Rethinking Sustainable Operations: A Multi-Level Integration of Circularity, Localization, and Digital Resilience in Manufacturing Systems

Abstract

The escalating climate crisis and global disruptions have prompted a critical re-evaluation of operations management within manufacturing and supply systems. This conceptual article addresses the theoretical and strategic gap in aligning resilience and sustainability by proposing an Integrated Sustainable Operational Strategy (ISOS) framework. Drawing on systems theory, circular economy principles, and sustainability science, the framework synthesizes multiple operational domains—circularity, localization, digital adaptation, and workforce flexibility—across macro (policy), meso (organizational), and micro (process) levels. This study constructs a conceptual model that explains the interdependencies and trade-offs among strategic operational responses in the Anthropocene era. Supported by multi-level logic and a synthesis of domain constructs, the model provides a foundation for empirical investigation and strategic planning. Key propositions for future research are developed, focusing on causal relationships and boundary conditions. The novelty of ISOS lies in its simultaneous integration of three strategic pillars—circularity, localization, and digital resilience—within a unified, multi-scalar architecture that bridges fragmented operational theories. The article advances theory by redefining operational excellence through regenerative logic and adaptive capacity, responding directly to SDG 9 (industry innovation), SDG 12 (responsible consumption and production), and SDG 13 (climate action). This integrative framework offers both theoretical insight and practical guidance for transforming operations into catalysts of sustainable transition.

1. Introduction

1.1. Global Sustainability Crisis and Manufacturing Realignment

The twenty-first century has been marked by unprecedented environmental, social, and economic turbulence, with the climate emergency, geopolitical disruptions, and pandemics converging to test the foundational assumptions of modern operational systems. For the manufacturing sector—a major contributor to global resource consumption and greenhouse gas emissions—these challenges are not peripheral, but existential. The industrial sector is responsible for nearly 20% of global CO₂ emissions, and remains deeply intertwined with intensive material extraction, high water consumption, and substantial waste generation, posing significant challenges for sustainability transitions [1]. As such, manufacturing organizations are increasingly called to play a leading role in addressing sustainability imperatives, particularly in alignment with global agendas such as the United Nations Sustainable Development Goals (SDGs), especially SDG 9 (industry, innovation, and infrastructure), SDG 12 (responsible consumption and production), and SDG 13 (climate action) [2,3].

While some firms have taken initial steps—through carbon-reduction targets, green certifications, or CSR reporting—these responses often remain fragmented, superficial, or reactive. What is needed is a systemic realignment of operational strategy, one that embeds sustainability at the design core of manufacturing processes, supply networks, and value-creation models. This realignment demands that operations managers shift from traditional performance paradigms focused solely on cost and efficiency toward integrative logics that prioritize resilience, circularity, and long-term ecological viability [4,5].

1.2. From Efficiency to Resistance–Sustainability Nexus

Historically, operations management has been dominated by principles of lean thinking, just-in-time production, and process optimization—frameworks that have delivered remarkable gains in efficiency and profitability. However, such models were developed under the assumption of stable environments, predictable demand, and global logistics reliability, assumptions that no longer hold in a volatile, uncertain, complex, and ambiguous (VUCA) world [6]. Events such as the COVID-19 pandemic, geopolitical trade frictions, and climate-induced disruptions have exposed the vulnerability of hyper-efficient but brittle operational systems [7].

In this context, the emerging discourse highlights a pressing need to move beyond efficiency as the singular logic of operational success. Instead, organizations must balance short-term efficiency with long-term resilience and sustainability. Resilience, in this sense, refers not only to the ability to recover from disruptions but to adapt, reconfigure, and evolve in response to systemic shocks [8,9]. Sustainability, meanwhile, expands the scope of operational performance to include ecological integrity, social responsibility, and intergenerational justice [10,11].

The intersection of these two paradigms—resilience and sustainability—offers a new frontier for rethinking operations strategy. Yet, integrating these paradigms into coherent operational practice remains an unresolved challenge. How can organizations design operations that are both agile and circular? How can digital technologies enhance environmental transparency without compromising speed and responsiveness? How can local sourcing be scaled without eroding competitiveness? These are questions that current operational frameworks often fail to address in an integrated manner.

To clarify the foundational logic of this study and prevent conceptual confusion, the three core concepts that underpin the ISOS model—circularity, localization, and digital adaptation—are summarized in

Table 1. Core concepts and working definitions.

Concept	Working Definition
Circularity	A regenerative operational model that minimizes waste and maximizes resource reuse through closed-loop systems [12,13,14].
Localization	A strategy that emphasizes sourcing, production, and distribution closer to the point of use, aiming to reduce dependency on global supply chains and enhance community resilience [14].
Digital Adaptation	The dynamic integration of digital technologies (e.g., IoT, AI, blockchain) to enable flexible, transparent, and responsive operations in uncertain environments [15,16].

.

1.3. Conceptual Gaps: Fragmented Integration in OM Theories

Despite increasing scholarly attention to sustainability in operations, the literature remains fragmented across disparate streams—green supply chain management, circular economy models, lean-green integration, Industry 4.0, and disaster resilience—each offering valuable insights but rarely coalescing into a unified strategic framework [15,16]. Moreover, much of the existing research emphasizes empirical findings, tool-based applications, or sector-specific case studies, while lacking the theoretical synthesis needed to guide cross-contextual understanding and strategic decision-making.

This fragmentation is problematic in three ways. First, it inhibits the development of generalizable operational models that are scalable across industries. Second, it creates disjunctures between environmental goals and operational capabilities, leading to trade-offs rather than synergies. Third, it limits the ability of scholars and practitioners to navigate the multi-level dynamics of sustainability transitions, which involve interactions between organizational routines, technological infrastructures, institutional logics, and global systems [17].

Notably, while lean manufacturing has evolved to incorporate some aspects of environmental thinking, the emphasis remains on incremental improvements rather than transformational shifts in design logic. Similarly, digital transformation efforts (AI, IoT, blockchain) often prioritize visibility and control rather than systemic sustainability. There is, therefore, a conceptual void in operational literature—a need for a theory-informed, integrative model that bridges circularity, localization, and digital resilience as mutually reinforcing pillars of sustainable operations.

1.4. Integrated Sustainable Operations Strategy (ISOS): A Conceptual Framework

This paper responds to the above gaps by proposing a conceptual framework for sustainable operations strategy that synthesizes three interdependent strategic domains: circularity, which embeds regenerative and closed-loop principles into production and logistics; localization, which promotes regionalized, proximity-based sourcing and production to enhance adaptability and reduce emissions; and digital resilience, which leverages real-time data, predictive analytics, and smart systems to improve sustainability performance under uncertainty.

By weaving together these domains, the paper introduces the Integrated Sustainable Operational Strategy (ISOS) framework—an original theoretical model that repositions operations not merely as process enablers, but as architects of sustainability transitions.

The main contributions of this paper are fourfold. First, it advances a multi-level conceptual framework that links operational design, technological enablers, and sustainability outcomes. Second, it integrates fragmented theories into a cohesive strategic operational architecture grounded in systems thinking and sustainability science. Third, it proposes research propositions for empirical testing, thereby supporting future theory building and cross-disciplinary scholarship. Finally, it aligns directly with the Aims and Scope of Sustainability (MDPI) by addressing technical, environmental, and organizational dimensions of sustainable development through a systems-based operational lens.

1.5. Paper Structure

To achieve the objectives outlined above, this conceptual article is organized into seven sections. Section 2 reviews and synthesizes relevant theoretical foundations across sustainability transitions, circular operations, localization strategies, digital enablers, and systems thinking. Section 3 develops the Integrated Sustainable Operational Strategy (ISOS) framework by detailing its conceptual logic, core dimensions, and boundary conditions. In Section 4, the paper elaborates on strategic operational domains and discusses their interdependencies, drawing implications for design, management, and organizational performance. Section 5 presents a theoretical discussion that highlights contributions to operations management, sustainability science, and strategic transformation. Section 6 offers a future research agenda, including propositions for empirical validation and cross-sectoral exploration. Finally, Section 7 concludes the paper with reflective insights on the evolving role of sustainable operations within the Anthropocene economy.

Through this structure, the paper aims to stimulate conceptual advancement, guide strategic reorientation, and contribute to global sustainability through transformative operational thinking.

2. Theoretical Foundations

2.1. Sustainability Transition in Operations Management

The evolution of operations management (OM) from a discipline focused solely on efficiency and cost optimization to one increasingly concerned with ecological sustainability and social responsibility represents a foundational shift in both theory and practice. This transformation reflects broader global dynamics, where organizations are no longer judged merely by their output metrics but by their contribution—or failure—to address systemic challenges such as climate change, resource depletion, and social inequity [18].

The concept of sustainability transitions, originating in sustainability science and socio-technical systems theory, provides a critical lens for understanding this evolution. At its core, sustainability transitions refer to long-term, multi-dimensional, and fundamental transformations in the way societal systems—such as energy, mobility, or production—are structured and governed to achieve ecological integrity, economic prosperity, and social justice [19,20]. Applied to OM, this framework calls for a shift from static, linear models of value creation toward adaptive and systemic thinking, positioning operations within broader ecological and institutional ecosystems [21].

Three theoretical streams are especially relevant in advancing a sustainability-oriented perspective in OM: sustainability science, systems theory, and the circular economy.

First, sustainability science emphasizes the need for transdisciplinary approaches that integrate environmental, economic, and social knowledge domains to generate actionable solutions for real-world problems [22]. It calls for a reconfiguration of operational thinking from a narrow focus on firm-level efficiency to a broader concern with systemic impacts, interdependencies, and long-term consequences. Manufacturing firms are thus understood not as isolated units but as interlinked agents within socio-ecological networks whose decisions ripple across supply chains and communities [23].

Second, systems theory offers essential tools for modeling these complexities. Originating from cybernetics and general systems thinking, this theory views organizations as open, dynamic systems characterized by feedback loops, emergent properties, and interdependent subsystems [24]. When applied to operations, systems theory helps shift attention from isolated process improvements to system-level coherence, adaptability, and resilience. It supports the development of models that internalize externalities—such as emissions and resource depletion—into performance indicators and decision logic [25,26,27].

Third, the circular economy provides a normative and practical framework for operational redesign. Unlike traditional linear models (take–make–dispose), circularity emphasizes resource regeneration, waste minimization, and closed-loop systems, aligning well with both sustainability goals and systems thinking principles [28]. It introduces new tools and mindsets—such as design-for-reuse, material stewardship, and lifecycle optimization—that reshape operational strategy beyond throughput efficiency.

The synergy among these three streams forms a compelling logic for transformation. A sustainability transitions lens enables OM scholars and practitioners to integrate the normative agenda of sustainability science, the structural insights of systems theory, and the practical mechanisms of the circular economy into a unified operational transformation logic. This logic reframes operations not as sites of cost engineering, but as strategic levers for systemic innovation and planetary resilience [29].

In the sections that follow, we further elaborate how this integrative approach sets the foundation for a new model of sustainable operations—one that merges circular design, localization strategies, and digital resilience as co-constitutive elements of transformation.

2.2. Circular Economy: Systemic Capability and Regenerative Logic

The circular economy (CE) has emerged as a transformative paradigm that disrupts the traditional linear logic (“take–make–dispose”) long embedded in operations management. Instead, CE promotes a regenerative model where resource flows are optimized, waste is minimized, and value is retained across multiple lifecycles [30,31,32]. It shifts the focus from end-of-pipe solutions to upstream design interventions and systemic loops.

Within operations management, the implications of CE are profound. CE demands that operations move beyond efficiency optimization toward the development of systemic capabilities—the ability to design, manage, and evolve operational processes that sustain material loops, extend product life, and decouple growth from resource extraction [33,34]. These capabilities require integrating environmental intelligence across the value chain, from upstream design and procurement to downstream recovery and remanufacturing [35].

Theoretically, CE is deeply aligned with systems theory and ecological economics, both of which emphasize the interdependence between technical systems and natural ecosystems. From this perspective, operational decisions cannot be divorced from their environmental context. Each product or service leaves a material footprint that must be accounted for across space and time [36]. CE thus demands that firms embed lifecycle thinking into core operational design, supported by tools like Life Cycle Assessment (LCA), material flow analysis, and product-service systems (PSSs) [37,38,39].

Moreover, CE enhances operational resilience by embedding redundancy and adaptability—not as inefficiencies, but as intentional design choices. Examples include reverse logistics, modular architectures, and secondary raw material markets that buffer against shocks such as commodity volatility or policy shifts [40,41].

Operationalizing CE also requires a shift in value logic and performance metrics. Conventional KPIs (e.g., cycle time, cost per unit) must be complemented—or replaced—by metrics like resource productivity, circularity ratio, and material retention index [42]. This transition reframes operational excellence from a narrow, process-centric paradigm to a systemic, sustainability-aligned logic.

Furthermore, CE opens avenues for strategic differentiation. Organizations embedding circularity can simultaneously achieve regulatory compliance, reduce long-term costs, and strengthen their sustainability credentials in the eyes of investors and consumers. However, this transition is often constrained by path dependency, capability gaps, and fragmented institutional support [43,44]. Thus, conceptual integration and strategic clarity become essential.

In sum, CE is not an operational add-on but a new logic of value creation. It reframes operations as regenerative functions that contribute value beyond the firm—ecologically, socially, and economically. When integrated with localization and digitalization strategies, CE forms a foundational pillar of sustainable operations, as explored in the next sections [45].

2.3. Localized Operations and Regional Resilience Framework

The hyper-globalization of supply chains over recent decades has enabled cost and scale efficiencies, but also revealed critical fragilities. Recent global shocks—COVID-19, geopolitical conflicts, and climate disruptions—have destabilized logistics flows, extended lead times, and threatened material access across sectors [46,47]. These crises have catalyzed a strategic pivot toward localized operations, emphasizing proximity, adaptability, and regional self-reliance as pillars of operational resilience [48,49].

Localization in operations refers to reconfiguring production, sourcing, and distribution closer to end markets. While often seen as a risk response, localization in a sustainability context serves a dual role: reducing environmental externalities (e.g., transport emissions) and enhancing social embeddedness by strengthening regional economies and labor systems [50]. This supports SDG 12 (responsible consumption and production) and SDG 13 (Climate Action).

From a systems theory lens, localized operations embed redundancy and diversity into supply networks, enabling shock absorption and rapid reconfiguration [51,52]. In high-uncertainty environments, adaptability becomes a core operational asset.

Theoretically, localization also aligns with ecological resilience thinking—the capacity to maintain core system functions under stress [53]. Regionalized operations promote institutional and cultural alignment with local stakeholders and environmental norms, enhancing legitimacy and responsiveness in sustainability governance.

Moreover, localization complements the circular economy by tightening material loops and reducing reverse logistics complexity. Firms sourcing regionally can build industrial symbiosis—partnering with local recyclers, remanufacturers, and service providers to form closed-loop ecosystems [54,55].

Operationalizing localization demands more than spatial realignment. It requires modular production systems, flexible supplier networks, and digital coordination platforms [56]. Governance must shift from centralized control to distributed decision-making, supported by local data and situational awareness.

Yet, localization entails trade-offs. Firms may encounter higher unit costs, reduced scale advantages, or supplier limitations. Thus, it must be viewed not as a binary alternative to globalization, but as part of a strategic resilience portfolio. The objective is not de-globalization, but smart regionalization that balances sustainability, agility, and competitiveness [57].

In summary, localized operations redefine operational strategy around resilience and place-based sustainability. By shifting the value focus from global optimization to regional robustness, and integrating circularity and digital infrastructure, localization becomes a foundational pillar for future-ready, sustainable operations.

2.4. Digital Transformation as an Enabler of Sustainability Adaption

Digital transformation has emerged as a key enabler of adaptive and sustainable operations amidst growing complexity, uncertainty, and environmental degradation. Digital technologies today are increasingly recognized for their potential to embed sustainability into the core of operational strategies [58]. This reframing positions digitalization not as a neutral process innovation, but as a strategic catalyst for sustainability transitions in operations management.

At the heart of this transformation is the integration of Industry 4.0 technologies—including the Internet of Things (IoT), artificial intelligence (AI), blockchain, and cloud computing—into operational systems. These tools enable real-time data, predictive analytics, and automation, thereby enhancing visibility, traceability, and responsiveness across supply chains [59,60,61]. From a sustainability perspective, such capabilities are critical for monitoring emissions, optimizing resources, and enforcing compliance in complex value networks.

For example, IoT sensors monitor energy and water use, while AI algorithms reduce waste through process optimization [62,63]. Blockchain ensures supply chain accountability, and cloud platforms enhance coordination among distributed actors [64]. These technologies create dynamic feedback loops that reflect the principles of systems theory and sustainability science: continuous learning, adaptation, and impact mitigation. Emerging digital technologies—AI, IoT, and blockchain—are now key enablers for environmental goals and ESG digitalization, enhancing data integrity, real-time monitoring, and sustainable decision-making [48,49].

Digitally enabled operations also improve resilience. Predictive maintenance prevents material loss, while digital twins simulate sustainability scenarios [65,66]. During disruptions—natural disasters, pandemics, or policy shifts—digital infrastructure enables rapid reconfiguration with minimal environmental cost, reinforcing adaptability as a sustainability asset.

Furthermore, digital transformation supports circular economy implementation. Real-time tracking aids reverse logistics, smart sorting boosts recycling, and advanced analytics identify options for remanufacturing or product-as-a-service models [67,68]. This synergy demonstrates how data-driven technologies operationalize sustainability goals.

However, the sustainability of digitalization itself warrants attention. Digital systems consume energy, generate e-waste, and may cause social displacement [69,70]. Thus, digital adoption must follow ecological design principles—e.g., energy-efficient computation, green data centers, and inclusive governance. It is not only about what technologies are deployed, but how and why they align with broader sustainability values.

In summary, digital transformation embeds intelligence, traceability, and adaptability into production systems. When integrated with circularity and localization, digital capabilities shift operations from reactive systems to proactive agents of sustainability, contributing to the realization of SDG 9 (industry, innovation), SDG 12 (responsible consumption), and SDG 13 (climate action).

2.5. System Thinking and Triple Bottom Line Convergence

As sustainability demands intensify, linear and fragmented operational models increasingly fall short. A shift is required—from optimizing isolated functions to managing operations as interdependent systems. This approach is grounded in systems thinking, which emphasizes feedback loops, emergence, and holistic integration across ecological, economic, and social dimensions [71,72]. It enables firms to connect operational decisions to sustainability outcomes at multiple scales.

Recent contributions have reinforced this view: OECD (2024) presents a system-based regional resilience framework, while a recent ResearchGate review highlights how supply chain recovery and balance are increasingly framed within Triple Bottom Line (TBL) thinking and systems logic [49,73].

In this light, the TBL—People, Planet, Profit—provides a structure to evaluate operations beyond efficiency metrics. Traditional KPIs (e.g., unit cost, cycle time) must be rebalanced with indicators of ecological footprint (e.g., carbon, resource use) and social equity (e.g., labor welfare, community impact) [74]. Integrating TBL with systems thinking fosters multi-dimensional assessments that prioritize long-term, systemic value over short-term gains.

A key insight from this perspective is the triadic convergence of three operational strategies. Circularity advances the Planet dimension by promoting regenerative design and closed-loop processes. Localization advances People by enhancing social embeddedness and regional resilience. Digitalization contributes to Profit by enabling agility, real-time optimization, and risk-informed control.

When unified through systems logic, these strategies become mutually reinforcing. Digital tools enhance tracking and traceability for circularity while also improving coordination within localized networks. Localized systems, in turn, support reverse logistics and closed material loops essential for circular models. Circular design, finally, strengthens resilience in localized operations by reducing reliance on vulnerable global supply chains [75,76,77].

To depict this integration, Figure 1 presents a Venn diagram showing the overlap of these domains.

The Venn diagram illustrates how resource regeneration (Circularity), local autonomy (Localization), and smart connectivity (Digitalization) intersect. Their overlap represents a “Sustainable Operational Core”—a zone where operations are regenerative, resilient, and digitally agile.

The strategic implication is clear: sustainability is not about optimizing one dimension, but about designing for systemic integration across complexity. This enables organizations to anticipate trade-offs, leverage synergy, and drive innovation that single-domain efforts might miss [78,79,80].

In essence, sustainable operations are not extensions of conventional models. They are adaptive, regenerative, and context-aware architectures. By embracing the intersection of circularity, localization, and digital capability, firms can build resilient and future-fit operational systems—a necessity in the Anthropocene economy.

2.6. Research Design of the Conceptual Paper

This paper adopts a structured approach to conceptual development, as recommended by Jaakkola [78], to ensure theoretical robustness and relevance. Conceptual papers are particularly valuable in emerging and complex domains—such as sustainability-oriented operations—where empirical work is still developing and fragmented. The approach used in this study combines theory synthesis and model development, which enables the integration of diverse constructs into a coherent framework.

The design process unfolded in three key stages:

• Problematization and Theoretical Synthesis
  The study begins by identifying key fragmentation points in the current literature on sustainable operations, particularly the disconnects between circularity, localization, and digital transformation. By synthesizing insights from circular economy (CE), regional resilience, and digital adaptation, the study constructs a comprehensive view of what sustainable manufacturing operations require in today’s context.
• Framework Construction and Integration Logic
  The conceptual model—Integrated Sustainable Operations System (ISOS)—is developed by aligning multi-level constructs (macro, meso, micro) and mapping them to strategic design drivers and operational outcomes. The framework integrates dimensions that are often discussed in isolation, such as local sourcing, reverse logistics, digital twins, and adaptive policy environments.
• Proposition Development for Future Research
  To enable empirical advancement, the paper derives a set of theoretical propositions based on the ISOS logic. These propositions serve as testable pathways linking antecedents, capabilities, and sustainability outcomes, offering a roadmap for future empirical validation and theory building.

By following Jaakkola’s guidance on conceptual article design [78], this study contributes a logically structured, integrative, and theoretically grounded model that addresses critical gaps in sustainable operations literature.

3. Conceptual Framework and Design Logic

3.1. Research Design as Conceptual Contribution

This paper is intentionally developed as a conceptual and theoretical contribution, not as an empirical study. Its primary aim is to synthesize fragmented theoretical streams in operations management, sustainability science, and systems theory into a cohesive integrative framework that addresses the complex realities of sustainable operations in the post-crisis era. Such an approach aligns with the tradition of conceptual scholarship that seeks to advance theory development through creative recombination, meta-synthesis, and model construction [81].

In the spirit of non-empirical inquiry, the research design adopted here is not built upon field data collection or statistical validation, but rather follows a logic-based, theory-building approach. Drawing from methodologies common in strategic management and organizational theory development, the design process proceeds through three deliberate stages:

The first stage, theory consolidation, involves identifying and extracting core constructs from the existing literature across sustainability transitions, circular economy, digital operations, and localized resilience. These constructs are not treated as fixed variables but as evolving, context-dependent logics that reflect contemporary shifts in operations.

The second stage, thematic integration, maps conceptual linkages and interdependencies across these domains. It highlights how each contributes unique yet complementary dimensions to sustainable operations. This stage moves beyond isolated best practices to reveal systemic patterns and conceptual overlaps that enable higher-order synthesis.

The third stage, framework articulation, culminates in the development of the Integrated Sustainable Operational Strategy (ISOS) model. This model serves as a conceptual architecture that captures the dynamic convergence of three strategic domains: Circularity, Localization, and Digital Adaptation.

To ensure definitional clarity and internal coherence, the key concepts used in the ISOS model are summarized in

Table 2. Key Concept Definitions for ISOS Pillars.

Strategic Pillar	Definition	Strategic Role in ISOS
Circularity	A systemic approach to designing out waste, keeping materials in use, and regenerating natural systems throughout the product lifecycle.	Drives resource efficiency, closed-loop flows, and long-term value regeneration.
Localization	The strategic realignment of production, sourcing, and decision-making to local or regional levels to enhance adaptability and reduce external dependencies.	Enhances supply chain resilience, reduces emissions, and empowers regional ecosystems.
Digital Adaptation	The dynamic use of data-driven technologies (e.g., AI, IoT, blockchain) to optimize, monitor, and reconfigure operational processes in real time.	Enables agility, transparency, and integration across complex operational layers.

below.

This structured and rigorous approach enables the construction of a middle-range theory—a framework that is abstract enough to be generalizable across settings, but grounded enough to be actionable within real-world operational contexts [82,83]. It responds directly to calls for deeper theoretical engagement in sustainability-oriented operations research, particularly through modeling causal logics, identifying conceptual boundaries, and illuminating trade-offs across competing operational priorities.

Importantly, the framework developed here is not intended as a predictive model for hypothesis testing, but as a generative platform for scholarly dialogue, strategic reflection, and future empirical investigation. It offers propositions about how operational systems might be designed to achieve sustainability transitions, especially in conditions characterized by volatility, environmental stress, and institutional complexity.

By explicitly avoiding empirical generalization, this study adheres to a central tenet of conceptual theory building: the emphasis on conceptual clarity, integrative coherence, and explanatory utility over data-driven correlation [84,85]. This distinction is especially critical given the increasing number of empirical manuscripts that are inappropriately submitted to journals seeking theoretical advancement, leading to desk rejections due to misalignment in contribution type [86].

Thus, this section serves to clarify the purpose and epistemological stance of the study: a conceptually driven exploration of sustainable operational design, grounded in cross-disciplinary literature and intended to advance both academic theory and practical insight. In doing so, it adheres to the expectations for conceptual contributions in sustainability scholarship—emphasizing theoretical synthesis, analytical coherence, and actionable implications for system-wide design.

3.2. Logic of Framework Construction: Antecendents, Drivers, Outcomes

The development of the Integrated Sustainable Operational Strategy (ISOS) framework follows a theory-driven logic that connects antecedent conditions, strategic design drivers, and intended sustainability outcomes. Rather than relying on empirical fieldwork, this construction is grounded in meta-synthesis of cross-disciplinary theoretical insights from sustainability science, system dynamics, organizational resilience, and operations strategy [87,88].

Antecedents: Structural Pressures and Transformational Imperatives

At the foundational level, the ISOS framework responds to macro-level antecedents that disrupt traditional operational logics. First, environmental degradation and climate volatility demand a fundamental rethinking of operations, particularly in alignment with SDG 13 (climate action) [89,90]. Second, global supply chain fragility, which became highly visible during recent crises such as the COVID-19 pandemic, has exposed the brittleness and risk of long-distance, efficiency-driven systems [91]. Third, social accountability and ESG mandates are increasingly pushing firms beyond basic compliance, encouraging them to pursue embedded, performance-based approaches to sustainability [92].

These antecedents serve not as variables to be measured, but as contextual conditions shaping the boundaries and urgency of strategic design.

Strategic Design Drivers: Conceptual Mechanisms for Operational Transformation

The ISOS framework introduces three interlocking strategic design drivers, each of which is derived from dominant yet often fragmented streams of theory.

The first driver, circularity, is grounded in the principles of industrial ecology and regenerative design. It emphasizes reducing material throughput, designing for reuse, and closing resource loops to enable long-term sustainability in production systems [93,94].

The second, localization, draws from regional development literature, supply chain resilience theory, and place-based strategy. It promotes proximity sourcing, decentralized operational structures, and meaningful engagement with local stakeholders to enhance responsiveness and embeddedness [95,96].

The third driver, digital adaptation, is rooted in Industry 4.0 paradigms and the application of real-time analytics. It enables firms to engage in predictive maintenance, responsive decision-making, and system-wide optimization through digital infrastructure and data-driven agility [97,98].

These design drivers interact not linearly but synergistically—their convergence enables a transformation from reactive to anticipatory operational logics. Unlike prior frameworks such as lean-green integration models that primarily focus on eco-efficiency trade-offs within existing operational systems, or resilience-based OM that emphasize response to disruption without embedding ecological logics [90], ISOS uniquely positions these three domains as co-evolving strategic pillars within a unified design structure. In contrast to Industry 4.0 for sustainability frameworks, which often elevate digital tools as central enablers, ISOS balances technological adaptation with spatial and material regeneration logics, offering a more integrated operational theory.

Intended Outcomes: Triple Bottom Line Sustainability

The synthesis logic concludes by projecting a set of intended outcomes that align with the TBL and relevant SDGs.

From an environmental perspective, the ISOS framework is expected to contribute to reductions in waste, emissions, and resource extraction. This is achieved through the application of closed-loop systems and real-time energy-optimization mechanisms that minimize ecological impact.

From a social dimension, the framework envisions the empowerment of local actors, the upskilling of the workforce, and the promotion of regional equity. These outcomes emerge from localized operations integrated with adaptive technologies that enhance participation and inclusion.

Economically, the ISOS design aims to deliver enhanced value creation, improve cost resilience, and stimulate innovation through regenerative processes and smart operational practices that support long-term viability.

Importantly, these outcomes are not presented as empirically validated results, but rather as propositional outputs—hypothetical consequences of the ISOS design that are intended to guide future empirical investigation and inform sustainability-oriented policy reflection [99].

Conceptual Integration and Boundary Logic

By explicitly structuring the ISOS framework into a sequence of Antecedents → Strategic Drivers → Outcomes, the model offers a mid-level conceptual architecture that balances breadth with depth. It is sufficiently generalizable across sectors and geographies, allowing for application in diverse industrial and institutional contexts. At the same time, it remains specific enough to guide operational redesign initiatives, providing actionable insight for firms seeking to align strategy with sustainability imperatives. Furthermore, the framework is inherently flexible, enabling it to incorporate emerging technologies and adapt to evolving environmental, regulatory, and socio-economic conditions.

This theoretical orientation reflects a commitment to model-driven thinking rather than data-driven deduction. It also meets the expectations of journals like Sustainability, which emphasize cross-disciplinary synthesis and actionable theory relevant to the SDGs and global policy frameworks.

In sum, this section articulates the internal logic of the ISOS framework: a structured theoretical model that integrates multiple bodies of literature into a coherent, future-facing strategy for sustainable operations. It positions the framework as a tool for strategic sense-making and conceptual advancement, not a prescriptive formula to be statistically validated. This integrative architecture represents a substantial advancement over prior fragmented models by offering a systemic, nested, and interdependent platform for rethinking operational sustainability.

3.3. Key Constructs Definitions and Boundaries

To enhance the conceptual clarity of the Integrated Sustainable Operational Strategy (ISOS) framework, this section defines the key constructs underpinning the model and delineates their theoretical boundaries. In line with the nature of theory-building articles, this section does not rely on operational definitions for empirical testing but instead presents analytical definitions derived from a cross-synthesis of theoretical traditions [100,101].

Circularity. Definition: Circularity refers to the regenerative operational logic that minimizes waste, optimizes resource loops, and extends product lifecycles through design innovation, reuse, and recycling.

Theoretical Foundations: It draws upon circular economy principles [102], cradle-to-cradle design [103], and industrial symbiosis.

Boundary Clarification: Rather than treating circularity as a general sustainability orientation, it is treated as a closed-loop production logic, distinct from linear or semi-linear eco-efficiency approaches. It excludes incremental green practices that fail to reconfigure material or energy flows systemically.

Localization. Definition: Localization encompasses the spatial and institutional reconfiguration of operations to favor proximity sourcing, community-based production, and regionally embedded value chains.

Theoretical Foundations: Anchored in regional resilience theory [104,105], place-based economic development [106,107], and adaptive governance [108,109], localization serves as a systemic counterweight to globalized fragility.

Boundary Clarification: It must be distinguished from decentralization or modular outsourcing. Localization implies a strategic realignment of operations with regional identity, relational embeddedness, and adaptive autonomy, rather than merely shifting operational control.

Digital Adaptation. Definition: Digital adaptation is the process of embedding intelligent technologies—such as IoT, AI, and cyber-physical systems—into operational decision-making to enable real-time responsiveness, predictive analytics, and systemic efficiency.

Theoretical Foundations: Informed by Industry 4.0 discourse [110,111], socio-technical systems theory [112,113], and digital sustainability [114,115], this construct highlights the role of tech-enabled agility.

Boundary Clarification: It is important to distinguish adaptive digital transformation from mere automation. Digital adaptation reflects a context-sensitive capacity for systemic reconfiguration, not just the adoption of tools. It includes organizational learning and agile restructuring at the process level.

Sustainable Operational Core (SOC)

Definition: The SOC is the emergent, integrative space formed by the intersection of circularity, localization, and digital adaptation, resulting in operational models that are regenerative, regionally resilient, and technologically adaptive.

Theoretical Foundations: SOC as a construct is derived conceptually by combining the principles of the triple bottom line [116], systems thinking [117,118], and sustainability transitions [119,120].

Boundary Clarification: The SOC is not a prescriptive blueprint but a conceptual attractor—an ideal-type model that can guide organizational innovation toward sustainability. It is deliberately abstract and sector-agnostic, allowing for contextual adaptation across industries and geographies.

To minimize conceptual drift and definitional inconsistency across sections, a tabular summary of constructs and boundaries is provided in

Table 3. Summary of Key Constructs and Their Boundaries in the ISOS Framework.

Construct	Analytical Definition	Boundary Clarification
Circularity	Regenerative operational logic that minimizes waste, optimizes resource loops, and extends product lifecycles via design innovation, reuse, and recycling.	Treated as closed-loop logic; excludes linear or semi-linear eco-efficiency strategies and green practices that do not fundamentally alter material/energy flows.
Localization	Spatial and institutional reconfiguration toward proximity sourcing, community-based production, and regionally embedded value chains.	Goes beyond decentralization or outsourcing; emphasizes regional identity, embeddedness, and adaptive autonomy.
Digital Adaptation	Embedding intelligent technologies (e.g., IoT, AI, CPS) into operations for real-time responsiveness, predictive analytics, and systemic efficiency.	Differs from basic automation; entails systemic reconfiguration, organizational learning, and agile restructuring to respond to contextual complexity.
Sustainable Operational Core (SOC)	Integrative intersection of circularity, localization, and digital adaptation, forming regenerative, regionally resilient, and tech-adaptive operational models.	SOC is an abstract ideal-type construct; not prescriptive, but flexible across industries and geographies.

. This ensures alignment and avoids redundancy throughout the article.

Summary of the core constructs within the ISOS model, including definitional clarity and theoretical boundaries to guide coherent interpretation and application.

3.4. Proposed Multi-Level Model: Macro (Policy)—Meso (Operations)—Micro (Processes)

To integrate the core constructs of the Integrated Sustainable Operational Strategy (ISOS) into a coherent conceptual architecture, this section introduces a multi-level model that reflects how strategic sustainability in operations is shaped across different levels of decision and action. This structure reinforces the systemic nature of sustainable operations—anchored in external pressures, internally driven by strategic logic, and enacted through operational routines and outcomes. The model is intentionally designed for theory development, not empirical testing, and is thus structured to highlight causal pathways, relational interdependence, and conceptual coherence across levels [121].

At the macro level, the model identifies policy, institutional, and ecological antecedents as the triggering conditions that compel organizations to rethink and realign their operational systems. These include environmental regulations, climate risks, global supply volatility, and stakeholder expectations for ESG compliance [122]. These antecedents are not within the direct control of operations managers, but they form the structural context in which all sustainability strategies are conceived.

The meso level represents the operational core of the ISOS model. Here, three interdependent strategy drivers—Circularity, Localization, and Digital Adaptation—are conceptualized as the mechanisms through which firms can respond to macro-level pressures. These drivers are not tactics or practices but design logics that guide operational transformation. At their intersection lies the Sustainable Operational Core (SOC), a conceptual space where regenerative, regionally resilient, and technologically adaptive operations converge. This level embodies the strategic heart of the ISOS framework.

Finally, at the micro level, the model identifies outcomes in alignment with the TBL: environmental (e.g., waste reduction, emissions minimization), social (e.g., inclusive labor, local empowerment), and economic (e.g., long-term efficiency, innovation capacity). These outcomes do not result from any one driver alone but emerge from the interaction and integration of the three strategic domains, reinforcing the systems thinking foundation of the model [123].

This conceptual structure is visualized in Figure 2, which illustrates the top-down and bottom-up dynamics between antecedents, drivers, and outcomes across macro, meso, and micro layers.

The Integrated Sustainable Operational Strategy (ISOS) Model illustrates how macro-level antecedents (e.g., regulatory, environmental, institutional pressures) inform meso-level strategic design drivers—Circularity, Localization, and Digital Adaptation—which converge at the Sustainable Operational Core. These, in turn, influence micro-level outcomes across environmental, social, and economic dimensions, reflecting the Triple Bottom Line. The model presents a systems-based logic for operational sustainability aligned with policy context and performance goals.

By structuring the ISOS model across these three levels, the framework avoids reductionist tendencies in operational theory and instead presents a multi-scalar, systems-integrative model that is both flexible and conceptually robust. Rather than prescribing one-size-fits-all practices, it offers a conceptual map for organizations to design and evaluate sustainable operational strategies within their own contextual realities. This theoretical clarity is essential for moving the discourse beyond fragmented sustainability tools toward a strategic and scalable transformation agenda—a key objective for conceptual contributions in sustainability and operations management literature [124].

In contrast to prior models such as lean-green integration or Industry 4.0 for sustainability—which often emphasize practice-level tools or technology adoption—the ISOS framework offers a novel design logic by aligning operational transformation with dynamic capability recombination and multi-level contextual fit. The emphasis on the interaction between macro antecedents, meso design drivers, and micro outcomes enables ISOS to function not merely as a practice taxonomy, but as a generative architecture for systemic innovation. This orientation allows ISOS to serve both as a theoretical advancement and a strategic heuristic for organizations navigating complex sustainability transitions under uncertainty and pluralistic stakeholder pressures.

The theoretical clarity and layered structure of the ISOS model lay the foundation for more granular conceptual articulation. To operationalize this framework further, the next section elaborates its internal logic, core design dimensions, and interlinkages that enable strategic alignment across the three levels. This ensures that the model functions not only as an abstract representation but also as a usable tool for theory development and empirical exploration.

4. Integrated Operational Strategies for Circular and Adaptive Sustainability

4.1. Operationalizing Circularity: Closed-Loop Design and Reverse Logistics

Building upon the ISOS framework introduced in the previous section, this chapter provides a detailed articulation of its key components and interdependencies. It aims to deepen the conceptual structure by unpacking the underlying dynamics across strategic design drivers and operational enablers.

Circularity in operations is not merely an environmental imperative but a strategic redesign of value creation and capture. By embedding closed-loop systems such as remanufacturing, design-for-disassembly, and reverse logistics, organizations shift from linear throughput models to regenerative and cyclical flows. These practices serve not only to reduce resource consumption and waste but also to unlock new revenue streams and operational efficiencies [125].

Strategically, circular operations must be evaluated through their causal mechanisms—how do these interventions alter cost structures, compliance trajectories, or innovation pipelines? For instance, in the automotive industry, remanufacturing reduces dependency on virgin materials while supporting modularity in product design, enabling scalability in innovation. In consumer electronics, take-back schemes for e-waste open avenues for secondary market exploitation and reduce compliance risk under growing global e-waste regulations [126].

This strategic framing is presented in

Table 4. Strategic Practices for Circular Operations across Industries.

Industry Sector	Circular Strategy Focus	Strategic Function
Automotive	Remanufacturing and Parts Recovery	Reduces raw material demand; supports modular product innovation
Consumer Electronics	Design for Disassembly and E-Waste Take-Back	Minimizes toxic landfill impact; enables secondary market channels
Apparel and Fashion	Recycled Materials and Product-as-a-Service	Builds brand legitimacy; enables recurring revenue models
Food and Beverage	Bio-packaging and Organic Waste Loops	Reduces landfill fees; appeals to green-conscious consumers
Pharmaceuticals	Reverse Distribution and Expiry Management	Improves inventory efficiency; aligns with health safety compliance

, which summarizes key circular strategies across five high-impact industries along with their underlying strategic functions.

Rather than treating circularity as a set of isolated sustainability tactics, this perspective emphasizes systemic interdependence—where the success of circular operations depends on the alignment of upstream design decisions, midstream logistics capabilities, and downstream market acceptability. Reverse logistics, for instance, cannot be optimized without digital tracking systems and regulatory alignment, which illustrates the tight coupling between operational architecture and institutional scaffolding [127,128].

In sum, operationalizing circularity demands a shift in mindset—from “waste reduction” to “value regeneration.” This paradigm elevates sustainability from peripheral compliance to a core strategic logic embedded in design, sourcing, production, and distribution decisions.

4.2. Localization Strategies: Risk Buffer, Emission Control, and Proximity Value

In an era of escalating geopolitical volatility, energy insecurity, and climate disruption, localization has re-emerged not just as an operational tactic but as a strategic imperative. Unlike the traditional efficiency-maximizing global supply chains, localized operations embed redundancy, proximity, and regional accountability as core enablers of resilience and sustainability [129].

The strategic logic of localization operates across three intertwined dimensions. First, it functions as a risk buffering mechanism: regional sourcing and nearshoring help mitigate supply disruption risks triggered by pandemics, political embargoes, or extreme climate events. By decentralizing production, firms reduce their reliance on long-haul logistics and fragile cross-border flows, thereby enhancing systemic resilience [130].

Second, localization contributes to emission control by reducing transportation distances, which directly supports Scope 3 emission-reduction targets. Moreover, situating operations locally improves traceability and facilitates stronger alignment with region-specific environmental regulations and sustainability mandates [131].

Third, it creates proximity value by embedding production closer to end markets. This enables real-time responsiveness to local demand, enhances cultural and contextual customization, and fosters deeper community engagement—all of which are becoming critical differentiators in markets where sustainability is a key driver of consumer preference and brand loyalty.

To enhance clarity,

Table 5. Strategic Dimensions of Localization and Operational Implications.

Strategic Dimension	Operational Benefits	Potential Trade-offs
Risk Buffering	Enhances supply continuity and logistical agility	May increase unit costs due to smaller scale
Emission Control	Reduces transport-related emissions; improves compliance	May require investment in cleaner local tech
Proximity Value	Boosts responsiveness, community trust, and local brand equity	May face local regulatory or labor complexities

summarizes the three strategic dimensions of localization along with their operational benefits and contextual trade-offs.

These strategic dimensions function interdependently. For instance, nearshoring a food production unit to a drought-prone area might reduce emissions but increase climate risk—thus, localized operations must be matched with context-specific resilience capabilities.

To synthesize these strategic interplays, we propose the Local Resilience-Enabling Capabilities Framework, visualized in Figure 3 below.

A diagram illustrating the integration of risk buffering, emission control, and proximity value, supported by regional logistics infrastructure, regulatory coherence, and cultural embeddedness.

This framework underscores that localization is not a return to protectionism or fragmentation, but a contextual adaptation strategy. It enables organizations to maintain operational continuity and environmental accountability while building embeddedness within local ecosystems. In doing so, localization becomes a transformative lever, not only for survival but also for long-term competitive advantage in the sustainability transition [132].

4.3. Digital Resilience: Real-Time Decisioning and Predictive Monitoring

In the face of increasing volatility, digitalization has evolved from an operational convenience into a strategic necessity for resilience and sustainability. No longer limited to automation or efficiency, digital tools now underpin how organizations sense, respond, and adapt to systemic disruptions—transforming operations into intelligent, anticipatory systems. This shift is encapsulated in the idea of digital resilience, where firms leverage data, algorithms, and connected technologies to build agility, traceability, and robustness into their operations [133].

Three key technologies—Internet of Things (IoT), Artificial Intelligence (AI), and blockchain—form the digital backbone of this resilience logic, each contributing distinct yet complementary capabilities:

IoT: Sensory Infrastructure for Operational Visibility

IoT serves as the sensory infrastructure of modern operations, embedding connected sensors and devices throughout the supply chain—from production lines to delivery fleets. Strategically, this enables real-time monitoring of energy consumption, equipment health, temperature fluctuations, inventory movements, and more [134]. This real-time visibility facilitates dynamic adjustments that reduce waste, prevent downtime, and pre-empt environmental violations.

IoT also strengthens reverse logistics and closed-loop systems by tracking the movement of used goods, enabling efficient product take-back, recycling, or remanufacturing—thus reinforcing circular strategies outlined in Section 4.1.

AI: Cognitive Engine for Predictive and Adaptive Control

Artificial intelligence adds analytical intelligence to operational data, enabling predictive maintenance, demand forecasting, and anomaly detection. Strategically, AI transforms passive data into proactive decisioning, allowing operations managers to simulate scenarios, allocate resources dynamically, and respond to fluctuations before disruptions occur [135].

In the context of sustainability, AI can be trained to optimize multi-objective targets—minimizing emissions while maximizing service levels or balancing resource efficiency with cost stability. In volatile contexts, such adaptability is critical to resilience.

Blockchain: Trust Infrastructure for Transparency and Traceability

Blockchain introduces a decentralized and immutable ledger, which secures data integrity and enhances traceability across actors. In sustainable operations, this technology is particularly valuable in tracking product provenance, enforcing ethical sourcing, and providing audit-proof verification of environmental claims [136,137,138].

Strategically, blockchain enables collaborative resilience in multi-stakeholder networks by removing information asymmetries, which is especially vital for localized and circular ecosystems.

To aid synthesis,

Table 6. Strategic Contributions of Digital Technologies to Resilient Operations.

Technology	Strategic Role in Operations	Sustainability Contribution
IoT	Enables real-time sensing and system-level visibility	Reduces waste, prevents failure, strengthens reverse logistics
AI	Facilitates predictive control and dynamic adaptation	Optimizes multi-objective performance, reduces emissions
Blockchain	Secures data integrity and trust in multi-party networks	Ensures traceability, enforces ethical sourcing

summarizes the strategic functions of these digital technologies in enabling operational resilience.

These digital technologies do not operate in isolation; their strategic value emerges from integration. For example, IoT-generated data becomes actionable when processed by AI, and blockchain secures the credibility of that processed data in multi-party contexts. Together, they establish an intelligent infrastructure that supports continuous learning and rapid reconfiguration—hallmarks of resilient operations.

This digital backbone enhances the Triple Bottom Line: reducing environmental impact through optimized resource use, increasing social trust through transparent governance, and delivering economic benefits through cost avoidance and operational uptime [139,140].

In synthesis, digital resilience redefines the role of technology from a support function to a strategic design pillar. It enables operations to become not just faster, but smarter, cleaner, and more socially accountable—capabilities that are indispensable for navigating and shaping the uncertain terrain of sustainable development.

Recent empirical studies further validate the synergy between digitalization and circular economy objectives. For instance, blockchain-enabled traceability systems are now deployed in electronics and apparel supply chains to certify recycled content and automate closed-loop logistics. Meanwhile, IoT sensors integrated with AI-driven analytics allow real-time remanufacturing decisions and predictive waste reduction, accelerating the transition from linear to regenerative operations. Meanwhile, IoT sensors integrated with AI-driven analytics allow real-time remanufacturing decisions and predictive waste reduction, accelerating the transition from linear to regenerative operations.

This digital backbone enhances the Triple Bottom Line: reducing environmental impact through optimized resource use, increasing social trust through transparent governance, and delivering economic benefits through cost avoidance and operational uptime [141,142].

4.4. Workforce and Process Flexibility for Adaptive Sustainability

While technological enablers and structural reconfiguration provide the backbone of resilient operations, human adaptability and process fluidity remain the most critical and often underestimated levers for sustainable transformation. In the context of sustainability transitions, flexibility is not simply a tactical response to variability—it is a strategic capability that enables systems to absorb shocks, reorient priorities, and evolve continuously across economic, environmental, and social dimensions [143].

Workforce Flexibility as a Strategic Sustainability Lever

Workforce flexibility refers to the capability of employees to shift roles, acquire new skills, and make context-sensitive decisions in response to dynamic operational and environmental conditions. Strategically, a flexible workforce plays a pivotal role in advancing sustainability on multiple fronts.

First, it ensures operational continuity during crises, such as when production staff can be rapidly reassigned to support logistics during supply shocks or emergency disruptions. Second, flexibility enables knowledge recombination, where multi-skilled teams are better positioned to embed sustainability metrics into routine decision-making processes, thereby supporting continuous improvement and adaptive learning [144,145].

Finally, workforce flexibility reinforces social sustainability by encouraging investments in reskilling, employee autonomy, and well-being. These elements not only improve retention rates but also foster organizational citizenship behaviors that are closely aligned with long-term sustainability goals.

This form of flexibility complements digital transformation efforts: AI and IoT may offer data, but it is human workers who often interpret ambiguous signals, make ethical trade-offs, and redesign workflows under pressure. Thus, human–machine complementarity becomes essential to resilient sustainability [146].

Process Flexibility: Reconfigurable Systems for Sustainable Adaptation

Process flexibility refers to the capacity of operational systems to adjust inputs, outputs, and workflows in response to internal or external variability. This capability enhances sustainability by enabling multiple forms of adaptive reconfiguration.

First, flexible systems can switch between different product types or production volumes with minimal downtime, allowing firms to respond swiftly to changing market demands or sustainability-driven design modifications. Second, process flexibility supports the adaptation to alternative materials or energy sources, which is especially valuable when facing shortages, volatile resource pricing, or shifting regulatory requirements.

Third, such systems can re-sequence or bypass certain production stages to meet emergent sustainability compliance needs—such as introducing low-emission subprocesses or omitting resource-intensive steps when possible [147,148]. Collectively, these capabilities make process flexibility a key enabler of sustainable operational transformation.

Strategically, flexible processes enable low-carbon innovation, waste minimization, and dynamic compliance alignment. For example, a food manufacturer with modular batch processing can respond to seasonal crop fluctuations without overproducing or generating excess waste. In the apparel sector, localized microfactories with digital cutting enable on-demand production that reduces inventory and emissions simultaneously.

Interdependence and Strategic Integration

The strategic impact of workforce and process flexibility is maximized when these capabilities are embedded into the broader ISOS framework. Within circular strategies, flexibility enables workers to apply skills in reuse, disassembly, and remanufacturing, while reconfigurable processes allow for batch adjustments using secondary or recycled materials.

In the context of localization, flexibility enhances resilience through cross-functional local teams and modular small-scale production systems that can be easily reallocated or scaled as needed.

Finally, within digital systems, real-time intelligence tools generate adaptive insights, but the ability to act on them requires human flexibility—both in decision-making and in ethical, environmentally sensitive responses.

In this way, flexibility functions not merely as an operational trait, but as a systemic connector that enables meaningful convergence across strategic domains within the ISOS model.

4.5. Synthesis: Interdependency and Trade-Off Management

The three strategic domains—Circularity, Localization, and Digital Adaptation—do not operate in isolation. Rather, their interconnections form a complex adaptive system in which trade-offs and synergies must be continually managed to achieve sustainable operational performance. Understanding the causal logic and dynamic interplay among these strategies is essential for organizations aiming to move beyond compliance toward strategic sustainability leadership [149].

Strategic Interdependency Across Domains

Each strategic domain within the ISOS framework contributes distinct capabilities, but their full value is realized through their dynamic interactions.

The synergy between circularity and digital adaptation is evident in how the success of circular operations—such as reverse logistics and remanufacturing—often depends on digital traceability. Tools like IoT-enabled product passports allow firms to track materials across lifecycles and anticipate reuse opportunities. In addition, AI-driven demand forecasting minimizes overproduction, thereby reinforcing circular outcomes and reducing waste [150,151].

The interdependency between localization and circularity is equally significant. Regional sourcing strengthens circular goals by reducing transportation-related emissions and streamlining reverse material flows. Furthermore, localized knowledge supports context-sensitive circular practices, including community-based recycling initiatives and industrial symbiosis tailored to regional characteristics [152].

Lastly, the interaction between digital adaptation and localization facilitates real-time monitoring at the regional level, enabling agile responses to localized disruptions such as extreme weather events or labor shortages. Digital platforms—including cloud systems and distributed ledgers—enhance coordination across decentralized operational hubs, sustaining performance while respecting the autonomy and specificity of local contexts [153,154].

These synergies form the basis for adaptive sustainability—an organizational ability to dynamically balance economic efficiency, environmental stewardship, and social equity through strategic configuration of interconnected capabilities.

Navigating Trade-Offs: Strategic Tensions and Resolutions

With interdependency comes inevitable trade-offs. One central tension lies between efficiency and redundancy. Localization strategies often require distributed facilities, which introduce additional costs and may appear to conflict with lean operational principles. However, under conditions of systemic risk—such as global supply chain disruptions—this redundancy functions as a strategic buffer, enhancing resilience and ensuring continuity [155].

A second trade-off emerges between speed and sustainability. Real-time digital systems enable operational agility and responsiveness, but an over-reliance on automation without adequate human oversight can potentially undermine ethical or social objectives. The strategic response involves embedding human-in-the-loop decision-making mechanisms, which preserve ethical alignment while maintaining the benefits of digital speed [156,157].

The third key tension involves standardization versus customization. Circularity often relies on modular design and standardization to enable reuse and closed-loop flows, while localization demands customization to meet specific regional, cultural, or regulatory conditions. This dilemma can be resolved through the implementation of configurable systems that maintain a standardized core architecture while allowing flexibility and adaptation at the periphery [158].

Rather than attempting to eliminate these trade-offs entirely, the strategic goal is to design operational systems that render tensions visible and manageable—through transparency, dynamic prioritization, and multistakeholder alignment.

Systemic Perspective for Strategic Alignment

Managing interdependencies and trade-offs requires a systems-thinking orientation—one that accounts for both short- and long-term implications across the triple bottom line. To achieve this, organizations must adopt several interrelated capabilities.

First, they need to establish cross-functional governance mechanisms that enable sustainability decisions to be coordinated across departments, business units, and geographical locations. These mechanisms ensure alignment in goal-setting, resource allocation, and accountability for outcomes.

Second, firms should develop and implement strategic metrics and dashboards that provide real-time visibility into the consequences of operational trade-offs. These tools help decision-makers recognize when short-term gains may compromise long-term environmental or social goals, and vice versa.

Third, the integration of feedback loops and scenario modeling is critical. These tools allow organizations to anticipate unintended outcomes, simulate potential configurations, and adjust strategies dynamically based on new data and emerging conditions [159,160].

Through this systemic orientation, firms are better equipped to align operational decisions with broader sustainability objectives, while remaining adaptable in the face of complexity and uncertainty.

These adaptive mechanisms are most effective when embedded within multi-actor governance structures that support transparency, accountability, and cross-sector learning. The ISOS model, as visualized in Figure 2, supports this systemic logic by structurally aligning macro-level conditions with meso-level drivers and micro-level outcomes, reinforcing the idea that sustainability is not a fixed state, but a managed process of trade-off negotiation and capability recombination.

To make this idea more concrete, the Sustainable Operational Core (SOC) can be understood as the strategic configuration of operations where circularity, localization, and digital adaptation converge and function as an integrated system—customized to industry context. For example, in the fast food supply chain, the SOC may consist of localized sourcing from regional farmers (localization), real-time demand prediction using AI for minimizing food waste (digital adaptation), and composting or biodigestion systems for waste management (circularity). In contrast, for an electronics manufacturing firm, the SOC might involve modular product design for easy disassembly (circularity), distributed repair hubs in emerging markets (localization), and blockchain-based tracking of critical minerals for compliance and transparency (digital adaptation). These SOCs reflect sector-specific applications of ISOS that embed sustainability into the operational heart of the organization—not as add-ons, but as fundamental design principles.

To further clarify the internal logic and applied relevance of the ISOS model,

Table 7. Mapping ISOS Strategic Pillars to Thematic Research Propositions.

Strategic Pillar	Thematic Focus	Key Proposition
Circularity	Resource efficiency and material reuse	Circular practices enhance operational sustainability when supported by traceability and modular design.
Localization	Regional resilience and adaptive supply	Localization strengthens system resilience and reduces emissions through proximity and redundancy.
Digital Adaptation	Data-driven agility and optimization	Digital tools improve sustainability alignment through real-time monitoring and predictive decision-making.
Pillar Interdependency	Trade-off management and systemic synergy	The convergence of all three pillars enables adaptive sustainability through managed tensions and strategic alignment.

summarizes the mapping between its three strategic pillars and the key thematic propositions that guide sustainable operations.

To make this idea more concrete, the Sustainable Operational Core (SOC) can be illustrated through real-world operational examples that showcase the integrated application of circularity, localization, and digital adaptation across different sectors.

In the textile and flooring industry, Interface Inc. exemplifies the ISOS logic by embedding circularity through modular carpet tile design and closed-loop material flows. The company sources recycled nylon, implements take-back programs for used tiles, and leverages blockchain for material traceability and certification—enabling transparency across its supply chain. Simultaneously, its regional manufacturing hubs enhance localization by minimizing transportation emissions and enabling faster market responsiveness. These initiatives are digitally coordinated through IoT-enabled inventory systems and energy monitoring platforms, reinforcing adaptive operations.

In the agri-food sector, Danone Indonesia applies a multi-level sustainability strategy that integrates local sourcing with digital precision. The company partners with over 100,000 smallholder dairy farmers, building proximity-based supply networks that enhance food security and rural empowerment. Through IoT sensors and AI-based analytics, Danone monitors milk quality, traceability, and cold chain efficiency in real time—significantly reducing waste and ensuring compliance. Additionally, the company embeds circularity through recyclable packaging and nutrient loop initiatives, such as utilizing organic by-products as animal feed or biofertilizer.

These examples demonstrate how the ISOS framework can be translated into sector-specific strategies that are both theoretically grounded and practically actionable. Rather than operating as abstract principles, the integration of circularity, localization, and digital adaptation enables firms to construct resilient, context-aware, and sustainability-aligned operational systems.

These examples reaffirm the theoretical stance of this paper: that sustainability and competitiveness are not conflicting objectives, but can co-evolve through integrative, context-sensitive operational design.

5. Conceptual Contributions

5.1. Redefining Operational Excellence in the Anthropocene

The notion of operational excellence has traditionally been defined through the lens of efficiency, consistency, and waste reduction, often benchmarked by lean metrics, productivity ratios, and cost-per-unit indicators. However, the Anthropocene—an era defined by unprecedented human impact on planetary systems—demands a radical rethinking of this paradigm. Efficiency alone no longer suffices as a guiding logic when supply chains are disrupted by climate volatility, ecological degradation, and social instability [161].

This article argues for a shift toward “sustainability-integrated operational excellence”—an expanded conceptualization that embeds resilience, adaptability, and regenerative value into the heart of operational strategy. The Integrated Sustainable Operational Strategy (ISOS) model proposed here provides a multi-dimensional framework to address this transformation.

Integrating Global and Local Operational Logics

One of the central theoretical contributions of this framework lies in its multi-scalar architecture. Rather than framing sustainability as either a top-down compliance mandate or a localized corporate social responsibility (CSR) effort, the ISOS model integrates macro-level elements (such as policy and global governance), meso-level organizational operations, and micro-level process practices into a coherent, aligned system [162,163].

This nesting of scales enables firms to translate global sustainability standards—including the Sustainable Development Goals (SDGs) and Conference of the Parties (COP) commitments—into locally actionable operational strategies. It also supports the customization of circular and digital strategies to fit regional infrastructure conditions, regulatory frameworks, and socio-cultural dynamics.

In addition, this approach allows organizations to harmonize decision-making across diverse geographies while preserving contextual sensitivity and local relevance. In doing so, the ISOS model positions sustainability not as a binary choice between global uniformity and local flexibility, but as a dynamic system that integrates both logics strategically.

This approach resolves a key tension in sustainability literature: the disconnect between global ambitions and local capabilities, providing a framework that is both normative and executable.

Bridging Technological and Organizational Dimensions

Operational excellence in the Anthropocene requires more than technological sophistication—it demands the integration of digital enablers with organizational transformation. The ISOS model rejects a deterministic interpretation of Industry 4.0. Instead, it positions advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and blockchain not as standalone solutions, but as strategic enablers embedded within broader sustainability goals.

These technologies support circular logistics by enabling material traceability, reverse flow optimization, and predictive analytics that anticipate reuse or remanufacturing needs. They also enhance resilience through tools like digital twins and real-time system monitoring, which allow firms to detect and respond swiftly to disruptions. Furthermore, they contribute to governance innovation by facilitating mechanisms such as smart contracts, which can enforce sustainable procurement criteria and increase transparency in supplier relationships.

By linking technological capabilities with organizational strategy, the model ensures that digital transformation is aligned with sustainability outcomes—bridging the often-siloed domains of IT systems and operational ethics.

This perspective situates technology within a socio-technical system, where outcomes depend on how tools are integrated with human decision-making, institutional structures, and ethical values [164,165]. The ISOS framework thus encourages a deliberate, embedded use of digital tools to reinforce sustainability goals, not bypass them.

Balancing Economic, Social, and Ecological Value

Perhaps the most transformative contribution of the ISOS framework lies in its redefinition of what constitutes operational value. Traditional models often prioritize economic efficiency, treating social and ecological considerations as secondary or external to the core of operations. In contrast, the ISOS model draws from the logic of the triple bottomline to position economic, social, and environmental dimensions as interdependent strategic assets rather than competing priorities.

Through this lens, circularity is seen not only as an ecological imperative, but also as a pathway to economic efficiency by reducing waste, recovering value, and minimizing input costs. Localization, likewise, contributes to operational resilience by embedding production within communities, fostering stronger stakeholder relationships, and creating shorter, more adaptive value loops. Meanwhile, digital adaptation enhances transparency, trust, and accountability across the value chain, allowing stakeholders to verify sustainability performance and enabling data-driven governance.

This reframing of value encourages organizations to move beyond extractive operational logics toward integrated systems that regenerate, empower, and sustain—economically, socially, and ecologically.

By articulating how these pillars intersect and reinforce one another (see Figure 1), the model moves beyond sustainability as risk mitigation toward sustainability as value creation. It aligns with the emerging discourse in operations management that argues for integrated, stakeholder-inclusive performance systems [166].

Reframing Excellence as Adaptive Capacity

Finally, this conceptualization reframes the notion of operational excellence—not as static efficiency or linear optimization—but as adaptive capacity: the organizational ability to sense, interpret, and respond to shifting environmental and market dynamics in ways that regenerate both institutional and ecological resources. This approach echoes principles of systems resilience while embedding them directly within the realm of operational decision-making.

The ISOS model encourages firms to build redundancy in areas of high fragility, such as developing local sourcing strategies to buffer against geopolitical disruptions. It also promotes modularity and configurability in both processes and products, enabling flexible adaptations—particularly through circular design principles. Additionally, it places emphasis on continuous learning and strategic realignment, supported by real-time data systems and feedback loops that allow for agile decision-making in uncertain conditions.

Through this reframing, operational excellence becomes less about minimizing variation and more about cultivating resilient responsiveness, positioning firms to thrive amid volatility while contributing to long-term sustainability goals.

Thus, excellence becomes not the absence of error or waste, but the presence of strategic flexibility, cross-functional coherence, and stakeholder legitimacy—operationalized through a design logic that transcends technocentric and efficiency-based frameworks. The ISOS model contributes a distinct integrative grammar by embedding circularity, localization, and digital adaptation into a multi-level structure that aligns macro-level imperatives with meso-level strategy and micro-level outcomes. This conceptual clarity and systemic orientation mark ISOS as a novel approach to sustainable operational excellence.

5.2. Theoretical Implications for Sustainability Science and Operations Management

The Integrated Sustainable Operational Strategy (ISOS) model contributes to both sustainability science and operations management (OM) by addressing several theoretical limitations and proposing a unifying conceptual logic. In particular, this framework responds to the fragmented discourse that has often treated sustainability, resilience, and operational excellence as separate or even competing paradigms [167,168]. By integrating them into a coherent and multi-level structure, the model offers three core theoretical contributions:

• Cross-Scalar Integration: From Global Norms to Local Capabilities

Traditional models in operations management (OM) have predominantly concentrated on firm-level optimization, while sustainability science has focused on global systems change and ecological thresholds. This divergence has created a conceptual vacuum in which organizations often lack effective tools to translate global sustainability goals into actionable strategies at local or regional levels.

The ISOS model addresses this gap through a nested architectural approach that links multiple levels of sustainability logic. At the macro level, it incorporates global imperatives such as SDG 9 on infrastructure, SDG 12 on responsible production, and SDG 13 on climate action. At the meso level, it emphasizes organizational strategies such as circular redesign, localization, and digital transformation. Finally, at the micro level, the model integrates process-level capabilities like predictive monitoring and flexible workflows.

This triadic structure fosters theoretical alignment between planetary boundaries and operational boundaries [169], enabling organizations to ground the abstract principles of sustainability science in the concrete language and actionable frameworks of operations management.

Unlike frameworks such as lean-green integration that concentrate on operational trade-offs, or resilience-based OM models that focus on response capabilities without ecological coupling, ISOS embeds a triple-scale logic that connects global policy with localized operational enactment—bridging levels that previous models often treat in isolation.

2.

Bridging Technological and Organizational Paradigms

Much of the existing literature on Industry 4.0 and digital transformation tends to emphasize the technical dimension of change while overlooking the organizational behavior, governance structures, and underlying values that shape technological outcomes. The ISOS framework challenges this siloed view by reconceptualizing digital tools not merely as instruments of efficiency, but as adaptive enablers embedded within socio-technical systems.

In doing so, the model bridges three critical layers. First, it integrates technological capabilities, such as IoT for real-time traceability and data-driven optimization. Second, it embeds these technologies within organizational routines, including cross-functional decision-making processes and agile operational governance. Third, it connects both to cultural and ethical dimensions, such as transparency, stakeholder trust, and sustainability-driven accountability.

This integrated perspective aligns with emerging sustainability scholarship that calls for holistic system innovation—moving beyond piecemeal technical fixes toward transformative structural change [170,171]. It also reinforces the concept of organizational ambidexterity: the ability to balance rapid technological innovation with resilient, human-centered governance.

ISOS moves beyond deterministic Industry 4.0 models by positioning digitalization not as the centerpiece, but as one of three equal pillars—integrated with material circularity and spatial proximity—to enable contextual, values-driven transformation.

3.

Reconceptualizing Operational Value: From Efficiency to Regeneration

The ISOS model challenges the monodimensional conception of value that has traditionally dominated operations management (OM), where economic efficiency is often prioritized at the expense of social and environmental concerns. By integrating the TBL—economic, social, and ecological value—into operational decision-making, the framework introduces a regenerative logic that positions sustainability not as a constraint but as a generative force within organizational design.

Within this model, circularity functions as a value amplifier, enabling material recovery, design reuse, and waste minimization that translate into both ecological gains and economic efficiency. Localization acts as a resilience multiplier, strengthening operational continuity, reducing exposure to global volatility, and embedding firms within local ecosystems. Meanwhile, digitalization serves as an enabler of transparency and coordination, facilitating real-time insight, accountability, and adaptive responsiveness across complex supply networks.

This holistic reconceptualization advances the literature by reframing sustainability not as a downstream result, but as an upstream organizing logic—a core determinant of strategy and system architecture [170,172]. It diverges from legacy models that treat sustainability as a by-product or externality, instead embedding it as a structural design principle within the heart of operations.

This approach diverges from prior models that treat sustainability as a by-product or add-on to existing practices, and instead frames it as a structural design logic embedded in the core of operations.

Implications for Theory Building in Operations Management

The ISOS model functions not only as a practical roadmap for sustainability-driven transformation, but also as a theoretical scaffolding that can expand the boundaries of operations management (OM) scholarship. It enables researchers to develop multi-level constructs that transcend traditional functional silos—linking supply chain management, product design, human resources, and organizational strategy within an integrated operational architecture.

Furthermore, the model encourages scholars to formulate theories rooted in dynamic capabilities, with a specific emphasis on navigating environmental uncertainty—going beyond market turbulence to include climate volatility, regulatory flux, and societal expectations. It also advances the development of systems-based operational theories, grounded in complexity science and interdependence, where feedback loops, emergent properties, and nonlinearity become central analytical elements.

Through these contributions, the ISOS framework invites OM researchers to redefine the unit of analysis—from isolated firm-level efficiency metrics toward systemic value flows and deeper ecological embeddedness. In doing so, it opens space for a new generation of theory building that is both contextually responsive and globally relevant.

Implications for Sustainability Science

From the perspective of sustainability science, the ISOS model offers key theoretical and practical contributions by translating abstract sustainability goals—such as those embedded in the SDGs—into actionable operational design logics. This bridge between normative vision and organizational reality strengthens the applicability of sustainability principles within complex industrial contexts.

The framework also serves as a platform for operational experimentation within broader sustainability transitions, enabling researchers and practitioners to test, iterate, and refine interventions in real-world systems. In doing so, it emphasizes the centrality of operations as a domain of transformation, not merely implementation.

Moreover, the ISOS model encourages the study of institutional and technical co-evolution, highlighting how infrastructure, governance mechanisms, and operational strategies mutually shape and constrain one another. This perspective opens the door for interdisciplinary dialogue that connects sustainability science with organizational theory, industrial ecology, and innovation systems.

By cross-pollinating with operations management, the model enriches sustainability theory—underscoring that transitions are not solely political, economic, or behavioral, but also deeply operational in nature.

Despite the integrative strengths of the ISOS model, organizations may encounter operational trade-offs that stem from tensions between its constituent dimensions—circularity, localization, and digitalization. These tensions often manifest in three interrelated forms:

First, economic–ecological trade-offs may arise when implementing circular strategies requires upfront capital expenditure, such as investment in reverse logistics or renewable inputs, which may reduce short-term profitability. Second, scale–resilience trade-offs emerge in localization efforts; decentralizing production can enhance supply chain agility but may increase per-unit costs and operational complexity. Third, efficiency–transparency trade-offs may be triggered by digitalization; systems that improve traceability and accountability often require resource-intensive data infrastructures and continuous organizational learning.

Such tensions are not unique to ISOS but are emblematic of sustainability transitions in complex systems. Drawing on trade-off theory in strategic operations, these dilemmas should not be viewed as binary choices but as optimization opportunities across dynamic frontiers. Organizations can apply mitigation strategies, such as staged investment (phasing circular innovations), hybrid sourcing (balancing global-local mix), and platform governance (modularizing digital integration), to reduce friction while preserving strategic coherence.

At a theoretical level, acknowledging these tensions reinforces the utility of ISOS as a non-linear framework—one that embraces bounded rationality, path dependence, and emergent learning as central features of sustainable operations. Rather than prescribing one-size-fits-all blueprints, the model encourages contextualized experimentation and adaptation, reflecting the plural and evolving nature of sustainability logics.

Ultimately, it is in navigating these trade-offs—not avoiding them—that organizations cultivate genuine resilience, innovation, and legitimacy in the sustainability era.

5.3. Managerial and Policy Implications: Strategic Integration over Silos

The Integrated Sustainable Operational Strategy (ISOS) model provides a set of pragmatic insights for both managers and policymakers, particularly in addressing one of the most persistent barriers to sustainability: the fragmentation of efforts across organizational silos. In many organizations, sustainability initiatives such as circularity, localization, and digital transformation are pursued as disconnected programs—often led by separate departments, funded by independent budget lines, and assessed through narrowly defined performance indicators. This fragmented approach dilutes impact, creates redundancy, and undermines the systems thinking needed for transformative change.

The ISOS framework responds to this challenge by offering a multi-dimensional integration logic that enables strategic coherence across levels and functions. First, it aligns global policy agendas—such as the Sustainable Development Goals (SDGs)—with local operational realities, ensuring that high-level commitments translate into actionable practices on the ground. Second, it bridges technological architectures—such as IoT, blockchain, and predictive analytics—with organizational routines, embedding digital tools into everyday decision-making rather than treating them as bolt-on solutions. Third, it reconciles short-term efficiency gains with the pursuit of long-term regenerative value creation, ensuring that tactical wins do not compromise strategic sustainability objectives.

This integrative logic supports not only operational alignment, but also enables more coherent investment, governance, and policy design, fostering cross-functional collaboration and sectoral convergence in the journey toward sustainable industrial transformation.

• For Managers: Operationalizing Integration at the Strategic Core

For business leaders, the ISOS model serves as a blueprint for strategic alignment, enabling sustainability to be embedded not at the periphery but at the very heart of operational decision-making. Rather than treating sustainability as a corporate social responsibility (CSR) add-on, the model repositions it as a core logic that guides cross-functional planning and execution.

One of the key managerial levers is the establishment of cross-functional governance structures that unite operations, supply chain, information technology, human resources, and sustainability departments under a shared strategic agenda. This integration fosters collective ownership, reduces coordination breakdowns, and enhances organizational agility in responding to sustainability challenges [173].

Another critical lever is investment prioritization, whereby managers use the ISOS model to identify high-leverage areas where circular practices, digital technologies, and localized resilience strategies mutually reinforce one another. For example, investing in blockchain infrastructure can improve reverse logistics tracking, while predictive analytics can inform localized inventory buffering—thus simultaneously advancing environmental, operational, and risk management goals.

Finally, the ISOS framework calls for the adoption of integrated metrics that move beyond siloed key performance indicators. Rather than tracking cost reduction or carbon footprint in isolation, managers are encouraged to adopt triple bottom line performance indicators that allow for the dynamic balancing of economic, environmental, and social trade-offs. This metric integration supports long-term strategic coherence and aligns day-to-day decisions with broader sustainability ambitions [174].

Stepwise Strategy for Implementation:

(1)

Initiate cross-functional dialogues to align vision and language;

(2)

Conduct operational sustainability audits to map existing silos;

(3)

Identify intersection points between circularity, localization, and digital tools;

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Co-develop pilot projects in selected business units or facilities.

Illustrative Scenarios:

To demonstrate the practical applicability of the ISOS model, consider two sector-specific examples that highlight how its core pillars—circularity, localization, and digital adaptation—can be integrated in real-world settings.

In the automotive industry, a firm might adopt the ISOS framework by establishing local remanufacturing hubs, thereby advancing both circularity (through component reuse and lifecycle extension) and localization (by reducing reliance on global supply chains). This strategy can be further enhanced through real-time inventory tracking systems, enabled by digital tools such as RFID or IoT sensors, which support just-in-time reverse logistics and reduce material waste.

In the food processing sector, companies can improve sustainability performance by combining localized sourcing with AI-driven shelf-life prediction algorithms. This approach enables firms to reduce spoilage, improve distribution accuracy, and optimize storage conditions—all while simultaneously activating the three ISOS pillars: digital intelligence, regional adaptability, and closed-loop thinking.

These illustrative scenarios show how the ISOS framework empowers managers to navigate operational uncertainty, respond proactively to regulatory expectations, and build competitive advantage. By embedding adaptability and sustainability as dual pillars of operational excellence, organizations can move beyond compliance and toward long-term, systemic value creation.

2.

For Policymakers: Enabling Systemic Transitions Beyond Compliance

The ISOS model offers valuable guidance for policymakers aiming to translate global sustainability goals—such as the SDGs or COP commitments—into enforceable and contextually grounded frameworks at national and regional levels. Rather than focusing on narrow compliance mechanisms, the model encourages a shift toward systemic enabling conditions that support integrated, long-term transformation across industries.

First, policymakers are urged to design interconnected incentive structures. Instead of issuing isolated policy tools—such as tax credits solely for digitalization or recycling subsidies in isolation—governments can foster innovation ecosystems that link environmental, technological, and regional development objectives. For instance, coordinated incentives that simultaneously support digital traceability, circular production, and local supply chains can activate ISOS pillars in a synergistic manner.

Second, the ISOS model highlights the need to develop regional platforms and infrastructures through public–private partnerships. These platforms can facilitate data sharing, establish reverse logistics networks, and invest in localized renewable energy systems. Such system-level enablers expand beyond firm-level interventions, reinforcing the institutional scaffolding necessary for sustainable industrial transformation [175].

Third, to strengthen the meso- and micro-layers of sustainability transitions, policymakers should support capability building across regional ecosystems. This includes investment in workforce reskilling, circular economy education, and local supplier development—all of which expand the adaptive capacity and innovation potential of organizations embedded in diverse geographies.

In essence, the ISOS framework provides policymakers with a strategic lens to move beyond fragmented interventions, enabling the design of multi-scalar policy environments that are aligned with operational realities and resilient to future disruptions.

Policy Co-Creation

In addition to designing incentives and enabling platforms, governments can engage in policy co-creation by collaborating with industry associations and sectoral actors to develop context-specific blueprints for sustainable operations. This approach emphasizes joint design over top-down enforcement, positioning the public sector as a facilitator of systemic capability building rather than merely a regulator.

For example, governments can work alongside stakeholders in the agro-industrial sector to develop digital traceability standards that enhance transparency and accountability across supply chains. Similarly, circular procurement guidelines can be collaboratively formulated for public infrastructure projects, aligning contractor incentives with environmental goals and long-term asset circularity.

This co-creative orientation reframes policy from a compliance-driven mechanism to an enabling infrastructure for innovation and transformation. Rather than imposing one-size-fits-all mandates, policy becomes a platform through which systems-level change is co-constructed, adapted, and scaled with the support of those directly involved in implementation.

3.

Shared Imperative: Breaking the Trade-off Mentality

Perhaps the most critical implication shared across both managerial and policy spheres is the urgent need to abandon the trade-off mentality—the outdated belief that economic competitiveness, environmental protection, and social responsibility are inherently in conflict. The ISOS framework offers a conceptual and strategic foundation to move beyond this zero-sum thinking by demonstrating that integration, rather than separation, yields the most robust and resilient operational outcomes.

Through deliberate strategic design and operational synchronization, firms and governments can pursue sustainability goals without sacrificing economic viability. For instance, circular design not only reduces environmental impact but also drives cost efficiency by minimizing waste and creating value from by-products. Similarly, localized supply strategies do more than reduce transportation emissions—they also lower supply chain risk and improve responsiveness during disruption. Meanwhile, digital enablers, such as predictive analytics and blockchain traceability, enhance operational agility and foster transparency across the value chain.

The ISOS model reframes sustainability not as a constraint, but as a multiplier of long-term strategic advantage—a paradigm that is essential for navigating the complexities of the Anthropocene economy.

This integrative logic reframes sustainability as a platform for innovation and resilience, not a burden of compliance or cost. It realigns actors across value chains, governance levels, and stakeholder domains toward shared systemic outcomes.

Concluding Perspective

In conclusion, sustainability emerges as a competitive capability—not as the product of isolated programs or compliance checklists, but as the outcome of strategically synchronized systems. The ISOS model challenges both managers and policymakers to step into the role of architects of coherence, shaping integrated operational landscapes where long-term value creation transcends short-term optimization.

This shift calls for a movement from siloed interventions toward strategic alignment, where cross-functional initiatives are guided by unified sustainability logic. It also demands a transition from incremental improvements to transformational integration, embedding sustainability at the heart of operational strategy rather than treating it as an adjunct. Finally, it urges organizations to replace fragmented KPIs with systemic value frameworks, enabling a holistic understanding of performance that accounts for ecological, social, and economic dimensions simultaneously.

In doing so, the ISOS framework not only redefines operational excellence, but also provides a strategic compass for navigating complexity, fostering innovation, and leading meaningful sustainability transitions in the Anthropocene era.

Such integrative thinking is essential not only for achieving the SDGs, but also for building organizational and societal resilience in the face of compounding global disruptions.

Future studies may also integrate stakeholder-based evaluation frameworks to assess how ISOS configurations are perceived and adapted by different actors—such as suppliers, regulators, communities, and consumers. This direction opens avenues for co-design methodologies and participatory scenario testing, particularly in high-variability sectors. Investigating how different stakeholders negotiate operational trade-offs and legitimacy concerns could enrich both theoretical robustness and practical applicability of the ISOS model.

5.4. Limitations of Current Framework and Boundary Conditions

While the Integrated Sustainable Operational Strategy (ISOS) model offers a novel synthesis across multiple dimensions—spanning global–local scales, technological and organizational mechanisms, and economic–social–ecological values—it is essential to recognize the framework’s limitations and define its boundary conditions with conceptual clarity. This transparency not only enhances theoretical rigor but also guides appropriate application and future extensions.

(1)

Theoretical Scope and Abstraction Level

The ISOS model is a conceptual integration rather than an empirical generalization. Its purpose is not to quantify direct causal relationships, but to provide a structured synthesis that brings together fragmented constructs from operations management, sustainability science, and systems theory [176]. As such, the model operates at a high level of abstraction, which may limit its immediate operationalizability without contextual adaptation. Organizations seeking to implement the model will need to translate it into actionable strategies tailored to their specific industry, geography, and maturity level.

(2)

Sectoral and Institutional Variability

The framework assumes a level of institutional readiness and policy support that may not exist uniformly across regions. In developing economies with weak regulatory infrastructures or fragmented supply chains, key enablers such as reverse logistics systems, data infrastructures, and policy coherence may be insufficiently developed [177,178]. Consequently, the model’s applicability could be constrained in such contexts unless supported by complementary public–private capacity-building initiatives.

Similarly, sectoral dynamics vary considerably: what works in automotive manufacturing may not directly transfer to textiles or food systems. The model must therefore be seen as sector-agnostic in structure, but sector-sensitive in application.

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Interdependency Management and Trade-off Complexity

While the ISOS framework offers a compelling architecture for integrating circularity, localization, and digitalization, it does not prescribe a universal method for navigating the complex trade-offs and temporal misalignments that can arise from their interaction. The framework is deliberately flexible, allowing adaptation across contexts; however, this flexibility also introduces managerial ambiguity when competing priorities must be reconciled.

For instance, digital transformation initiatives often depend on centralized data architectures and harmonized platforms to ensure traceability, analytics, and integration at scale. In contrast, localization strategies emphasize decentralized decision-making, regional autonomy, and context-specific agility—potentially creating structural tensions between standardization and responsiveness.

Similarly, while circular design can yield long-term environmental and economic benefits, its implementation often involves extended payback periods and upfront investments in redesign, reverse logistics, or material innovation. These time horizons may conflict with short-term financial performance expectations, particularly in sectors driven by quarterly reporting or cost-centric KPIs.

Although the “win–win school” of sustainability argues that operational efficiency and sustainability goals can be synergistically aligned, the ISOS model acknowledges that such alignment is contingent rather than guaranteed.

This reflects the broader discourse in OM theory, where the tension between integration and specialization has long been explored, particularly through the lens of trade-off theory and the foundational debates initiated by Skinner and later extended by Schmenner.

Rather than resolving these tensions, ISOS encourages firms to adopt a dynamic prioritization logic based on strategic intent, system maturity, and stakeholder alignment.

Thus, the ISOS model highlights strategic interdependencies, but leaves open the question of how organizations dynamically prioritize, sequence, or balance these elements—a challenge that future research must address through empirical testing, scenario analysis, and organizational learning models.

Moreover, in resource-constrained environments, partial digitalization may result in sunk costs without long-term support, and attempts at localization may duplicate functions inefficiently or generate electronic waste if technological coordination is weak.

The model illuminates these tensions but does not resolve them through a specific decision-making tool or algorithm. Hence, it serves better as a guiding logic than a deterministic blueprint.

(4)

Sustainability Value Interpretation

The ISOS model adopts a triple bottom line approach, aligning with global SDGs and embedding social, ecological, and economic values into operational thinking. However, the interpretation of “sustainability value” remains contextual and contested—what constitutes “sustainable” may differ across stakeholder groups (e.g., shareholders, communities, regulators) and across time horizons (short-term gains vs. long-term system viability) [179].

This ambiguity may be amplified in cross-cultural or multi-stakeholder settings, where normative values and priorities diverge. As such, consensus-building mechanisms—such as participatory governance or stakeholder co-design—become necessary to navigate competing interests.

Future work should consider integrating stakeholder engagement mechanisms into the operational governance structures proposed by ISOS.

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Need for Empirical Grounding and Evolution

Lastly, although this article deliberately avoids empirical data collection—as it seeks to contribute to the conceptual domain of theory building—the model’s validity and utility ultimately depend on empirical interrogation, contextual validation, and iterative refinement. Its current form reflects a synthesis of literature and theory; the next stage must involve comparative case analyses, system dynamics modeling, or action research to explore how the ISOS framework behaves in complex operational environments.

In summary, while the ISOS model provides a robust conceptual map for rethinking sustainable operations, its limitations include the need for contextual adaptation, stakeholder alignment, interdependency navigation, and future empirical enrichment. In particular, implementation risks in developing contexts must be carefully managed—including digital divide issues, limited institutional support, the risk of technology obsolescence, and unintended environmental externalities such as e-waste from digitization or production inefficiencies from over-localization. Recognizing these boundary conditions enhances both its credibility and usability, ensuring it is applied not as a rigid doctrine but as a flexible strategic compass guiding transitions toward resilient and regenerative operations in the Anthropocene.

By explicitly reflecting on the dialectic between trade-offs and synergies, the ISOS framework not only bridges competing schools of thought in operations theory, but also invites a new generation of empirical and theoretical work to explore how sustainability-driven transformation unfolds in diverse organizational realities.

These conceptual limitations and boundary conditions do not reduce the model’s theoretical relevance, but rather provide important guideposts for empirical exploration. In the next section, we develop a set of testable propositions and methodological directions that operationalize the ISOS framework into actionable research paths. This continuation ensures coherence between the framework’s conceptual foundation and its empirical applicability.

5.5. Practical Indicators of ISOS

To enhance the practical applicability of the ISOS model, this section introduces a set of concrete indicators that enable organizations and researchers to translate the model’s conceptual pillars—circularity, localization, and digitalization—into actionable strategic metrics. These indicators serve as directional tools for assessing alignment, diagnosing operational readiness, and guiding implementation decisions.

To support this practical translation,

Table 8. Practical Indicators for Implementing ISOS Pillars.

ISOS Pillar	Strategic Focus	Practical Indicators	Illustrative Metrics/Questions
Circularity	Closed-loop resource use, waste minimization	- % of materials reused or recycled - Product design for disassembly - Reverse logistics presence	What % of production input comes from recycled content? Is there a take-back program in place?
Localization	Regional sourcing, context-specific responsiveness	- % of procurement from local suppliers - Local workforce ratio - Customization to local needs	How much of the supply chain is domestically embedded? Are local R&D centers active?
Digitalization	Data-driven operations, intelligent systems	- Adoption of AI/IoT systems - Real-time data visibility across supply chain - Cybersecurity index	Are predictive analytics used in operational decisions? How integrated are digital dashboards?
Integration Mechanism	Cross-pillar synergy and alignment	- Conflicts or complementarities mapped - % of integrated initiatives - Strategy coordination forum	Are there tensions between local autonomy and centralized digital control? Is there a platform for resolving such tensions?

below synthesizes key indicators for each ISOS pillar, providing illustrative questions and metrics that can be adapted based on sectoral needs, organizational maturity, and regional conditions.

These indicators are not intended as rigid benchmarks but as adaptable guides that help organizations reflect on their progress and potential within the ISOS architecture. They also offer a starting point for future empirical studies that seek to evaluate ISOS implementation in different institutional or geographic contexts.

5.6. Policy and Stakeholder Roles in ISOS

Sustainable operational transformation is not solely an internal organizational endeavor; it is deeply embedded in broader policy ecosystems and stakeholder networks. The successful implementation of the ISOS model depends on enabling policy frameworks and active engagement with key external actors such as regulators, industry associations, civil society, and local communities.

First, policy alignment is critical. Governments can accelerate ISOS adoption by offering incentives for circular practices, investing in digital infrastructure, and developing localization-supportive regulations such as green procurement mandates, carbon accounting standards, and regional innovation hubs. Without coherent and forward-looking policy scaffolding, ISOS strategies may remain aspirational.

Second, stakeholder collaboration fosters legitimacy and adaptive fit. Engaging local communities enhances trust and contextual responsiveness; partnering with supply chain actors improves traceability and shared accountability; and involving NGOs or sustainability coalitions can amplify monitoring and transparency. This multi-actor approach ensures that ISOS initiatives are not only operationally sound but also socially accepted and resilient.

In short, ISOS implementation requires a co-evolutionary process—where firms, policymakers, and stakeholders co-design solutions that are feasible, equitable, and future-proof. This systemic engagement ensures that the transition toward sustainable operations becomes a shared journey, not a siloed pursuit.

6. Future Research Agenda

6.1. Propositions for Empoirical Validation

Although the present article develops a conceptual model through theoretical synthesis, its practical utility and theoretical robustness will benefit significantly from empirical validation. Future research can operationalize the constructs proposed in the ISOS model using quantitative or mixed-method approaches to examine the mediating mechanisms, moderating conditions, and causal pathways across contexts.

To support this endeavor, we outline a set of clear, theory-driven propositions that are suitable for empirical testing across diverse sectors and geographies. These propositions are grounded in the interdependencies mapped in our conceptual framework and reflect current priorities in sustainable operations, as emphasized by both academic and policy communities [180].

Table 9. Propositions and Suggested Empirical Approaches.

Proposition	Underlying Logic	Suggested Empirical Design
P1. The integration of circularity practices positively affects sustainable operational performance, mediated by reverse logistics capabilities.	Closed-loop design requires enabling logistics structures to realize sustainability outcomes.	Structural Equation Modeling (SEM); mediation analysis.
P2. The effectiveness of localization strategies in enhancing resilience is moderated by the level of institutional coordination at the regional level.	Policy coherence and regional governance influence localization’s impact.	Multi-group regression analysis; hierarchical linear modeling.
P3. The relationship between digital adaptation and sustainability performance is mediated by real-time data utilization.	The impact of IoT and AI on operations depends on effective data decisioning.	Mediation test using PROCESS macro or PLS-SEM.
P4. Workforce flexibility strengthens the relationship between circularity and operational adaptability.	Human agility enhances the responsiveness of circular systems to disruption.	Moderation analysis; interaction terms in regression.
P5. Simultaneous pursuit of circularity, localization, and digitalization leads to superior sustainability outcomes, moderated by organizational integration capacity.	Synergistic strategies require internal capability to manage trade-offs.	Moderated mediation or configurational analysis (e.g., fsQCA).

below outlines these propositions and the suggested empirical strategies for each, facilitating future work that bridges the gap between theory and practice.

These propositions serve as entry points for future empirical studies, offering a structured and scalable research agenda for scholars in sustainability, operations management, and systems thinking. They also ensure that the conceptual advancement offered in this paper does not remain abstract, but instead catalyzes evidence-based exploration and continuous refinement of the ISOS framework.

6.2. Methodological Paths: Case-Based Modelling, Simulation, System Dynamics

Beyond statistical validation of propositions, the complex interdependencies embedded in the Integrated Sustainable Operational Strategy (ISOS) model invite methodological pluralism—especially methods capable of capturing dynamic, multi-scalar, and nonlinear patterns. To deepen and operationalize this conceptual contribution, we propose three complementary methodological directions:

(1)

Case-Based Modelling for Contextualization

Proposition:

P6. Contextual configurations—including the policy environment, supply chain maturity, and cultural alignment—significantly influence the operationalization of the ISOS framework across different sectors.

The rationale for this proposition rests on the understanding that sustainable strategies are deeply embedded in institutional and cultural contexts. Attempts to universalize a one-size-fits-all operational model risk overlooking critical contingencies that shape the feasibility and effectiveness of sustainability transitions. For example, regulatory incentives in the energy sector may differ substantially from those in agri-food or consumer manufacturing, affecting how circularity or localization strategies can be deployed.

To explore this complexity, in-depth comparative case studies across sectors—such as manufacturing, agri-food, and energy—are recommended. Analytical approaches like fuzzy set Qualitative Comparative Analysis (fsQCA) are particularly suited to this inquiry, as they can uncover multiple equifinal pathways—distinct configurations that lead to similar sustainability outcomes.

The expected contribution of this proposition is the development of typologies of implementation strategies, categorized by organizational archetypes and regional settings. Such typologies would offer valuable guidance for both scholars and practitioners seeking to adapt the ISOS framework to diverse institutional landscapes.

(2)

Simulation-Based Design for Scenario Testing

Proposition:

P7. The interaction between digital adaptation and localization strategies can produce nonlinear outcomes under different disruption scenarios, such as supply shocks or climate-related events.

The rationale behind this proposition stems from the recognition that traditional linear models are insufficient to capture the complexity of sustainability transitions. These transitions often involve feedback loops, time delays, and emergent dynamics that require systems-oriented perspectives. Specifically, when digital systems interact with localized operations—such as real-time monitoring informing decentralized decision-making—the outcomes may exhibit threshold effects, tipping points, or bottlenecks not evident in static models.

To examine this interaction, scholars should employ agent-based modeling (ABM) or discrete event simulation (DES)methodologies. These tools enable the testing of the ISOS framework under diverse, hypothetical disruption scenarios—including new climate regulations, raw material shortages, or sudden demand surges. Such simulations help illuminate how digital-local synergies unfold in dynamic environments, offering insights that are not observable through conventional empirical methods.

The expected output from this line of inquiry includes the identification of leverage points, critical thresholds, and systemic bottlenecks under varying operational configurations. These findings can inform both theory refinement and managerial decision-making, particularly in volatile, uncertain, complex, and ambiguous (VUCA) contexts.

(3)

System Dynamics for Macro–Meso Integration

Proposition:

P8. Long-term sustainability performance depends on the feedback effects between macro-level policy incentives, meso-level operational redesign, and micro-level process innovation.

This proposition is grounded in the ISOS model’s view of sustainability not as a fixed outcome or KPI, but as a systemic property that evolves over time. Unlike traditional models that treat sustainability as a discrete goal to be reached, ISOS conceptualizes it as an emergent result of interactions across levels—policy shaping strategy, strategy informing operations, and operations generating iterative learning that feeds back into governance.

To investigate this dynamic, system dynamics modeling offers a robust methodological approach. It allows researchers to simulate time delays, resource feedback loops, and behavioral responses across institutional and organizational layers. This approach captures how policies designed at the macro level—such as subsidies, carbon pricing, or reporting mandates—may interact with meso-level design choices (e.g., localization, circular flows) and micro-level practices (e.g., adaptive scheduling, real-time monitoring) over extended periods.

The expected output includes the generation of dynamic system maps that visualize policy-operational alignment, while also revealing potential unintended consequences from siloed interventions or poorly timed incentives. These insights are crucial for designing more coherent, cross-level strategies in both policymaking and organizational practice.

By integrating these methodological paths, researchers can avoid the limitations of cross-sectional designs and engage with real-world complexity. More importantly, these approaches ensure that the theoretical synthesis presented in this paper translates into actionable, adaptive insights for practitioners, policymakers, and sustainability scholars—particularly in line with recent calls for evidence-based and system-aware frameworks to navigate the co-benefits and trade-offs of natural climate solutions at multiple scales [181].

6.3. Multi-Stakeholder and Cross-Sector Testing

The operationalization of the ISOS framework demands validation not only across industrial and geographical contexts, but also through the lens of diverse stakeholder ecosystems. Sustainability in operations is not confined to the firm boundary; it is co-produced by suppliers, governments, regulators, civil society, customers, and local communities. This aligns with the emerging nature-positive business paradigm, which emphasizes regenerative value creation, multi-actor co-implementation, and systemic outcomes—moving beyond compliance-driven ESG toward shared planetary and human well-being [182,183].

1.

Proposition P9.

P9. The effectiveness of integrated sustainable operational strategies varies significantly across sectors, influenced by differences in regulatory pressure, resource dependency, and stakeholder salience.

This proposition is justified by the observation that sectors such as food processing, automotive manufacturing, and renewable energy differ widely in their carbon intensity, supply chain complexity, and level of public and regulatory scrutiny. These contextual features not only shape the strategic intent of sustainability initiatives but also directly affect their feasibility, pace of implementation, and institutional support. For example, decarbonization in automotive sectors may be driven by stringent emissions regulations, while sustainability in food processing may hinge on water usage and perishability logistics.

To evaluate these variations, sector-stratified comparative studies are needed. These can be conducted through structured surveys or stakeholder interviews, targeting how the core ISOS dimensions—circularity, localization, digitalization, and flexibility—are adopted and operationalized within specific industry settings. Such studies allow for grounded insights into how theory translates into practice under sector-specific constraints.

The goal of this proposition is to identify sector-specific leverage points that enhance strategic impact, while also uncovering common failure modes that hinder scalability. These findings would improve the generalizability and adaptive utility of the ISOS framework across diverse operational landscapes.

2.

Proposition P10.

P10. Stakeholder alignment—among firms, governments, civil society, and end-users—mediates the translation of sustainable operational design into measurable outcomes.

This proposition is grounded in the recognition that sustainability, by its very nature, is systemic and cross-sectoral, requiring more than just firm-level initiative. While operational models such as ISOS can offer internal coherence, their effectiveness in practice is often mediated by the degree of alignment or friction among external stakeholders. Misalignment between organizational goals and stakeholder expectations—whether due to conflicting priorities, regulatory gaps, or cultural divergence—can lead to resistance, delays, or superficial compliance.

To investigate these dynamics, researchers are encouraged to employ multi-stakeholder workshops, participatory modeling, or co-design action research approaches. These methods enable the mapping of actor perspectives, power asymmetries, and zones of consensus or contestation regarding specific ISOS components, such as circular redesign, digital traceability, or localized procurement.

The goal of this proposition is to identify stakeholder friction points and synergy zones, thereby informing the development of more inclusive and adaptive implementation strategies. In doing so, it acknowledges that successful sustainability transitions depend not only on operational logic, but also on the social architecture of collaboration and legitimacy that surrounds it.

3.

Proposition P11.

P11. Geographical localization of sustainable operational strategies yields better outcomes when aligned with local governance capacity, cultural norms, and resource endowments.

This proposition underscores that localization in sustainability transitions is not merely a matter of spatial distribution, but is deeply relational and institutional. The effectiveness of localized strategies—such as regional sourcing, place-based innovation, or decentralized energy use—depends heavily on local capabilities, governance structures, and cultural legitimacy. Without alignment to these contextual elements, sustainability strategies risk poor uptake, tokenistic implementation, or even outright failure.

The ISOS model acknowledges that sustainability must be embedded, not imposed, and thus calls for empirical approaches that reflect geo-contextual nuance. One such approach involves the study of regional case clusters, such as industrial parks, eco-industrial zones, or municipal sustainability initiatives. By comparing the performance trajectoriesof ISOS-aligned firms or networks across different local contexts, researchers can identify patterns of success and failure.

The ultimate goal is to produce a geo-contextualized implementation map, which links specific local enablers—such as governance quality, cultural openness to innovation, or natural resource availability—with operational outcomes. This would support both place-sensitive strategy formulation and scalable policy frameworks that respect local complexity while striving for systemic impact.

Together, these propositions offer empirical roadmaps to evaluate the transferability, inclusivity, and contextual integrity of the ISOS framework. This stakeholder-oriented approach is particularly critical in overcoming organizational resistance to change, fostering mutual accountability, and ensuring that integrated sustainability strategies are not only designed top down, but also co-implemented and continuously adapted with bottom-up input. For the sustainability field, this shift toward cross-sectoral and multi-actor integration provides not only practical validation but also opens avenues for theoretical refinement grounded in systemic interdependencies.

The simulation also assumes an internal governance structure; future deployment of ISOS should include stakeholder mapping, particularly for external actors such as regional suppliers, local governments, and civil society groups, to ensure ethical alignment and contextual relevance during operational transition.

6.4. Suggested Empirical Designs

To move beyond conceptual robustness and advance the ISOS framework toward actionable scholarship, several empirical research pathways are proposed. These designs aim to investigate how circularity, localization, and digital adaptation interact across varied industrial settings, while also exploring how organizations manage operational trade-offs under conditions of complexity and uncertainty.

From the propositions outlined earlier, three key research questions emerge that can serve as entry points for empirical inquiry. The first question asks: How do firms operationalize trade-offs between circularity and localization in high-velocity sectors such as fast fashion or consumer electronics? This question addresses the practical tensions between regional adaptability and material loop closure in time-sensitive, consumer-driven industries.

The second question explores: To what extent does the integration of digital traceability technologies—such as blockchain or Internet of Things (IoT) systems—enhance adaptive sustainability performance? This line of inquiry tests the role of real-time data in improving responsiveness, transparency, and closed-loop accountability within operational systems.

The third question probes: What types of governance configurations—centralized versus decentralized—most effectively moderate the tensions between operational efficiency and ethical oversight in ISOS-based operations? Here, the focus is on understanding how structural choices influence accountability, compliance, and value alignment across multiple actors and geographies.

Together, these research questions provide a foundation for mixed-methods investigations—including case studies, simulation modeling, and large-scale surveys—that can empirically validate and refine the ISOS model across contexts.

To address these questions,

Table 10. Suggested Research Pathways for ISOS Model Testing.

Research Question (RQ)	Recommended Methodology	Sectoral Focus	Outcome Variable
RQ1	Multiple Case Study	Textile/Electronics	Trade-off Resolution Strategies
RQ2	Longitudinal Study	Agritech	Adaptive Sustainability Index
RQ3	Quasi-Experimental Design	Automotive	Governance–Performance Alignment

summarizes suitable methodological approaches, sectoral contexts, and potential outcome variables.

These methods offer empirical traction for ISOS by enabling comparisons across governance modes, sector-specific dynamics, and organizational learning trajectories. For example, a longitudinal study in agritech could examine how IoT and AI-based analytics evolve to support both local sourcing and circular waste processing. Alternatively, a quasi-experimental design in the automotive sector could test the performance differential before and after modular circular integration using digital twins.

By applying such designs, scholars can bridge the normative vision of ISOS with the operational realities of firms navigating sustainability transitions—contributing both theoretical refinement and practical relevance to the literature on sustainable operations.

7. Conclusions

7.1. Summary of Contributions

This article presents an integrative and future-oriented conceptual framework—Integrated Sustainable Operational Strategy (ISOS)—that redefines the operational function through the lenses of resilience, circularity, localization, and digital adaptation. By bridging insights from sustainability science, systems theory, and operations management, the paper contributes a synthesized model that addresses longstanding fragmentation in operational sustainability discourse.

Our model makes three distinct contributions. First, it reframes operational excellence not merely as efficiency maximization but as multi-capital value creation, encompassing environmental regeneration, social cohesion, and adaptive capacity. Second, it theorizes the multi-level configuration of sustainable strategies across macro (policy), meso (organizational), and micro (process) levels. Third, it provides a scalable and transferable structure to guide both empirical investigation and practical design in diverse contexts.

7.2. Strategic Relevance and Future Orientation

The urgency of climate change (SDG 13), the need for responsible consumption and production (SDG 12), and the call for innovation in infrastructure and industry (SDG 9) form the global mandate that this framework seeks to answer. Unlike fragmented approaches, ISOS offers a strategic convergence zone where firms, policymakers, and stakeholders can co-align their efforts. It recognizes that sustainability is not a fixed target but a dynamic, negotiated, and context-dependent pursuit.

Looking forward, the model invites future empirical studies, particularly those that examine causal mechanisms, implementation trade-offs, and sectoral adaptations. It also opens the door for policy innovation, such as new metrics, regulatory designs, and incentive schemes that recognize multi-dimensional operational performance.

7.3. Final Reflection: Operational Innovation for Sustainability Transitions

In the face of complex global disruptions, operations must evolve beyond the paradigms of stability, standardization, and cost efficiency. The proposed ISOS framework encourages a paradigm shift where operational innovation becomes central to sustainability transitions—not merely reactive to crises, but proactively shaping regenerative futures.

This work does not claim to offer a universal solution. Rather, it aspires to catalyze critical reflection and strategic experimentation within the field. Sustainability is a shared responsibility, and operations—when intelligently reimagined—can be one of its most powerful drivers.