Agri-Food Supply Chain Sustainability Indicators from a Multi-Capital Perspective: A Systematic Review

Abstract

The concept of sustainability in agri-food supply chains (AFSCs) is gaining traction among researchers and practitioners. There has been a considerable effort to define and identify frameworks for assessing, monitoring, and improving sustainability practices within systems and organizations. The multi-capital approach presents an alternative tool for sustainability that integrates various types of capital to provide a deeper understanding and assessment of the impacts across different facets of the system. This review systematically examines existing research on AFSC sustainability indicators and assessment from a multi-capital perspective. Based on 106 articles, 116 indicators from various databases (Web of Science, Scopus, and others) are identified. These indicators are assigned to specific AFSC actors and forms of capital. Their role in evaluating the AFSCs through a sustainability lens is examined. The analysis also identifies the most significant capital associated with each actor. This analysis leads to the development of a structured framework that helps actors assess their resources and pinpoint sustainability challenges. Following this review, a theoretical framework is derived, connecting sustainability capital, key themes, and relevant Sustainable Development Goals. This provides a comprehensive tool for evaluating assets and guiding strategic actions for AFSC.

1. Introduction

The agri-food supply chain (AFSC) is essential for global food security; it involves numerous actors from farmers to consumers and comes with a range of socioeconomic and environmental challenges [1,2]. To address these challenges, there is a growing emphasis on enhancing the resilience and sustainability of the AFSCs [3]. Despite advancements in legislation and guidelines that enable stakeholders to adopt sustainable practices effectively, identifying the most appropriate metric for assessing the sustainability of specific activities remains a complex task. That is why numerous studies propose different frameworks and methodologies to define and categorize sustainability indicators [4,5,6]. The multi-capital sustainability approach (MCSA) is one of these methods [7]. This model has been influenced by significant developments, such as the IIRC’s 2013 Integrated Reporting Framework, which incorporates multi-capital principles, and the momentum of global sustainability movements [8]. To fully understand the challenges and opportunities of this approach, it is essential to clarify what “capital” means. It refers to “a stock or resource from which revenue or yield can be extracted”, [9]. It encompasses ‘resources and relationships’ [8], representing various essential assets for sustainable development. The MCSA incorporates different types of capital [10], each linked to the traditional pillars of sustainability to better understand and assess the nuanced impacts across various facets of the system [11]. Consistent with the Brundtland definition of sustainability, the MCSA emphasizes the well-being of current and future generations, which depends on the prudent use of material and non-material resources. This approach enables a comprehensive evaluation of sustainability performance by offering a detailed understanding of the interconnectedness and influences of different capital. It helps users identify weaknesses in their strategies and implement targeted, practical solutions [8,10].

In this paper, we are interested in the application of MCSA in the agri-food sector. MCSA has been widely adopted in various domains. For instance, in the banking and industrial sectors, the authors of [8,12] explored the implications of using a multi-capital strategy for financial reporting, which helps businesses understand and manage their different types of capital, thereby positioning themselves for long-term sustainability. Authors in [9] highlighted how incorporating multiple forms of capital—such as human, social, natural, and constructed—can provide a more comprehensive picture of performance beyond just financial metrics. Similarly, a sustainability framework based on six types of capital has been applied in [13] to evaluate the local impacts of resource extraction in rural Australia, considering financial, human, social, natural, built, and cultural capital. This approach has also influenced other fields, such as the oil and gas industry [11], delivery [14], and firms striving for competitiveness through multi-capital sustainability strategies [15], demonstrating the versatility and advantages of utilizing MCSA to address sustainability objectives across different industries. Despite this breadth, an examination of the literature revealed that it has not yet been applied correctly in the agri-food sector [10]. Adopting the MCSA for AFSCs could provide valuable insights and enhance sustainability efforts across the agri-food system. Our research work focuses on this research area and aims to answer the following research questions (

Table 1. Research questions.

Question	Research Significance
RQ1: How widely has MCSA been applied to address sustainability challenges in AFSCs?	Determining the degree of MCSA implementation aids in evaluating its maturity within the agri-food industry and shows how various contexts have included multi-capital thinking.
RQ2: What capital and indicators should be considered to characterize the performance of AFSCs while addressing sustainability concerns?	Building a strong framework that can capture the multifaceted character of sustainability in AFSCs is made possible by identifying pertinent types of capital and the indicators that go along with them.
RQ3: How can these indicators be effectively evaluated or calculated?	Searching the evaluation techniques that guarantee the chosen indicators are quantifiable, actionable, and comparable across settings.
RQ4: How are the sustainability capital and themes connected to particular Sustainable Development Goals (SDGs)?	Mapping capital and themes to particular SDGs further strengthens the alignment between AFSC sustainability assessments and global development targets.

):

To answer these research questions and highlight the contributions of this paper, it is essential to understand how AFSC sustainability has been tackled. Various frameworks have been developed by international organizations, such as the United Nations (UN) and the Food and Agriculture Organization (FAO), as well as by academic researchers. Frameworks developed by international bodies have served as foundations for arranging the different facets of sustainability and direct initiatives to incorporate sustainable practices in various contexts. For instance, the SDGs defined by the UN, particularly Goal 2 (Zero Hunger) and Goal 12 (Responsible Consumption and Production), provide a global framework for achieving sustainability in agri-food systems [3,16]. These goals offer targets and indicators relevant to sustainable agri-food systems [17]. The FAO defined other frameworks for AFSC, such as SAFA (Sustainability Assessment of Food and Agriculture Systems) [4], which is structured hierarchically, with four main sustainability dimensions: Good Governance, Environmental Integrity, Economic Resilience, and Social Well-Being. These dimensions are divided into 21 themes and 58 sub-themes, each representing specific sustainability areas and providing a total of 116 indicators. This makes it one of the most powerful sustainability assessment tools available. Despite its strengths, SAFA’s exclusion of consumer and end-of-life stages represents its significant limitations, neglecting critical factors such as labeling transparency and environmental impacts after the product’s use. Additionally, due to its generic nature, SAFA fails to address the specific challenges of some chains. These limitations and the need for more context-specific indicators prompted the authors [18] to develop a personalized sustainability framework based on SAFA for the flowering potted plants value chain.

Regarding frameworks developed by academic researchers, similarly to the previous one, several papers addressed AFSC sustainability using a thematic approach that breaks down the pillars of sustainability into specific categories or themes and indicators. In fact, [5] emphasised the social dimension, identifying and organizing indicators into eight distinct themes. However, this focus on a single dimension limited the ability to analyze the broader range of key dimensions comprehensively. In [6], the authors did not provide detailed classifications or explanations of the indicators employed. Still, the distinctiveness of this framework lies in its integration of coordination across AFSC stages as a pivotal sustainability dimension. Authors in [6] highlighted the importance of coordination between supply chain stages and its impact on economic, environmental, and social performance. In [19], the authors proposed using food sovereignty as a framework to assess food systems by incorporating the political dimension into analyzing their outcomes. They presented a database and divided these indicators into six categories: gender, agrarian policies, commercialization, food consumption and the right to food, productive models, access to resources, and productive models. However, the authors of [19] did not specify how the indicators are calculated. Furthermore, ref. [20] stood out for its detailed description of methods for calculating indicators and examination of research contributions to AFSC networks. In contrast, the authors of [21] proposed a methodology for calculating and defining key performance indicators (KPI). Their approach is geared toward a framework for selecting indicators through sample analysis. Finally, the authors of [2] provided valuable definitions and a structured framework for sustainability performance measurement in the AFSCs. Their framework identified 16 performance areas and 71 subcategories for measuring sustainability in AFSCs. However, it did not explicitly mention measurable indicators that actors can quickly implement within the supply chain. Additionally, while specific actions, such as employee engagement in ecological programs, are important for the environmental dimension, they may also be relevant to the social dimension (focused on employee well-being, engagement, and ethics) rather than strictly within the environmental one. This distinction ensures that sustainability efforts are categorized according to their primary focus area.

Table 2. Comparison of existing literature reviews on AFSC and the positioning of our review.

Reference	Time Horizon	Scope	N Article	Sustainability Dimension	Categorizations		Indicator
						Number	Methodology/Formula
[5]	Completed in August 2021	Identifying and analyzing social sustainability indicators	128	Soc.	8 themes	36	No
[6]	1997–2018	Sustainability assessment frameworks and indicators measurement	109	Env., Eco., Soc.		40	No
[19]	2009–2019	Food sovereignty framework, database indicators, and its limitations		Env., Eco., Soc.	6 categories	97	No
[20]	2005–2020	Challenges, performance indicators, and modeling	108	Env., Eco., Soc.	--	--	Methodology
[21]	2007–2020	Indicators selections	99	Env., Eco., Soc.	--	49	No
[22]	2010–2022	Indicators selections	157	Env., Eco., Soc.		101	No
[2]	2000–2021	Categorizations and identifying key subcategories	142	Env., Eco., Soc.	16 categories	71	No
[23]	1990–2022	Conceptualization and metrics selections	81	Env., Eco., Soc.	---	40	No
Our work	2017–2024	A conceptual framework based on multi-capital, categorization by multi-capital, and indicator measurement per actor	106	Env., Eco., Soc.	12 types of capital and 6 categories	116	Formula and methodology

Note: Env.: Environmental; Eco.: Economic; Soc.: Social.

summarises this research and compares our work with them. This comparison is built on the following criteria: time horizon, scope, number of articles, AFSC actors, sustainability dimension, categorizations, indicator definitions, methodology (procedures used in research to collect and calculate data), and indicator formulas.

Table 2 and the review of existing frameworks show that:

-

Most studies address the AFSC, with limited attention to how sustainability responsibilities and indicators are distributed among individual actors—an issue highlighted by [2,6]. Such allocation highlights each actor’s responsibility for sustainability, reinforcing the need to consider all AFSC actors in the framework development.

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There is a lack of accurate indicator formulas across most of the developed frameworks.

-

There is a lack of studies adopting the MCSA despite its recognized advantages.

-

To our knowledge, no review has been published recently on this topic as of 2024. Moreover, the most recent review of sustainability indicators considered studies published only up to 2022.

To address these gaps, we propose a fresh review of the literature on AFSC indicators by including published papers up to 2024 while considering various AFSC actors, from farmers to consumers. Formulas for indicators are presented based on validated references. Moreover, the MCSA is adopted to categorize gathered indicators by linking them to various types of capital. This classification results in a multi-capital sustainability framework (MCSF). Contrary to traditional frameworks that often overlook the interdependencies between resources, MCSF recognizes that value creation in AFSCs depends on managing multiple types of capital. It helps businesses identify trade-offs and balance short-term gains with long-term sustainability goals [8]. According to [10], there is no consensus on the types of capital and indicators relevant to each actor. Building on the results of [10], our study contributes to the AFSC sustainability and MCSA literature in the following ways:

• It is an attempt to develop an MCSF for the AFSC by adapting the MCSA to the agri-food context. To do so, the proposed framework breaks down the 3 sustainability dimensions into 12 distinct types of capital as listed and defined in

  Table 3. Capital forms, definitions, and roles for each sustainability dimension.

  Dimension	Capital	Description	Role
  Environmental	Natural	Refers to the essential resources and ecosystems that provide goods and services necessary for human well-being [7].	It is essential to maintaining life and human development, but it must be kept within reasonable bounds to prevent going beyond its ability to recover or absorb effects [7].
  Economic	Financial	Identifies investments and financial resources that promote value and growth [8].	Accessible to a company for usage in manufacturing products or rendering services [7]. A business model that prioritizes financial gain may reduce overall value if it depletes more valuable resources, like human effort or natural assets, for short-term profits [7].
  	Material	Pertains to physical resources such as new infrastructure, raw materials, and technologies [15]. It can also be referred to as physical capital [26] and manufactured capital, which encompasses mainly physical assets, plants, machinery, and equipment [27]. Those are a subset of material capital due to their tangible nature and central role in production processes [8].	It is vital in reducing risks, improving efficiency, and meeting quality requirements. Such investments are increasingly essential for maintaining competitiveness.
  	Shareholders	Represents shares owned by the corporation and the dedication to maximizing and protecting asset value for the organization’s and each investor’s long-term growth [15,28]. It is also called share capital [28].	It is crucial in determining an enterprise’s worth and future direction [15].
  	Stakeholders	Highlights the collective interests and contributions of all stakeholders: internal (e.g., employees) and external (e.g., customers, suppliers), emphasizing the interconnected importance of all the actors [15,29].	Addresses tensions in profit allocation between stockholders and other stakeholders [29]. Maintaining stakeholder capital benefits both the firm and the broader economy by aligning the interests of all parties involved.
  	Human	It focuses on the individual level and refers to individuals’ ages, experiences, knowledge, and capabilities and their active contribution to work processes.	Drives innovation and productivity through skills and expertise at the individual level [30].
  	Intellectual	It focuses on the organizational level and is seen as the total knowledge of an organization’s members. It also examines how this knowledge is practically applied to create valuable assets for the company. It is also known as scholarly capital [31].	Converts personal knowledge into organizational assets that may be utilized, distributed, and sold, giving an organization a competitive edge [32]. It provides a long-term competitive advantage.
  Social	Internal social	Refers to connections between individuals and groups within organizations [15,33].	Increases internal cooperation and information exchange [34].
  	External social	This refers to the relationships with other businesses and institutions beyond the organization that impact broader society. Relevant in activities like regional fairs or representing national agriculture [15,33].	It allows the company to learn from its external partners, improve its processes, and strengthen its organizational capabilities [35].
  	Relational	Focuses on value generated from external relationships and their direct contribution to the organization’s value.	Builds loyalty and trust with clients and partners [36].
  	Image	It influences how the public views a company/service and is improved by effective communication, strategic brand selection, and promotion of the organization’s activities or services [37]. It is also called brand capital.	Significantly strengthens the company’s ability to generate revenue and drive sales. Higher revenue can result from a stronger brand attracting more clients [37].
  	Ethical	It entails a dedication to moral behavior, bolstering social legitimacy and confidence [38].	Guarantees the adaptability and robustness of economic networks by incorporating moral values like justice, openness, and ecological care [39].

  and aligned with [15]. Each type of capital addresses specific aspects of sustainability, contributing to a holistic evaluation of economic, social, and natural interactions. Adopting these types of capital varies depending on the activities of each AFSC actor. In this paper, we consider five AFSC actors [24,25]: (i) smallholders (SH) as they form the backbone of agriculture, focusing on growing and harvesting agricultural products; (ii) transport companies (TC) that carry these products to processing facilities; (iii) stakeholders (ST), including manufacturers, food processors, distributors, restaurants, hotels, and retail stores; (iv) consumers (CS); and (v) policymakers (PM) such as government agencies and regulatory bodies that create and implement regulations to govern various aspects of the supply chain. To the best of our knowledge, this is the first study that defines a comprehensive MCSA for AFSCs with a structured understanding of the three dimensions of sustainability from a resource perspective for each actor.
• There is a meticulous gathering of indicators crucial for sustainability assessment assigned to the different types of capital based on the systematic literature review. Furthermore, a rigorous linking of each indicator to its specific capital and AFSC actor steers away from the mere collection of data and comprehensively addresses the spatial and temporal scales within the assessment context.
• Crafting specific formulas for each indicator and providing transparent methodologies for their calculation is proposed.
• Based on the literature review, a theoretical AFSC sustainability framework linking the set of sustainability capital, themes, and SDGs is proposed.

The remainder of this paper is organized as follows. Section 2 presents the research methodology. The main results achieved by its application are illustrated in Section 3. The discussion of major findings is provided in Section 4. The article’s main conclusions and directions for future research are summarized in Section 5.

2. Materials and Methods

To achieve the research purposes exposed in Section 1, a systematic literature review (SR) method is applied following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The complete PRISMA checklist is provided in the Supplementary Material Table S1.

The SR described by [40] includes structured search processes, meta-analytic techniques, and narrative synthesis to achieve a replicable and rigorous literature synthesis. This method provides a standardized means to collect and evaluate data from published studies to address the research questions. Meta-analysis allows for statistical pooling of quantitative findings, while narrative synthesis facilitates qualitative exploration of relationships within the data. Together, these methods enable a robust generation of insights from multiple investigations featuring numeric and textual data. The SR protocol includes seven main steps to address the established research questions cited in the introduction. These steps are detailed in

Table 4. Review steps and the corresponding analytical techniques.

Steps	Decision Point	Rationale	Activity
1. Search Strategy	Identify where to look	Databases, keywords, type, language, and date of publication	Develop a protocol for conducting systematic searches across multiple sources.
2. Study Selection	Decide what to include	Rigor, relevance, data quality, inclusion/exclusion criteria	Using reference management software, create a PRISMA flow diagram to document the selection process.
3. Data Extraction	Extract what matters	Key research questions, study design, outcomes	Design data extraction forms and coding schemes.
4. Analysis Pathway	Choose how to synthesize	Narrative synthesis, meta-analysis, qualitative/quantitative analysis	Ensure a clear and systematic method for analyzing and classifying sustainability indicators based on well-defined criteria.
5. Results and Interpretations	Choose classification criteria	Findings	Classify indicators by capital, followed by thematic categorization through tables and analyses.
6. Discussion	Determine trends to discuss and propose a framework	Alignment between sustainability capital, themes, and corresponding SDGs.	Discuss the connection between the selected themes and the relevant SDGs.
7. Dissemination and Engagement	Share the literature review outcomes	Publications, presentations, knowledge translation strategies	Articles

. The third column comprises the essential elements or tasks of the research process and the instruments and techniques to be employed. The fourth column, Activity, describes the actions performed during the process phase.

2.1. Search Strategy

Following the research questions outlined in the introduction, a comprehensive search strategy was developed to ensure the collection of potentially relevant and high-quality academic literature. Two major bibliographic databases were considered, namely, Web of Science and Scopus, covering publications from 2017 to 2024. Supplementary platforms such as Google Scholar, IEEE Xplore, and ScienceDirect were consulted to ensure a comprehensive collection of relevant studies. We collected academic research papers from these databases and platforms that contained at least one of the identified terms or keywords in either the abstract, title, or keywords; they were published in journals and were written in English. The keywords are listed in

Table 5. Keyword categorization for comprehensive search.

Group	Keywords
Topic	Agri, agro, food supply chain, sustainable, sustainability
Actors	Smallholder, farmer, transport; policymaker, decision maker, stakeholder, consumer, retailer
Capitals and dimensions	(i) Environmental–economic–social dimension (ii) Natural, financial, material, stakeholders, shareholders, human, intellectual, relational, social, external social, internal social, ethical, image capital
Indicators	Indicator, metric

. Meticulous attention was given to selecting keywords, which are thoughtfully categorized into four main groups: AFSC sustainability, AFSC actors, forms of capital and dimensions, and indicators. The topic reflects the general theme, while the actors represent the participants involved in the chain. The capitals and dimensions group highlights the various types of capital under the broader sustainability dimensions, which refer to the key areas of sustainability that guide the assessment. The indicators are used to measure performance. Detailed explanations of each capital are provided in Table 3.

To thoroughly refine the search and filter relevant papers, a Boolean “AND” operation is applied to link all the groups. Each group links individual keywords using the Boolean “OR” operator.

2.2. Study Selection

Each paper obtained from the final search (684 papers) was evaluated by two evaluators (research collaborators with demonstrated knowledge of sustainability and AFSC) and was assessed for inclusion in the full review based on clearly defined inclusion and exclusion criteria, as outlined in

Table 6. Inclusion/exclusion criteria.

Inclusion Criteria	Exclusion Criteria
Study design: Only peer-reviewed original research articles that report on empirical studies related to sustainability in the agri-food supply chain should be included.	Non-empirical studies: Studies that are not original research articles or do not report on empirical studies should be excluded.
Timeframe: Studies published within the last 7 years should be included for the indicator, while the calculation formulas can apply to any date range.	Language: Studies published in languages other than English should be excluded.
Participants: Studies should investigate sustainability issues related to agri-food supply chains, including farmers, processors, distributors, retailers, consumers, and other relevant stakeholders.	Duplicate studies: If multiple studies report on the same dataset, only one study should be included.
Outcomes: Studies should report on specific outcomes related to the sustainability of AFSCs, such as environmental impact, economic viability, social equity, and consumer health and safety.	Studies on non-agri-food supply chain sustainability: Studies that do not specifically investigate sustainability issues related to the agri-food supply chain should be excluded.
Interventions: Studies should investigate interventions or strategies that aim to improve the sustainability of AFSCs, such as reducing waste, improving resource efficiency, enhancing product quality and safety, and promoting ethical and social responsibility.	Poor quality studies: Studies with poor or incomplete data should be excluded.

. These criteria were explicitly detailed to ensure a consistent and objective evaluation of all papers. Only papers that met the inclusion criteria were deemed eligible. A total of 414 papers were excluded during the eligibility phase because they did not match the research domain and did not include any mention of key KPIs or forms of capital.

This process allowed us to identify the most relevant articles for our research objectives, particularly those providing the highest number of indicators and topics related to AFSC sustainability. Although some studies were thematically related to the AFSC context, they were excluded from the final synthesis because they did not report quantifiable indicators or did not address specific forms of capital. For example, ref. [41] addressed sustainability issues in agri-food systems, but it lacked measurable measurements and frameworks related to capital.

The PRISMA flowchart, illustrated in Figure 1, is the output of this step. The graphical representation illustrates the flow of information through different phases of an SR or meta-analysis, from identifying relevant studies to their inclusion or exclusion in the final analysis. It typically outlines the number of articles identified at each stage, reasons for exclusions, and the final number of studies included in the SR. This enhances transparency and helps readers comprehend the study selection process. It is important to emphasize that the selected articles will be focused on exploring indicators. If certain formulas are not readily available, an additional search will be conducted using reliable and authoritative sources, ensuring a comprehensive investigation beyond Google Scholar or other trusted platforms. In the end, 106 papers out of potential ones entered the data extraction stage for qualitative and quantitative analysis, and 77 of the included articles were used to extract indicators.

2.3. Data Extraction

A standardized form should be used to extract data from 106 selected articles. This will facilitate the process of comparing and synthesizing information across different studies. For each included paper, two types of information should be extracted and entered into the database:

 (i)

Basic data about the paper, such as author, paper title, date, country/affiliation, type of paper, paper keywords, and topic.

(ii)

Content-related data, such as sustainability capitals/dimensions, actors in the AFSCs, indicators used to measure sustainability, case studies, and the sustainability approach taken in the study. This will provide a comprehensive overview of the different sustainability-related issues and approaches investigated in the AFSCs.

2.4. Analysis Pathway

The analytical process entails a global and detailed analysis. The first one, presented in Section 2.5, provides the overall picture of AFSC sustainability indicators from the capital and AFSC actors’ perspectives. Two key outputs are generated: (i) the percentage of capital addressed in the AFSC sustainability literature (Figure 2) and (ii) the percentage of actors considered in the same body of work (Figure 3). The detailed analysis itself is divided into two parts. First, a comprehensive classification of sustainability indicators by dimension, capital, and actor will be provided in the deeper analysis, detailed in Section 3. This classification is based on the placement of each indicator in the literature. It specifically follows where the authors of the articles have positioned the indicator within the dimensions and types of capital. If the indicator is mentioned in multiple articles that do not specifically focus on AFSCs, its classification within each capital or dimension is based on its general treatment in the broader literature. In cases of ambiguity or disagreement among authors, such as when indicators could fit into two or more types of capital, a discussion was held among the article’s authors to determine the most appropriate classification. If confusion persisted, an expert AFSC review was conducted to ensure accurate classification. Based on the generated classification for each dimension, the second part of the detailed analysis identifies major sustainability themes, highlighting the interconnectedness of capital within that dimension. In this context, a theme refers to a recurring topic or pattern extracted from the existing literature, reflecting key sustainability concerns or priorities. These themes are derived from a systematic review of articles, focusing on recurring concepts and their relationships to different forms of capital. As many of these indicators align with those involved in the SDGs, establishing a clear connection between the identified themes and the global sustainability goals is essential.

In summary, this systematic methodology groups indicators by dimension and aligns them with the relevant forms of capital and actors, offering a comprehensive breakdown of sustainability indicators. It also ensures a clear understanding of multi-capital sustainability measurement and highlights key themes across dimensions and types of capital based on the consensus from the literature and expert input.

2.5. Data Analysis: An Overview of Considered Types of Sustainability Capital and AFSC Actors

A dataset of 106 articles related to sustainability in the AFSCs was collected, identifying 116 indicators. These indicators are categorized according to the types of sustainability capital and AFSC actors. Figure 2 and Figure 3 depict the distribution of sustainability indicators among capital and AFSC actors, respectively.

Figure 2 emphasizes a heightened focus on natural capital compared to other ones such as financial, social, and human. This allocation of attention points out the recognition of the paramount importance of natural resources and environmental sustainability within the broader context of the AFSCs. In fact, the concept of sustainability has historically strongly emphasized the environmental component [43]. Nonetheless, the idea has changed to acknowledge the significance of social and economic factors, particularly in light of the 17 SDGs. Natural resources are becoming increasingly important because of their scarcity and the damage they cause during extraction, exacerbating climate change [44].

Figure 3 illustrates the pre-eminence of studying sustainability for smallholders within the AFSC where they are considered a cornerstone of agricultural activity development [45]. This finding highlights the critical role smallholders play in achieving sustainability. Understanding the challenges and opportunities small-scale producers face is essential to promoting sustainable and equitable agricultural development. That is why most studies focus on smallholders’ sustainability using different forms of capital. However, the AFSC does not solely focus on actors and indicators but emphasizes the significance of exploring sustainability across various fields. Identifying sustainability indicators across diverse domains and geographical regions further highlights their importance in evaluating and advancing sustainable practices in the AFSC. The selection of sustainability indicators in various domains and geographical areas emphasizes how important they are for appraising and advancing sustainable practices in the AFSC. Studies have examined the environmental effects of supply networks for perishable foods, including bananas in Sri Lanka [46] or the co-design of sustainable performance goals in French pig value chains [47]. The broad application of such evaluations is also shown by the sustainability performance of smallholder quinoa production in Peru [48], rice crop management techniques in Vietnam [49], and sugarcane agro-industries in Indonesia [50]. Even though every field has its own challenges, these indicators provide a common framework applicable in different contexts. By combining these metrics, researchers and practitioners can create standardized methods for assessing sustainability.

3. Identification of Sustainability Capital and Indicators for AFSCs

This section is structured as follows: each sustainability dimension and its related forms of capital are represented in a dedicated subsection, and identified forms of capital and indicators within each dimension are classified in a table. These tables include the indicator name, the associated actor or entity, the reference, and the indicator formula provided in the appendices. Key sustainability themes are identified at the end of each subsection using the indicators for each dimension that have been identified. The purpose of these themes is to highlight how intertwined its forms of capital are.

3.1. Environmental Dimension Capital and Indicators

3.1.1. Classification and Results

Only one capital is identified within the environmental dimension: “natural capital” [15]. Various categories of ecological sustainability indicators could be defined within this capital. Thanks to the categorization, we can group indicators according to their particular areas of significance and influence. Each group represents a significant component of natural capital. Various categories were defined in the literature in the framework of the AFSC. The authors of [51] divided environmental metrics into seven categories: mineral resources and materials, impact on the environment and climate change, energy and water, biodiversity, land use and rehabilitation, emissions and waste, and implications for human health. The authors of [2] proposed eight categories: energy use, water use, material and resources use, waste management, emissions, product requirements, environmental compliance, and ecosystem preservation. Another categorization suggested by the authors of [52] is that ecological indicators are split into three major groups: atmosphere, water, and land. The atmosphere group is distinguished by climate change and air quality; the water group focuses on water quality; and the land group includes soil quality, forest management, and solid waste generation and management.

Based on the latest research, a proposal outlining six categories for the environmental dimension is presented in

Table 7. Identification of the categories of sustainability environmental indicators for AFSCs.

Proposed Category	Definition	Equivalent or Similar Category in the Literature
Input	Refers to the substances used in the production process to raise livestock or grow crops.	Mineral Resources and Materials focuses on the inputs in various fields, encompassing the resources and materials extracted and utilized [51].
Land	Concerns the use and management of land, including soil rehabilitation and preservation.	[52], “Land Use and Rehabilitation” (according to [51]) and can also be associated with “Ecosystem Preservation” (as per [2]).
Energy	Includes the consumption and efficiency of energy in production and operational processes.	“Energy Use” category is proposed by the authors of [2], and the energy dimension of the “Energy and Water” category according to [48].
Water	The use of water includes water consumption in production processes.	[52] “Water Use” is classified by [4] and is also part of the broader “Energy and Water” category according to [48]
Air	Encompasses greenhouse gas emissions, air pollution, and their impact on climate.	Equivalent to the categories “Impact on the Environment and Climate Change”, “Emissions”, and “Atmospheric” according to [2], [51], and [52], respectively.
Waste	Measures liquid discharges and solid waste, providing insights into the environmental impact of these emissions and waste products.	Corresponds to “Waste Management” in [2] and “Emissions and Waste” in [51].

. These categories are commonly used and are linked to those found in the literature, including their definitions and references. This classification aids in distinguishing the similarities and differences between the categories proposed in various scientific studies on environmental sustainability indicators. On the one hand, the categories of land, water, air, and energy align with the elements of nature necessary to support ecosystems and life. On the other hand, the input and waste categories represent the environmental effects of human activities. The impact of using fertilizers is considered in the input category, whereas solid waste and liquid discharge belong to the waste category. Reducing the harm humans cause to the land, water, and air depends on efficient waste management. By making this distinction between natural elements and human impacts, environmental sustainability is ensured through a holistic approach that addresses both the preservation of natural resources and the mitigation of environmental issues produced by human activities.

The environmental indicators for each category, the relevant AFSC actor, and its formula are listed in

Table A1. Natural capital: multi-actor indicators.

Ca	Indicator	Unity	SH	TC	ST	PM	CS	Ref	Formula
Input	Percentage of external inputs used for production (IE)	%	*					[74]	$IE={\displaystyle \frac{IC}{ITC}}\times 100$; [75] Input cost (IC) = X × Px X: Number of inputs, Px: Price of input (Currency/unit) The total cost of production inputs (ITC)= EIC+IIC; EIC: External Input cost IIC: Internal input cost
	Nitrogen and phosphorus balances (NP)	kg ha−1	*					[76]	$NP={\displaystyle \frac{Differencebetweeninputsandoutputs}{Totalfarmarea}}$; [76]
	Number of treatment days using antibiotics per 100 days (TD100)		*					[65]	${TD}_{100}={\displaystyle \frac{Qtantibiotic}{{DDDA}_c\times kganimalsatrisk\times daysr}}\times {LA}_c\times 100$; [77] Qt antibiotic: antibiotics quantity DDDAc: Defined daily dose animal defined for ‘any country’ kg animals at risk: Total mass of animals at risk of treatment (animal’s average number present multiplied by the estimated mass at the time of treatment) Daysr: Total number of days that an animal was at risk of treatment. LAc: Long-acting factor adjusts for extended duration of action and could be defined for all products for the same country
	Nitrogen use efficiency (NUE)	grain kg N kg−1	*					[49]	$NUE=\mathrm{A}\mathrm{m}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{v}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{e}\mathrm{d}/N$; [78] N: fertilizer amount added through sources (organic or inorganic)
	Phosphorus use efficiency (PUE)	grain kg P kg−1	*					[49]	$PUE=\mathrm{A}\mathrm{m}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{v}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{e}\mathrm{d}/P$; [78] P: Fertilizer amount added through sources (organic or inorganic)
	Potassium use efficiency (KUE)	grain kg k kg−1	*					[49]	$KUE=Cropyield/k$; [79] K: fertilizer amount added through sources (organic or inorganic)
	Eutrophication potential	kg PO43- eq ha−1 year−1	*					[48]	PEN = Load (mass) of nitrogen/mass or units produced; [80] PEP = Load (mass) of phosphorous/mass or units produced
Land	Agricultural land occupation	ha	*			*		[47]	Data
	Area under native grasslands (AUNG)	%				*		[76]	$AUNG={\displaystyle \frac{\mathrm{A}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{u}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{r}\mathrm{n}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{s}\mathrm{s}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{s}}{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{f}\mathrm{a}\mathrm{r}\mathrm{m}\mathrm{a}\mathrm{r}\mathrm{e}\mathrm{a}}}\times 100$; [76]
	Land cover	%	*		*	*		[81]	Data: % of:—Artificial surfaces -agricultural areas—forest and semi-natural area -wetlands -water bodies; [81]
	Urban land occupation	%				*	*	[47,82]	Data: the urban land occupation indicator is more dedicated to bringing information on transport planning issues and on tensions between agricultural and urban land occupation; [83]
	Annual soil loss	Mg ha−1 yr−1	*			*		[84]	A = R.K.LS.C. SP; [84] R calculated using the equation: R = 10.8 + 0.415 MRRm MRRm: Monthly average precipitation from the 3 closest climatological stations of the study area weighted by the inverse of the distance between the plot and the stations. K: Soil erodibility, LS: Slope length and steepness factor, C: Cropping factor, SP: Support practice factor
	Terrestrial acidification	kg SO2eq /ha/year	*			*		[82]	The specific equation for calculating terrestrial acidification involves the Acidification Potential (AP). (recipe 2016) ${AP}_{x,i}={\displaystyle \frac{{FF}_{x,i}}{{FF}_{so2,worlaverage}}}$; APx,i: Acidification potential for a specific precursor (e.g., NOx, NH3, SO2) in a specific grid FFx,i: Fate factor for acidification due to emissions of the precursor (x) in grid i FFso2, world average: the world average is the emission-weighted world average fate factor for SO2
Energy	Abiotic depletion (AD)	kg Sb eq	*					[48]	$AD=\sum _j{ADP}_j\times M_j$; [85] ${ADP}_j={\displaystyle \frac{{DR}_j/{R_j}^2}{{DR}_{ref}/{R_{ref}}^2}}$; Mj: Quantity of resource i extracted (kg). ADPj: Abiotic depletion potential of resource i (kg Sb equivalents/kg of resource i) Rj: Ultimate reserve of resource j (kg) DRj: Extraction rate of resource j (kg yr−1) (regeneration is assumed to be zero) Rref: Ultimate reserve of the reference resource, antimony (Sb) (kg) DRref: Extraction rate of the reference resource (kg yr−1)
	Energy use (EU)	MJ/kg	*	*	*	*	*	[76]	$EU=\sum _i{Q}_i\times {EF}_i$; Qi: Quantity or amount of a specific energy source i used. Efi: Energy conversion factor for that particular energy source i.
	Use of renewable energy (RE)	%	*	*	*			[74]	$RE={\displaystyle \frac{ER}{TE}}\times 100$; ER: renewable energy used in kWh TE: Total of energy used in kWh
	Fossil fuel depletion (FFD)	kg oil-eq/unit output	*	*	*		*	[82]	$FFD={FFET}_t\times {OILQ}_t$; [86] FFETt: Fossil fuel extraction by type t (in kg/unit output or MJ/unit output of the process under study) OILQt: Oil equivalent characterization factor by type t (in kg oileq/kg or kg oileq /MJ). Types ‘t’: Crude oil, hard coal, natural gas, brown coal, and peat
			*		*			[47]
	Use of electrical vehicles	number	*	*	*	*	*	[87]	Data
	CO2 emission by electrical used (C1)	tco2 per ton product	*	*	*			[50]	C1$={\displaystyle \frac{electricityused\left(MWh\right)\times {0.485}^{\raisebox{1ex}{$tco2$}\!\left/ \!\raisebox{-1ex}{$MWh$}\right.}}{Numberofproduct\left(Ton\right)}}$; [50]
Water	Water use for agriculture production	m3	*			*		[49,88]	Data
	Water use efficiency (WUE)	Value added/m3	*	*	*	*	*	[55]	$WUE=\sum _i^n{WUE}_i\times {weight}_i$; [89] WUE: the overall water use efficiency at the national level. WUEi: the water use efficiency for the i-th sector. Weighti: the % of water withdrawn by the i-th sector relative to the total water withdrawals. ${WUE}_i={\displaystyle \frac{{NVA}_i}{{VW}_i}}$; [89] NVAi: Net value added; VWi: Volume of water used (m3)
			*					[49,90]
	Water depletion (WD)	m3	*		*		*	[82]	WD = (CURSW + CUARG) − AAWA; [91] CURSW: Consumptive use of renewable surface water (m3) CUARG: Consumptive use of annually renewable groundwater (m3) AAWA: Average annual water availability (m3)
			*		*		*	[47]
	Water footprint (WF)	m3/ton	*					[92]	$WF={\displaystyle \frac{\mathrm{c}\mathrm{r}\mathrm{o}\mathrm{p}\mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{u}\mathrm{s}\mathrm{e}\mathrm{o}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{a}\mathrm{s}\mathrm{o}\mathrm{n}}{Cropyield}}$; [92]
	Water scarcity footprint (WSF)	m3 world-eq,/kg	*					[93]	${WSF}_{Specificcrop}=annualawareCF\times {WC}_{gs}$; [93] WCgs: Total growing season water consumption (m3/kg) Annual aware CF: annual available water remaining characterization factors of specific crops (m3 world-eq,/m3 consumed)
	Irrigation water use productivity (IWP)	kg m−3	*					[49]	$IWP={\displaystyle \frac{yieldproduced}{irrigationwateruse}}$; [94]
	Water loss (Wloss)	m3/year	*	*	*		*	[16]	Wloss [p, c] = WF [p, c] × Floss[p]; [16] Wloss [p, c]: Loss of water based on each water footprint (WF) component c used to produce the quantity of food item p in the year t. WF [p, c]: Water footprint of the food item pp associated with component c. Floss: Amount of food loss recorded across the supply chain in year t for the selected food item p.
	Freshwater eutrophication	kg P eq	*	*	*			[47]	Based on [95], there are several methods for calculating freshwater eutrophication, such as the Trophic Level Index (TLI) method, the Trophic State Index (TSI) method, and the Fuzzy Comprehensive Evaluation (FCE) method. These methods use specific formulas to calculate the eutrophication indices based on measured parameters such as nutrient concentrations and water clarity.
	Water quality	------	*		*	*		[56]	Data: Total of suspended solid (mg/L), Biochemical oxygen demand (mg/L), Chemical oxygen demand (mg/L), sulfide (mg/L)
			*	*	*			[50]
Air	Acidification potential (AP)	kg SO2eq	*					[48]	$AP=\sum _i^n{ESO}_2\times {Wi}_2$; [96] ESO2i: Coefficient of sulphur dioxide equivalent for i-th material [kgSO2eq kg−1]; Wi2 weight of i-th material (kg)
	GHG emissions (GHG)	kg CO2	*	*	*			[97]	$GHG=\sum _i^n{Activity}_i\times emissionfactor$;
	Global warming potential (GWP)	Kg CO2eq	*			*		[48]	$GWP=\sum _i^n{ECO}_2\times {Wi}_2$; [96] ECO2i: Coefficient of carbon dioxide equivalent for i-th material [kgCO2eq kg−1]; Wi2, weight of i-th material (kg)
			*	*	*			[46]
	Odor and dust disruption to the community	-	*	*	*			[50]	Data
	Noise level	dB	*	*	*			[50]	Data from sensors: Workplace noise (DB), open space noise (DB)
	Ambient air quality		*	*	*			[50]	Data: Dust (µg/Nm3), sulfure dioxide(µg/Nm3), carbon monoxid (µg/Nm3), nitrogen dioxide (µg/Nm3)
	Time temperature indicator (TTI)	°C	*	*	*	*	*	[98]	Data via sensors
	Ozone depletion (ODP)	Kg CFC-11 eq/kg emission	*					[48]	$ODP={\displaystyle \frac{\mathrm{O}\mathrm{D}\mathrm{f}\mathrm{r}\mathrm{o}\mathrm{m}\mathrm{S}\mathrm{u}\mathrm{b}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e}}{ODfromCFC-11}}$; [99] CFC: Chlorofluorocarbon
			*	*	*	*	*	[82]
Waste	Natural preservation in fresh fruit	-	*		*		*	[60]	data
	Green packaging (GP)	%			*		*	[59]	For …: $GP={\displaystyle \frac{\mathrm{n}.\mathrm{o}\mathrm{f}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{a}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{o}\mathrm{f}\mathrm{a}3\mathrm{R}\mathrm{s}\mathrm{o}\mathrm{u}\mathrm{r}\mathrm{c}\mathrm{e}}{\mathrm{n}.\mathrm{o}\mathrm{f}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{a}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}}\times 100$; $\mathrm{n}.\mathrm{o}\mathrm{f}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{a}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{o}\mathrm{f}\mathrm{a}3\mathrm{R}\mathrm{s}\mathrm{o}\mathrm{u}\mathrm{r}\mathrm{c}\mathrm{e}$: Use of returnable, reusable, and recycled packages …… with 3R concept (remanufacturing, recycling, and reuse) [100]
				*	*			[100]	$GP={\displaystyle \frac{\mathrm{n}.\mathrm{o}\mathrm{f}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{a}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{u}\mathrm{s}\mathrm{e}\mathrm{d}\mathrm{i}\mathrm{n}\mathrm{l}\mathrm{o}\mathrm{g}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{c}\mathrm{s}\mathrm{w}\mathrm{i}\mathrm{t}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{p}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}\mathrm{d}\mathrm{i}\mathrm{s}\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{d}}{\mathrm{n}.\mathrm{o}\mathrm{f}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{a}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}}\times 100$; [100]
	Food waste (FW)	%	*	*	*		*	[101]	$Fw\%={\displaystyle \frac{TotalFW}{TotalIP}}$; Total FW: Total amount of food waste Total IP: Total amount of input food commodities
			*	*	*	*	*	[102]
	Solid waste (SW)	solid/product	*	*	*			[50]	$SW={\displaystyle \frac{BLotong\left(kg\right)\times 0.76\%\times {0.005}^{{\frac{kgNOx}{}}_{kgN}}\times 0.7kg{SO}_{2-eq}}{Numberoftotalproduct\left(kg\right)}}$; Blotong: Product or solid waste resulting from the refining process

Note: CA: Capital, SH: Smallholder, TC: Transport company, ST: Stakeholder, PL: Policymaker, CS: Consumer, *: Marks the actor associated with a specific indicator.

(see Appendix A). Figure 4 illustrates the number of indicators per category and per AFSC actors. The following is evident from this figure.

Most indicators are held by smallholders, with 38 specifically created for them that highlight their crucial role in managing natural resources, contributing significantly to the food supply while closely engaging with their environments. According to an analysis of Table A1 (Appendix A), this actor’s primary sustainability indicators enable the assessment of the effects of its farming methods on ecosystems, with a particular emphasis on soil health, water consumption, and sustainable farming methods to strike a balance between sustainability and production [53].

The remaining players demonstrate shared accountability for preserving natural resources and hold a substantial share of environmental indicators (19 for transportation corporations, 24 for important stakeholders, 15 for policymakers, and 13 for consumers).

The following key conclusions are drawn from an analysis of Table A1, which shows how indicators are distributed throughout categories and actors:

• Of all the characters, water has the most indicators, highlighting its critical role in agricultural operations, including crop irrigation and the production and consumption of food. Since agriculture uses 70% of the world’s water withdrawals and more than 80% in agrarian economies, water, acknowledged as essential to life and socioeconomic development [54], is under increasing strain [55]. Sustainable water management is supported by indicators that offer insights into productivity, consumption, and policy optimization, such as irrigation water productivity (IWP), water use efficiency (WUE), and agricultural water use [55]. Social capital also affects water management since decisions about optimal practices and water quality are shaped by the trust and collaboration of farmers, regulators, and extension workers [56].
• The second category, air indicators, assesses atmospheric properties and their significant environmental effects. Climate change, fuelled by globalization and industrialization, is one of the most important challenges. Storms, floods, and droughts are among the major environmental disasters exacerbated by this phenomenon, affecting transportation, distribution, and agricultural output. Key metrics like GHG emissions and global warming potential (GWP) are essential. These indicators are crucial and need to be considered separately for an appropriate estimate, even though they are connected. GHG emissions quantify the amount of greenhouse gases released into the atmosphere, whereas GWP measures the warming potential of greenhouse gases compared to carbon dioxide over a given period [46]. Both metrics guide climate policy and mitigation efforts. Linking to GWP and GHG emissions, ozone depletion is another critical indicator. It is assessed through changes in stratospheric ozone concentration, with ozone depletion potential (ODP) measuring a substance’s impact relative to CFC-11.
• Issues for the AFSC’s energy category include resource depletion and reliance on fossil fuels. To lessen dependence on fossil fuels, the number of electrical points along the chain is a crucial indicator that shows improvement but is still low, particularly in developing nations where infrastructure development is the responsibility of policymakers [57]. This provides a vital focus for sustainability initiatives and research since it illustrates the intricate interactions among consumer preferences, packaging innovation, and energy dynamics.
• In the land category, the “native grassland” indicator is often overlooked despite its role in climate change mitigation and ecosystem services like carbon sequestration and water regulation [58]. To determine significant conservation areas, biodiversity, and ecosystem health, the area of natural grasslands must be measured. Innovations in sustainable packaging have resulted from these decisions, which show how consumer tastes, environmental concerns, and industry activities are changing over time [59].
• The input category only applies to smallholders because it concentrates on materials used for livestock and soil.

3.1.2. Themes Identified

Three main themes can be identified based on the important indicators shown in Table A1 and per the most widely used method of organizing sustainability indicators, theme-based frameworks (UN, 2007).

“Health and Waste” addresses the detrimental impacts of rubbish and air pollution on the environment and human health while concentrating on sustainable packaging and air quality to increase resilience and lessen environmental harm. “Climate change” focuses on indicators like GHG emissions, especially from the air and energy categories. Last, “Resource Efficiency and Use” prioritizes the sustainable management of land, water, and energy, guaranteeing long-term productivity and striking a balance between agricultural demands and ecological preservation.

3.2. Economic Dimension Forms of Capital and Indicators

3.2.1. Classification and Results

This subsection focuses on the economic dimension. Table 3 divides it into six separate types of capital: financial, material, human, intellectual, stakeholder, and shareholder.

The list of economic sustainability indicators by capital, along with their respective formulas and the involved actors, is presented in

Table A2. Economic dimension/multi-capital multi-actor indicators.

Ca	Indicator	Unit	SH	TC	ST	PL	CS	Ref	Formula
Financial	Benefit-cost ratio (BC)	Currency unit	*					[49]	$BC={\displaystyle \frac{\sum _{i=0}^n\frac{Y_i}{{\left(1+r\right)}^i}}{\sum _{i=0}^n\frac{k_i}{{\left(1+r\right)}^i}}}$; [80] Yi: Net annual benefit of year i = Bi − Oi + Epi − Eni Bi: Total benefit (or revenue) of year i; Oi: Operating cost of year i; Epi: Total positive externalities; Eni: Total negative externalities; Ki: Capital outlay for assets of year i (initial investments + re-investments); r: Discount rate; n: Number of years in operation. n ≥ 20.
	Net farm income (NFI)	currency unit	*					[103]	NFI = CR + Yk − OE − Dep + VIC; [104] NFI: Total net farm income Yk: Income in kind CR: Total farm cash receipts including direct program payments OE: Total operating expenses after rebates (including costs of labour) Dep: Depreciation VIC: Value of inventory change
	Net income (Ni)	currency unit	*	*	*			[49]	Ni = sales revenue − total costs
	Total production costs (TPC)	currency unit/ha	*					[49]	TPC = Fixed cost + Variable cost
	Payback period (PP)	currency unit/year	*	*	*			[105]	$PP=\mathrm{C}\mathrm{i}\mathrm{n}/ACF$; [106] Cin: Cost of investment ACF: Average Annual Cash Flow
	Access to credit score (ACC’s)		*	*	*			[97]	ACC’s = [0.5 × Normalized IMF] + [0.5 × (Normalized Findex)]; [107] IMF: Financial institution access Findex: Share of adults with an account
	Cash requirement (CR)	currency unit/month	*	*	*			[108]	$CR=TE/NM$ TE: Total expenses over the accounting period. NM: Number of months in the accounting period.
	Net cash flow (CF)	Currency unit/month	*					[109]	CR = Total Cash Inflows − Total Cash Outflows
	Land productivity (LandP)		*					[110,111]	$\mathrm{L}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{P}={\displaystyle \frac{\mathrm{P}\times GP\times \times SI}{AY}}\times SLF$; P: Total production income (per acre) GP: Government payments (per acre) SI: Secondary income (per acre, e.g., hunting leases) AY: Adjusted yield per acre SLF: Share lease factor (typically 1/3 or 0.33)
	Farmers reference price (FRP)	Currency unit	*					[50]	Data
	Access to markets (AM)		*					[112,113]	Data
			*		*			[114]
	Road density (RD)	RD/country		*				[115]	$RD=TotalLR/LR$; Total LR: Total length of road network (km2) LR: Land area (km2)
	Transport cost	Currency unit × ton agro-material−1		*				[116]	Data: These would include mode of transportation, distance traveled, type of goods, and other logistical considerations
	Grocery store density (GSD)	GS/100,000 people			*		*	[113]	$GSD={\displaystyle \frac{GS}{population}}\times \mathrm{100,000}$; GS: Total number of grocery stores in the area, and Population: Total population of the area.
	Gross domestic product (GDP)	Currency unit/country				*	*	[117]	$GDP=Cs+In+Gs+Ne$ Cs: Consumption; In: Investment; Gs: Government spending; Ne: Net Exports
Material	Cost of fertilizer, equipment, and machines	Currency unit	*					[118]	Data
	Storage facilities (SF)	Number of facilities	*					[97]	Data: Farmer surveys project records [119]
	Cold infrastructure storage (CIS)		*					[120]	Data: Farmer surveys project records [119]
	Material for packaging			*	*			[120]	Data
	Pre-cooling facilities			*				[121]	Data: Farmer surveys project records [119]
	Variable and fixed costs		*		*			[122]	Variable costs: labor costs (paid and unpaid) + material costs Fixed Costs: land charge + costs of certification + costs of own capital
Stakeholders	Lead time (Ltime)		*	*	*			[123]	Ltime = the promised delivery date of the product − the actual delivery date of the product
	Delivery flexibility			*		*		[123]	Data: The possibility to change planned delivery dates
	change in the nutritional value						*	[124]	Data
	Number of food exports		*		*		*	[19]	Data
	Number of food imports		*		*		*	[19]	Data
	Entrepreneurial orientation			*		*	*	[125]	Data
	Number of agricultural raw materials exports		*		*		*	[19]	Data
	Number of agricultural raw materials imports		*		*		*	[19]	Data
	Degree of quality performance of collaboration				*			[126]	Data
Human	Labor intensity (Lint.)	h/wage	*					[70]	Data: Laborers’ time per hectare, wage value and hours of work per wage; [70]
	Labor productivity (LaborP)	currency unit/person/day	*					[70]	$LaborP={\displaystyle \frac{Pr}{\raisebox{1ex}{$person$}\!\left/ \!\raisebox{-1ex}{$day$}\right.}}$; Pr: Product value ($)
	Child labor costs	currency unit	*					[49,122]	Data
	Costs of hired labor in accordance with international labor standards	currency unit	*					[122]	Total workings day X (minimum wage in accordance with international standards—paid wages)
	Food self-sufficiency		*					[70]	Data: Caloric production necessary for the household supplied from the pastures
	Labor reduction (LR)	%	*					[70]	$LR={\displaystyle \frac{InitialLabor-Finallabor}{InitialLabor}}\times 100$;
	Total off-farm labor performed	hr year–1	*					[127]	Data [128].
	Hired labor	hr year–1	*					[127]	Data
Intellectual	% Use of agriculture education (AEDU)	%/country	*					[113]	$AEDU={\displaystyle \frac{NF}{TF}}\times 100$ NF: Number of farmers who received technical education. TF: Total number of farmers.
	Use of production technology		*		*			[108]	Data
	% Project supported by the governmental (PSG)	%PSG/Time period	*			*		[118]	$\%PSG={\displaystyle \frac{NumberofPSGforsmallholders}{NumberoftotalPSG}}\times 100$;
	% Project supported by the Private investment (PSPI)	%PSPI/Time period	*		*			[68]	$\%PSPI={\displaystyle \frac{NumberofPSPIforsmallholders}{NumberoftotalPSG}}\times 100$;
	Education level		*					[129]	Data
Shareholders	Concept of management—Cash conversion cycle (CCC)	number of days/companies			*			[130]	The indicator of how long cash is tied up between procurement and sales developed CCC = DIO + DSO − DPO DIO: Days of inventory outstanding DSO: Days sales (receivables) outstanding DPO: Days payables outstanding

Note: CA: Capital, SH: Smallholder, TC: Transport company, ST: Stakeholder, PL: Policymaker, CS: Consumer, *: Marks the actor associated with a specific indicator.

(see Appendix A), compiling 45 economic indicators. Additionally, Figure 5 highlights two major findings. The contributions of labor, financial inputs, knowledge, and skills underscore their significance in the economic context. However, financial capital was the most examined and had the most indicators, followed by stakeholder and human capital. This finding underscores the critical role of financial resources, stakeholder involvement, and human capabilities in shaping the economic sustainability and success of the AFSC.

A detailed examination of Table A2 highlights the following major findings: sustainability metrics such as cash needs, credit availability, investments, farmer income, and market accessibility have been considered in the literature under financial capital. However, less research has been conducted on other AFSC actors, including packaging costs for consumers [60] and shipping costs for transport companies [61]. Intellectual capital, which includes the indicator of technology adoption, is increasingly emphasized in the literature because it can influence various types of capital. It is particularly crucial for smallholders, representing a novel and transformative element. Policymakers consider entrepreneurial orientation. Additionally, market accessibility is a vital component of sustainability in the AFSC. Production and factor endowment, input and output market channels, value addition, physical infrastructure (such as roads, storage, telecommunication, and market facilities), market information, training, and advisory services are some of the components included in this [61]. Additionally, the density of grocery stores is a crucial determinant of the AFSC’s distribution system and market accessibility. Furthermore, operational success depends on material capital comprising storage, machinery, and equipment. A coherent supply chain also depends on stakeholder capital, which includes import/export dynamics and cooperation. Human capital is concerned with working circumstances, emphasizing problems such as child labor, inequality, and farmers’ standard of living. Lastly, a common tool for evaluating shareholders is the cash conversion cycle, which measures the time it takes to convert capital into cash flow and represents the efficiency and liquidity of business activities.

3.2.2. Themes Identified

Aligned with the economic sustainability categories proposed in [4], four major themes can be defined in this paper based on the list of selected indicators. These include financial performance, investment and existing resources, productivity and efficiency, and flexibility and responsiveness. Liquidity, solvency, and profitability—all primarily categorized under financial capital—are the main topics of financial performance. Key indicators such as net farm income, net cash flow, and benefit-cost ratio are pivotal in evaluating this theme. To guarantee effective operations and long-term resilience, the second theme, investment and existing resources, combines aspects of material and financial resources. Indicators like access to credit scores, packaging material and fertilizers, equipment, and machine costs underscore the significance of balancing strategic expenditures and operational requirements. Both natural and human capital have an impact on the third theme, which is productivity and efficiency. Necessary intellectual and human capital measures include production technology and labor productivity. Finally, the fourth theme, flexibility and responsiveness, encompasses important metrics such as road density, which reflects infrastructure support for logistical efficiency, and delivery flexibility (DF), which highlights the ability to adjust operations in response to consumer demands.

3.3. Social Dimension Capital and Indicators

3.3.1. Classification and Results

Table A3. Social dimension/multi-capital multi-actor indicators.

Ca	Indicator	Unit	SH	TC	ST	PL	CS	Ref	Formula
Social (external + internal)	Healthiness index (HI)	%					*	[131]	$HI={\displaystyle \frac{MPF+UPF}{18}}\times 100$; [131] MPF: Total score of subgroups of minimally processed foods sold UPF: Total score of subgroups of ultra-processed foods not sold
	Organic food consumption (OFC)	%/week					*	[132]	$\%OFC={\displaystyle \frac{OrganicfoodConsumption}{Totalfoodconsumption}}\times 100$;
	Dietary diversity	%/country				*	*	[113]	$DD={\displaystyle \frac{PFD}{Totalpopulation}}\times 100$ PFD: Those who, according to the Food Diversity Score, consume more than six food types each day
	Number of new employees per year		*					[133]	Data
	Number of contracts with buyers		*					[134]	Data
	Participation in cooperative organization		*					[110]	Data
	Match supply to demand (MS-d);	%/company or country			*		*	[135]	$MS-d={\displaystyle \frac{ActualSales}{ForecastedSales}}\times 100$;
	Food security	%				*		[136]	Data: % of the population that is food secure [113]
	Household hunger Scale		*					[137]	Data:
	Access to health insurance programs (AHP)	Employee/country				*		[138]	$AHP={\displaystyle \frac{{\mathrm{N}\mathrm{u}\mathrm{m}}_{\mathrm{h}\mathrm{i}}}{{\mathrm{N}\mathrm{u}\mathrm{m}}_{\mathrm{e}\mathrm{o}}}}\times 100$; Numhi: Number of employees and owners with health insurance Numeo: Number of employees and owners
	Number of social network		*	*	*	*	*	[139,140,141]	Data
		Number	*					[118]
	Degree purchase behavior	Purchase number/period					*	[142,143]	Data
	Number of participations in actions	Number of actions/years	*		*	*			Data
	Local availability of products (Lap)	%/period	*	*	*	*	*		$L.ap={\displaystyle \frac{N.T.F.}{T.N.F.}}\times 100$; N.T.F.: Number of local agrifood purchased products per product category per month T.N.F.: Total number of agrifood purchased products per product category per month
	% of permanent employees for the agriculture activity per year (peas)	% of peans/year	*			*			$\%PEAS={\displaystyle \frac{NumberofPEAS}{Numberoftotalemployees}}\times 100$;
Relational	Coordination degree			*				[120]	Data
	Number of collaborations		*	*		*	*	[144,145]	Data
	Customer needs		*		*		*	[60,64,146]	Data
					*		*	[126]
	Gender equity		*					[147]	Data
	Trust degree		*			*		[148]	Data
					*	*	*	[149]
					*		*	[150]
	Number of followers on the social media (NFSM)	Followers	*		*		*	[151]	Data
	Number of deliveries (ND)	ND/consumer		*	*		*	[152]	Data
	Additional work hours (AWH)	AWH/month	*	*	*			[47]	Data
	% Rural population	%R/country			*	*	*	[19]	$\%Rp={\displaystyle \frac{Ruralpopulation}{Totalpopulation}}\times 100$; Rural Population: The number of people living in rural areas. Total Population: The total population of the country or region.
Image	Net promoter score (NPS)		*			*	*	[148]	$NPS=\%Promoters-\%Detractors$; % Promoters: The percentage of respondents who score 9 or 10 on a scale of 0 to 10 when asked, “How likely are you to recommend our product/service? “ % Detractors: The percentage of respondents who score 0 to 6 on the same scale.
	Local consumption of production (LC)						*	[153]	$LC={\displaystyle \frac{massofproductsoldinthelocalmarket}{totalproduction}}$;
	Local brand value		*		*	*	*	[63]	Data: Recognition and awareness of the brand, perceived quality, examine promotional materials’ content for recurring themes and visuals.
	Enforcement of the law					*		[62]	Data: Legal actions taken, regulatory compliance costs, stakeholder perceptions…
Ethical	Animal-based indicators		*					[154]	Data: Directly measure aspects of animal well-being, such as physiological parameters, behavior, and health.
	Certifications and labels	Number	*		*		*	[155]	Data: Labels such as organic, non-GMO (Genetically Modified Organism), free-range, and sustainable agriculture certifications provide consumers with assurance that products meet specific ethical standards and production practices.
	% Corporation Social Responsibility (CSR) Initiative	% CSR/ Country			*			[156]	$\mathbf{\%}\mathit{C}\mathit{S}\mathit{R}\mathbf{=}{\displaystyle \frac{\mathit{C}\mathit{S}\mathit{R}}{\mathit{T}\mathit{o}\mathit{t}\mathit{a}\mathit{l}\mathit{c}\mathit{o}\mathit{m}\mathit{p}\mathit{a}\mathit{n}\mathit{i}\mathit{e}\mathit{s}}}\mathbf{\times }\mathbf{100}$; CSR: Companies taking responsibility for their social and environmental impacts by implementing ethical sourcing policies

Note: CA: Capital, SH: Smallholder, TC: Transport company, ST: Stakeholder, PL: Policymaker, CS: Consumer, *: Marks the actor associated with a specific indicator.

(see Appendix A) and Figure 6 present a comprehensive breakdown of 31 relevant social indicators for each capital and actor, recognizing that some indicators, such as access to health insurance programs, apply to multiple actors across the chain.

Consumers and smallholders receive the highest rankings, emphasizing their well-being across the supply chain. With the 36 indicators overall, smallholders do well across all types of capital, particularly in relational and social capital. This illustrates how important they are to the supply chain and how their welfare is prioritized. Consumers follow with 19 indicators, excelling in relational capital (8) and image capital (3), though their performance in ethical capital is notably weaker.

Beyond the smallholders and consumers, other actors, such as policymakers, transport companies, and stakeholders, also engage with different forms of capital, but these were less addressed compared to environmental and economic dimensions. For instance, policymakers have shown image capital through the enforcement of laws [62] and efforts to enhance the local brand value [63]. Similarly, customer satisfaction [64], a key indicator for image capital, is applied to smallholders, consumers, and stakeholders.

Regarding ethical capital, indicators such as animal welfare [65] and equity [66] have been proposed for smallholders, ensuring their rights and fair treatment. Another important ethical metric for consumers and transportation businesses was equity, which illustrated the larger goal of guaranteeing inclusion and justice in the supply chain. These indicators show how the social dimension of sustainability goes beyond just environmental concerns to include important ethical and relational aspects of the AFSC.

3.3.2. Themes Identified

From analyzing these forms of capital and their associated indicators, our focus has shifted to three themes—well-being, security and confidence, and local development and governmental support—to address emerging sustainability challenges within the AFSC. For instance, well-being metrics such as the healthiness index and organic food consumption emphasize the importance of health and nutrition in building consumer trust and refer to the interrelated components of dietary practices and overall well-being.

The security and confidence theme stresses the stability and reliability of supply chain relationships, incorporating metrics such as the number of contracts with buyers, participation in cooperative organizations, and trust degree. These metrics highlight the value of trustworthy alliances and teamwork in building resilience.

Finally, local development and governmental support highlight the role of localized initiatives in strengthening agricultural communities and emphasize improving local communities with the help of both local projects and state policy indicators, such as the local availability of products, local brand value, and the % of permanent employees in agriculture per year, demonstrate the importance of community investment and consistent employment.

4. Discussion

4.1. Major Findings

To summarize the major results of our review, it is interesting to highlight that each dimension’s percentage of indicators is allocated as follows: 34% for the environmental dimension, 39% for the economic dimension, and 27% for the social dimension. Consequently, the economic dimension exhibits the highest percentage of the other dimensions. This highlights the need for a normative vision aligned with current material needs to achieve non-holistic sustainability based on a multi-capital approach [7]. In contrast, ref. [22] prioritizes the environmental dimension, as evidenced by its inclusion of detailed and measurable indicators like soil analysis, soil cover, and soil health, among others. However, its treatment of the economic dimension remains vague, relying on non-measurable references such as “price” or “working capital level”, which lack the specificity necessary for practical sustainability assessment. Similarly, [6] provides a minimalistic view of the economic dimension, focusing on only the most basic indicators. Furthermore, the study groups all financial aspects together without providing distinct metrics related to material capital, which are essential components of the economic dimension.

Our review’s second key finding concerns the capital perspective.

The most significant capital with the highest number of indicators is natural capital since it is the basis of agricultural production, sustainable management, and resource efficiency, which go hand in hand. Increased production and lessened environmental effects can be achieved by optimizing the use of essential resources such as water, energy, and nutrients while upholding appropriate land use practices. However, climate change poses a serious risk to the stability of agricultural systems. Urgent and group action is required in response to the long-term changes in weather patterns brought about by human actions, such as deforestation and the usage of fossil fuels. Resilience-boosting strategies like agroforestry, carbon sequestration, and renewable energy sources are essential for reducing these hazards.

Additionally, waste management—whether for liquid or solid waste—has become a prominent topic in the literature, indicating the growing significance of waste management in conversations about sustainability. Key initiatives supporting a healthier society and ecosystem include lowering CO₂ emissions, encouraging the prudent use of antibiotics, and ensuring that trash is disposed of effectively, whether by managing agricultural runoff or food waste. The growing emphasis on waste management emphasizes developing practical plans to lessen adverse environmental effects and improve supply chain resource efficiency.

Furthermore, the analysis underscores the significant role of smallholders across sustainability dimensions, contributing, respectively, to 42%, 45%, and 39% of environmental, economic, and social indicators. Despite obstacles, including restricted access to markets, funding, and contemporary technology, their resource management choices significantly impact the resilience and productivity of AFSCs. Strengthening their role through focused initiatives is essential for enhancing food security and promoting sustainable practices across global supply chains as they are frequently marginalized by policies that favor industrial agriculture [67].

A closer look at the results reveals that each actor—smallholders, policymakers, or other stakeholders—prioritizes specific indicators depending on the capital involved. However, the distribution of indicators reveals an imbalance, with different actors, such as policymakers and transport companies, being under-represented. This under-representation may stem from differing priorities, limited engagement in data collection processes, or a lack of tailored frameworks that address these actors’ specific needs and contributions [68]. This suggests the need for a more equitable distribution of indicators to ensure a comprehensive approach to sustainability across the entire AFSC.

Additionally, a limitation of the MCSA lies in the overlap between different forms of capital and indicator selections. The risk of bias in the indicator selection process cannot be entirely eliminated; however, efforts were made to minimize it through expert consultation and the involvement of multiple authors in the review process.

This risk is further compounded by the fact that human activity is not easily separable into distinct economic and social categories [69]. The indicators that fall under ’Human Capital’ encompass aspects related to both economics and sociology, acknowledging the interconnectedness of these dimensions. For instance, metrics like unemployment and poverty are considered important economic factors, but they also have significant social implications in terms of their effects on individuals, families, and communities. Some authors may categorize these indicators as primarily social [70], while others view them as economic. A similar issue arises with ’Intellectual Capital’ where the overlap between types of capital complicates indicator attribution. However, this classification may be challenging for individuals with limited educational backgrounds, particularly smallholders in underdeveloped regions. They may have difficulty distinguishing between the different forms of capital or fully understanding their significance. Therefore, particular attention should be given to this issue when applying the framework in such contexts.

4.2. Connecting Multi-Capital Sustainability Framework with the SDG Targets

After conducting this analysis, themes are proposed that build on existing categorizations in the literature while offering a more generalized view of the indicators identified in our study. Unlike existing frameworks, such as the one provided in [22] or [2], which categorizes indicators directly into sustainability dimensions, our proposed themes transcend strict dimensional boundaries. However, our approach highlights that while an indicator can only be associated with one specific capital, the overarching themes proposed can belong to multiple dimensions or types of capital. For example, while well-being is mainly associated with the social side, it also raises environmental concerns because it addresses waste and health issues. This integrative approach ensures a more complete portrayal of ecological challenges.

Our results demonstrated that each of the considered capital tackles different themes of sustainability, which can be interlinked with the SDGs. These relationships are depicted in Figure 7.

Starting with the environmental dimension, the theme of resource efficiency and use is connected to SDG 6 through effective water use. SDG 6.4.1 has been tracked in a number of nations using the water usage efficiency indicator. Morocco’s water use efficiency increased from 10.3 to 15.7 USD/m³ between 2015 and 2018, primarily as a result of agricultural investments in drip irrigation systems [71]. By increasing production per unit of water consumed, this instance demonstrates how focused resource management in the AFSC may directly help progress toward SDG 6.4.

This theme also links to SDGs 9, 7, and 12, which focus on reducing greenhouse gas emissions and energy consumption [72]. One of the targets of SDG 9 focuses on upgrading industrial infrastructure with environmentally sound technologies, while SDG 12 highlights the importance of efficient resource use, including energy. Digital technologies like IoT, ML, and Blockchain are crucial for achieving SDGs by addressing sustainability issues in agriculture and food supply chains [72]. They reduce agricultural and food waste (SDG 2, 12), enhance food quality and security, and minimize GHG emissions (SDG 9, 13). SDG 12 links water and energy efficiency as better water management reduces energy demand, highlighting the interdependence of these goals. Reducing food waste under SDG 12 helps mitigate environmental impacts that affect public health (SDG 3) and enhances food security (SDG 2). Further, the topic of production and efficiency from an economic standpoint is central to SDG 12, which aims to promote sustainable production and consumption patterns.

Inefficiencies in food supply chains, ranging from post-harvest losses to poor distribution networks, are significant barriers to achieving this goal [72]. Addressing these inefficiencies can contribute to SDG 2. Through monetary expenditures in environmentally friendly infrastructure, the promotion of technical innovation, and enhanced market accessibility, the economic dimension is also linked to SDGs 9 and 8. Similarly, by supporting inclusive and equitable quality education and encouraging opportunities for lifelong learning for all, this dimension strongly aligns with SDG 4.

The social dimension is represented by SDG 2 and SDG 3.

Furthermore, confidence and security promote openness and equitable opportunity, which achieves SDG 5. Governments play a crucial role in supporting SDGs by designing policies, regulations, and frameworks that promote sustainable practices. They coordinate stakeholders, align sustainability with other agendas, and encourage the adoption of standards like ISO 14001 and ISO 22000 [73]. By fostering systemic changes, governments enable efficient resource use, waste reduction, and responsible production, ensuring progress toward sustainable development goals [73]. Local development and governmental support are key to achieving SDGs 9 and 11.

5. Conclusions and Future Research Areas

This study presents a literature review on AFSCs and contributes to developing an MCSF. The results offer a fresh, multi-capital perspective on sustainability, providing valuable insights into various supply chain actors and helping them identify the key resources they impact. Indicators have been categorized under distinct forms of capital, which is a significant advancement in sustainability research and allows for a more nuanced understanding of how diverse actors prioritize sustainability. In addition, identifying critical capital allows for more focused interventions, aiding enterprises and policymakers in making informed decisions about resource management, environmental practices, and social effects.

Despite its essential contributions, this research study has some limitations. Due to the vast volume of the available literature, not every sustainability indicator could be included in our review; only the most relevant ones are considered.

Although the sustainability assessment is based on the multi-capital approach, which considers various perspectives and contextual variations of the AFSC, the number of capital types adds another complexity to calculating a sustainability index. So, conducting surveys among AFSC actors is crucial to empirically validating the sorts and the number of most pertinent types of capital that best suit each actor’s needs. This validation of the suggested framework with pertinent AFSC would also allow for a deeper exploration of the relationship between theory and actual situations.

Future research can build upon this framework by developing it into a sustainability assessment tool that offers a customized dashboard for each AFSC actor. It will focus on how to calculate the performance of each capital using real-time data and how these relate to each dimension by actor. Furthermore, a more detailed classification of indicators could be introduced, linking them to the identified themes and allowing users to track performance by capital type and theme. This tool can represent a promising starting point for future work aimed at deepening and expanding the application of this methodology approach. As for barriers to adoption, there are several potential challenges. These could include limited access to technology in rural areas, the need for extensive data collection and integration from various sources, and the cost of implementing such systems.