International Journal of Business Continuity and Risk Management (4 papers in press)

Regular Issues

• Exploring factors that affect internal audit effectiveness with the mediating role of Risk Management in Ethiopian Commercial Banks  
  by Teshome Mengstu Mekonen, Gurudutta Pradeep Japee 
  Abstract: This study examines how audit competency, internal audit independence, management support, and the quality of audit work indirectly influence internal audit effectiveness, with risk management serving as a mediating factor in Ethiopian commercial banks (ECB). A sample of 237 respondents was drawn from a total population of 582, and structural equation modeling (SEM) using SPSS AMOS was applied. The findings indicate that internal audit independence has the strongest positive indirect effect on internal audit effectiveness through enhanced risk management in ECBs. In contrast, audit competency shows a weak and negative indirect effect on internal audit effectiveness. The quality of audit work and management support demonstrates only modest impacts on risk management practices and internal audit functions. Overall, the study underscores the crucial mediating role of risk management and offers insightful recommendations for banking regulators, legislators, and practitioners in Ethiopia seeking to improve audit quality, effectiveness, and institutional accountability.
  Keywords: IAE; Risk management; SEM; and Ethiopian Commercial Banks.
  DOI: 10.1504/IJBCRM.2026.10079756
   
  
• AI-enabled enterprise risk management in cooperative banks - Successful paths to go  
  by Susanne Durst, Samuel Foli 
  Abstract: In this article, we apply various organisational characteristics to find out how they can support the journey to AI-supported enterprise risk management (ERM) in cooperative banks in different constellations. For this purpose, we used Fuzzy Set Qualitative Comparative Analysis (fsQCA) with data from employees of Italian cooperative banks. This method helped us to identify different paths of cooperative banks that provide valuable insights for achieving the goal of AI-powered ERM. Our results suggest that there are three overarching paths, i.e., strategy path, strategy-knowledge path and strategy-knowledge-resource path. The results not only underline the central importance of the strategy for AI-supported ERM in cooperative banks across all paths, but also show different paths that take the organisational context into account.
  Keywords: Enterprise risk management (ERM); Artificial intelligence (AI); AI-supported ERM.
  DOI: 10.1504/IJBCRM.2026.10079795
   
  
• A Hybrid Framework for Hazard-Based Risk Analysis and Resource-Constrained Action Planning  
  by Murat Oturakçi, Seçkin Çeliker, Esra Ekinci 
  Abstract: The primary objective of this study is to systematically identify and assess risks arising from uncertainties in industrial environments and developing optimal action plans considering organizations? existing resource constraints. Hence, a model was developed that integrates fuzzy logic and multi-criteria decision-making (MCDM) techniques. This model quantifies the uncertainties arising from decision-makers? judgments during the risk assessment process and attempts to provide an organization-specific prioritization mechanism by considering the criticality of risk-affected departments. The methodological process begins with determining risk severity levels and then constructs a binary programming model to generate the most appropriate action plans under constraints such as cost, time, and labour. To test the model?s flexibility, the effects of different resource scenarios on the action plan were examined through sensitivity analysis. This study provides an application-oriented and flexible methodological framework that can be integrated into existing risk analysis processes, in addition to its contribution to the academic literature.
  Keywords: Risk Analysis; Fuzzy Logic; MCDM; Resource Constrained Optimization.
  DOI: 10.1504/IJBCRM.2026.10080112
   
  
• Impact of AI-Enabled Decision Support Systems on Strategic Decision Quality: The Mediating Role of Decision Confidence  
  by Ashok Kumar, Saurabh Verma, Owais Farooq, Tarun Saini, Akshay Kandwal, Giri Raj, Lalit Kumar 
  Abstract: This paper examines the effects of AI-based decision support systems (AI-DSS) on strategic decision quality, with decision confidence as a mediating variable and task complexity as a moderating variable. The survey was conducted using a cross-sectional research design with a 37-item adapted scale, and purposive sampling was used to select 423 managerial-level and top executives of Indian companies who utilised it. The data were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 4.0. According to the findings, system quality, information quality, user interaction, and data processing speed are critical to improving the AI-DSS, which positively affects decision confidence. The predictability of results, perceived lower risk, and perceived credibility of the information are strong predictors of confidence in the decision. The two AI-DSS, as well as decision confidence, have positive effects on the strategic quality of decisions, where decision confidence serves as a central mediating variable.
  Keywords: AI-enabled Decision Support Systems; Decision Confidence; Strategic Decision Quality; Task Complexity; PLS-SEM.
  DOI: 10.1504/IJBCRM.2026.10080723