Is it possible to quantify the current resilience level of an agri-food system? A review of the literature
Agricultural and Food Economics volume 11, Article number: 45 (2023)
Nowadays being resilient is a requirement of all companies and more in general supply chains, as a consequence of the frequent disruptions which repeatedly affect systems and challenge markets from different sides. But how to state whether a company and its related supply chain are resilient or not? To address the present issue, a literature review was carried out on documents proposing quantitative tools or metrics for quantifying the resilience level of an agri-food supply chain, which is a specific field subjected to several threats and accordingly deserving attention. Due to the limited number of documents retrieved (i.e., 26 articles), stressing the gap to be filled in literature, mainly bibliometric analyses were performed on the sample, but contents were also deepened, resuming the different tools available at present. Results reflect the call for the development of models aiming at assessing the resilience of these systems before disruptions and non-controlled events occur; moreover, the industrial level turned out to be neglected, given the fact that all the studies deal with the farm stage (and in general agricultural activities).
According to several accredited dictionaries, the term resilience can be mainly defined in three different fields: in material sciences it represents the ability of a material to absorb energy under elastic deformation and to recover its energy at removal of a load (Vegas and Martin del Yerro 2013); in psychology, instead, it refers to how individuals recover from or adapt to stress and restore mental, psychological and emotional balance (Bowling et al. 2021); again, in ecology it represents the persistence of relationships within an ecosystem after disturbance, and it is a measure of the ability of ecosystems to absorb changes of state variables (Standish et al. 2014). Starting from these definitions in these application fields, the term resilience was declined and adapted in other different contexts, including that general of supply chains, for which resilience is considered as the responsiveness of the supply chain itself to any non-controlled event which may challenge it (Clavijo-Buritica et al. 2023). More specifically, as the first authors that attributed the definition of resilience to supply chains in 2004 stated (Kochan and Nowicki 2018), it refers to the ability of the system to return to its original state or move to a new more desirable one after being disturbed by any form of disruption (Christopher and Peck 2004). Starting from here there is a plethora of studies dealing with its definition, evolution and development, emphasizing the variability and the great factors affecting it (e.g., (Kochan and Nowicki 2018; Geske and Novoszel 2022; Simbizi et al. 2021)).
Undoubtedly, resilience represents one of the principal keywords associated with supply chains in the last decade, due to the several challenges they were subjected to; for instance, in primis the Covid-19 pandemic, but also the recent war between Russia and Ukraine which challenged economic systems and materials supply, the climate change that is actually further intensifying its impact, the water shortage in some geographical areas or the increasing world population requiring more food to be produced (Preite et al. 2023); and all the cascading effects deriving from these negative events. This is further stressed by the scientific activity focusing on this issue: a simple query on the Scopus database (https://www.scopus.com) having “resilience” and “supply chain” as keywords, at the beginning of year 2023 returns more than 3 thousand papers, half of which published in 2021 and 2022; this is surely a symptom of the relevance of the topic among the academic world. Clearly, aspects to be investigated and analyzed are manifold, as well as the fields of application.
This study originates from a practical need. Indeed, the authors of the present manuscript were required to quantitatively assess the as-is resilience level of an agri-food supply chain. In this field, in fact, resilience is an element of significant importance: as stressed by other authors, agri-food systems represent one of the major victims affected by the climate change (Bilali 2021; Borghesi et al. 2022), and they were damaged by the recent pandemic (Popescu and Popescu 2022); at the same time, they belong to one of the most relevant sector, since it guarantees the population’s food security, is an important source of income and livelihoods and is a contributor to the national gross domestic product. The food production is suitable for feeding a third of the world population (Herman 2015), and above all for this reason being resilient is mandatory; as stated by Miranda et al. (2023), new business models for agri-food supply chains should allow to increase levels of resilience to mitigate the negative consequence of possible crises similar to those already caused by pandemics or wars.
As always happens the starting point is the literature analysis to understand whether previous studies were already carried out and to define the state-of-the-art and immediately, at the first impact, what emerged was that there was a huge number of heterogeneous documents resulting from literature apparently dealing with resilience (as also confirmed by the results from the Scopus search mentioned few lines above), whose main argument deflected from the mere resilience topic: in other words, the feeling was a sort of abuse of the keyword resilience. This fact further made the research difficult, as the number of resulting documents intensified the work and the efforts to be involved, and resulted in few pertinent studies. Moreover, another element arose is that quite often quantitative assessments of the agri-food supply chain resilience (AFSCR, in the following) are made a posteriori or while the disruption is manifesting, and accordingly can only reveal the resilience level after a disturbance has occurred (or in the meantime); with reference to that, sometimes the resilience assessment is simply derived from surveys proposed to practitioners (e.g., (Hossard et al. 2021; Meldrum et al. 2018; Paas et al. 2021)), or there are some studies that provide a measure in terms of the average food price, of time/costs required to restore the situation (Proag 2014) or of failure in producing what was requested (Haqiqi and Bahalou Horeh 2021). But what about the as-is resilience level of a system, so before an unforeseen event occurs?
In addition, recalling the subdivision of a whole agri-food supply chain into three main phases, i.e., supply, production and distribution, if we consider with supply a phase in which the product is treated as raw material including activities such as cultivation or farming and with production the real industrial transformation as suggested by Tebaldi et al. (2021), the focus is only addressed toward the first one; indeed, no studies mentioning industrial plants or companies are addressed.
On the bases of these short premises, the aim of this paper is twofold: first of all, it presents the results from the literature analysis focusing on quantitative assessments of the AFSCR carried out at the beginning of 2023, whose initial research question was the following: how to measure the resilience of an agri-food supply chain? Second, this manuscript constitutes the call for the important development of quantitative models useful for managers and practitioners in order to assess the current resilience level of the supply chain they belong to, since prevention is better than cure. Indeed, having a structured tool that allows to derive the major areas in which the system is weak may support the decision management in understanding where the focus should be addressed. For instance, according to the opinion of the authors, the number of suppliers of a specific raw material can be considered a key indicator (e.g., from the side of a pasta producer, the wheat supply is essential, as is for the pasta sauce manufacturer the tomatoes); if the company in question has only a unique supplier for that basic material, this could constitute a warning, which could be detected by a model which considers the key elements to be monitored for ensuring an adequate resilience level. Ex-ante quantitative assessments are already proposed to deal with other food-related issues for their being useful tools to improve the understanding of dynamics and increase the evidence base underlying future actions (Mouratiadou et al. 2021); indeed, the numerical output is renowned for its being easily interpreted, comparable and immediate (Mikusova and Janeckova 2010).
This paper also responds to the call for more research in this area so as to design more efficient and resilient supply chains (Zhao et al. 2017), given the fact that nowadays food systems have no more to be designed only for economic efficiency as it happened in the past but must be re-evaluated for and according to their resilience (Stone and Rahimifard 2018).
The remainder of contents is organized as follows: Sect. "Methodology" proposes the methodology followed for carrying out the literature review as well as the analyses performed on the sample, both bibliometric and contents-related; Sect. "Results" deals with the results including the list of the tools found in the documents, followed by Sect. "Conclusions" presenting a brief discussion and the conclusions, including the relevant future research directions.
The starting point for carrying out the literature review on quantitative assessments and models for the AFSCR were 11 queries launched in January 2023 on the two main scientific database, i.e., Scopus and Web of Knowledge, for collecting pertinent documents. The queries are listed in Table 1.
No temporal constraints were set so as to include all the possible sources; only journal articles and conference papers written in English language were considered, given the fact that English is considered the main language of scientific dissemination. After having removed duplicates, this first research returned a total of 184 documents.
The authors started a first screening for selecting those papers which may fit with the topic in question; indeed, as already stressed in the introduction section, quite often the word resilience is improperly used and several articles were returned from the queries but were completely out of scope (for instance, this is the case of Salazar et al. (2019) whose focus is on the behavior of a specific microbiota or of Gwadz et al. (2021) which deals with the resilience of people affected by HIV in the early phase of the recent pandemic). As additional exclusion criterion, also studies carried out in fields different from that of agri-food were excluded, as well as those for which no specific sector was mentioned (e.g., (Anderson et al. 2020) whose research was conducted in the aerospace sector, or (Neves Santos and Magrini 2018) which deals with biorefineries); this constraint may preclude other pertinent assessments in other fields, which could be then adapted in this specific context, but at this stage it was decided to study the topic in its specific application field. As inclusion criterium, only documents in which a clear quantitative assessment was proposed or implemented with a clear numerical output (e.g., a percentage, or a score) were considered, and this was the strongest restriction which let the sample be further reduced.
This first screening returned a total of 44 papers (so approximately 24% of the initial sample). These 44 documents were further analyzed through a comprehensive reading, and according to the abovementioned inclusion/exclusion criteria the final sample corresponds to 26 articles.
At first, for these 26 documents bibliometric parameters were investigated, namely their temporal evolution, their type of document (i.e., journal article or conference proceeding), research methodology, geography of the study (made both according to the affiliation of the first author and to the country in which the study was carried out), most productive authors and citations. Regarding contents, instead, the elements investigated recall a framework proposed by other researchers and mentioned in further studies (Meuwissen et al. 2019) developed for investigating the resilience of farming systems, and adapted for the purposes of the present literature review. In this framework, 5 key questions are to be addressed, below listed, including their adaptation in the present study:
Resilience of what? To reply this question, the subject of the resilience assessment under investigation in each of the 26 document is defined (i.e., general AFSC, a country, resilience of water management etc.);
Resilience to what? This point refers to the challenges the subject of resilience defined in the first point is subject to; in other words, the type of disruption undermining a balanced situation;
Resilience for what purpose? In the original framework, at this stage it was recalled the fact that farming systems’ function can be divided into the provision of private and public goods: private goods include the production of food and other bio-based resources but also ensuring a reasonable livelihood for people involved in farming, while public goods comprise maintaining natural resources in good condition, animal welfare and ensuring that rural areas are attractive places for residence and tourism. In this analysis, this is translated into recognizing which dimension of resilience is addressed: economical (referring to private goods), environmental or social (referring to public goods);
What resilience capacities? The three capacities of resilience under stake in this fourth question are those of robustness, adaptability, transformability. Other authors as well refer to these capacities (e.g., (Paas et al. 2021; Bertolozzi-Caredio et al. 2022; Zawalinska et al. 2022)); some others, instead, similarly refer to the resilience capacities as anticipatory, coping and responsive (e.g., (Coopmans et al. 2021)). What these capacities have in common is the timing they manifest: robustness and anticipatory capacities occur before a disruption happens; adaptability and coping during the negative event and similarly capacities of transformability and responsive after. In the present research this information was translated into the moment in which the resilience assessment was performed: pre, in and post disruption occurrence;
What enhance resilience? This corresponds to the last question of the original framework, but according to the opinion of the authors, given the aim of the present manuscript, this question was re-interpreted into the following: what enhance the resilience assessment? And the reply is simply the summary of the tools and methods identified in the 26 screened documents, which is one of the contribution of the present manuscript.
The software Microsoft Excel™ was implemented for supporting these analyses.
For concluding this section, the authors are aware of the fact that the sample is constituted by a limited number of documents; however, other literature analyses rely on reduced samples (e.g., (Tebaldi et al. 2021) or (Bigliardi et al. 2023)), given the fact that this can be considered a result itself as well; it also follows that results cannot be generalized and no inferential statistics can be applied.
As already stated, after the second screening papers have significantly reduced in numerical terms, and only 26 scientific documents were included in the sample. Results are proposed in the subsections that follow: the first is dedicated to the bibliometric analyses, the second to the contents and the last third summarizes the quantitative AFSCR assessments and replies to the last fifth question of the abovementioned framework.
The temporal distribution of the reviewed documents is proposed in Fig. 2, below.
As it is possible to deduce from the graph, the topic in question is mainly investigated in the last five years (as partially expected), starting from 2018 which is the most productive. After the pandemic year as well, i.e., 2020, a considerable number of articles was recorded (15, so approximatively half of the sample). From the first document in 2008, however, there is a long period of almost ten years in which no study specifically dealt with a quantitative assessment of the AFSCR. Overall, it is not possible to derive a specific trend for this argument as production over time is extremely heterogeneous and the number of documents is limited; it can only be stated that in numerical terms documents are timidly growing.
As far as the type of document is concerned, they are all from scientific international journals; no conference proceeding was recorded, probably symptom of the fact that, when discussed, the topic is worth of scientific journals rather than a conference act. Going into the detail of the journals, it is worth mentioning Agricultural Systems by Elsevier (4 publications), and Ecological Indicators (Elsevier, again), Environment, Development and Sustainability (Springer) and Sustainability (MDPI), all with two contributions.
Another descriptive parameter investigated was the research methodology implemented for carrying out the study; specifically, this classification was made according to the guidelines proposed in Seuring and Muller (2008), which identify five different methodologies: empirical surveys, case studies, theoretical and conceptual papers, modeling papers and literature reviews. First of all note that in line with the topic treated, as well as with the inclusion criterium of proposing numerical assessment of resilience, no literature review was recorded in the sample, while in most cases we deal with empirical studies, analyzing collected data from real contexts or by means of questionnaire surveys. The resulting classification is proposed in the pie chart of Fig. 3.
As far as the geography is concerned, the analysis was carried out in a twofold way: indeed, while performing the first screening, it emerged that quite often the geography of the first author did not match with the country of the study, and quite often as well the affiliation of the first author corresponded to a western state, while the analyses and the research were carried out in Asiatic or African regions (i.e., developing countries); according to that, both the geographies were investigated.
The first table and figure (i.e., Table 3 and Fig. 4) refer to the classification depending on the affiliation of the first author, while the following (i.e., Table 4 and Fig. 5) to the country in which the study was carried out.
Overall, from the first classification 20 countries were found; from the second, instead, 18 (plus a study referring in general to the Asiatic region, i.e., (Dixon et al. 2021) and one implemented in 156 countries labeled worldwide, i.e., (Chaudhary et al. 2018)). What at first stands out is that, when shifting from the results deriving from the nationality of the first author to those returned from the country in which the assessment was performed, some countries disappear (i.e., Australia, Brazil, Canada, France, Germany, Portugal, Turkey and United Kingdom), while some others appear, namely Bangladesh, Bolivia, Cyprus, Indonesia, Kenya and Niger. In other words, it is possible to notice an albeit weak trend highlighting that more developed countries perform their resilience-related studies in poor and less developed ones; this is supported, for instance, by Upton et al. (2022), whose first author is form the USA, but the study was then carried out in both Ethiopia and Niger; by Jacobi et al. (2018) whose first author comes from Switzerland, and the research took place in Bolivia and Kenya; or again by Meldrum et al. (2018) whose research center of the first author is Italian but the study was developed in Bolivia. A possible explanation, given the fact that some of these studies address the resilience of African families, is that these regions are particularly affected by the climate change in the guise of drought, and accordingly this fact could have attracted researchers. As expected, the two papers for which no specific country was involved for the research are the two articles belonging to the theoretical and conceptual papers group with reference to their methodology (i.e., (Zhao et al. 2018) and (Valenti et al. 2018)). Overall, the only two notably countries are the USA which contributed with 4 documents, and Switzerland (3 articles); as far as the research territory, instead, it can be noted that some developing countries such as Bangladesh, Indonesia or Niger are not represented by any authors, supporting the sentence stated few lines above.
Other two bibliometric parameters investigated are the presence of an author in more publications, and the citations trend. Regarding the first, out of 26 documents a total of 157 different authors was recorded.
Only one of them contributed with two studies, namely Isabeau Coopmans from the KU Leuven (Belgium) and their two empirical studies published both in 2021 respectively deal with a survey aimed at assessing the resilience of Flemish food supply chain in the immediate post Covid-19 pandemic (Coopmans et al. 2021) and with a participatory assessment on the resilience and sustainability of three farming systems focused on three different products, i.e., hazelnuts, potatoes and a dairy (Paas et al. 2021).
Overall, most of the documents have 3, 4 or 5 authors (respectively, 6 papers, 5 and 4); one single paper has only one author (i.e., (Cetinkaya Ciftcioglu 2022)), and 4 documents have a number of contributions equal or greater than 8. It is definitely worth nothing a paper with 45 authors (i.e., (Dixon et al. 2021)).
As far as citations are concerned, which may reflect the interest of the topic among the academic community, 10 documents do not have any citation (recently published); 8 documents are within the range of 1–25 mentioning in other studies, 5 between 30–50, and finally there are three studies worth of noting for their resonance: the first, with 87 mentioning deals with the resilience assessment of households toward droughts (i.e., social resilience) (Keil et al. 2008); note that this is the oldest document of the sample (it was published 15 years ago), and surely this may have impacted on this result since clearly for more recent papers it is difficult to reach such numbers. The other two documents published five years ago in 2018 are both focused on a multi-indicators sustainability assessment, in the first case of aquaculture systems (Valenti et al. 2018), while in the second of global food systems (Chaudhary et al. 2018); respectively, they are mentioned in other documents 107 and 243 times at the time this research was conducted.
After the round of bibliometric analyses, contents were addressed. Recalling the order of the questions of the starting framework (Meuwissen et al. 2019), the subsections that follow propose the replies.
Resilience of what?
At first, the subject of the resilience assessment of each document was identified. Table 5 illustrates outcomes. Note that a single document (i.e., (Maydana et al. 2020)) compares twice since two issues are addressed, namely the resilience of both soil and water subjects.
Overall, in most cases the subject of resilience is the general AFSC, and it is worth noting that it is mostly referred to what has been defined in the introduction the supply level, i.e., agricultural and farming activities; indeed, the only document in which the agroindustry is mentioned is (Jacobi et al. 2018), revealing as already stated a gap which should be filled. It is also worth of mention the fact that in four documents the resilience of households it quantified; the peculiarities of these four documents is that all these empirical studies are survey-based and carried out in less developed countries, i.e., Bangladesh (Béné et al. 2017), Ethiopia (Upton et al. 2022; Williams et al. 2020), Indonesia (Keil et al. 2008) and Niger (Upton et al. 2022). Another interesting common characteristic is that, exception for one document (i.e., (Béné et al. 2017)), in the remaining three the disruption affecting families and toward which the resilience level is determined is the climate change, and more specifically the already mentioned droughts.
Resilience to what?
To reply to the second question, the type of disruption or negative event which challenges the system and accordingly may affect the equilibrium was investigated: in 11 documents out of 26 no reference to a specific disturbance was mentioned; in the remaining sample, instead, the majority of cases (i.e., 11) deals with the climate change and the concerns that derive, such as droughts (e.g., (Sharma and Kumar Goyal 2018)) or water shortage (e.g., (Xu et al. 2021)); only three studies treated the Covid-19 issue (i.e., (Haqiqi and Bahalou Horeh 2021; Coopmans et al. 2021; Dixon et al. 2021)), while in one unique paper the topic of pest infections which could affect plants is addressed (i.e., (Rescia and Ortega 2018)). To be honest, it was expected a greater impact from the pandemic side, having passed three years. The pie chart of Fig. 6 graphically resumes these results.
Resilience for what purpose?
Regarding the dimensions of the resilience, recalling the triple bottom line (TBL) concept related to sustainability (Alhaddi 2015) and adapted to that of public and private goods for addressing the third question, outcomes are below proposed, in Fig. 7.
Most of the papers (i.e., 11) considers all the three dimensions of resilience, as it happens for the sustainability concept. When deepening the analysis of the single pillars, instead, the main outcome reveals that in the majority of documents (i.e., 8) the economic aspect is investigated, and it does not surprise at all; in fact, when referring to the AFSCR, it is meant the ability of a system to recover after disturbances implicitly referring to its system in terms of productivity, and accordingly an economic-related issue. As also stressed in the introduction section, in fact, in several cases the resilience is a posteriori evaluated in terms of non-production, time or costs employed for restoring the equilibrium or food price, and accordingly in economic terms. It is equally unsurprising that in the four documents whose focus is on the social aspect the subject of the resilience assessment are the households, and is mainly addressed to a food security assessment. For concluding this aspect, when referring to the three documents focusing on the mere environmental dimension, research whose subject of resilience is a natural resource (e.g., water, soil or landscape) are recalled.
What resilience capacities?
As far as the moment in which the study was carried out and implicitly referring to the abovementioned capacities and recalling the proposed subdivision into pre, in and post resilience assessment, numerical outcomes are proposed below, in Fig. 8. For let the readers better understanding how this classification was carried out, for each group an example is provided: (Clavijo-Buritica et al. 2023) fits in the “pre” group since this work is based on a simulation study which simulates the behavior of the network, and the disruption has not yet occurred; this second study (Chaudhary et al. 2018), instead, regards the assessment of the as is situation of a system during the disruption, while this third (Coopmans et al. 2021) investigated the resilience after a disruption manifested (in this specific case after the Covid-19 pandemic).
Most of the documents under investigation (i.e., 14) analyzes the as is impact on the subject in question; note that all the three documents dealing with the Covid-19 pandemic, as expected, are studies aimed at assessing post effects. It is important to stress, going back to the origin of the present study, that for an as-is assessment of the AFSCR the pre phase is relevant, corresponding to the above mentioned anticipatory capacity, representing the robustness of the system as a whole.
What enhance the resilience assessment?
The last subsection of the results is dedicated to summarize the quantitative assessments which were derived from the 26 documents, and aimed at replying the fifth final question of the initial framework. This represents one of the contribution of the paper, since interested researchers or practitioners may refer to this summary for their scope and needs.
As emerged, in several cases the resilience is computed on the bases of a questionnaire survey result, for instance according to an achieved score; according to that, at first documents in which the assessment is based on a survey score achieved by respondents and interested parties are recalled and detailed in Table 6. The grading scale is clearly different depending on the study.
In the abovementioned cases, the resilience level is simply determined according to the responses of the surveyed participants to the issues posed to them. The surveys are significantly different, as well as are their aims and the indicators considered, as deductible from the last column referring to their description. However, surely a weakness of such investigations is that replies (and accordingly scores) are subjective: the level of perception can vary from respondent to respondent, and may not really reflect the real status.
In other documents, instead, specific indexes or ad hoc models were used or derived and implemented for computing the resilience level. For completeness and for the interest of readers and practitioners, they are resumed in the table below (Table7).
The findings proposed in the two tables above are definitely heterogeneous: sometimes they refer to a determined subject, to a specific dimension, sometimes to a model or to an index; accordingly, their application field may vary as well and it is difficult to derive common characteristics or limits, since each of them has its own. They only share the fact that a numerical output measuring a determined resilience dimension is derived. It is interesting to note that among the papers addressing a multi-dimensional assessment of sustainability (Valenti et al. 2018; Maydana et al. 2020; Chaudhary et al. 2018), resilience is considered among the factors affecting the sustainability level of a system, as also previously stressed by other authors (e.g., (Javed Iqbal et al. 2022)); thus the reason for their inclusion. According to their needs, readers are invited to refer to the specific manuscripts for deepening the models.
In this manuscript outcomes from a literature analysis carried out on documents dealing with quantitative assessments of AFSCR are proposed, so as to reply to the original research question to be addressed: how to measure the resilience of an agri-food supply chain? Actually, we could not reply at all. Surely the reduced number of documents, namely 26, attracted the attention, being considered a first symptom of the fact that probably the topic is poorly treated, and this was confirmed.
Going in order, at first the temporal evolution of the journal studies was investigated, showing a timidly growing trend starting from year 2018, after approximately ten silent years from the first paper of the sample. The reason can be attributed to the fact that, at present, harmful events impacting supply chains are unfortunately increasing, both in number and in forms, and force to face new challenges.
The first bibliometric analyses let emerge the fact that, as expected and in line with the topic, the most common methodology is that of empirical studies, and with reference to the geography sometimes there is a mismatch between the affiliation of the authors and the country in which the study is then developed, and this happens quite often when dealing with social resilience of households, being families located in less developed countries. USA and Switzerland stand out for their scientific production in terms of number of publications. However, the feeling is that now also developed (e.g., European or North American) countries were bent for several reasons not previously considered; as a consequence more studies are expected to assess their attitude and behavior.
As far as contents are concerned, the subject of the resilience assessment turned out to be in most cases the general AFSC, with a specific focus at the farm level; indeed, no mentioning to production or transformation of food (i.e., to the industry) was found. According to the opinion of the authors, this could be actually due to the fact that, so far, resilience was mainly associated with environmental issues such as the climate change, whose primary and direct impact is on agricultural productivity; as a consequence of a pandemic and a recent war that no one would have imaged, the equilibrium of companies as well started to waver; this surely reveals a gap which should be filled. Families as well quite often are under exam, specifically in terms of food security and accordingly the social side of resilience.
Several documents do not refer to a specific disruption, but among those in which it is manifested the climate change is recalled, probably as already emphasized given the fact that so far it was considered the main negative event; more into detail, when dealing with social resilience effects of droughts are referred. A greater component from the recent Covid-19 pandemic was expected, but in only few documents it was mentioned; undoubtedly, effects are still being felt. With reference to the resilience dimensions, it was noted that in most cases the economic aspect is predominant, supporting the definition of resilience from the managerial point of view; however, among literature a great attention to a social resilience as well was found, while the environmental aspect turned out to be the less debated but this outcome as well is in line with the resilience definition.
Overall, the main issue returned from the present research is that, at present, a structured analytic model to be used both from researchers and practitioners for assessing the resilience level of an AFSC does not exist; and in fact this paper represents the call for future research on the development of models for this purpose, both at farm and industry stage. Indeed, existing general evaluations as anticipated in the introduction section, mainly refer to post (or also in) effect assessments so as to reply to the question addressing if the system was resilient or not. But the as-is resilience level so as to prevent a disruption may be useful to highlight where the efforts should be addressed for increasing the robustness of a system and being able to face any event. This last statement may be interpreted in contrast to the reply to the fourth question referring to the moment in which the assessment was carried out, as it emerged that in the majority of documents the in-resilience was investigated; however, in resilience means that the disruption has already occurred and started to impact the system, and accordingly its potential shortcomings could have already manifested.
As a final remark, results from this scientific review should give pause for thought on the usage of the term resilience among the scientific community: by involving pertinent keywords, starting from a total of 184 documents, only 26 turned out to be really suitable. We are aware of the fact that quite often this happens when reviewing, but we all know that this particular word, resilience, is currently in fashion. Resilience can be everything and nothing. The authors wish for a conscious use of the term with its real meaning.
Surely a limit of this research is represented by one of the inclusion criterium depicted in the methodology section, which stated that only assessments in the agri-food field could be included; as already declared in the methodology section in other fields, some methods or tools could have been already developed and implemented, and may be adapted to this field. In this regard, expanding the search in other contexts in terms of literature analysis represents a future directions which the authors surely will deepen. Another limit already mentioned is the scarce number of reviewed documents, which impacted in terms of analyses that could be performed on the sample and on the general statistics which could be applied. Other research, moreover, may include investigations of the social resilience of households in western well and are not limited to the emerging ones. As last limitations, it is worth noting that only documents written in English language were considered, and this may have caused the exclusion of articles not respecting this criterium; moreover, only Scopus and WoS database were involved in the research, neglecting some documents which may be found in other minor database such as Google Scholar.
Finally, for the future, as the main aim of this paper stresses, quantitative models for the assessment of the AFSCR are expected, including more contributions from the scientific community.
Availability of data and materials
Agri-food supply chain resilience
Exempli gratia (for example)
Framework of Participatory Impact Assessment for Sustainable and Resilient FARMing systems
id est (that is)
Notre Dame Global Adaptation Initiative
Resilience Capacity Index
Resilience Indicators for Measurement and Analysis
Self-evaluation and Holistic Assessment of Climate Resilience of Farmers and Pastoralists
Triple bottom line
Total Interpretive Structural Modeling
Vulnerability and Resilience Indicators Model
Water use efficiency
Alhaddi H (2015) Triple bottom line and sustainability: a literature review. Bus Manag Stud 1:2
Anderson K, Hotchkiss E, Myers L, Stout S, Grue N, Gilroy N, Aldred J, Rits M (2020) After the hurricane: validating a resilience assessment methodology. Int J Disast Risk Reduc 51:101781
Béné C, Chowdhury F, Rashid M, Dhali S, Jahan F (2017) Squaring the circle: reconciling the need for rigor with the reality on the ground in resilience impact assessment. World Dev 97:212–231
Bertolozzi-Caredio D, Soriano B, Bardaji I, Garrido A (2022) Analysis of perceived robustness, adaptability and transformability of Spanish extensive livestock farms under alternative challenging scenarios. Agric Syst 202:103487
Bigliardi B, Bottani E, Casella G, Filippelli S, Petroni A, Pini B, Gianatti E (2023) Industry 4.0 in the agrifood supply chain: a review. Procedia Comput Sci 217:1755–1764
Borghesi G, Stefanini R, Vignali G (2022) Life cycle assessment of packaged organic dairy product: a comparison of different methods for the environmental assessment of alternative scenarios. J Food Eng 318:110902
Bowling J, Jason K, Cross L, Vercruysse C, Reichard G (2021) Definition and operationalization of resilience in qualitative health literature: a scoping review. Int J Soc Res Methodol 25(2):1–16
Cetinkaya Ciftcioglu G (2022) Assessment of the resilience of the agricultural landscapes and associated ecosystem services at multiple scales (a farm and landscape) in Kyrenia (Girne) Region of Northern Cyprus. Landsc Ecol Eng 18:277–298
Chaudhary A, Gustafson D, Mathys A (2018) Multi-indicator sustainability assessment of global food systems. Nat Commun 9:848
Chen C, Noble I, Hellmann J, Coffee J, Murillo M, Chawla N (2015) University of Notre Dame Global Adaptation Index—country index technical report, ND-GAIN: South Bend, IN, USA
Christopher M, Peck H (2004) Building the resilient SC. Int J Logist Manag 15(2):1–14
Cissé J, Barret C (2018) Estimating development resilience: a conditional moment-based approach. J Dev Econ 135:272–284
Clavijo-Buritica N, Triana-Sanchez L, Escobar J (2023) A hybrid modeling approach for resilient agri-supply network design in emerging countries: Colombian coffee supply chain. Socio-Econ Plan Sci 85:101431
Coopmans I, Bijttebier J, Marchand F, Mathijs E, Messely L, Rogge E, Sanders A, Wauters E (2021) COVID-19 impacts on Flemish food supply chains and lessons for agri-food system resilience. Agric Syst 190:103136
Diserens F, Humphries Choptiany J, Barjolle D, Graeub B, Durand C, Six J (2018) Resilience assessment of Swiss farming systems: piloting the SHARP-tool in Vaud. Sustainability 10(12):4435
Dixon J, Weerahewa J, Hellin J, Fay Rola-Rubzen M, Huang J, Kumar S, Das A, Ejaz Quereshi M, Krupnik T, Shideed K, Jat M, Vara Prasad P, Yadav S, Irshad A, Asanaliev A, Abugalieva A, Karimov A, Bhattarai B, Balgos C, Benu F et al (2021) Response and resilience of Asian agrifood systems to COVID-19: an assessment across twenty-five countries and four regional farming and food systems. Agric Syst 193:103168
El Bilali H (2021) Climate change and agriculture in Burkina Faso. J Aridl Agric 7:22–47
F. a. A. Organization (2016) Resilience index for measurement and analysis—II: analysing resilience for better targeting and action
Geske AM, Novoszel L (2022) Definition and development of supply chain resilience. In: Supply chain resilience: insights from theory and practice. Springer, pp 3–23
Gwadz M, Campos S, Freeman R, Cleland C, Wilton L, Sherpa D, Ritchie A, Hawkins R, Allen J, Martinez B, Dorsen C, Collins L, Hroncich T, Cluesman S, Leonard N (2021) Black and latino persons living with HIV evidence risk and resilience in the context of COVID-19: a mixed-methods study of the early phase of the pandemic. AIDS Behav 25(5):1340–1360
Haqiqi I, Bahalou Horeh M (2021) Assessment of COVID-19 impacts on U.S. counties using the immediate impact model of local agricultural production (IMLAP). Agric Syst 190:103132
Heckelman A, Smukler S, Wittman H (2018) Cultivating climate resilience: a participatory assessment of organic and conventional rice systems in the Philippines. Renew Agric Food Syst 33(3):225–237
Herman A (2015) Enchanting resilience: relations of care and peopleeplace connections. J Rural Stud 42:102–111
Hossard L, Fadlaoui A, Ricote E, Belhouchette H (2021) Assessing the resilience of farming systems on the Sais plain, Morocco. Region Environ Change 21:36
Ibarraran Viniegra M, Malone E, Brenkert A (2010) Climate change vulnerability and resilience: current status and trends for Mexico. Environ Dev Sustain 12(3):365–388
Jacobi J, Mukhovi S, Llanque A, Augstburger H, Kaser F, Pozo C, Ngutu Peter M, Delgrado J, Kiteme B, Rist S, Speranza C (2018) Operationalizing food system resilience: an indicator-based assessment in agroindustrial, smallholder farming, and agroecological contexts in Bolivia and Kenya. Land Use Policy 79:433–446
Javed Iqbal K, Akhtar N, Amir S, Irfan Khan M, Shah A, Ur Rehman Tariq M, Ullah W (2022) Multi-variable governance index modeling of government’s policies, legal and institutional strategies, and management for climate compatible and sustainable agriculture development. Sustainability 14(18):11763
Karan E, Asgari S, Asadi S (2023) Resilience assessment of centralized and distributed food systems. Food Secur 15:59–75
Keil A, Zeller M, Wida A, Sanim B, Birner R (2008) What determines farmers’ resilience towards ENSO-related drought? An empirical assessment in Central Sulawesi, Indonesia. Clim Change 86:291–307
Kochan C, Nowicki D (2018) Supply chain resilience: a systematic literature review and typological framework. Int J Phys Distrib Logist Manag 48(8):842–865
Maydana G, Romagnoli M, Cunha M, Portapila M (2020) Integrated valuation of alternative land use scenarios in the agricultural ecosystem of a watershed with limited available data, in the Pampas region of Argentina. Sci Total Environ 714:136430
Meldrum G, Mijatovic D, Rojas W, Flores J, Pinto M, Mamani G, Condori E, Hilaquita D, Gruberg H, Padulosi S (2018) Climate change and crop diversity: farmers’ perceptions and adaptation on the Bolivian Altiplano. Environ Dev Sustain 20:703–730
Meuwissen M, Feindt P, Spiegel A, Termeer C, Mathijs E, de Mey Y, Finger R, Balmann A, Wauters E, Urquhart J, Vigani M, Zawalinska K, Herrera H, Nicholas-Davies P, Hansson H, Paas W, Slijper T, Coopmans I, Vroege W, Ciechomska A, Accantino F, Kopainsky B, Poortvliet P, Candel J, Maye D, Severini S, Senni S, Soriano B, Lagerkvist C-J, Peneva M, Gavrilesco C, Reidsma P (2019) A framework to assess the resilience of farming systems. Agric Syst 176:102656
Mikusova M, Janeckova V (2010) Developing and implementing successful key performance indicators. World Acad Sci Eng Technol 42:969–981
Miranda F, Garcia-Gallego J, Chamorro-Mera A, Valero-Amaro V, Rubio S (2023) A systematic review on the literature on agri-food business models: critical review and research agenda. Brit Food J 6:66
Mouratiadou I, Latka C, van der Hilst F, Muller C, Berges R, Bodirsky B, Ewert F, Faye B, Heckelei T, Hoffmann M, Lehtonen H, Lorite I, Nendel C, Palosuo T, Rodriguez A, Rotter R, Ruiz-Ramos M, Stella T, Webber H, Wicke B (2021) Quantifying sustainable intensification of agriculture: the contribution of metrics and modelling. Ecol Indic 129:107870
Neves Santos V, Magrini A (2018) Biorefining and industrial symbiosis: a proposal for regional development in Brazil. J Clean Prod 177:19–33
Nunez-Lopez J, Cansino-Loeza B, Sanchez-Zarco X, Ponce-Ortega J (2022) Involving resilience in assessment of the water–energy–food nexus for arid and semiarid regions. Clean Technol Environ Policy 24:1681–1693
Paas W, Coopmans I, Severini S, Van Ittersum M, Meuwissen M, Reidsma P (2021) Participatory assessment of sustainability and resilience of three specialized farming systems. Ecol Soc 26(2):2
Popescu G, Popescu M (2022) COVID-19 pandemic and agriculture in Romania: effects on agricultural systems, compliance with restrictions and relations with authorities. Food Secur 14:557–567
Preite L, Solari F, Vignali G (2023) Technologies to optimize thewater consumption in agriculture: a systematic review. Sustainability 15:5975
Proag V (2014) Assessing and measuring resilience. Procedia Econ Finance 18:222–229
Remans R, Wood S, Saha N, Anderman T, DeFries R (2014) Measuring nutritional diversity of national food suplies. Glob Food Secur 3:174–182
Rescia A, Ortega M (2018) Quantitative evaluation of the spatial resilience to the B. oleae pest in olive grove socio-ecological landscapes at different scales. Ecol Indic 84:820–827
Salazar N, Arboleya S, Fernandez-Navarro T, de Los Reyes-Gavilan C, Gonzalez S, Gueimonde M (2019) Age-associated changes in gut microbiota and dietary components related with the immune system in adulthood and old age: a cross-sectional study. Nutrients 11(8):1765
Seuring S, Muller M (2008) From a literature review to a conceptual framework for sustainable supply chain management. J Clean Prod 16:1699–1710
Sharma A, Kumar Goyal M (2018) Assessment of ecosystem resilience to hydroclimatic disturbances in India. Glob Change Biol 24(2):e4432–e4441
Simbizi D, Benabbou L, Urli B (2021) Systematic literature reviews in supply chain resilience: a systematic literature review. In: Proceedings of the international conference on industrial engineering and operations management—11th annual international conference on industrial engineering and operations management, IEOM 2021, Virtual, Online
Smith L, Frankenberger T (2018) Does resilience capacity reduce the negative impact of shocks on household food security? Evidence from the 2014 floods in Bangladesh. World Dev 102:358–376
Smith L, Frankenberger T, Langworthy B, Stephanie M, Spanggler N, Downen J (2022) Ethiopia pastoralist areas resilience improvement and market expansion (PRIME) project impact evaluation, Feed the Future FEEDBACK Project Report, USAID
Standish R, Hobbs R, Mayfield M, Bestelmeyer B, Suding K, Battaglia L, Eviner V, Hawkes C, Temperton V, Cramer V, Harris J, Funk J, Thomas P (2014) Resilience in ecology: abstraction, distraction, or where the action is? Biol Conserv 177:43–51
Stone J, Rahimifard S (2018) Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework. Supply Chain Manag Int J 23(3):207–238
Tebaldi L, Vignali G, Bottani E (2021) Digital twin in the agri-food supply chain: a literature review. In: IFIP advances in information and communication technology
Upton J, Constenla-Villoslada S, Barret C (2022) Caveat utilitor: a comparative assessment of resilience measurement approaches. J Dev Econ 157:102873
Valenti W, Kimpara J, de L Preto B, Moraes-Valenti P (2018) Indicators of sustainability to assess aquaculture systems. Ecol Indic 88:402–413
Vegas M, Martin del Yerro J (2013) Stiffness, compliance, resilience, and creep deformation: understanding implant-soft tissue dynamics in the augmented breast: fundamentals based on materials science. Aesthet Plast Surg 37:922–930
Volkov A, Zickiene A, Morkunas M, Balezentis T, Ribasauskiene E, Streimikiene D (2021) A multi-criteria approach for assessing the economic resilience of agriculture: the case of Lithuania. Sustainability 13(4):2370
Williams T, Guikema S, Brown D, Agrawal A (2020) Resilience and equity: quantifying the distributional effects of resilience-enhancing strategies in a smallholder agricultural system. Agric Syst 182:102832
Xu W, Zhong Z, Proverbs D, Xiong S, Zhang Y (2021) Enhancing the resilience of the management of water resources in the agricultural supply chain. Water 13(12):1619
Zawalinska K, Was A, Kobus P, Bankowska K (2022) A framework linking farming resilience with productivity: empirical validation from Poland in times of crises. Sustain Sci 17(1):81–103
Zhao G, Liu S, Lopez C (2017) A literature review on risk sources and resilience factors in agri-food supply chains. In: PRO-VE 2017: collaboration in a data-rich world
Zhao G, Liu S, Lu H, Lopez C, Elgueta S (2018) Building theory of agri-food supply chain resilience using total interpretive structural modelling and MICMAC analysis. Int J Sustain Agric Manag Inf 4:3/4
This study was carried out within the Agritech National Research Center and received funding from the European Union Next-Generation EU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)—MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4—D.D. 1032 17/06/2022, CN00000022). This manuscript only reflects the authors’ views and opinions and neither the European Union nor the European Commission can be considered responsible for them.
The authors declare that they have no conflict of interest.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Tebaldi, L., Vignali, G. Is it possible to quantify the current resilience level of an agri-food system? A review of the literature. Agric Econ 11, 45 (2023). https://doi.org/10.1186/s40100-023-00286-3