The Bounded Deliberation-Decision Feasibility Theory (BDDFT)

This paper proposes the Bounded Deliberation-Decision Feasibility Theory (BDDFT), a two-branch research framework designed to investigate how analytical refinement, information acquisition, resource expenditure, and delay interact with the availability of a usable decision under a finite deadline, focusing primarily on the Analytical Refinement-Decision Availability Paradox (ARDAP). Branch I, the Analytical Refinement-Decision Depletion Model (ARDDM), describes conditions where additional analysis can improve a decision's estimated quality while raising the probability of missing its operational deadline, whereas Branch II, the Bounded Deliberation-Adaptive Decision Regulation Model (BDADRM), outlines candidate control policies for deciding whether to continue analysis, acquire information, stop, escalate, or invoke a fallback action. The framework keeps decision quality, epistemic uncertainty, risk, resource expenditure, delay loss, and decision availability distinct, establishing a state representation, a constrained objective, an operational divergence indicator, an optimal-stopping formulation, twelve analytical layers, and eight core domains for interdisciplinary investigation. Emphasizing a conditional research claim, the work provides a formal research program, falsifiable hypotheses, baseline comparisons, boundary conditions, and reproducibility requirements without treating unperformed experiments as evidence.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-26
DOI
https://doi.org/10.5281/zenodo.23674546
Primary Topic
Decision-Making and Behavioral Economics
Type
preprint
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preprint

The Bounded Deliberation-Decision Feasibility Theory (BDDFT)

Shamiul Hoque Shan
Zenodo (CERN European Organization for Nuclear Research)
Decision-Making and Behavioral Economics
preprint

The Bounded Deliberation-Decision Feasibility Theory (BDDFT)

Shamiul Hoque Shan
preprint en

Abstract

This paper proposes the Bounded Deliberation-Decision Feasibility Theory (BDDFT), a two-branch research framework designed to investigate how analytical refinement, information acquisition, resource expenditure, and delay interact with the availability of a usable decision under a finite deadline, focusing primarily on the Analytical Refinement-Decision Availability Paradox (ARDAP). Branch I, the Analytical Refinement-Decision Depletion Model (ARDDM), describes conditions where additional analysis can improve a decision's estimated quality while raising the probability of missing its operational deadline, whereas Branch II, the Bounded Deliberation-Adaptive Decision Regulation Model (BDADRM), outlines candidate control policies for deciding whether to continue analysis, acquire information, stop, escalate, or invoke a fallback action. The framework keeps decision quality, epistemic uncertainty, risk, resource expenditure, delay loss, and decision availability distinct, establishing a state representation, a constrained objective, an operational divergence indicator, an optimal-stopping formulation, twelve analytical layers, and eight core domains for interdisciplinary investigation. Emphasizing a conditional research claim, the work provides a formal research program, falsifiable hypotheses, baseline comparisons, boundary conditions, and reproducibility requirements without treating unperformed experiments as evidence.

Zenodo (CERN European Organization for Nuclear Research)
Decision-Making and Behavioral Economics
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