Linking Sustainable Business Models to Socio-Ecological Resilience Through Cross-Sector Partnerships: A Complex Adaptive Systems View

Socio-Ecological Resilience

The concept of resilience has been increasingly used to understand the dynamics of socio-ecological systems (Folke, 2006). At a systemic level, resilience has been defined as the “capacity [. . .] to proactively adapt to and recover from disturbances that are perceived within the system to fall outside the range of normal and expected disturbance” (Boin et al., 2010, p. 9). According to established interpretations stemming from the fields of ecology and social sciences (Carpenter et al., 2001; Folke, 2006; Walker et al., 2004), resilience can be interpreted through two dimensions. First, the amount of disturbance a system can absorb while remaining within the same balancing state, and, second, the degree to which the system is capable of self-organization, learning, and adaptation.

The field of ecology has focused mostly on the first dimension of socio-ecological resilience: the capacity to absorb disturbances. From an ecology perspective, this “absorbing” or “buffering” capacity of the system can be measured in terms of the persistence of the relationships within a system despite remarkable fluctuations of some of its agents (Holling, 1973). For example, the system of a forest can be considered resilient to the extent that it can absorb fluctuations in heat or precipitation, in the short run, while eventually bouncing back to the initial state, in the longer run. The second dimension of socio-ecological resilience was established in the early 2000s when social scientists engaged in multidisciplinary work with ecologists in developing the so-called adaptive ecosystem management perspective (Berkes et al., 2003; Gunderson & Holling, 2002). From this social perspective, resilience can be observed as a capacity to adapt to disturbances (Norberg & Cumming, 2006; Smit & Wandel, 2006). This adaptive capacity takes place as actors engage in a “recombination of evolved structures and processes” in response to external changes (Folke, 2006, p. 259). This perspective suggests that organizations (including, for example, partnerships in sustainable business models) need to learn and change in anticipation of disturbances occurring in the socio-ecological systems in which they are embedded (Berkes et al., 2003; Kinzig et al., 2006).

In relation to these dimensions of socio-ecological resilience, threatening factors involve changes that may alter the relationships within the socio-ecological system in irreversible ways, even in the long run. From the perspective of cross-sector partnerships, or other subsystems within the broader socio-ecological system, these disturbances may either be exogenous or endogenous. Exogenous disturbances entail natural fluctuations (e.g., rising temperatures) or social fluctuations (e.g., greenhouse gas emissions or the introduction of a new policy, Orr et al., 2018) that may cause the system to reach a “tipping point,” that is, “the moment of critical mass, the threshold, the boiling point” that risks to shift relationships within an ecosystem in irreversible ways (Gladwell, 2000, p. 12). Conversely, endogenous disturbances refer to actions undertaken within the partnership that may cause a disruption in the external system, such as tensions or conflicts among partners (e.g., a public actor introducing a regulation that clashes with the interests of a private actor, Orr & Donovan, 2018) or the unintended consequences of an undiscussed partnership intervention (e.g., introducing a car sharing service that disrupts the local system of transport and public safety, Dreyer et al., 2017).

CAS

The notion of CAS has been widely used to interpret the dynamics that may influence socio-ecological resilience, first in the field of systems theory (Kauffman, 1995; Nicolis & Prigogine, 1989) and later in environmental sciences (Olsson et al., 2004; Walker et al., 2004). More recently, the notion of CAS has been used in management studies to describe and explain how a wide range of organizations, such as companies, communities, or supply chain partnerships (Boisot & Child, 1999; Inigo & Albareda, 2016; Orr et al., 2018), interact with their external environments, including their socio-ecological systems (Whiteman et al., 2013; Winn & Pogutz, 2013). In what follows, we describe the features of CAS that have been used in management studies to conceptually link sustainable business models, cross-sector partnerships, and socio-ecological resilience.

As a first step, we synthesize and exemplify the distinctive features of CAS. First, CAS are complex. Complexity refers to the large number of agents, their partial independence, and the multiple layers of interdependence in a system. For example, the global biosphere involves myriad human and natural agents (Winn & Pogutz, 2013). These agents are partially independent: Humans do not directly depend on their interaction with other natural agents, such as water, land, plants, or animals, nor on the interaction with the majority of other humans. At the same time, when looking at the system as a whole, all humans indirectly depend on each other and on all other natural agents in innumerable ways (Whiteman et al., 2013). Water or land scarcity constrains humans’ access to nutritious and affordable food while socioeconomic inequality creates disturbances that ultimately affect their safety.

Second, CAS are adaptive. The notion of adaptiveness highlights that CAS are self-organizing, path-dependent and dynamic. Given their partial independence, human agents either individually or collectively (e.g., organized in subsystems, such as families, friends, companies, or even countries) change how they organize themselves depending on changing conditions in the overall system surrounding and interacting with them (Whiteman et al., 2013). Subsequently, patterns emerge from the interactions among these agents, which are giving life to novel routines, structures, and logics (Dooley, 1997). These emerging patterns either develop into new resources and competencies that create value for organizations if recognized and cultivated (Jones & Corner, 2012) or lead to tensions when ignored or suppressed (Schad & Bansal, 2018). Organizations need to be aware of these dynamics of emergence to prevent and absorb shocks that may arise within their boundaries (B. B. Lichtenstein et al., 2007).

Finally, CAS are systems. This systemic nature of CAS entails nonlinear, recursive, and modular sets of relationships among multiple agents. When agents collaborate to innovate in an innovation ecosystem, the outcomes emerge from innumerable interaction effects among agents, such as funders, researchers, policymakers, consumers, and civil society (Inigo et al., 2017). These outcomes are inherently nonlinear due to multiple interaction effects. Given the presence of interaction effects, a small action may generate a remarkable chain of reactions (i.e., ripple or butterfly effects). Conversely, even remarkable efforts (e.g., large business investments or policy changes) may generate no apparent or perceived effects (B. M. Lichtenstein, 2000) when these interaction effects in the system act as bottlenecks. Due to the interaction effects, it is impossible to disentangle the causes and effects of specific phenomena or actions in the system because the effect may influence or be perceived as the cause (Kurtz & Snowden, 2003). It is challenging to make claims that any isolated investment has influence on the rest of the system. These nonlinear relationships in the system also relate to the modularity of CAS; that is, the fact that agents are organized in strongly interdependent subsystems, yet poorly connected to each other (Schilling, 2000). Given their modularity, human agents tend to be closely interdependent in specific groups (e.g., families, group of friends, companies, professions, partnerships, or countries) and poorly connected to other groups. These multiple, self-organizing, and nonlinear processes—developed on the basis of the existing status and memory of interdependent agents—make the system dynamics difficult for agents to predict.

These features of CAS have important implications for understanding and predicting how the specific design of the partnership component of sustainable business models can support the resilience of socio-ecological systems. From a CAS perspective, all interactions among agents over time, including the evolution of cross-sector partnerships as a form of interdependence among agents, can be seen hierarchically as subsystems within larger systems (Schad & Bansal, 2018). Cross-sector partnerships are embedded in CAS and configured as subsystems that involve multiple sub-subsystems (see Figure 1). They involve sets of interdependent and partially independent organizations (e.g., a focal company, customers, government or nonprofit partners, and investors) that involve individual agents who self-organize and interact within these organizations as well. Cross-sector partnerships can thus be seen as subsystems embedded in (and part of) broader socio-ecological systems (Schad & Bansal, 2018; Williams et al., 2021). Insight into how sustainable business models allow different interactions and interdependencies among partnering organizations to emerge contributes to our understanding of how they collectively manage to support the buffering capacity and adaptation of the socio-ecological systems (Folke, 2006).

OPEN IN VIEWER

Figure 1.

Sustainable business models and cross-sector partnerships embedded in socio-ecological systems.

Cross-Sector Partnerships as Organizational Mechanisms of Sustainable Business Models

We argue that cross-sector partnerships represent a core component and distinctive organizational mechanism through which sustainable business models create social and environmental value in support of socio-ecological systems. We base our view on two well-established literatures, one on sustainable business models and the other on cross-sector partnerships. Sustainable business models represent an organized system of interconnected and interdependent activities and actors which, together, have potential to generate positive impact for sustainability (Boons & Lüdeke-Freund, 2013). To achieve their sustainability aspirations, sustainable business models depend on “collaboration across a wider set of stakeholders in an industrial system” (Bocken et al., 2015, p. 67) and must consider the effects on the plurality of agents embedded in their socio-ecological system (Pedersen et al., 2019; Upward & Jones, 2016). The cross-sectoral nature of the partnership component of sustainable business models clearly sets them apart from other business models where companies mainly collaborate with their supply chain actors or other industry players to create economic value (Osterwalder & Pigneur, 2010). In sustainable business models, companies tend to partner with public and nonprofit actors to create or prevent the destruction of social or environmental value (Stubbs & Cocklin, 2008).

The literature on sustainable business models explicitly refers to partnerships among stakeholders from different sectors as a key organizational component for the creation and capture of value in the broader socio-ecological system. As Rohrbeck and colleagues (2013) put it, sustainable business models inherently require “multiple organizations to work together and pool complementary assets” (p. 3). More specifically, they “differ in type (industry, public research and nonprofit), in their position in the value chain (manufacturing, service, etc.) and industry (energy, ICT, etc.),” and in creating a value-creating or value-capturing system (p. 5). What distinguishes sustainable business models from the traditional business models is not only their aspiration to create social and environmental value for a wide range of stakeholders but also the collaboration among stakeholders with diverse backgrounds and values (Boons & Lüdeke-Freund, 2013; Pedersen et al., 2019; Stubbs & Cocklin, 2008).

Complementarily, the literature on cross-sector partnerships has widely investigated the organizational processes of interaction among multiple stakeholders to create and capture value (Van Tulder et al., 2016). This literature specifies how cross-sector partnerships engage and deliver value to the involved actors (Clarke & MacDonald, 2019; Dentoni et al., 2016), the intended beneficiaries (Le Ber & Branzei, 2010; Trujillo, 2018), and the socio-ecological systems in which they are embedded (Clarke & Crane, 2018; Van Tulder & Keen, 2018). This literature has recently suggested that cross-sector partnerships create value to participants through the development of organizational capabilities (Dentoni et al., 2016) and by gaining organizational, human, and physical resources (Clarke & MacDonald, 2019). Furthermore, cross-sector partnerships create value to their beneficiaries by including their voice in deliberation and decision-making processes (Le Ber & Branzei, 2010), thus expanding their capacities for collective action (Trujillo, 2018). Finally, cross-sector partnerships create value in their ecosystem by developing organizational mechanisms that take the complex nature of the encountered problems into account (Clarke & Crane, 2018; Van Tulder & Keen, 2018).

Cross-Sector Partnership Elements of Sustainable Business Models

Despite their complementarity, the two strands of literature do not delineate how they consider and act upon the nature of CAS, thereby limiting threats to socio-ecological resilience. This represents a remarkable knowledge gap, considering that many studies suggest that the resilience of socio-ecological systems is being seriously compromised (Whiteman et al., 2013; Winn & Pogutz, 2013). Based on these two parallel literatures, we identify three key elements of the partnership component of sustainable business models that can be designed and aligned in awareness of the nature of CAS. In the following, we refer to these as strategic, institutional, and learning elements of cross-sector partnerships.

First, strategic elements of cross-sector partnerships refer to the processes of value creation and capture among multiple agents, including their impacts on the socio-ecological systems surrounding them. The literature on sustainable business models (Abdelkafi & Täuscher, 2016; Bocken et al., 2013; Joyce & Paquin, 2016) and cross-sector partnerships (Clarke & Fuller, 2010; Clarke & MacDonald, 2019; Stadtler & Van Wassenhove, 2016) explain how cross-sector partners create value in socio-ecological systems through their resource and activity interdependencies. For example, the interdependency of the phone company Telenor and the microfinance organization Grameen Bank is based on the complementarity of the former’s technological resources and the latter’s knowledge and networks in the Bangladeshi context (Seelos & Mair, 2007). Through these interdependencies, cross-sector partners mitigate uncertainty and limit unintended consequences for the environment where they try to deliver positive outcomes (Dahan et al., 2010). Along with building interdependencies among partners, creating value in socio-ecological systems also requires deep understanding of how sustainable business models interplay with (Abdelkafi & Täuscher, 2016) and influence (Joyce & Paquin, 2016) the agents outside the boundaries of the partnership. For example, Bocken and colleagues (2013) illustrated how cross-sector partners in Europe that were trying to create sustainable value mapped not only their own resource interdependencies but also the resources and networks of other agents in the socio-ecological system. More recently, van Hille and colleagues (2020) illustrated how cross-sector partners considered how nature acts as a key agent that influences the value creation process in socio-ecological systems by regenerating tea plantations and its agroecological systems.

Second, institutional elements refer to organizational arrangements meant to navigate the interplay of heterogeneous and sometimes conflicting logics, values and identities that sustainable business models experience in their cross-sector partnerships. These institutional elements have been widely analyzed both in the sustainable business models (Laasch, 2018, 2019; Ocasio & Radoynovska, 2016; Randles & Laasch, 2016) and the cross-sector partnerships literature (Ashraf et al., 2019; De Lange et al., 2016). Partnerships often involve a careful combination of formal and informal structures to regulate interactions among partners (Cohen & Winn, 2007). For example, multinationals and NGOs mutually co-evolved their initially conflicting logics into compatible logic differences (De Lange et al., 2016). Cross-sector partners used what Brown and Eisenhardt (1997) called “semi-structures”: formal arrangements that deliberately leave space for informal adaptation processes (De Lange et al., 2016). When these organizational arrangements support partnerships to embrace multiple logics, they can effectively address complex socio-ecological issues (Ferraro et al., 2015) and generate pervasive change in socio-ecological systems (Laasch, 2019). Yet, when they fail to do so, they risk triggering dynamics of exclusion and oppression (Martí, 2018). Institutional elements of cross-sector partnerships help to focus on the “fundamental role of values and normative orientations as motivational forces and guides for innovation processes” in sustainable business models (Breuer & Lüdeke-Freund, 2017, p. 27).

Third, learning elements of cross-sector partnerships refer to the processes of experimentation and sensemaking that develop into knowledge and capabilities among multiple agents. Learning elements have been widely investigated, both in the sustainable business model (Martins et al., 2015; Sosna et al., 2010) and the partnership literature (Dentoni et al., 2016; Ryan & O’Malley, 2016). Frequent and widespread experimentation in cross-sector partnerships supports processes of innovation and change among (Berends et al., 2016) and within partnering organizations (Dentoni et al., 2016; Martins et al., 2015; Sosna et al., 2010), especially in uncertain contexts (Andries et al., 2013). When carefully considered, learning in cross-sector partnerships can shape outcomes through the building of more collaborative practices and a stronger vision alignment (Roome & Louche, 2016; Schaltegger, Lüdeke-Freund, & Hansen, 2016). As Schaltegger, Hansen, and Lüdeke-Freund (2016) underline, much remains to be explored about how learning theories at the organizational and individual level “explain the transformation of business models of established firms,” through “learning-action networks and cooperative arrangements, but also political power struggles between stakeholder groups” (p. 8). To support the design of learning elements of cross-sector partnerships, Inigo and colleagues (2017) identified the dynamic capabilities that played an essential role for a set of Basque companies to adapt their established partnerships. Furthermore, Kurucz and colleagues (2017) and Nicholson and Kurucz (2017) developed a framework to develop relational leadership competencies for agents involved in cross-sector partnerships.

Although scholars in the fields of sustainable business models and cross-sector partnerships seem to agree that these three elements of cross-sector partnerships need consideration and alignment to deliver and create social and environmental value (Bocken et al., 2013; Schaltegger, Lüdeke-Freund, & Hansen, 2016), the extant literature does not inform how their design could influence socio-ecological resilience. In the next section, we therefore relate these three elements of partnerships to the three key distinctive features of CAS.

Strategic Elements From a CAS Perspective

The first row of the framework depicts how the strategic elements of partnerships can take into account and act upon the nature of CAS (see Table 1). From a CAS perspective, the leading question for designing the strategic elements of partnerships entails: When aware of the nature of CAS, how would cross-sector partnerships organize their resource and activity interdependencies to sustain value creation (and limit value destruction) in socio-ecological systems? As we discuss below, CAS theory suggests that partners need to zoom out, zoom in, and transcend language and disciplinary silos (see Table 1, top row).

First, from a CAS perspective, partners that collaborate in sustainable business models are fundamentally challenged in assessing the value that they create or destroy beyond the partnership boundaries because they are embedded in complex networks of multiple, interdependent, and independent agents. Partners actually know very little about the indirect consequences of their actions for the socio-ecological system. This challenge is acute, for example, for partnerships aiming to produce sustainable outcomes to restore depleted natural ecosystems (Whiteman et al., 2013) or to stabilize socio-political turbulence in fragile contexts (Kolk & Lenfant, 2015). Along with the challenge, though, the nature of CAS may provide opportunities for partners. By coordinating purposively with other agents at, or outside the boundaries of the partnership, they can indirectly, yet purposively influence changes in the overarching system. CAS theory suggests that cross-sector partners need to purposively engage in zooming out (Schad & Bansal, 2018). Zooming out refers to allocating attentional resources and simultaneously adopting multiple frames necessary to sense the interconnectedness of issues and agents surrounding and interacting with the organization. When unraveling the broader interconnectedness of agents in a system (i.e., seeing the forest beyond the trees, Schad & Bansal, 2018), organizations gain a broader strategic perspective on competition and cooperation, as predator and prey may become allies in complementing each other’s resource endowments (Bansal et al., 2018). To engage in zooming-out practices, organizations first need to allocate resources (e.g., communication channels, time) to gather and interpret information on the continuous changes in the external environment (Bansal et al., 2018). Second, cross-sector partners need to adopt complex frames to interpret the interrelatedness of relevant elements in socio-ecological systems that surround them (Hahn et al., 2014; Schneider et al., 2017). Valente (2010) suggests that “the increasing recognition of the interconnectedness of social, ecological, and economic issues [. . .] implies the need for frameworks and tools that comprehend and incorporate complexity rather than frameworks that gravitate toward simplicity and reductionism” (p. 469).

Second, according to CAS theory, all organizations also face internal change forces—which may cause instability and disruption—given the dynamic, self-organizing, and path-dependent relationships among agents in CAS. The dynamics of these internal forces have implications for cross-sector partners, because self-organizing processes among agents could build synergies or clashes between them. Depending on how these self-organizing forces are recognized and coordinated, they constitute either a critical resource or a liability for cross-sector partnerships. To uncover the tensions emerging among agents and to generate valuable resources (Colbert, 2004; Rycroft & Kash, 2004), Schad and Bansal (2018) suggest organizations to engage in zooming-in practices. Zooming in entails unveiling the tensions and synergies that continuously emerge among agents within the organization. By zooming in, cross-sector partners gain an “understanding of the dominant processes that lead to the emergence of systems changes” (Schad & Bansal 2018, p. 17). If aware of this CAS feature, cross-sector partnerships build unique competences from within through co-agency as a process of emergence (Inigo & Albareda, 2016). To intentionally engage in zooming-in practices, Colbert (2004) suggests that organizations should concede some organizational slack, leaving resources, such as people’s time or organizational space, purposively unused. Slack gives room to cross-sector partners to discover inner and emergent tensions or competencies.

Third, given the nonlinear, recursive, and modular sets of relationships among agents, CAS theory suggests that cross-sector partners are challenged to build collaborations, despite fuzzy and unstable incentives and perceptions of what the collaborative outcomes may be over time. As small actions may unexpectedly cause remarkable consequences, depending on the complex interplay of factors in the ecosystem, partners need to continuously reconsider, and, if necessary, suspend the expectations of impact that lead their actions. If they do not take the time and the space to reconsider, they face risks of unintendedly making the problems that they seek to address even more acute (Ferraro et al., 2015). Under these circumstances, CAS theory suggests designing partnerships that support transcending language and disciplinary silos. To do so, cross-sector partners can establish processes of deliberation and decision-making that purposively give voice to agents with heterogeneous backgrounds, languages and disciplines. Transcending language and disciplinary silos entail cultivating cross-disciplinary discourses, nurturing multidisciplinary perspectives, and drawing on the diverse capabilities of practitioners who develop new approaches on the ground (Winn & Pogutz, 2013). With the support of their cross-sector partners, companies would need to increasingly get out of their comfort zone to re-assess their footprint in socio-ecological systems in terms of chemical pollution, climate change, fresh-water use or biodiversity loss measures (Whiteman et al., 2013). In terms of decision-making processes, partnerships would need to develop voluntary, self-regulating approaches (Breite & Koskinen, 2014; Pathak et al., 2014). As partners’ incentives and expectations of impact may change unexpectedly, these approaches should take into account the heterogeneous stakeholder perceptions of fairness (Winn & Pogutz, 2013). These perceptions are likely to vary widely, especially among poorly connected, yet potentially complementary stakeholders in a system (Manning & Reinecke, 2016). In recent years, for example, companies involved in trading and manufacturing palm oil had to reform their decision-making routines and bylaws in the Roundtable for Sustainable Palm Oil (RSPO) partnership to better involve complementary, heterogeneous agents embedded in the socio-ecological system (Dentoni, Bitzer, & Schouten, 2018).

Institutional Elements From a CAS Perspective

The second row of the framework articulates how the institutional elements of cross-sector partnerships can take into account and act upon the nature of CAS (see Table 1), thus supporting sustainable business models to influence the socio-ecological systems they are embedded in. Here, the leading question for the design of institutional elements of cross-sector partnerships from a CAS perspective involves: When aware of the nature of CAS, how would cross-sector partnerships organize themselves according to the multiple underlying logics, values and identities of their agents? As we will elaborate below, CAS theory suggests that cross-sector partners should build narratives across multiple logics; nurture the emergence of new logics; and renegotiate on the basis of logics.

First, as CAS involve multiple, interdependent and independent agents, the behavior and structure of cross-sector partnerships emerge from myriad interactions among the multiple agents involved (Boal & Schultz, 2007). Under CAS assumptions, a focus on changing technologies and structures (as suggested for example by Ramus et al., 2017) would not suffice to coordinate agents driven by multiple heterogeneous institutional logics. From a CAS perspective, hierarchical authority and control in partnerships would be useless because emergence among interacting agents in and around organizations simply occurs. This raises the question what leadership would entail in partnerships. A partial answer suggests that leaders would be more effective “by influencing the tags that produce the structure of interactions among organizational agents” (Boal & Schultz, 2007, p. 411) rather than seeking to build organizational structures themselves. Through dialogue and storytelling, leaders can narrate a vision that inspires and influences how partners interact and construct shared meanings of their past, present and future collective actions (Waddock et al., 2015). The use of dialogue and storytelling with agents within and outside the partnership allows building narratives that transcend multiple logics that coalesce in and around their boundaries (Laasch, 2018, 2019). These narratives involve conveying and communicating visions that influence the structure of interactions among agents with different logics. Without using hierarchical authority, narratives act as triggers and catalyzers of self-organized actions and interactions among agents within and outside the partnership. For example, over the past 15 years in global food and agriculture, leaders of various partnerships promoting vegetarian and vegan diets were able to build a narrative around the production and distribution of sustainable alternative protein sources for human consumption without any structured interaction (Dentoni et al., 2017).

Second, given the dynamic, self-organizing, and path-dependent relationships among agents in CAS, cross-sector partners may spontaneously and continuously reorganize their interactions (Tsoukas & Chia, 2002). From the actions and interactions occurring among agents, structural change emerges through self-renewal and it produces a history of organizational becoming and change (Dooley, 1997). Partners progressively realize or discover from the tensions that they face in action (Chia, 2014) that their interactions are driven by novel or shifting logics. For example, through experimenting and making sense of their outcomes, partners in many local food communities (such as community gardens or organic food associations) across Europe realized and changed the underlying values driving their actions, even over short periods (Dentoni, Pascucci, et al., 2018). Drawing implications for cross-sector partners, the emergence of new logics gives new energy to or draws energy from the interactions that constitute the collaboration. Building on these CAS assumptions, we propose that cross-sector partners aware of the nature of CAS would nurture the emergence of new logics and reflect retrospectively on what intrinsically motivates the on-going relationships among cross-sector partners. How can the partnership support these practices? First, through frequent interactions, partners could establish new motives and modalities of interaction and collaboration (Ashmos et al., 2002). Second, they could activate “internal” attentional resources—such as slack specifically dedicated to “make room” for deeper reflexive processes—outside the established routines that hinder deeper processes of reflection and paradigm-shift. Third, as they engage in deeper reflection processes, partners make sense retrospectively and collectively of why they engaged in interactions and reactions to discover the institutional logics that drive them from the bottom up (B. B. Lichtenstein et al., 2007).

Third, given the nonlinear, recursive, and modular sets of relationships among agents in CAS, competing logics among cross-sector partners risk leads to outbursts of tensions and conflicts in different ways and patterns. To avoid unintended consequences from these outbursts, CAS theory suggests leaving room in organizations for uncodified information to diffuse among members, negotiate horizontal coordination, as well as personal, nonhierarchical relationships (Boisot & Child, 1999). To avoid oversimplistic frames of codified information within its boundaries (e.g., catchy vision statements or grand plans that may not resonate with agents involved in a partnership), organizations aware of CAS would organize more like a clan than a firm (Boisot & Child, 1999). Accordingly, cross-sector partners aware of CAS would continuously renegotiate their goals and activities on the basis of the heterogeneous logics to pursue a meaningful influence on the socio-ecological systems they are embedded in. By continuously renegotiating their values and beliefs, cross-sector partners would more effectively prevent and absorb the nonlinear, recursive, and modular dynamics involved in CAS (Boisot & Child, 1999). To practice these continuous renegotiations of logics, partners may solicit each other to articulate deeper meanings as they act and interact (Colbert, 2004). They give priority to full engagement of all agents involved, for example, by investing time in sharing information across all levels of the partnership rather than seeking rapid and cost-effective decision-making processes (Colbert, 2004). Finally, if aware of the nature of CAS, more powerful agents in cross-sector partnerships would voluntarily avoid exerting their power to avoid unintended outbursts of conflict and instead promote participatory processes of interaction (Accard, 2019) to stabilize partners’ interactions and mitigate the risks inherent in nonlinear, recursive, and modular socio-ecological systems (Ashmos et al., 2002).

Learning Elements From a CAS Perspective

The third row of the framework synthesizes how the learning elements of cross-sector partnerships can take into account and act upon the nature of CAS (see Table 1). The leading question that partnerships need to address to design learning elements to influence the socio-ecological systems would entail: When aware of the nature of CAS, how would cross-partnerships organize their individual and organizational learning processes? CAS theory suggests that cross-sector partners would enhance distributed experimentation; engage in purposive unlearning processes; and encourage sensemaking and sensegiving.

As CAS involve multiple, interdependent, and independent agents, cross-sector partners inherently lack the knowledge how to coordinate with most of the other agents outside their boundaries that, directly or indirectly, influence their sustainability aspirations. Under these conditions, learning from many small-scale local experiments (Andries et al., 2013) is critical to assess what works and what does not in the plethora of local contexts where the partnership realizes its outcomes (Ferraro et al., 2015). Conversely, cross-sector partners would avoid large-scale, top-down, context-unspecific interventions that may impact different agents in the system with unintended and poorly understood effects. When facing complex sustainability challenges (Ferraro et al., 2015), CAS theory suggests organizations to encourage distributed experimentation. This refers to “iterative action that generates small wins, promotes evolutionary learning, and increases engagement, while allowing unsuccessful efforts to be abandoned” (Ferraro et al., 2015, p. 376). The notion of distributed experimentation implies that the most suitable idea in a local context will survive and thrive. For example, the business models used to scale the use of alternative energy and reduce greenhouse gases, such as those involving wind and bio-fuel energy in the United Kingdom (Parkhill et al., 2015), entailed many small local experiments within partnerships among municipalities, house owner associations, and energy companies. Through observation, reflection, and extensive communication among agents within and across multiple local experiments (Jalas et al., 2017), agents learn from each other in real time. Along this engaged process of learning, given their embeddedness in dynamic, self-organizing, and path-dependent relationships among agents, cross-sector partners aware of the nature of CAS would strive to rapidly interpret the outcomes of the many small-scale experiments that they run. Conversely, they may fail to learn if, during and after engaging in distributed experimentation, the partners do not go through a process of reflection that is open to multiple interpretations (Bettis & Prahalad, 1995). To interpret which local experiments may have realized a small win or a small loss, partners would seek a diversity of lenses, or mental models, to make sense of these outcomes (Becker, 2010). Cross-sector partnerships aware of CAS would thus continuously challenge their dominant logic when interpreting the outcomes of their experiments. They would engage in purposive unlearning processes to stimulate organizational intelligence and adaptive learning (Bettis & Prahalad, 1995). The business model literature provides rich examples of how partners unlearn when they face external challenges or internal tensions (Mehrizi & Lashkarbolouki, 2016; Sosna et al., 2010). In the case of a partnership led by a dietary product retail store (Sosna et al., 2010), partners were confronted with rapid changes that increase their “repositories of knowledge.” These changes prompted “managers to re-conceive situations beyond their previous cognitive structures, and this increased knowledge leads them to develop more complex cognitive schema to deal with their future decision-making” (Sosna et al., 2010, p. 392). To purposively unlearn, CAS theory suggests, first, that partners honor their errors made by encouraging reflective practices—for example, promoting incentive schemes that honor what they would collectively sense to be remarkable learning experiences (Becker, 2010). Second, they invite dialogue on alternative approaches through virtual or physical platforms for discussion (Colbert, 2004). Finally, partners provide organizational support and training during the process of unlearning (Cegarra-Navarro & Dewhurst, 2006), because “unlearning must be a prior consideration and not an afterthought” (Becker, 2010, p. 263) to effectively facilitate learning and collaboration.

Finally, given the nonlinear, recursive, and modular nature of their environment, cross-sector partners may struggle to realize whether some outcomes are to be considered negative, positive, or just partial, as heterogeneous partners inherently look at different facets of the same outcome (Kurtz & Snowden, 2003). Even when a general sense of satisfaction (or frustration) permeates the outcome of an experiment, CAS theory posits that it would be hard to pinpoint the specific drivers for that outcome, nor to univocally disentangle causes and effects related to that outcome (B. M. Lichtenstein, 2000). In these situations, partnerships aware of the nature of CAS would engage in processes of sensegiving and sensemaking to collectively interpret the partial, in-becoming organizational outcomes (Wesley et al., 2013). Sensemaking refers to developing a coherent story that helps agents interpret partial outcomes in becoming (Plowman et al., 2007; Wesley et al., 2013). Following this interpretive work, sensegiving entails visioning a way forward for the partners involved to collectively deal with these outcomes (Gioia & Chittipeddi, 1991). When faced with complex issues of wetland management (Wesley et al., 2013), for example, partners involved in a Biosphere Reserve in Sweden during the 1970s “embarked on an exercise to thoroughly map historical and present-day land use practices, creating a system wide picture” (i.e., sensemaking) and then took “steps to disseminate this understanding of the ecosystem through a series of exhibitions” and one-to-one meetings, giving “new meaning to the wetlands as water rich rather than water sick” (Wesley et al., 2013, p. 27). According to CAS theory, cross-sector partners can effectively engage in sensemaking and sensegiving retrospectively (Kurtz & Snowden, 2003). Although causes and effects of partial outcomes are not predictable in advance, they can be examined backward in time with stakeholders, to collectively understand cause-and-effects and feedback loops when seeking to understand past patterns (Snowden & Boone, 2007). Yet, for this retrospection to happen, resources for convening need to be allocated in terms of regular communication and interaction among partners (Seidl & Werle, 2018). For the partners involved, this process of retrospection involves an artful use of language and symbols to give meaning to unfolding events and fostering the development of a shared understanding (B. B. Lichtenstein & Plowman, 2009). How partners collectively engage in sensemaking and sensegiving processes depends on the psychological traits of the agents involved—such as their congruence between real and ideal self and their ability to embracing a variety of conflicting issues (Akrivou & Bradbury-Huang, 2011).

Contribution to Theory on Cross-Sector Partnerships and Sustainable Business Models

In this article, we developed a framework based on CAS theory that analyzes how cross-sector partnerships as a core and distinctive mechanism of sustainable business models can support socio-ecological resilience. The framework combines the key features of CAS and the key strategic, institutional, and learning elements of partnerships that sustainable business models rely on to support socio-ecological resilience. Our CAS perspective corroborates the notion that sustainable business models distinguish themselves from other business models by relying on cross-sector partnerships to create social and environmental value (Boons & Lüdeke-Freund, 2013; Pedersen et al., 2019; Stubbs & Cocklin, 2008). Although business models, in general, have been conceptualized as subsystems—bound by interrelated sets of resources and activities (Foss & Saebi, 2018; Massa et al., 2018; Zott & Amit, 2010)—a CAS perspective highlights that business models are subsystems within a broader socio-ecological system. From this perspective, a business model aiming to be sustainable needs to engage in cross-sector collaboration to negotiate and make sense of how to create value in socio-ecological systems (Bocken et al., 2015; Boons & Lüdeke-Freund, 2013; Rohrbeck et al., 2013; Schaltegger, Hansen, & Lüdeke-Freund, 2016; Stubbs & Cocklin, 2008). Organizing through cross-sector partnerships is critical for sustainable business models to fulfill the promise of addressing socio-ecological problems such as climate change, biodiversity loss, and global inequality.

Our article’s first main contribution is that we consider socio-ecological resilience as the main outcome to analyze the effectiveness of sustainable business initiatives and by adopting CAS theory explain what the consequences are of doing so. We reinforce the idea that sustainable business initiatives should be assessed in terms of their impact on the level of socio-ecological systems instead of the level of the organization only (Hahn et al., 2015; Williams et al., 2021). Although extant studies argue that sustainable business models’ purpose is to create social and environmental value (Aguiñaga et al., 2018; Bocken et al., 2015; Boons et al., 2013), such value often boils down to improvements in organizations’ social and environmental performance. We argue that support for socio-ecological resilience is a more adequate outcome measure because it better aligns the promise of sustainable business models’ contribution to addressing socio-ecological problems and their actual impact.

Our perspective also highlights the challenge of assessing the impact of an organizational-level sustainability initiative such as a sustainable business model on a system-level outcome such as socio-ecological resilience. Although existing studies have tried to conceptualize value creation (Evans et al., 2017; Joyce & Paquin, 2016) and the delivery of net-positive impact (Dyllick & Muff, 2016) in socio-ecological systems, CAS theory suggests that defining and assessing a business model’s value creation and impact—similar to any other agent or subsystem of agents in a system—is quite simply impossible. The involvement in CAS of multiple, interdependent, and independent agents does not allow for distinguishing their impact from those of other agents acting simultaneously within the same socio-ecological system. Due to the dynamic, self-organizing, and path-dependent nature of interdependencies among agents, no impact can be claimed beyond partial and unstable outcomes, which may change unexpectedly and unwittingly over time. The nonlinear, recursive, and modular configuration of agents in the system implies that impact can easily be contested, because disentangling causes from effects is problematic. We argue, therefore, that sustainable business models can, at best, be expected to support socio-ecological resilience but not to have a direct impact at the system level.

As our second main contribution, we extend previous studies by showing in detail how cross-sector partnerships provide the organizational structure for sustainable business models to support socio-ecological resilience (Heuer, 2011; Seitanidi, 2008; Winn & Pogutz, 2013). Our framework presents the strategic, institutional, and learning elements that allow cross-sector partnerships to organize the resource and activity interdependencies, the multiple underlying logics, values, and identities of their agents, and the learning processes. It sheds a new light on the ways in which cross-sector partnerships can design their organizational processes in relation to the complex socio-ecological issues that they seek to address (Dentoni, Bitzer, & Schouten, 2018; Ferraro et al., 2015; Kolk & Lenfant, 2015). Consistent with the partnership literature, we concentrate on designing and aligning organizational elements in relation to key dimensions of complexity. Taking a CAS perspective rather than an issue-centered view (Ferraro et al., 2015) broadens the scope of the partnership elements that require design and alignment as it not only considers institutional elements (Dentoni, Bitzer, & Schouten, 2018) but also strategic and learning elements.

By considering the partnership elements through the lens of CAS theory, we also extend the literature that relates business models (Andries et al., 2013; Sosna et al., 2010), including those aiming to be sustainable (Abdelkafi & Täuscher, 2016; Bocken et al., 2015; Laasch, 2018; Martí, 2018), to different facets of complexity in socio-ecological systems (Boons et al., 2013). We build on studies suggesting that sustainable business models need to understand the complex interplay among multiple interdependent actors in socio-ecological systems (Abdelkafi & Täuscher, 2016; Cosenz and Noto 2018). We highlight the need to consider the internal complexity of sustainable business models that arise from the interdependencies and interactions among agents within the cross-sector partnership. As such, our framework reiterates studies suggesting that the more complex a cross-sector partnership’s external environment, the more complex it needs to be in terms of establishing new processes and structures (De Lange et al., 2016; Ryan et al., 2012; Schneider et al., 2017). For example, our framework underlines the need for finding a normative synthesis between the multiple logics and values that cross-sector partners put forth (Breuer & Lüdeke-Freund, 2017; Laasch, 2018, 2019) and for learning in rapid, distributed cycles of experimentation and sensemaking (Andries et al., 2013; Sosna et al., 2010). The nonlinear, recursive, and modular configuration of agents involved in a partnership means that for them to collectively support a system-level outcome like resilience, they need to constantly realign the strategic, institutional, and learning elements of partnerships to avoid unintended consequences on the level of socio-ecological systems (Martí, 2018).

To summarize, then, our article advocates for the need to assess sustainable business models in terms of their support for socio-ecological resilience. Yet, it also underlines the complexity involved in doing so. Our framework suggests how this challenging task of designing cross-sector partnerships, while being aware of CAS, can best be managed to most effectively support socio-ecological resilience and avoid unintended consequences.

Managerial Implications and Directions for Future Research

This article makes organizational decision-makers aware of the complexity of having a positive, or limiting a negative, impact on the resilience of socio-ecological systems. No matter how good the intentions, the complexity of socio-ecological problems means that sustainable business initiatives run the risk of not having the intended impact or making things worse even due to unintended consequences. Our CAS framework helps decision-makers to cope with this complexity by informing them how to design the partnership component of their sustainable business models to better support socio-ecological resilience. By aligning partnership elements (i.e., strategic, institutional, and learning elements) with the nature of CAS, decision-makers claiming to design and implement sustainable business models have the opportunity to limit both exogenous threats (e.g., environmental or socio-political disturbances such as the negative effects of climate change or an adverse policy decision that may affect an economic sector) and endogenous threats (e.g., tensions or conflicts with pervasive negative effects on the ecosystem as well as unintended consequences) to socio-ecological resilience.

A limitation of our study is that it does not shed light on the conditions and incentives needed to do so. For example, do decision-makers have the private interest to voluntarily relax exerting their power for the sake of making a partnership better able to interpret possible threats to socio-ecological resilience using multiple frames and perspectives? Or, would decision-makers have the incentive to renegotiate their logics when establishing goals and activities of their partnerships? In our framework, we assume that being aware of the nature of CAS and of the threats to socio-ecological resilience would automatically lead cross-sector partners to act upon them. However, behavioral theories show that awareness often does not suffice to meaningfully influence practice; stakeholder pressures and power imbalances could hinder developing and aligning the elements in practice. More generally, while CAS theory often implies rejecting command-and-control approaches to manage organizations—including cross-sector partnerships—it has been recently criticized for taking little account of the power dynamics (Cleaver & Whaley, 2018). To make our CAS view more robust, we invite scholars to investigate the power dynamics that underlie designing or adapting the partnership component of sustainable business models for socio-ecological resilience.