Determining resources and capabilities in complex context: A decision-making model for banks

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.

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Publication Details

Journal
PLoS ONE
Published
2025-05-20
DOI
https://doi.org/10.1371/journal.pone.0323735
Citations
1
Primary Topic
Impulse Buying and Technology Impacts
Type
article
Field-Weighted Citation Impact
3.13
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article

Determining resources and capabilities in complex context: A decision-making model for banks

Utomo Sarjono Putro, Mochammad Ridwan Ristyawan, Manahan Siallagan
1 citations
PLoS ONE
Impulse Buying and Technology Impacts
3.13
article

Determining resources and capabilities in complex context: A decision-making model for banks

Utomo Sarjono Putro, Mochammad Ridwan Ristyawan, Manahan Siallagan
article en
1 citations

Abstract

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.

PLoS ONEVol. 20(5)
Tanjungpura University (ID), Bandung Institute of Technology (ID)
Openalex Percentile: Top 8%
Impulse Buying and Technology Impacts
3.13
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