Saji K Mathew

Firms across the industry segments have been exploring cloud computing to derive benefits out of its technological features. Even though literature pertaining to cloud adoption by firms exists, the factors based on cloud-specific characteristics are mostly anecdotal in nature. Following a multiple case study approach, we identify factors specific to cloud technology adoption by firms. We further explain the differential adoption of the cloud between large and small firms. Overall we obtained 11 variables that differentiate large firms and SMEs in their adoption behavior. We further contribute to theory by mapping the extracted variables of cloud adoption to Diffusion of innovation theory (DOI) and Technology organization Environment framework (TOE).

Cloud computing1 services have gained a lot of attraction in the recent years, but the shift of data from user-owned desktops and laptops to cloud storage systems has led to serious data privacy implications for the users. Even though privacy notices supplied by the cloud vendors details the data practices and options to protect their privacy, the lengthy and free-flowing textual format of the notices are often difficult to comprehend by the users. Thus we propose a simplified presentation format for privacy practices and choices termed as "Privacy-Dashboard" based on Protection Motivation Theory (PMT) and we intend to test the effectiveness of presentation format using cognitive-fit theory. Also, we indirectly model the cloud privacy concerns using Item-Response Theory (IRT) model. We contribute to the information privacy literature by addressing the literature gap to develop privacy protection artifacts in order to improve the privacy protection behaviors of individual users. The proposed "privacy dashboard" would provide an easy-to-use choice mechanisms that allow consumers to control how their data is collected and used.

Cloud computing is widely advertised as a technology-based service model and an emerging business model which is highly beneficial for the adopting organizations. But, academic landscape lacks sufficient empirical studies of cloud adoption at firm-level, and the existing cloud adoption factors are mostly anecdotal in nature. A multiple case study approach was used to extract and compare adoption characteristics of SMEs and large firms in Germany, based on the Technology-Organization and Environment (TOE) framework. The study shows that there exist important differences between SMEs and large enterprises regarding the cloud adoption factors. The results further show that large firms perceive characteristics of the cloud to be more complicated and not easy to implement compared to SMEs which contradicts the popular belief that large firms are forerunners in adopting innovations and, the widely publicized cost benefits of cloud services are perceived to be in favor of SMEs.

With increasing maturity of analytical software tools, many companies deploy at least basic forms of business analytics to improve data-based decision making. Research about analytics in the field of information systems is currently scarce. While existing work primarily focused on capabilities for successful implementations, no attention has been paid to the role of the IT department. The goal of this paper is to explore and validate different roles of how the IT unit contributes to business value for business analytics. The proposed research model draws from the resource-based view and IT management theory. It provides a comprehensive summary of critical resources that are derived from literature. Preliminary results of case studies with nine CIOs and senior IT executives confirm the presence of four typological profiles for the IT. In a next step, we plan to formulate hypothesizes and empirically validate the model.