Advancing Circular Business Models through Big Data and Technological Integration: Pathways for Sustainable Value Creation
Abstract
The global transition toward sustainable development has intensified research on circular business models (CBMs) as mechanisms for economic, social, and environmental value creation. This study synthesizes existing literature on CBMs and explores the intersection of technology, big data analytics, and circular economy principles. Circular business models aim to decouple economic growth from resource consumption by promoting strategies such as product life extension, resource recovery, and service-based value delivery (Geissdoerfer, Vladimirova, & Evans, 2018; Frishammar & Parida, 2019). While numerous typologies and frameworks have been proposed, the integration of digital technologies remains underexplored in systematically advancing CBM implementation (Ellen MacArthur Foundation, 2019; Gupta et al., 2018). This research adopts a qualitative literature synthesis approach, drawing on 30 seminal and recent publications that address sustainable business models, circular economy tools, and technology-enabled business innovations. The study identifies the mechanisms through which big data, artificial intelligence, and cloud-based manufacturing systems enhance circularity by improving resource tracking, predictive maintenance, and lifecycle optimization (Grover et al., 2018; Fisher et al., 2018). Results suggest that CBMs benefit from a hybridized approach that combines traditional sustainability strategies with digital transformation, enabling firms to navigate complex supply chains, manage critical material scarcity, and foster stakeholder engagement (Gaustad et al., 2018; Hopkinson et al., 2018). The discussion elaborates on the theoretical implications of CBM digitalization, highlighting the role of data-driven decision-making in sustaining competitive advantage while addressing environmental imperatives. Limitations include the predominance of secondary data analysis and the need for empirical validation across industries and geographies. Future research directions involve the development of quantitative frameworks to measure circularity impact, longitudinal studies on CBM performance, and policy integration strategies that harmonize technological adoption with regulatory incentives (Wasserbaur, Sakao, & Milios, 2022; Kanther, 2025). This article contributes to the scholarship on sustainable business models by emphasizing the strategic integration of technology and circular economy principles, offering a roadmap for researchers, practitioners, and policymakers committed to sustainable industrial transformation.
Keywords
References
Most read articles by the same author(s)
- Dr. Chinedu Okafor, Dr. Amina Ibrahim Bello, Preparing National Security Systems for the Quantum Era: A Roadmap for Post-Quantum Cryptographic Migration , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- John A. Prescott, A Unified Framework for Time-Sensitive and Resilient In-Vehicle Communication: Integrating Automotive Ethernet, Wireless TSN, and IoTEnabled Vehicle Health Monitoring , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 08 (2025): Volume 02 Issue 08
- Jianhong Wei, Aaliyah M. Farouk, MITIGATING CONFIRMATION BIAS IN DEEP LEARNING WITH NOISY LABELS THROUGH COLLABORATIVE NETWORK TRAINING , International Journal of Modern Computer Science and IT Innovations: Vol. 1 No. 01 (2024): Volume 01 Issue 01
- Dr. Jonathan Miller, Dr. Emily Carter, A Deep Learning-Based Biometric Authentication Architecture for Banking Fraud Prevention Using Google Teachable Machine and Facial Recognition Analytics , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 05 (2026): Volume 03 Issue 05
- Dr. Mingyu L. Chen, Muhammad Siddiqui, CODE-SWITCHED RELATION EXTRACTION: A NOVEL DATASET AND TRAINING METHODOLOGY , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 02 (2025): Volume 02 Issue 02
- Mr. Swapnil Joshi, Deep Learning-Based Customer Segmentation for Targeted Marketing in E-Commerce Platforms , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 07 (2026): Volume 03 Issue 07
- Dr. Aarav Sharma, AI-Driven Hyper-Automation for Financial Workflows , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 07 (2026): Volume 03 Issue 07
- Alistair J. Finch, Integrating Jira, Jenkins, and Azure DevOps to Optimize Software Release Pipelines , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Aarav Mehta, Kavya Sharma, Deep Belief Network-Based Intelligent Framework for Financial Fraud Detection and Real-Time Alerting in Cloud Computing , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Dr. Aarav Sharma, Ms. Priya Nair, A Hybrid Deep Learning Framework for Automated Liver Tumor Segmentation and Malignancy Prediction from CT Imaging Data , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 07 (2026): Volume 03 Issue 07
Similar Articles
- Victor P. Ionescu, EXPLAINABLE ARTIFICIAL INTELLIGENCE AS A FOUNDATION FOR SUSTAINABLE, TRUSTWORTHY, AND HUMAN-CENTRIC DECISION-MAKING ACROSS CONSUMER, SUPPLY CHAIN, AND HEALTHCARE DOMAINS , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 02 (2026): Volume 03 Issue 02
- Dr. Leila Mansouri, Cloud Computing AsInfrastructural ESG Capital: Strategic Implications For Corporate Sustainability , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 11 (2025): Volume 02 Issue 11
- Dr. Oliver Bennett, Dr. Sophie Williams, Scalable Machine Learning Approach in R for Structural Classification and Behavioral Analysis of Massive Twitter Network Data , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 06 (2026): Volume 03 Issue 06
- Dr. Kwame Mensah, Ms. Ama Boateng, Comparative Analytical Framework for Assessing Multiple Machine Learning Classifiers in Twitter Sentiment Analysis Using Bag-of-Words Feature Representation , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Dr. Rohan S. Whitaker, Predictive and Intelligent HVAC Systems: Integrative Frameworks for Performance, Maintenance, and Energy Optimization , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Dr. Elena Marković, Hyperautomation as a Socio-Technical Paradigm: Integrating Robotic Process Automation, Artificial Intelligence, and Workforce Analytics for the Future Digital Enterprise , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Mr. Raman Kumar, Intelligent Supply Chain Management Using Artificial Intelligence: Models, Challenges, And Future Prospects , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 09 (2026): Volume 03 Issue 09
- Serhii Svynarov, AI-Driven Automation in Cloud-Based Business Systems: A Practical Implementation Using Microservices Architecture , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 05 (2026): Volume 03 Issue 05
- Prof. Elise Vandermark, Integrating Lakehouse Architectures and Cloud Data Warehousing For Next-Generation Enterprise Analytics , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 12 (2025): Volume 02 Issue 12
- Dr. Carlos A. Benítez, Prof. Prashant Singh Baghel, UNVEILING AFFLUENCE: A BIG DATA PERSPECTIVE ON WEALTH ACCUMULATION AND DISTRIBUTION , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 06 (2025): Volume 02 Issue 06
You may also start an advanced similarity search for this article.