Having a modern Enterprise Resource Planning (ERP) system is seen as increasingly important if an organisation wants to compete in today’s business environment. The implementation of a new ERP system can result in added automatization and the replacement and/or coupling of legacy systems. The replacement and coupling of legacy systems can help an organisation increase data integrity and accessibility by lowering data fragmentation. Previous research on the topic of ERP implementations has emphasized user participation as an important factor when aiming to succeed with an implementation. The research is however inconsistent with its use of participation and involvement where involvement is often used synonymously with participation, but sometimes it signifies that the implementation is of personal importance to the user. This study defines user participation as the user partaking in activities relating to the implementation, and user involvement is defined as the user perceiving the project or system as important. This study also introduces a new term: user inclusion, which encompasses both user participation, and if a user is on the receiving end of one-way communication, for example when receiving a newsletter. This study argues that symbolic adoption, the belief that implementing the system is a good idea, is an important part of system success and uses a combination of factors from the UTAUT model and the I/S success model as antecedents to the dimensions of symbolic adoption that has been presented in previous research. The purpose of this study is to examine how users are included in ERP implementation processes, and how their inclusion in the process affects users’ symbolic adoption. To address this purpose, a qualitative multi-case study that included two cases was conducted. In order to answer how users are included, this study divides how into three sub-questions; who; when and in what way users were included throughout the implementation. ​This study concludes that users’ inclusion increases over time throughout the implementation process, both in terms of influence, and in number of participating users. This study also shows that users included in project initiatives can affect the antecedents to symbolic adoption in various ways, both their own symbolic adoption, and that of their non-participating colleagues. An example of this is how intended users’ expectations can be managed through communication and when they get first-hand experience of the system, their expectations correct themselves so that they are closer to the actual performance and effort required. The antecedents, performance and effort expectancy, are in turn linked to the symbolic adoption dimension effort worthiness.

Les centres de calcul cloud consomment d'importantes quantités d'énergie et il devient nécessaire de réduire leur consommation en raison des changements climatiques actuels. Bien que des propositions d'optimisations énergétiques existent, elles ne tiennent pas compte des utilisateurs finaux. Cette thèse propose d'inclure les utilisateurs cloud dans l'optimisation énergétique afin de réduire la consommation d'énergie des centres de calcul. L'inclusion se fait, dans un premier temps, en délivrant une information énergétique pour sensibiliser, puis dans un second temps, en fournissant des moyens d'action. Les contributions portent sur les couches cloud IaaS et PaaS. Nos résultats montrent que les utilisateurs tolérants à la variation des performances (e.g. retarder l'obtention de résultats) permettent de réduire la consommation d'énergie des centres de calcul. / Cloud datacenters consume large amounts of energy and it becomes necessary to reduce their consumption due to current climate changes. Although energy optimization propositions exist, they do not take into account end-users. This thesis proposes to include cloud users in the energy optimization as a means to reduce datacenters energy consumption. The inclusion is done, first, by delivering energy related information to raise awareness, and second, by providing means of actions. Contributions are located at IaaS and PaaS cloud layers. Our results show that users tolerant to performance variation (e.g. delay in obtaining execution results) allow to reduce datacenters energy consumption.