Presentation Schedule
The Architecture of Wise Decisions: A Grounded Theory for High-Stakes Leadership (102530)
Session Chair: Shirley Ho
Thursday, 26 March 2026 10:55
Session: Session 2
Room: Room 705 (7F)
Presentation Type: Oral Presentation
Introduction: Behavioral economics and decision science have long revealed the limits of Homo economicus. In our research, Wise Decision-Making (WDM) is introduced as a mixture of cognitive traits and deliberative processes. Using the Grounded Theory Approach, we construct the new WDM model that incorporates otherwise neglected ethical and affective aspects.
Objective: We aim to construct a theory of Wise Decision-Making (WDM) by outlining the main processes, antecedents, and moderators for wise leadership decisions in complex, high-stakes environments.
Methods: An exploratory research design that involved in-depth interviews was used. To gain insights into critical judgment, we constructed a protocol that diminished biases. The design consists of three phases: Unprimed Recall-Primed Exploration-Post-Priming Synthesis.
This protocol was tested for clarity by expert raters. We interviewed 50 male and female leaders of high responsibility, including surgeons, bureaucrats, judges, and military officers.
Analysis & Results: Narrative data was coded according to the Gioia method, proceeding from first-order codes to second-order themes and aggregate dimensions to build grounded theory from transcripts of interviews. For example, the codes "stepping back before acting" and "checking multiple viewpoints" constructed the theme of reflective deliberation under "metacognitive regulation." Likewise, "considering downstream effects" and "managing competing obligations" generated the theme "ethics of foresight," and the second-order dimension "moral framing."
Conclusion and Future Directions: Initial analysis refutes simple rational-actor scenarios, showing that WDM is connected to meta-cognition, ethical foresight, and emotional regulation. To fortify the model, it is important to extend the dataset, resulting in a more accurate WDM model.
Authors:
Jyoti Sharma, Indian Institute of Technology Jodhpur, India
About the Presenter(s)
Ms. Jyoti Sharma is currently a PhD scholar at the Indian Institute of Technology Jodhpur, Rajasthan, in India.
See this presentation on the full schedule – Thursday Schedule
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