How firm level responsiveness influences supply chain network resilience

Supply chains (SC) operate in an increasingly volatile and unpredictable environment due to pervasive challenges such as economic uncertainty (Fan et al., 2022), geopolitical conflicts (Ngoc et al., 2022), human error (Wieland et al., 2023), and natural disasters (Sodhi and Tang, 2014). This complex environment has led to frequent SC disruptions and an awareness of the challenges created when flows are impeded (Galeano and McSwigan, 2022). To date, SC network research has overemphasized firm-level vulnerabilities (Ivanov, 2020; Li et al., 2021) and de-emphasized the adjustments made to address network-level disruptions (Bae et al., 2023). In recent years, firms have expanded their focus on resilience beyond internal operations to also encompass their SC network (Alicke et al., 2024). The shift toward addressing SC network resilience alongside firm-level resilience underscores the need for additional research. We contend that it is vital to understand how individual firms' resilience-creating activities fortify the SC against disruptions.

SCs are complex and changeable systems that benefit from firm-level adjustment capabilities, which enhance SC network resilience (Novak et al., 2021). Firms capable of adjusting to disruptions and sustaining their operations manage SC complexity more effectively (Richey et al., 2022). Yet, understanding SC resilience requires investigating firm characteristics across the network (Wieland and Durach, 2021). Specifically, we explore the relational nature of SC resilience, where resilience develops through the collaborative responses of network partners (Ambulkar et al., 2015). This evolution of SC resilience provides an opportunity to integrate SC responsiveness, resilience, and network literature by exploring how firms contribute to SC network resilience and responsiveness.

The Responsiveness View of logistics and SC management argues that firms adjust both operational and strategic capabilities in response to environmental and organizational complexity by utilizing adaptable, flexible, agile, and improvisational capabilities (Richey et al., 2022). Such individual firm responsiveness is a precursor to SC resilience as those strategies spread across the network (Morgan et al., 2023). SC network theory supports the Responsiveness View by clarifying how the system's structures and characteristics shape resilience (Wieland and Durach, 2021). Firm level responsiveness capabilities thus enable SCs to persist, change, adapt, and transform in response to a dynamic environment. This phenomenon motivates the following research question (RQ):

To answer this, we conducted an extensive literature review of SC network and SC resilience articles in leading peer-reviewed SC journals to develop a conceptual model and propositions that outline how firms and SC networks influence resilience across the network. One of the main contentions is that resilience across the SC network is a product of information propagating throughout the network as individual firms adjust (Munir et al., 2022). The relationships between firms across the SC network facilitate the dissemination of knowledge about successful and unsuccessful adjustments. Through adjustments in response to and preparation for disruptions, the system becomes more resilient as best practices spread across SC network partners and disseminate to individual firms.

This study extends the Responsiveness View by identifying how firms' responsiveness activities (i.e., adjustment capabilities) instill resilience in their SCs, enabling them to address changes that potentially disrupt operations. This responsiveness-resilience relationship highlights how resilience goes beyond “bouncing back” and instead is shaped by an evolutionary process driven by firms' adjustments to their SC processes and structures. The study also clarifies how firms' relationships within and across SC networks shape how they develop and influence resilience across the network. Consequently, firms should balance perceptions of strategic and operational complexity with the resilience capabilities their network possesses.

When disruptions occur, the impact is described as a contagion (McFarland et al., 2008) or ripple effect (Dolgui and Ivanov, 2021) which spreads across a SC network. The concept of SC resilience is a product of explaining how inventory movement and service flow is maintained across the SC network despite increasing complexity (Sheffi and Rice, 2005) through both proactive and reactive strategies (Ponomarov and Holcomb, 2009; Tan et al., 2019). This conceptualization has evolved over time. We draw from Wieland and Durach (2021)'s more recent definition of SC resilience:

Persistence refers to the ability to maintain flow by absorbing and withstanding the shock created by a disruption or, if disrupted, having the ability to quickly restore flow and return conditions to a pre-disruption state (Wieland et al., 2023). Adapt describes firms' adjustments and alterations to SC structure to restore flow and enable the transition to an improved state (Richey et al., 2022). Transformation refers to SC structures, processes, and relations as the SC ideally evolves into an improved state post-disruption (Wieland et al., 2023; Wieland and Durach, 2021).

Responsiveness expands these concepts to describe a firm's ability to act quickly based on knowledge generated in the face of change. Responsiveness is fundamental in managing both anticipated and unforeseen disruptions. When SCs are responsive, they are better positioned to adjust to complexity early, adapt operations in real time, and preserve swift and even flow — all of which directly contribute to resilience. In essence, responsiveness is an antecedent to resilience, enabling firms to recover and maintain performance in volatile environments (Nikookar and Yanadori, 2022b; Morgan et al., 2023).

As firms endure and recover from disruptions, they engage in both prospective and reflective learning that refines their ability to respond to future events (Fletcher et al., 2021). The organizational memory formed through resilience-building experiences becomes a foundation for more effective sensing, faster adjustments, and improved coordination across the network. Over time, learning informs responsiveness, creating an evolutionary cycle. Thus, responsiveness and resilience continuously inform and amplify one another in a dynamic loop. Improving resilience demands continuous strategic and operational adjustments where the firm and SC network partners work toward being responsive. SC resilience is thus an outcome and an antecedent within the Responsiveness View due to the cyclical nature of SC management reality. Richey et al. (2022) clarify that:

The Responsiveness View asserts that structure, policy, and process-based adjustments can increase adaptability, flexibility, and agility capabilities not only within individual firms but also across the SC network to achieve resilience (Morgan et al., 2023). Preparing for and reacting to change is inherent in this view (Goldsby et al., 2024). It requires firm interconnectivity that extends beyond immediate SC partners to include all organizations the focal firm depends on to access scarce resources (Wiedmer and Griffis, 2021). Relationships are thus an important aspect of adjustments to improve resilience as they facilitate collaboration, communication, and information sharing among SC members (Munir et al., 2022).

This is where SC network theory becomes a critical component of SC resilience. The central tenets of SC network theory are that SCs are complex, adjustable networks (Choi et al., 2001) of connections that collectively impact overall SC performance (Wieland and Durach, 2021). Incorporating SC network theory with responsiveness and resilience clarifies how relationships allow organizations to influence each other's capabilities, enhancing their ability to address disruption risk (Ambulkar et al., 2015). The individual capabilities (Zouari et al., 2020) and collective adaptation (Feizabadi et al., 2021) in response to environmental vulnerabilities are termed SC network resilience (Li et al., 2021; Münch and Hartmann, 2022). SC network resilience involves examining the structures of SC networks to determine how SCs remain responsive (Wiedmer and Griffis, 2021). Therefore, we review SC network resilience literature to understand how an organization's SC responsiveness activities influence SC network resilience.

We address our research question through a systematic literature review that focuses on SC network resilience guided by the Responsiveness View. Our review gathers input from prior literature through consistent and repeatable steps (Durach et al., 2017) that infuse transparency to strengthen validity (Ketchen and Craighead, 2023). To accomplish this, we followed the eight-phase process employed by Cole et al. (2025) that expands upon prior literature review methods to provide a comprehensive search and review process. Figure 1 provides an overview of these literature review steps adapted from Cole et al. (2025). Where relevant, the number of articles in the literature review is listed in brackets. The first number is the articles returned in the initial search. The second number is from the backward and forward search discussed later.

In Phase 1, formulation of the problem, we clarify the purpose of the study by defining our research question: How do firms' responsiveness activities build resilience across a SC network? For Phase 2, we developed a research protocol. The keywords “Supply Chain Resilience,” “Supply Chain Network,” and “Risk” were used in conjunction to identify relevant literature ^[1], as these keywords covered the concepts of our research question. A second search was done that replaced “Supply Chain Network” with “Logistics Network” given the interchangeable nature of those terms. The terms were searched in tandem to ensure the literature includes a discussion on SC resilience with a SC network orientation, as past work on SC resilience has often focused on individual firms, thus lacking nuance around the multi-tier SC network context (Ambulkar et al., 2015). We did not use less restrictive keywords (i.e., Resilience and Network) because those words are commonly used in unrelated literature. Less restrictive searches generated thousands of irrelevant results, such as resilience contextualized as a human mental state, a computer network, or an electrical grid. Our more restrictive keywords restricted the returned literature to papers that at least covered topics of interest but still yielded over six hundred studies during the initial search. Using these more restrictive keywords is in line with Cole et al. (2025), who similarly did not use individual terms because they were commonly found in unrelated literature.

Journal list selection began with those used by Cole et al. (2025). Three journals from that list were removed as they were specifically related to sustainability, the focus of Cole et al. (2025), but do not fit within the scope of this review. The journal list from Cole et al. (2025) was augmented with four additional journals. First, the Journal of Business Logistics was added to align with best practices of including the entire SCM List of journals (Ketchen and Craighead, 2023). Additionally, given the central role of logistics management in addressing disruptions, we further add three leading logistics journals (indicated with an asterisk in Table 1) which have been included in other recent SC-focused systematic literature reviews (Ali and Gölgeci, 2019). The list of journals and number of articles found and kept from each source after both the initial search and backward/forward search, discussed below, is found in Table 1. To avoid an arbitrary timeframe since there is no logical cut-off as to the earliest date to search (Ketchen and Craighead, 2023), the literature review covers digitally available articles from the listed journals from their inception to July 2023, when the search was performed. Figure 2 provides the count of articles retained after full-text reading, column (c) in Table 1, by year.

In Phase 3, the actual search was performed using Google Scholar following the procedure in Cole et al. (2025). After removing duplicates, 616 articles were returned in the initial search. To align with best practices which require two sources be searched (Carter et al., 2024), Scopus was used to perform an identical search. No new articles were returned in this second search. Phase 4, screening for inclusion, was accomplished with the same two-step approach as Cole et al. (2025). First, each article was searched for inclusion of the keywords: “network”, “risk”, and “resilience”. If the keywords only appeared outside the body of the text, such as the reference section, the article was excluded. Second, abstracts were reviewed for studies emphasizing SC resilience in an SC network or multi-firm context. Papers that did not discuss these topics were excluded. Following these steps, 125 articles remained.

Phase 5 was to assess the relevance of each article. The full text of all remaining articles was fully read to assess study fit. To be comprehensive, articles were retained if they offered insights into resilience within SC networks, even if only a smaller portion of the article provided such insight. Thirteen articles that did not provide insights into the topic were removed. An additional step within the fifth phase is to perform a backward and forward search on “landmark” papers within the topic. Following the guidance of Cole et al. (2025), “landmark” papers were defined as the top 10% of papers, rounding up, in terms of citations per year at the time of the search. This would equate to 12 papers based on the 112 articles deemed relevant. Since this number was lower than the 14 papers used for the backward and forward search by Cole et al. (2025), we chose to do the backward and forward search for the 14 papers ^[2]. See queries with the highest number of citations per year at the time of the search to ensure adherence and comprehensiveness.

The backward and forward search entailed creating a list of all the papers cited in those fourteen papers, as well as all papers that cited them per Google Scholar. After duplicate papers, papers in journals outside our search list, and papers reviewed from the original search were removed, the backward and forward search yielded an additional 496 papers. This brought us to a total of 1,112 articles screened for this literature review, as shown in column (a) of Table 1. For these 496 articles, we performed the same two-step process of searching for keywords in the article's main text and reading the abstract. 20 articles were retained after this stage, leading to a total of 145 articles that were fully read. The low ratio of kept articles in the backward and forward search can be attributed to this being a list of articles not returned in our initial search, meaning the articles were often not related to resilience or SC management. After reading the full text of these 20 articles, 12 were deemed relevant and retained, leading to a final list of 124 articles for this literature review, as noted in column (c) of Table 1.

Phase 6 of this process is data extraction. During the extraction phase, we collected data from the articles through an iterative process. This was done with thematic analysis, which has been employed within SC research for theory development of under-researched and emerging topics (Arunachalam et al., 2018; Fawcett et al., 2014). Braun and Clarke (2006) stated that “thematic analysis is a method for identifying, analyzing, and reporting patterns or themes in data” (p. 79). Methodical rigor and validity of this process involves the following steps: A) data familiarization, B) developing codes that evolve and change as the research team immerses in the literature, C) identifying themes, D) refining the themes, E) tracking the process, and F) generating a report (Byrne, 2021). Steps E and F will appear in Phases 7 and 8 of the literature review methods, respectively.

Steps A and B of the thematic analysis involve the research team familiarizing itself with the literature and coding sections of the text. The team applied a reflexive process in which codes were initially identified and evolved as the literature was iteratively reviewed (Braun et al., 2013). Wieland and Durach (2021)'s definition of SC resilience, the Responsiveness View, and SC network theory provided the framework for categorizing the codes into the initial codes of structure, relation, and process. Additionally, each of these codes may occur at either the firm or SC network level. The Durach et al. (2017) approach led to a multi-stage, iterative discussion to solidify initial codes. A summary of the initial codes can be found in Table 2, with extended definitions in Section OS1 of the Online Supplement.

In step C, the research team analyzed the initial codes by meaning. The process consisted of re-reading the applicable literature sections to validate the interpretation of the data. The analysis identified 16 initial themes that help SC networks and organizations manage and recover from disruptions. In step D, the themes were reviewed and analyzed to generate overarching themes. This analysis process further grouped the initial codes to capture the collective meaning from the literature. See Table 3. Drawing on the framework provided by Durach et al. (2017), the research team identified six overarching themes. The overarching themes solidified the importance of SC networks in the adaptation to disruptions and the importance of collective adjustments to restore flow across the network.

Phase 7, synthesis of the data, was covered in this methods section of the paper to generate an organizing framework. Also occurring during this phase is step E of the thematic analysis, where the data analysis process is tracked and recorded. Phase 8, report the findings, and step F of the thematic analysis, generating the report, appears in the synthesis section.

Establishing interrater agreement of the themes involved multiple rounds of classification and comparison between the author team. In line with best practices, at least two reviewers were required for reviewing each article (Carter et al., 2024). First, two authors read each article fully, classifying it as firm or network and either structure, process, or relation. Of the 124 articles, there was an identical assessment for 79 (64%) articles during this stage. Second, a third author assessed all articles where there was any disagreement. If two of the three authors rated an article identically, that was agreed to as the consensus. Of the 45 articles reviewed during this phase, there was consensus on 44. Third, for the one article without a consensus, Baryannis et al. (2019a), the three authors discussed the article to form a consensus. Due to the repetition of concepts and the number of articles to summarize, not every paper deemed relevant is cited in the literature synthesis. However, a complete listing of the articles with appraisals and a summary of relevant concepts appears in Section OS2 of the Online Supplement.

Based on the findings of the literature review, described in detail in the next two sections, Figure 3 presents a novel conceptual framework that lists the significant concepts drawn from the literature and illustrates how firms' responsiveness activities influence resilience in SC networks. The framework shows how firms' influence permeates throughout SC networks and how the network shapes and influences the types of activities firms adopt to improve or enhance their responsiveness. Responsiveness acts as a crucial building block for resilience, which encompasses a SC's capacity to recover from disruptions (Richey et al., 2022). This relationship is depicted as a feedback loop, offering insights into how a collective of firms' responsiveness activities create the ability for SC networks to persist, adapt, and transform. Finally, the figure lists the three propositions proposed in the following sections as untested concepts, highlighting the future direction for SC network resilience research.

Risk management processes facilitate assessment and inform the development of mitigation capabilities (Schmitt and Singh, 2012). These processes result in the creation of continuity and contingency plans that guide preparedness and recoverability (Adobor and McMullen, 2018; Zhao et al., 2023). These encompass proactive measures such as establishing alternate facilities (Brusset and Teller, 2017), holding safety stock (Tan et al., 2019), and maintaining alternate suppliers (Hosseini et al., 2022a). The plans also include procedures for reactive disruption recovery (Schmitt and Singh, 2012) and enabling coordinated operational adjustments or reconfiguration of resources to recover flow (Zhao et al., 2023).

Flow is improved by agility, which is a process-oriented capability that utilizes slack to scale resources, allowing shifts in operational requirements (Goldsby et al., 2006). Firms' development of agile processes stems from an understanding that quick adjustments enable reaction to change (Richey et al., 2022). Firms also develop processes to evaluate SC partners (Lee, 2017), monitor partners' capabilities to address disruption risk, and sustain SC flow (Bag et al., 2023) to ensure resiliency (Kähkönen et al., 2023).

Further, firms develop knowledge management processes to make sense of and learn from experiences (Fletcher et al., 2013). Knowledge motivates changes to improve firm fitness and enhances responsiveness (Adobor and McMullen, 2018), enabling disruption mitigation capabilities (Nikookar and Yanadori, 2022a). Similarly, firms leverage data management processes to create disruption-detecting capabilities (Kähkönen et al., 2023; Zouari et al., 2020). This improves the visibility of trends, such as changes in demand or supply which inform adjustments to inventory levels (Hosseini et al., 2022a; Zouari et al., 2020). Additionally, firms use flexible work policies and a multiskilled workforce to improve labor capacity (Tukamuhabwa et al., 2015). Further, inventory buffering (Schmitt and Singh, 2012) increases the ability to respond to possible disruptions (Lee, 2017). Other process changes include modifying transportation modes (Nikookar and Yanadori, 2022a; Ivanov, 2020), and altering products and service offerings (Ivanov and Dolgui, 2020).

The Responsiveness View puts forth adaptability of SC structures as one of its major dimensions. SC structures are designed to support firms' exchanges with suppliers and customers (Hearnshaw and Wilson, 2013). Managers pursue different structural designs to address vulnerabilities (Hearnshaw and Wilson, 2013; Zhao et al., 2019). One such vulnerability is supplier dependency. Firms address this through supplier selection, sourcing volumes (Lee, 2017), and multi-sourcing strategies to mitigate disruptions (Nikookar and Yanadori, 2022a).

Firms also adapt SC structures through facility expansion and infrastructure improvements (Ghanei et al., 2023). Increasing warehousing space (Scala and Lindsay, 2021) and expanding facility locations (Brusset and Teller, 2017) improve throughput and provide network flexibility. Additionally, facility fortification (i.e., making the facility more durable) (Fattahi et al., 2017; Ghanei et al., 2023) and backup sites (Tan et al., 2019) enable preparedness. These provide extra capacity (Schmitt and Singh, 2012) and support continuity (Ponomarov and Holcomb, 2009).

However, structural adaptations depend on perceiving potential risks and being able to act on them. Firms may lack foresight (Spieske et al., 2022), knowledge of how to address disruption risk (Scholten et al., 2014), or sufficient resources to develop robust structures (Chopra et al., 2021). Firms may instead design their SC structure to focus on swift adjustments (Aldrighetti et al., 2021) and reconfigurability (Childerhouse et al., 2020) to speed recovery instead of resisting disruptions. Such adjustment capabilities are made possible through alternate routing strategies (Kähkönen et al., 2023), near or local sourcing (Spieske et al., 2022), and employing multi-channel distribution (Chopra et al., 2021). These adaptations and eventual transformations (Wieland et al., 2023) address disruptions and transition to a post-disruption state (Tan et al., 2019; Tukamuhabwa et al., 2015), but require balancing in-house and outsourced production (Nikookar and Yanadori, 2022a). If the systems fail to persist when confronted with further change, re-adaptation is required (Richey et al., 2011).

Relationships between firms facilitate transparency (Münch and Hartmann, 2022), trust, cooperation, communication (Chowdhury et al., 2023), and align goals (Spieske et al., 2022). As relationships progress, they culminate in mutually beneficial collaboration (Kähkönen et al., 2023) and knowledge sharing (Zhao et al., 2023) that reduces disruption risk. To foster these mutually beneficial relationships, firms develop digital information-sharing capabilities (Zouari et al., 2020) and invest in information-sharing technologies (Kähkönen et al., 2023). Doing so enables transparency across SC members (Zhao et al., 2023), fosters collaboration, and motivates managers to build social capital by forming social ties across firm boundaries (Ponomarov and Holcomb, 2009). Relational ties foster commitment among stakeholders (Bag et al., 2023), provide access to leadership (Shin and Park, 2021), promote collaboration through institutions such as trade associations (Azadegan and Dooley, 2021), and offer pathways to seek advice.

Establishing contracts is another way that firms foster and govern relations. Contracts improve transparency, influencing the willingness of managers to share information (Yoon et al., 2020). Contracts also help establish risk management expectations, delineating the types of procedures to be followed to address disruption (Wu et al., 2023). Establishing these expectations helps to improve trust among SC partners, improving coordination and collaboration when disruption occurs (Datta, 2017). Additionally, social network expansion improves flexibility as more resources are made accessible through various relationships (Nikookar and Yanadori, 2022a). These relationships also provide firms with a connection to the network through which they can influence the responsiveness capabilities that other firms implement.

From a SC network perspective, process normalization (i.e., firms adopting similar disruption mitigating practices) and structure variety (i.e., firms establishing and using alternative SC pathways) across SC network stakeholders work in tandem to infuse resilience in SC networks. This dichotomy of normalization and variety originates from the network's reliance on best practice standardization across firms and non-conforming structural diversity needed to find alternatives that can be implemented. While contradictory, the literature reveals that network resilience arises from firms leveraging relationships with other firms that have complementary responsiveness activities, balancing standard practices with structural variety to mitigate disruption risk.

Firms act independently to address their SC risk and protect their own interests (Ponomarov and Holcomb, 2009; Tan et al., 2019). Yet, they eventually face similar disruption risks (Lee, 2017) and their response depends on other organizations (Feizabadi et al., 2021). Disruption is thus mitigated across the SC network through an aggregation of adjustments across firms. These adjustments are facilitated through communication with other SC network members with whom the firm has a relationship (Hosseini et al., 2022a). Through these interactions, firms learn from one another about risk-reducing capabilities they can adopt. This facilitates the dissemination of disruption mitigation processes (Lee, 2017; Zouari et al., 2020). Thus, responsiveness is sustained by firms deliberately sourcing from organizations with agile process capabilities (Küffner et al., 2022; Scala and Lindsay, 2021).

Shared agile processes facilitate the development of risk-reducing and reactive capabilities (Fattahi et al., 2017). These capabilities are essential for informing strategies related to disruption response and resilience recovery (Schmitt and Singh, 2012). Agile processes depend on firms fostering a culture of risk management (Küffner et al., 2022; Spieske et al., 2022) to address disruption risk (Chen et al., 2022). Thus, firms in their respective SC networks are able to align responsiveness capabilities that address vulnerabilities (Lohmer et al., 2020) to improve resilience. Therefore, we propose:

When multiple firms across a network develop resilience by strategically structuring their supply base, it has a stabilizing effect by ensuring that each firm can effectively respond to disruptions (Alikhani et al., 2021). This comes from individual firms across the SC network choosing to connect with lower-risk suppliers (Li and Zobel, 2020), maintain backup suppliers (Chen et al., 2022), establish ties with geographically dispersed suppliers (Childerhouse et al., 2020), and multi-source (Scala and Lindsay, 2021). Resilience across the SC network is also strengthened through structurally adaptive diversity, such as a variety of shipping routes (Wieland et al., 2023) and distribution schemes (Chopra et al., 2021). This diversity causes SC networks to grow in complexity with increasing touchpoints for firms to manage (Dixit et al., 2020) but also helps improve the options they have available to address disruptions.

Stability across SC networks is further improved through structures that enable interoperability through technologies that facilitate information sharing (Dev et al., 2021) and designing structures that enable the throughput of resources (Chopra et al., 2021). At the network level, interoperable structures improve connectivity across SCs, improve efficiency due to better flow, and facilitate communication (Dixit et al., 2020). Dispersion and disruption-persisting facilities also strengthen the structural stability of the SC network. Firms enable these capabilities by constructing facilities in less risk-prone areas, maintaining a geographically dispersed supply base (Fattahi et al., 2020), fortifying facilities, and establishing protection systems such as fire suppression systems (Aldrighetti et al., 2021; Childerhouse et al., 2020). Partner dispersion schemes also increase distance across a SC network, potentially making the system more robust against localized threats (Aldrighetti et al., 2021).

Structural variety is another avenue to improve adaptability across SC networks. Alternate supply sources (Yue et al., 2023) and distribution channels (Spieske et al., 2022) across the network enable disruption reactiveness (Gholami-Zanjani et al., 2021). This permits firms to meet supply requirements quickly (Dixit et al., 2020), modify distribution channels (Spieske et al., 2022), and access additional supplier capacity (Alikhani et al., 2021). Consequently, structural variety adds contingency capacity to restore flow when primary channels cannot meet requirements. Thus, structural variety enables SC network-responsive capabilities. Therefore, we propose:

Just as relationships at the firm level facilitate the dissemination of practices across the SC network, those practices flow back to the individual firms. Collaboration (Kamalahmadi and Parast, 2016) and resource dependency motivate firms to work together (Li and Zobel, 2020; Scholten and Schilder, 2015), connecting the network back to individual firms. This can occur horizontally between firms that provide similar services or products. This provides visibility of peer organizations, benchmarking opportunities, and peer-to-peer learning (Durach et al., 2020; Massari and Giannoccaro, 2021). It can also occur vertically, in which firms connect with others upstream and downstream across the SC. Vertical relationships create a bridge among suppliers, producers, and distributors (Ghanei et al., 2023). This enables disruption detection (Durach et al., 2020) and transparency (Bag et al., 2023) while harnessing complementarities among firms (Münch and Hartmann, 2022). These connections to improve SC resilience then facilitate the diffusion of best practices across firms (Massari and Giannoccaro, 2021).

SC relationships also inform decisions on quick adjustments (Aldrighetti et al., 2021) or balancing inventory levels (Ghanei et al., 2023) that improve response time (Kamalahmadi and Parast, 2016). This enables anticipatory (Durach et al., 2020) and reactive (Durach et al., 2020; Ghanei et al., 2023) capabilities that can help with disruption recovery. Finally, relationships uncover complementarities across the SC network through interfirm collaboration. Collaboration is based on interfirm trust (Giannoccaro and Iftikhar, 2022), dependency (Durach et al., 2020), cooperation (Durach et al., 2020; Ghanei et al., 2023), common ground (Ghanei et al., 2023; Scholten and Schilder, 2015), relationship longevity (Li et al., 2020), and shared risk (Kamalahmadi and Parast, 2016). These attributes bring firms together to address challenges across boundaries and build on one another's strengths and abilities (Adobor and McMullen, 2018). Therefore, we propose:

The time is ripe for new research on the interplay between responsiveness and resiliency across SC networks. The three propositions offered by this research provide avenues for scholars to advance research on the responsiveness-resilience link in SC network settings. Opportunities in this space are not only abundant but increasingly vital as internal and external uncertainties intertwine to increase complexity. For example, vulnerabilities emerge at different levels of the SC network, which may produce different approaches to utilizing responsiveness adjustment mechanisms that could produce variations in resilience outcomes (Carnovale et al., 2025). Network theory may offer a foundation for understanding this phenomenon, as partners in the network may interpret uncertainties differently and apply different adjustment mechanisms. The absence of coordination among partners (consciously or not) may lead to ineffective resilience strategies. This layered exposure provides rich ground for empirical and theoretical development.

An interesting aspect of interorganizational learning is the idea of knowledge transfer. While learning helps firms develop and share insights to create strategies, knowledge transfer may also unintentionally erode competitive advantages as best practices are transferred to competing firms (Zhu et al., 2018). This ultimately affects responsiveness capabilities and, in turn, worsens resilience. Organizational learning theory could be applicable in this area. Wieland and Wallenburg (2013)'s findings from a relational view lens suggest that firm integration does not influence resilience. However, the addition and application of responsiveness capabilities that address vulnerabilities may provide more insight (Guntuka et al., 2024a). Moreover, resource dependency theory could also help to explain the nuance associated with relationships in the SC network and how the firms utilize their interdependent resources collectively. Table 4 offers research questions to help scholars push important conversations forward.

Research on responsiveness-resilience interplay could also be advanced through various contexts and methodological approaches. The rise of emerging technologies is an important area of examination (Rainer et al., 2025). Today, more than ever, we need research that uncovers how firms sense, interpret, and act on network information, including the use of technologies in real-time, particularly during disruptions (Jiang et al., 2025). Tools like machine learning and predictive AI have reshaped how firms build and scale responsiveness capabilities. Generative AI may bring even more expansive knowledge-based support to SC networks (Modgil et al., 2022; Ivanov et al., 2021). AI tools can align with the dimensions of the Responsiveness View—adaptability, flexibility, agility, and improvisation—supporting firm-level best practices that impact all levels of the network (Condé and Münch, 2025). We also need a deeper inquiry into how cognitive and behavioral boundaries influence technologically augmented decision-making and what that means for downstream resilience. Equally important is the human side of decision-making. AI can offer faster, data-driven insights, but it does not eliminate the role of managerial judgment (Dai et al., 2025). In fact, human biases in interpreting AI-generated outputs may distort and disrupt network-level outcomes. Surveys and experiments have the potential to unlock causality related to this. However, a Delphi study could prove highly valuable in providing a deeper understanding based on experts' perspectives on the critical role of managerial decision-making and the tools (e.g., responsiveness mechanisms) used to achieve resilience under SC uncertainties and disruptions (internal and external influences).

Government policy also deserves more attention as a moderating force. Regulatory mechanisms like tariffs or trade restrictions can either enable or restrict responsiveness. We do not fully understand how these economic levers impact adaptive actions or alter the resilience landscape. In global SCs, the complexity introduced by inconsistent international regulations adds another layer. Studying regulatory heterogeneity as a dynamic moderator could open new pathways for theory and practice. A longitudinal study (i.e., quasi-experiment) could prove useful in understanding the effect these regulatory mechanisms have on SCs and the effectiveness of various kinds of responsiveness measures on assuring SC resilience.

Additionally, transparency and knowledge are essential to responsiveness (Morgan et al., 2023). The complexity of internal and external uncertainties highlights the importance of data visibility and the need for transparency across organizational levels. Clear communication upstream and downstream facilitates learning loops that enable coordinated awareness and timely reactions. We urgently need research exploring how network transparency supports feedback mechanisms and enhances network-level adaptability, especially in light of advancing technology. Research in this area could be advanced through case study research augmented by expert interviews and simulation targeting assessment of the interrelationships across SC partner levels. The idea would be to observe and evaluate how interactions within these areas shape and influence the transformation of SC resilience capability that originates at the firm level, transmits to the network, and finally disperses back to the firm level.

The framework outlined throughout this research demonstrates how firm-level responsiveness efforts influence SC network resilience. Rather than assuming that SCs revert to a pre-disruption state, the approach aligns with an iterative view of resilience that is enabled by responsiveness' adjustment capabilities (Richey et al., 2022). Each incremental improvement reinforces a firm's ability to adjust to its environment, which can then spread across the network to other firms through the relationships between them (Guntuka et al., 2024b). This adds network nuance to the conceptualizations of SC resilience and responsiveness where the network itself influences how individual firms detect threats, mobilize resources, and coordinate responses. This interplay between the firm and the network offers promising avenues for research into how the dimensions of responsiveness produce varied outcomes (Carnovale et al., 2025). Managers can look beyond simply “bouncing back” and instead view resilience as an ongoing evolution, driven by knowledge-sharing platforms, small-scale policy adjustment, and trust-building measures. For example, our review of the literature identifies a more definitive link between responsiveness and resilience within the network, deepening our understanding of how the complexity of resilience facilitates SCs transitioning from bouncing back to adapting and transforming. This link adds to a growing body of literature that highlights a potential curvilinear relationship between complexity and the temporal dimensions of resilience (i.e., persistence and transformation), given the growing need for interorganizational interaction (Guntuka et al., 2024b; Carnovale et al., 2025). Finally, responsiveness reflects both network and firm capabilities, which can serve as adjustment mechanisms in the face of disruptions.

Establishing this link between responsiveness and resilience also contributes to the growing scholarship on transilience—a concept that explores how firms address major disruptions by partially restoring some SC processes and structures while transforming others to adapt to rapid and profound environmental changes (Gatenholm and Halldorsson, 2023; Craighead et al., 2020). Research in this area remains nascent, with scholars calling for further exploration (Craighead et al., 2020; Saisridhar et al., 2024). Our framework advances this discussion by clarifying how the evolution of responsiveness activities and knowledge sharing among firms facilitates the type of transformation described.

Further, our framework advances mainstream resilience scholarship (Ponomarov and Holcomb, 2009; Wieland and Durach, 2021) by clarifying how different capabilities can be leveraged to emphasize policy, process, or adaptive adjustments to improve persistence, adaptation, and transformation. The responsiveness-resilience relationship also implies that resilience is not only an outcome of effective response to disruptions, but resilience is also embedded in the considerations for responsiveness capabilities (Masorgo et al., 2024). For example, utilizing flexibility through policy adjustments such as inventory pooling or managing contractual configurations within the network are tools that can be foundations to develop risk mitigation strategies that address disruption uncertainties.

Managers may further leverage the findings by focusing on how firm responsiveness capabilities and external network relationships combine to bolster SC resilience. For instance, managers may leverage local risk management planning and networked knowledge-sharing processes that guide contingency planning and also enhance overall responsiveness (Friday et al., 2024). Fostering strong interfirm relationships through information sharing, contractual agreements, and communication enables coordinated responses and collaborative learning across the network (Budler et al., 2023). Adopting multi-sourcing network strategies and investing in infrastructure improvements may also mitigate vulnerabilities present in single-sourcing approaches (Carnovale et al., 2025). Overall, our insights empower managers to think strategically about their organizations' positions within networks, their implications, and the roles they play in designing systems that withstand disruptions while responding to evolving challenges and opportunities.

Finally, there are limitations to this study. First, it is limited to what is published in academic articles. There is still much to be explored and understood about responsiveness and the influence it has on resilience within SC networks. Thus, this study offers many opportunities for researchers to continue advancing knowledge on this important topic. Additionally, academic literature lags industry practices, impairing the ability to capture the most recent industry activities. Advances in technology and changes to the latest SC processes outpace the rate at which scholars are able to assess and document these changes. Therefore, continued research is needed to address the gaps these changes create. Finally, academic literature tends to predominantly focus on larger corporations operating in more economically developed countries. The strategies put forth in the literature may not be applicable to smaller organizations in developing regions. Studies that target smaller organizations and less developed regions of the world can further enhance our understanding of responsiveness and resilience relationships, as these may represent untapped data sources further capturing SC network complexities.

The supplementary material for this article can be found online.