I am a graduate student in Communication Studies at New Mexico State University whose work examines how people and organizations make decisions, interpret evidence, exercise judgment, and communicate under conditions of uncertainty and change.
My research sits at the intersection of organizational communication, leadership, decision-making, behavioral science, and technology. Across projects, I am especially interested in a recurring problem: what happens when organizations mistake a useful strength, metric, model, or tool for something that works universally, regardless of context?
That question connects several current areas of work. Strength Overshoot examines how leadership strengths may become counterproductive when they are applied beyond the point at which a situation benefits from them. Other projects examine employee voice and employer recommendation, the use and limitations of NPS and eNPS, and how organizations can choose AI and machine-learning segmentation approaches based on the decision they need to support rather than technical precision alone.
My work also explores broader questions involving leadership framing, managerial judgment, organizational change, talent management, and the relationship between technical systems and the people who use them.
Alongside my academic work, I bring more than two decades of professional experience in marketing, growth strategy, customer analytics, loyalty, lifecycle marketing, segmentation, and organizational transformation. That practitioner background shapes my interest in research that connects communication theory and behavioral insight with consequential problems faced by organizations, leaders, customers, and employees.
Current Research and Projects
- Strength Overshoot — a developing conceptual framework examining when leadership strengths become counterproductive
- Employee Voice and Employer Recommendation — analysis of 604,320 public workplace reviews examining ratings, narrative employee voice, and firm-level variation
- Net Promoter Score and eNPS — research on how recommendation metrics diffuse, what they measure, and what organizations may infer from them
- AI/ML Segmentation for Marketing Decisions — research on selecting segmentation models based on decision fit rather than technical performance alone
- Organizational Decision-Making and Leadership — work on framing, judgment, negotiation, and the assumptions that shape managerial choices
Research Interests
- Organizational communication
- Leadership and organizational behavior
- Decision-making and managerial judgment
- Employee voice and employee experience
- Behavioral science
- Artificial intelligence and technology adoption
- Customer and audience segmentation
- Measurement and organizational metrics
- Organizational change and transformation
Use the links on this site to learn more about Patrick Diogenia’s biography, current research, professional background, and ongoing projects.
This is a personal website. The views expressed here are my own and do not represent the views of CVS Health or its affiliates.