Digital-Driven Circular Ecosystems for the Textile Sector: Insights from a Survey on Sustainable Practices in Italy

Abstract

The textile industry is among the most environmentally impactful sectors, underscoring the urgency of transitioning to circular economy models. This study examines the development of a digital-driven circular ecosystem for the Italian textile sector, leveraging insights from a comprehensive survey on sustainable practices. By analyzing material flows and identifying inefficiencies, the research proposes an integrated framework to enhance sustainability across the supply chain. Key indicators are established to monitor environmental, economic, and social impacts, offering a practical tool for decision-making. The findings reveal how scenario-based approaches and targeted strategies can empower Italian textile companies to adopt circular practices effectively. This work lays the groundwork for a robust ecological transition, fostering both environmental sustainability and competitive advantage in the global market.

1. Introduction

The transition to a circular economy represents a strategic response to contemporary ecological crises, favoring the reintegration of biological flows—such as resource recovery and sustainable waste management—into the biosphere. At the same time, it aims to optimize technical flows, which include production, reuse, and recycling processes, drastically reducing the generation of waste [1]. In this sense, the analysis and measurement of energy and material flows in manufacturing companies becomes crucial to identify opportunities for improvement, not only in terms of operational efficiency, but also to ensure sustainable management of resources, be they financial, human, or technological [2].

Particular attention is paid to the textile sector, recognized as one of the most impactful for the environment [3]. This sector, considered a strategic industrial supply chain, presents several critical issues, including the poor diffusion of ecodesign strategies and the absence of adequate tools for product traceability, such as the digital passport [1]. It is therefore essential to rethink energy and material flows, evaluating their potential through innovation and the adoption of sustainable practices.

The textile and clothing industry is one of the most important sectors in Italy, known for its quality, flexibility, and innovation, and is a key strength for the country’s economy and the image of Made in Italy. According to Euratex (in Italian: Unione europea delle associazioni industriali del tessile-abbigliamento), Italy is the leading player in the European textile and clothing industry, representing 36% of the EU’s total turnover (EUR 147 billion). Italy also employs 22% of the 1.3 million workers in the sector across Europe and accounts for 27% of the total textile and clothing exports in the EU [4].

In Italy, the sector employs over 400,000 people, representing 12% of all manufacturing workers, and its turnover accounts for 8% of total manufacturing output. According to ISTAT (in Italian: Istituto Nazionale di Statistica), there are 53,272 companies in the textile and clothing sector in Italy, confirming the sector’s significant role in the economy. The Italian fashion industry is largely composed of small- and medium-sized enterprises, which foster strong innovation, flexibility, and competitiveness [5].

However, the industry is also responsible for a significant amount of textile waste. According to Ispra (in Italian: Istituto superiore per la protezione e la ricerca ambientale), around 160,000 tons of textile waste are produced annually in Italy, equivalent to about 500 million garments. This trend is increasing, highlighting the urgent need for improved waste management practices in the sector [6].

In a context such as the Italian one, the complete transition to the circular economy is configured as a strategic objective. It allows us to address global challenges, such as the restructuring of globalization processes, capitalization on the opportunities offered by the digital revolution, and the launch of green transformation processes [7]. To effectively implement this transition, it is imperative to stimulate greater awareness and participation among all the actors involved, from production to consumption. This requires an unprecedented commitment in terms of information, communication, and education to promote integrated sustainable development [8,9,10].

Despite the growing attention to the circular economy in the textile sector, there is a significant research gap in terms of quantifying and effectively implementing sustainability metrics across the entire supply chain. While many studies focus on large corporations, there is little focus on how SMEs can practically engage in circular practices. This work aims to bridge this gap by providing an integrated, measurable framework that is both practical and adaptable to the varied realities of SMEs.

In the textile sector, the measurability of sustainability remains a crucial challenge. In many cases, it is seen more as a concept than as a concrete fact, exposing the sector to the risks of greenwashing and disinformation. This study intends to overcome these challenges by proposing an integrated network capable of collecting and analyzing essential data to measure the sustainability and circularity of the practices implemented. Among the main objectives are the reduction in the water and carbon footprint, as well as the definition of specific strategies, such as carbon sequestration, to promote a more sustainable future.

To assess the state of sustainability and circularity within the Italian context, a survey was conducted. The data collected were then analyzed through descriptive statistics, and the chi-square test was applied to examine the relationships between categorical variables and determine the statistical significance of the observed patterns.

The rest of the paper is organized as follows. Section 2 reviews circular architectures, environmental impacts of the textile sector, and digital technologies for material flow optimization, emphasizing the role of data collection in sustainability. Section 3 outlines the methodology. Section 4 analyzes and discusses survey results on sustainability practices in the Italian textile industry. Section 5 proposes an operational model to measure and track the effectiveness of their sustainable practices. Finally, Section 6 concludes with key findings and insights.

2. State of the Art

In recent years, the textile industry has increasingly recognized the need for the adoption of circular economy principles to tackle its substantial environmental impact. The focus on sustainability through the reuse and recycling of materials has become vital, particularly given the sector’s high contribution to pollution, land degradation, and natural resource depletion. Alongside this, digital technologies have gained prominence as crucial tools for optimizing material flows and improving process efficiency.

By reviewing the existing literature on circular architectures and environmental impacts, this section establishes a foundational understanding of the challenges and opportunities in transitioning to sustainable practices. Furthermore, the emphasis on data collection reflects its pivotal role in enabling evidence-based decision-making, a key aspect explored in the survey. As will be analyzed in Section 4, the survey results further validate and contextualize these aspects by providing empirical insights into the current adoption levels and barriers faced by Italian textile companies, bridging theoretical frameworks with practical applications.

One of the main considerations underlying our research is that the textile and fashion industries are among the most resource-intensive and polluting sectors globally. According to Jia et al. (2022), the sector consumes about 100 million tons of non-renewable resources annually, alongside massive water consumption, which exacerbates environmental stress [11]. Studies by Saha et al. (2021) confirm that such patterns are unsustainable, with many companies still relying on linear economic models that end with products being discarded, contributing to vast waste accumulation [12]. Despite efforts to embrace sustainability, only 20% of textiles produced globally are recycled, highlighting a critical inefficiency in the current system [13]. The adoption of a circular economy, which encourages the reuse and recycling of textiles, offers a promising solution to these environmental challenges. Notably, Sandvik and Stubbs (2019) emphasize that transitioning to a circular economy requires a fundamental shift in product design, business models, and supply chain management [14,15]. The survey results align with this, as they suggest that while many textile companies in Italy are beginning to engage with sustainable practices, their adoption of circular models is still uneven. However, the data also indicate that a sizable portion of businesses has already embraced recycling practices and is working towards reducing waste through better material management (e.g., recycling residual fibers). These findings highlight how systemic change, as discussed in the literature, is already underway but needs further acceleration, particularly in areas such as reverse logistics and garment leasing.

In line with the literature, which points to the increasing importance of product redesign in the circular economy, the survey results indicate that the Italian textile sector is slowly embracing these concepts. Companies report using more eco-friendly processes and materials, and efforts to minimize water use and chemical waste are becoming more widespread. These practices mirror the trends identified by Leal Filho et al. (2019) and Dahlbo et al. (2017), who underline the environmental and economic benefits of textile recycling [16,17]. The survey’s findings on waste management, particularly the significant adoption of fiber recycling, demonstrate that Italian companies are beginning to realize the potential of circular models to not only reduce environmental harm but also create economic opportunities. Moreover, the role of industrial districts in fostering collaboration between small and medium enterprises (SMEs) has been emphasized by Coppola et al. (2023) [7] and Bressanelli et al. (2022) [18], as they argue that such collaborations can help drive sustainability across regions. The survey results confirm this, showing that while companies in various regions face similar barriers to adopting circular practices, those located in areas with stronger industrial district networks are more likely to have adopted sustainable practices. This suggests that fostering collaboration and innovation at the local level can be pivotal in overcoming national sustainability challenges.

Digital technologies have emerged as a critical enabler of the circular economy in the textile sector. As noted by Heim and Hopper (2022), technologies such as blockchain and the Internet of Things (IoT) can optimize supply chain operations, providing greater traceability and promoting responsible resource management [19,20]. Blockchain enhances traceability and transparency across the supply chain, enabling decentralized, immutable records that ensure ethical sourcing, reduce waste, and improve recycling processes [21]. When paired with RFID (Radio Frequency Identification) technology, blockchain enables real-time tracking of products, further minimizing inefficiencies and waste [16]. A key component in this process is the digital product passport (DPP), which leverages blockchain to provide a detailed, transparent history of a product throughout its life cycle, supporting responsible consumption and facilitating recycling [9]. Furthermore, Digital Twin (DT) technology contributes to sustainability by creating virtual models of physical products and processes. This allows for real-time data collection and dynamic simulations that optimize manufacturing, reduce downtime, and minimize resource consumption, leading to more efficient operations [22]. In the design phase, 3D technologies such as 3D printing, body scanning, and visualization support sustainability by enabling the creation of virtual prototypes. These technologies reduce the need for physical prototypes, cut down on material waste, and help in producing garments based on actual demand, thereby conserving water and dyes [23].

Data collection is a central theme in both the existing literature and the present survey. As Dissanayake and Weerasinghe (2021) emphasize, effective data collection enables companies to assess their environmental impact and make informed decisions towards sustainability [1]. The survey reveals that many textile companies are still in the early stages of data-driven sustainability efforts, but there is growing recognition of the importance of monitoring environmental performance. By tracking specific indicators, such as water usage, chemical disposal, and energy consumption, companies can develop more targeted strategies to reduce their ecological footprint. Rossi et al. (2019) stress that these indicators are essential for evaluating the effectiveness of circular strategies and guiding companies towards continuous improvement [24].

3. Materials and Methods

As mentioned, the textile industry is a sector characterized by a complex and long supply chain that extends from design to waste management, including crucial stages such as the supply of raw materials, production, packaging, consumption, and end-of-life of the product [25]. To analyze and promote sustainability and circular economy practices in the textile sector, data collection was carried out through a structured questionnaire (link to the survey; https://forms.office.com/Pages/ResponsePage.aspx?id=rhZ-ARX0jU-a8KIbV81Ejorsjny0h2hFsDOxuOoZbrRUOUg3MTdLNE41OFVMUldXQ1RUSVNHU1lCVy4u (accessed on 9 March 2025)).

This tool aimed to collect direct information from Italian textile companies, providing a precise picture of their current practices, the challenges they face, and the opportunities perceived in the transition towards a circular economy model. The results of the questionnaire were analyzed through a descriptive method, with the representation of graphs and diagrams, to have a clear and direct visualization of the results. In addition, for some questions a quantitative analysis was carried out, specifically chi-square analysis, to verify if there were any quantitative associations between the geographical location of the companies and sustainability practices. Specifically, the research design includes three main steps, such as a literature review, survey, and analysis of results, as shown in Figure 1.

The research design includes three main phases:

• Pahse#1. Document Review. This phase aims to identify sustainability and circular economy practices adopted by textile companies in Italy, analyzing academic documents, industry reports, and current regulations.
• Phase#2. Survey. A structured survey is administered to a sample of companies in the textile sector to collect data on their practices and perceptions regarding sustainability and circular economy.
• Phase#3. Analysis. The data obtained from the literature review and the survey are compared and analyzed to identify trends, challenges, and opportunities in the textile sector, with a focus on sustainable and circular practices.

This mixed-method approach, combining elements of both qualitative and quantitative methods, is best suited for those topics in which a single data source may not be sufficient. Therefore, the two first steps of the exploratory sequential research design were applied, starting with a collection of qualitative data followed by a quantitative method [26]. Hence, a literature review, as well as expert consultations, served to design the survey. This methodological approach allows to have a complete vision of the current dynamics of the sector and its challenges in the sustainable field.

3.1. Phase#1: Document Review

The goal of phase 1 is to identify relevant information to include in the survey. This phase serves as a preparatory step, forming the basis for addressing the research questions through the survey. The Document Review phase is focused on gathering insights into the sustainability and circular economy practices adopted by textile companies in Italy, through the analysis of academic articles, industry reports, and current regulations.

3.1.1. Step#1.1: Analyze Sustainable and Circular Practices in the Textile Sector

The first step of the research was dedicated to gathering information on sustainability and circular practices in the textile sector, with the aim of gaining a deep understanding of the challenges and opportunities related to sustainability and the circular economy. To achieve this, an in-depth search was conducted using high-quality sources, such as scientific articles, industry reports, and regulatory documents. The scientific research was primarily carried out through the SCOPUS research database, one of the largest systems for peer-reviewed article databases, which provided numerous studies on sustainability in the textile sector. These articles addressed key aspects such as the use of eco-friendly materials, the reduction in environmental impact in production processes, material recycling, and the application of circular business models. The search was conducted using specific keywords, starting from a general context and gradually narrowing down to more specific topics. A first screening was performed based on the language (only English articles were considered) and the type of document (only academic articles were selected). Subsequently, further screenings were carried out by first reviewing the titles, followed by abstracts and conclusions, to assess their relevance to the study. In total, 53 articles were selected for analysis. In parallel, industry reports were analyzed, offering practical insights into emerging trends in the textile sector regarding sustainability. These reports highlighted best practices adopted by companies, as well as innovative solutions to reduce ecological footprints and improve resource management. Reports from Italian textile companies were selected, covering different types of fabrics in order to provide a comprehensive and global view of the sector. Since only the largest companies typically produce sustainability reports, a total of 10 reports from these companies were analyzed. Additionally, regulatory documents and global and national policies were examined, such as the Circular Economy Action Plan of the European Union and the European Green Deal, to understand the regulations that promote sustainability and the circular economy in the textile sector.

This phase allowed for the characterization of the textile sector, with a particular focus on the Italian context, where the textile industry has a strong tradition and a significant role in the economy.

3.1.2. Step#1.2: Characterization of the Textile Sector in Italian Scenario

The second phase concerns the characterization of the textile sector, a crucial step due to its complexity and the variety of stakeholders involved. The textile industry is a highly complex economic sector that covers a wide range of applications and products. It refers to the set of industrial and commercial activities that cover the entire process of production, transformation, distribution, and consumption of textile products, such as clothing [27]. The Italian context was chosen for this analysis because Italy has a long-standing tradition in the textile and fashion industries, playing a significant role in the global market. The Italian context is particularly complex and diverse, as the textile industry is organized into numerous industrial districts, each with unique characteristics related to its region. Given this diversity, it was essential to create a mapping of Italian textile companies in order to obtain a comprehensive and detailed view of the production realities and the sustainable practices adopted.

To characterize the textile sector, it is useful to report the ATECO (short for “ATtività ECOnomiche”, an Italian classification system for economic activities) codes. The ATECO code consists of an alphanumeric sequence designed to identify a specific economic activity. In this sequence, the letters in the code delineate the macroeconomic sector, while the numbers, ranging from two to six digits, provide details at various levels, specifying the articulations and subcategories within the sectors themselves. ATECO serves as the classification system for economic activities in Italy and is used by ISTAT for statistical purposes in collaboration with other institutions, ministries, and business associations involved in statistics [5].

The supply chain is composed of a core part, represented by the companies of division 13 (Textile industries), division 14 (Manufacture of clothing articles; manufacture of leather and fur articles), and division 15 (Manufacture of leather and similar articles). In turn, each of the three ATECO divisions is composed of different subcategories depending on the production specialization of the companies shown in

Table 1. Textile supply chain divisions and groups (ATECO).

Division	Group
13 Textile Industries	13.1—Preparation and spinning of textile fibers
	13.2—Weaving
	13.3—Textile finishing
	13.9—Other textile industries
14 Packaging of Items of Clothing; Package of Items in Leather and Fur	14.1—Packaging of clothing items (excluding fur clothing)
	14.2—Packaging of fur articles
	14.3—Manufacture of knitwear
15 Manufacture of Articles in Leather and Similar	15.1—Tanning and dressing of leather; manufacture of luggage, bags, saddlery, and harness; dressing and dyeing of furs
	15.2—Manufacture of footwear

.

By broadening the horizon of analysis beyond the core part of the supply chain, it is possible to identify an extended supply chain, composed of three distinct parts depending on the processing phases carried out by the different companies:

• An upstream stage composed of all the subcontracting companies of the core phase;
• A downstream stage consisting of the transport, in its various typologies, of the products exiting from the core phase and the marketing activities.

Table 2. The different activities of the textile supply chain (ATECO).

Stages	Ateco-Sector
Upstream Stage	01.16.00 Cultivation of textile plants
	17.21.00 Manufacture of corrugated paper and paperboard and of packaging of paper and paperboard
	20.12.00 Manufacture of dyes and pigments
	20.16.00 Manufacture of plastics in primary forms
	20.17.00 Manufacture of synthetic rubber in primary forms
	20.59.60 Manufacture of auxiliary products for the textile and leather industries
	20.60.00 Manufacture of synthetic and artificial fibers
	22.19.00 Manufacture of other rubber products
	22.22.00 Manufacture of plastic packaging
	22.29.00 Manufacture of other plastic products
	32.99.20 Manufacture of umbrellas, buttons, zippers, wigs, and similiar
	71.20.00 Testing and technical analysis
	74.10.00 Specialized design activities
Manufacturing Stage	13.00.00 Textile industries
	14.00.00 Manufacture of clothing articles; manufacture of leather and fur articles
	15.00.00 Manufacture of leather and similar articles
Downstream Stage	46.41.00 Wholesale trade of fabrics
	46.42.00 Wholesale of clothing and footwear
	47.51.00 Retail sale of textile products in specialized stores
	49.20.00 Rail freight transport
	49.41.00 Transport of goods by road
	50.20.00 Maritime and coastal transport of goods
	51.21.00 Air freight
	95.23.00 Repair of footwear and travel goods
	95.29.03 Alteration and repair of clothing items not carried out by tailors

shows the main stages of the textile supply chain, considering the upstream and downstream stages.

To characterize the textile sector, it is essential to consider the geographical location of textile companies. The origin and location of companies can influence different aspects of the sector, such as the availability of raw materials, the presence of specific skills and local development policies. The geographical belonging of textile companies can be identified through parameters such as the place of production, the legal and operational headquarters of the company, and the presence of branches or factories in certain regions or countries [28].

The textile sector is significantly present throughout the national territory even if it is distributed with a clear concentration in the northern area. The industries of the Italian textile sector are mostly located in central-northern Italy (see

Table 3. Active companies in the textile supply chain (ISTAT 2022).

Region	Textile	Clothing	Total TC	Leather Goods	Total TCL
Italy	11,495	28,535	40,030	13,242	53,272
Northwest	3850	6030	9880	1269	11,149
Piemonte	946	1146	2092	134	2226
Valle d’Aosta	12	18	30	6	36
Liguria	116	249	365	34	399
Lombardia	2776	4617	7393	1095	8488
North East	2.107	6453	8560	2407	10,967
Trentino Alto Adige	96	199	295	53	348
Veneto	1060	3304	4364	1740	6.104
Friuli Venezia Giulia	156	209	365	53	418
Emilia Romagna	795	2741	3536	561	4097
Center	3584	9721	13,305	7335	20,640
Toscana	2730	6606	9336	4618	13,954
Umbria	238	876	1114	61	1175
Marche	346	1.102	1448	2514	3962
Lazio	270	1137	1407	142	1549
South	1587	5692	7279	2.106	9385
Abruzzo	292	644	936	256	1192
Molise	27	86	113	11	124
Campania	599	2660	3259	1413	4672
Puglia	521	1981	2502	394	2896
Basilicata	37	91	128	8	136
Calabria	111	230	341	24	365
Islands	367	639	1006	125	1.131
Sicilia	232	466	698	86	784
Sardegna	135	173	308	39	347

): north-west (33.5%), central Italy (31.2%) and north-east (18.3%). The remaining 17%, however, is found in southern Italy (13.8%) and in the Islands (3.2%) [5].

Lombardy, with an incidence of 24.2% and almost three thousand companies, is the region with the highest number of companies belonging to the textile supply chain. It is followed by Tuscona (23.7%), Veneto (9.2%), Piemonte (8.2%), Emilia-Romagna (6.9%), Campania (5.2%), Puglia (4.5%), Marche (3%), Abruzzo (2.5%), Lazio (2.3%), Umbria (2.1%), Sicilia (2%), Friuli-Venezia Giulia (1.3%), Sardegna (1.2%), Liguria (1%), Calabria (0.9%), Trentino-Alto Adige (0.8%), Basilicata (0.3%), Molise (0.2%), and Valle D’Aosta (0.1%).

Another element that characterizes the sector is linked to the average size of companies: the productive fabric of the Italian fashion system is mainly made up of medium- and small-sized companies, strongly interrelated with each other. This peculiarity allows for a high capacity for innovation, greater flexibility, and a significant degree of specialization, guaranteeing a strong competitiveness of the supply chain.

Companies in Italy are mostly small- to medium-sized, while there are few large ones. In terms of employees, 81.1% employ between 0 and 9 workers, 18.7% between 10 and 249 workers, and only 0.2% have 250 employees or more [5].

Table 4. Production structure by the class of employees in the fashion sector (ISTAT 2022).

Class of Employees	Number of Businesses	Percentage (%)
0–9	43.304	81.1
10–49	8.849	16.6
50–249	991	1.9
250 and above	128	0.2
Total businesses	53.272	100.0

shows the production structure by the class of employees in the fashion sector.

3.2. Phase#2: Survey

Research phase 2 involves the administration of a survey aimed at collecting data on the practices and perceptions of Italian textile companies regarding sustainability and the circular economy. This phase is crucial for obtaining direct information from companies to understand the extent to which they are adopting sustainable and circular solutions, the challenges they face, and how they perceive policies and opportunities in this area.

First, the target group of companies to be involved in the survey was identified, defining the characteristics and types of companies to include. Next, the most suitable communication channel was selected to reach this group, ensuring maximum participation and data accuracy. In this case, the email of the companies was used as the primary communication channel. Once these aspects were defined, the survey structure and content were developed, creating a questionnaire designed to collect relevant and detailed information on the sustainable practices adopted by the companies. Finally, the delivery method for the survey was determined, choosing the most effective and practical format to facilitate participation from the involved companies.

3.2.1. Step#2.1: Identify the Target Group

To analyze the challenges and opportunities related to the adoption of the circular economy in the textile sector, a structured survey was designed and administered to a representative sample of Italian companies. The sample selection followed a stratified approach, using the ATECO code to identify companies relevant to the textile supply chain and the geographical distribution to ensure the representation of strategic industrial regions. Companies of different sizes (mostly micro-, small-, and medium-sized companies) and sectors (production of yarns, fabrics, clothing, and accessories) were included, representing the entire spectrum of the textile supply chain.

The hypotheses underlying the study concern several factors that are believed to influence the adoption of the circular economy in the textile sector. Specifically, the following hypotheses were formulated:

H1. 

It was hypothesized that to fully understand the challenges and opportunities linked to the adoption of the circular economy in the textile sector, it was necessary to include different types of companies covering all phases of the supply chain. The inclusion of companies operating in the production of yarns, fabrics, clothing, and accessories will allow for collecting complete data on the different needs, problems, and potential of each segment.

H2. 

Regional differences in Italy, related to factors such as industrial density, sectoral specialization, and local policies, may influence the adoption of the circular economy in the textile sector. Including companies from different strategic regions of the country (such as northern, central, and southern Italy) will provide a comprehensive view of the challenges and opportunities at the national level, considering the peculiarities and resources of each area.

These hypotheses guided the selection of the sample and were formulated to better understand the challenges and opportunities associated with this transition process.

The use of ATECO codes and industrial distribution for selection may introduce certain biases, such as overrepresentation or underrepresentation of specific industries based on the coding system. Additionally, there could be response bias, where certain types of companies may be more likely to participate due to factors like size, location, or technological readiness. However, efforts were made to mitigate these biases by considering a wide range of business types and including regions from the north, center, and south of Italy, aiming to provide a more balanced and representative sample.

The choice of the typology of companies, based on the ATECO code, was made because the production and packaging phases of fabrics are among the most impactful [29], together with the leather sector [30]. For this reason, it was considered useful to focus attention on the production and packaging phases of fabrics and on the production of fabrics for clothing. In

Table 5. ATECO codes of selected companies (ATECO).

Sector	Activity
13. Textile Industries	13.10.00 Preparation and spinning of textile fibers
	13.20.00 Weaving
	13.30.00 Textile finishing
	13.91.00 Manufacture of knitted fabrics
14. Packaging of Clothing Items; Packaging of Leather and Fur Items	14.10.00 Packaging of clothing items (excluding fur clothing)
	14.11.00 Leather clothing packaging
	14.12.00 Workwear packages
	14.13.00 Packaging of other outerwear
	14.13.10 Mass production of outerwear
	14.13.20 Tailoring and made-to-measure outerwear
	14.14.00 Production of shirts, T-shirts, corsetry, and other underwear
	14.19.00 Packaging of other clothing items and accessories
	14.19.10 Various packaging and clothing accessories
	14.19.20 Sportswear or special clothing packages
	14.19.29 Packages of sportswear or other special clothing
	14.20.00 Fur articles packaging
	14.30.00 Manufacture of knitwear
	14.39.00 Manufacture of sweaters, cardigans, and other similar knitted articles
15. Manufacture of Leather and Similar Articles	15.10.00 Preparation and tanning of leather; manufacture of luggage, bags, leather goods, and saddlery; dressing and dyeing of furs
	15.11.00 Preparation and tanning of leather; preparation and dyeing of furs
	15.12.00 Manufacture of travel goods, bags and the like, leather goods, and saddlery
	15.12.09 Manufacture of other travel goods, handbags and the like, saddlery, and harness
	15.20.00 Footwear manufacturing
	15.20.10 Manufacture of footwear
	15.20.20 Manufacture of leather parts for footwear

, the ATECO codes of the selected companies are shown.

As regards the textile-clothing aggregate, Tuscany, Lombardy, Veneto, Emilia Romagna, Campania, and Puglia have the greatest sectoral representation per production unit (>2.5% of the national total), as shown in

Table 6. Active textile-clothing companies by region (ISTAT 2022).

Region	Number of TC Companies	% of National Total
Tuscany	9.336	23.3%
Lombardy	7.393	18.5%
Veneto	4.364	11%
Emilia-Romagna	3.536	8.8%
Campania	3.259	8.2%
Puglia	2.502	6.3%
Marche	1.448	3.6%

. In these areas, the sector has a significant weight, characterizing the local economy.

For the leather and tanning sector, considering a higher value > 2.5% of the national total, the regions with a greater number of companies are Tuscany, Marche, Veneto, Campania, Lombardy, Emilia Romagna, and Puglia (see

Table 7. Active leather companies by region (ISTAT 2022).

Region	Number of Leather Companies	% of National Total
Tuscany	4.618	34.9%
Marche	2.514	19%
Veneto	1.740	13.1%
Campania	1.413	10.7%
Lombardy	1.095	8.3%
Emilia-Romagna	561	4.2%
Puglia	394	3%

).

The above-mentioned regions, Tuscany, Lombardy, Veneto, Emilia Romagna, Campania, Puglia, and Marche, also appear to have the highest number of industrial districts and therefore their selection is further suitable given that a greater effectiveness of sustainability practices at company level is associated with the need for a systemic approach, which transversally involves the entire supply chain [18].

The companies were selected based on the above criteria through the Bancomail database, which allowed for identifying the companies operating in the sectors relevant to the study. This approach facilitated the selection of companies involved in the production and packaging phases of fabrics, as well as in the production of leather, in line with the objective of analyzing the sectors with the greatest environmental and social impact, as described above. Through the database, according to the above criteria, 6179 Italian companies were identified. The classification of the companies in the database, based on their specialization activities, is shown in

Table 8. Database companies by ATECO code.

Activity	Total
Clothing—Production and Wholesale	1098
Clothing Accessories—Production	225
Underwear—Production and Wholesale	178
Clothing, Leather, and Leather Goods—Production and Wholesale	250
Linen—Production and Wholesale	790
Bags and Suitcases—Production and Wholesale	89
Footwear—Production	1220
Tanneries and Leather and Leather Production	549
Knitwear—Production and Wholesale	289
Sports Equipment and Clothing—Production and Wholesale	230
Fabrics—Production and Wholesale	1116
Fabrics—Treatments	145

.

While

Table 9. Database companies by geographical origin.

Region	Total
Campania	537
Emilia-Romagna	630
Lombardia	1787
Marche	579
Puglia	361
Toscana	1253
Veneto	1032

shows the classification of the companies in the database, based on the region they belong to.

3.2.2. Step#2.2: Selection of the Sample for the Survey

The survey was conducted using Microsoft Forms and was available in both Italian and English ensuring that all participants, regardless of their language proficiency, could fully engage with the content and provide accurate responses.

The decision to use a digital channel for survey distribution brings multiple advantages, primarily in terms of speed and convenience. One of the most significant advantages of using an online survey is the automatic data collection and organization. Responses are automatically recorded in a database, reducing the need for manual data entry. This automation not only minimizes human error but also accelerates the data processing phase, allowing for more efficient analysis and decision-making. With built-in analysis tools, the responses can be organized into digestible formats such as charts and graphs, which can be readily reviewed and interpreted. Additionally, digital surveys enable real-time monitoring, allowing researchers to track response rates, detect trends as they emerge, and make adjustments as needed during the data collection phase. Finally, opting for digital distribution aligns with environmental sustainability goals. As the survey was conducted entirely online, there was a significant reduction in the use of paper and other physical resources.

3.2.3. Step#2.3: Design the Survey

The procedure for constructing the questionnaire was structured in several phases to ensure the validity and reliability of the data collected.

Following the Document Review, a preliminary list of questions was drafted. The focus of the questions was on understanding the sustainability practices and circular economy strategies implemented by textile companies. The questions were designed to assess how companies address key sustainability aspects, such as the use of sustainable materials, recycling efforts, waste management, and adherence to environmental regulations. This phase aimed to create a comprehensive overview of the sustainability efforts within the sector. To ensure the appropriateness and clarity of the questions, the preliminary list was submitted to a panel of experts. This group consisted of academics and researchers with expertise in sustainability within the textile sector. The experts evaluated the relevance of the questions in relation to the research objectives and assessed their clarity and comprehensibility. Based on their feedback, several questions were revised, removed, or added to improve the overall quality and focus of the questionnaire.

This rigorous procedure allowed us to develop a well-structured questionnaire capable of gathering accurate and relevant data, essential for analyzing sustainability practices in the Italian textile sector.

The survey consists of 18 closed-ended questions, including multiple choice and yes/no answers, as shown in Appendix A. This question format was chosen to ensure uniform data, making it easier to analyze, compare, and interpret. Closed answers, in fact, allow for more efficient management of the information collected, as they simplify the coding and analysis process. Furthermore, they are more streamlined both for respondents, who can answer quickly, and for researchers, who benefit from a faster and more precise data analysis, facilitating comparison between responses [31].

The survey was designed with a modular structure and organized into two main sections:

• Section#1. General information. The first part of the questionnaire, which goes from questions 1 to 11, collects general information, mainly about the company and its employees. These questions aim to provide a basic picture of the structure and context in which the company operates.
• Section#2. Sustainability and circularity. The second part, from questions 12 to 18, focuses on the issues of sustainability and circularity, exploring corporate practices in these areas and the degree of awareness and implementation of sustainable strategies within the organization.

The selection of each question in the survey was carefully designed to assess the sustainability practices and circular economy strategies adopted by companies in the textile sector.

Table 10. Rationale for the questions choices.

Section	Question	Rationale for the Choice
Section 1: General Information	Type of the company	Identifies the company’s legal structure, which influences its financial capacity and ability to adopt sustainability practices.
	Identification within the textile supply chain	Helps understand the company’s role in the supply chain, impacting their ability to contribute to sustainable practices.
	Region of the company	Provides insights into regional factors affecting sustainability practices, such as local regulations and resources.
	Company’s ATECO code	Identifies the specific industry sector, aiding in understanding the company’s alignment with textile sector sustainability practices.
	Company size	Larger companies often have more resources to implement sustainability, while smaller ones might face barriers due to limited resources.
	Staff composition	Reflects labor-related sustainability practices, including fair wages, inclusivity, and equal opportunities.
	Staff demographics	Reveals insights into workforce training needs and generational perspectives on sustainability practices.
	Educational qualifications of the staff	Indicates the expertise within the company to execute complex sustainability strategies and practices.
	Disabled employees	Measures the inclusivity of the company in terms of providing equal opportunities for disabled workers, an important aspect of social sustainability.
	Percentage of women in the staff	Gender diversity is crucial for inclusive workplaces. Higher female representation could indicate a focus on gender equality.
	Percentage of women who are mothers	Assesses support for working mothers, linking to social sustainability practices and family-friendly policies.
Section 2: Sustainability and Circularity	Sustainability certifications or standards	Reflects the company’s adherence to recognized sustainability standards, highlighting their commitment to environmental and social sustainability.
	Use of renewable energy	Directly measures efforts in reducing carbon emissions by transitioning to renewable energy sources.
	Water recycling and reuse	Helps determine if the company is managing one of the most critical resources in textile manufacturing (water) and reducing waste.
	Waste management and minimization practices	Measures efforts in minimizing waste and reusing materials, a key practice in circular economy models.
	Emission and pollutant reduction practices	Assesses commitment to reducing environmental pollutants.
	Barriers to implementing sustainable practices	Identifies challenges faced by companies in adopting sustainable practices, helping to understand the barriers that need to be addressed.
	Services necessary to increase circularity and sustainability	Guides policymakers and service providers on the type of support companies need to improve their sustainability practices

shows the rationale for the questions choices:

Each of these questions, along with the corresponding answer choices, has been chosen to give an in-depth understanding of the sustainability efforts and barriers within the companies. By asking about certifications, workforce composition, emissions, waste management, and the support services needed, the survey aims to capture a comprehensive picture of both the practices and the challenges faced by companies in the textile sector when it comes to sustainability and circularity.

The aim of the questionnaire was to explore the challenges faced by companies in adopting circular solutions, as well as to identify the perceived opportunities for development and innovation in the future.

3.2.4. Step#2.4: Distribute the Survey and Collect the Answer

Once the survey channel is identified, distributing the survey and collecting the responses is streamlined using online survey tools. By opting for digital distribution, the survey responses can be gathered in real time, allowing for immediate data entry without delays caused by physical shipping or manual processing. Moreover, online access enables recipients to participate in the survey at their convenience, regardless of location or time zone. This flexibility makes it easier for people who are geographically distant, have busy schedules, or work irregular hours to take part in the survey without needing to be present physically. Furthermore, digital channels ensure wide reach, allowing the survey to be distributed to a larger number of participants without geographical constraints, which is essential for collecting a diverse set of responses across various sectors of the textile industry. From a cost perspective, digital distribution significantly reduces expenses. Traditional survey methods, such as printing paper questionnaires and mailing physical copies, can be expensive due to printing, postage, and handling costs. By using an online platform, these costs are eliminated, making digital surveys a more economical solution [32]. The questionnaire was sent to all companies identified through the Bancomail database. This approach resulted in a 75% response rate, ensuring statistical robustness to the collected dataset.

3.3. Phase#3: Analysis

The collected data were subjected to rigorous quantitative and qualitative analysis, using scientific techniques to ensure reliable and interpretable results. Survey responses are completely anonymous, as no company names are requested. Special care has been taken to ensure the privacy and confidentiality of the information provided.

3.3.1. Step#3.1: Conduct an Analysis to Receive an Overview of the Survey Results

Descriptive analysis played a fundamental role in this process, as it allowed us to map the current state of business practices in the sector and identify the main challenges. Using graphs and diagrams, it was possible to communicate in a clear and visual way the information extracted from the dataset. Descriptive analysis, in fact, provides a detailed overview of the structure and properties of the collected data, allowing us to photograph the reality of the observed phenomena [33]. In this way, it was possible to obtain a clear and synthetic portrait of the main characteristics, facilitating the understanding of emerging trends and issues to be addressed. This analysis was carried out for all the questions of the questionnaire, ensuring a comprehensive and detailed view of the responses obtained.

3.3.2. Step#3.2: Processing Data Using Statistical Tool

For the section on sustainability, a more in-depth statistical analysis was applied using the chi-square test. The test was used to verify the possible existence of significant associations between the geographical location of the companies and the adoption of sustainable practices, with the aim of determining whether the observed differences were statistically significant or due to chance [34].

Since the survey responses were categorical in nature, the chi-square test was deemed the most appropriate statistical method for analyzing the distribution of these variables. This test allows for the evaluation of potential associations between categorical variables, specifically assessing whether the frequency of responses differs in relation to the geographical location of the companies. The chi-square test is particularly well suited for examining the relationships between discrete events, such as the number of companies adopting sustainability practices, as it compares the observed distribution of responses to what would be expected under the null hypothesis of independence [35]. By applying this test, it is possible to observe variations in sustainability practices across regions are statistically significant, thereby providing insights into the influence of geographical factors on corporate sustainability behavior.

The process considered the following considerations:

• Formulation of hypotheses. The null hypothesis states that there is no relationship between the variables, while the alternative hypothesis suggests that there is a significant relationship.
• Level of significance. The test is conducted with a significance level of 5% (0.05), which indicates the acceptable probability of error in rejecting the null hypothesis;
• Organization of data: The data are presented in a contingency table, which shows the distribution of the variables being tested.
• Calculation of expected frequencies: Under the null hypothesis, the expected frequencies for each cell in the table are calculated, based on the overall proportions.
• Calculating the chi-square. The chi-square value is calculated by comparing the observed frequencies with the expected frequencies, using the formula (Equation (1)):

$$x^2=\sum {\displaystyle \frac{{\left(Oi-Ei\right)}^2}{Ei}}$$

(1)

where

Oi: Observed frequency for each category.

E_i: Expected frequency, calculated as (R_i ·C_j)/N in which R_i is the sum of the rows, C_j the sum of the columns, and e N is the grand total.

• The degrees of freedom are calculated as defined in Equation (2):

Df = (r − 1)(c − 1)

(2)

where r is the number of rows and c is the number of columns in the contingency table.

The calculated χ² value is compared against a critical value from the chi-square distribution table at a chosen significance level (α = 0.05). If the calculated value exceeds the critical value, the null hypothesis (H0)—stating no association between variables—is rejected.

The significant relationships identified through the chi-square test provide actionable insights, guiding regional policies to target specific barriers and promote sustainable practices more effectively.

6.

Comparing with the critical value. The calculated value is compared with the tabulated value. If the calculated chi-square is greater than the critical value, the null hypothesis is rejected, indicating a significant relationship between the variables. If it is less, the null hypothesis is accepted, indicating that there is no significant relationship. In this case, the chi-square test on proportions was used to verify the presence of a relationship between the geographical location of the companies and the adoption of sustainability practices.

3.3.3. Step#3.3: Summarize Key Findings

After the descriptive and chi-square analysis, the key findings were identified and explored. These included the following:

• Significant associations between categorical variables;
• Emerging trends and patterns;
• Areas for improvement and issues to address.

These key findings provided valuable insights into the dynamics revealed by the dataset and helped pinpoint areas to focus on. In particular, the chi-square analysis highlighted significant associations between categorical variables, uncovering crucial aspects that might not have been evident through simple observation. Once identified, the key findings were analyzed in detail to understand their impact. The correlations between variables were examined to uncover emerging trends and explore any hidden patterns that could influence future decisions. The key findings were then synthesized into a clear overview of the main conclusions, enabling the identification of issues to address, areas for improvement, and guiding the formulation of strategic recommendations.

4. Results and Discussion on the Survey

4.1. Analysis of the Main Results of the Survey

The survey results cover significant aspects of business practices in the textile sector, offering insights into how companies are approaching the transition to a circular economy model. Below is the analysis of the results based on economic, social, and technological theories related to the circular economy.

Type of Company and Circular Business Models. The prevalence of limited liability companies (54%) and limited partnerships (13%) in the Italian textile sector (see Figure 2) underscores the dominance of small- and medium-sized enterprises (SMEs), which is a hallmark of Italian industrial districts.

The high concentration of micro-enterprises and small businesses (88%) is shown in Figure 3.

The prevalence of SMEs offers flexibility but also presents obstacles, mainly related to limited financial resources for investing in advanced technologies. As noted in circular economy theory, SMEs are more agile and can more rapidly adopt innovative solutions, but they also face significant barriers due to high upfront costs for adopting circular practices, such as material recycling or green technologies. These financial challenges limit their ability to scale up circular models [36]. The main challenges identified are listed in

Table 11. Challenges and focus related to type of company.

Main Challenges	Focus
Financial barriers (high initial costs)	Limited access to capital and investment in green technologies
Access to advanced technologies	Need for support to adopt local circular models

.

Supply chain and stakeholders. The results show that 71% of stakeholders are textile/clothing producers, followed by fiber/yarn producers (6%) and other figures such as distributors (7%) and raw material suppliers (10%), as shown in Figure 4. This suggests that production occupies a central position in the textile value chain.

The central role of textile producers in the value chain suggests that efforts to optimize production processes should be prioritized. According to circular economy theories, to successfully implement circular models, it is essential to rethink the entire value chain, not just individual production stages [37]. Thus, focusing on fiber recycling, reducing resource consumption, and integrating sustainable materials across the supply chain is key to enhancing circularity. The main challenges related to the supply chain are shown in

Table 12. Challenges and focus related to stakeholders.

Main Challenges	Focus
Optimizing production processes	Adoption of technologies for fiber recycling
Supply chain traceability	Need for systems to monitor the entire production cycle

.

Location of Companies. The textile companies are primarily located in the north (30% in Lombardy), followed by a good representation in central Italy and a smaller presence in the south (see Figure 5).

This may reflect the industrial structure of the country, where northern Italy has a well-established textile tradition and greater availability of technological resources. Circular economy in industrialized regions has greater opportunities for take-off, due to access to advanced technologies, recycling infrastructure, and a higher level of competition that stimulates the adoption of circular practices. However, even in southern Italy, where the adoption of sustainable practices might be slower, introducing support initiatives and incentives for SMEs could help spread green practices (see

Table 13. Challenges and focus related to location.

Main Challenges	Focus
Delay in southern regions	Encouraging the adoption of circular practices in southern Italy through targeted policies

).

Workforce Composition and Social Inclusion. The data, showing that 74.3% of workers are from the same region and that a large portion of the workforce is aged 34 to 64 years (see Figure 6), indicates a strong reliance on experienced, local labor in the Italian textile sector.

This composition reflects the sector’s reliance on traditional craftsmanship. However, the data also suggest that this demographic may limit the influx of younger professionals who are crucial for driving the integration of digital technologies and sustainability practices into the sector. As suggested in circular economy theories, involving younger talent is essential to foster innovation and accelerate the transition to circular business models [38].

Additionally, the high female workforce participation (68% in many companies) and the inclusion of disabled workers (see Figure 7) reflect the industry’s growing commitment to social inclusivity.

This aligns with circular economy principles, promoting not only environmental sustainability but also social responsibility. Fostering a diverse and inclusive workforce helps the sector remain adaptable and ensures that sustainable practices are widely embraced. The social challenges highlighted are listed in

Table 14. Challenges and focus related to workforce characteristics.

Main Challenges	Focus
Lack of generational turnover	Need to attract younger talent to drive innovation
Social inclusion and equal opportunity	Continuing to promote inclusivity

.

Sustainability Certifications and Transparency. The data reveal that 57% of companies in the Italian textile sector have at least one sustainability certification, with common certifications including OEKO-TEX [39], GOTS [40], and GRS [41], as shown in Figure 8.

The most common certifications, such as OEKO-TEX, GOTS, and GRS, are undoubtedly positive indicators of companies’ commitment to sustainability:

• OEKO-TEX primarily focuses on the safety of textile products, ensuring they are free from harmful chemicals. This is an essential step in protecting consumer health and reducing chemical pollution.
• GOTS (Global Organic Textile Standard) certifies products made from organic fibers, but also includes strict environmental and social criteria throughout the production chain. This represents a significant commitment to environmental and worker rights.
• GRS (Global Recycle Standard) focuses on the use of recycled materials in the production process, promoting waste reduction and the use of existing resources.

This indicates that many companies are adopting specific eco-friendly practices but are not yet fully embracing a comprehensive circular business model. These initiatives are often limited to specific practices that are not sufficient to ensure a lasting positive impact on the overall system. In many cases, companies

• Do not integrate sustainability across all stages of the product life cycle;
• Focus more on reducing direct environmental impacts during production, without considering the end-of-life of products or interactions with other stages in the supply chain.

For instance, companies using recycled or natural materials do not have systems in place for post-consumer recycling, which limits their ability to truly reduce textile waste.

Circular economy theories emphasize the need for a holistic approach that integrates circular practices across all production stages, rather than isolated sustainable actions. The main challenges related to certifications are shown in

Table 15. Challenges and focus related to sustainability certifications.

Main Challenges	Focus
Fragmented approach to sustainable practices	Integrating circular models across the entire production process
Diversity in certifications	Creating common standards for sustainability practices

.

Technologies for Sustainability. Technologies for sustainability are a crucial pillar for the transition to a circular economy, but the data highlight that the Italian textile sector is still adopting such technologies in a limited way. Only 40% of the companies surveyed use renewable energy, a positive figure, but it indicates that most businesses have not yet fully integrated clean energy into their operations. Similarly, only 14% have adopted water recycling systems, another essential aspect to reduce environmental impact, suggesting that there is still significant room for growth in this area.

Although a significant portion of companies (27%) has implemented optimization practices such as reducing the use of water and chemicals, which represent more immediate and lower-cost approaches, the adoption of closed-loop systems for water and chemical reuse remains marginal, with only 4% of companies applying this practice (see Figure 9).

The data highlight a significant gap in the adoption of advanced technologies, such as closed-loop recycling systems, which are crucial for reducing environmental impact and promoting a fully circular production process. Technological innovation theories in the context of the circular economy suggest that the transition to a circular model requires a strong commitment to research and development (R&D) [39]. However, these investments are difficult for small companies to sustain, as they are limited by financial and infrastructural resources. To support companies in this innovation process, targeted public policies are necessary to encourage investment in R&D through funding, subsidies, and tax incentives, which can make the adoption of sustainable technologies more accessible (see

Table 16. Challenges and focus related to sustainability technologies.

Main Challenges	Focus
Limited adoption of advanced technologies	Encouraging the use of green technologies through funding and public support
High implementation costs	Overcoming economic barriers through incentives and R&D support

).

Barriers and needs for circularity. The adoption of circular economy models in Italian SMEs is hindered by a series of barriers, as shown in Figure 10, that prevent a smooth transition to more sustainable practices.

Financial barriers, which account for 20% of responses, are among the main difficulties highlighted by companies. The high upfront costs required to implement advanced technologies and circular processes limit SMEs’ ability to adopt these models on a large scale. Organizational barriers (17%) are another significant obstacle. Barriers related to market demand (13%) also emerge as a limiting factor.

To overcome these barriers, companies have identified several needs (see Figure 11), such as sustainability training (23%) and the introduction of traceability systems (21%).

Circular economy theories suggest that a collaborative approach between businesses, research entities, and governments could facilitate the removal of these obstacles [40]. The creation of supportive policies that encourage the adoption of sustainable practices, through tax incentives, research funds, or promoting synergies between different companies, would be fundamental to accelerating the transition to a more circular and sustainable business model.

4.2. Detailed Analysis of the Survey Using Chi-Square Analysis

In this section, we report the results of the chi-square analysis conducted to verify whether there was a significant relationship between the geographical location of companies and the sustainable practices adopted. The test was performed on the questions belonging to the second section, from questions 12 to 18.

Question 12. For this question the hypothesis is as follows: There is a significant relationship between the geographical location of companies and the possession of sustainability certifications and standards.

The contingency and expected frequencies table (

Table 17. Contingency and expected frequencies table—question 12.

Location	With Certifications	With Certifications (Expected)	Without Certifications	Without Certifications (Expected)
Northern Italy	0.70	0.4028	0.30	0.0972
Central Italy	0.92	0.2256	0.08	0.0543
Southern Italy	0.90	0.1772	0.10	0.0427

) shows the percentage of companies that have sustainability certifications based on the geographical area (northern, central, and southern Italy) and the expected values for each cell were then calculated, using these general proportions.

The chi-square calculated, according to Equation (1), was 5.808. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was smaller than the chi-square critical value at 5.99. Thus, we cannot accept the hypothesis. Therefore, there is no significant relationship between the geographical location of companies (north, center, south Italy) and the possession of sustainability certifications.

Question 13. For the chi-square analysis on proportions, the comparison between the proportions of companies that have adopted renewable energy, divided by geographical was considered. The hypothesis is as follows: There is a significant relationship between the geographical location of companies and the use of renewable energy. The analysis focused on the proportions of companies that use renewable energy in the different regions. The proportions of companies that use renewable energy are classified and the expected frequencies are then calculated and shown in

Table 18. Contingency and expected frequencies table—question 13.

Location	Yes (Renewable Energy)	Yes (Renewable Energy) (Expected)	No (Renewable Energy)	No (Renewable Energy) (Expected)
Northern Italy	0.34	0.20844	0.66	0.33156
Central Italy	0.44	0.08878	0.56	0.14122
Southern Italy	0.44	0.08878	0.56	0.14122

.

The chi-square calculated, according to Equation (1), was 5.67. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was smaller than the chi-square critical value at 5.99. This means that there is no significant relationship between the geographical location of companies and the use of renewable energy.

Question 14. The same procedure already performed for question 13 was carried out. The hypothesis for question 14 is as follows: There is a significant relationship between the geographical location of companies and the adoption of water reuse or repurposing systems.

The proportions of companies using water reuse or reuse systems are as follows:

• Northern Italy: 18%.
• Central Italy: 13%.
• Southern Italy: 0%.

The proportions of companies that use water reuse systems and the expected frequencies are shown in

Table 19. Contingency and expected frequencies table—question 14.

Location	Yes (Water Reuse)	Yes (Water Reuse) (Expected)	No (Water Reuse)	No (Water Reuse) (Expected)
Northern Italy	0.18	0.0685	0.82	0.4715
Central Italy	0.13	0.0292	0.87	0.2008
Southern Italy	0.00	0.0292	1.00	0.2008

.

The chi-square calculated was 6.226. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was greater than the chi-square critical value at 5.99. Thus, we cannot accept the hypothesis. This implies that there is a significant relationship between the geographical location of companies and the adoption of water reuse or repurposing systems.

Question 15. To analyze the relationship between the geographical location of textile companies and sustainable practices to manage and reduce waste during the processing of textile fibers (such as minimization, recycling, use, composting, and disposal), we can apply the chi-square test. The hypothesis is as follows: There is a significant relationship between the geographical location of textile companies and the sustainable practices adopted for waste management and reduction.

The percentage of companies that adopt each of the five sustainable practices in the different geographical areas and the respective expected values are shown in

Table 20. Contingency and expected frequencies table—question 15.

Practice	North	North (Expected)	Center	Center (Expected)	South	South (Expected)
Minimizing water usage in dyeing and finishing processes	0.58	0.31	0.32	0.07	0.11	0.03
Recycling leftover fibers or scraps for reuse	0.58	0.31	0.16	0.04	0.26	0.06
Utilizing pre-colored fibers to eliminate dyeing altogether	0.67	0.36	0.00	0.00	0.33	0.08
Composting organic waste like cotton seeds	0.00	0.00	0.33	0.08	0.67	0.15
Disposing of excess chemicals down the drain	0.29	0.15	0.43	0.10	0.29	0.08

.

The chi-square calculated was 786.3. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was much greater than the chi-square critical value at 15.51. Thus, we cannot accept the hypothesis. There is a significant relationship between the geographical location of textile companies and the sustainable practices they adopt for waste management and reduction during textile fiber processing.

Question 16. For this question, the hypothesis is as follows: There is a significant relationship between the geographical location of textile companies and sustainable practices related to the reduction in emissions and pollutants in the textile sector. Data on the percentages of companies that have adopted sustainable practices and the expected frequencies, broken down by geographical area, are reported in

Table 21. Contingency and expected frequencies table—question 16.

Practice	North	North (Expected)	Center	Center (Expected)	South	South (Expected)
Optimizing processes to minimize water and chemical usage	0.53	0.29	0.27	0.06	0.20	0.05
Utilizing energy-efficient machinery in various stages of processing	0.57	0.31	0.21	0.05	0.21	0.05
Implementing waste heat recovery systems to capture and reuse heat generated during processes	0.80	0.43	0.20	0.05	0.00	0.00
Employing natural and biodegradable fibers	0.71	0.38	0.13	0.03	0.17	0.04
Adopting closed-loop systems for water and chemical reuse in dyeing and finishing	0.50	0.27	0.50	0.12	0.00	0.00
Utilizing pre-colored fibers to eliminate the dyeing process and associated pollutants	0.33	0.18	0.17	0.04	0.50	0.12
Investing in air filtration systems to capture and reduce harmful airborne emissions	0.50	0.27	0.00	0.00	0.50	0.12
Treating wastewater	0.42	0.23	0.25	0.06	0.33	0.08

.

The chi-square calculated was 1215.08. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was much greater than the chi-square critical value at 23.685. Since the calculated chi-square was much larger than the critical value, we can conclude that there is a significant relationship between the geographical location of companies and sustainable practices to reduce emissions and pollutants in the textile sector.

Question 17. To apply the chi-square analysis, the hypothesis is as follows: There is a significant relationship between the geographical location of companies and the barriers they encounter to implement sustainability and circular economy practices. The percentages of companies that selected each barrier (Organizational, Supply chain, Financial, Technological, Market related, Customer driven, Governmental, Other) and the expected frequencies for each geographical area are reported in

Table 22. Contingency and expected frequencies table—question 17.

Barrier	North	North (Expected)	Center	Center (Expected)	South	South (Expected)
Organizational	0.46	0.25	0.21	0.05	0.32	0.07
Supply chain	0.53	0.29	0.21	0.05	0.26	0.06
Financial	0.57	0.31	0.07	0.02	0.36	0.08
Technological	0.30	0.16	0.10	0.02	0.60	0.14
Market related	0.55	0.30	0.15	0.03	0.30	0.07
Customer driven	0.53	0.29	0.32	0.07	0.16	0.04
Governmental	0.60	0.32	0.10	0.02	0.30	0.07
Other	0.75	0.40	0.25	0.06	0.00	0.00

.

The chi-square calculated was 10.24. The hypothesis was tested at 5% level of significance. Since 10.2409 is less than the critical value, in this case 23.685, we cannot accept the hypothesis. This means that there is no statistical evidence of a significant relationship between the geographical location of companies and the barriers they face in implementing sustainability practices.

Question 18. In relation to this question, the hypothesis that was made is as follows: There is a significant relationship between the geographical location of companies and services that companies think are necessary to increase circularity and sustainability. In

Table 23. Contingency and expected frequencies table—question 18.

Services	North	North (Expected)	Center	Center (Expected)	South	South (Expected)
LCA analysis support service	0.50	0.27	0.21	0.05	0.29	0.07
Ecodesign support service	0.50	0.27	0.11	0.02	0.39	0.09
Integration of traceability systems	0.55	0.30	0.20	0.05	0.25	0.06
Advanced services related to freight logistics	0.80	0.43	0.00	0.00	0.20	0.05
Digitalization support services	0.54	0.29	0.23	0.05	0.23	0.05
Training services on the management of processes	0.48	0.26	0.24	0.05	0.28	0.06
Other	0.60	0.32	0.40	0.09	0.00	0.00

, the proportion of the companies based on the geographical area they belong to and the expected frequencies for each service are reported.

The chi-square calculated, according to the formula, was 8.343. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was smaller than the chi-square critical value 21.026. This means that there is no significant relationship between the geographical location of companies and services that companies think are necessary to increase circularity and sustainability.

The results of the survey provide a comprehensive overview of the current state of sustainability practices in the Italian textile sector, highlighting both the advancements and challenges faced by companies. The key aspects identified in the survey offer valuable insights into the most commonly adopted sustainable practices, the barriers hindering broader adoption, and the specific needs of companies in terms of services and support. Additionally, the survey sheds light on regional differences, emphasizing the role of national policies in reducing geographical disparities.

Table 24. Key findings from the survey.

Key Area	Findings
Most Common Sustainability Practices	Recycling of fibers (57%) Use of renewable energy (40%)
Least Adopted Practices	Water reuse systems (14%) Closed-loop chemical systems (4%)
Main Barriers	Financial barriers (20%) Organizational barriers (17%) Market demand-related barriers (13%)
Demand for Services	Sustainability training (23%) Traceability systems (21%) Ecodesign (17%)
Regional Differences	Significant differences in sustainability practices across regions
Importance of National Policies	Supportive policies to reduce regional disparities and promote the adoption of circular practices

summarizes the most relevant findings from the survey, offering a detailed snapshot of the sector’s efforts towards circularity and sustainability.

This study provides an updated and detailed overview of sustainability practices in the Italian textile sector, significantly contributing to the academic debate on the application of the circular economy in this field. The collected information reveals how companies are addressing the adoption of circular models, highlighting not only the progress made but also the challenges that remain, such as the limited adoption of advanced technologies and economic and organizational difficulties. In this way, the work enriches the academic discussion, offering new insights into sustainable practices in the textile sector. The manuscript also proves to be an important resource for guiding political and industrial decisions. The collected data can be used to create targeted policies that support businesses in the transition to a circular economy, with tax incentives and financial support that could alleviate the economic difficulties faced by small- and medium-sized enterprises. The policies suggested by the study could help overcome the main barriers, such as the high costs of sustainable technologies and the lack of market demand for sustainable products, thus promoting a wider adoption of green practices in the textile sector. The contribution of this study extends to strengthening the dialogue between the scientific community and the industrial sector. By identifying the main needs of businesses, such as sustainability training and the introduction of traceability systems, the study fosters collaboration between researchers, companies, and institutions, which is essential for developing practical and applicable solutions. This dialogue is fundamental for promoting innovation and improving sustainability practices, thus accelerating the transition to a circular economic model in the textile sector.

4.3. Main Considerations on the Results

The survey results provide a detailed overview of sustainability practices in the Italian textile sector, highlighting both progress and existing challenges. In particular, the survey pointed out that 57% of companies adopt fiber recycling practices, and 40% have implemented renewable energy solutions. However, only 14% have adopted water reuse systems, and a mere 4% utilize closed-loop chemical systems, highlighting significant opportunities for improvement in advanced technologies. To accelerate adoption, businesses can focus on less costly practices, such as material reuse and energy optimization.

A notable 23% of companies express the need for sustainability training, while 21% demand tools for supply chain traceability. These figures reflect a growing awareness of the importance of digital tools for transparency. Technologies like blockchain, digital product passports, and automated sorting can significantly improve traceability and waste management. Blockchain provides a transparent and immutable record of sustainability practices across the supply chain, ensuring credibility and minimizing the risk of greenwashing. Digital product passports offer consumers and businesses access to crucial product data, such as sourcing, material composition, and recycling instructions, which promote circularity. Automated sorting technologies, using AI and machine learning, enhance the efficiency of textile waste management, making recycling processes faster, more accurate, and more scalable.

The main barriers identified include financial constraints (20%) and organizational challenges (17%), with a clear disparity between northern and southern Italy. Companies in the northern regions have better access to advanced technologies, while those in the south could benefit from targeted incentives and financial support to bridge this gap. The limited adoption of advanced technologies, such as water reuse systems (14%), underscores the need for modular and scalable solutions tailored to small- and medium-sized enterprises. Real-time monitoring systems and digital platforms for life cycle assessment could assist businesses in identifying inefficiencies and defining more effective strategies.

Although 57% of companies possess sustainability certifications, the application of circular economy models remains fragmented. Integrating circular practices throughout the production process is essential to meet global demand for sustainable products and comply with increasingly stringent environmental regulations. Italian textile companies must expand their sustainability efforts to maintain competitiveness in the global market. Addressing regional disparities, policymakers should offer incentives to less industrialized areas, enabling companies to access necessary technologies and resources.

To advance sustainability in the sector, businesses should focus on adopting scalable, cost-effective solutions such as material reuse and energy optimization. Investing in training and digital tools for traceability is crucial to enhance transparency and credibility. Adopting technologies like blockchain, digital product passports, and automated sorting can streamline the process of managing waste and materials, making it easier for businesses to operate sustainably and meet global sustainability standards. Encouraging regional collaboration and implementing public policies that promote knowledge sharing and innovation will further accelerate the adoption of circular economy practices. By fostering collaboration, innovation, and targeted investments, companies can enhance their sustainability efforts and strengthen their global market position. This revised analysis provides actionable insights to guide future strategies in research, policy, and business practices, contributing to the ongoing transition towards a circular economy in the textile sector.

The regional differences in circular economy adoption, particularly between northern and southern Italy, suggest that national policies are needed to promote a more uniform approach. Policymakers should focus on providing incentives for SMEs in less industrialized regions to help them access the necessary technologies and resources. Such initiatives will strengthen the competitiveness of the Italian textile sector on the global stage.

Based on the survey results, the following recommendations can help improve sustainability within the Italian textile sector:

• Invest in scalable, cost-effective solutions. Companies should focus on adopting practices that are both affordable and scalable. Starting with smaller, manageable initiatives such as material reuse and process optimization will help mitigate financial risks while improving sustainability.
• Prioritize training and knowledge development. Given the demand for sustainability training and traceability systems, companies should invest in upskilling their workforce and collaborate with research institutions to develop expertise in sustainability practices. This will enhance their ability to implement circular models and meet the growing consumer demand for transparency.
• Increase supply chain transparency. The implementation of digital traceability tools will not only improve sustainability reporting but also enhance the credibility of companies’ sustainability claims. Integrating these systems across supply chains will help companies meet consumer expectations for sustainable products and improve operational efficiency.
• Encourage regional collaboration. SMEs, particularly those in regions with limited access to advanced technologies, should collaborate with other businesses, universities, and industry clusters to share knowledge, resources, and best practices. Public policies should incentivize these collaborations to facilitate the widespread adoption of circular economy practices.

The findings from this study serve an important resource for guiding future research, policy development, and business practices, contributing to the ongoing transition to a circular economy in the textile sector.

4.4. Highlight from the Survey

This survey offers valuable insights into the sustainability practices of Italian textile companies; however, several limitations must be taken into consideration. First, the sample primarily consisted of micro and small enterprises, which restricts the generalizability of the findings to larger companies that possess different resources and organizational structures. Additionally, there was a geographical bias, as most of the participating companies were in northern and central Italy. This regional concentration might not adequately represent the practices prevalent in southern Italy, where industrial infrastructure and conditions differ significantly.

Another notable limitation arises from the reliance on self-reported data in the survey. This method introduces the potential for response bias, including the possibility of overreporting sustainability practices. Furthermore, the scope of the study was primarily focused on environmental sustainability, offering only limited consideration of social and economic dimensions of sustainability. Lastly, the cross-sectional nature of the research presents another constraint, as it provides a snapshot of sustainability practices at a single point in time, thus limits the ability to analyze long-term trends in the sector.

It is important to keep these limitations in mind when interpreting the study’s results.

However, despite the limitations mentioned above, the results from the survey provide an important foundation for developing more targeted and effective strategies to promote sustainability in the Italian textile sector. To address some of the identified challenges, such as the need for continuous monitoring and a more comprehensive view of the data, the introduction of an operational model based on a real-time sustainability monitoring dashboard is proposed. This tool, using real-time data, would allow companies to have a more accurate and dynamic view of their progress towards sustainability goals, reducing the risk of errors from self-reported data and enabling more strategic resource management.

5. Proposed Operational Model: Real-Time Sustainability Monitoring Dashboard

Based on the results obtained, it is clear that for many companies in the textile sector it is important to measure and track the effectiveness of their sustainable practices. To address this challenge, we propose an operational model that we called GENIUS “A GrEen Network for an Integrated bUsiness Strategy to monitor sustainability measures”. It is based on an interactive dashboard designed to help companies monitor their sustainability performance in real time. Thus, the aim of the model is to monitor energy and material flows to measure sustainability/circularity through a digital platform in which all “actors” (from producer to consumer) involved in the textile supply chain are linked together to reduce the carbon water footprint and to define specific strategy (i.e., carbon sequestration). A simplified scheme is shown in Figure 12.

5.1. Model Structuring

The operating model focuses on the continuous monitoring of key sustainability indicators, including water and carbon footprints. Through a system based on big data and predictive analytics, the dashboard will provide critical information to support strategic decisions along the supply chain. In addition, the model will promote a collaborative approach, involving all actors in the textile supply chain, including producers, distributors, and consumers. Using technologies such as blockchain to track and authenticate data, transparency will be guaranteed throughout the product life cycle.

To create an effective real-time sustainability monitoring dashboard, a structured process must be followed, which consists of three main features:

• F#1. Defining sustainability indicators.
• F#2. Data collection and management.
• F#3. Information visualization.

Each phase plays a crucial role in ensuring that the platform provides accurate and useful data to support informed decisions and promote sustainable business practices.

5.1.1. F#1: Defining Sustainability Indicators

The first phase of the process involves defining the sustainability indicators, a fundamental step in establishing the metrics to monitor. The indicators must be chosen strategically to accurately measure the environmental, social, and economic impacts of business operations. The indicators proposed for the dashboard were initially selected according to the principles outlined in ISO 14031:2013, the standard for Environmental Performance Evaluation (EPE). These guidelines provide a framework for choosing, classifying, and designing performance indicators. The results were then compared with the key indicators from the EU monitoring framework for the circular economy, published in 2018, which includes ten key indicators. Afterward, the indicators were further examined in light of those suggested by various researchers in scientific articles on the textile industry. This process allowed for the identification of the most appropriate indicators for the specific sector, ensuring a balanced approach that not only focused on environmental aspects but also encompassed social and economic dimensions.

Table 25. KPIs for each pillar of sustainability (environmental, social, and economic).

Pillar	KPI	Description	References
Environmental	CO2 emissions per unit of product	Measurement of greenhouse gas emissions per unit of product	[ISO 14031:2013, Bianchini et al. (2019)] [41,42]
	Liters of water consumed per unit of product	Water consumption per unit of product	[ISO 14031:2013, Luis Alves et al. (2023)] [9,41]
	Percentage of recycled materials	Percentage of recycled materials used in production	[ISO 14031:2013, Rossi et al.(2020)] [24,41,43]
Economic	Energy cost per unit of product	Energy consumption per unit of product	[ISO 14031:2013, Bianchini et al. (2019),Luis Alves et al. (2023)] [9,41,42]
	Percentage of turnover from sustainable products	Percentage of turnover generated by innovative and sustainable products	[ISO 14031:2013, Rossi et al. (2020)] [24,41]
Social	Percentage of suppliers with ethical standards	Percentage of suppliers that comply with ethical and social certifications	[ISO 14031:2013] [41]
	Training hours per employee per year	Number of hours spent training employees to improve skills	[Luis Alves et al. (2023)] [9]

shows a set of fundamental indicators for the textile sector, divided by each pillar of sustainability.

These indicators are relevant to the company’s sustainability goals and aligned with international standards, such as those established by the United Nations’ Agenda 2030 (see

Table 26. KPIs with the sustainable development goals.

Pillar	KPI	SDG/Justificative
Environmental	CO2 emissions per unit of product	SDG 13: Climate Action. Reducing greenhouse gas emissions is crucial for combating climate change and limiting global warming.
	Liters of water consumed per unit of product	SDG 6: Clean Water and Sanitation. Managing water resources sustainably is essential to ensure access to safe and sustainable drinking water for all.
	Percentage of recycled materials	SDG 12: Responsible Consumption and Production. Promoting the use of recycled materials reduces waste and environmental impact, contributing to more sustainable production.
Economic	Energy cost per unit of product	SDG 7: Affordable and Clean Energy. Optimizing energy use and reducing energy costs per product unit helps improve energy efficiency and reduce environmental impact.
	Percentage of turnover from sustainable products	SDG 8: Decent Work and Economic Growth. Increasing revenue from sustainable products supports inclusive and sustainable economic growth.
Social	Percentage of suppliers with ethical standards	SDG 12: Responsible Consumption and Production. Ensuring suppliers adhere to ethical standards is key to promoting responsible practices across the supply chain.
	Training hours per employee per year	SDG 4: Quality Education. Providing continuous training to employees promotes access to educational opportunities and fosters the development of skills necessary for decent work and inclusive growth.

).

KPIs are essential for identifying areas of success, detecting inefficiencies, and taking timely corrective actions. Furthermore, through KPIs, companies can assess the effective-ness of their initiatives, compare results with industry standards, and ensure that sustainability efforts align with long-term strategic objectives.

5.1.2. F#2: Data Collection and Management

The next phase, which is equally critical, is data collection and management. After defining the indicators, it is necessary to collect data related to each indicator in a systematic and structured manner. Data collection takes place through Business Analytics tools, such as Company Reports (CRs), which are digitized and stored in the company’s IT systems. These reports contain critical information about various aspects of sustainability, such as energy consumption, CO₂ emissions, waste management, and so on. The use of digital systems enables efficient data collection and storage in an easily accessible and updatable format.

Data management represents the next crucial step, where the collected data are organized, structured, and stored in SQL (Structured Query Language) databases. SQL is a standard used to manage and manipulate large volumes of data through structured tables, divided into rows and columns. This tabular format allows for simple and efficient data storage and querying, centralizing the information in a single system that facilitates access and consultation. Managing data in SQL systems also allows for processing the data so that they can be easily used for analysis and reporting. Data management can be carried out using simple tools offered by Microsoft 365, such as Azure, due to its ability to provide a scalable and secure platform for data storage and processing. Azure offers a wide range of services that support the integration and management of business data, allowing companies to store, analyze, and visualize data efficiently. Using Microsoft Azure enables companies to centralize information within a single ecosystem, facilitating access and management of resources without the need for complex solutions. Additionally, Azure offers high levels of security and compliance, ensuring that data are protected in line with global regulations, thus improving risk management.

5.1.3. F#3: Information Visualization

Once the data have been collected and managed, the next critical step is data visualization. This phase is essential because it allows stakeholders to interpret complex data in a more intuitive and actionable format. By transforming raw data into clear visual representations, companies can gain insights that are crucial for decision-making and performance evaluation.

Among the available visualization tools, Power BI is a highly effective option. Power BI as a Key Visualization Tool. Power BI by Microsoft is one of the most powerful and versatile tools for data visualization and business intelligence. It allows organizations to transform their raw, complex datasets into interactive and dynamic visual representations (see Figure 13). This facilitates deeper understanding and more informed decision-making across the business. Here is a more detailed description of how Power BI works and why it is particularly effective:

• Real-Time Data Updates. One of Power BI’s most powerful features is its ability to display real-time data. As new data are processed and uploaded into the system, it automatically updates the visualizations, ensuring that users always have the most up-to-date information at their fingertips.
• User-Friendly Visualizations. Power BI enables the creation of a wide variety of visualizations, making it highly flexible and adaptable to different business needs, such as tables, bar and column charts, line charts, maps, and pie charts.
• Advanced Analytical Features. Power BI also includes powerful analytical features that allow businesses to derive deeper insights from their data. Some of these include descriptive, predictive, and prescriptive analysis.
• Interactivity and Customization. Users can filter, drill down, or slice the data to obtain a more granular view of specific metrics. For example, a sustainability manager might want to filter the emissions data by department, time period, or region to evaluate specific areas of the business. Power BI also allows for extensive customization, meaning businesses can tailor the dashboards and reports to meet their specific needs.
• Collaboration and Sharing. Power BI enables seamless collaboration by allowing users to share reports and dashboards with team members or stakeholders. Reports can be published to the Power BI Service, making them accessible across devices, including smartphones and tablets. This means decision-makers can access real-time data and insights wherever they are, promoting more agile and responsive business operations.

Power BI is a powerful tool for businesses looking to transform raw data into valuable, actionable insights. Its ability to create real-time, interactive, and dynamic visualizations helps organizations make informed decisions, track performance, and optimize processes. With advanced analytical capabilities such as descriptive, predictive, and prescriptive analysis, Power BI empowers businesses to not only understand their past and present but also predict and optimize their future. This makes it an invaluable tool for monitoring sustainability metrics, improving operational performance, and driving business growth.

The real-time sustainability monitoring dashboard for the textile industry is a crucial tool for the sustainability of the textile sector, because it provides a robust, data-driven solution for companies aiming to monitor, assess, and enhance their sustainability initiatives. By tracking performance across environmental, social, and economic dimensions, the dashboard empowers textile businesses to make informed decisions, optimize their sustainability efforts, and gain a competitive edge in an increasingly eco-conscious market. This tool not only fosters continuous improvement but also ensures that companies can align their practices with industry standards, ultimately contributing to a more sustainable and responsible future for the textile sector.

6. Conclusions

This study highlights that the transition to a circular economy model in the Italian textile sector represents a significant yet essential challenge for ensuring a sustainable and competitive future. The circular economy, which aims to minimize resource waste and extend the life cycle of products, offers unique opportunities to reduce environmental impact, optimize the use of natural resources, and create new business models based on sustainability. The textile sector is one of the most resource-intensive in terms of natural resource consumption, waste generation, and CO₂ emissions. Therefore, adopting circular models is not only a responsible choice but also a fundamental strategy to address global challenges related to climate change and resource depletion.

The results of the survey highlight that, despite the structural challenges and limited resources of many companies, there is a growing commitment to adopting sustainable practices. Even smaller enterprises are beginning to embrace circular business models, such as recycling and reusing materials, improving energy efficiency, and using regenerated or biodegradable fibers. These approaches not only contribute to reducing environmental impact but also offer opportunities for innovation, fostering the creation of new products and services and improving long-term competitiveness. However, despite these advances, significant challenges remain, including waste management, large-scale adoption of advanced technologies, and the need to shift the entrepreneurial mindset towards long-term models rather than short-term practices.

The chi-square results indicate a significant relationship between the geographical location of companies and their adoption of sustainable practices, such as water recovery systems, waste reduction strategies, and efforts to minimize emissions and pollutants. This finding suggests that regional factors may influence the extent to which companies are able to implement these practices, emphasizing the need for targeted policy interventions that consider geographic and local contextual factors.

Based on these findings, practical recommendations for the industry include the need for stronger collaboration between small and large enterprises to overcome resource and technological limitations, as well as the promotion of policy incentives that support the adoption of sustainable practices across the entire supply chain. Companies should invest in the research and development of circular technologies, such as closed-loop systems and resource-efficient production methods, while also prioritizing transparency in their sustainability efforts. To support long-term monitoring, a monitoring platform has been proposed, which will facilitate continuous tracking and evaluation of sustainability practices, ensuring the ongoing improvement and adaptation of circular economy strategies.

Future research will address these limitations by exploring several key areas. International comparative studies will examine how sustainability practices vary across countries, revealing the influence of regional regulations, culture, and market dynamics on sustainability efforts. Longitudinal studies will assess how sustainability practices evolve over time, evaluating their long-term effectiveness and impact on environmental, social, and economic outcomes. Additionally, research into the adoption of advanced technologies, such as blockchain for supply chain transparency or closed-loop waste systems, will provide insights into their economic and environmental effects, helping companies improve sustainability and operational efficiency.