2026· International journal of research and innovation in social science· Vol 10, pp. 16658-16669· 0 citations
TL;DR
A theoretically grounded conceptual Circular ERP architecture that integrates fragmented lifecycle data into a unified Lakehouse platform that eliminates data fragmentation across the Beginning-of-Life, Middle-of-Life (MOL), and End-of-Life (EOL) phases is proposed.
Abstract
As industries move towards a circular economy, traditional Enterprise Resource Planning (ERP) systems struggle with a significant information gap during the product usage and end of life stages. To address this architectural limitation, this study highlights the essential system requirements for a Circular ERP (C-ERP) platform tailored for closed-loop resource management. Through a structured conceptual review of 30 high-impact studies retrieved from the Scopus database and a subsequent integrative thematic analysis, the research identifies three core capabilities for Circular ERP which are technological tracking, data interoperability, and organizational readiness. Guided by Dynamic Capabilities Theory, this study proposes an Integrated Circular ERP Architecture driven by closed loop feedback mechanism, Digital Product Passports (DPPs), AI-powered decision intelligence and Data Lakehouse infrastructures where ELT pipelines flow exclusively into the centralized platform. Ultimately, this architecture offers a strategic roadmap for shifting legacy transactional systems into unified coordination platforms across decentralized circular ecosystems while supporting the United Nations Sustainable Development Goals. The main contribution of this study is a theoretically grounded conceptual Circular ERP architecture that integrates fragmented lifecycle data into a unified Lakehouse platform that eliminates data fragmentation across the Beginning-of-Life (BOL), Middle-of-Life (MOL), and End-of-Life (EOL) phases. This framework practically supports manufacturers and policymakers by providing a structured architecture to guide future empirical validation through industrial case studies.
Construction supply chains are pivotal to circular economy transitions but remain structurally fragmented, limiting the scalability of resource-efficient solutions. At the same time, digital technologies and life cycle assessment are often deployed in isolation, constraining their ability to enable system-level circularity. Using a theory-building literature synthesis of 141 publications across circular economy, sustainable supply chain management, digitalization, and life cycle sustainability assessment, this study develops an integrated conceptual framework that explains how circular performance may be shaped by AI-enabled decision capabilities, lifecycle sustainability constraints operationalized through PESI-LCA, and system-level alignment conceptualized through DCAM. AI is conceptualized as a dynamic capability for prediction and optimization, while PESI-LCA is positioned as an operationalized LCSA-based constraint system that embeds environmental, social, and economic criteria into decision architectures. DCAM defines the alignment conditions required across digital infrastructure, circular strategies, business models, and institutional enablers. The framework advances a non-additive logic: circular outcomes depend on how sustainability constraints shape AI-driven decision-making and how alignment enables coordinated implementation across supply chains. A key theoretical contribution is the identification of structural distortion as a failure mode in which digital optimization reinforces linear resource flows. The study advances sustainable supply chain theory and offers testable propositions and governance implications for scaling circular construction systems.
Global transition toward circular economy (CE) has fundamentally changed the operation requirements of Supply Chain Management (SCM) systems and the architecture requirements to enable such transition are still largely under-explored. The traditional SCM structure is fundamentally unsuitable to deal with the bidirectional logistics, multi-lifecycles use of resources, and multi-stakeholder collaboration that circular logistics require. Although there are a number of studies that have focused on a single enabling technology like Blockchain, the Internet of Things (IoT), Building Information Modelling (BIM), and Artificial Intelligence (AI), a comprehensive integrated architectural framework that covers the technical, organizational and governance aspects have not yet been developed. The purpose of this study is thus to identify and validate the fundamental architectural needs for SCM systems to fulfill the principles of the circular economy. By applying a Model-Based Systems Engineering (MBSE) methodology, the research consolidates 102 peer-reviewed papers found in Scopus, IEEE Xplore, SpringerLink and ScienceDirect that were relevant to Industry 4.0, digital construction and sustainable logistics between 2016 and 2025. Each requirement identified is confirmed through structured requirement, structured block definition, and structured activity diagrams through mapping to the literature that has been used as a source for the requirement and to the architectural components that support it. These core, interdependent needs traceability and provenance, lifecycle visibility and resource reuse, interoperability and standards, and security and trust are identified in the analysis and integrated solutions, as opposed to individual solutions, are required to achieve operational benefits. The study moves away from the focus on individual technologies and offers a conceptual blueprint for designing resilient, transparent, and sustainable circular supply chain systems; it recognizes that the framework is conceptually rather than empirically validated.
Xiao-Jia Chong, Jia-Xin Lim, Xin-Qian Chai et al.· International journal of res...· 0 citations
The transition to a circular economy requires organisations to move beyond sustainability commitments and embed circular principles into daily operations. Yet little is known about how this occurs in resource‐constrained contexts such as startups and small organisations. This paper addresses this gap by examining how circular economy strategies can be operationalised through integrated management systems (IMSs) using a dynamic capabilities perspective. Drawing on an exploratory case study of a university startup, the study develops a theoretically grounded IMS design that supports sensing, seizing and reconfiguring circular opportunities. Building on the integration logic of ISO 9001, ISO 14001 and ISO 45001 and aligning with ISO 59004 principles, the findings show how quality, environmental, safety and circularity objectives can be integrated within a coherent organisational architecture. By conceptualising IMS as an enabling infrastructure for dynamic capabilities, the study shifts attention from normative frameworks to implementation mechanisms and offers a transferable design logic for startups pursuing circularity.
Unknown authors· Business Strategy and the En...· 0 citations
The manufacturing industry fulfils essential societal needs, but it creates substantial environmental pressure. Decision support systems serve as valuable tools to steer manufacturing toward sustainability. However, manufacturers are currently limited to a structured decision-support system for integrating circular economy principles across the product, process, and system levels. This systematic literature review examines decision support systems for circular economy implementation in manufacturing through bibliometric and qualitative content analysis. The analysis reveals significant fragmentation: only 5% of studies integrate product, process, and system levels simultaneously, while 52% address a single level. The developed decision support systems were evaluated primarily by using life cycle assessment and life cycle costing. Digital technologies enable predictive capabilities, but implementation barriers remain substantial. Critical gaps include limited integration across decision levels, end-of-life bias, and inadequate focus on business model innovation. The discussion emphasises developing an integrated decision support system by converging system-level thinking with a circular economy framework and digital capabilities, creating an early-stage tool that provides feedback during design phases, and enabling organisations to proactively position sustainability.
Themiya S. Kuruppuge, A. Kulatunga, Martino Luis et al.· Journal of Industrial Ecolog...· 0 citations
To address the significant fragmentation in Circular Economy (CE) assessment models and the gap in their deployment within digital enterprise platforms. This research presents the Quantitative ERP-Driven CE (Q-EDCE) Framework to bridge the divide between sustainability theory and manufacturing Information Technology.
The study develops a multi-layered architecture that includes a Strategic Layer for establishing Value Retention Processes (VRPs), an Operational Layer that links these to functional ERP modules (such as Reverse Logistics and SCM), and a Measurement Layer that defines six specific Sustainability KPIs.PIs (S-KPIs). This conceptual model integrates Industry 4.0 technologies like IoT and Big Data, along with real-time MES data flows. The framework is validated through a Python-based numerical simulation using an industrial detergent manufacturing dataset.
The simulation demonstrates that the architecture effectively transforms a linear “As-Is” baseline into a circular model, resulting in a 69.7% increase in the Material Circulating Rate (MCR) and a 50% increase in the Waste Recovery Rate (WRR). Additionally, the conceptual integration enables a shift from retrospective, static reporting to dynamic, proactive decision-making and real-time resource optimization.
This work redefines ERP systems from simple transactional tools to powerful digital infrastructures that enable circularity. It provides a unique, systematic roadmap for integrating circular performance directly into organizational data flows, transforming sustainability from an abstract goal into a tangible corporate advantage.
The circular economy has emerged as a promising pathway for sustainable development, yet limited research explains how small and medium-sized enterprises (SMEs) operating in resource-constrained environments scale circular business models over time. Existing studies predominantly focus on circular business model typologies, implementation barriers, and policy mechanisms, providing limited insight into the capability development processes required for scaling. This study addresses this gap by developing a theory-building framework that explains how SMEs progressively transition from market participation to scalable circular enterprises. Drawing on dynamic capabilities theory, the resource-based view, and institutional theory, the study adopts a qualitative, theory-building approach that combines a structured synthesis of circular economy, sustainability, and strategic management literature with abductive reasoning. GreenSense Ghana Ltd. is used as an illustrative case to contextualize framework development; it is not treated as empirical evidence and is not used for statistical or analytical generalization. Through this synthesis, the study develops a Phased Circular Scaling Model comprising three sequential stages: market entry and validation, manufacturing and waste valorization, and digital integration for ESG-enabled value capture. The study contributes to circular economy scholarship by shifting attention from static circular business model configurations toward dynamic scaling processes. It further extends dynamic capabilities theory by demonstrating how sensing, seizing, and transforming capabilities evolve throughout circular business model development. For practitioners and policymakers, the framework provides a structured roadmap for scaling circular initiatives in emerging markets characterized by institutional and resource constraints.
