1. Introduction
Supply chains (SCs) are vital for economic development in a globalized world. In its most general form, the SC is defined as a system in which raw materials are converted into final products and are delivered to consumers [
1]. However, companies are concerned about a broader complex system called Supply Chain Network (SCN). The SCN is defined as a network of organizations and processes where various stakeholders (i.e., suppliers, manufacturers, distributors, retailers, among others) collaborate to acquire raw materials, convert them into final products, and deliver them to costumers [
2,
3,
4].
Considering the types of decision-making in the SCN, one of the most expensive and irreversible long-term, strategic decisions is the Supply Chain Network Design (SCND) [
5]. The SCND is a problem whose decisions include “the assignment of facility role; location of manufacturing-, storage-, or transportation-related facilities; and the allocation of capacity and markets to each facility” [
6] (p. 108). As stated by Yu and Solvang [
7], SCND involves several decision levels. The strategic level includes the optimal network configuration and at a tactical level the optimal use of such infrastructure. Particularly, operational decisions in the SCND include fulfillment of customer demands, pricing, and provided service level [
8].
Therefore, the complexity of the decisions in the SCND is related to the strategies needed for increasing the value-added, efficiency, resilience, and sustainability of the network structures. Hence, the integration of resilience and sustainability into the SCND has emerged as key criteria, considering that a system that cannot recover from disruptions will not be able to recover its original quality and therefore will not be able to fulfill its social, environmental, and economic function [
9].
The concept of resilience has had multiple definitions in various contexts, starting with Holling’s study on the stability of ecosystems [
10]. Other definitions are related to individual and community (psychology) and organizational and supply chain contexts [
11,
12]. Resilience can be defined as “the ability of a system to return to its original state or move to a new more desirable state after being disturbed” [
13] (p. 2). In terms of the supply chain, resilience can be defined as “The adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions, and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and functions.” [
12] (p. 131).
In the case of micro and small enterprises (MSEs), additional complexities arise compared to the supply chains of medium and large companies, mainly that are influenced by factors such as market structures, institutions, and the business environment. The design of resilient chains for MSEs must consider these complexities because these companies have important contributions in regional development due to their local character and history [
14]. This fact has been magnified due to the pandemic of COVID-19 that has generated a great impact in supply chains both in magnitude (scale of the impact) and duration (length of the impact) [
15]. Thus, the resilience of supply chains has become important considering the local disturbances that can spread upstream and downstream affecting the entire chain. This phenomenon is known as the ripple effect [
16].
In the literature, different frameworks of resilient SC have been studied. For example, Christopher and Peck [
13] proposed four fundamental aspects for the creation of resilient supply chains: (i) the engineering or re-engineering that focus on risk reduction, (ii) collaboration across the network, (iii) agility, and (iv) a risk management culture. Another work is presented by Ponomarov and Holcomb [
12] who established the relationship between specific capabilities (i.e., control, coherence, and connectedness) throughout the phases of resilience, i.e., readiness, response, and recovery. Furthermore, recently, Purvis et al. [
17] developed the RALF resilience framework in which resilience is defined through Robustness, Agility, Leanness, and Flexibility.
Regarding sustainability, its economic dimension was first defined by the United Nations Brundtland Commission as the “development of the needs of the present without compromising the ability of the future generations to meet their own needs” [
18] (p. 14). Since then, different theories have emerged for complementing the original concept of sustainability, e.g., the Triple Bottom Line (TBL) [
19,
20]. Therefore, the concept of sustainability has evolved into the so-called Sustainable Development Goals (SDGs) [
21], defined into 17 goals as a United Nations agenda for 2030.
The analysis of the SDGs in supply chain management starts addressing materials and information flows [
22]. For example, Genc [
23] studied the closed-loop supply chain structures relations considering industry investment, innovation, affordability, clean product, and responsible consumption/production; Jouzdani and Govindan [
24] proposed a mathematical model of sustainable network design for perishable products and established its contribution to the objectives of zero hunger, affordable and clean energy, decent work and economic growth, climate actions, among others; and Tsolakis et al. [
25] studied the design of blockchain-centric supply chains to achieve SDGs.
Particularly, the intersection between resilience and organizational sustainability and its relationship with business continuity management emerges as an important topic in academia and industry [
26]. This integration can be seen as a complex but relevant criterion in the SCND. Thus, contributions including frameworks in the subject have increased over time. For example, de Souza et al. [
27] propose a framework that migrates the design of supply networks from an anthropocentric vision to a biocentric and transdisciplinary vision; this can lead to long-term SCND and ensure sustainable functionality and feasibility while adapting to disruptions.
The difficulty in implementing sustainability and resilience practices in supply chains lies in the contradictory objectives that entail, for example, focusing on efficiency (sustainable) or flexibility (resilient); the study developed by Rajesh [
28] identifies these underlying contradictory objectives and the trade-offs among them. Despite its academic and practical relevance, the existing literature reviews study separately resilience and sustainability criteria in the SCND. Thus, this work wants to contribute to fulfilling this gap by providing a systematic review of Resilient and Sustainable Supply Chain Network Design (SRSCND).
The following contributions are given in this study: (i) Provides recent development in the field of Supply Chain Network Design, (ii) highlights the importance of considering sustainability and resilience criteria in the supply chain design decisions, (iii) addresses the Sustainable Development Goals in the SCND, and (iv) identifies research gaps and proposes future research trends.
The remainder of this document is organized as follows:
Section 2 describes previous reviews of SCND considering resilience or sustainability criteria.
Section 3 explains the review methodology.
Section 4 shows a descriptive analysis of the selected documents. The main findings of this paper are presented in
Section 5.
Section 6 presents the insights and the future research directions, and
Section 7 presents the concluding remarks.
2. Previous Reviews and Position of Our Work
This section will summarize some of the most representative related reviews that consider resilience, sustainability, or both on the SCND.
An effective, responsive, and sustainable supply chain network design (SCND) is a vital component for companies to deal with the dynamic, uncertainty, and competitiveness of the market. Thus, academics and practitioners have contributed to the SCND providing a spectrum of applications, frameworks, methods, paradigms, decisions, and analysis, through the years. For example, the COVID-19 pandemic related SC studies [
29] and SC decision making supported by the Internet of Things and Big Data Analytics [
30].
For instance, Klibi et al. [
31] discussed the SCND under uncertainty and presented a critical review of the optimization models found in the literature. The authors analyzed the supply chain’s uncertainty, major disruptive events threatening, and risk exposures. It also discussed relevant strategic SCND evaluation criteria.
Farahani et al. [
8] considered the trends of markets and their effects on SCND. A general framework for modeling competitive SCND is provided, linking market types, SC network configuration, competition types (e.g., developing market, growth market, steady market, and mature market), and structural attributes.
Ivanov et al. [
32] synthesized research on supply chain design with disruption considerations in terms of the ripple effect in the supply chain. Features such as risks, affected areas, recovery, and affected performance were considered with its respecting bullwhip effect, i.e., operational, lost sales, short-term coordination to balance demand and supply, and current performance like daily stock-out/overage costs.
Govindan et al. [
33] provided a comprehensive review of studies in the fields of SCND and reverse logistics network design under uncertainty. Two main parts were investigated. The first part studied the planning decisions, network structure, paradigms, and aspects related to SCM. In the second part, existing optimization techniques were explored for dealing with uncertainty such as recourse-based stochastic programming, risk-averse stochastic programming, robust optimization, and fuzzy mathematical programming.
Moreno-Camacho et al. [
34] assessed sustainability in real-case applications of the supply chain considering strategic, tactical, and operational levels, in which at least two or three dimensions of sustainability are considered. The authors studied the forward, reverse, and closed-loop supply chains.
Esmizadeh and Mellat Parast [
35] examined the logistics network designs and evaluated their performance concerning cost, quality, delivery, flexibility, and resilience. Additionally, the authors provided an assessment of the strengths and weaknesses of each logistics design for different operations strategies.
Dolgui et al. [
36] considered a holistic framework on SC that includes digitalization, resilience, sustainability, and leagility (combination of lean and agile). In the paper, reconfigurability is considered as an integral perspective giving a new concept for complex value-adding systems in highly vulnerable environments, called the X-network.
Aldrighetti et al. [
37] presented a systematic literature review of quantitative models of SCND under disruption risks in industrial SCM and logistics. The authors analyzed the costs induced by the planning of proactive investments in robustness and through adaptation at the recovery stage. Besides, the integration of different SCM dimensions i.e., social and environmental impact, responsiveness, and risk-aversion, are discussed.
Finally, Tordecilla et al. [
38] provided a review of contributions on simulation–optimization methods for designing and assessing resilient supply chain networks under uncertainty. The authors considered the solving approaches, uncertain parameters, objective criteria, supply chain design, and application to real-world cases.
As can be seen, there is a lack of studies dedicated to analyzed contributions that combine sustainable and resilience criteria on the SCND. In this context, this paper aims to contribute to this subject, considering: levels in the SCND, levels of the decision-making, i.e., strategic, tactical, and operational, resilience and sustainability criteria, solving approach, objective criteria, and real-world applications.
3. Review Methodology
The present review is based on the Systematic Literature Review (SLR) approach [
39]. The SLR steps are (i) question formulation; (ii) location of studies; (iii) study selection and evaluation; (iv) analysis and synthesis; and (v) reporting and use of results.
For this review, a general question and some specific ones were formulated. The general question is ¿How resilience and sustainability criteria are considered in the supply chain network design? The specific questions were formulated as follows:
What elements of sustainability are considered?
What kinds of disruptions are taken into account?
What is the term of decisions?
How resilience and sustainability are linked?
Which links in the supply chain are considered?
How is the supply chain modeled?
The search for documents was carried out in the Scopus and Web of Science, which are the major citation databases [
40]. The search was conducted from the next combinations of terms:
The search was filtered by publication period (between 2010 and April 2021), by document type (research article and book chapter), and by language (English). The search terms were located in the title, abstract, and keywords. Two initial filters were carried out to select the documents: (i) the first filter considers just research articles, and (ii) the second filter eliminates papers that do not consider network design, sustainability, or resilience together and those that do not consider sustainability as a design criterion.
Figure 1 shows the detail of the paper selection for this study. A total of 54 papers were selected for the analysis.
To analyze the selected papers, a review taxonomy was built. All papers were classified according to three main components: Network design, Resilience, and Sustainability; details are explained later.
Figure 2 shows a graphical representation of the taxonomy.
In terms of network design, the scope of decisions was established as the number of links considered in the supply chain between suppliers (S), manufacturing centers (M), distribution centers (D), primary markets (R), collection centers (C), remanufacturing, recycling and recovering (Y), secondary and tertiary markets (U), and disposal centers (G).
Figure 3 shows the possible generic links in forward and reverse flows.
From the resilience perspective, the classification contemplates the strategic level for dealing with disruptions and uncertainties. The three categories are explained below:
Robustness: the ability of a supply chain to resist or avoid change [
41].
Agility/Flexibility: supply chain abilities to adjust its operations and tactics to respond to opportunities, threats, and environmental changes in turbulent markets [
42,
43] and to adapt to changes in demand, customer requirements, customer service levels, and delivery conditions [
44].
Risk assessment: is a stage of the supply chain risk management in which mitigation strategies are determined to be implemented when a disruption occurs [
45].
In the literature, flexibility and agility are considered as different concepts, i.e., flexibility is related to known situations at the operational level, and agility is considered as a wider concept at the business level [
17]. However, we consider both terms as a single category that encompasses the adaptability of the SC to disruptions and uncertainties.
Regarding sustainability, the classification includes the network design decisions criteria and the impact on sustainable development, i.e., economic, environmental, and social, in the SDGs (See
Figure 4). The numbers in
Figure 4 correspond to the official numbers of the SDG’s [
21]: (1) No poverty, (2) Zero hunger, (3) Good health and well-being, (4) Quality education, (5) Gender quality, (6) Clean water and sanitation, (7) Affordable and clean energy, (8) Decent work and economic growth, (9) Industry, innovation and infrastructure, (10) Reduced inequalities, (11) Sustainable cities and communities, (12) Responsible consumption and production, (13) Climate action, (14) Life bellow water, (15) Life on land, (16) Peace, justice and institutions, and (17) Partnership for the goals.
Finally, the objective criteria that each article addressed are considered. In many cases, the objective shows the relationship between sustainability and resilience. Additionally, the solution methods are registered to characterize the methodologies and tools that allow addressing the SRSCND. The term of decisions, whether strategic, tactical, or operational, is also examined.
4. Descriptive Analysis
The integration of resilience and sustainability in the supply chain network design is recent and its interest has grown over the years. Although this review was carried out in the last decade, the first article can be found in 2014.
Figure 5 shows the distribution of the number of publications through the years. As can be seen, the trend is growing, and almost 58% of the documents were published between 2020 and 2021.
Regarding the type of document, only one is a book chapter [
46], and the rest are research articles. The articles are distributed in 32 journals, 23 of them with one publication. A summary of the numbers of papers per journal is presented in
Figure 6. This figure includes only journals with two or more papers with the SRSCND.
The selected articles are written by 116 authors, 30 of them with two or more contributions, being Armin Jabbarzadeh, Behnam Fahimnia, and Mir Saman Pishvaee the ones with more articles on the SRSCND.
Figure 7 shows the authors with three or more contributions. The authors’ frequency contribution does not consider their position in the paper. In terms of the geographical location of the authors’ affiliation, the countries that appear the most are Iran (29 articles), Australia, the United States, and France (five articles each).
As mentioned above, the SCND is a complex decision-making process, so it is common to be approached from a mathematical modeling perspective. Consequently, 52 of the analyzed articles propose optimization models and the remaining is a conceptual framework [
27].
Regarding the academic visibility of the papers, the three most cited are: Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty [
47] with 148 citations according to Scopus, 124 citations according to Web of Science, and 222 citations according to Google Scholar; Marrying supply chain sustainability and resilience: A match made in heaven [
48] with 107 citations according to Scopus, 88 citations according to Web of Science, and 149 citations according to Google Scholar; and Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study [
49] with 64 citations according to Scopus, 53 citations according to Web of Science, and 96 citations according to Google Scholar.
6. Insights and Future Research Directions
This section presents insights on SRSCND problems, as well as some suggestions for future research. In the literature, many models perform sensitivity trade-off and “what if” analysis as strategies for evaluating decisions. In addition, most contributions consider contradictory objectives, as shown in
Table 9 and that confirms what is mentioned by Rajesh [
28], that produce efficient boundaries for decision-makers to choose between non-dominated solutions. Since this is the classical procedure of operations research, the analysis of its use will not be deepened; instead, specific sustainability and resilience criteria in SCND are addressed.
Both the insights and the research trends are classified according to the elements of the framework shown in
Figure 2.
6.1. Network Design
In
Section 5.1 it was explained which characteristics were taken as parameters for the network design; however, if the decisions include the determination of which facilities to open or put into operation (a generalized strategic decision in the models) and if these decisions are taken for different regions or geographic locations, then the result of the model is a network design with certain characteristics. This is why
Figure 2 shows bidirectional relationships between the components of the analysis. This section analyzes in which cases the introduction of sustainability and resilience criteria produced insights about these structures.
In Fazli-Khalaf et al. [
71] authors determined that a focus on the objective function of minimizing environmental impact (emissions) led to the centralization of designed network structures since the model tends to select for opening facilities with potential locations with high demands and low transportation costs and that minimize the emissions emanating from production and transportation. Mishra and Singh [
57] show that the result of disrupted demand due to a disaster is the modification of the network to have more spread facilities to supply partially or totally the demand after a disruption. In Fazli-Khalaf et al. [
81] there is a relationship between the decentralization of the reverse flow network and the reduction of CO
2 emissions during transport.
Future contributions could consider a deeper analysis of the network structure’s characteristics. This could facilitate higher-level decision-making that must go beyond purely economic aspects such as the location and size of industrial parks and free zones, command and control posts in emergency or disaster situations, the supply that affects natural reserve or protected areas, among others.
6.2. Sustainability
In the SRSCND, the sustainability dimension is evaluated and incorporated into the models through direct measurements. The economic perspective includes revenues and costs, the environmental dimension contemplates emissions, and as social criteria, the main objective is generally job creation. In terms of sustainability in the design of networks, the economic dimension has the property of containing the other two. This is achieved through specific environmental [
49,
52,
57,
58,
64,
73,
86,
90,
91,
95] and social costs [
59,
64]. In this sense, sustainability can be approached holistically without the need for direct impact measurements.
Future research could incorporate considerations on differentiated regional development, that is, having the possibility of privileging the use of logistics facilities in areas that are to be developed. This can also favor decision-making in public policies on infrastructure development.
Since freight transportation is responsible for up to 8% of greenhouse gas emissions (rises to 11% if warehouses and ports are included) [
99], it is a research challenge that supply network design includes considerations on fuel efficiency, the use of biofuels, and electric vehicles.
6.3. Resilience
The assessment of resilience in the SRSCND has several forms, including uncertainty and disruptions, indicators, or a combination of these. Such as in sustainability, there are also costs associated with resilience or disruptions in the models [
50,
60,
73,
86]. Given this heterogeneity of concepts, the emphasis on resilience is established using three categories: Robustness, Agility/Flexibility, and Risk Assessment, the last being the most used. In addition to using mathematical tools to model uncertainty, such as probability and fuzzy sets, indicators and other resilience measurement methods, such as Ecosystem Network Analysis (ENA) [
51], resilience pillars [
56], or LARG approach [
79], can be used.
There is a lack of contributions that address the three categories of resilience, i.e., robustness, agility/flexibility, and risk assessment in an integrated way. Thus, research opportunities that consider this integration could generate efficient designs for facing disruptions and responding to changes. In this context, optimization–simulation models can be useful methods for this purpose.
6.4. Term of Decisions
The decision term shows an important pattern, the prevalence of strategic decisions, some models with tactical decisions, and no consideration of operational decisions. The tactical decisions include inventory level policy [
47,
52,
73,
79,
95], waiting processes [
47], and transport mode selection [
58,
59,
60].
In this regard, there are research opportunities by incorporating other tactical and operational aspects such as pricing, product quality, perishability, vehicle routing, and the possibility of direct sales, vertical integration, and other commercial distribution strategies into decisions.
6.5. Real World Cases and Relationship with Sustainable Development Goals
Supply chains play a vital role in achieving sustainable development goals, as they are the link between producers and consumers in all aspects of the global economy. In the articles analyzed, in addition to dealing with sustainability aspects in their network designs, the proposed applications show alignment with some sustainable development objectives. In particular, applications were identified for SDGs 2, 3, 4, 7, 8, and 12.
Future research may address the problem of network design for local logistics systems such as urban logistics and last-mile distribution that can improve the quality of life, the satisfaction of basic needs, and the management of disruptions due to social and mobility problems. In this way, it would contribute to the fulfillment of SDGs number 9 Industry, innovation, and infrastructure and number 11 Sustainable cities and communities.
7. Conclusions
This paper has provided a systematic literature review on recent works about the supply chain network design with sustainability and resilience criteria. This study shows that the integration of sustainability and resilience in the SCND is gaining the interest of academics and practitioners due to its practical impact. Its applications cover products ranging from raw materials to high added value goods, and the scope of networks can be from regional to transnational influence. In terms of quantity, the largest number of developments have occurred in Middle Eastern countries, mainly Iran.
The scope of the majority of the networks analyzed considers only the forward flow, with a predominance of the demand, manufacturing, and distribution center links. In cases where the reverse flow was taken into account (as in closed-loop supply chains), the most commonly used links are transformation (value recovery) and collection centers.
Regarding the sustainability criteria, economic considerations prevail over the others dimensions. The most common objective in economic sustainability is the minimization of costs and profit maximization. In some cases, this sustainable dimension contains the evaluation of the environmental and social dimension through associated costs, such as carbon taxes and the cost of resilience (or non-resilience).
For environmental sustainability, the CO2 emissions are the most used indicators either in the objective function or in the constraints. Other indicators are the carbon footprint and energy consumption. The social component of sustainability is the least used in the SCND and mainly considers job creation. When all dimensions of sustainability are included as objectives, they are commonly contradictory, which is why a Pareto frontier is generated for the decision-maker to choose between the non-dominated solutions.
The resilience assessment was carried out through three categories that are not mutually exclusive: Robustness, Agility / Flexibility, and Risk Assessment. In addition, through the identification of the links subjected to disruption. Unlike sustainability, which has pre-established standards, resilience is much more varied in the way it is approached in the models; the forms range from scenario evaluation to the introduction as an indicator in the models.
On the other hand, the design of sustainable and resilient networks contributes to the SDGs of Zero hunger, Good health and well-being, Quality education, Affordable and clean energy, Decent work and economic growth, and Responsible consumption and production.
Future research may include detailed analysis of the structures resulting from the SCs that help to make high-level decisions such as public policy as well as the incorporation of operative level aspects to the SRSCND and the design of local networks with resilience and sustainability criteria.