International Journal of Business Continuity and Risk Management (8 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
   
  
• Blending Enterprise Resource Planning on Supply Chain Management in Aerospace Sector in India and Analysis using Multi-scale Adaptive Dilated Convolutional LSTM  
  by Joydeep Banerjee, Santanu Kumar Das 
  Abstract: The aerospace organisations which have already executed enterprise resource management (ERP) tools along with the supply chain management (SCM) models are considered in this research work. At first, information is gathered from these organisations as a form of structured questions. These questions are then evaluated using relevant statistical methods to obtain the necessary goal. After that, the distribution of the questions to the authorised parties of these organisations is done. The authorities of these industries are requested provide information asked more precisely. At the final stage, the effectiveness of integrating the SCM with ERP is validated with the help of multi-scale adaptive dilated convolutional long-short-term memory (MADC-LSTM). The optimisation of the MADC-LSTM networks parameters is carried out by Golden Eagle with bee collecting pollen optimisation algorithm (GE-BCPOA). The effectiveness of integrating SCM with the ERP is analysed by conducting diverse experiments.
  Keywords: Enterprise Resource Planning; Supply Chain Management; Aerospace Sector in India; Statistical Approach; Multi-scale Adaptive Dilated Convolutional Long Short-Term Memory.
  DOI: 10.1504/IJBCRM.2025.10068462
   
  
• Enhancing Crime Record Analysis: Information Extraction and Categorisation using a Fuzzy Logic Approach  
  by Sheela J, B. Janet, Bijay Kumar Paikaray, Sachi Nandan Mohanty 
  Abstract: Efficiently extracting and categorizing information from crime records is crucial for actionable insights in law enforcement. Traditional methods struggle with language uncertainty. We propose a fuzzy logic-based approach for information extraction and categorisation from criminal event documents. Fuzzy rules enhance imprecise boundary delineation among patterns. Fuzzy crime extracts crime-r elated named entities (NER) like incident date, weapon type, location, nationality, and involved persons. It builds a crime-related thesaurus using computational linguistic methods. The ANFIS model categorizes sentence patterns, using fuzzy rules designed with four variables to generate 16 patterns. Higher weighted patterns indicate more significant sentences. The system effectively extracts specific crime-related details from reports; classifying sentences using ANN. Experiments on the Iraq Body Count (IBC) benchmark dataset validate our model's accuracy using precision, and recall measures, outperforming previous techniques. Our fuzzy logic-based approach enhances information extraction and categorisation in crime records, enabling law enforcement agencies to make informed decisions.
  Keywords: Text mining; NER; Lexicons; Extraction; Fuzzy system.
  DOI: 10.1504/IJBCRM.2025.10068839
   
  
• Environmental Risk Disclosure: an Analysis of Integrated Reports of Companies Listed on the Johannesburg Stock Exchange  
  by Lorren Haywood, Michelle Audouin, Nikki Funke, Karen Nortje, Phumza Ntshotsho, Maronel Steyn 
  Abstract: A content analysis was employed to extract the strategic and material environmental risks disclosed in integrated reports by top-listed companies on the Johannesburg Stock Exchange as of May 2020. Findings suggested that environmental risk disclosure was low for the year considered. The range of environmental risks listed as material and strategic, across the companies, was extremely limited, with climate risks being identified the most. The types of environmental risks disclosed by these JSE companies were found to be well aligned with the top global risks listed by the World Economic Forum in 2020. With continued and increasing global environmental degradation, together with pressure from company stakeholders, as well as recently introduced international and national guidance, it could be expected that environmental risk disclosure will improve among top-listed JSE companies. It is recommended that a review of the environmental risk landscape and disclosures of these companies is regularly undertaken.
  Keywords: risk disclosure; environmental risks; sustainability; integrated reports.
  DOI: 10.1504/IJBCRM.2025.10068844
   
  
• Conflict of Interest Moderation on the Relationship of Value Creation and Its Determinants  
  by Piyumi Seneviratne, Ravindra Hewa Kuruppuge, Hotniar Siringoringo 
  Abstract: This paper ultimately determines how commitment continuation of family owners with the combination of value orientation within the business can drive value creation capacity with the emphasis on mediating role of conflict of interest. To answer this objective, data was collected using a semi-structured questionnaire from the family businesses in Sri Lanka. The statistics technique was used to analyse data collected. The results of the study imply that the moderation of conflict of interest on the relationship of commitment continuation with value creation as well as the relationship of value orientation with value creation was evident. The study further emphasises that commitment continuation and conflict of interest was correlated positively, satisfying the hypothesis developed. The conceptual framework is tested for the validation of research to determine the applicability to the family-oriented small and medium businesses with reference to business owners in Sri Lanka.
  Keywords: Small and medium enterprise; Value Creation; Value Orientation; Conflict of Interest; Sri Lanka; Family Business.