Stakeholders’ Involvement, Organizational Learning and Social Innovation: Factors for Strengthening the Resilience of Moroccan Cooperatives in the Post-COVID-19 Era

Abstract

The Moroccan cooperative sector is increasingly important, not only in the social and economic fabric of Morocco, but also in the sustainable development of the Kingdom. With the advent of COVID, the cooperative sector offers more inclusive and sustainable economic alternatives than ever before. In this context, organizational resilience is essential to preserve the sustainability of cooperatives and anticipate potential crises. This study addresses the following issue: What are the organizational factors necessary to strengthen the organizational resilience of the Moroccan cooperative in the Fez-Meknes region in times of COVID-19 crisis? The purpose of this paper was to test the hypothesized relationships between a set of latent constructs (actor involvement and mobilization, organizational learning in times of a crisis and social innovation) and the organizational resilience of cooperatives in times of a COVID-19 crisis. The methodology adopted is structural equation modeling based on the PLS-SEM method under the “SmartPLS Version 3” used on data collected through a printed questionnaire administered to 160 cooperatives in the Fez-Meknes region. The results show the significant and positive influence between the exogenous constructs on the strengthening of organizational resilience of cooperatives as an endogenous construct. The novelty of the study lies in the identification of the organizational resources needed to strengthen the organizational resilience of cooperatives in the Moroccan context. The results show that organizational resilience depends on three selected organizational factors: stakeholder involvement and mobilization, organizational learning in the times of a crisis and social innovation.

1. Introduction

No one can deny that today, the COVID-19 crisis, which was subsequently transformed into a socio-economic crisis [1], has pushed companies to rethink their mode of unpredictability management in light of the probability of a succession of new crises. This probability reinforces the unpredictability that characterizes the COVID-19 crisis as a black swan event [2]. This had a direct negative effect on the organizational capacity of firms to deliver finished products to the market [3]. The crisis can negatively impact the company by creating a learning barrier threatening the continuity of its business [4].

Economic recessions due to a crisis can increase the interest of some companies to continue to invest in innovation during an economic crisis [5,6]. The instability caused by the crisis can present the company with a favorable opportunity to learn, and can therefore be a learning lever to ensure the proper functioning of the organization and the continuity of its activity [4]. This organizational learning is essential for the acquisition of the resources necessary for the development of the capacities of adaptation and absorption of shocks helping the company mobilize its resources and reconfigure itself in order to adapt and face unexpected situations [7]. To confront future crises, firms should have the dynamic resilience capabilities to absorb the harmful effects of the crisis, develop flexibility and adaptability to develop innovative solutions in response to the crisis, thus allowing to change the imposed situation to its own advantage [7,8,9].

In times of a dynamic crisis, the mobilization and deployment of necessary organizational resources mitigates the adverse effects of crises [9]. Furthermore, these organizational resources can be considered the critical competitive factors for developing dynamic capabilities in a resource-based view (RBV) [9,10]. In this view, the firm would develop a competitive advantage in the face of rare and unexpected situations [7,9,10].

In this sense, a competitive advantage can be materialized through “innovation”. The more unstable the company’s environment, the more likely it is to engage in innovative solutions [11]. Innovation can take the form of social innovation, and this can be achieved by addressing an unmet or poorly met social need, creating a change in social relations, or ensuring a better use of resources [12].

The COVID-19 crisis has had socio-economic impacts on low-income countries [13]. This stimulates interest in social enterprises to create social value in business and in addressing social issues [13,14]. Therefore, social enterprise actors actively contribute to the creation of social value, while also contributing to the resolution of social problems, with the goal of ensuring and maintaining community sustainability [15,16]. The proper understanding of the crisis on the part of business actors is paramount to “sensemaking” of the crisis and avoid its negative effects [17].

Through this article, we aim to affirm the role played by “the involvement and mobilization of actors”, “organizational learning in times of a crisis” and “social innovation” in strengthening the “organizational resilience” of Moroccan cooperatives post-crisis. We therefore pose the following problem: “What are the organizational factors necessary to strengthen the organizational resilience of the Moroccan cooperative in the Fez-Meknes region in the post-COVID-19 period?”.

To answer this question, we construct a research model that integrates three factors that will be presented in a literature review, including the study hypotheses. Next, we will present a description of the data collection process and the methods used to verify the study design. Finally, we will present the results of the study, followed by the discussion, implications and limitations of the study.

2. Theoretical Background and Research Hypotheses

This study aims to understand the important issue of organizational factors necessary for building the resilience of cooperatives as social enterprises. Based on the literature on organizational resilience, we develop a research model examining the importance of stakeholders’ involvement and mobilization, organizational learning in times of a crisis, and social innovation in building organizational resilience (see Figure 1).

In the table below (

Table 1. Definition of measurement items.

Variable	Measurement Items
Organizational resilience	- The proactive capacity of the cooperative’s management system to facilitate management change - The ability to anticipate and avoid internal and external risks - The ability to absorb tensions in times of a crisis to maintain the continuity of the cooperative’s activity - The ability to bounce back to preserve the functions and structure of the cooperative - The ability to adjust in order to transform and adapt to the crisis - The implementation of new operational routines by reconfiguring the cooperative’s activity - The mobilization of human and non-human resources in order to ensure the strength and sustainability of the enterprise - Maintaining a competitive advantage in times of a crisis
Social innovation	- Identifying poorly met or unmet customer needs in times of a crisis - Improving products and services to meet social needs in times of a crisis - Introduction of new goods and services to meet social needs in times of a crisis - Introduction of improvements in manufacturing processes in times of a crisis - Introduction of improvements in organizational methods in times of a crisis - Introduction of new commercial and communication actions in times of a crisis - Development of a marketing strategy for its products and services in times of a crisis
Organizational learning in times of a crisis	- Encouraging interaction and exchange between members at different levels - Involving the different members in understanding and interpreting the COVID-19 crisis - The development of new attitudes during the COVID-19 crisis -The generation and acquisition of new knowledge, skills and values in times of a crisis -Encouraging the mobilization and sharing of knowledge gained through experience among the different members
Involvement and mobilization of stakeholders in social innovation	- The contribution of stakeholders in determining the social need (employees, customers, suppliers) - The mobilization of internal and external stakeholders in the improvement and adaptation of its products/services (employees, clients, suppliers) - Financial support from national and international donors for business improvement or product/service innovation in times of a crisis - Support from international organizations for the improvement of the activity or the innovation of products/services in times of a crisis

), we present the variables of our study and the items chosen to measure them through the means of Likert scales.

2.1. Involvement and Mobilization of Actors

Stakeholders are defined as key groups that are essential to the existence and sustainability of the firm and that can in turn be affected by the operation, performance or achievement of the organization’s objectives [18]. In this perspective, the company must be present at the center of a network of stakeholders [19] in order to exchange organizational and informational resources [20].

These stakeholders can have a beneficial or detrimental effect on the organization [21] (Razali and Anwar, 2011). Moreover, there are several studies that have estimated the presence of a positive relationship between stakeholder management and company performance [22,23]. These studies have made a strong case for stakeholder theory.

Indeed, stakeholders are considered to be all persons with an interest in the success of any organizational change introduced within the firm, including the success of social innovation [21,24,25]. Social innovation is presented as a nexus of intersecting interdependent social exchanges among a large number of actors, with the goal of solving problems impacting the continuity of the business [26].

2.2. Organizational Learning in Times of a Crisis

The impact of the crisis on the company can be negative, leading to an organizational vacuum that can cause paralysis of the organization [4]. Indeed, the crisis can have a negative impact on the commitment of internal and external employees (customers), and thus consequences on performance [27]. Hence, the crisis can be an obstacle to organizational learning [4]. However, the crisis can be transformed into a lever for organizational learning [4]. Good crisis management requires the construction of meaning involving actors in the exchange of information and interpretation of the crisis, hence the opportunity for organizational learning and innovation, reinvention and adaptation to traumatic changes [28]. Furthermore, organizational learning should be stakeholder-driven by introducing the mechanisms of knowledge acquisition [29]. Therefore, the following hypothesis was formulated.

Hypothesis H1.1.

The integration of stakeholder engagement influences (positively) the organizational learning of cooperatives in times of a crisis.

Organizational learning is considered a capacity to generate innovative ideas, as well as a collective phenomenon that modifies the management of the envisaged situations [4]. Moreover, the company can emerge from the crisis thanks to its resilience that will allow it to see the opportunity in the chaos, while applying creativity to the envisaged problems [30]. Thus, we propose the following hypotheses:

Hypothesis H2.1.

Organizational learning in times of a crisis has a positive effect on the organizational resilience of cooperatives in times of a crisis.

Hypothesis H2.2.

Organizational learning in times of a crisis positively enhances the social innovation of cooperatives in times of a crisis.

2.3. Organizational Resilience

Due to the nature of the impact that may occur after the crisis, the organization is forced to arm itself with dynamic capabilities to take advantage of the instability created by the event. These capabilities are considered the ability of the organization to reconfigure and mobilize a set of organizational resources in advance, in order to adapt and achieve the desired results in the face of the unpredictable situation imposed by the crisis. Dynamic capabilities allow the organization to be flexible, active and proactive, and to change the situation to its own advantage while maintaining a competitive advantage [7,31].

Through their various dimensions, dynamic capabilities are considered an integral part of resilience-enhancing antecedents [32]. Resilience is considered a multidimensional concept [33]. Resilience is a concept intimately related to the ability to regain balance after trauma [34]. Resilience thus involves the ability to overcome regular disruptions and the ability to adapt to turbulent environments [35,36].

In a similar vein, Weick and Sutcliffe (2007, 2015) identify the three interrelated and sine qua non capabilities for developing the organizational resilience necessary to overcome crises, and the resulting organizational changes: the ability to absorb the adverse effects of the crisis; the ability to bounce back from the devastating event; and the ability to adjust and learn [17,37]. On the one hand, building organizational resilience requires socially relevant stakeholder participation that relies on meaningful communication and social learning. Moreover building resilience requires the resilience of its stakeholders [38,39]. Thus, we propose the following hypothesis:

Hypothesis H1.2.

The integration of stakeholder engagement positively enhances the organizational resilience of cooperatives in times of a crisis.

2.4. The Social Innovation

Innovation can have a social dimension other than economic, called “Social Innovation”. This concept of social innovation consists of developing new solutions to newly detected or poorly met social needs [40,41].

Social innovation consists of the implementation of radical changes of products and services, with the objective of improving well-being [42,43].

Social innovation is a mechanism requiring the cooperation of different internal and external corporate actors [44] with the aim of generating new and inclusive solutions to address socio-economic challenges or preventing social problems [45]. In addition, social innovation builds organizational resilience [46,47].

Hypothesis H3.

Social innovation has a positive effect on the organizational resilience of cooperatives in times of a crisis.

3. Research Methodology

The research will follow a largely confirmatory perspective, with the objective of explaining the organizational resources that strengthen the organizational resilience of the cooperatives studied. As such, the development of the conceptual framework was developed from the literature review, obviously within the framework of CFA studies, allowing for the modeling of the measurement and structural model [48].

The study questionnaire was administered to a population consisting of social enterprises (mostly cooperatives) belonging to several sectors of activity (see

Table 2. Sector of activity of cooperatives and characteristics of respondents (N = 160).

	Frequency	Percentage
Handicraft	82	51.3
Agriculture	62	38.8
Services	5	3.1
Beekeeping	4	2.5
Aromatic plants	2	1.3
Tourism	2	1.3
Oil distillation	1	0.6
Education	1	0.6
Printing and advertising	1	0.6
Total	160	100
Characteristics of respondents	Frequency	Percentage
President	104	65.0
Member	31	19.4
Manager	22	13.8
Treasurer	2	1.3
General secretary	1	0.6
Total	160	100.0

) in the Fez-Meknes region of Morocco. A total of 160 responses were collected through the use of a paper questionnaire. Cooperatives were approached in a regional forum in Taza (city of the Fez-Meknes region) and another local forum in Taounate (city of the Fez-Meknes region). Data collection was conducted in November and December 2022.

From Table 2, we can see the heterogeneity of our sample. The cooperatives belong to various sectors of activity, mainly the craft industry with a percentage of 51.3%, followed by agricultural cooperatives with a percentage of 38.8%, while other cooperatives are scattered in other activities such as beekeeping, services, tourism, etc. The cooperatives in our study are therefore from several cities in the region of Fez-Meknes.

Our questionnaire consists of questions that revolve around the following variables: involvement and mobilization of actors, organizational learning in times of a crisis, organizational resilience and social innovation. We used a five-level Likert scale ranging from “1: Strongly disagree” to “5: Strongly agree”.

For the analysis of the research hypotheses, we used the structural equation modeling (PLS-SEM) method. PLS-SEM is considered the most suitable method for analyzing direct and indirect paths in causal research [49]. The statistical tool used was the SmartPLS-3 software to generate the CFA results, with the objective of facilitating solutions, while examining the hypothesized causal relationships between the different constructs in a complex structural model [50].

4. Results

4.1. Measurement Model

The verification of the research hypotheses using the PLS-SEM approach requires the assessment of the measurement model, in order to test both the validity and reliability of the items of our research model that we have developed under SmartPLS 3 (presented in Figure 2). This verification is done in two main steps, the first one to verify the convergent validity and the second one to verify the discriminant validity.

Evaluation of the measurement model requires testing the convergent validity of the measurement model, which begins with the assessment of factor loadings measuring the factor contribution of each item, with the goal of measuring the validity and the reliability of latent variables (Table 2) [51]. Factor loadings assess the contribution of each item in its own latent variable.

In the present study, we began by deleting measurement items with values below 0.50, although retaining items with factor loadings above 0.7 is desirable [50]. However, rather than automatically eliminating items below 0.70, it is appropriate to test whether the effects of deletion allow for a higher composite reliability or mean variance extracted (MVE) values relative to the recommended threshold [52]. Thus, all the items were retained.

We then assessed the convergent reliability of the model through two criteria, namely the composite reliability (CR) and the average variance extracted (AVE). Composite reliability is an internal reliability that allows us to judge the internal consistency of the measurement scales, knowing that the value of the composite reliability varies between 0 and 1 [53]. This test is considered acceptable when the value of this criterion is greater than 0.7 [54]. As for the average variance extracted (AVE), it is used to evaluate the way in which a latent theoretical construct explains the variance shared between a latent construct and the items that measure it [50]. Indeed, Fornell and Larcker (1981) and Chin (1998) [53,54] suggest that the AVE should be greater than 0.50 for a measure to be considered reliable, i.e., at least 50% of the variance in the measure should be captured by indicators of the construct. Indeed, the convergent validity of our model is acceptable because the composite reliability is above 0.7 and the AVE is above 0.5.

Table 3. The convergent validity (measurement model).

	Code	Factor Loadings	Composite Reliability	Average Variance Extracted (AVE)
Involvement and mobilization of actors	IMA5	0.732	0.821	0.535
	IMA7	0.723
	IMA8	0.736
	IMA9	0.735
Organizational learning in times of a crisis	OLTC4	0.877	0.792	0.563
	OLTC6	0.637
	OLTC7	0.719
Organizational resilience	OR1	0.715	0.814	0.523
	OR2	0.761
	OR6	0.737
	OR8	0.676
Social innovation	SI10	0.951	0.911	0.729
	SI11	0.943
	SI8	0.506
	SI9	0.931

Source: SmartPLS 3 release.

presents “the construct reliability and validity”.

Discriminant validity in the PLS approach represents the extent to which the items in one construct differ from items in another construct in the model. The logic of this test is based on the idea that a construct shares more variance with its associated indicators than with the indicators of any other construct. In this logic, we assessed discriminant validity using three tests: the Fornell–Larcker criterion [54], the cross-loading, and the HTMT.

The first test is the Fornell–Larcker criterion [54], which consists of comparing the square root of the AVE with the correlations between the constructs of the model. In fact, the square root of the AVE must be greater than the highest correlation of one construct with another. In practice, this amounts to checking that the diagonal elements have a greater value than the off-diagonal elements. Therefore, the Fornell–Larcker criterion is met (see

Table 4. Fornell–Larcker criterion.

	IMA	OLTC	OR	SI
Involvement and mobilization of actors	0.731
Organizational learning in times of a crisis	0.316	0.751
Organizational resilience	0.375	0.406	0.723
Social innovation	0.235	0.369	0.407	0.854

Source: SmartPLS 3 release.

).

The second criterion is the examination of cross-loading.

Table 5. Cross-loading.

	IMA	OLTC	OR	SI
IMA5	0.732	0.321	0.432	0.240
IMA7	0.723	0.103	0.128	0.055
IMA8	0.736	0.160	0.112	0.124
IMA9	0.735	0.162	0.115	0.130
OLTC4	0.279	0.877	0.407	0.460
OLTC6	0.285	0.637	0.176	0.015
OLTC7	0.160	0.719	0.255	0.166
OR1	0.255	0.253	0.715	0.239
OR2	0.351	0.354	0.761	0.302
OR6	0.200	0.261	0.737	0.391
OR8	0.264	0.295	0.676	0.234
SI10	0.288	0.324	0.398	0.951
SI11	0.269	0.315	0.392	0.943
SI8	-0.059	0.261	0.152	0.506
SI9	0.210	0.360	0.389	0.931

Source: SmartPLS 3 release.

shows that all factor loadings for all items are greater than their cross-loadings, which is the verified discriminant validity [55].

Finally, we tested for discriminant validity using the heterotrait–monotrait ratio of the correlations (HTMT).

Table 6. Heterotrait–monotrait ratio (HTMT).

	Involvement and Mobilization of Actors	Organizational Learning in Times of a Crisis	Organizational Resilience	Social Innovation
Involvement and mobilization of actors
Organizational learning in times of a crisis	0.317
Organizational resilience	0.362	0.536
Social innovation	0.230	0.390	0.508

Source: SmartPLS 3 release.

shows that all values are below the recommended threshold of 0.85 [55].

Following the three tests we conducted, the discriminant validity of our model is established.

4.2. Structural Model

We then proceeded to evaluate the structural model after verifying the reliability and validity of the measurement scales by evaluating the measurement model. The structural model reflects the hypothetical paths between the latent variables—the constructs—of the model. The evaluation of the structural model goes through a series of steps, starting with the evaluation of the “coefficient of determination R²”, then the “indirect effect F²”, then the “predictive relevance Q²”, then the “Goodness of Fit (GoF)” and finally “the significance of paths”.

The quality of the model is determined by the strength of each structural path determined by the coefficient of determination R², which represents the proportion of variation in the dependent endogenous variables that can be explained by one or more independent exogenous variables [52]. In addition, the R² value should be equal to or higher than 0.1 [56].

From Table 6, the R² value for the model constructs of organizational resilience, organizational learning and social innovation are greater than 0.10 [52,56].

The Q-squared denotes the predictive relevance of the endogenous variables, which must be greater than zero to be considered good.

Table 7. The coefficient of determination R² and the predictive relevance Q².

	R2	Q2
Organizational learning in times of a crisis	0.100	0.054
Organizational resilience	0.292	0.133
Social innovation	0.136	0.081

Source: SmartPLS 3 release.

shows that the Q2 for all endogenous variables is greater than zero [57], hence the predictive relevance of the model is established.

In addition, we checked the fit of the model using the Goodness of Fit (GOF) criterion. Tenenhaus, Vinzi, Chatelin and Lauro (2005) defined the GOF as the measure of the overall fit. The purpose of the GOF is to take into account both the measurement model and the structural model, with a focus on overall performance [58].

The formula for calculating the GoF is as follows:

$$\mathrm{GOF}=\sqrt{\overline{{\mathrm{R}}^2}*\overline{\mathrm{AVE}}}$$

Table 8. The model fit using the GOF.

	R2	AVE	GoF
Involvement and mobilization of actors		0.535
Organizational learning in times of a crisis	0.100	0.563
Organizational resilience	0.292	0.523
Social innovation	0.136	0.729
The sum	0.528	2.350
The mean	0.176	0.588
			0.321

Source: Based on SmartPLS 3 results.

shows that the GOF is a value of 0.321. This value is judged according to Wtezels, Odekerken-Schröder and Van Oppen (2009) as “Medium”, since it is between 0.25 to 0.36. We can conclude that the GOF model in the study is sufficient for the validity of the PLS model.

4.3. Path Coefficient

In order to better evaluate the quality of the adjustment, we proceeded to measure the influence between the latent variables, using the path coefficients (or standardized partial regression coefficient) [59]. On the other hand, we proceeded to the verification of the significance of the hypothetical relations between the latent variables of our structural model with the help of Student’s test, and we used the probability associated with Student’s test to determine a possible significance.

For Hypothesis H1.1, the results revealed a positive effect on the involvement and mobilization of actors on the organizational learning in time of a crisis (β = 0.316, t = 3.153, p-value = 0.002). Therefore, Hypothesis H1.1 is confirmed.

Hypothesis H1.2, that “the involvement and mobilization of actors” has a positive influence is significant on the variable, the organizational resilience (β = 0.239, t = 2.835, p-value = 0.005) is verified. This means that when “the involvement and mobilization of actors” increases, the organizational resilience variable increases similarly.

The results revealed that the organizational learning in time of a crisis has a positively significant influence on the organizational resilience (β = 0.233, t = 2.513, p-value = 0.012) and the social innovation (β = 0.369, t = 2.839, p-value = 0.005). Thus, Hypotheses H2.1 and H2.2 are confirmed.

The results of Hypothesis H3 revealed the presence of a positive influence of social innovation on organizational resilience (β = 0.265, t = 3.277, p-value = 0.001). Hypothesis H3 is therefore supported.

The results of the path coefficients are presented in

Table 9. Test the hypothetical relationships of the research.

Hypotheses		Original Sample (β)	T-Statistics	p-Values
H1.1	IMA→OLTC	0.316	3.153	0.002
H1.2	IMA→OR	0.239	2.835	0.005
H2.1	OLTC→OR	0.233	2.513	0.012
H2.2	OLTC→SI	0.369	2.839	0.005
H3	SI→OR	0.265	3.277	0.001

Source: Based on SmartPLS 3 results.

and in Figure 3.

The figure below shows the verified hypothetical relationships.

5. Discussion

In this research, we were able to examine the relationship between a set of organizational resources—referencing Barney’s 1991 [10] resource theory—and their role in building organizational resilience during a crisis. We used the variable “actor involvement and mobilization” as an independent variable, a cornerstone in understanding a crisis [17], to clarify the role of internal and external actors in building organizational resilience. The following results were obtained:

(1)

In a complex and unstable environment, actor involvement and mobilization have a positive and significant influence on the organizational resilience variable. This result is coherent with our initial expectations and with the prior research literature that assumed stakeholder involvement necessary to build organizational resilience [38,39].

(2)

The positive effect of stakeholders’ involvement and mobilization on organizational learning in times of a crisis. Prior literature assumes that stakeholder involvement is a factor that enhances organizational learning in times of a crisis, especially if the firm engages in multi-stakeholder networks, relational engagement focused on deliberating complex problems and challenges with stakeholders, which facilitates learning [29,60,61,62,63].

(3)

The presence of a positive influence of organizational learning in times of a crisis on social innovation. Previous literature assumes the importance of organizational learning in acquiring the knowledge needed in the process of social innovation, and that its success requires the cooperation and collaboration of stakeholders [4,17,44,64].

(4)

The results revealed that organizational learning in times of a crisis has a positive effect on organizational resilience. Previous literature assumes that organizational learning is necessary for organizational resilience [4,30,37].

(5)

The results revealed a positive effect of social innovation on organizational resilience, this being consistent with previous literature assuming that social innovation is a primary component for building organizational resilience. This is through the generation of new ideas, allowing for adaptability, flexibility and learning capacity in the face of complex problems being considered [46,47,65].

In sum, these results suggest that the acquisition of organizational resilience for social enterprises, specifically cooperatives in the Fez-Meknes region, requires a number of organizational resources, namely the involvement and mobilization of internal and external actors of the cooperative, organizational learning in times of a crisis and strengthening social innovation through the satisfaction of unmet and poorly met needs.

6. Conclusions

For this study, we constructed and empirically tested a research model, of which the data were collected through a printed questionnaire administered to 160 cooperatives in the Fez-Meknes region. At the end of this study, we were able to identify that stakeholders’ involvement and mobilization, organizational learning and social innovation are considered essential organizational resources for strengthening the organizational resilience of the Moroccan cooperative.

The novelty of this study lies in the identification of factors that strengthen the organizational resilience of cooperatives in the Moroccan context. The results showed a positive and significant impact of the involvement and mobilization of actors on organizational learning in times of a crisis. The study also showed a positive and significant influence of the involvement and mobilization of actors on organizational resilience. In addition, organizational learning in times of crisis has a significant positive influence on both social innovation and organizational resilience.

From our results, the implications of our study are as follows:

Theoretical: We provided empirical evidence reinforcing the findings of previous studies regarding the importance of stakeholders’ involvement in organizational learning and social innovation in the face of devastating events, to build resilience [4,17,26,29,38,39,46,47].

Practical: Social enterprises need to strengthen their organizational resilience through a good relationship with their stakeholders, which is likely to facilitate crisis sensemaking and detect poorly or unmet needs, thus strengthening learning in times of a crisis. This will have a positive effect on social innovation.

Policy: Because of the importance of stakeholders’ involvement in building cooperative resilience, governments can mobilize (local) stakeholders by promoting communication and information exchange through the organization of forums, trade shows, scientific events (seminars and conferences) facilitating the emergence of new coalitions of stakeholders [65], or even the development of partnerships between universities and cooperatives by creating clusters [66,67,68]. Thus, the government can define a public policy based on dynamism, flexibility and adaptability by promoting social innovation that enables an improved economic and social performance [65,69,70,71].

Our study is relevant to Moroccan cooperatives in their management of unpredictability, but it has limitations that prevent the generalization of the results, since we chose a convenience sample to be limited to the Fez-Meknes region. Indeed, other exogenous variables could have been considered in the research model as antecedents of the organizational resilience the cooperatives surveyed, among others, the personality traits of the leaders, the human potential, the management of skills and knowledge, the management control system, the commitment and ethical alignment, the organizational communication adopted in times of a crisis and the nature of organizational resilience being active or passive [72]. However, considering the following limitations, future research directions should be explored:

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The role of the management control system in strengthening the organizational resilience of the social enterprise;

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The role of organizational communication in strengthening the organizational resilience of the social enterprise;

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The psychological resilience of the entrepreneur as a factor in strengthening the organizational resilience of the social enterprise.