Date of Graduation
Doctor of Philosophy in Business Administration (PhD)
Second Committee Member
Third Committee Member
Social sciences, Applied sciences, Big data, Business model, New venture, Social media, Social networks
New information technology (IT) ventures are at the forefront of developing IT innovations. In spite of their importance in the advancement of IT and the unique risks of survival that distinguishes them from established firms, the organizational literature on IT has mostly overlooked new IT ventures. Specifically, Big Data industry is a context where new IT ventures actively change the landscape of IT innovations. However, less is known about the factors influencing the economic success of Big Data ventures (BDVs), as well as the established firms that invest in them. To shed light on these factors, three essays are designed and executed.
The first essay investigates the value proposition of a BDV’s product/service as an important constituent of its business model and seeks to understand how it affects the capital raised by BDVs in their early stages of development. Then, the second essay is concerned with the role that the network embeddedness of a BDV plays in its success. Building on the notion of Socially-constructed innovations, this essay examines the suitable network structures that help BDVs succeed. Finally, the third essay focuses on a BDV’s strategy in management of its communication with the potential investors on Social media platforms. In this essay, we extend the previous literature that had highlighted the importance of the verbal content of communication on Social media platforms for a new venture’s success and in turn focus on the non-verbal aspects of communication in Social media. Building on the notion of symbolic actions to theorize about non-verbal communication, we focus on the sequence of message narrators in Social media and investigate the different tactics BDVs follow to raise capital.
Havakhor, T. (2016). Big Data and Organizational Impacts: A Study of Big Data Ventures. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/1763