Key Factor Identification.

The role of resources and capabilities in shaping and implementing a firm’s strategy is paramount. The COVID-19 pandemic underscored the necessity for managers to possess a decision-making model that facilitates the selection of resources and capabilities in a real-time, dynamic, adaptive, and iterative manner. However, the dynamic capabilities framework, which serves as a decision-making model, faces three significant issues when selecting resources and capabilities within complex contexts. These issues, identified as research gaps, include context mismatch, inappropriate treatment, and strategy alignment. These gaps serve as the foundation for decision making models. This study aims to develop a decision-making model for determining banking resources and capabilities. The novelty of this study is encapsulated in the proposed decision-making model for resource and capability determination in complex contexts. Furthermore, this study employed a methodology adapted from the International Society of Pharmacoeconomics and Outcomes Research—Society of Medical Decision Making (ISPOR-SMDM). The research methodology was conducted in ten stages to develop a decision-making model. This study used qualitative methods, a case study strategy, and an abductive approach. The research sample consists of Indonesian State-Owned Banks (SOB). This research culminated in a proposed decision-making model that includes seven managerial decisions: probe, sense, structuring, bundling, building, leverage, and reconfiguring. This model integrates fuzzy preference judgments as inputs, deep learning analytics (predictive analysis) as processes, and success rate predictions as outputs. Theoretically, this research contributes to the enhancement of dynamic capabilities through the complex domains of the cynefin framework. Practically, it offers a decision-making model for the board of directors (BOD) to determine resources and capabilities amid complex environmental changes.