Publications
This Publications page presents the doctoral research, academic scholarship, and technical publications of Dr. Alan F. Castillo, DM/IST, focused on Generative AI, applied data science, cloud security, and federal mission outcomes. These works provide verifiable evidence of subject-matter expertise and contribute to the broader advancement of secure, compliant, and operationally effective AI systems.
Each publication listed here includes formal citation information and, where available, an official repository link to support academic verification, procurement validation, and professional reference.
Featured Doctoral Dissertation
The following dissertation represents the culmination of doctoral research in Information Systems and Technology, providing original contributions to the field and establishing a foundation for ongoing research and federal mission applications.
A Quantitative Study of the Relationship Between Leadership Practice and Strategic Intentions to Use Cloud Computing
Author: Dr. Alan F. Castillo, DM/IST
Institution: University of Phoenix
Year: 2014
Repository: ProQuest Dissertations & Theses Global
Publication Number: 3583230
Purchases and access are securely handled by ProQuest. Pricing and format options are displayed on the ProQuest website.
Abstract
This doctoral research examined the relationship between leadership practice, attitudes toward business process outsourcing, and strategic intentions to use cloud computing. The purpose of this quantitative correlational, cross-sectional study was to evaluate how leadership behavior influences enterprise cloud computing adoption decisions.
The study surveyed Information Technology managers and directors from medium-sized enterprises across multiple industries in the United States. Using Structural Equation Modeling (SEM), the research tested a theoretical model examining the relationships among leadership practice, outsourcing attitudes, and cloud computing adoption intentions.
The findings revealed that leadership practice was positively correlated with strategic intentions to use cloud computing, while attitudes toward outsourcing were positively correlated with cloud computing adoption intentions but did not mediate the relationship between leadership and adoption. These results provide insight into how leadership behavior influences strategic technology adoption decisions. [oai_citation:0‡ERIC](https://eric.ed.gov/?id=ED557435)
This research contributes to academic and professional understanding of how leadership influences enterprise cloud adoption and provides practical implications for organizations seeking to optimize business processes and achieve strategic advantage through cloud computing.
Research Contributions
- Original research: Provides new knowledge and analysis in the field
- Operational relevance: Supports real-world implementation and governance
- Evidence-based findings: Derived from formal research methodology
- Federal mission alignment: Applicable to government and enterprise environments
Citation
Technical Research and Professional Writing
These technical works provide practical implementation guidance for organizations adopting advanced technologies, including artificial intelligence, cloud computing, and secure system architectures.
Research Areas
- Generative AI systems and governance
- Cloud computing and secure architecture
- Applied data science and machine learning
- Federal technology modernization
- Cybersecurity and risk management
Academic and Research Profiles
Dr. Castillo maintains verified academic and professional profiles to ensure research transparency, citation accuracy, and entity verification across scholarly and professional systems.
Research and Technical Publication Areas
Dr. Castillo’s research and technical publications support the advancement and secure implementation of modern technology systems.
Primary research domains
- Generative Artificial Intelligence and Autonomous Systems
- Cloud Computing Architecture and Adoption
- Cybersecurity and Zero Trust Architecture
- Applied Data Science and Machine Learning
- Federal and Defense Technology Modernization
Academic Authority and Professional Expertise
Dr. Alan F. Castillo is a doctoral-level technology leader, Generative AI Data Scientist, and federal technology expert specializing in artificial intelligence, cloud computing, and secure system architecture.
His academic work and applied research support federal agencies, defense missions, and enterprise organizations implementing advanced technology systems.
Use and Citation of These Publications
These publications may be cited in academic research, government proposals, technical documentation, and professional analysis. Proper citation ensures accurate attribution and academic integrity.
Contact and Research Collaboration
For research collaboration, speaking engagements, or consulting related to these publications, please visit the Contact page .
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Publications FAQ
Where can I access or purchase the dissertation?
The official version of the dissertation is available through ProQuest Dissertations & Theses Global, the primary academic repository for doctoral research. Abstract and reference information are also available through the ERIC (Education Resources Information Center), a publicly accessible database sponsored by the U.S. Department of Education.
Is this an officially published doctoral dissertation?
Yes. This dissertation was completed as part of the Doctor of Management in Information Systems and Technology (DM/IST) program at the University of Phoenix and is formally archived in recognized academic repositories, including ProQuest and ERIC.
How should this research be cited?
Citation information is provided on this page in APA 7 format. Researchers, students, and professionals are encouraged to cite the work using the official academic citation to ensure proper attribution.
What topics does this research cover?
This research focuses on cloud computing adoption, leadership practices, and technology strategy, with implications for enterprise organizations, federal agencies, and technology leaders responsible for modernization initiatives.
Can federal agencies and organizations reference this research?
Yes. This research may be referenced in federal proposals, technical documentation, academic publications, and professional analysis, subject to standard academic citation practices.