre. Elles positionnent les stagiaires à la tête d’entreprises virtuelles et simulent un marché concurrentiel. Le déploiement de cette pratique se heurte néanmoins à des difficultés opérationnelles : taille du groupe, formation de l’animateur… C’est dans ce contexte que nous envisageons la mise en œuvre d’agents autonomes permettant d’accompagner ou de concurrencer les apprenants.Pour cela, nous proposons, tout d’abord, une modélisation performante d’une entreprise à base de programmes linéaires mixtes permettant l’optimisation des départements internes des entreprises (production, distribution, finance). Ensuite, nous introduisons une heuristique de recherche locale afin de générer des solutions performantes dans un environnement économique. Aussi, à la suite d’une phase d’extraction de connaissances, nous proposons la définition et la construction d’arbres d’anticipation qui permettent de prévoir les décisions concurrentielles des protagonistes engagés et ainsi de pouvoir estimer la qualité des solutions construites. Afin de valider les approches proposées, nous les avons comparées aux comportements réels de joueurs et avons évalué l’apport de l’exploitation de la connaissance. Enfin, nous avons proposé une généralisation de la méthode à d’autres simulateurs de gestion d’entreprise. / Digital technologies are becoming increasingly popular in teaching and learning processes. New educational practices are also revolutionizing the standards of training. For example, the "gamification" of the curricula has become a current trend. It allows, through games, to exercise learners differently. Business management simulation, also known as business games, fall within this context. They place learners at the head of virtual companies and simulate a competitive market. The deployment of this practice nevertheless encounters some operational difficulties: size of the group, training of the teacher... It is in this context that we envisage the implementation of autonomous agents to accompany the learners or the competitors.To do this, firstly, we propose a modeling of a company, based on mixed linear programs allowing optimization of the internal departments of the companies (production, delivery, finance). For the second step, we will introduce a local heuristic search, ensuring a generation of efficient solutions in a given economic and competitive environment. Thirdly, following a knowledge extraction phase, we propose the definition and construction of anticipation trees that predict the competitive decisions of the engaged protagonists and thus to be able to estimate the quality of the solutions built. In order to validate the proposed approaches, we compared them with the real behaviors of players and evaluated the contribution of the exploitation of the knowledge. Finally, we proposed a framework allowing a generalization of the method to other business games.

Milling is one of the most important and common processes widely used in manufacturing industry, which is a very competitive environment. For this reason, manufacturing companies are facing many different challenges. The offering of a variety of high quality products, the restriction of production time and costs, the increase of productivity, and the need for flexibility of production are the goals that manufacturers have to consider and achieve in order to succeed in their field. These aspects relate to the process study, optimization and control, and in recent years many attempts to find possible solutions and techniques to manage these steps in a proper way have been done. The first solution that a lot of enterprises were motivated to research and utilize relates to the application of the finite element modeling (FEM) techniques to study manufacturing processes or to highlight behaviour of products, for example of cutting tools, during the design phase. The second technique deals with the manufacturing process control, and is aimed at the increasing of automation level of modern production systems by evolving them towards the paradigm of Intelligent Manufacturing. The present work is focused on the study and evaluation of the effectiveness of both techniques. The first part of the research presented in this thesis is dedicated to the study of the application of Intelligent Manufacturing Systems to milling processes. In particular, in the Chapter 1 it is discussed the improvement of the artificial operator called Evaluation and Perception Controller (EPC) built by the Mechatronics group of the University of Trento within the national project Michelangelo in 2013. In this thesis it is proposed to improve the performance characteristics of the EPC system in terms of the process quality, described by the surface roughness value. In particular, it is proposed to associate the surface roughness term to the scallop height value, and to include a model that describes the mechanism of scallop height formation into the Optimal Control Problem formulation. Chapter 2 of this work is related to the application of FEM techniques to study milling processes. In particular, in this section the influence of CAD cutting tool models (STEP and STL) on 3D FEM AdvantEdge prediction accuracy in terms of the average and maximum cutting forces, and deformed chip thickness and curvature radius values are studied. In addition, this part of the thesis includes also the discussion of the problems related to the application of 2D FEM modeling techniques to study the influence of cutting tools geometries on the feed and tangential cutting forces that act in three-dimensional cutting processes. Chapter 3 of this thesis is dedicated to the development of a model suitable for prediction of cutting forces that act in non-tilted and tilted side down-milling processes performed with end mills. The development of this model has two purposes. First of all, it can be included into the EPC controller, thus extending the field of the possible applications of this system. The second purpose relates to the fact that in case the side down-milling process simulations are performed by using cutting forces coefficients identified based on 2D FEM cutting forces data, the proposed model allows to overcome the mismatches between real processes and 2D FEM, and to simulate two cutting forces, feed and normal, arising in three-dimensional processes.

No description available.

The decision-making process (DMP) is based on two elements: Organizational and technical (Poleto et al., 2015). The organizational element is related to managers’ everyday decisionmaking based on the organization strategy (Poleto et al., 2015). Its aim is to set up specific actions for the planned objectives for the business (Rouse, 2018). The second element is the technical DMP. According to (Poleto et al., 2015), it is related the set of tools that are used as an aid in the DMP, which includes information technology and big data. Business intelligence (BI) is the decisionmaking helping system (Ali et al., 2017). Consequently, BI helps make better decisions, and it has become popular in many organizations. As a result, it is important to show BI’s power over DMPs and to show how the tools used in BI facilitate the DMP. “Higher education institutions worldwide are operating today in a very dynamic and complex environment” (Kabakchieva 2015, p. 104). As a result, universities that are within higher education are threatened because competition is serious (Barrett, 2010). Moreover, higher education is another area that will potentially impact big data research (Ong, 2016). Consequently, the application and use of big data in higher educational institutions may result in better quality education for students and a better experience for the university staff (Ong, 2016). As a result, HEI is adopting new technologies with the aim of sustaining its position on the market. DMPs at higher academic institutions require structured data from a sophisticated system, which can be only done through efficient and effective use of BI tools. This thesis will investigate how the BI system is used at Linkoping University (LIU) and how its benefits have changed DMPs. We studied the BI tool (Qlikview) that has been used at LIU for 10 years. 10 To answer the research question, a theoretical framework was developed that was based on two models: Simon’s (1997) and Huber’s (1980) DMP models. The two models were combined with the BI benefits that were based in El Bashir et al.’s (2008) model. The research is done through a qualitative method of data collection and data analysis. At LIU, seven interviews were conducted with BI users and with strategic decision-makers. The findings show that the BI system, alongside Qlikview, has a positive effect on DMPs at LIU as a public HEI. The factors affected are the information gathering time, the quality of data provided and the accessibility to information by all BI users.

Yes / As big data (BD) and data analytics having gain significance the industry expects helping executives will eventually move towards evidence based decision making. The hope is to achieve more sustainable competitive advantage for their organisations. A key question is whether executives make decisions by intuition. This leads to another question whether big data would ever substitute human intuition. In this research, the ‘mind-set’ of executives about application and limitations of big data be investigated by taking into account their decision making behaviour. The aim is to look deeply into how BD technologies facilitate greater intuitiveness in executives, and consequently lead to faster and sustainable business growth.