Explaining organizational adoption of technology : the case of cloud platforms

The internet of things (IOT) is a vision that represents a world of connected devices which are identifiable and may have capabilities to sense and act on the surrounding environment. Almost every item in the planet has the potential to become part of the IOT. The data exchange between these devices requires that cloud technologies are applied. These cloud computing platforms already exist and need to adapt to the specific needs of the IOT in order to cope with the high demands of the IOT, for example handling the Big Data generated by the IOT devices. Nonetheless, little is known about the adoption levels of these platforms. In the past the UTAUT2 has been used to help explain technology adoption. However, the UTAUT2 was developed to explain consumer adoption, failing to investigate organizational adoption of technology. Furthermore, the role of the manager of the organization, a crucial one in the decision making process, has not been taken into account. Moreover, in the context of studying cloud computing the construct of Security needs to be taken into account to better investigate the adoption of this technology. The UTAUT2 does not include Security as a construct. The objective for this thesis is to explain the adoption of cloud for IOT by organizations. For this purpose a new framework derived from UTAUT2 is proposed. This framework modifies the UTUAT2 by replacing Hedonic Behavior with Eudaimonic Well-Being and extends it by including Security as a construct. The modified framework has been empirically validated by using a survey that had been administered to a panel of managers from ICT companies from Finland. The results confirmed that the framework is useful in discovering the adoption of technology by organizations when considering the manager as an influencer of the decision to adopt and that the new constructs contribute positively towards the Behavioral Intention to use the technology, specifically in the case of cloud computing for IOT.