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

Regular Issues

• Enhancing Software Design Through Dynamic Metrics and Entropy: A Case Study in Cloud Security for Healthcare Systems  
  by Subhasish Mohapatra, Abhishek Roy, Bijay Paikaray 
  Abstract: The computational analysis through dynamic metrics and entropy potentially makes the system more robust before its real-time application. It can further bridge the missing link between component slicing and package restructuring. It ensures reliability in design and developers gain a methodical blueprint before coding. The result section elaborates on the cohesive analysis of each class. For a good software design, we need high cohesion and low coupling, so this adaptive analysis is achieved for this cloud-integrated healthcare model at the conceptual level of modelling. This analysis proves the flexibility of our proposed model. It systematically controls the ripple effect of changes in a model by coupling measures. The above concept further demonstrates how the structure of a unified modelling language (UML) class module within a model will explore the future scope of research work to provide an ultimate integrated cloud-based healthcare model to the end user.
  Keywords: cloud-healthcare; cohesion; coupling; modularisation; healthcare model; entropy.
  DOI: 10.1504/IJBCRM.2024.10065480
   
  
• Managing Supply Chain Risks for Enhanced Logistic Performance: Insights from the Automotive Industry in Morocco  
  by Mariame Ababou 
  Abstract: In today's volatile business environment, supply chain disruptions pose significant challenges to firms, impacting their logistic performance and overall competitiveness. This study aims to investigate the relationship between supply chain risks and firm logistic performance, with a focus on identifying key risk factors and mitigation strategies. Drawing upon an extensive literature review, a comprehensive framework of supply chain risks, including market risks, supplier risks, and inventory risks, is developed. Through empirical analysis using structural equation modelling (SEM) techniques, data collected from 82 automotive firms are examined to assess the impact of these risk factors on logistic performance indicators. The findings reveal significant associations between various risk factors and logistic performance outcomes, highlighting the critical role of proactive risk management in mitigating disruptions and improving operational efficiency. Practical implications for supply chain managers are discussed, emphasising the importance of implementing robust risk mitigation strategies and fostering resilience in supply chain operations. This research contributes to a deeper understanding of the complex dynamics between supply chain risks and firm performance and provides valuable insights for firms seeking to enhance their competitiveness in today's uncertain business landscape.
  Keywords: supply chain management; SCM; logistic performance; supply chain risks; PLS-SEM; Morocco; structural equation modelling; SEM.
  DOI: 10.1504/IJBCRM.2025.10066248
   
  
• Artificial Intelligence in Trucking Industry: A Triple-win Environmental, Social, and Governance Approach  
  by Kun Liao, Ozden Bayazit, Pingping Tang 
  Abstract: This study examines a triple-win approach introduced by an artificial intelligence (AI) technology service company in Shenzhen, China, that is analysed through the environmental, social and governance (ESG theory) factors. This approach is promising because it may improve the operational efficiency as well as the financial performance of the insurance company and the trucking logistics company. More importantly, technology and service can vastly decrease the accident rate of logistics companies, resulting in positive social impacts. Hence, this study proposes a framework for adopting AI in logistics and classifies success factors of AI projects into three categories based on findings from the innovative Chinese startup and other previously implemented AI projects: viable technology, profitability, and positive social impact.
  Keywords: artificial intelligence; autonomous driving; social responsibility; insurance; trucking industry; success factors.
  DOI: 10.1504/IJBCRM.2025.10066552
   
  
• Sustainable Development Goals Reporting and Firm Value in Indonesia: Moderating Role of Separate Risk Management Committee  
  by Decky Riadi, Andrey Hasiholan, Faris Windiarti 
  Abstract: This research aims to assess the impact of Sustainable Development Goals (SDGs) disclosure on firm value and examine how separate risk management committee moderates the relationship between SDGs disclosure and firm value. This research samples were 328 firms listed on Indonesian Stock Exchange during 20172021. This study uses secondary non-financial and financial data from annual, sustainability report, and other financial database. Data were analysed using fixed effect method. Results revealed that SDGs disclosure has positive and significant influence on firm value, implying that the publication of commitment to SDGs may acts as a signal of firm best practice in sustainability. The study also revealed that separate risk management committee does not have any impact the firm value. Similarly, the separate risk management committee does not moderate the association between SDGs disclosure and firm value. The research results support the implementation of signalling theory and enhance a comprehensive understanding about firm valuation. This research also provides insights for managers, investors, and policy makers to consider the effectiveness of establishment of separate risk management committee in firm.
  Keywords: firm value; risk management; Sustainable Development Goal; SDGs; sustainability; Indonesia.
  DOI: 10.1504/IJBCRM.2025.10066903