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Manjunath Paramashivaiah

DBA Graduate - 2019

Thesis title



Federico Pigni
This research examines factors that facilitate or inhibit organizational adoption of Real-time Digital Data Streams (DDS). Very little academic and empirical research has been conducted on adoption of DDS at an organizational level. Most of the research on DDS has been conceptual and clear focus on value addition provided by DDS and organizational readiness. Previous research clearly suggests that DDS has enormous potential for organization willing to exploit it. Further research can allow organizations to make data-based decisions to use DDS to improve business processes, improve existing products and services, and create new products and services. DDS provides new opportunities for businesses to create value, so it is important for practitioners and academics to fully understand how environmental, organizational, and innovation factors influence DDS adoption. This study aims to improve the understanding of how organizational, environmental and innovation factors influence an organization’s decision to adopt DDS following an integrated research methodology. In the first phase of the research, case studies were conducted with four representative innovative companies, and the analysis revealed that organizations with high-risk acceptance in their culture were likely to embrace new innovations. These organizations were unconcerned with failure and the complexity and incompatibility of an innovation only had a limited effect on the organization’s willingness to adopt. They reported that they would rather be trend-setters than followers (Paramashivaiah & Pigni, 2015). In the context of these studies, established adoption models are limited in their ability to explain and predict organizational adoption. This study improves the applicability of organizational adoption theories by employing an integrative model using historical methods to elicit dimensions emerging from a single case study on Ultimate Software. Results are discussed in the context of current literature. The analysis of historical data and oral interviews of participants at Ultimate Software reveled new emerging factors such as organizational culture, people-first culture, fear of failure & risk acceptance, family like environments. These elements incorporated within existing organizations as well as newly formed organizations will have positive influence in organizational adoption of innovations. This was demonstrated at Ultimate Software. Re-evaluating and expanding the resulting framework or model as well as incorporating historical methods and applying these on larger audience is a potential future research suggestion. Key Words: Innovation Diffusion Theory, Ultimate Software, Digital Data Streams, Historical Methods