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Data value creation of Industry 4.0 : an empirical study of Quebec’s manufacturers / La création de valeur des données de l’Industrie 4.0 : une étude empirique dans les manufacturiers québécoisBordeleau, Fanny-Ève January 2018 (has links)
Abstract : Manufacturing companies in developed countries face a digital transformation that is meant to improve their productivity, but also produces a large volume of data. This data will go to waste if it is not valorized by using it to gain actionable insights, for example with business intelligence and analytics. This master’s thesis presents a systematic literature review and a multiple case-study on the subject of Business Intelligence in manufacturing companies. The first article, “Business Intelligence in Industry 4.0: Research opportunities”, present a literature review. Results show a lack of studies on the impacts of business intelligence activities on manufacturing small and medium enterprises. The strategic impacts should be studied, since they are often neglected in favor of the operational impacts such as quality improvement and operating costs reductions. The second article, “Business intelligence value creation: A multiple case study in manufacturing SMEs”, presents an exploration of the factors influencing strategic and operational business values of business intelligence. Results show the limit of the traditional models based on the Resource-Based View of the firm, which overlooks organizational factors that might be more important in smaller organizations. Contingency factors, such as organisational learning, leadership style, and the role of the owner, should be included when studying small and medium enterprises, as in these smaller organizations the lack of resources and the simpler structure affect business value of business intelligence and analytics systems differently than in larger firms. There is an interesting potential for the model suggested in this master’s thesis to understand the factors linked to business value creation in smaller organization, which should be empirically tested with a larger and more diverse sample in a future study. / Ce mémoire présente les travaux réalisés dans le cadre de ma maîtrise en
Stratégie de l’intelligence d’affaires, de l’École de Gestion de l’Université de
Sherbrooke. Il consiste en deux articles. Le premier est une revue de littérature
systématique ayant été soumise et acceptées à la 51e
édition de Hawaii International
Conference on System Sciences, qui a eu lieu du 3 au 6 janvier 2018. Il est présenté
intégralement au chapitre deux. Le second article, présenté dans sa version longue au
chapitre trois, a été soumis à la 7e
édition de International Conference on Information
Systems, Logistics and Supply Chain qui aura lieu du 8 au 10 juillet 2018. Les notices
d’acceptation seront envoyées après la date de dépôt de ce mémoire. Toutes les preuves
de soumissions sont présentées dans les annexes de ce mémoire. Les articles ont tous
été rédigé par moi, Fanny-Ève Bordeleau, qui a également réalisé toutes les prises de
données et les analyses, assistée de mes co-directeurs, les professeurs Elaine Mosconi
et Luis Antonio De Santa-Eulalia.
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