Extended Abstract (At least 700 words)
Introduction
Circular economy (CE) business models have emerged as a transformative paradigm in response to the limitations of traditional linear production–consumption systems. They aim to decouple economic growth from resource depletion by maintaining material value through reuse, recycling, and regeneration. Among various CE business models, those based on circular inputs—which rely on renewable, recyclable, or biodegradable materials—play a crucial role in minimizing waste and pollution across the value chain.
Despite the growing theoretical interest in CE models, their sustainability performance and influencing factors remain underexplored in developing economies, particularly in Iran’s packaging industry. This industry represents a high-impact sector due to its dependence on non-recyclable materials and its contribution to environmental degradation. Many Iranian packaging firms still follow linear production models and lack awareness of CE and sustainability principles. Therefore, identifying the key factors that enhance the sustainability of circular input-based business models is essential for enabling the transition toward a greener and more resilient industrial structure.
The present study aims to develop and empirically test a structural model of sustainability for circular input-based business models within Iran’s packaging sector. It examines how institutional, market, technological, and environmental factors affect sustainability outcomes measured across three dimensions—sustainable value proposition, value creation and delivery, and value capture. By applying a structural equation modeling (SEM-PLS) approach, the study provides quantitative evidence that bridges the gap between CE theory and industrial practice in emerging markets.
Methodology
The research adopts a descriptive-correlational design with an applied purpose, integrating theoretical modeling and quantitative analysis. The target population comprises Iranian packaging companies that implement or align with circular input-based business models. Because the total number of such firms is not precisely known, non-probability convenience sampling was applied. A total of 60 valid responses were collected, which satisfies the recommended sample size for PLS-SEM analysis given the study’s model complexity and desired statistical power (Hair et al., 2014).
Data were gathered using a researcher-designed Likert-scale questionnaire (five-point scale). The questionnaire’s content validity was confirmed by five academic experts specializing in CE and sustainable management. Reliability was assessed through Cronbach’s alpha and composite reliability (CR) indices, while average variance extracted (AVE) was used to test convergent validity. The Shapiro–Wilk and Kolmogorov–Smirnov tests indicated non-normal data distribution; thus, SmartPLS 4 software was employed to conduct Partial Least Squares Structural Equation Modeling (PLS-SEM), which is robust under non-normality and small-sample conditions.
The conceptual model included four exogenous constructs (Institutional, Market, Technological, and Environmental factors) and one endogenous construct (Sustainability of circular input-based business model), which in turn was operationalized through three reflective sub-dimensions: Sustainable Value Proposition (SPV), Sustainable Value Creation and Delivery (SVCR), and Sustainable Value Capture (SVCA).
Results and Discussion
The reliability and validity tests confirmed that all measurement constructs achieved acceptable thresholds (CR > 0.7; AVE > 0.5). Discriminant validity was verified using both cross-loadings and the Fornell–Larcker criterion. The structural model exhibited satisfactory explanatory power with R² = 0.515 for overall sustainability, R² = 0.823 for sustainable value proposition, and R² = 0.763 for sustainable value creation and delivery—indicating strong predictive accuracy.
Path coefficients revealed that Environmental (β = 0.362, t = 3.199), Market (β = 0.347, t = 3.814), and Technological (β = 0.312, t = 2.675) factors exerted positive and significant effects on sustainability. Conversely, the Institutional factor (β = 0.012, t = 0.106) was statistically insignificant, suggesting that governmental and regulatory frameworks currently play a weak role in promoting CE adoption in Iran’s packaging industry.
Among sustainability sub-dimensions, the hierarchical importance analysis indicated that Sustainable Value Proposition contributes most strongly to overall sustainability, followed by Value Creation and Delivery, and then Value Capture. This hierarchy implies that Iranian firms prioritize eco-friendly product offerings and responsible production practices before focusing on monetization or financial returns.
These findings differ from Irgens (2021), who found institutional and market factors to be the dominant barriers in Norway’s manufacturing context. The discrepancy can be attributed to differences in industrial environments and methodological rigor: Irgens relied on descriptive statistics, whereas this research employed SEM to examine causal paths. Moreover, interviews with Iranian managers revealed that weak enforcement of environmental regulations and limited export activity reduce the influence of institutional mechanisms. In contrast, customer awareness and environmental performance emerged as stronger drivers of sustainable behavior.
The environmental factor proved to be the most influential, highlighting that firms integrating environmental performance metrics—such as emissions reduction, resource efficiency, and eco-innovation—achieve higher sustainability scores. The market factor ranked second, showing that consumer demand for green products and brand reputation for sustainability motivate companies to redesign their models around circular inputs. The technological factor ranked third, emphasizing the importance of adopting clean technologies, renewable energy systems (e.g., solar panels), and R&D investments that support sustainable production.
Effect-size (f²) and predictive-relevance (Q²) analyses confirmed the model’s robustness: environmental, market, and technological variables exhibited medium-to-strong effects (f² = 0.25–0.35), and Q² values exceeded 0.3 for key endogenous constructs, indicating strong predictive relevance. Overall, the model demonstrated a good level of internal consistency, explanatory strength, and predictive capability.
Conclusion
The study provides empirical evidence that environmental, market, and technological drivers significantly enhance the sustainability of circular input-based business models in Iran’s packaging industry, while institutional support remains weak. To strengthen sustainability outcomes, environmental considerations should be prioritized within corporate strategies and national policies.
From a managerial perspective, firms are advised to:
1. Integrate environmental performance measurement (e.g., carbon footprint, material efficiency) into their business model evaluation.
2. Leverage market demand for sustainable packaging by enhancing transparency and communicating environmental benefits to consumers.
3. Invest in green technologies that enable resource efficiency and waste minimization.
4. Develop internal cultures that embed sustainability across value creation, delivery, and capture processes.
From a policy standpoint, regulators should:
• Establish environmental performance indicators and certification systems specific to the packaging industry;
• Introduce incentives and subsidies for companies adopting renewable materials and circular technologies;
• Strengthen collaboration among government, industry, and civil society to create an ecosystem conducive to CE innovation.