Pre-Conference Workshop

AI-Assisted Research Discovery: From Broad Interest to a Focused, High-Impact Research Topic

DESCRIPTION:

This hands-on workshop shows how AI can help researchers transform a broad interest into a focused, relevant, and researchable topic using the PGVC Framework: Problem, Gap, Value, and Contribution. Participants will use structured prompts to narrow topics, explore and critique potential research gaps, develop literature-search strategies, and refine research questions, titles, and contribution statements. AI-generated suggestions will be treated as starting points that require verification through peer-reviewed literature.

KEY TAKEAWAYS:

  • Apply AI within the PGVC Framework to move from a broad research interest to a focused problem, preliminary gap, research value, and contribution.
  • Use structured prompts and prompt chains to narrow topics, generate alternatives, challenge assumptions, and improve research focus.
  • Use AI to develop search keywords, synonym clusters, Boolean search strings, and a literature-based gap-validation plan.
  • Critically evaluate AI-generated research gaps and distinguish between an AI suggestion and a gap verified through peer-reviewed evidence.
  • Leave with a focused research question, working title, contribution statement, and one-page AI-assisted research discovery blueprint.

Click to Watch: https://go.screenpal.com/watch/cOiUDDnv1pt

AI-Assisted Theory Building: From Research Question to Conceptual Framework and Hypotheses

DESCRIPTION:

This practical workshop demonstrates how AI can support theory building through the QTMC Framework: Question, Theory, Model, and Contribution. Participants will use structured prompts to compare theoretical perspectives, clarify mechanisms, assign appropriate roles to variables, develop conceptual models, and refine hypotheses and contribution statements. AI will serve as a critical thinking and review assistant, while all theoretical claims and relationships remain subject to scholarly verification.

KEY TAKEAWAYS:

  • Apply AI within the QTMC Framework to connect the research question, theoretical lens, conceptual model, and scholarly contribution.
  • Use theory-comparison prompts to evaluate theories based on mechanism fit, level of analysis, construct alignment, boundary conditions, and contribution potential.
  • Use AI to determine whether variables should function as predictors, outcomes, mediators, moderators, or boundary conditions.
  • Generate, compare, simplify, and stress-test conceptual models and hypotheses using AI-assisted reviewer and critique prompts.
  • Leave with a refined research question, defensible theoretical lens, conceptual framework, draft hypotheses, and clear contribution statement.

Click to Watch: https://go.screenpal.com/watch/cOiUDOnv15l

Speaker: Dr. Syed Haider Ali Shah

Assoc. Prof. Dr. Syed Haider Ali Shah is an Associate Professor in the Department of Business Administration at Abdullah Gül University in Kayseri, Türkiye. He earned his PhD from the University of Malaya, Malaysia, in 2017. His principal research areas include leadership, organizational behavior, sustainability, entrepreneurship, and innovation.

His broader research and training interests include green human-resource practices, corporate social responsibility, pro-environmental behavior, responsible leadership, artificial intelligence, research design, tourism and hospitality, and sustainable development. Before joining Abdullah Gül University, he served at Bahria Business School, Bahria University Islamabad. He has more than eleven years of combined academic and industry experience and has delivered research-development and capacity-building workshops for academic audiences.

His work is characterized by a strong interest in connecting theoretical knowledge with practical research development. Through interactive demonstrations, structured frameworks, and applied examples, he supports students and researchers in transforming emerging ideas into more focused, theoretically meaningful, and publication-oriented research projects.