Graduation Semester and Year
Summer 2024
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Information Systems
Department
Information Systems and Operations Management
First Advisor
Dr. Sridhar Panchapakesan Nerur
Second Advisor
Dr. Radha Mahapatra
Third Advisor
Dr. Abdul Rasheed
Fourth Advisor
Dr. Mahmut Yasar
Abstract
Understanding the dynamics and predictors of patent litigation is crucial in intellectual property management, especially given the competitive edge patents offer companies. Also, patents serve as both legal tools and repositories of innovation. This research delves into the complex world of patent litigation within the pharmaceutical industry, focusing on creating and applying advanced computational models to study litigation propensities. Techniques such as Graph Neural Networks (GNN), Agent-Based Modeling (ABM), and Bayesian Analysis of Network Autocorrelation Models (BANAM) are employed to explore the litigation phenomenon
Keywords
GNN, Deep learning, ABM, BANAM, Patent litigation, Network theory
Disciplines
Artificial Intelligence and Robotics | Business Analytics | Business Intelligence | Data Science | Intellectual Property Law
License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Gopinathan, sreehas, "A COMPREHENSIVE STUDY OF PATENT LITIGATION IN THE PHARMACEUTICAL SECTOR: EMPLOYING NETWORK THEORIES, GRAPH NEURAL NETWORKS, AGENT BASED MODELING, BAYESIAN NETWORK AUTOCORRELATION MODELS" (2024). Information Systems & Operations Management Dissertations. 54.
https://mavmatrix.uta.edu/infosystemsopmanage_dissertations/54
Included in
Artificial Intelligence and Robotics Commons, Business Analytics Commons, Business Intelligence Commons, Data Science Commons, Intellectual Property Law Commons
Comments
I am immensely grateful to Dr. Sridhar Nerur, my dissertation committee chair, for
his unwavering support and encouragement throughout my Ph.D. journey. His guidance
has been invaluable, and I am deeply indebted to him. I also extend my heartfelt thanks
to Dr. Mahapatra for his pivotal advice and guidance during crucial phases of my doctoral
studies. Both of their patience, support, and guidance were essential to completing this
research.
I would like to sincerely thank Dr. Abdul Rasheed for his profound theoretical
insights and expertise in the domain. His guidance has been a cornerstone of my academic
development. Additionally, I am thankful to Dr.Mahmut Yasar for his extensive technical
knowledge and assistance in navigating the complexities of my analytical work, which was
crucial for this research.Both of them were an awe inspiring presence during my research
and deeply indebted for all time and effort they have put forth.
I would also like to acknowledge Minesoft for granting access to patent data platform
which has been very valuable and played a critical role in successful completion of
this research