dc.contributor.advisor | Beard, Cory | |
dc.contributor.author | Tonhozi de Oliveira, Pedro | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017 Summer | |
dc.description | Title from PDF of title page viewed August 27, 2018 | |
dc.description | Dissertation advisor: Cory Beard | |
dc.description | Vita | |
dc.description | Includes bibliographical references (pages 119-138) | |
dc.description | Thesis (Ph.D.)--School of Computing and Engineering and Bloch School of Management. University of Missouri--Kansas City, 2018 | |
dc.description.abstract | The advances of the future will demand scholars have a systemic vision to solve problems. Integration across disciplines is needed to study, explain, inquire and discover
beyond the traditional borders of academic areas. In this research,we consider the effects
of crowd behavior in wireless networks and funding. First,we seek to demonstrate how to
improve the allocation of wireless network resources based on the use of aggregate data
from crowds’ mobile phones and dynamically improve the wireless network around them.
The data is used to develop an optimization allowing a more efficient management of the
network. Second,using tool sets from engineering and entrepreneurship,we study the interaction of herding and speed to goal towards success on the crowdfunding environment
using the liability of newness as a theoretical lens. Finally, we advance entrepreneurial
crowdfunding literature through developing a new framework to understand the different
paths to success.
One of the challenges of deploying dense networks is unpredicted human mobility
behavior. Today, the static allocation of carriers results in a suboptimal use of spectrum
resources. In this essay, we introduce the concept of Dynamic Carrier Allocation as the
ability of dynamically move carriers from one cell to another based on the demand. Simulation results demonstrate on average 25% higher efficiency when compared with the
previous static allocation schemes.
Crowdfunding has become a popular substitute for traditional sources of funding
for new ventures. While some research has been done to explain the reasons an entrepreneur is successful in this environment, the understanding of the interaction between
the early and late stages of the campaign still cloudy. In this essay, we use the liability of
newness theory and over 2,400 crowdfunding projects to discuss the connection between
the timing of the herding effect and the speed in which the campaign is funded. We also
look how the size of the goal moderates this effect. Then, we propose a taxonomy for the
different paths towards crowdfunding success. The conceptual and empirical findings of
this work extend our understanding of entrepreneurial legitimacy and the roles played by
early stage funding strategies in overcoming internal and external liabilities of newness. | eng |
dc.description.tableofcontents | Introduction -- Optimal dynamic carrier allocation for future wireless networks -- Alternative pathways to succeed in rewards-based crowd-funding campaigns -- Conclusion and future research -- Appendix A.Mathematical justification of efficiency distribution -- Appendix B. Tutorial in Web scraping kickstarter | |
dc.format.extent | xii, 140 pages | |
dc.identifier.uri | https://hdl.handle.net/10355/64515 | |
dc.publisher | University of Missouri -- Kansas City | eng |
dc.subject.lcsh | Collective behavior | |
dc.subject.lcsh | Wireless communication systems | |
dc.subject.lcsh | Crowd funding | |
dc.subject.other | Dissertation -- University of Missouri--Kansas City -- Computer science | |
dc.subject.other | Dissertation -- University of Missouri--Kansas City -- Business administration | |
dc.title | Understanding and Adapting to Crowd Behavior: A Study of Wireless Networks and Entrepreneurial Crowdfunding | eng |
dc.type | Thesis | eng |
thesis.degree.discipline | Telecommunications and Computer Networking (UMKC) | |
thesis.degree.discipline | Entrepreneurship and Innovation (UMKC) | |
thesis.degree.grantor | University of Missouri--Kansas City | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Ph.D. | |