Abstract
Purpose
Amidst compounding crises and increasing global population’s nutritional needs, food supply chains are called to address the “diet–environment–health” trilemma in a sustainable and resilient manner. However, food system stakeholders are reluctant to act upon established protein sources such as meat to avoid potential public and industry-driven repercussions. To this effect, this study aims to understand the meat supply chain (SC) through systems thinking and propose innovative interventions to break this “cycle of inertia”.
Design/methodology/approach
This research uses an interdisciplinary approach to investigate the meat supply network system. Data was gathered through a critical literature synthesis, domain-expert interviews and a focus group engagement to understand the system’s underlying structure and inspire innovative interventions for sustainability.
Findings
The analysis revealed that six main sub-systems dictate the “cycle of inertia” in the meat food SC system, namely: (i) cultural, (ii) social, (iii) institutional, (iv) economic, (v) value chain and (vi) environmental. The Internet of Things and innovative strategies help promote sustainability and resilience across all the sub-systems.
Research limitations/implications
The study findings demystify the structure of the meat food SC system and unveil the root causes of the “cycle of inertia” to suggest pertinent, innovative intervention strategies.
Originality/value
This research contributes to the SC management field by capitalising on interdisciplinary scientific evidence to address a food system challenge with significant socioeconomic and environmental implications.
Keywords
Citation
Alem Fonseca, M., Tsolakis, N. and Kittipanya-Ngam, P. (2024), "Breaking the cycle of inertia in food supply chains: a systems thinking approach for innovation and sustainability", Supply Chain Management, Vol. 29 No. 3, pp. 414-443. https://doi.org/10.1108/SCM-01-2023-0019
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited
1. Introduction
In the face of climate change and compound global risks, the world food supply chain (SC) system must sustainably and resiliently fulfil the dietary and nutritional needs of nearly 10 billion people by 2050 (Graziano Da Silva, 2021). Specifically, meat is elemental in human diets as it is the main source of protein, phosphorus, zinc and iron (Bohrer, 2017). However, overconsumption of meat is claimed to have the “greatest combined negative impact on environmental and human health” (Rust et al., 2020, p. 2).
Meat has a central role in humans’ diet, challenging food system sustainability in multiple ways (Graça et al., 2015; Pashaei Kamali et al., 2014). First, people overconsume protein in an accelerating trend (World Resources Institute, 2019). In the last 50 years, the average global animal-based food consumption has almost doubled (Bonnet et al., 2020). Global protein consumption exceeds the average daily requirement of 50 g per capita, whereas an unequal distribution of meat consumption is observed (Resare Sahlin and Trewern, 2022). In economically developed regions, more than half of protein consumption is animal-based, while in emerging economies, the daily protein requirements are primarily addressed by plant-based protein (World Resources Institute, 2019). However, meat consumption and respective protein intake volumes in the latter economies are expected to become fivefold compared to developed countries by the end of the decade (OECD and FAO, 2020).
Second, meat is a resource-intensive commodity that challenges the ability of the food sector to achieve sustainable development goals (SDGs) (Rust et al., 2020). From an environmental perspective, the meat, dairy and animal-based feedstock industries account for about 20% of greenhouse gas (GHG) emissions (SDG#13), as: “Beef and other ruminants also require more than 20 times more land and generate more than 20 times more GHG emissions than pulses per unit of protein consumed” (Ranganathan et al., 2016, p. 21). In this regard, amenable alternative sources of protein have been identified (e.g. pulses, fava beans, lentils) with associated nutritional, health and sustainability benefits (FAO, 2018, 2019); however, these are overlooked as staples and food ingredients in Western-style diets (van der Weele et al., 2019). Notably, by substituting 20% of the current global beef consumption with a meat substitute over the next three decades, it is possible to reduce deforestation and the corresponding carbon emissions by half (Guglielmi, 2022).
From a nutritional perspective, the protein content in meat can range from 15 to 32 g per 100 g and from 6.6 to 33 g in plant-based protein products (Ložnjak Švarc et al., 2022). Nonetheless, producing a kilogramme of meat requires 15,000 l of water (SDG#6), while 1,500 l are needed to produce a kilogramme of cereals (Graziano Da Silva, 2021). Furthermore, from a socioeconomic perspective, meat production could cause social issues such as the displacement of communities and social breakdown (SDG#1 and SDG#2) (Godfray et al., 2018). At the same time, meat overconsumption can contribute to human health issues (SDG#3), such as diabetes, obesity and cardiovascular incidents (Vega Mejía et al., 2018). Overall, the excessive production and consumption of meat food supplies pose a significant caution globally due to the associated environmental and human health ramifications (Saget et al., 2021).
Third, food SC system stakeholders share a prevalent “lack of urgency” in tackling the “diet–environment–health” trilemma (EAT-Lancet Commission, 2018). “Inertia” in this sense can be understood as the inability of stakeholders to act and address sustainability challenges associated with meat production and consumption (Kanerva, 2021). On the one hand, citizens and industrialists expect governments to act and promote sustainable diets (Froggatt, 2017). On the other hand, governments are reluctant to act in the absence of societal pressure whilst aiming to avoid potential public and industry-driven repercussions (McSweeney, 2015). The “limited precedent for intervention” perpetuates inaction as insufficient and inconclusive evidence around the efficacy of interventions exists (Wellesley et al., 2015). The paucity of scientific efforts on approaching and overcoming inertia is evident; confirmed by the low public awareness and policy initiatives on driving change in the food system towards sustainability and resilience. Indicatively, both the horse-meat incident in the UK and Ireland in 2013 (Smith and McElwee, 2021) and the disruptions experienced in the protein sector during the COVID-19 pandemic in 2020 (Do et al., 2021) serve as examples of the complex nature of meat SCs and how a heavy reliance on meat jeopardises food system resilience. These chains involve multiple stages of production and numerous intermediaries in comparison to the SCs of other sources of protein (e.g. plants), which makes ensuring transparency and traceability more challenging (Stone and Rahimifard, 2018). To illustrate this complexity further, recent investigations have exposed concerning links between meat products sold in Tesco stores and illegal fires and deforestation, resulting in the loss of 400 hectares of the Brazilian Amazon rainforest (Mitchell, 2023).
In this research, the object of scrutiny is meat-based protein, with the term “meat” referring to the tissue of animals used for food, including seafood, poultry and fresh red meat (Godfray et al., 2018). In the meat sector, change is required to address environmental, health, animal welfare and resource efficiency concerns associated with conventional meat production (Bonnet et al., 2020). Considering that current levels of meat production and consumption have led studies to stress the importance of internalising the negative externalities, as ignoring them would exacerbate long-term threats to the viability of the food system (Meier et al., 2022). Therefore, research efforts shall take into account all stages of the meat value chain – from agriculture of animal feed and meat production to retail and consumption.
Meat SCs are characterised by specific features and challenges that distinguish them from other food networks (Parlasca and Qaim, 2022). Such particularities include:
the need for stringent food safety and quality control measures to ensure product integrity, traceability and compliance with regulations throughout the complex chain from farm to fork (Lindgreen and Hingley, 2003);
the dependence on live animal transportation and handling, requiring specialised infrastructure and expertise to ensure animal welfare standards (Wiedemann et al., 2015);
the perishable nature of meat products necessitating efficient cold chain management to preserve freshness, increase shelf life and reduce waste (Bogataj et al., 2020);
the sourcing of raw materials from multiple farms and regions, leading to complex logistics and SC coordination (Djekic and Tomasevic, 2016);
the extensive processes and diversity/amount of resources being consumed to produce meat (Parlasca and Qaim, 2022); and
the continuous demand for innovation and adaptation to address sustainability concerns (Fernandes et al., 2019).
Extant research tends to investigate individual aspects of the meat system, e.g. environmental impact through life cycle analyses (Asem-Hiablie et al., 2019), or a combination of facets, e.g. sustainability assessments (Parlasca and Qaim, 2022). To this end, introducing efficient interventions requires considering the entire food system (Kirwan et al., 2017) instead of focusing on isolated echelons in the respective meat supply network, from agriculture of animal feed and husbandry to processing, retailing and consumption (Tsolakis et al., 2018).
The meat SC system involves multiple interactions among different operational echelons, several stakeholders and diverse non-linear feedback processes; thus, interdisciplinarity is required to tackle the “cycle of inertia” complex challenge (Friel et al., 2017). According to Hovmand and O’Sullivan (2008), an interdisciplinary approach can help understand the complex and interconnected nature of any problem, allowing for a more holistic understanding and effective problem-solving across various disciplines. In this research, the underlying behaviour and interrelationships between the different areas in the meat food system were explored, with the aim of proposing targeted interventions that can foster the transition to alternative protein sources and discontinue the “cycle of inertia” characterising meat production and consumption. To this effect, this study poses the following research questions (RQs):
What underlining meat SC system structure and interlinkages lead to the emergence of the “cycle of inertia”?
How to efficiently and innovatively intervene in meat SC systems to mitigate the associated sustainability ramifications?
This study addresses the aforementioned research queries by adopting the systems thinking lens (Meadows, 2008) that has been successfully used to investigate complex dynamic systems and tackle associated challenges (Forrester, 1961; Sterman, 2000), especially food systems’ sustainability issues (Global Alliance for the Future of Food, 2021). In response to RQ#1, this research conducted a systematic literature review and a critical synthesis that decomposed the end-to-end meat SC system into six key sub-systems. Notably, the “cycle of inertia” in the meat system emerges as a consequence of identified interrelated variables per sub-system. Following, to address RQ#2, secondary evidence and findings from experts’ interviews and a focus group in an international exhibition were synthesised to outline innovative interventions that can propel the transition of the meat system towards sustainability and resilience. Noteworthy, this study is set within a developed economy context, predominantly the USA and the European Union, but the research findings could apply to emerging economies.
This research contributes to the SC management field by addressing a food supply system challenge with significant socioeconomic and environmental implications. The study builds on scientific evidence to provide effective intervention strategies that can help reduce the impact of meat production and consumption, inform the decision-making processes of governments, industry, NGOs, academia and civil society and drive change towards a sustainable food system. The originality of this research lies in understanding the interconnections among system variables that lead to the emergence of the phenomenon of inertia in end-to-end meat SCs. In order to unveil these interrelations, this research also introduces a novel systems perspective, addressing the mechanisms of inertia through the identification and mapping of five sub-systems. This unique systems thinking approach provides a comprehensive framework for tackling inertia, which sets it apart from other studies in the field.
The remainder of this paper is structured as follows. Section 2 describes the methodological steps pursued to respond to the study’s research questions. In Section 3, the structure of the meat SC system is demystified by leveraging key literature review findings. Following, in Section 4, a synthesis of evidence from literature, expert interviews and a focus group helped to identify leverage points to transit to more sustainable food systems and articulate innovative intervention strategies for sustainable and resilient protein supply. Section 5 concludes by discussing theory and practice implications, limitations and future research avenues.
2. Methodology
The overall research process underpinning this study included three phases (Figure 1). In Phase #1, the system structure was identified, and intervention strategies were conceptualised. Extant literature was reviewed and synthesised to identify the key drivers and impacts of meat production and consumption, which constitute the system’s variables and parameters. The interconnections among these structural elements were also explored. Following that, in Phase #2, data was collected through interviews and analysed to refine the system structure and the intervention strategies identified in the literature review. Based on systems thinking, the variables and parameters, along with their structural interrelations and feedback mechanisms, were mapped. In Phase #3, the system structure was refined, and a conceptual framework of innovative intervention strategies to reduce the impact of meat production and consumption was proposed.
2.1 Basic terminology
The term “inertia” was introduced in the physics domain to describe the property of a mass to resist change. It was initially used in the 17th century by Johannes Kepler, who borrowed the concept from the Latin “inertem”, which translates to “without art” (i.e. without skill, idle, inactive, ignorant) (Zimmerman, 2019). The operations management domain adopted this concept to describe organisational resistance to change (Ford et al., 2008), preventing innovation and business model adaptation. Norrgrann and Luokkanen (2005) explained that when organisations have high inertia, their speed of reorganisation is considerably lower than the pace at which external conditions change. According to the authors, the sources of inertia can be found internally (e.g. investments’ limitations, constraints on information received from decision-makers, internal political constraints) and externally (e.g. legal and fiscal barriers to entry and exit from markets, problematic acquisition of information). According to Sull (1999), the issue is not the inability of companies to take action but the inability to take “appropriate action” when dramatic external shifts occur. In line with this, Moradi et al. (2021, p. 1) outlined different types of organisational inertia (e.g. insight, structural, psychological) and considered this concept to be: “the most important factor which prevents the recognition of setting threats for the organisation and results in low speed of adaptability to the new setting”. In SC management, Smith et al. (2005) defended that inertia can impact firms’ ability to respond to external market pressures and develop corrective strategies.
The field of sustainability in the SC Management domain, which encompasses the environmental, social and economic constituents, has also adopted the concept of inertia. In 2005, Placet et al. (2005, p. 5) defined inertia as “one of the greatest barriers to sustainability-focused innovation” due to “the tendency for companies to continue operating as they have in the past”. Stål (2015, p. 1) stated that inertia is: “a disinclination to enact necessary change in unsustainable activities”, occurring mainly because of the lack of technology, weak knowledge transfer and changes in the market economy. The author explained that this concept: “cannot only be understood as non-change, but also as the pursuit of change in an unfruitful direction” (Stål, 2015, p.14). According to Ghadge et al. (2021), stakeholder inertia is also a critical sustainability implementation challenge in food SCs. Other perspectives defined climate change inertia as a “tragedy of the commons”, which needs to be better understood if effective efforts are to be devised, including policy, to overcome inaction at scale (Pfeiffer and Nowak, 2006).
In this study, we adopt the views from Placet et al. (2005), Stål (2015) and Ghadge et al. (2021), and we approach inertia from a sustainability viewpoint, combining the environmental, social and economic pillars. Based on our understanding of the literature, we propose a definition of inertia within the scope of food systems. Thus, we define inertia as:
The inability to drive change towards more sustainable food production and consumption patterns at an individual, organisational and societal level, due to lack of awareness and proactiveness to lead and embrace positive change in our food system.
In the case of meat SCs specifically, the state of inertia is characterised by resistance from network stakeholders (Verkuijl et al., 2022) to adapt to changing protein market demands, sustainability concerns and consumer preferences (Arcari, 2017). This results in continuing traditional practices and leveraging infrastructure that may be inefficient, environmentally impactful and lacking transparency (Frank, 2007). In addition, governments lack a coherent approach to policies on diversifying sources of protein, which has prevented countries from implementing a clear strategy to reduce the impact of protein production (Morrison, 2022). Factors contributing to this inertia include established industry norms, complex SC dynamics, high capital investments in existing infrastructure, the historical and economic importance of meat and a traditional meat-centric culture that may hinder the adoption of alternative approaches or innovations (Sievert et al., 2022).
2.2 Theoretical lens
This study adopts the systems theory perspective, an area of inquiry that allows a comprehensive understanding of scientific and organisational problems (Ackoff, 1971). Fundamentally, systems thinking consists of seeing “wholes” instead of “parts”, demystifying the interrelationships between system components to understand the drivers of dynamic behaviour (Senge, 1990). For example, Holweg and Pil (2008) built on the concepts of general Systems Theory to study the SC coordination between actors in the automotive industry and the use of IT systems to drive systemic change.
Systems thinking methodology provides a “new way of thinking” to manage complex problems in a local or global context (Bosch et al., 2007). The underlying systemic structures of reality are sometimes difficult to see because of the two levels of perspective which attract more attention, i.e. events and patterns. While events refer to the occurrences encountered daily, patterns are the “accumulated memories of events” that reveal recurring trends. Since human language is rooted at the level of events, it is essential to profoundly comprehend the drivers of events and observed patterns (Kim, 2016).
Systems thinking remains a valuable approach to consider and characterise the different disciplines explored. In this study, the systems-level view provides an appropriate theoretical perspective for understanding and mapping the fundamental cause-and-effect interrelations within the meat system (Meadows, 1980). In particular, a systems view allows capturing positive and negative cause–effect links in the form of feedback loops, i.e. circular sequences of causes and effects that can be either balancing or reinforcing (Sterman, 2000).
System mapping is beneficial in multiple ways (Hummelbrunner, 2011). First, mapping helps find opportunities that address the root cause of a problem rather than “band-aids” that may not entirely provide a viable solution (Blair et al., 2021). Second, system mapping guides the identification of leverage points and the prioritisation of effective intervention strategies (Meadows, 2008). Third, mapping facilitates understanding an intervention’s unintended consequences, especially in problems associated with wide-ranging impacts over time (Größler et al., 2008).
Borman et al. (2022) regarded food system frameworks as tools to enhance our understanding of agriculture, food security and nutrition and shape interventions for more desirable system outcomes. Regarding the meat system, Westhoek et al. (2011) addressed the interactions between the impacts of meat or “scarcities”, as research has largely ignored the relationships between natural and societal dimensions by merely focusing on individual impacts. Furthermore, Vinnari and Vinnari (2014) investigated other dimensions (besides social and environmental) to understand what drives meat consumption. Notwithstanding the fact that several studies in the literature have tried to approach meat production and consumption using various theoretical frameworks, to the best of our knowledge, there is still a scarcity of analyses on the meat system structure and its multi-dimensional interactions.
Reducing the impact of meat is a complex problem that requires a systems approach (Aronson, 1996, p. 3). According to Bendoly (2014) and Nair and Reed-Tsochas (2019), the raison d’etre of systems view over meat production and consumption includes the global scope of the problem, the interconnection between the different drivers and impacts, the multiple actors involved and most importantly, the fact that not a single solution to the problem has been identified or proven to be successful. Henceforth, in this study, the underlying behaviour and relationship between the different food sub-systems are explored, which will serve as an evidence base to propose effective, innovative interventions to reduce the impact of meat production and consumption.
2.3 Conceptual framework development
A literature review was carried out to systematically capture research evidence identifying key drivers and impacts of meat production and consumption, as well as strategies that can help reduce meat impact. A structured keyword search was conducted in the Scopus of Elsevier to identify relevant scientific articles, as the database offers a broad range of peer-reviewed journals and thus ensures access to “best-quality evidence” in different domains (Tranfield et al., 2003). Despite the availability of various electronic search engines for accessing academic contributions, Scopus was chosen because of its broad acceptance for systematically mapping and reviewing the existing body of literature (Srai et al., 2018). Furthermore, based on our investigation of the Web of Science database, we found that Scopus offers a wide range of highly relevant articles published on the research topic under consideration. Specifically, for this study, we observed that the search results in Scopus comprehensively cover and exceed those obtained from the Web of Science.
The literature search included the following query: “meat” AND (“food” OR “diet*”) in the “Keywords” category, in combination with the terms “sustainab*” AND (“consumption” OR “production”) AND (“drive*” OR “impact*” OR “factor*”) in the “Article Title, Abstract, Keywords” category. The data range was set from the year 2000 until the present, while the selected document type was “Article” and “Review”. Every identified article’s content was carefully evaluated to verify its eligibility, according to the purposes of this research, and the selected articles were accepted or rejected for detailed review. The exclusion criteria are summarised in Figure 1. Specifically, the analysis was restricted to publications focused on the meat production and consumption system written in English. By the 29th of August 2021, 390 articles concerning the meat production and consumption system had been identified, and 130 studies were selected for final review. These articles originate from a range of diverse academic journals which cover different disciplines, including social and behavioural (44% of articles), nutritional (22%), political (18%), management (15%), economics (10%) and environmental sciences (27%). The distribution of articles per journal and the subject areas covered are outlined in more detail in Table A1 in the Appendix.
Overall, the used literature review process for identifying the structure of the meat production and consumption system had a threefold aim:
identify the system’s variables and parameters, including impacts and drivers of meat production and consumption;
recognise the interrelations and feedback loops between the system variables and parameters; and
conceptualise intervention strategies that can help reduce the impact of meat.
2.4 Data collection and analysis
First, to capture and refine the realistic structure of the meat system, the group model-building method, grounded in system dynamics research, was used to ensure the validity of the system’s interconnections (Vennix, 1996). Group model-building is a means of engaging diverse stakeholders to jointly understand and address “messy problems” through systems thinking (Vennix, 1999). Group model-building offers the opportunity to explore and align mental models (Huz et al., 1997) and creates the possibility of integrating partial mental models into a holistic system description (Rouwette et al., 2002).
This process enabled us to engage with twelve experts from different fields in the process of analysing and refining the resulting meat system structure (Srai et al., 2022). The selection of the experts was based on their long-term involvement in the protein industrial ecosystem and their awareness of the sustainability impact of meat production and consumption (Figure 2). Stakeholders were identified through a purposive sampling approach (Creswell, 2013), considering criteria such as having held their position for more than five years, occupying senior management roles and having a master’s or Ph.D. degree. The participants were identified through interactions with associations, universities and professional bodies, making sure that their expertise and insights were particularly relevant to the study’s objectives. The experts’ selection approach was employed to obtain a well-rounded and highly informed perspective on the complexities of the meat value chain and its alternatives. The interviewed stakeholders, as summarised in Table 1, represented: public health bodies – one expert; government authorities – two experts; meat industry – three experts; meat substitutes industry – three experts; retail fast food chain – one expert; food distributor – one expert; and NGOs – one expert.
The group-model building approach involved a structured process with a series of iterative steps. Initially, one-hour-long semi-structured interviews were carried out to encourage in-depth conversations. These were recorded and transcribed, with prior ethical approval granted based on the anonymity of the participants. Open-ended questions covered four main topics: the interviewee’s experience, impacts and drivers of meat production and consumption, current intervention strategies in their field, and potential interventions that could be effective in the future. Stakeholders’ engagement results were analysed qualitatively through inductive coding (Leech and Onwuegbuzie, 2007), allowing us to identify and classify such components into commonly observed themes. Parameters, variables and structural interconnections were captured, and participants were additionally asked to comment and review them. The interrelations between the variables and parameters of the system were reviewed based on Ford and Sterman (1998). This conducive learning process ensured the consensus among stakeholders about the meat system to enrich the identified interventions (Rouwette et al., 2002). In this context, the “models” represented by the resulting meat system and sub-system maps were created as visual representations to depict the complex interconnections and dynamics within the research domain.
Due to the availability of participants and time constraints, contributions from different fields were explored, but the findings were not representative of all actors involved (e.g. consumers and farmers). Thus, the scope of this study is limited to the perspectives and insights provided by the key stakeholders included in the data collection, specifically value chain actors from the meat manufacturing and distribution sectors and other experts in the field, which provide the research basis. The involvement of meat industry representatives in the research was deemed fundamental due to their direct engagement and collaboration with their suppliers/farmers and their integral role in the industry’s operations. Such collaboration is essential in the meat industry to ensure quality control, traceability and compliance with safety regulations (Lindgreen and Hingley, 2003). The inclusion of these participants helped capture the industry’s unique perspectives and insights, which are crucial for a comprehensive analysis of the meat SC. The interviews’ outline and the interviewees’ salient points are inserted in Tables A2 and A3, respectively, in the Appendix. Details on the secondary sources validating the individual variables, parameters and connections in the system can be reviewed in the Supplementary Material. Specifically, Tables S1 and S2 outline the data used to inform the identification and creation of sub-systems and the relationships and linkages represented in the respective diagrams. The interviews were then used to refine the system, following the method explained by Ford and Sterman (1998).
Second, the mapping of the system was operationalised via leveraging causal loop diagrams (CLDs). This approach helps illustrate the significant cause–effect interactions and feedback loops and thus captures the underlying structural interdependencies in a complex system (Meadows, 2008). The interdependencies between the system variables are represented by arrows, where the variable at the origin has a causal effect on the variable at the arrow tip (Forrester, 1961; Goodman, 1974). Relationships can be positive or negative, typically denoted through the respective polarity. A positive relationship denotes that both variables change in the same direction (e.g. an increase). In contrast, a negative relationship implies that variables change in the opposite direction (e.g. an increase leads to a decrease). Time delays, which affect the rate of change, are depicted by a double slash sign over the arrow (Sterman, 2000).
Circular causalities create a feedback loop which can either be reinforcing (encapsulates exponential growth or destruction) or balancing (leads the system towards equilibrium) (Maani and Cavana, 2007). In this study, the structure of the meat food system was unravelled by demystifying its fundamental sub-systems, which are independent clusters of interacting variables categorised according to the nature of their behaviour (Dennis, 2002). Sub-system emergence occurs when distinct elements are identified within the system that have their unique functions and relationships. These sub-systems are often defined based on their specific roles or contributions to the overall system’s functioning. By decomposing a system into its constituent sub-systems, we can better understand how the system operates and how changes or interventions within one sub-system can impact the overall system behaviour (Jackson, 2003). Boundaries that set the scope of the system were also defined. These were conceptual rather than physical, as they condition which components are included or excluded from the system (Lee et al., 2017).
Third, following the mapping of the complex food production and consumption system, “leverage points” were identified where the introduction of “… a small shift […] can produce big changes in everything” (Meadows, 1999, p. 1). However, intervening in every structural element of the system would be impractical and infeasible. To this effect, Pareto’s principle was used (Grosfeld-Nir et al., 2007) to select the system’s variables and parameters that could act as “the vital few”, using the number of outward connections as a criterion, as this is an indication of every system’s node’s degree. “The vital few” control the system’s behaviour and provide ground for effectively introducing interventions.
Several steps were followed to identify “leverage points”. First, the number of outbound connections was calculated for each system node (i.e. variable or parameter). Afterwards, the nodes were sorted in descending order according to their degree. The nodes with new connections only were selected to ensure that nodes with a degree but repeated connections were not included as duplicates of the top nodes. The level of effectiveness in inducing a change in these critical nodes was then analysed through the model of Meadows (1999), which defines twelve places to intervene in a system. This method helped prioritise the leverage points according to their level of effectiveness and feasibility.
2.5 Model structure refinement
In the last research phase, a focus group on the food sector was organised as part of an international exhibition focusing on plant-based food, involving representatives from developed and emerging economies around the globe. These representatives particularly included actors from the protein industrial ecosystem, such as retailers, food service, hospitality, distributors, manufacturers, farmers and investors. They were selected based on a pre-existing participant list and by proactively approaching stakeholders acknowledged for their high-level expertise in the protein industry. The experts’ voluntary participation in our research, in line with their comprehensive understanding of this study’s objectives, was vital to ensuring the quality of the group's contributions. Furthermore, we put emphasis on ensuring our informants’ diversity, striving to encompass representatives from a wide range of operations echelons within the protein industry to enrich the discussions and generate valid insights. The focus group selected included the following stakeholder representatives: farmers, policymakers, academic institutions, consultants and stakeholders from both the meat and meat substitute industries. These participants helped review and refine the system structure and the outline of innovation-driven interventions in a unified framework, which can help propel the transition of the meat system towards sustainability and resilience. Notably, many innovative interventions were discussed within the focus group. For example, “providing cheap and tasty alternatives”, “developing new technologies” and “adjusting restaurant offerings” were suggested as feasible approaches to developing and supplying protein-rich meat alternatives.
3. Results
The meat food system’s complexity and non-linear behaviour in this research are captured by 97 variables and parameters, with 40 main feedback loops (involving 26 reinforcing and 14 balancing loops) overall. The interlinkages among the system variables and parameters (212 connections in total) highlight the system’s complexity, interconnectedness and feedback mechanisms (Nguyen and Nguyen, 2013). Figure 3 illustrates the CLD that maps the structure of the overall meat food system.
In the meat system, food products are embedded in multi-faceted and multi-layered processes linking “animal feed agriculture”, “meat production”, “retail availability” and “consumer demand”. Notably, these processes are underpinned by complex social, institutional, value chain, cultural, economic and environmental relationships (van Berkum et al., 2018). Thus, six key sub-systems were identified within the meat food system:
Social – Refers to the well-being of the population, denoting the sociodemographic drivers of meat consumption such as “population growth” (Godfray et al., 2018), “level of education” (Stubbs et al., 2018) and “gender equality” (Rosenfeld and Tomiyama, 2021). The social sub-system has to be investigated in tandem with its impact on people’s quality of life (González et al., 2020);
Institutional – Addresses the institutional influence from the diverse stakeholders involved across the end-to-end echelons of the meat value chain, including the meat industry (Stoll-Kleemann and O’Riordan, 2015), governments (Wellesley et al., 2015), NGOs (Laestadius et al., 2013) and the media (Milford et al., 2019);
Value chain – Addresses the end-to-end technology infrastructure and processes that enable and support the meat industry (Milford et al., 2019). Such a supportive environment can be operationalised via SC improvements (Allievi et al., 2015), investments in infrastructure and transportation systems (Bailey et al., 2014), production and food technology advancements (Brameld and Parr, 2016) and differentiation of offered products (Broad, 2020);
Cultural – Demystifies the fundamental rationalisations for consuming meat, reflecting the cultural and personal values that drive the downstream echelon of the meat value system, i.e. consumer demand (Stubbs et al., 2018). Several studies advocate meat consumption by promoting the belief that meat is natural, normal, necessary and nice (Piazza et al., 2015). The latter traits stand as the origin of meat demand and are responsible for triggering the inertia in the system (Piazza et al., 2015);
Economic – Addresses the economic drivers and impacts of the meat value chain, including economic development (Milford et al., 2019), globalisation and trade facilitation (Cole and McCoskey, 2013), urbanisation and employment (Freibauer et al., 2011); and
Environmental – Refers to the biophysical context in which the meat system operates (van Berkum et al., 2018), specifically focusing on the associated environmental sustainability impact (Stubbs et al., 2018).
Considering that this research aims to take a “high-level” look at the meat system and the determinants of inertia, key variables and feedback loops identified within each sub-system are discussed. Specifically, one reinforcing and one balancing loop are explained to narrow the scope and clarify how systems thinking applies to the context of each sub-system.
3.1 Social sub-system
The social sub-system is captured through 17 variables that interconnect via two reinforcing loops, which affect “Meat Demand” (Whitnall and Pitts, 2019), and five balancing loops, which capture the social impact of meat production and consumption (Salter, 2018), as depicted in Figure 4. The social sub-system links to “Inertia” through the “Level of Education” and “Consumer Awareness” variables (Wellesley et al., 2015).
The social sub-system illustrates the long-term impact of meat consumption on human health. Indicatively, in the balancing loop B1, an increase in the “Rate of Meat Consumption” can intensify people’s “Exposure to Foodborne Infections”. Animals can act as reservoirs for pathogens that can infect humans, thus increasing “Health Damage” (Godfray et al., 2018). Consequently, “Death Rates” increase and as a result “Population Growth” decreases, leading to lower “Meat Demand”. The existing delay between the “Rate of Meat Consumption” and “Health Damage” is critical, as it influences people’s awareness of the health consequences of meat overconsumption, affecting the rate of change in the system (Stoll-Kleemann and O’Riordan, 2015).
The impact of meat production on food security is also captured in this sub-system (Tilman and Clark, 2014). In the reinforcing loop R9, a high “Level of Meat Production” can lead to an increase in “Food Security”, which in turn reduces “Health Damage” and “Death Rates”, thus accelerating “Population Growth”. Enhanced growth entails “Meat Demand” and, thus, increasing meat production (Westhoek et al., 2011). This loop is complemented by the balancing loop B4, which illustrates that a high “Level of Animal Agriculture” intensifies the hunger problem instead due to unsustainable “Land-use”, which negatively affects the “Level of Meat Production” and “Food Security”. The negative impact of meat production on food security is not directly evident either (i.e. there is a delay), so the issue is not perceived as urgent and action is not taken (Cheah et al., 2020).
The phenomenon of inertia also affects the rate of change in the social sub-system as it directly impacts consumer awareness (Wellesley et al., 2015). In the reinforcing loop R10, a high “Level of Meat Production” leads to increased “Land-use” causing “Disruption of Property Rights” in certain regions (Schneider, 2014). Especially in emerging economies, this may pave the way to “Local Displacement” of communities and “Poverty”, reducing a region’s “Economic Development” and thus the “Level of Education” of the respective population (Vranken et al., 2014). Lower levels of education consequently lead to a higher rate of “Inertia”, which in turn leads to lower “Consumer Awareness” and perpetuating inaction, ultimately leading to a higher “Meat Demand” (Wellesley et al., 2015).
3.2 Institutional sub-system
The institutional sub-system (Figure 5) is formed by 15 variables and comprises six interconnected reinforcing loops which originate from the “Political Influence and Lobbying of the Animal Agribusinesses” (Lazarus et al., 2021) and which directly affect the “Levels of Meat Production” (Stoll-Kleemann and O’Riordan, 2015). Furthermore, this sub-system is connected to factors from the social, economic and environmental sub-systems. The links to the variable of “Inertia” are operationalised through the “Political Influence and Lobbying of the Animal Agribusinesses” and the “Level of Food Reforms & Regulations” variables (Dagevos and Voordouw, 2013).
This sub-system shows the direct correlation between meat demand and income growth in animal agribusinesses (Stoll-Kleemann and Schmidt, 2017). In the indicative reinforcing loop R12, an increase in “Meat Demand” leads to higher “Income for Animal Agribusinesses” which allows food companies to continue growing and invest further in “Meat Advertising & Marketing” initiatives (de Bakker and Dagevos, 2012). Marketing and media communication investments intensify corporate “Market Influence” and “Brand Positioning”, increasing meat demand (Stubbs et al., 2018).
The potential influence over political decisions from animal agribusiness is also illustrated in the institutional sub-system. In the reinforcing loop R14, a high level of “Political Influence & Lobbying from Animal Agribusinesses” could enable companies to control the level of consumers’ “Exposure to Meat Production” and thus the “Consumer Awareness” (Kunst and Palacios Haugestad, 2018). In general, the higher the industry influence, the lower the level of consumer awareness due to the lack of transparency (Steinfeld et al., 2006).
Inertia also strengthens the political influence of animal agribusinesses (Dagevos and Voordouw, 2013). In the reinforcing loop R15, a high level of “Political Influence & Lobbying from Animal Agribusinesses” intensifies the system’s “Inertia” level (Wellesley et al., 2015). In turn, “Inertia” blocks the “Level of Food Reforms & Regulations” in the industry, which lowers “Consumer Awareness” and paves the way for companies to have more political influence (Apostolidis and McLeay, 2016).
3.3 Value chain sub-system
The value chain sub-system (Figure 6) is formed by 17 variables and comprises four interconnected reinforcing loops, representing the level of “Efficiency” that has been reached in meat SCs (Vinnari and Vinnari, 2014), as well as two balancing loops which affect “Meat Demand” through the development of novel meat substitutes (Gerhardt et al., 2020). The sub-system is connected to factors from the social, cultural and institutional sub-systems and links to the variable of “Inertia” through the “Food Technology Advancements” and the “Level of Meat Offered in Public Catering” (Wellesley et al., 2015).
Furthermore, the value chain sub-system captures the influence of meat demand on the industry’s response to consumers’ nutritional requirements (Allievi et al., 2015). Indicatively, in the balancing loop B7, an increase in “Meat Demand” translates into a higher “Need for Faster Responsiveness to Consumers” (Leroy and Degreef, 2015). This pressure to satisfy demand in a short lead time motivates the industry to accelerate “Food Technology Advancements” and increase the “Availability of Meat Substitutes” that have similar characteristics to meat (e.g. texture, taste). To this effect, the decreasing demand for conventional meat products balances the system (Broad, 2020).
The exponential growth of meat demand due to efficient production systems and product differentiation is also considered (Brameld and Parr, 2016). In the reinforcing loop R23, a higher “Need for Faster Responsiveness to Consumers” drives the industry to accelerate “Production Technology Advancements” and helps companies focus on improving their “Efficiency” and “Standardisation of Production Processes” (Bartnicka et al., 2020). Such improvements in the meat SC can lead to an increase in product differentiation, which in turn increases the “Variety of Meat Products Offered” by companies, positively influencing “Meat Demand” (de Bakker and Dagevos, 2012).
In this case, inertia directly affects the rate at which technology and meat substitutes are developed (Wellesley et al., 2015). In the reinforcing loop R26, the limited precedent for intervention from governments and institutions deaccelerates “Food Technology Advancements” and the “Availability of Meat Substitutes”, reducing meat demand (Gerhardt et al., 2020). As a result, continuous market demand and supply of meat products perpetuate consumers’ unwillingness to alter dietary habits (Morris et al., 2014).
3.4 Cultural sub-system
The cultural sub-system (Figure 7) is formed by 18 variables and comprises eight interlinked reinforcing loops representing the cultural reasons and most common justifications underpinning “Meat Demand” (Piazza et al., 2015). Furthermore, this sub-system connects to the variable of “Inertia” through the “Scepticism to Scientific Evidence” (Graves and Roelich, 2021) and the “Moral Disengagement” variables (Happer and Wellesley, 2019).
This sub-system elucidates the value attributed to meat in a specific context and culture, explaining that consuming meat is “normal” as it is “what most people do” (Milford et al., 2019). Indicatively, in the reinforcing loop R1, the “Sociocultural Valuation of Meat” in a specific culture can cultivate a society’s “Deep-rooted Habits of Meat Consumption” (Stubbs et al., 2018). Such habits can result in a higher “Societal Pressure to Consume Meat”, which causes meat demand to continue growing (Macdiarmid et al., 2016).
Furthermore, from a systems perspective, it is also significant to capture the perception that consuming meat-based food products is necessary for maintaining physical well-being and fulfilling the sensory pleasures of food consumption (Piazza et al., 2015). In the reinforcing loop R7, the pleasure associated with meat consumption is influenced by the consumers’ “Level of Satiety” attributed to the high level of protein intake (Vranken et al., 2014). Thereafter, an increase in the “Perceived Tastiness of Meat Products” leads to consumers’ “Cognitive Reframing and Self-Exoneration” and “Moral Disengagement” (Graça, 2016), which could cause an increase in “Meat Demand” (Buttlar and Walther, 2019).
Inertia strengthens the “Cognitive Reframing and Self-Exoneration” level in the sub-system (Graça et al., 2016). In the reinforcing loop R8, as “Inertia” increases, the “Scepticism to Scientific Evidence” rises (Happer and Wellesley, 2019). This scepticism could lead to lower levels of “Consumer Awareness”, strengthening the “Cognitive Reframing and Self-Exoneration” and “Moral Disengagement” of consumers (Onwezen and van der Weele, 2016). Sequentially, inertia and perpetuated inaction increase (Graça et al., 2014).
3.5 Economic sub-system
The economic sub-system (Figure 8) is formed by 13 variables and comprises:
six interconnected reinforcing loops that affect “Meat Prices” and the “Purchasing Power” of consumers (Lusk and Tonsor, 2016); and
one balancing loop that represents the economic impact of low-cost meat imports (Cole and McCoskey, 2013)
The link to “Inertia” is apprehended through the “Meat Prices” variable (Wellesley et al., 2015).
The economic sub-system demonstrates the impact of cheap meat imports on people’s affluence (Weis, 2013). In the indicative balancing loop B6, as the “Level of Cheap Imports” increases in a region, the greater the disruption to local markets is Savary et al., 2020. Especially in emerging economies, local producers may be unable to compete with low-cost imported meat products (Vranken et al., 2014). Such disruptions may cause lower “Levels of Employment”, leading to a lower “Level of Affluence” and “Purchasing Power” of consumers; henceforth, the demand for meat products decreases (Milford et al., 2019).
On the contrary, increases in the meat production industry can enhance the economic development of a region (Duchin, 2005). In this case, the more extensive the meat SC operations, the higher the “Levels of Employment” in a region, and as a result, the greater the “Level of Affluence” and the “Purchasing Power” of consumers that result in higher demand for meat products (Milford et al., 2019).
Inertia affects meat SC growth (Wellesley, 2015). Due to governments’ support provided to the livestock industry through subsidies in certain regions, the prices for meat products remain low. As a result, consumers are less willing to shift their consumption patterns, causing the level of “Inertia” to remain high. This inaction from consumers leads to a continuous demand for meat, thus supporting the industry’s growth (Bailey et al., 2014).
3.6 Environmental sub-system
The environmental sub-system (Figure 9) is formed by 16 variables and comprises six interlocked balancing loops with delays which reflect the environmental impact of the meat SC (Stoll-Kleemann and Schmidt, 2017). The link to the variable of “Inertia” is materialised through the “Animal Welfare Standards” variable (Wellesley et al., 2015).
The direct association between meat production and environmental damage is depicted evidently (Godfray et al., 2018). In the indicative balancing loop B11, an increase in the “Level of Animal Feed Agriculture” leads to an increase in “Land-use”, causing “Deforestation”, “Land Degradation” and “Desertification” over time (Stoll-Kleemann and O’Riordan, 2015). At the same time, in the balancing loop B9, an increase in the “Level of Meat Production” causes a rise in “Animal Manure” that, in the long-term, pollutes the “Clean Water” used for the continuous nurturing of animals (Westhoek et al., 2011). These changes balance the system, eventually limiting agriculture and meat production levels.
Inertia also affects the rate of change in the environmental sub-system as it directly influences the inclusion of sustainability standards in new and existing production guidelines (Wellesley, 2015). In the balancing loop B10, the lack of policy interventions and government inaction maintain the same level of “Inertia”. Therefore, the development and use of “Animal Welfare Standards” are being limited, preventing reductions in the “Use of Antibiotics” and “Chemical Pollution” currently contaminating the freshwater reserves necessary for meat production (Gerbens-Leenes et al., 2013).
4. System interventions
This research proposes innovative intervention strategies for sustainable protein SCs to break the “cycle of inertia”, which is the main barrier to reducing the impact of meat production and consumption. Three main categories of innovative strategies are recognised with an interdisciplinary outlook (Hovmand and O’Sullivan, 2008), encapsulated into a unified framework (Figure 10).
The proposed framework is a simplified representation of the model the UK Department for Environment, Food and Rural Affairs applies to overcome inaction and induce behaviour change (DEFRA, 2008). The three main action stages are the following:
Engaging stage – “Getting People Involved”: Facilitates the comprehension of a problem and helps develop a sense of personal responsibility through the participation and interaction between actors (DEFRA, 2008);
Encouraging stage – “Giving the Right Signals”: Involves incentives that encourage action and disincentives that ensure the target audience’s response. These typically take the form of price interventions as a policy instrument (Dagevos and Voordouw, 2013); and
Enabling stage – “Making it Easier”: Removes barriers, provides alternatives and reorganises the provisioned infrastructure to facilitate accessibility, affordability and availability of more sustainable products.
Innovative interventions across the abovementioned action stages would need to be applied contemporarily to effectively reduce the impact of meat food systems. For example, increasing meat prices can be controversial if implemented as a standalone intervention. This financial measure may jeopardise food security in low-income households/families and enhance social inequality. Therefore, promoting subsidies to protein-rich crops and securing accessibility to healthier food options in local communities should be implemented in parallel (Apostolidis and McLeay, 2016). The six innovative intervention strategies proposed in this research are explicated in Table 2.
4.1 Change labelling of meat products
In the social sub-system, mandatory labels on meat products could be legally imposed to inform about associated nutritional value, carbon footprint and animal welfare standards. Complementarily, a public labelling authority could be established that develops and standardises food labels to improve consumer trust. This intervention tackles the leverage points “Rate of Meat Consumption”, “Animal Welfare Standards” and “Market Influence” to support decreasing meat consumption through transparency while encouraging meat producers to develop healthier alternative options. Informant #6 discussed that food labels are a way of helping companies to “innovate and develop alternatives which satisfy consumers becoming more health-conscious and who demand more sustainable options”. This statement is supported by Apostolidis and McLeay (2016), who explained that product labelling is an intervention that can help reduce meat consumption by focusing on specific consumer segments instead of targeting the average consumer. Within the identified segments, consumers can be characterised as: price-conscious; healthy eaters; taste-driven; green oriented; organic eaters; and vegetarian. Representatives from NGOs (i.e. Informant #12) and the government (i.e. Informant #2) discussed how labelling on meat products could help increase consumer awareness and “demand greater transparency in the meat industry and its supply chains” (Informant #12).
4.2 Rethink subsidies schemes
In the institutional sub-system, governments could reduce their financial support to animal farming and direct any subsidies to the production of more sustainable protein alternatives (e.g. protein crops). This intervention tackles the leverage points “Political Influence and Lobbying” and “Income for Animal Agribusiness” to increase the production cost of meat while encouraging farmers to transition towards other sustainable protein sources and increase consumers’ affordability of these products. According to Carrington (2018), changing subsidies and taxes on meat and dairy are necessary. The latter notion is supported by Informant #8, who explained that reforming subsidies is the “key to support the transition towards a healthier and more sustainable food system”. In addition, Informant #2 and Informant #5 added that subsidies should align with objectives that promote human health, ensure animal welfare and mitigate climate change. For Informant #3, “disincentivising or incentivising individual choices through fiscal measures is a very powerful strategy”.
4.3 Support the development and supply of protein alternatives
In the value chain sub-system, the meat industry, in collaboration with academia, shall invest in developing alternative meat proteins and achieving economies of scale to their supply. This intervention strategy tackles the leverage points “Market Influence” and “Efficiency”, encouraging the development and supply of low-cost protein alternatives while increasing the protein value chain efficiency by eliminating meat production process stages. In the case of plant-based proteins, for example, inconsistencies in supply and price will need to be addressed with innovative technologies to isolate valuable proteins from sustainable sources. Indicative extraction technologies include electrostatic separation, subcritical water extraction, reverse micelles extraction, aqueous two-phase systems extraction, enzyme-, microwave-, ultrasound-, pulsed electric energy- and high pressure-assisted extraction (Pojić et al., 2018). However, depending on the technology, protein extraction efficiency, quality of protein isolates, composition and range of functional properties may vary. Nonetheless, innovative protein extraction technologies are currently under experimentation, with many not being commercially adopted.
According to Informant #9: “if cheap and tasty protein alternatives are available, and there continue to be technological breakthroughs, consumers will start seeking alternatives as a replacement to meat”. According to Informant #11, this development should be supported by the “close cooperation between the industry and academia and the development of production technologies which help scale up supply chains”. To a greater extent, the development of meat alternatives should be accompanied by consumer education and solutions to address the perceived unnaturalness of meat from alternative sources and other barriers to consumer acceptance (Bryant et al., 2019).
4.4 Develop food choice and personalisation technologies
In the cultural sub-system, consumers shall have access to personalised food products. Through the leverage points “Consumer Awareness” and “Sociocultural Valuation of Meat”, consumers could be motivated to adapt their protein consumption habits with personalised protein products, considering crop varieties available in their region and personal requirements in terms of sensory attributes such as flavour, texture, portion size and composition (e.g. macro- and micro-nutrients, calories). Knowledge is needed about which characteristics of nutrients, production processes, geographic conditions, consumers’ sensory preferences and health-care profiles can impact personalisation (Ueland et al., 2020). For example, extrusion-based 3D printing technology for protein pastes is a starting point in developing healthy, customised snack products (Lille et al., 2018). The latter claim is validated by Informant #1, who stated that personalising food options could prevent consumers from: “feeling social pressure to consume meat” and instead motivate them to “feel good for choosing an option that is tailored to their profile and potentially more sustainable”.
4.5 Increase in meat prices
In the economic sub-system, governments could regulate the price of meat products and implement a meat consumption tax. The aim of tackling the leverage points “Rate of Meat Consumption” and “Economic Development” is to reflect the environmental and health costs of meat products and incentivise behaviour change towards lower rates of meat consumption. Evidence supports that taxes and fees on harmful or unsustainable food options “create financial incentives that steer market-actor behaviour” (Reisch et al., 2013, p. 20). Furthermore, Reisch et al. (2013, p. 20) considered such financial instruments to be: “potentially powerful tools because, in the food domain, price is a key decision criterion for consumption and hence a critical competitive advantage”. Informant #2 validated this latter statement and further supported that taxes are a stronger incentive than subsidies for consumers to replace meat with other alternatives. According to Informant #9, increasing meat prices should be complemented with an “information nudge” where the revenue obtained from taxation shall be used to finance education campaigns and training of health and nutrition practitioners.
4.6 Improve animal welfare standards
In the environmental sub-system, governments and NGOs could request that the meat industry complies with strict animal welfare standards, e.g. appropriate nutrition, housing and temperature, sufficient breeding space, high hygiene and medical care. To this effect, policy stakeholders could formulate a legal framework supporting animal rights. This strategy tackles the leverage points “Animal Welfare Standards” and “Disease Transmission Between Animals”, aiming to prevent the spread of shared diseases between animals and the use of antibiotics, which affects productivity and human health in the long run.
Furthermore, a legal framework supporting animal rights can help change humans’ anthropogenic mindset towards animals, motivating actors to drive system change. While resistance from meat companies may rise in this scenario as costs increase due to efficiency reductions, Informant # 4 explained that: “animal welfare must be considered an important part of today’s animal production as societal concern increases over time”. According to Stubbs et al. (2018), economic incentives and emphasis on environmental and animal welfare benefits could reduce the intention-behaviour gap. Ultimately, behaviour change is motivated by increasing consumer awareness of how meat consumption affects health and climate change.
5. Conclusions
Reducing the impact of meat production and consumption is a considerable challenge; however, it represents a pivotal opportunity to improve the global food system and feed 10 billion people by 2050 in a sustainable and resilient manner (Searchinger et al., 2019). The underlying structure of the meat food system, as complied in this study, reveals that six key sub-systems dictate the “cycle of inertia” that prevents the transition towards sustainability, namely: (i) social; (ii) institutional; (iii) value chain; (iv) cultural; (v) economic; and (vi) environmental. Due to the number of connections in the system, reducing the sustainability impact of meat is a complex problem which will continue growing over time due to the unequal contribution of the reinforcing loops (26 in total) compared to the number of balancing loops (14 in total). In response to RQ#1, owing to the delays characterising the balancing loops, the awareness about the pertinent sustainability challenges is low, thus leading to the “cycle of inertia”.
Moreover, to address RQ#2, the proposed system model motivated six main innovative strategies for governments, public bodies, NGOs, industry, academia and civil society to intervene and effectively reduce the impact of meat production and consumption. These strategies can be categorised into three main action stages, i.e. engaging, encouraging and enabling. Strategies alone would not necessarily be effective, as unintended consequences may occur if the change is not contemporarily driven in other parts of the system. Furthermore, concentrating on the engaging phase is recommended, as it “activates attention” and ensures all actors are aligned when stringent measures are implemented later (Apostolidis and McLeay, 2016). The proposed qualitative framework in this study can help break the “cycle of inertia” once the intervention strategies are prioritised and adopted according to the required scale and context.
This research contributes to the SC management field by shedding light on the inertia phenomenon and emphasising the importance of comprehending the interconnections among variables that contribute to its emergence. While existing studies often focus on interventions without a profound understanding of the underlying mechanisms of inertia, this research deployed a novel approach by considering different scientific disciplines integrated through a systems thinking lens. This research extends the prevalent discussions on inertia by introducing the concept of sub-systems and analysing the interrelations within the meat food system. This unique perspective offers valuable insights and provides a comprehensive framework for understanding and addressing the inertia phenomenon. The research’s originality lies in the ability to bridge the gap between theory and practice, offering practical implications for overcoming inertia and ultimately reducing the impact of meat in various domains.
5.1 Academic contributions
Existing proposed solutions to mitigate the sustainability impact of meat mainly have a value chain (Rosales et al., 2020) and economic perspective (Zylbersztajn and Pinheiro Machado Filho, 2003). Challenges encountered by the agri-business have been studied (Krishnan et al., 2021), with strategies focusing principally on efficiency improvements, technological advancements and food waste management, overlooking the dominant role of social, cultural, institutional and environmental factors (Rust et al., 2020).
In this regard, our research contributes to the relevant theoretical field in several ways. First, while extensive knowledge exists on the impacts and drivers of meat production and consumption, a model that illustrates the underlying system-level relationships is lacking. Extant evidence myopically focuses on individual impacts and solutions without considering the spill-over effects in other parts of the system (Stone and Rahimifard, 2018). This study addresses the sustainability impact of meat by adopting a systems thinking lens, further contributing to the existing literature on food systems thinking (Borman et al., 2022). Specifically, in this study, a meat system model was mapped to understand the complex causal connections between a range of drivers, impacts and the meat value chain, which is helpful to define leverage points to intervene and break the “cycle of inertia”.
Second, by analysing the extant literature, this research contributes towards capturing the interplay of the sub-systems’ factors and investigating the role of delays and feedback loops in defining the behaviour of the meat system (Bendoly, 2014). Compared to the balancing loops, the unequal contribution of the reinforcing loops is currently responsible for the continuous growth of meat production and consumption (Meadows, 2008). It is necessary to intervene in this reinforcing relationship to prevent irreversible environmental impacts and worsen socioeconomic factors.
Third, this study proposes strategies which showcase how the “cycle of inertia” in the meat system can be broken (Wellesley et al., 2015). We approached the meat value chain through a systems view and recognised that inertia is a common factor in all sub-systems. Consequently, we expanded the myopic view of literature on inertia (Ghadge et al., 2021; Placet et al., 2005; Stål, 2015) and explored the interdependencies among the complex system’s variables. In general, inertia is a vital sustainability implementation challenge in the food system and a barrier to driving change at an individual, organisational and societal level due to the lack of awareness and proactiveness to lead and embrace positive change (Abbasi and Nilsson, 2012).
5.2 Practical implications
Regarding implications for practice, our research presents a model that facilitates understanding the underlying causal structure and interdependencies of the meat food system. The proposed CLD and the captured system interconnections could inform practitioners on where and how to intervene in the system and thus gain a deeper systemic understanding of what challenges can be encountered in the process. Furthermore, the CLD could guide actors towards developing a pertinent system dynamics model which can accelerate scenario planning and act as a decision-making tool to tackle inertia through innovative interventions in local and global meat food systems (Joglekar and Phadnis, 2020). In agricultural value chains, scenario planning could further propel resiliency and eco-friendliness (Dong, 2021).
The development of a qualitative framework of interventions in this study can act as a roadmap for the meat industry, governmental institutions, public bodies, academia, NGOs and civil society to identify the appropriate portfolio of strategies to reduce meat’s impact. The proposed framework can help advance decision-makers’ participatory interactions and promote learning among experts, particularly those involved in the meat SC (Black, 2013). However, the proposed interventions shall be tailored to the contextual conditions. The success rate in achieving a significant reduction in the sustainability impact of meat will depend on the conditions under which the strategies are implemented, without overlooking the interrelations outlined in the meat system, the key actors and the leverage points identified in this research.
5.3 Limitations
This research has limitations which can act as a basis for future studies. According to Forrester (1961), systems thinking involves capturing complex systems into models, potentially oversimplifying reality and overlooking critical details. Time delays between cause and effect can be challenging to quantify and predict accurately. Limited data can also affect the reliability of system models, while dynamic complexity with numerous variables and non-linear relationships adds to the challenge of analysing systems.
In this study, the proposed system model is generic and needs to be tailored to local, regional and national contexts, as required. Most of the studies considered in our literature synthesis focused on the drivers and impacts of meat production and consumption in developed countries, predominantly the USA and the European Union, and not in emerging economies. Particular attention should be paid to emerging economies due to their rising affluence and population, where unintended consequences can have detrimental outcomes. Furthermore, our research highlights the need for future studies to draw more on social and behavioural sciences literature to include these disciplines’ perspectives in greater detail. By integrating these disciplines, researchers can enhance the effectiveness of the systems thinking methodology in addressing complex issues.
Finally, the results obtained from the interviews were constrained by the researcher’s time and the experts’ availability. An additional point of view from a representative group of experts from different disciplines would add to this study’s knowledge base and ensure that the proposed intervention strategies are robust. Particularly, including the viewpoints of other stakeholders directly, such as pastoral farmers, would provide valuable insights and promote a more holistic understanding of the subject. Involving actors from a wide range of countries would be valuable as well, as they may allow inter-country comparisons that measure the effectiveness of intervention strategies in different national contexts.
5.4 Future research
This study provided a conceptual system model as a first-effort approach to elucidate the complex interplay of factors influencing the meat value chain. While the primary focus of this research is on the meat system’s mapping, which informed the identification of interventions, we are mindful of the need to analyse these interventions and their impact further. Validating the results through system dynamics simulation modelling (Cunico et al., 2022) can also provide quantitative indications to researchers and practitioners about the benefits of the causality and the meat SC impact. Specifically, time delays and inertia are inherent to system dynamics, thus helping to perform scenario planning and inform policy-making interventions to enable shared value across multiple food system actors (Srai et al., 2022). Particularly, additional research is needed to identify the level of impact of the identified leverage points. Since key variables were selected based on the number of outward connections, more data is needed to understand the strength of these relationships (e.g. variables with fewer outward links might have more leverage than some of the points selected in this study). Concerning the proposed qualitative framework, exploring how the suggested intervention strategies affect different population segments (e.g. farmers and workers) and behavioural responses is particularly interesting. Particularly, future research could build on this study’s meat system with the addition of other key value chain actors’ perspectives. The proposed fundamental innovations to tackle the “cycle of inertia” also motivate future research avenues to conduct case studies for verifying the results.
Furthermore, exploring the drivers and impacts of protein value chains versus meat value chains is appealing in an industrial context. Specifically, future research shall provide evidence on upscaling novel protein alternatives to products such as cheese and seafood (Grossmann and McClements, 2021) and future protein extracts that do not need to be ultra-processed. Interdisciplinary approaches and evidence from different food SC stakeholders are required (Yang et al., 2021) to develop new high-quality, nutritious, sustainable and accessible protein products. Developing system dynamics models from a multisolving angle would provide validated action programs to effectively address food security and climate change challenges (Breeze Ceballos, 2022).
Figures
Interview experts
| Informant | Informant role | Organisation/institution | Organisation/institution type |
|---|---|---|---|
| #1 | Clinical scientist | Cambridge University Hospitals NHS | Health public body |
| #2 | Former policy analyst | UK Department for Environment, Food and Rural Affairs | Government |
| #3 | Lecturer of human and animal rights law | Faculty of Law, Cambridge University | Government |
| #4 | Corporate social responsibility and investment coordinator | Private global meat company | Meat industry |
| #5 | Engineer in meat packaging research | Meat packaging industry | Meat industry |
| #6 | ESG and corporate sustainability coordinator | Private global meat company | Meat industry |
| #7 | Co-founder | Cellular agriculture and clean meat organisation | Meat substitutes industry |
| #8 | Chief scientific officer | Private cellular agriculture company | Meat substitutes industry |
| #9 | Operations manager | Private plant-based meat company | Meat substitutes industry |
| #10 | Supply chain director | Private global fast food chain restaurant | Retail fast food chain |
| #11 | Vice president global foods supply chain | Private global food company | Food distributor |
| #12 | UK coordinator | Animal welfare international non-profit organisation | NGO |
Source: Authors’ own work
Innovative intervention strategies in the meat food system
| Intervention strategy | Meat food sub-system | Leverage point(s) | Key actor(s) | Supporting evidence |
|---|---|---|---|---|
| 1. Change labelling of meat products | Social |
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| 2. Rethink subsidies schemes | Institutional |
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| 3. Support the development and supply of protein alternatives | Value chain |
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| 4. Develop food choice and personalisation technologies | Cultural |
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| 5. Increase in meat prices | Economic |
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| 6. Improve animal welfare standards | Environmental |
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Source: Authors’ own work
Number of articles and journal subject areas covered in the review
| Journal title | Number of articles (in our review) |
Subject areas (as per the journal) |
|---|---|---|
| Appetite | 20 | Nursing: nutrition and dietetics; psychology: general psychology |
| Meat Science | 11 | Agricultural and biological sciences: food science |
| Journal of Agricultural and Environmental Ethics | 6 | Agricultural and biological sciences: agricultural and biological sciences (miscellaneous); arts and humanities: history; environmental science: environmental chemistry; environmental science: general environmental science |
| Food Quality and Preference | 4 | Agricultural and biological sciences: food science; nursing: nutrition and dietetics |
| Food Policy | 4 | Agricultural and biological sciences: food science; economics, econometrics and finance: economics and econometrics; environmental science: management, monitoring, policy and law; social sciences: development; social sciences: sociology and political science |
| Ecological Economics | 4 | Economics, econometrics and finance: economics and econometrics; environmental science: general environmental science |
| Environmental Communication | 4 | Environmental science: environmental science (miscellaneous); environmental science: management, monitoring, policy and law |
| British Food Journal | 3 | Agricultural and biological sciences: food science |
| Animals | 3 | Agricultural and biological sciences: animal science and zoology; veterinary: general veterinary |
| The Journal of Peasant Studies | 3 | Arts and Humanities: Arts and Humanities (miscellaneous); Social Sciences: Anthropology; Social Sciences: Cultural Studies |
| Food and Foodways | 3 | Agricultural and biological sciences: food science; social sciences: anthropology; social sciences: cultural studies; social sciences: health (social science); social sciences: sociology and political science |
| Climatic Change | 3 | Earth and Planetary Sciences: Atmospheric Science; Environmental Science: Global and Planetary Change |
| Food Security | 2 | Agricultural and biological sciences: agronomy and crop science; agricultural and biological sciences: food science; social sciences: development |
| Nature | 1 | Multidisciplinary |
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Source: Authors’ own work
Interview protocol outline
| Interview type | Semi-structured |
|---|---|
| Duration of each interview | One hour (approximately) |
| Main topics covered |
|
| Guidance questions |
|
Source: Authors’ own work
Salient points of experts’ interviews
| Informant | Stakeholder type | Informant’s role | Interview salient points |
|---|---|---|---|
| #1 | Health public body | Clinical scientist |
|
| #2 | Government | Former policy analyst |
|
| #3 | Government | Lecturer of human and animal rights law |
|
| #4 | Meat industry | Corporate social responsibility and investment coordinator |
|
| #5 | Meat industry | Engineer in meat packaging research |
|
| #6 | Meat industry | ESG and corporate sustainability coordinator |
|
| #7 | Meat substitutes industry | Co-founder |
|
| #8 | Meat substitutes industry | Chief scientific officer |
|
| #9 | Meat substitutes industry | Operations manager |
|
| #10 | Retail fast food chain | Supply chain director |
|
| #11 | Food distributor | Vice president global foods supply chain |
|
| #12 | NGO | UK coordinator |
|
Source: Authors’ own work
Appendix 1
Appendix 2
Appendix 3
Supplementary material
The supplementary data for this article can be found online.
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Acknowledgements
This research has been supported by the Costa Rican Ministry of Science, Technology and Telecommunications (MICITT) and the Costa Rican National Council for Scientific and Technological Research (CONICIT), National Scholarship No. FI-021B-18. This research has also received academic support from the Industrial Resilience Research Group at the Institute for Manufacturing, Department of Engineering, University of Cambridge, and financial support from Cambridge International Trust and Newnham College, Scholarship No. 10659661. The authors also acknowledge Dr. David Morgan for his guidance and support on an earlier version of this work.
Corresponding author
About the authors
Ms Mariel Alem Fonseca is a PhD candidate in the Industrial Resilience Research Group at the Institute for International Manufacturing, University of Cambridge. Her research focuses on the design of sustainable and resilient alternative protein supply chains. She has over six years of experience in process design and optimisation, supply chain management and data analytics and is particularly interested in the relationship between business productivity and environmental sustainability in the food industry. Mariel holds a Master in Engineering for Sustainable Development from the University of Cambridge and an undergraduate degree in Industrial Engineering from the University of Costa Rica.
Dr Naoum Tsolakis is Research Associate in Industrial Systems and Network Analysis at the Department of Engineering, University of Cambridge, where he focusses on the design, analysis and management of multi-level operations in sustainable supply network systems. More specifically, his main research and practice interests include the areas of simulation modelling and optimisation of end-to-end supply chain operations, enabled by digital technologies, to assess emerging configurational designs for the efficient management of industrial manufacturing networks. Naoum holds a five-year engineering diploma (top graduate for the Academic Year 2005–2006) and a PhD degree in mechanical engineering, along with four Masters degrees in the engineering and business management domains.
Dr Pichawadee Kittipanya-Ngam is an Assistant Professor of operations management at Thammasat Business School, Thailand. She is also a research affiliate at Institute for Manufacturing, University of Cambridge. Pichawadee specializes in research and practices on supply chain and management aspects of social enterprises. She is also a founder of Cambridge Babies, a social project encourages the early year development. The project, in collaboration with Cambridge Thai Foundation, annually donates part of profits as scholarships to Thai students at the University of Cambridge.