Exploratory Survey—The Role of Traceability Systems in Quality Assurance and Advancement of the Circular Economy for Recycled Plastics in Australia

Abstract

Plastic recycling is critical to transitioning toward a circular economy (CE), yet traceability systems for recycled plastics remain unevenly adopted. While effective traceability supports transparency, compliance, and supply chain accountability, its implementation is shaped not only by technological readiness but also by organisational behaviours and strategic priorities. This study explores how traceability adoption is influenced by company size, internal CE strategy, and perceptions of cost, risk, and regulatory demand. A survey of 65 Australian industry stakeholders reveals that 76% of companies with a CE strategy have implemented traceability systems, compared to 42% without. Larger firms report higher adoption rates than small and medium enterprises, largely due to resource advantages and differing interpretations of traceability’s value. Key barriers include high perceived costs, lack of standardised frameworks, and scepticism toward digital tools. Conversely, motivations such as reputational benefits, regulatory alignment, and inter-organisational trust were identified as enablers, alongside emerging technologies like blockchain and chemical tracers. The findings underscore the role of organisational context in shaping traceability practices and highlight the need for tailored interventions. Recommendations include financial incentives, harmonised standards, and sector-specific guidance that address not only technical gaps but behavioural and structural factors limiting uptake. Positioning traceability as an integrated organisational strategy may accelerate its adoption and support broader circular economy outcomes across the plastics value chain.

1. Introduction

The world generated over 489 million tonnes of plastic in 2023, yet only 8.17% of that waste was recycled, while 17.17% was mismanaged, contributing significantly to environmental degradation, human health risks, and climate impacts [1,2,3,4]. As concerns about sustainability intensify, industries are turning to circular economy (CE) principles, which aim to maximise material recovery and reuse while minimising waste throughout the lifecycle [5,6,7]. In this transition, traceability plays a crucial role. It refers to the ability to track the movement, origin, and handling of recycled plastics across the supply chain, providing transparency and supporting CE objectives. By enabling better oversight of material flows, traceability helps reduce contamination, supports compliance with policies such as Extended Producer Responsibility (EPR), and builds trust among stakeholders and consumers [8,9,10]. Geng and Sarkis [11] advocate for a global approach supported by cross-sectoral collaboration and innovative policy to improve recycling and resource efficiency, where traceability is a critical enabler. In this study, traceability refers to the ability to track and verify the origin, composition, and transformation of recycled plastic materials across the value chain: from initial waste recovery, through processing and conversion, to reintegration into new products. While traceability often begins with the recovery of post-consumer or post-industrial plastics, its endpoint can vary. In some systems, traceability terminates once the material is converted into a new product; in others, particularly those enabled by digital or chemical tracking systems, it can extend across multiple life cycles, documenting materials as they are reprocessed or remanufactured again. However, most current systems in practice capture only first-loop traceability due to infrastructure and data limitations. This paper focuses on the traceability necessary to validate recycled content claims and quality assurance at the first integration stage while acknowledging the potential for expanded multi-loop systems in future policy or technology development.

In Australia, efforts to shift towards more sustainable production and consumption patterns have been hindered by a low plastic recovery rate of 14.03%, with the majority of the recovered fraction being recycled and the remainder directed to energy recovery [12,13]. Improving traceability is seen as essential for addressing the system’s inefficiencies. Hossain, Islam [14] and Sohal and De Vass [15] stress the importance of involving various stakeholders and fostering collaboration across levels of governance to reform recycling systems. These collaborative efforts rely on transparent information sharing, which traceability systems can facilitate.

Emerging technologies like blockchain are proposed to improve traceability in plastic recycling by enhancing data accuracy, transparency, and stakeholder coordination [16]. These tools can enhance trust, minimise reporting discrepancies, and improve the reliability of the recycled plastic supply chain. For example, traceability audits can identify mismatches between reported recycling data and actual practices [17], reinforcing the need for robust tracking systems. Survey-based findings also highlight that traceability influences perceptions around recycled plastics. Clear labelling and supply chain visibility can enhance consumer and producer confidence while supporting informed decision-making [8]. Still, despite the growing recognition of its value, traceability remains underutilised due to technological costs, fragmented policies, and a lack of universal standards. Current literature acknowledges the importance of traceability in enabling circularity, but most studies remain conceptual, with limited empirical evidence on how traceability systems are implemented [9,10]. Furthermore, although some regions like the European Union (EU) are advancing traceability through mechanisms such as the Digital Product Passport, comparable approaches for plastic materials are not yet widespread [18].

This study investigates the role of traceability in advancing circularity within Australia’s plastic recycling sector. It addresses existing gaps by analysing how traceability systems are adopted, the challenges and drivers influencing their implementation, and the methods available for tracking and verifying recycled materials, such as blockchain technology and chemical markers. While traceability is often framed as a technical or regulatory instrument, its implementation within businesses is shaped by organisational context. Decisions to adopt traceability systems reflect behavioural factors such as perceived cost, internal capacity, strategic alignment with circular economy principles, and stakeholder pressures. Small and medium enterprises (SMEs), in particular, face unique challenges in balancing regulatory compliance, profitability, and investment in digital tools. Understanding how company size and CE strategy influence traceability practices offers valuable insight into the behavioural dimensions of sustainability transitions. A key objective is to develop a structured framework and policy recommendations to support industry and government in embedding traceability as a core component of circular economy strategies. The research examines the relationship between traceability and quality of recycled plastics, with a focus on their contribution to more sustainable resource management. Central to the analysis is the fact that traceability enhances plastic supply chain circular practices. Four areas are examined in this paper:

• The importance of traceability in enabling circular economy outcomes,
• The barriers and enablers that shape its adoption,
• The techniques used to monitor and integrate traceability across value chains,
• The development of a practical protocol to guide and improve traceability efforts across the sector.

This study makes three contributions to the literature on circular economy and traceability. First, it is the first empirical investigation of how industry stakeholders in Australia perceive and adopt traceability systems in the recycled plastics sector, providing evidence from a national survey. Second, it links organisational perceptions of barriers and enablers to broader circular economy adoption pathways, thereby integrating behavioural and policy dimensions that are often treated separately in the literature. Third, it develops a structured framework for understanding traceability through four interrelated clusters: importance, technological approaches, barriers and enablers, and governance frameworks, which can guide both academic research and policy development. While rooted in the Australian context, the framework and findings are designed to be transferable to other national settings particularly those with comparable regulatory, market, or infrastructure challenges. Together, these contributions provide a novel perspective on the underexplored role of traceability in operationalising circular plastics economies and offer a replicable model that may inform traceability policy and system design in other countries.

2. Literature Review

The academic literature on circular economy and plastic recycling increasingly emphasises the need for integrated approaches that combine technological, organisational, and policy innovations. Within this body of research, four interrelated clusters emerge that frame the role of traceability in advancing CE practices. The first cluster highlights the importance of traceability as a critical enabler for circular systems, ensuring that material flows are visible, verifiable, and aligned with quality and sustainability objectives. The second cluster examines technological approaches, including both digital tools such as blockchain and mobile applications, and physical methods such as tagging, sorting, and analytical systems, which together enable more precise monitoring of recycled plastics. A third cluster identifies the barriers and enablers that shape adoption, ranging from cost and infrastructure limitations to the influence of consumer demand, certification programmes, and industry collaboration. Finally, the fourth cluster brings attention to policy and governance frameworks, recognising that regulatory structures, standards, and producer responsibility schemes create the institutional conditions that either foster or constrain traceability adoption. Together, these clusters provide a structured lens for analysing how traceability systems contribute to the development of a more circular plastics economy. They illustrate that effective CE implementation depends not only on technological advances but also on the alignment of industrial practices, market incentives, and governance mechanisms. The following sections elaborate on each cluster in detail, integrating empirical findings and conceptual insights from the literature.

2.1. Importance of Traceability in CE

Traceability has emerged as a cornerstone of circular economy practices, providing a structured foundation for accountability, transparency, and quality assurance across the plastics value chain. Policies that hold producers responsible for the entire lifecycle of their products, including end-of-life recycling, are central to this vision. However, traceability is increasingly recognised as a critical enabling mechanism for effective Extended Producer Responsibility (EPR) implementation, supporting functions such as compliance verification, recycled content tracking, and system transparency. In this way, traceability is not an obligation per se but rather a necessary complement to managing circular responsibilities across the supply chain. EPR schemes, for instance, create obligations that not only strengthen recycling outcomes but also incentivise firms to implement traceability measures that track products from production to recovery [19]. Alongside such policy measures, technical systems designed to recycle materials back into the same product type highlight the necessity of robust traceability frameworks to safeguard compliance and quality standards [20].

Digital innovation has also played a significant role in establishing the importance of traceability in CE. Online platforms that connect diverse stakeholders, including manufacturers, recyclers, and consumers, demonstrate how digital ecosystems can facilitate information sharing and visibility across supply chains [21]. At the consumer level, initiatives that promote awareness and education about proper recycling practices show how traceability benefits are amplified when public engagement translates into improved recycling rates [22]. On the industry side, data-sharing agreements between companies have been recognised as critical instruments for enhancing transparency and building collaborative traceability systems [23].

Beyond these discrete mechanisms, the literature increasingly frames traceability as a structured approach that enhances visibility and accountability throughout the lifecycle of recycled plastics. Conceptual and empirical studies converge on the understanding that traceability is not only a technical feature but also a strategic management tool that helps organisations align sustainability initiatives with resource optimisation goals [20,24,25,26,27,28,29,30,31,32,33,34,35].

Several frameworks emphasise how traceability supports CE principles by structuring collaboration and coordination among stakeholders. For example, proposed frameworks identify key components that enable traceability to function as an integrative mechanism across the supply chain [26]. Others underline the importance of joint stakeholder action and coordinated strategies to strengthen traceability implementation [26]. The literature also highlights the role of traceability across different stages of the lifecycle of assets, reinforcing its systemic character [26]. Moreover, the position or function of a company within the supply chain has been shown to influence both the design and adoption of traceability systems, underscoring the structural dynamics that shape its effectiveness [25].

2.2. Technology Approaches

Technological innovation forms a critical foundation for enabling traceability in circular economy systems, offering both digital and physical solutions to monitor, track, and optimise the flow of plastics across their lifecycle. A central development has been the application of blockchain as a decentralised ledger that records transactions immutably, thereby creating secure and transparent tracking systems for plastics from production through recycling [36]. This disruptive capability has been extended into decentralised systems that reinforce accountability, transparency, and trust within recycling networks, illustrating blockchain’s role as a transformative technology for CE adoption [20,24,35,37,38,39,40,41].

Complementing blockchain are digital product passports (DPPs), which act as lifecycle data tools that consolidate and share information on material composition, recyclability, and environmental impacts. These passports have been studied across different industries as mechanisms to improve transparency, recycling performance, and circularity by linking product data with end-of-life management [27,28,31,34,39,40,42].

Technological advancements are not limited to digital tools but also extend into physical systems that improve recycling efficiency. Smart bins equipped with sensors, for instance, classify disposed materials and generate data that can enhance collection systems and track flows in urban environments [43]. Similarly, spectroscopic technologies such as near-infrared (NIR) enable accurate sorting by identifying polymer types in mixed waste streams, thereby improving the quality and reliability of recycled plastics [44]. However, it is important to note that conventional NIR systems cannot reliably detect black plastics, as the carbon black pigments used in many such products absorb infrared light and render spectral differentiation ineffective. In addition, chemical tracers and embedded markers have been explored as techniques for distinguishing polymer compositions and facilitating more efficient separation during recycling [45,46,47].

Analytical tools further complement these approaches by enabling system-wide evaluations of environmental performance. Life Cycle Assessment (LCA) has become particularly important for quantifying the benefits of recycled content and linking traceability data to broader sustainability outcomes [48]. Likewise, mobile applications designed for consumer engagement serve to extend traceability to the household level by raising awareness, supporting responsible disposal practices, and providing information on recycling options [49,50].

Technological approaches combine disruptive innovations such as blockchain with practical tools like smart bins, NIR spectroscopy, LCA, and mobile apps. However, a critical limitation of NIR is its inability to detect black plastics, due to the use of carbon black pigments that absorb infrared light and prevent spectral differentiation. Therefore, NIR alone is insufficient for comprehensive traceability. To address this technological gap, traceability systems should incorporate complementary methods such as digital watermarking, fluorescent tracers, or AI-assisted hyperspectral imaging to accurately identify and track a broader range of plastic materials, including black and multilayer composites. Recent studies also explore the use of AI and machine learning (ML) in plastic waste management, particularly for improving sorting accuracy and detecting contamination in real time [51,52,53,54,55]. While AI/ML are not integrated into this study’s analytical framework, they represent a promising direction for future research, offering opportunities to automate traceability verification, optimise data-driven material classification, and enhance system responsiveness in circular plastics systems. Together they not only create transparent and efficient recycling ecosystems but also act as enablers for overcoming barriers along the plastics value chain, reinforcing the role of traceability as both a technical and systemic driver of circular economy practices [30,40,56].

2.3. Barriers and Enablers

A combination of enabling mechanisms and persistent barriers shapes the integration of traceability systems in circular economy practices. Standards and guidelines are central to this process, as they provide the necessary protocols to ensure that recycled plastics meet industry requirements, thereby maintaining consumer trust and encouraging the uptake of recycled materials in new products [30]. In parallel, organisations that promote best practices and industry standards play a vital role in offering resources and sector-wide support for the adoption of traceability systems [30].

Despite these enabling factors, technological pathways such as tracer-based sorting (TBS) illustrate both opportunities and challenges. Business strategies tailored to TBS highlight the potential of such methods in CE applications [57], but conditions affecting their implementation, including cost, market readiness, and technological constraints, hinder wider uptake. While TBS offers a structured approach to enhancing material quality and ensuring standards [30], it faces barriers such as slow market implementation [40] and the need for continuous advice and improvement strategies [57].

Digital technologies also occupy an ambivalent role as both enablers and sources of difficulty. Blockchain integration has been identified as a transformative process that enhances transparency and operational efficiency in CE systems [29]. Innovative blockchain-enabled business approaches are seen as promising solutions for overcoming adoption challenges [56], but they remain uneven in implementation across sectors. Similarly, regulatory guidelines designed to help companies comply with local and international recycling frameworks provide a governance foundation for traceability adoption [30,58]. However, these frameworks may not fully address the disparities in organisational capacity, scale, and readiness, which demand more tailored policy approaches [25].

The broader landscape of barriers is characterised by systemic challenges such as supply chain complexity, stakeholder resistance, technological limitations, and the absence of harmonised practices [31]. These factors collectively inhibit the diffusion of traceability innovations, even when robust quality assessment methods and structured guidelines are available [30]. Consequently, while enablers such as standards, blockchain integration, and organisational initiatives provide pathways for progress, persistent technical, organisational, and systemic barriers continue to constrain the realisation of fully traceable and circular plastics systems.

2.4. Policy and Governance Frameworks

Policy and governance frameworks provide the institutional backbone for advancing traceability within circular economy systems, shaping how recycled plastics are monitored, standardised, and integrated into markets. One approach has been the creation of online platforms that act as digital marketplaces, connecting buyers and sellers of recycled materials. By facilitating information exchange and material transactions, these platforms can enhance transparency and streamline flows across the recycling value chain [59]. Similarly, systematic assessments of material flows, particularly through Material Flow Analysis (MFA), have been shown to provide actionable insights into recycling opportunities and waste reduction strategies, thereby strengthening traceability mechanisms [60].

Corporate governance frameworks have also become increasingly important, with sustainability reporting standards encouraging companies to disclose their use of recycled materials and environmental impacts. These reporting mechanisms enhance accountability and create transparency within supply chains [61]. At the consumer-facing level, eco-labelling initiatives that display the percentage of recycled content in products are identified as effective tools for guiding consumer preferences, encouraging sustainable purchasing, and indirectly reinforcing traceability [62].

Beyond reporting and labelling, proposed frameworks have been developed that aim to embed traceability and circularity more deeply into sectoral practices. In agriculture, for example, a twelve-principles framework has been suggested to improve circularity and promote the integration of blockchain-enabled traceability across supply chains [35]. At a broader level, the collective enhancement of recycling standards across industries highlights the need for harmonised protocols in quality testing and traceability, helping to build trust and consistency in the use of recycled plastics [30].

Taken together, these governance mechanisms illustrate how policy instruments, sustainability reporting systems, labelling initiatives, and industry-wide standards can complement technological and market innovations. They provide the regulatory and institutional structures necessary to ensure that traceability not only supports circular economy goals but also gains legitimacy across businesses, regulators, and consumers.

3. Methods

This study adopts a mixed-methods survey approach to investigate the role of traceability in supporting circularity within plastic supply chains in Australia. By combining quantitative and qualitative data, the study aims to understand how traceability is currently adopted across the sector, identify the main barriers and enablers to its implementation, evaluate the effectiveness of various traceability methods, such as blockchain and chemical tracers, and propose a structured framework with policy guidance to improve traceability practices.

The survey was divided into two thematic sections. The first gathered background information about participants, including their role in the industry, company size, and involvement in circular economy strategies. The second section focuses explicitly on traceability practices, such as how suppliers and customers exchange data and the mechanisms used to trace recycled plastic through the value chain. Which include the perceived barriers and enablers influencing traceability adoption, participants’ plans and their willingness to invest in traceability. And allowed participants to express perceived benefits and share additional perspectives on traceability development.

The survey was developed based on a review of previous research on traceability in plastic waste systems [9,10] and aligned with international standards such as ISO 22095 [63], which guides chain of custody. It included a mix of multiple-choice, Likert-scale, and open-ended questions to capture structured data and in-depth responses. Before full distribution, the survey was pilot-tested with five industry experts, including recyclers, manufacturers, and a policy advisor, to refine the wording and improve clarity. The data collection took place between July 2023 and February 2024 using the Qualtrics online platform.

A purposive sampling strategy targeted stakeholders actively involved in the plastic recycling value chain. This included raw material suppliers, plastic compounders, converters, end-user manufacturers, waste management firms, and supporting organisations such as research and development (R&D) labs, testing services, machine suppliers, consultants, and universities. Invitations were distributed through professional networks and email outreach, with additional recruitment supported through word-of-mouth referrals. The final survey was distributed mainly through professional networks, industry associations, and word-of-mouth referrals. A total of 548 invitations were issued to stakeholders across Australia’s plastic production, waste management, and recycling sectors. Participation was restricted to companies operating within Australia with a minimum of one year of experience in the field. In total, 190 responses were received. After removing incomplete responses and submissions from outside Australia, which were not covered under the study’s ethics approval, a final sample of 65 valid responses was retained for analysis. Among these, stakeholder representation was distributed as follows: plastic converters made up 20.16% of the sample, end-user manufacturers 8.06%, compounders 8.87%, waste stakeholders 21.77%, raw material suppliers 10.48%, and support services 30.65%. Some respondents operated in overlapping roles across multiple segments of the supply chain.

Both qualitative and quantitative analysis provided a comprehensive view of industry perceptions. Qualitative responses offered more profound insight into stakeholder motivations and contextual factors influencing traceability efforts, while the quantitative data allowed for trend identification and generalisation across the broader population. This combination of methods enabled a more nuanced understanding of how traceability is currently used and what is needed to enhance its adoption.

The survey was designed to capture the viewpoints of industry participants, such as manufacturers, recyclers, and supply chain intermediaries responsible for operationalising traceability within the plastic value chain. However, other stakeholder groups including consumers, government agencies, or Non-governmental Organisations (NGOs) were not included in the current sample. Incorporating these actors in future studies would provide a broader and more systemic perspective on the drivers and enablers of traceability adoption. Prior research led by Stewart and Niero [64] has shown that most collaborative initiatives remain industry-centred, even though public actors and end-users play a vital part in accelerating circular transition. Similarly, Ruokamo, Räisänen [8] observed that consumers attitudes toward recycled plastic are generally positive, suggesting untapped potential for aligning consumer demand with traceability-based market incentives. To promote transparency and reproducibility, the complete survey questionnaire is provided in the Supplementary Materials File S1, and all steps involved in data processing and statistical analysis are clearly documented. The dataset supporting this study is available upon request, in accordance with ethical guidelines. Focusing on industry views regarding traceability, this research provides valuable insights into the challenges and opportunities of integrating traceability systems into circular economy practices within Australia’s plastic recycling sector.

Descriptive statistics, independent t-tests, and effect size analysis were employed to evaluate industry perceptions regarding traceability. Descriptive statistics provide an overview of how respondents answered key questions, helping identify data patterns. The independent t-test was applied to determine whether statistically significant differences exist between businesses that have adopted circular economy strategies and those that have not. To understand the practical relevance of these differences, Cohen’s d was used to calculate effect sizes. This approach facilitates a more nuanced interpretation of the results, providing guidance for policymakers and industry leaders [65]. These methods align with best practices in survey-based sustainability research, where statistical significance and effect size are key factors in shaping evidence-based recommendations. The mean and standard deviation were used to summarise stakeholder responses. The mean reflects the average score on survey items, while the standard deviation indicates the extent to which responses varied around that average [66]. A low standard deviation shows that participants largely agreed on a particular issue, whereas a higher value indicates more diverse opinions [67]. These measures help quantify stakeholder views and allow for comparisons across different groups within the industry.

The independent t-test was used to compare perceptions between CE-adopting and non-CE businesses. This test is appropriate for comparing the means of two groups and determining whether any differences are statistically significant [68]. It usually assumes distributed data and equal group variances [69]. The test statistic (t) and p-value were reported, with a significance threshold of 0.05. A p-value below this level indicates a meaningful difference between the two groups’ responses. H₀ (Null hypothesis) fixes no difference in traceability adoption or shared amongst stakeholders scores between companies, irrespective of CE implementation. The alternative hypothesis asserts that companies with a CE strategy have significantly higher traceability adoption scores.

Using an equation for the t-test and assuming the null hypothesis H₀: μ₁ = μ₂ (the population means are equal), the t-statistic simplifies to:

$$\mathrm{t}={\displaystyle \frac{\overline{{\mathrm{X}}_1}-\overline{{\mathrm{X}}_2}}{\sqrt{\frac{{\mathrm{s}}_1^2}{{\mathrm{n}}_1}+\frac{{\mathrm{s}}_2^2}{{\mathrm{n}}_2}}}}$$

(1)

where $\overline{\mathrm{X}}$ represents the group mean, s the standard deviation, and n the sample size.

$$\mathrm{d}\mathrm{f}={\mathrm{n}}_1+{\mathrm{n}}_2-2$$

(2)

Cohen’s d was calculated to further assess the importance of these differences. This effect size statistic estimates the magnitude of the difference between two means, helping to clarify whether the results are practically significant [70]. A value of 0.2 indicates a small effect, 0.5 is moderate, and 0.8 or above is significant [71]. Including effect size is significant in sustainability research, where the findings may be statistically significant but not necessarily impactful in practice [72].

Equation for Cohen d-effect:

$$\mathrm{d}={\displaystyle \frac{\overline{{\mathrm{X}}_1}-\overline{{\mathrm{X}}_2}}{\sqrt{\frac{({\mathrm{n}}_1 - 1){\mathrm{S}}_1^2 + {({\mathrm{n}}_2 - 1)\mathrm{S}}_2^2}{({\mathrm{n}}_1 + {\mathrm{n}}_2 - 2)}}}}$$

(3)

In addition, Analysis of Variance (ANOVA) is used to determine whether there are significant differences between the means of three or more independent groups. It is particularly suitable when the independent variable is categorical and the dependent variable is continuous. The reason for choosing ANOVA in this study is its ability to assess group-level differences efficiently without inflating the risk of Type I error that occurs when conducting multiple t-tests. ANOVA helps to separate the total variation observed in the data into the variation between groups and variation within groups, allowing researchers to understand whether the group classification explains a significant portion of the differences in outcomes. In this context, ANOVA offers a robust and appropriate approach for comparing how different groups of stakeholders perceive or adopt traceability practices. The rationale for using this method is supported by Iversen and Norpoth [73] and Hoaglin, Mosteller [74], who explain its value in detecting meaningful differences across multiple categories in applied social science research. Eta-squared (η²) is a measure of effect size used alongside ANOVA to quantify how much of the total variance in a dependent variable can be attributed to a specific independent variable [75]. While ANOVA tells us whether group differences are statistically significant, η² provides insight into how meaningful those differences are in practical terms. It does this by calculating the proportion of the variance explained by the grouping variable in the analysis. In this study, η² was used to complement the ANOVA results by indicating the strength of the relationship between stakeholder group classifications and their responses regarding traceability. This helps move beyond significance testing alone and offers a clearer picture of the impact of the differences, which is especially important for guiding policy or industry interventions. Including η² ensures that findings are statistically valid and practically relevant.

4. Results

The dataset used for the survey results and analysis comprises responses from 65 Australian entities, divided into two groups based on their adoption of a CE strategy. Among these entities, 16 do not have a CE strategy, while 49 have implemented one. The segmentation by company size (see Table 1) will be used to analyse the scale of a company approach to use traceability, quality control, and circular economy practices. Larger businesses generally have more resources, financial, technical, and operational, to invest in advanced tracking systems, certifications, and quality control measures. They are often better equipped to implement comprehensive sustainability initiatives and adhere to stricter environmental standards. Medium-sized businesses may have some resources for these practices but may not achieve the same depth as larger organisations. Small businesses, on the other hand, often have limited resources and may focus only on basic compliance or immediate operational needs. This segmentation helps to highlight the differences in sustainability practices and challenges across business sizes, offering a clearer picture of how each group can improve its circular economy efforts. Understanding these variations allows for more tailored recommendations, recognising that large, medium, and small businesses face distinct barriers and opportunities in achieving circularity and enhancing the quality of recycled plastic in their supply chains.

Table 1. Segmentation by Australian company size.

Size of Companies	With CE Strategy	Without CE Strategy
Small (1 to 25 employees)	25	7
Medium (26 to 500 employees)	16	4
Large (Above 501 employees)	8	5

4.1. The Importance of Traceability in Enabling Circular Economy Outcomes

The analysis focuses on traceability-related survey questions to understand their significance within the broader framework of circular economy adoption (Table 2).

Table 2. Traceability system implementation (a high score indicates that the practice has been implemented).

Company Size	Indicator	Score Without CE	Score with CE
Small	Mean	0.00	0.44
	stdev	0.00	0.51
Medium	Mean	0.25	0.56
	stdev	0.50	0.51
Large	Mean	0.40	0.62
	stdev	0.55	0.52
All included	Mean	0.19	0.51
	Stdev	0.40	0.50

Table 2, which evaluates the implementation of traceability systems across company size and CE strategy, shows a clear trend: Companies with a CE strategy are more likely to implement traceability systems than those without. Small companies’ mean score increases from 0 (no traceability) without CE to 0.44 with CE, though variability (standard deviation) remains moderate at 0.506. Medium-sized companies exhibit a similar improvement, with the mean rising from 0.25 to 0.5625 when adopting CE strategies, indicating higher adoption of traceability. Large companies exhibit the highest overall adoption rates, with a mean score of 0.4 without CE and 0.625 with CE. This aligns with the hypothesis that larger firms typically have more resources and systems in place to implement traceability. The standard deviations suggest that variability is relatively consistent across all company sizes and CE strategies. The skewness and kurtosis values reveal that the traceability data for companies without CE strategies are heavily skewed (positive skewness of 1.771), indicating most companies scored near zero (no traceability). In contrast, those with CE strategies display a more symmetrical distribution, with skewness close to zero and negative kurtosis, suggesting a flatter spread.

4.2. The Barriers and Enablers That Shape Its Adoption

Specifically, the survey responses will be examined to identify trends, relationships, and potential gaps regarding traceability systems implemented across organisations. The questions cover traceability dimensions, such as the integration of traceability systems with suppliers and customers (Table 3 and Table 4), and familiarity with digital and physical traceability technologies, including blockchain, chemical tracing, and other methods. By analysing these responses, the study will explore awareness, adoption, and confidence in traceability systems, as well as their perceived value in improving material flows within the recycling process. Cross-tabulation and statistical methods, including correlation and regression analysis, will be used to link traceability outcomes with factors such as company size, adoption of circular economy strategies, and economic or systemic influences. This approach will provide insights into how traceability systems contribute to ensuring the quality of recycled materials, strengthening supply chain transparency, and addressing systemic challenges within the circular economy. The focus on traceability will also highlight critical areas where improvements or policy interventions may be needed to support better integration and standardisation of traceability frameworks across industries.

Table 3. Shared traceability system with suppliers and customers (a high score indicates that the system has been shared).

CE Strategy	Indicator	With Suppliers	With Customers
Without	Mean	0.12	0.18
	Stdev	0.34	0.40
With	Mean	0.22	0.36
	Stdev	0.42	0.48

Table 4. Shared traceability system with suppliers and customers clustered by company size (a high score indicates that the system has been shared).

Company Size	Indicator	With Suppliers	With Customers	With Suppliers	With Customers
		Without CE Strategy		With CE Strategy
Small	Mean	0.00	0.00	0.12	0.32
	Stdev	0.00	0.00	0.33	0.48
Medium	Mean	0.25	0.25	0.25	0.44
	Stdev	0.50	0.50	0.45	0.51
Large	Mean	0.20	0.40	0.50	0.37
	Stdev	0.45	0.55	0.53	0.52

Table 3 explores traceability systems shared with suppliers and customers. Companies with CE strategies show higher mean scores for both suppliers (0.224) and customers (0.367) compared to companies without CE strategies (0.125 and 0.1875, respectively). This indicates that adopting a CE strategy increases collaboration and transparency in traceability with external partners. The standard deviations reflect more significant variability among companies with CE strategies, suggesting differing levels of maturity and adoption. Notably, skewness and kurtosis values highlight that traceability sharing among companies without CE strategies is highly skewed and leptokurtic (suppliers skew = 2.509, kurtosis = 4.897), pointing to a small subset of companies engaging in traceability sharing. In contrast, companies with CE strategies show reduced skewness and flatter kurtosis values, indicating more uniform adoption patterns. In Table 4, the data is further clustered by company size, providing a more granular view of traceability sharing. For small companies, traceability systems with suppliers and customers are absent without CE (mean = 0), but with CE, traceability sharing increases slightly to 0.12 with suppliers and 0.32 with customers. Medium-sized companies demonstrate moderate engagement, with mean scores increasing from 0.25 (without CE) to 0.25–0.4375 (with CE), particularly with customers. Large companies’ mean traceability scores are the highest across all categories, reaching 0.5 with suppliers and 0.375 with customers when CE strategies are adopted. The standard deviations indicate that larger firms have more consistent implementation of traceability systems than small and medium companies, which show more significant variability.

These tables illustrate that circular economy strategies significantly enhance traceability adoption and sharing, particularly among medium and large companies. Small companies need help implementing traceability systems, likely due to resource constraints. Larger firms benefit from economies of scale, which may explain their higher scores and lower variability. The skewness and kurtosis trends reinforce the observation that CE strategies reduce the concentration of companies without traceability systems and promote more uniform adoption across company sizes. These findings highlight the need for targeted support and incentives, especially for smaller firms, to facilitate wider adoption of traceability systems.

A t-test is used to compare responses between organisations with and without a CE strategy to analyse the differences in industry perceptions further. In addition to the t-test, Cohen’s d-effect size is calculated to assess the practical significance of these differences among the company size for each category. While statistical significance identifies whether a difference exists, effect size quantifies the magnitude of that difference, providing a clearer understanding of its real-world relevance. This approach ensures that statistical and practical implications are considered when evaluating how organisations perceive and address traceability and circularity challenges. A degree of freedom (df) of 63 corresponds to a critical value of ±2.00 from the t-table, based on a significance level of α = 0.05 as the target p-value (Equation (2)). The t-test result of 2.60 indicates a statistically significant difference in traceability implementation scores between companies with and without a CE strategy (Equation (1)). The H₀ is rejected since the obtained t-value exceeds the critical threshold and the p-value. This confirms that companies with a CE strategy have significantly higher traceability implementation scores than those without, suggesting that CE implementation is associated with a stronger emphasis on traceability measures.

Cohen’s d effect size analysis is conducted to assess the practical significance of differences in traceability adoption scores across different company sizes. While the t-test identifies whether these differences are statistically significant, Cohen’s d provides insight into the magnitude of these differences, helping to determine whether they are meaningful in real-world applications. Given that larger companies often have more resources and structured processes for implementing traceability system compared to smaller businesses, it is important to quantify the extent of these disparities. By segmenting the analysis based on company size, we can better understand whether variations in traceability adoption are substantial or merely a result of sample variability. This approach ensures that findings are statistically significant and relevant for strategic decision-making in promoting circular economy practices across businesses of different scales.

The effect size results from Cohen’s d indicate varying levels of impact for traceability implementation and sharing using Equation (3). The most significant effect was observed in implemented traceability (d = 0.67), suggesting a substantial difference between companies with and without a CE strategy. This implies that CE adoption strongly influences whether a company integrates traceability measures, making it a key determinant. In contrast, traceability shared with customers (d = 0.38) represents a small-to-medium effect, indicating that while CE strategy plays a role, other factors such as market demand, regulatory pressure, or industry norms might influence traceability sharing with customers. Finally, traceability shared with suppliers (d = 0.25) had the weakest effect, suggesting that CE adoption does not substantially change supplier-related traceability sharing. This could mean supply chain pressures, contractual obligations, or existing industry frameworks are more dominant in supplier traceability than CE adoption. For traceability shared with suppliers, small companies show a small effect size (d = 0.41), while large companies show a medium effect (d = 0.58). This indicates that larger companies share traceability data with suppliers more consistently than smaller ones. Medium-sized companies show no notable difference (d = 0.00), suggesting similar practices to the reference group. Regarding traceability shared with customers, small companies exhibit a moderate effect size (d = 0.77), suggesting they are more proactive than the reference group in sharing traceability data with customers. Medium-sized (d = 0.37) and large companies (d = −0.05) show small or negligible effects, indicating less variation from the baseline. Regarding traceability implementation, small companies have the most significant effect (d = 0.99), showing a strong tendency to implement traceability systems. Medium-sized companies also demonstrate a medium effect (d = 0.61), while large companies show a more negligible effect (d = 0.43). This suggests that traceability is more actively implemented by smaller and medium enterprises, possibly due to more agile systems or targeted sustainability strategies. At the same time, larger companies may face more structural or integration challenges. Company size influences the extent to which traceability is implemented and how it is communicated across the supply chain, with small companies standing out in their engagement.

Although the ANOVA test (Table 5) did not produce any breakthrough findings, the eta-squared (η² = 0.567) reveals that CE strategy and company size together explain over half (56.7%) of the variation in how companies adopt traceability systems. This means that, even if group averages appear similar, these two factors still have a strong influence on whether a company has implemented traceability practices. In simpler terms, larger companies and those with a CE strategy are much more likely to adopt traceability systems, even if the differences are not always sharp enough to show up as statistically significant in a small sample. This finding is consistent with the effect sizes (Cohen’s d) observed for implemented traceability, reinforcing that CE adoption plays a key role in whether firms actually track their recycled materials. However, when it comes to sharing traceability data externally, with either customers or suppliers, the influence of CE strategy and company size weakens. In those cases, other factors likely matter more, such as industry-specific regulations, data-sharing hesitancy, or customer demand. For instance, companies might be tracking materials internally but may not yet have systems or incentives to share that information with external stakeholders.

Table 5. ANOVA and η² results.

Source of Variation	Degrees of Freedom (df)	Sum of Squares (SS)	Mean Square (MS)	F-Value	p-Value	Eta-Squared (η2)
Between Groups	2	444.02	222.01	10.05	0.0017	-
Within Groups	15	331.16	22.08	-	-	-
Total (Traceability shared with Suppliers)	17	775.18	-	-	-	0.572
Between Groups	2	438.70	219.35	9.93	0.0018	-
Within Groups	15	331.18	22.08	-	-	-
Total (Traceability shared with Customers)	17	769.88	-	-	-	0.569
Between Groups	2	434.99	217.50	9.85	0.0018	-
Within Groups	15	331.31	22.09	-	-	-
Total (Traceability implementation)	17	766.30	-	-	-	0.567

This paradox arises because ANOVA tests whether group means are significantly different, but significance depends on sample size and group variability. If there is considerable overlap in traceability adoption levels between companies with and without a CE strategy, ANOVA may not detect statistically significant differences. However, eta-squared remains useful because it measures how much variance in traceability adoption is accounted for by CE strategy and company size, independent of statistical significance. While the absolute difference in means may not be significant enough to pass the ANOVA threshold, the overall effect of CE strategy and company size is still meaningful in explaining traceability trends. For implemented traceability, the considerable eta-squared value aligns with Cohen’s d, reinforcing that CE adoption is a dominant factor in whether companies implement traceability. In contrast, for traceability shared with customers (η² = strong effect, but Cohen = small effect), while CE strategy does influence traceability sharing, other factors likely dilute its impact, such as customer expectations or industry-specific regulations. Similarly, for traceability shared with suppliers (η² = strong effect, but Cohen = small effect), the minimal Cohen’s d and eta-squared indicate that supplier-side traceability decisions are likely governed by factors external to CE strategy and company size, such as compliance standards, operational constraints, or data-sharing reluctance. While CE adoption is an important driver, policies aiming to improve traceability adoption should also consider sector-specific influences, digital infrastructure, and regulatory incentives beyond just CE integration.

4.3. The Techniques Used to Monitor and Integrate Traceability Across Value Chains

The question, “How to incorporate activities within the value chain/stages to ensure the traceability of recycled plastics?” highlights a critical element in understanding the integration of traceability systems within the circular economy framework. Based on the data analysed, incorporating traceability activities within the value chain requires targeted approaches at various stages of the recycling and production process, with different implications for companies of varying sizes and their CE strategies. The responses highlight a range of perspectives and approaches across industries regarding the implementation and feasibility of traceability systems for recycled plastics.

A significant proportion of respondents (98%) emphasise in-house waste management as part of their circular economy implementation, reflecting a strong internal focus on closed-loop systems. Various technological solutions are proposed, such as barcoding laser-engraved into parts to track material combinations, production batches, and blockchain applications; however, the workability of blockchain is met with scepticism. Alternatives like chemical or catalyst recovery are mentioned as promising but require further evaluation. Centrally managed registries, which enable data sharing between manufacturers and recyclers, are suggested as practical mechanisms for monitoring the origin and composition of materials. Chain-of-custody systems, such as International Sustainable and Carbon Certification (ISCC PLUS certification), emerge as a recognised standard for ensuring traceability and preventing greenwashing, alongside correct labelling, product passports, and smaller batch labelling that details ingredients and weight percentages. Some responses highlight the importance of education for the general public, utilising digital spectrum technologies such as fluorescence and closed-loop certification systems to enhance end-user confidence. Legislation and mandatory schemes are frequently cited as critical enablers, with calls for national centralised registers to trace inventories across import, manufacturing, and recycling stages. Uniform standards, auditing systems, and thorough feedstock reporting are deemed necessary to ensure traceability, consistency and accountability. A few respondents expressed hesitation or doubt, highlighting concerns over complexity, cost, and difficulty tracing materials once mixed, shredded, or melted. Some responses also reflect disinterest in overcomplicating systems for what they perceive as inferior products. In contrast, others indicate significant investments in proprietary systems to trace plastics from collection to final product. Strengthening relationships with suppliers through quality assurance, regular visits, and feedstock monitoring is emphasised as a practical measure to improve traceability outcomes. Additionally, returning plastics to their original manufacturers to produce new products exemplifies small-scale closed-loop practices that are already in place. Overall, the responses reflect a mix of existing efforts, technological proposals, legislative demands, and uncertainty surrounding the feasibility of fully implementing traceability systems across all stages of the value chain.

4.4. The Development of a Practical Protocol to Guide and Improve Traceability Efforts Across the Sector

The score grading system assesses the degree of traceability implementation across organisations by evaluating their engagement in reporting, procurement, and additional traceability measures (Table 6). A score of 5 indicates that organisations focus on either reporting or procurement activities individually, where reporting refers to tracking and documenting traceability data and procurement reflects sourcing practices with traceability considerations.

Table 6. Score for reporting traceability system in place in organisation clustered by company size (a high score indicates that the practice has been implemented).

Company Size	Indicator	Without CE	With CE
Small	Mean	0.00	2.44
	Stdev	0.00	3.40
Medium	Mean	1.25	3.00
	Stdev	2.50	3.95
Large	Mean	2.00	5.62
	Stdev	2.74	5.34
All included	Mean	0.94	2.89
	Stdev	2.01	3.17

The significant difference in traceability reporting scores between large and medium companies likely stems from structural capacity and system maturity. Large firms are more likely to have formalised quality and compliance systems, internal audit processes, and advanced infrastructure that support consistent traceability practices. In contrast, medium-sized firms, while often more capable than small enterprises, may still face operational uncertainty or lack integrated digital traceability tools. This could explain the smaller performance gap between medium and small companies, who often share similar constraints in human and financial resources. These dynamics suggest that achieving traceability maturity is not only a function of size but also of institutional capability and strategic alignment with circular economy principles.

A higher score of 10 is assigned when both reporting and procurement processes are integrated, reflecting a more comprehensive approach. Organisations achieving a score of 12 demonstrate the most advanced systems, incorporating reporting, procurement, and additional measures such as batch numbering and certifications like ISCC Plus, which ensure third-party validated chain-of-custody practices. Lower scores, such as 2 and 3, indicate essential efforts, including internal record-keeping or compliance with ISO 9001’s one step up, one step down requirements [76]. These requirements focus on tracking direct suppliers and customers but lack broader third-party certification. The lowest score of 1 is given when traceability efforts are minimal or unclear, categorised as “other.” This system effectively differentiates the maturity of traceability practices, with higher scores representing greater integration, formalisation, and validation within organisational processes.

The mean score for small companies without a CE strategy is 0, indicating that these companies do not have any systems in place to trace recycled plastics. The standard deviation is also 0, indicating that none of the small companies without a CE strategy reported having a traceability system. Small companies with a CE strategy have a mean score of 2.44, with a standard deviation of 3.40, indicating that they have more developed traceability systems. However, there is a wide range in the level of comprehensiveness of these systems across small companies.

In medium companies without a CE strategy, the mean score increases to 1.25, with a standard deviation of 2.5, suggesting that while some of these companies have minimal traceability systems, there is considerable variation in their responses. Medium companies with a CE strategy have a mean score of 3, with a standard deviation of 3.95, showing that these companies have more advanced systems than those without a CE strategy.

Large companies without a CE strategy have a higher mean score of 2, with a standard deviation of 2.74, indicating that larger companies tend to have more advanced systems than smaller ones. However, there is still significant variability in the traceability systems used. For companies with a CE strategy, the picture is quite different. The responses vary considerably. Large companies with a CE strategy show the highest mean score of 5.63, with a standard deviation of 5.34, reflecting that these companies tend to have the most advanced and comprehensive traceability systems in place. However, there is still significant variation within this group.

In Table 7, the questions “Have you heard about digital traceability systems? (Mass Balance, Blockchain, and others)” and “Have you heard about physical traceability systems? (Chemical tracing, fluorescent ink, material DNA, and others)” aim to assess the level of awareness and familiarity among respondents regarding emerging tools and technologies that enable traceability of recycled plastics.

Table 7. Understanding and knowledge about traceability systems within organisations clustered by company size (high score means higher awareness).

Company Size	Indicator	Digital Traceability	Physical Traceability	Digital Traceability	Physical Traceability
		Without CE		With CE
Small	Mean	0.43	0.28	0.60	0.60
	Stdev	0.53	0.49	0.50	0.50
Medium	Mean	0.50	0.50	0.75	0.69
	Stdev	0.58	0.58	0.45	0.48
Large	Mean	1.00	1.00	0.87	0.62
	Stdev	0.00	0.00	0.35	0.52

The first question explores digital traceability systems, which encompass advanced data-driven technologies, including mass balance approaches, blockchain, and similar platforms. These systems track and verify material flows across the supply chain by leveraging digital tools that ensure transparency, accuracy, and accountability. Mass balance methods allocate recycled content within products based on a proportionate input-output calculation, whereas blockchain provides a decentralised, immutable ledger to trace material origins, movements, and transactions. The inclusion of this question aims to determine whether respondents are aware of such technological advancements and their potential to enhance the reliability and efficiency of recycled plastic tracking.

The second question focuses on physical traceability systems, which use material-based identification techniques to trace recycled plastics. Examples include chemical tracing, fluorescent ink, and material DNA markers. These systems embed unique physical properties or markers into materials during production, enabling identification and verification of material origins, composition, and pathways even after recycling. Unlike digital systems that rely on data management, physical traceability methods offer tangible, embedded identifiers, which are particularly useful in sorting processes and ensuring quality standards during material recycling. By exploring the familiarity with digital and physical traceability approaches, these questions aim to uncover gaps in knowledge, identify existing adoption barriers, and highlight opportunities for integrating innovative technologies into traceability frameworks. Ultimately, this line of inquiry explores the potential for digital and physical systems to complement each other in developing robust traceability solutions that support circular economy objectives, improve recycled material quality, and ensure compliance with regulatory requirements.

The analysis of traceability systems highlights the critical role of CE strategies and company size in shaping awareness and implementation. Small companies with a CE strategy tend to show more familiarity with traceability systems, particularly physical traceability, indicating a lower emphasis on advanced tracking mechanisms. However, adopting a CE strategy significantly improves their understanding of digital and physical systems. This suggests that CE implementation encourages small companies to adopt traceability tools, likely driven by the need to enhance material monitoring and align with sustainability initiatives. Medium-sized companies exhibit a moderate baseline awareness of digital and physical traceability systems, even without a CE strategy. However, the presence of a CE strategy markedly strengthens their familiarity, particularly with digital systems. This improvement reflects a proactive approach by medium organisations to integrate traceability within their circular economy practices. For medium companies, CE strategies likely encourage investment in tools and frameworks that facilitate better traceability to meet regulatory, market, or operational demands. Large companies stand out with the highest levels of awareness, as all respondents without CE strategies report complete familiarity with digital and physical traceability systems. This demonstrates that larger organisations have already embedded traceability practices within their operations due to their resources and scale. Interestingly, CE strategy adoption slightly reduces the reported focus on physical traceability systems, while awareness of digital systems remains robust. This shift could indicate that large companies with CE strategies prioritise other aspects of circular economy implementation, such as material recovery or process efficiency, over physical traceability mechanisms, which may be perceived as more complex or less impactful.

Overall, the findings suggest that while large companies lead in traceability awareness irrespective of CE adoption, small- and medium-sized organisations demonstrate substantial gains when implementing CE strategies. This highlights the enabling role of circular economy practices in fostering traceability awareness, particularly among companies with fewer resources or initial engagement in traceability frameworks. The results underscore the need for tailored support and incentives to encourage the widespread adoption of traceability systems across companies of varying sizes.

Building on the findings of this exploratory survey, future research will focus on two key directions. First, we aim to validate the traceability framework proposed in this study through semi-structured interviews with industry stakeholders across different roles and company sizes. This qualitative phase will provide deeper insight into the organisational drivers and constraints shaping traceability adoption. Second, we intend to expand the scope of analysis through cross-national comparisons with other countries implementing circular economy reforms, such as those in the EU or Southeast Asia. These comparisons will help assess the framework’s transferability and scalability beyond the Australian context. Additionally, we will explore technological integration pathways, such as digital product passports and blockchain-based verification, as part of a broader roadmap for operationalising traceability systems within circular supply chains.

5. Discussion

This study provides new empirical evidence on how Australian organisations perceive and adopt traceability in recycled plastics, highlighting differences between companies with and without circular economy strategies. These findings enrich the theoretical literature by grounding discussions of CE adoption, organisational readiness, and traceability in a national context.

Traceability continues to emerge as a vital component in circular economy systems, with stakeholders increasingly advocating for mechanisms that verify the origin and composition of recycled plastics. These mechanisms are crucial for meeting regulatory requirements and for responding to the rising expectations of consumers. In line with prior studies that highlight the adaptability of SMEs in adopting digital traceability tools [77], our survey revealed that organisations with circular economy strategies reported significantly greater openness to digital solutions such as blockchain and digital product passports, whereas non-CE firms expressed lower readiness levels. This divergence suggests that the presence of a CE strategy can act as a proxy for digital traceability adoption, supporting organisational readiness frameworks which emphasise the importance of internal strategic alignment as a driver of systemic change. The reliance on digital systems is significant because they provide a more reliable alternative to self-reported data, ensuring accuracy, transparency, and accountability in tracking materials, components, and products across the value chain. As Argus and Iyer-Raniga [78] argue, the effectiveness of circular economy business models depends on the development of robust data frameworks that enable the consistent capture and verification of information throughout the product lifecycle. Our findings reinforce this claim by showing that firms strategically committed to CE are already better positioned to leverage such frameworks, while others remain hesitant, reflecting uneven levels of preparedness for circular transitions.

The broader trend of greater standardisation and coordination in traceability reflects a parallel push to invest in advanced recycling infrastructure as a foundation for scaling circular economy systems. These steps are crucial for improving the integrity of recycled plastics and are fundamental to scaling a sustainable circular economy. However, many SMEs prioritise legal compliance and corporate image over environmental goals, often due to concerns about profitability and competitiveness [79]. Our survey results support this pattern: many respondents without CE strategies ranked regulatory compliance and reputational concerns as higher priorities than environmental objectives, suggesting that profitability remains a dominant driver in traceability adoption. Nonetheless, collaborative opportunities, such as industrial symbiosis and closed-loop systems, remain underutilised despite their proven benefits in several studies [80,81]. This underutilisation was also evident in our data, where relatively few firms reported active traceability collaboration with suppliers or customers, indicating that systemic integration across the value chain is still limited. As Negri, Neri [82] noted, manufacturers often face structural and relational barriers that hinder effective collaboration. Performance measurement is another area that requires development. While it is key to evaluating circularity outcomes, many SMEs lack access to integrated frameworks suited to their scale and context [83]. This aligns with our finding that SMEs in particular expressed uncertainty about data quality and standardisation requirements, pointing to gaps in available tools for performance tracking at their operational scale. In the Australian setting, Feldman, Seligmann [84] identified multiple barriers to circular economy implementation across different waste streams, including misaligned regulations, high transportation costs, limited government support, and inconsistent data quality. Our survey responses reinforce these observations, with respondents frequently citing inconsistent regulatory expectations and data challenges as obstacles to effective traceability. Addressing these barriers will therefore require targeted actions such as improving access to reliable data, harmonising regulatory frameworks, and introducing verification protocols for recycled materials, as both the literature and our empirical evidence confirm.

In addition to company-level practices and technical systems, policy frameworks play a crucial role in shaping the trajectory of traceability and circularity in plastic recycling [85]. While some businesses take the initiative, the broader system remains heavily influenced by regulatory clarity, consistency, and enforcement. A lack of harmonised national policies, particularly in federated systems like Australia’s, often creates fragmented responsibilities across states and territories. Our survey findings echo this challenge: respondents frequently identified inconsistent regulatory expectations and unclear responsibilities as barriers to traceability adoption, particularly among firms operating across multiple jurisdictions. This policy fragmentation can discourage investment in traceability infrastructure, especially for companies operating across multiple jurisdictions. Without clear guidelines or incentives, businesses may deprioritise traceability despite its potential to support regulatory compliance and enhance competitiveness in emerging circular markets. Moreover, policy design often overlooks SMEs’ operational realities and resource constraints, which comprise a large proportion of the plastics value chain [86,87]. This was evident in our data, as SMEs consistently reported higher sensitivity to compliance costs and limited access to certification schemes compared to larger firms, suggesting that one-size-fits-all approaches risk excluding smaller players. While larger firms may be able to invest in digital tools and third-party certification schemes, smaller firms are more likely to be excluded from such transitions without targeted support. This underscores the importance of designing scalable and accessible policy instruments that align with the varying capacities across industry segments. In particular, the strong support expressed by respondents for government-led incentives highlights that policy levers such as subsidies, tax credits, or mandatory traceability reporting requirements could be decisive enablers if tailored to industry needs [88].

International developments such as the European Union’s Digital Product Passport [89] and the Basel Convention’s controls on transboundary plastic waste movements [90] also signal an increasing shift towards mandatory traceability on a global scale. These initiatives reflect a move from voluntary practices to enforceable obligations, which may soon influence global trade and market access. Australian businesses seeking to remain competitive in international markets must likely align with these evolving standards. Our survey highlights that only a minority of firms reported alignment with, or awareness of, international traceability frameworks, underscoring a gap between global policy trajectories and current industry practice in Australia. This suggests that without stronger national guidance, many organisations risk being unprepared for international compliance obligations. This makes it even more urgent to develop a national traceability framework that is interoperable with international systems and capable of supporting compliance with cross-border expectations. There is also an opportunity for governments to foster public–private partnerships that pilot innovative traceability solutions in key sectors such as packaging, construction, or agriculture [88]. Respondents expressed support for collaborative initiatives of this kind, with several noting that shared pilot projects could reduce costs and accelerate knowledge transfer, particularly for SMEs. Such collaborations serve as test beds for regulatory innovation, allowing policymakers to refine standards based on real-world feedback. Furthermore, better integration between policy and research could help bridge current data gaps by establishing coordinated mechanisms for reporting, sharing, and analysing traceability data across the value chain [20]. Traceability should not be positioned as a technical fix but a policy priority embedded in broader sustainability and climate agendas. Our findings support this position, as firms consistently ranked policy clarity and integration with broader sustainability goals among the most critical enablers of traceability adoption. Linking traceability to national targets on emissions reduction, resource efficiency, or EPR would reinforce its relevance and attract broader institutional support. Doing so could accelerate progress toward circular economy goals and ensure that traceability becomes a cornerstone of resilient and transparent plastic waste management systems.

One of the key barriers to traceability adoption in Australia is the inconsistency of regulations across state and territory jurisdictions. For example, while some states mandate the use of digital waste tracking systems (New South Wales through the WasteLocate platform), others rely on more manual or voluntary approaches, creating incompatibility in data formats and reporting expectations. In addition, recycled content targets and procurement standards vary between federal, state, and local levels, which causes uncertainty for businesses aiming to certify and track recycled input materials across markets. Another example is the lack of national alignment on plastic classification and labelling, which affects interoperability between waste processors and manufacturers. Without harmonised definitions of recyclable grades or contamination thresholds, traceability systems cannot reliably track material attributes through the supply chain. These regulatory inconsistencies hinder investment in scalable traceability tools and reduce the comparability of traceability data across regions. A unified national framework, aligned with global standards such as GS1 [91] and ISO 22095 [63], would improve transparency, lower compliance costs, and accelerate adoption by reducing the complexity faced by businesses operating across multiple jurisdictions.

This study reveals apparent differences in how companies with and without circular economy strategies approach traceability, particularly in implementation among smaller businesses. Survey data showed that firms with CE strategies were more likely to engage in basic traceability practices, such as internal monitoring of recycled content. In contrast, non-CE firms reported significantly lower levels of adoption. However, effect sizes for traceability shared with suppliers and customers remained small across both groups, indicating that external integration is still weak. When examined through the lens of the ISO 59000 series, these findings expose important gaps. ISO 59004 [92] underscores the importance of systems thinking and inter-organisational collaboration in achieving circular outcomes. ISO 59010 [93] further emphasises the importance of supply chain engagement and the need to identify leverage points for creating circular value networks. Our results confirm that this type of supply chain engagement remains limited: most respondents prioritised internal processes over upstream or downstream traceability, suggesting that circularity is still treated as an internal adjustment rather than a systemic transformation. Moreover, ISO 59020 [94] points to the importance of establishing shared indicators and data exchange mechanisms to assess circularity at the network level. Respondents’ uncertainty about performance metrics and data exchange requirements reflects this gap, pointing to the need for clearer and more standardised indicators to enable inter-organisational alignment. This study’s limited engagement with supplier and customer traceability may therefore indicate missed opportunities for more integrated and collaborative circular practices. These findings highlight that current industry practice lags behind international frameworks, reinforcing the importance of moving beyond internal compliance to network-level coordination. Future research should move beyond survey data to better understand these dynamics and incorporate interviews or case studies that explore how companies engage their upstream and downstream partners. This would align with ISO recommendations and support a deeper understanding of systemic value creation and the socio-economic dimensions of circularity. Strengthening these external connections could enhance traceability, improve material flow management, and increase the resilience and sustainability of circular transitions.

While this study focuses primarily on empirical patterns of traceability adoption, the findings can be further enriched through engagement with established theoretical frameworks. First, Rogers’ [95] Diffusion of Innovation theory offers a useful lens for interpreting the heterogeneity in traceability adoption. Large firms in this study appear to function as early adopters or innovation leaders, often driven by reputational advantage, regulatory anticipation, or resource availability. In contrast, smaller firms demonstrate more variable or lagged adoption, consistent with diffusion patterns influenced by perceived complexity, observability, and relative advantage. Second, Institutional Theory [96] helps explain the presence of isomorphic pressures influencing traceability system uptake. Coercive pressures (emerging recycled content mandates), mimetic pressures (copying competitors’ traceability practices), and normative pressures (alignment with sustainability certifications) all contribute to traceability adoption becoming an organisational norm, especially among firms aligned with CE strategies. Finally, Geels’ [97] Multi-Level Perspective (MLP) provides a systemic understanding of how traceability systems are emerging within the CE transition. From this perspective, traceability can be considered a niche innovation that interacts with established industry regimes (waste management, manufacturing standards) and landscape-level pressures (global plastic pollution, consumer demand for transparency). The uneven diffusion observed across firm sizes and roles may reflect the early-stage alignment, or misalignment, between these levels. Our findings suggest the value of a hybrid theoretical framework that integrates organisational behaviour [93,94] with system-level transition theory [97], offering a more comprehensive view of the opportunities and constraints shaping traceability implementation in circular plastics economies.

One major limitation is the sample size, which restricts the ability to draw statistically significant conclusions. This study should therefore be exploratory, providing a first structured baseline of how Australian organisations perceive traceability within the recycled plastics sector. Although this study focused exclusively on industry actors, we acknowledge the critical role that consumers, NGOs, and policymakers play in supporting circular economy adoption. Their perspectives are essential for understanding demand-side pressures, regulatory influence, and advocacy for traceability. Future research should expand to include these actors, either through stakeholder interviews or cross-sectoral collaboration frameworks. Expanding the participant pool in future studies would strengthen the robustness and representativeness of the findings, allowing a more detailed comparisons across company sizes, industrial sectors, and levels of CE integration. Furthermore, gathering responses from multiple individuals within each organisation, for instance, both senior decision-makers and operational personnel, would yield a more holistic understanding of how traceability is perceived and implemented internally. This multi-level approach would also make it possible to examine internal differences, revealing whether strategic priorities at the management level are consistently reflected in day-to-day operational practices. Another limitation relates to the method: while surveys help map perceptions, they cannot fully capture the organisational and relational dynamics involved in implementing traceability systems. Complementary methods such as interviews, case studies, or longitudinal tracking would provide richer insights and allow triangulation of results. Extending this research to international context where circular economy initiatives are more mature would offer valuable comparative perspectives. Examining countries with well-established circular frameworks could help identify emerging trends, performance benchmarks, and effective policy models that may guide both industry and regulatory development in regions where CE implementation remains in its early stages. Addressing these current limitations would greatly enhance the study’s ability to generate robust indicators and actionable insights, thereby contributing to a broader, globally informed understanding of traceability management within recycled plastics system. By addressing these limitations, future research can build on this exploratory study to develop meaningful indicators, refine theoretical frameworks on organisational readiness for the circular economy, and generate actionable insights for both policy and industry. In this way, the limitations also highlight the potential of this study as a foundation for a broader research agenda.

6. Conclusions

In conclusion, this study reinforces that traceability is a foundational enabler of circular plastics systems, particularly among firms that have adopted circular economy strategies. While awareness and internal implementation are advancing, traceability remains inconsistently applied across the value chain, limiting its potential to support system-wide circularity. The gap between organisational uptake and inter-organisational integration reflects broader issues of fragmented governance, technological misalignment, and weak incentives for data transparency. To address these challenges, we propose establishing a national traceability mandate for recycled plastics as part of Australia’s circular economy strategy. This mandate should include mandatory traceability reporting for plastic producers and recyclers, financial incentives for SMEs to adopt interoperable digital or physical tracking systems, and the development of a unified certification and labelling framework aligned with emerging international initiatives such as the EU Digital Product Passport. By institutionalising traceability as a regulated and incentivised norm, not merely a voluntary practice, policymakers can accelerate systemic collaboration, enhance trust in recycled materials, and improve Australia’s competitiveness in global circular markets.