Advancing the WEFE Nexus Approach with Multi-Criteria Decision Analysis and Standardization Refinements

Abstract

Water, energy, food, and ecosystem (WEFE) components constitute fundamental dimensions contributing to human well-being, poverty alleviation, and sustainable development. Despite the prevalent specialization among WEFE professionals, there is a lack of multidisciplinary approaches in their work, with limited attention given to carbon footprint management. Against this backdrop, this study aims to explore the potential role of standardization and multi-criteria decision analysis (MCDA) in implementing the WEFE approach within the food sector. The research entails a comprehensive examination of the International Standard Organization (ISO) 22000 certifications in Balkan countries, coupled with an analysis of the ISO 14067 standard and its alignment with food safety requirements. Finally, this study proposes a novel MCDA framework for integrating food safety considerations with criteria, factors, and indicators aimed at addressing both food safety and carbon footprint management. A hierarchical structure composed of influential criteria and factors was used to rank activities in sustainable, preferably carbon-neutral food production. Group decision making was applied in the fuzzy domain using triangular numbers, and the influence of experts was determined based on their experience. Practical recommendations aimed at managing trade-offs between the requirements of two elaborated standards are provided, emphasizing key environmental, societal, and economic insights to identify critical indicators for addressing biases in food safety and carbon footprint management.

1. Introduction

The Water–Energy–Food–Ecosystems (WEFE) Nexus approach has increasingly been recognized as vital for addressing interconnected challenges related to water, energy, food, and ecosystem management issues. The WEFE Nexus paradigm entails the coordination, integration, and cost-effective planning and management of interconnected natural resources across these sectors. Strategic collaboration and synergistic efforts within this approach can yield enhanced overall resource security compared to conventional fragmented strategies. This methodology facilitates the identification of synergies in natural resource management to achieve objectives such as ensuring WEFE security, conserving ecosystems and their functions, bolstering climate resilience, and facilitating the transition to green economies. However, achieving these objectives necessitates inter-sectoral capacity building and cooperation among professionals engaged in relevant water, energy, food, and ecosystem strategic and operational initiatives, particularly within food production [1,2]. The adoption of a WEFE Nexus approach promotes resource efficiency by optimizing the use of water, energy, and food resources. For instance, improving the irrigation efficiency not only conserves water, but also saves energy used for pumping water and enhances agricultural productivity [3]. Similarly, renewable energy technologies such as solar and wind can reduce water usage compared to fossil fuel-based energy generation [4]. The WEFE Nexus acknowledges the interdependencies and trade-offs between water, energy, food, and ecosystems. Changes or disruptions in one sector can have cascading effects on others. For example, water scarcity can impact energy production (e.g., hydropower), agricultural productivity, and ecosystem health [5,6]. Understanding these interconnected relationships is also vital for reaching sustainable development goals (SDGs). With regard to sustainable development, the WEFE Nexus is closely aligned with several SDGs, particularly Goal 2 (Zero Hunger), Goal 6 (Clean Water and Sanitation), Goal 7 (Affordable and Clean Energy), Goal 13 (Climate Action), and Goal 15 (Life on Land) [7].

Adopting a Nexus approach can facilitate the achievement of these goals by promoting integrated solutions and holistic planning [8]. However, climate change intensifies existing challenges within the WEFE Nexus. The increased frequency and intensity of extreme weather events, such as droughts and floods, disrupt the water availability, agricultural production, and energy infrastructure [9]. By adopting a Nexus approach, countries can enhance their resilience to climate change impacts by integrating adaptation and mitigation strategies across sectors [10]. Hence, ensuring access to water, energy, and food is essential for human security and socio-economic stability. The WEFE Nexus approach helps identify vulnerabilities and risks within these systems, allowing for more effective management and mitigation strategies [11]. By addressing the root causes of resource scarcity and enhancing resilience, the Nexus approach contributes to reducing conflicts over natural resources. Of no less importance and in line with the previous statement is the fact that the effective management of these shared resources requires cooperation and collaboration among countries. The WEFE Nexus provides a framework for dialogue and cooperation, fostering regional partnerships and promoting the sustainable management of transboundary resources, eventually leading to improved higher education curricula [12]. The multi-dimensional concept of the WEFE Nexus approach is important from a global perspective because it recognizes the interconnected nature of water, energy, food, and ecosystems, promotes resource efficiency, enhances climate resilience, contributes to security and stability, aligns with sustainable development goals, and encourages transboundary cooperation [13,14].

Nevertheless, the WEFE Nexus approach is not an ideal concept and should not be seen as panacea universalis for all natural resource management challenges. Since the first scientific promotion of this term in 2011 (originally WEF Nexus, with later modifications, of which WEFE is the most significant), the WEF Nexus approach has been the subject of numerous scientific controversies [15]. In essence, the WEF Nexus is a classic example of the integration of multiple approaches and methods, or in this case, resources that are managed in a sustainable manner, from the standpoint of the most correct trade-offs between different stakeholders’ needs. Any type of integration, including WEF-WEFE-based integration, leads to a factual situation in which the set is more significant than its individual elements, with all the accompanying advantages and disadvantages of integration. For example, there are studies that do not deny the importance of the Nexus approach, specifically in the field of water resources, but recommend the use of a classic systems approach, which allows for the consideration of all the complex connections and interdependencies of different aspects in the water management system [16]. There are also studies that confirm the thesis given at the beginning of this paragraph, namely that the WEFE Nexus is not a universal solution to all challenges in the field of environmental resources, but rather a new approach that possesses appropriate driving factors and can generate certain outcomes [17]. The imperfection of the Nexus approach was particularly pronounced during the pandemic caused by the COVID-19 virus, with highly heterogeneous experiences with the adaptation of water, energy, and food systems in changed, partly emergency conditions [18]. On the other hand, there are prominent scientific debates that emphasize that adequate planning and the use of the advantages of the WEF Nexus approach brings concrete benefits for various users or stakeholders in the water–energy–food system, which additionally highlights the need for objective decision making [19]. In support of the fact that the WEF Nexus-based approach has its undoubted advantages, there is also the fact that various modifications or additions are being increasingly used, where, in addition to the already mentioned WEFE approach, there are also the WEFEC (Water–Energy–Food–Ecosystem–Climate), the WFECE (Water–Food–Energy–Climate–Ecosystems), and the FEW (Food–Energy–Water) approach, which essentially represent the same line of action. The WEFE Nexus approach acknowledges the intrinsic interdependence of water, energy, and agricultural management, together with the environmental consequences associated with each of them. As a result, competing demands on shared resources have intensified, heightening the risk of conflicts of interest, particularly as resource pressures continue to mount. Of no less importance is the fact that the WEFE Nexus approach seeks to illuminate the intricate trade-offs arising from the interdependence between energy, food, and water systems and natural resources, while also addressing the associated environmental risks. These risks encompass biodiversity loss, climate change, and localized air and water pollution, emphasizing the need for integrated resource management to mitigate negative impacts. Traditionally, these interconnections have not been explicitly factored into decision-making processes within these sectors, which is another reason why this paper highlights the need to use the MCDA approach.

In this sense, the multidimensional nature of the WEFE Nexus approach allows adjustments, with appropriate focus on emerging challenges [20]. For instance, the adjusted WEFE Nexus approach is promoted by the COST Action CA20138: Network on the water–energy–food Nexus for a low-carbon economy in Europe and beyond, where the advantages of the adjusted WEF Nexus approach are used to target a low-carbon economy [21]. This unequivocally suggests that the WEFE Nexus approach should be focused on carbon footprint management, greenhouse gas (GHG) elimination, and climate change mitigation strategies [22]. The coupling of the relevant ISO sectoral standard requirements, primarily ISO 22000 and ISO 140067, may result in a more carbon-sensitive, participatory-based, and climate-responsible WEFE Nexus application [23,24]. This modification reveals a tendency toward more climate-resilient societies, ready to combat greenhouse gas emissions [25,26,27]. Since later stages of the modified WEFE Nexus approach create the need for an adequate decision-making process in significantly modified surroundings compared to the initial WEFE Nexus approach, the introduction of multi-criteria decision analysis backed by expert decisions is more than welcome [28,29,30]. In sustainable and carbon-responsible food systems, ensuring food safety and minimizing the environmental impact are complex challenges that require systematic decision-making approaches. A hierarchical Multi-Criteria Decision Analysis (MCDA) approach can provide a structured, transparent, and rational framework for evaluating complex decision-making scenarios, particularly in food safety and carbon-related environmental impact assessments. Its application facilitates a comprehensive evaluation of food safety risks and environmental footprints, providing a rational basis for prioritizing actions and optimizing resource allocation. This methodology is particularly relevant in demonstrating compliance with standards such as ISO 22000 and ISO 14067. A fundamental step in applying MCDA is the identification of critical indicators that reflect key aspects of food safety and carbon footprint management. In food safety, these indicators may include compliance with regulatory standards. For carbon footprint management, indicators often encompass greenhouse gas (GHG) emissions, energy consumption, and waste generation. The selection of these indicators is typically guided by scientific risk assessments, regulatory frameworks, and sustainability goals [29]. Through MCDA, experts and stakeholders systematically assess these indicators based on their relevance, reliability, and potential impact, and thus facilitate the structuring of these complex decision problems by establishing a hierarchical representation of factors influencing food safety and the carbon footprint performance. By applying hierarchical MCDA in practice, organizations can achieve the following: improved compliance demonstration with ISO standards by transparently evaluating decisions with structured justifications; conflict resolution between competing priorities, such as balancing food safety with carbon neutrality goals; enhanced stakeholder engagement by clearly communicating how decisions are made using a systematic and replicable approach; and advanced risk management through the proactive identification of vulnerabilities in food safety and environmental sustainability efforts.

In accordance with the aforementioned facts, the aim of this paper is to analyze the advantages of the WEFE Nexus approach, elaborate the intensity of standardization in the field of food safety with the example of Balkan countries, provide a brief insight into carbon-footprint-relevant standards, and provide an adequate MCDA structure, referencing the WEFE Nexus needs and standard requirements.

The introduction offers an in-depth analysis of the characteristics of the Water–Energy–Food–Ecosystems (WEFE) Nexus, highlighting its advantages. This includes assessments of the benefits associated with adopting a WEFE Nexus approach, such as improved resource efficiency, enhanced resilience to climate change impacts, and greater socio-economic stability.

The second part of this paper delves into the practical aspects of standardization within the WEFE Nexus domain and carbon footprint management. This involves qualitative evaluations of the feasibility and effectiveness of implementing standardized protocols and methodologies across various sectors. It includes discussions on the potential benefits of standardization, such as the improved comparability of data, enhanced transparency, and streamlined decision-making processes. This paper concludes with the presentation of a robust Multi-Criteria Decision Analysis (MCDA) hierarchical model. This model is developed based on expert-based assessments of selected relevant criteria, factors, and alternatives joined within the WEFE Nexus framework, food safety, and carbon footprint management. Additionally, it includes a detailed example of an expert choice session, demonstrating the application of the MCDA model in real-world decision-making scenarios. The quantitative analysis within this section provides insights into the effectiveness and applicability of the MCDA approach in addressing complex interdependencies within food safety as a part of the WEFE Nexus and carbon footprint mitigation.

2. Theoretical Background and Literature Review

Standardization holds immense importance across various fields and industries for several reasons. Standardization ensures that different systems, products, and processes can work together seamlessly [31,32,33]. This is particularly important in sectors such as technology, manufacturing, healthcare, waste management, education, etc., where compatibility between various components is essential for efficiency and effectiveness [34]. Standards define best practices and specifications, helping to maintain and improve the quality of products and services. By adhering to standardized processes and procedures, organizations can ensure consistency in their output, thereby enhancing customer satisfaction and trust. This is particularly important considering that all modern system standards are based on the Plan–Do–Check–Act (PDCA) cycle of continuous improvement and that they primarily deal with the quality of processes, products, and services, primarily defined by the requirements of ISO 9001:2015. ISO 9001:2015 is often regarded as a framework for implementing the requirements of other system standards, particularly those in the field of environmental protection. ISO 9001:2015 is a globally recognized standard for quality management systems (QMS) and serves as the foundation for various other management system standards, including food safety, carbon responsibility, and environmental management. Its importance lies in its structured approach to continuous improvement, risk management, and customer satisfaction. ISO 9001:2015 serves as the foundation standard for a range of management systems by promoting consistency, risk management, and continuous improvement-based activities. Its principles are widely adopted in food safety, carbon responsibility, and environmental management to ensure policy compliance, resource efficiency, and long-term sustainability [35].

With regard to the environment and risk management, standardization can contribute to environmental sustainability by promoting eco-friendly practices. Standardized risk management frameworks and practices help organizations identify, assess, and mitigate risks more effectively [36]. By following established protocols, businesses can anticipate and respond to potential threats in a structured manner, safeguarding their operations and reputation. Environmental standards ensure that products and materials are sourced, produced, and distributed in an environmentally responsible manner. Standards for sustainable forestry, water, responsible mining, and fair trade promote transparency and accountability across supply chains, reducing deforestation, habitat destruction, and social inequalities [37]. Standards for land use planning, habitat restoration, and biodiversity management contribute to the conservation of ecosystems and wildlife. By establishing criteria for sustainable land development and ecosystem restoration, standardization also helps preserve biodiversity/ecosystems. Standardization further provides frameworks for environmental monitoring, data collection, and reporting [38]. Standards for environmental management systems (e.g., ISO 14001:2015) allow organizations to assess and improve their environmental performance, track progress towards sustainability goals, and communicate their efforts to stakeholders. In the face of increasing environmental concerns and the need for sustainable food production, ISO 14001:2015, the internationally recognized standard for Environmental Management Systems (EMS), plays a significant role in aligning food industry operations with ecological responsibility. While primarily designed to enhance the environmental performance, ISO 14001:2015 is indirectly linked to food safety and carbon footprint management, as sustainable resource utilization and pollution control significantly influence the food quality and climate impact. Implementing ISO 14001:2015 in the food industry ensures that food safety risks linked to environmental factors are systematically addressed. ISO 14001:2015 provides a well-balanced but basic starting point for carbon footprint management (this reflects the reason why ISO 14067:2018 is being introduced in addition), in part by ensuring that food production systems adopt climate-resilient and low-emission practices [39]. In addition, sustainable energy management standards such as ISO 50001:2018 play a key role in establishing, implementing, maintaining, and improving an energy management system (EnMS), which is one of the pillars of the WEFE Nexus approach. In the context of industrial sustainability and global climate commitments, energy efficiency plays a vital role in reducing environmental impacts and ensuring food safety. ISO 50001:2018 represents an internationally recognized standard for energy management systems, providing a structured framework for organizations to optimize energy use, enhance operational efficiency, and, consequently, minimize carbon emissions. The adoption of the ISO 50001:2018 standard in the food industry is not merely an operational necessity, but rather a strategic imperative for enhancing both food safety and carbon footprint management. By integrating energy efficiency measures into food production, organizations can reduce operational costs, ensure compliance with safety standards, and minimize the environmental impact. Furthermore, as the global food sector shifts towards more sustainable practices, ISO 50001:2018 provides a scientific and systematic approach to balancing energy efficiency with food safety and carbon neutrality, contributing to long-term business resilience and environmental sustainability [40].

Additionally, standardization is essential for food safety across various stages of the food supply chain. Standardization ensures that food products meet established safety requirements, protecting consumers from health risks associated with foodborne illnesses or contamination. Adherence to food safety standards raises consumer confidence, thereby strengthening trust in the food supply chain. This is predominantly achieved through the implementation of ISO 22000:2018 [41]. The ISO 22000:2018 standard provides a systematic, science-based framework for food safety management, applicable to food producers, processors, distributors, and service providers. Its implementation varies across countries based on regulatory structures, industry needs, and economic factors. Several positive examples illustrate its benefits. A study in India evaluated the food safety management systems of a small-scale food enterprise before and after ISO 22000:2018 certification, showing a drastic reduction in non-compliance in all areas [42]. In Taiwan, the application of ISO 22000:2018 significantly improved the control of raw materials, thereby enhancing the quality of final products [43]. A study in Latin America and the Caribbean showed higher consumer trust in organizations implementing various food safety standards, including ISO 22000:2018 [44]. Research in Lebanon highlighted positive effects on market operations following the standard’s adoption [45]. A study in Spain showed that the ISO 22000:2018 standard in the food supplement industry not only ensured food safety, but also boosted the industry’s competitiveness in the global market [46].

Beyond ISO 22000:2018 (but compatible with it), several other frameworks safeguard food safety across production, processing, and distribution stages. These include international regulations such as Hazard Analysis and Critical Control Points (HACCP), Good Manufacturing Practices (GMPs) and Good Hygiene Practices (GHPs), Global Food Safety Initiative (GFSI) schemes, Codex Alimentarius standards, or national/regional regulations such as the United States of America Food Safety Modernization Act (FSMA), European Union Food Law, or Russian Federation GOST standard “Safety of consumer goods. Guidelines for the suppliers and distributors”. HACCP Indirectly reduces greenhouse gas (GHG) emissions by minimizing food recalls, which can lead to additional transport and disposal emissions. GMPs promote energy and water efficiency in food processing facilities, reducing their operational footprints. Manufacturing facilities following GMPs can integrate renewable energy solutions to work toward carbon neutrality. While the primary objective of GHPs is to ensure food safety, they also influence an organization’s carbon footprint through reduced energy use and smart water consumption and optimized chemical applications. GHPs, when implemented with sustainability principles in mind, contribute to reducing the environmental impact without compromising food safety. GHPs provide materiality analysis as a directing tool used in sustainability and corporate responsibility to identify and prioritize factors that have a significant impact on the business performance, stakeholder interests, and regulatory compliance. Applying materiality analysis to GHPs involves assessing their dual importance in food safety assurance and carbon footprint mitigation. GFSI schemes support carbon footprint tracking, ensuring that supply chain partners comply with emission reduction targets. The FSMA aligns with U.S. sustainability initiatives, such as regenerative farming, and emphasizes local food sourcing to reduce emissions from long-distance transportation. EU food regulations require eco-labeling, helping consumers choose low-carbon, sustainably produced foods. Codex includes carbon footprint considerations in food trade regulations, supporting low-emission agricultural practices [47].

In line with the above, food production—particularly agriculture—contributes significantly to greenhouse gas emissions through land use change, livestock rearing, fertilizer application, and machinery use. The carbon footprint of food production depends on factors such as production methods, inputs, and transportation, and it contributes to climate change by releasing GHGs such as carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) into the atmosphere [48]. Climate change, in turn, affects food production through changes in temperature, precipitation patterns, and extreme weather events, leading to disruptions in agricultural productivity and food security. Addressing the carbon footprint of food production is, therefore, essential for promoting sustainable agriculture practices minimizing the environmental impact while ensuring food security and livelihoods [49].

Sustainable agriculture emphasizes resource efficiency, biodiversity conservation, soil health, and resilience to climate change, seeking to balance economic, social, and environmental objectives. Efforts to mitigate the carbon footprint of food production include improving agricultural practices, enhancing soil carbon sequestration, reducing fertilizer and pesticide use, increasing energy efficiency, and transitioning to low-carbon technologies [50]. These strategies can help mitigate GHG emissions, enhance carbon storage, and promote environmental sustainability in food systems [51]. Consequently, the relevant sector standard for mitigating the carbon footprint in this context is ISO 14067:2018 [48].

Indeed, the comprehensive ISO 14060 series aims to clarify and standardize the measurement, tracking, declaration, and authentication or confirmation of GHG emissions or removals, thereby fostering sustainable development in low-carbon economies [52]. ISO 14064-1 guides organizations in quantifying and reporting GHG emissions and removals, encompassing the principles, prerequisites, and guidelines for conducting GHG inventories. This involves delineating boundaries, selecting emission sources, quantifying emissions, and reporting outcomes. ISO 14064-1 is applicable to organizations of various sizes and types [25]. ISO 14064-2 focuses on GHG projects, detailing how to quantify, monitor, and report emission reductions or enhancements achieved through specific projects. It sets requirements for project design, establishing baselines, monitoring, reporting, and verification. ISO 14064-2 is especially pertinent for organizations implementing GHG reduction projects, such as those related to renewable energy or energy efficiency enhancements [26]. ISO 14064-3 sets requirements and guidance for the validation and verification of GHG assertions, spanning GHG inventories and project emission reductions. It delineates the roles and responsibilities of validators and verifiers, along with the procedures and criteria for validation and verification activities. ISO 14064-3 aims to ensure the trustworthiness, precision, and openness of GHG information reported by organizations and projects [27].

Finally, ISO 14067 specifies principles, prerequisites, and guidelines for quantifying and communicating the carbon footprint of products, encompassing goods and services. It applies to all organizations engaged in product production, distribution, and consumption, regardless of the size, sector, or location. This standard outlines methodologies and procedures for computing the carbon footprint of products across their life cycles, covering stages such as raw material extraction, production, transportation, use, and disposal or recycling. It provides guidance on data collection, emission factors, allocation methods, and calculation tools to ensure consistency and accuracy in carbon footprint assessments. ISO 14067 necessitates defining a functional unit for the product, serving as a benchmark for comparing different products and assessing their carbon footprints relative to their intended purpose. The standard also specifies the system boundary for carbon footprint assessments, requiring organizations to justify their choices regarding included or excluded life-cycle stages or emission sources based on relevance, materiality, and consistency with established methodologies. ISO 14067 offers guidance on the allocation of GHG emissions among co-products or multi-functional processes within the product system, recommending transparent and scientifically sound allocation methods while emphasizing the importance of data quality and uncertainty assessment in carbon footprint calculations. Furthermore, ISO 14067 calls for the clear, transparent, and understandable communication of carbon footprint results to stakeholders, promoting informed decision making and sustainable consumption and production patterns [48].

The WEFE Nexus involves complex interdependencies among four key elements, requiring the effective management of trade-offs, balancing competing demands, setting priorities, and integrating multiple factors. MCDA methods help in analyzing different criteria and engaging multiple stakeholders. Uncertainties make the decision-making process challenging. Fuzzy logic can incorporate the uncertainties to a certain extent and thus improve the analysis. Participatory decision making can be achieved by involving multiple stakeholders and aggregating their preferences in order to reach an acceptable solution. For example, it is possible to analyze different scenarios [53], define priorities by quantifying impacts [54], assess vulnerabilities [55], and identify obstacles [56].

In similar research, one noteworthy study examines decarbonization strategies at the facility level, evaluating and comparing them using MCDA [57]. Additionally, other studies provide a systematic review of MCDA techniques for food sector sustainability in a comprehensive yet detailed manner [58]. These studies reveal a gap in the application of system standards that could regulate low-carbon development in food system sustainability more closely, motivating the methodological approach presented here.

In conclusion, in terms of food safety requirements, ISO 22000:2018 requires the establishment of a Food Safety Management System (FSMS). In terms of standardization, carbon footprint management is detailed in ISO 14067:2018. However, what is common to these standards is that they do not offer methods for selecting priority measures (although they define the obligation to plan and define goals—for instance, organizations must establish procedures to manage food safety hazards during production, storage, and distribution, but there is no guidance on how to identify the procedure priorities). Therefore, in the decision-making phase, it is preferable to establish straight decision-making mechanisms, given in the section below through the proposed MCDA method.

3. Materials and Methods

For the purpose of this research, a comprehensive literature review was conducted, coupled with relevant standards’ requirements analysis and the use of ISO survey data [59]. Initial ISO survey data were used to assess the level of standardization in Balkan countries, with the addition of two new indicators: number of ISO 22000 certificates per one billion GDP (Gross Domestic Product) (Cert/BGDP) and number of ISO 22000 certificates per one hundred thousand inhabitants (Cert/kinh) [60,61]. A similar approach in the creation of derived meta-indicators appears in recent literature [62]. This involved consolidating pertinent academic literature related to the Water–Energy–Food–Ecosystem (WEFE) Nexus and consulting online databases. Additionally, a comparative analysis of the implementation rate of various system standards at the global level was also performed, using ISO Survey data to quantify total certificates [63].

The second part of this research aims to provide a descriptive analysis of the ISO 22000:2018 system standard requirements and their connections with the WEFE Nexus approach, food safety, and environmental aspects. Given that ISO 22000:2018 focuses on producing food that is safe for human health while also establishing mutually beneficial relationships with stakeholders and encouraging environmentally responsible operations, ISO 14067:2018 was identified as a complementary standard in the context of carbon footprint and GHG management.

What is common to all system standards, including ISO 14067:2018, is the fact that these types of standards provide a robust conceptual framework and standardized, highly traceable procedures. The requirements are clearly definable, obliging the organization to set a relevant policy, analyze the pertinent aspects (in the case of ISO 14067, the carbon footprint), conduct a planning process, and define the methods, resources, and activities needed to achieve the desired goals.

However, these system standards do not define a methodology for selecting priority goals regarding carbon footprint mitigation. Therefore, to prioritize and analyze the influence of different alternatives, a multi-criteria decision-making method was applied in [64]. A defined decision-making hierarchy in the selection of priority areas of carbon footprint mitigation was created with reference to the requirements of ISO 22000:2018, ISO 14067:2018, as well as the guidelines of the Best Available Techniques Reference (BREF) document for the production of food, drink, and milk, which is excellent at identifying environmental risks in the food production process. By establishing industry benchmarks for the environmental performance, the BREF document helps food producers comply with regulations, reduce their carbon footprint, and adopt best practices for food safety and sustainability. It provides technical recommendations for reducing the environmental impact while ensuring food safety and efficiency. The BREF document also outlines best practices for energy efficiency and decarbonization in food production, helping industries transition to carbon-neutral operations. However, among the many recommended techniques, there is no guideline on how to select priority sectors, which also highlights the need for multi-criteria decision making [65].

The created hierarchical decision-making model represents a unique combination of the requirements of one system and one technical standard as well as one BREF document, properly following the integrative nature of the WEFE Nexus approach [66,67]. Considering the importance of the input data, adequate online surveys were used. The relevant institutions that observe the standardization process primarily include the International Standard Organization (ISO) and the International Accreditation Forum (IAF), followed by the European Committee for Standardization (CEN) and the Organization for Economic Co-operation and Development (OECD).

When determining priorities, the following procedure is applied. First, an initial hierarchical structure is proposed based on the problem analysis and experts are contacted. By confirming their participation, experts provide data on their experience. They either accept the initial hierarchy or suggest changes. Based on the collected data, experts’ influence in the process of setting priorities is determined. The influence of expert i is described by the coefficient θ_i, which is calculated based on the expert’s work experience (e_i), experience in food production (f_i), and sustainability in general (s_i) as follows:

$${\theta }_i={\displaystyle \frac{f_i\times e_i\times s_i}{{\sum }_{j=1}^n{f}_j\times e_j\times s_j}},$$

(1)

where n is the total number of experts (1 ≤ i ≤ n), while f_i, f_j, e_i, e_j, s_i, and s_j are elements of the set {1,3,5}, which represent quantitative values of the experts’ experience [28]. A value of 5 represents more than 10 years of experience, while a value of 1 represents a maximum of 5 years of experience.

The analytic hierarchy process is used for ranking. It is applied in the fuzzy domain, using triangular fuzzy numbers [68]. The structure of the problem, which is reflected in the organization of criteria, factors, and indicators, led to the application of AHP-like methods. Previous experience with AHP methods in group ranking has shown that some experts have difficulty comparing alternatives using crisp values. Some of them find it easier to select a fuzzy number, described by a term or a linguistic variable, defining a range of values. This approach incorporates uncertainty into the decision-making process, allowing for greater tolerance compared to requiring an expert to select a crisp value. The standard fuzzified Saaty scale is used, with values from (1,1,3) to (7,7,9) for describing experts’ preferences. Experts could also use numbers with fuzzy distance δ = 1.

Aggregation of individual preferences of experts is conducted at each level using the row geometric mean method. The aggregation is based on individual assessments of experts and their experience. For a given pairwise comparison matrix of expert k, which compares n alternatives, the matrix is represented as follows:

$$B^{\left(k\right)}={\left[{\tilde{b}}_{ij}^{\left(k\right)}\right]}_{nxn}.$$

(2)

Using the coefficient of experience θ_k, determined from Equation (1), the elements of the aggregate matrix for m experts are determined as follows:

$${\tilde{b}}_{ij agg}={\left({\tilde{b}}_{ij}^{\left(1\right)}\right)}^{\theta 1}·\dots ·{\left({\tilde{b}}_{ij}^{\left(k\right)}\right)}^{\theta k}·\dots ·{\left({\tilde{b}}_{ij}^{\left(m\right)}\right)}^{\theta m}.$$

(3)

The fuzzy weight of an individual element is calculated from the aggregate matrix as

$${\tilde{\omega }}_{j }={\left({\prod }_{k=1}^n{\tilde{b}}_{ik agg}\right)}^{{\displaystyle \frac{1}{n}}}/\left({\sum }_{i=1}^n{\left({\prod }_{k=1}^n{\tilde{b}}_{ik agg}\right)}^{{\displaystyle \frac{1}{n}}}\right),$$

(4)

where n is the number of compared elements (j = 1, ..., n), while ${\tilde{b}}_{ik agg}$ represents the elements of the aggregate matrix consisting of fuzzy numbers. Aggregation is considered acceptable if the centric consistency index (CCI) is below 0.35 for four elements or below 0.37 for matrices of larger dimensions [64].

Defuzzification of the fuzzy weight ${\tilde{\omega }}_k=\left({\omega }_1,{\omega }_2,{\omega }_3\right)$ is performed by calculating the mean value

$${\omega }_k=\left({\omega }_1+{\omega }_2+{\omega }_3\right)/3,$$

(5)

followed by normalization

$${{\omega }_k}^{*}={\omega }_k/\left({\sum }_{l=1}^n{\omega }_l\right),$$

(6)

where n is the number of compared elements (k = 1, ..., n).

4. Results and Discussion

Table 1. System standards: number of certificates, sites, and share of each standard.

Standard	Total Valid Certificates	Total Number of Sites	% of Total Certificates	% of Total Sites
ISO 9001:2015	1,265,216	1,666,172	52.57	51.28
ISO 14001:2015	529,853	744,428	22.02	22.91
ISO 45001:2018	397,339	512,069	16.51	15.76
ISO IEC 27002:2013	71,549	120,128	2.97	3.70
ISO 22000:2018	45,459	51,535	1.89	1.59
ISO 13485:2016	29,543	40,208	1.23	1.24
ISO 50001:2018	27,765	53,703	1.15	1.65
ISO 20000-1:2018	27,009	29,616	1.12	0.91
ISO 37001:2016	5969	12,837	0.25	0.40
ISO 22301:2012&2019	3200	10,658	0.13	0.33
ISO 39001:2012	1550	3662	0.06	0.11
ISO 55001:2014	997	2449	0.04	0.08
ISO 28000:2007	521	973	0.02	0.03
ISO 20121:2012	247	526	0.01	0.02
ISO 29001:2020	177	253	0.007	0.008
ISO 44001:2017	118	166	0.005	0.005
Sum	2,406,512	3,249,383	100	100

displays the quantitative data on the total count of certificates issued annually (the year 2022 in this case) for all system standards covered by the ISO survey (a total of 16 in 2022), sourced from the International Accreditation Forum (IAF) and available as ISO survey documents (also available as Supplementary Materials) [59]. Additionally, it presents the percentage distribution of individual system standards relative to the overall count of issued certificates across all system standards. Similarly, an examination of the number of registered locations where these certificates are utilized is provided as a percentage share. The variance between the number of issued certificates and the places of application arises due to the possibility of one economic entity possessing a single certificate applicable across multiple locations or work units.

The analysis of the data presented in Table 1 shows that the so-called key system standards have the largest number of confirmed certificates in 2022, namely ISO 9001 (about 52%), ISO 14001 (about 23%), and ISO 45001 (about 16%), and that together they make up 90% of all certified certificates. Another interesting fact is that these standards often form the basis of most integrated management systems.

Considering the fact that standardization follows trends in society and the economy, it is not surprising that ISO 27001 is represented by approximately 3% of the total certificates issued in 2022. Concerning the WEFE Nexus and the safe food production system, the share of the total number of issued ISO 22000 certificates is almost 2%, with a steady growth trend, which indicates the relevance of this standard.

Similarly, Figure 1 shows the world’s ten leading countries in issued certificates while Figure 2 shows the distribution of ISO 22000:2018 certificates among Balkan countries.

Regarding the number of certificates issued by the countries of the world, it is interesting to note that there is a pronounced difference between the two most populous countries in the world, China and India, since the number of issued certificates is six times higher in China (18,970 versus 3094). In addition to this non-compliance, it is interesting that Japan, South Korea, and Taiwan have a significant number of registered certificates, while from Europe, Greece and Italy are among the ten countries with the largest number of certificates issued. It is also worth noting that the countries that are considered as synonyms for quality (Germany, France, Great Britain, USA, etc.) are not ranked among the top ten countries.

Regarding the number of ISO 22000 certificates issued among Balkan countries, Greece takes the first place with by far the largest number of certificates, followed by Romania, Bulgaria, and Hungary. Interestingly, Serbia and North Macedonia, although not members of the EU, have a respectable number of registered certificates, while Croatia and Slovenia, as members of the EU, do not have a large number of issued certificates. Somewhat unexpectedly, Montenegro and Bosnia and Herzegovina are at the bottom of the list.

Given that the nominal number of certificates issued provides only a rough insight into the level of standardization in a specific field, for the purpose of a more detailed assessment of the intensity of standardization and for the purpose of this paper, two new meta-indicators were created, specifically the number of issued certificates per one billion GDP (Cert/BGDP) and the number of issued certificates per one hundred thousand inhabitants (Cert/100 kinh). GDP and population data were taken from the Eurostat databases. After creating new indicators and applying them to the Balkan countries, it is possible to conclude the following (Figure 3):

• Greece is the absolute leader in the field of standardization, with 6.85 Cert/BGDP and 13.80 Cert/100 kinh, followed by Romania, Bulgaria, and Hungary, creating the same order as in the example of the total number of certificates issued.
• It is interesting to note that, for Serbia and North Macedonia, a difference can be observed in the comparison between the total number of certificates issued and the number of certificates issued. Namely, North Macedonia has more certificates issued per one billion GDP than Serbia (4.71 vs. 3.1), as well as more certificates issued per one hundred thousand inhabitants (3.10 vs. 2.80). A similar difference is observed between Albania and Croatia (1.91 vs. 0.55) or Montenegro and Slovenia (1.53 vs. 0.32).

Based on the given analyses, it is possible to conclude that there is a significant but non-linear correlation between the number of certificates issued and the development of the national economy, i.e., the population number in a specific country. This confirms the view that the intensity of standardization is the result of several factors, starting from the development and diversification of the economy, historical heritage, quality culture, international connections, as well as stimulation and incentives in the field of standardization.

The performed analysis points to the fact that there is a well-developed practice of applying standards for the production of health-safe food (a typical example is Greece) and that it is necessary to think about a harmonized decision-making model in the context of creating a balance between the requirements for the production of health-safe food and the minimization of the carbon footprint, wherein the following MCDA decision-making model should be seen as a proactive component.

The proposed ISO 22000/ISO 14067-balanced hierarchical structure consists of three levels, as shown in

Table 2. Influential criteria, factors, and alternatives in sustainable food production addressing carbon footprint management.

Criteria	Factors	Alternatives
C1: Environment C2: Society C3: Economy	F1: Production (P)	Land use (P1), Crop diversity (P2), Fertilizers (P3), Pesticides (P4)
	F2: Transport (T)	Distance (T1), Route options (T2), Fuel usage (T3), Machinery (T4)
	F3: Processing (PR)	OHS (PR1), Emission to water (PR2), Emission to air (PR3), Processing waste (PR4), Noise/odors (PR5)
	F4: Storage (S)	Warehouse (S1), Cooling and heating (S2), Package (S3), Internal transport (S4)
	F5: Waste/Disposal (WD)	Collection (WD1), Transport (WD2), Treatment and reuse (WD3), Disposal (WD4)

. Factors at the second level influence each individual criterion at the first level, while the alternatives describe the individual factors in more detail. The criteria were defined based on the requirements of the ISO 22000/ISO 14067 standards, the influencing factors were determined by reviewing the additional requirements of the BREF document for the production of food, drink, and milk, while the alternatives were selected in iterative consultative sessions with involved experts. Concerning the selected factors, it is important to point out the following aspects. Food production, whether organic or conventional, serves as the fundamental stage in the food supply chain. Sustainable agricultural practices focus on reducing GHG emissions, improving soil health, and conserving biodiversity. Therefore, the following alternatives have been defined: land use, crop diversity, and fertilizers and pesticides. The transportation of food products contributes significantly to the carbon footprint of the food industry. Logistic strategies must balance efficiency with sustainability, as food often travels large distances from the farm to consumer. In this case, suitable alternatives include distance, route options, fuel usage, and machinery. Food processing involves various stages, including cleaning, sorting, packaging, and preserving, all of which require energy and resources. Carbon-responsible processing hinges on optimizing energy use, minimizing waste, and utilizing eco-friendly packaging materials. Here, suitable alternatives include Occupational Health and Safety (OHS), emissions to water, emissions to air, processing waste, and noise/odors. Proper food storage is essential to reducing food waste and maintaining product quality. Cold storage, refrigeration, and controlled-atmosphere storage contribute to substantial energy consumption, making energy-efficient technologies critical for sustainability and carbon neutrality. Consequently, fitting alternatives include warehouses, cooling and heating, package, and internal transport. Waste management and disposal are vital factors in carbon responsibility. Additionally, consumer awareness campaigns and policy interventions are instrumental in reducing food waste, reinforcing the accountability of both producers and consumers in sustainable food systems. Therefore, satisfactory alternatives include collection, transport, treatment and reuse, and disposal. In real life, the factors and alternatives defined in this way enable long-term planning and a visionary approach to developing carbon-sensitive policies based on the common requirements of ISO 14067 and ISO 22000.

Five experts participated in determining the weights of influential criteria and factors. The group of experts was created to reflect the views of various stakeholders, so it included an expert from the regional administration (policy), an expert from the chamber of commerce (economy), an expert from a large production chain (production), an expert from an association of small producers (society), as well as an expert in the field of certification of standard requirements (knowledge). They have extensive experience in both the scientific and practical study of the analyzed problems. Thanks to the role of the Innovation Center of the University of Niš, which represents the link between higher education, research, and business, experts with undoubted experience in this issue were engaged. Consultations with experts implied immediate work in the premises of the center. Their influence on the final decision is defined by the set Θ = {0.12,0.18,0.18,0.26,0.26}. These values were determined based on Equation (1) and the following vectors that describe the experts’ experience: F = {2,2,2,3,3}, E = {2,2,2,2,2}, and S = {2,3,3,3,3}.

All expert matrices were consistent, and the CCI index for group decision making had acceptable values [64]. According to Equation (3), the aggregate matrix for the criteria was

$$C=\left[\begin{array}{ccc}(\mathrm{1,1},1)& \left(\mathrm{0.74,1.64,1.99}\right)& \left(\mathrm{0.62,1.37,2.21}\right)\\ \left(0.50, \mathrm{0.61,1.35}\right)& \left(\mathrm{1,1},1\right)& \left(\mathrm{0.56,0.69,1.68}\right)\\ \left(\mathrm{0.47,0.73,1.62}\right)& \left(\mathrm{0.60,1.44,1.79}\right)& \left(\mathrm{1,1},1\right)\end{array}\right],$$

(7)

on the basis of which the fuzzy weights of criteria w_C1 = (0.18, 0.43, 0.78), w_C2 = (0.18, 0.43, 0.78), and w_C3 = (0.18, 0.43, 0.78) were determined using Equation (4). The crisp values of criteria weights, obtained by defuzzification (Equations (5) and (6)), are presented by vector W_C = {0.386, 0.287, 0.327}.

The elements of aggregate matrices of factors in relation to the criteria (C_i) and fuzzy weights (FWs) are shown in

Table 3. Influential criteria and factors in sustainable food production.

C1	F1	F2	F3	F4	F5	FWs
F1	(1,1,1)	(0.89,1.64,2.56)	(0.68,1.39,2.04)	(1.08, 2.07,3.55)	(0.62,0.94,1.85)	(0.10,0.26,0.61)
F2	(0.39,0.61,1.12)	(1,1,1)	(0.45,0.82,1.34)	(0.82,1.47,2.47)	(0.37,0.62,1.11)	(0.07,0.16,0.40)
F3	(0.49,0.72,1.47)	(0.75,1.23,2.24)	(1,1,1)	(1.01,1.66,2.99)	(0.37,0.70,1.11)	(0.08,0.19,0.48)
F4	(0.28,0.48,0.92)	(0.40,0.68,1.21)	(0.33,0.60,1.01)	(1,1,1)	(0.32,0.49,0.93)	(0.05,0.12,0.30)
F5	(0.54,1.06,1.62)	(0.90,1.62,2.67)	(0.90,1.44,2.67)	(1.07,2.04,3.16)	(1,1,1)	(0.11,0.27,0.61)
C2	F1	F2	F3	F4	F5	FWs
F1	(1,1,1)	(0.62,1.20,1.85)	(0.54,1.29,1.78)	(0.69,1.10,2.20)	(0.48,0.92,1.54)	(0.08,0.22,0.52)
F2	(0.54,0.83,1.62)	(1,1,1)	(0.49,0.78,1.47)	(0.51,0.87,1.74)	(0.52,0.88,1.75)	(0.07,0.17,0.48)
F3	(0.56,0.77,1.85)	(0.68,1.28,2.04)	(1,1,1)	(0.35,0.73,1.14)	(0.46,0.81,1.74)	(0.07,0.18,0.48)
F4	(0.45,0.91,1.45)	(0.57,1.15,1.97)	(0.88,1.37,2.88)	(1,1,1)	(0.47,1.01,1.45)	(0.08,0.21,0.53)
F5	(0.65,1.09,2.07)	(0.58,1.16,1.98)	(0.57,1.23,2.16)	(0.69,1.01,2.13)	(1,1,1)	(0.08,0.22,0.58)
C3	F1	F2	F3	F4	F5	FWs
F1	(1,1,1)	(0.51,0.94,1.52)	(0.54,1.18,1.44)	(0.88,1.01,2.64)	(1.00,1.39,3.00)	(0.10,0.22,0.54)
F2	(0.66,1.06,1.97)	(1,1,1)	(0.54,0.83,1.62)	(0.75,1.28,2.24)	(0.75,1.60,2.69)	(0.09,0.22,0.55)
F3	(0.69,0.84,1.87)	(0.62,1.20,1.85)	(1,1,1)	(0.69,0.95,1.87)	(0.79,1.30,2.37)	(0.09,0.21,0.53)
F4	(0.38,1.00,1.14)	(0.45,0.78,1.34)	(0.54,1.05,1.44)	(1,1,1)	(0.75,1.45,2.38)	(0.07,0.21,0.43)
F5	(0.33,0.72,1.00)	(0.37,0.63,1.34)	(0.42,0.77,1.27)	(0.42,0.69,1.34)	(1,1,1)	(0.06,0.15,0.36)

.

Based on the fuzzy weights of the factors, according to Equations (4)–(6), the following crisp weights were determined: WF = {0.229, 0.191, 0.201, 0.168, 0.212}.

The elements of the matrix of alternatives in relation to the criteria are shown in

Table 4. Elements of matrices of alternatives in relation to criteria, fuzzy weights, and global weights of alternatives.

F1	P1	P2	P3	P4		FWs
P1	(1,1,1)	(1.13,1.98,3.16)	(0.74,1.83,2.37)	(0.88,1.82,3.02)		(0.15,0.38,0.81)
P2	(0.32,0.51,0.88)	(1,1,1)	(0.54,1.00,1.62)	(0.68,0.94,2.04)		(0.09,0.20,0.49)
P3	(0.42,0.54,1.35)	(0.62,1.00,1.85)	(1,1,1)	(0.51,0.94,1.52)		(0.10,0.20,0.52)
P4	(0.33,0.55,1.14)	(0.49,1.06,1.47)	(0.66,1.06,1.97)	(1,1,1)		(0.09,0.21,0.50)
wPi	0.080	0.048	0.051	0.049
F2	T1	T2	T3	T4		FWs
T1	(1,1,1)	(0.38,0.65,1.14)	(0.31,0.55,0.83)	(0.88,1.00,2.64)		(0.09,0.19,0.46)
T2	(0.88,1.53,2.64)	(1,1,1)	(0.40,0.69,1.21)	(1.00,1.53,3.00)		(0.12,0.28,0.64)
T3	(1.20,1.82,3.24)	(0.82,1.44,2.47)	(1,1,1)	(0.75,1.28,2.24)		(0.15,0.33,0.75)
T4	(0.38,1.00,1.14)	(0.33,0.65,1.00)	(0.45,0.78,1.34)	(1,1,1)		(0.08,0.21,0.40)
wTi	0.039	0.054	0.063	0.035
F3	PR1	PR2	PR3	PR4	PR5	FWs
PR1	(1,1,1)	(0.33,0.49,1.14)	(0.31,0.55,0.83)	(0.35,0.49,0.84)	(1.00,1.39,3.00)	(0.06,0.13,0.35)
PR2	(0.88,2.05,3.02)	(1,1,1)	(0.54,1.20,1.62)	(0.75,0.94,2.24)	(1.00,2.31,3.59)	(0.10,0.26,0.62)
PR3	(1.20,1.82,3.24)	(0.62,0.83,1.85)	(1,1,1)	(0.56,0.78,1.68)	(1.14,2.25,3.82)	(0.10,0.23,0.62)
PR4	(1.19,2.02,2.88)	(0.45,1.06,1.34)	(0.60,1.28,1.79)	(1,1,1)	(1.20,2.79,4.31)	(0.10,0.28,0.59)
PR5	(0.32,0.73,1.00)	(0.28,0.43,1.00)	(0.26,0.40,0.88)	(0.23,0.36,0.83)	(1,1,1)	(0.04,0.10,0.28)
wPRi	0.030	0.054	0.053	0.051	0.024
F4	S1	S2	S3	S4		FWs
S1	(1,1,1)	(0.33,0.59,1.14)	(0.31,0.66,0.83)	(0.66,1.00,1.97)		(0.08,0.19,0.43)
S2	(0.88,1.71,3.02)	(1,1,1)	(0.54,1.00,1.62)	(1.00,2.05,3.43)		(0.13,0.33,0.74)
S3	(1.20,1.51,3.24)	(0.68,1.28,2.04)	(1,1,1)	(0.35,0.73,1.14)		(0.14,0.31,0.78)
S4	(0.51,1.00,1.52)	(0.29,0.49,1.00)	(0.29,0.59,1.00)	(1,1,1)		(0.07,0.18,0.41)
wSi	0.031	0.054	0.056	0.029
F5	WD1	WD2	WD3	WD4		FWs
WD1	(1,1,1)	(0.38,0.65,1.14)	(0.33,0.61,1.00)	(0.37,0.55,1.01)		(0.08,0.17,0.38)
WD2	(0.88,1.53,2.64)	(1,1,1)	(0.40,0.83,1.21)	(0.46,0.78,1.38)		(0.10,0.24,0.53)
WD3	(1.00,1.63,3.00)	(0.82,1.20,2.47)	(1,1,1)	(0.62,0.83,1.85)		(0.14,0.28,0.70)
WD4	(0.99,1.82,2.67)	(0.72,1.28,2.17)	(0.54,1.20,1.62)	(1,1,1)		(0.13,0.31,0.64)
wWDi	0.035	0.049	0.064	0.059

.

Expert ranking yielded the following results. Among the criteria, the environment (w_C1 = 0.386) stands out as the most important, followed by society (w_C2 = 0.287) and economy (w_C3 = 0.327). The factors have very close weight values, viewed collectively in relation to all three criteria. Among the factors, production (w_F1 = 0.229), waste/disposal (w_F5 = 0.212), and processing (w_F3 = 0.201) are more prominent. Comparing a number of alternatives in relation to factors and criteria can lead to the fact that if the factor is not dominant and the alternatives have similar importance, their overall importance for sustainable food production will be much lower than the real impact. Therefore, without diminishing the importance of the global ranking, we highlighted alternatives in relation to each individual influencing factor.

In relation to factor F₁, an alternative P₁ (land use) with weight w_P1 = 0.080 has the greatest importance. In relation to factor F₂, the experts highlighted the importance of alternatives T₂ (route options) and T₃ (fuel usage), with weights w_T2 = 0.053 and w_T3 = 0.062.

Regarding factor F₃, described by five alternatives, PR₂ (emission to water), PR₃ (emission to air), and PR₄ (processing waste) were highlighted as particularly significant alternatives, with weights w_PR2 = 0.054, w_PR3 = 0.053, and w_PR4 = 0.051, respectively. With regard to factor F₄, the experts identified S₂ (cooling and heating) and S₃ (package) as key alternatives, with weights of w_S2 = 0.054 and w_S3 = 0.056. Finally, a very significant factor for sustainable food production is F₅, with particularly prominent alternatives WD₃ (treatment and reuse) and WD₄ (disposal), and their weights w_wd3 = 0.064 and w_wd4 = 0.059.

The difference between the individual weights of the alternatives, viewed globally, is small. Sensitivity to changes in weights is much more pronounced globally than locally, as observed within individual groups of alternatives, where there are always dominant alternatives.

One of the most significant outcomes of the conducted MCDA is the derivation of weights that quantify the relative importance of each identified criterion, factor, or alternative. The analysis shows that energy-intensive production processes (production, processing, waste/disposal) carry greater weight than transport and storage due to their substantial contribution to GHG emissions. The practical significance of these weights lies in their ability to inform decision making by providing a structured rationale for prioritization. In carbon footprint management, weighted indicators enable policymakers and industry leaders to implement targeted mitigation strategies, such as optimizing transportation logistics or adopting renewable energy sources, to reduce the overall emissions effectively. On the example of an alternative P₁ (land use), it has the greatest importance with a weight of w_P1 = 0.080, which means that sustainable, carbon-neutral land use is a critical component of the future of food production. With regard to the aforementioned ecolabeling, this information can lead to a consumer demand for sustainably produced food that can drive industry-wide shifts toward carbon-neutral land use.

By incorporating MCDA into food safety and carbon footprint management, decision makers benefit from a transparent, evidence-based approach that enhances the efficiency of risk mitigation and sustainability efforts. The structured evaluation of multiple criteria ensures that decisions are not based solely on intuition, but are backed by a rigorous quantitative and qualitative analysis, ultimately contributing to safer food systems and a lower environmental impact.

In terms of certain limitations of this study, if there is a need for more precise metrics and quantification of performance related to meeting the requirements of both analyzed standards (ISO 22000 and ISO 14067), organizations should implement another complementary standard, in this case ISO 14031:2021. ISO 14031:2021 details how organizations can evaluate their environmental performance using key indicators. This evaluation is vital for safe and carbon-neutral food production, as it enables producers to systematically assess and reduce their environmental footprint while ensuring compliance with food safety regulations. ISO 14031:2021 emphasizes the use of Environmental Performance Indicators (EPIs), Operational Performance Indicators (OPIs), and Management Performance Indicators (MPIs). EPIs represent metrics of environmental aspects such as energy consumption, emissions, and waste management. OPIs indicate factors related to internal processes, including sustainable land use and carbon emissions from transport and storage, followed by pesticide pollution control. MPIs refer to indicators assessing policy effectiveness, regulatory compliance, and organizational strategies for environmental sustainability. By enabling a systematic environmental performance evaluation based on ISO 14031:2021 EPIs, OPIs, and MPIs, organizations ensure that food production aligns with sustainability goals while maintaining high safety standards [69].

5. Conclusions

This paper has presented research on the integrative nature of the WEFE Nexus approach that may be observed from different perspectives, namely standardization, carbon neutrality, and safe food production. The fact is that there is no harmonized implementation model of the WEFE Nexus approach, and thus no appropriate metric of the performance of Nexus actions at different levels. This can be replaced by an analysis of the degree of standardization in different fields, which is illustrated in the first part of this paper. A critical review of the combination of applied methods lays the foundation for improving the used model and for considering limitations. The basic flaw in the system standards intended for the production of health-safe food is an excessive focus on the delivery of a health-safe product, with little or no reference to the environmental aspects. As standardization in itself, especially in the domain of system standards, enables the integration of the requirements of several standards into a single integrated management system, it is desirable in the future to always recommend the integration of the requirements of ISO 22000 and ISO 14067, with the possibility of including ISO 14090. This is very important to consider because of the fact that for most researchers and other stakeholders, integration implies the inclusion of ISO 9001, 14001, or 45001 standards only. In addition, as there are no instructions for the selection of priorities in the requirements of system and sector standards, the proposed MCDA model is an appropriate scientific and professional step forward. In the context of objective decision making as well as the sustainability of defined decisions, the engagement of a larger number of experts from different backgrounds enables an additional level of compliance, diverse capacity, and flexibility–adaptability in the decision-making process. Relevant to the research topic, by viewing the food production process as part of a larger system, stakeholders can identify feedback loops, interdependencies, and potential unintended consequences of decisions. The integration of all these concepts—systems thinking, resilience, resource management, food safety (ISO 22000), and multi-criteria decision making—creates a synergistic approach to addressing modern food production challenges. Together, they allow stakeholders to design adaptive, sustainable, and safe food systems that not only meet present demands, but also preserve resources and resilience for future generations.

However, there are limitations and threats that can affect the effective implementation of this approach. Various systemic and structural challenges hinder joint ISO 22000 and ISO 14067 implementation, particularly in terms of financial constraints, policy resistance, and regional governance issues. These factors create barriers that impact compliance, operational efficiency, and long-term sustainability in food production and supply chains. One of the primary challenges in applying both ISO 22000 and ISO 14067 is the financial burden associated with certification, process optimization, and compliance. Organizations, particularly small and medium-sized enterprises (SMEs), often struggle to allocate resources for achieving food safety while also minimizing their carbon footprint. This often necessitates advanced processing technologies, sustainable sourcing, and efficient waste management systems, triggering investments that demand substantial capital. From the policy perspective, despite the growing awareness of sustainable food production, policy resistance poses a significant challenge to the simultaneous application of ISO 22000 and ISO 14067. This resistance stems from several factors. Food safety policies often prioritize hazard prevention and hygiene, while carbon footprint standards focus on supply chain emissions and environmental sustainability. In some jurisdictions, regulatory bodies may not fully integrate these objectives, creating conflicting compliance requirements. Policymakers and industry stakeholders may prioritize food security and economic stability over sustainability efforts, particularly in regions where food production is a key economic driver. This can lead to resistance against environmental regulations that increase production costs. From the regional governance outlook, the successful application of both standards depends on effective governance structures at the regional and national levels. Regional food supply chains involve multiple stakeholders operating under different regulatory environments. Variations in governance structures create inconsistencies in compliance, making it difficult to achieve a uniform adoption of ISO 22000 and ISO 14067. In some regions, regulatory bodies lack the resources to monitor compliance, conduct audits, and enforce penalties, leading to the uneven implementation of food safety and environmental standards. In some cases, political and trade priorities influence standard adoption. Export-oriented economies may be more likely to implement ISO 22000 to meet international food safety requirements, while local environmental policies related to the carbon footprint may not be as strictly enforced. These conflicts arise from differing objectives and regulatory considerations, making it difficult to create a unified approach that satisfies all parties. Governments often focus on export competitiveness and agricultural GDP growth, which may lead to policies that encourage intensive farming practices and large-scale production. These approaches, while improving food availability and compliance with ISO 22000, can contradict sustainability goals. For instance, industrialized food production, driven by the need to meet food safety and production efficiency standards, often relies on high-input methods (e.g., fertilizers, pesticides, and mechanization) that increase carbon emissions. Balancing food safety (ISO 22000) with sustainability (ISO 14067) requires shifting toward agro-ecological practices, which can be expensive and technically challenging. On the other hand, small farmers and food producers must respond to consumer demand, which often prioritizes price and availability over sustainability. If consumers are unwilling to pay a premium for carbon-neutral or low-emission food, producers may deprioritize ISO 14067 implementation. Finally, the role of environmentalists is no less important. Environmentalists support organic farming, regenerative agriculture, and low-input methods, which may not align with large-scale food safety and production models. Environmental groups often push for mandatory carbon footprint reporting and reduction targets. While such policies support ISO 14067 objectives, they can be perceived as burdensome regulations that limit economic competitiveness and increase costs for food producers. These competing interests often create regulatory fragmentation, financial constraints, and resistance to change, making it difficult to achieve an integrated approach to food safety and environmental sustainability. Addressing these challenges requires a holistic policy approach, financial support mechanisms, and stronger international collaboration to create a balanced framework that prioritizes both food safety and environmental sustainability coupled with carbon responsibility. In this sense, the WEFE Nexus approach is increasingly recognized as an essential model for managing the complex trade-offs between water, energy, food, and ecosystem services in the transition to a low-carbon, climate-resilient economy. By fostering integrated resource management, promoting adaptive strategies, and aligning policy frameworks, the WEFE Nexus ensures that economic development and environmental sustainability can progress hand in hand, mitigating climate risks while securing essential resources for future generations. Climate policies often operate in silos, but the WEFE Nexus encourages cross-sectoral governance, aligning water, energy, and food policies with climate adaptation and mitigation goals.

Accordingly, from the standardization perspective, future research should focus on the elements of integrating the requirements of not only these two standards, but also others that are important for sustainability (namely ISO 14090 and ISO/TR 22370), while exploring a more suitable model that would satisfy the interests of as many stakeholders as possible. For example, in the current circumstances, it is impossible to deny the challenges of adapting to climate change as well as the need to strengthen the resilience of all key pillars of society, including food chains. Climate disruptions affect food production, transportation, and storage. ISO 14090 provides a framework for ensuring resilient supply chains, reducing food loss and contamination risks in compliance with ISO 22000. Some adaptation strategies (e.g., increased irrigation, energy-intensive cold storage) may reduce climate risks but increase carbon footprints. In such cases, ISO 14090 helps organizations balance climate adaptation with emissions reduction to meet ISO 14067 demands. ISO 14090 promotes climate-smart food practices, such as regenerative farming, which directly lower emissions and improve compliance with ISO 14067. Last but not least is the importance of resilience in such a system. The integration of ISO/TR 22370 (Security and Resilience–Urban Resilience–Framework and Principles) with ISO 22000 and ISO 14067 is pivotal for developing resilient and sustainable urban and peri-urban food systems. Urban areas, projected to house two-thirds of the global population by 2050, are central to economic growth and are significant consumers within food supply chains. Implementing ISO/TR 22370′s principles can enhance the resilience of urban and peri-urban food systems. By adopting the resilience framework outlined in ISO/TR 22370, urban and peri-urban areas can proactively prepare for and respond to disruptions in food supply chains, ensuring consistent access to safe food as mandated by ISO 22000. This framework also encourages urban stakeholders to implement practices that reduce the carbon footprint of food products, aligning with the objectives of ISO 14067. This includes supporting local food production and optimizing distribution networks to minimize emissions. With no less importance is the possibility of jointly considering the requirements of ISO 14001:2015 as well as ISO 50001:2018 standards in terms of the integrated management of all significant elements in the WEFE Nexus. Finally, given that the focus of this paper is on carbon footprint management in sustainable food production according to ISO 14067 requirements, future research should consider influential factors in the context of implementing the ISO 14046 standard, which establishes a framework for sustainable water footprint management.