Introduction

People with disabilities are a large group with significant difficulties entering the labor market and with a high risk of poverty and social exclusion. In the European Union, for example, the unemployment rate for disabled individuals in 2018 was 18.6%, compared to 8.8% for those without disabilities (Grammenos, 2020). These figures were worse in the case of Spain, where in 2020, the unemployment rate of the disabled (22.2%) was 6.8 points higher than that of the non-disabled (15.4%). The Strategy for the Rights of Persons with Disabilities 2021–2030 (European Commission, 2021) points out the importance of quality employment for this group to have dignified and independent lives, as well as the role that the Social Economy (SE) plays in offering them employment opportunities.

Sheltered Workshops (SWs), called Special Employment Centers (SECs) in Spain, are companies specifically established to offer employment opportunities to individuals with disabilities. These centers aim to help individuals transition into the mainstream labor market while also providing personal and social services to this group (Díaz et al., 2020). An SW is a kind of Work Integration Social Enterprise (WISE), and, hence, is part of the SE (Savall Morera et al., 2022). In Spain, SWs operate across various economic sectors to both public authorities and private clients, and at least 70% of workers must have at least a 33% degree of disability.

Research highlights SWs as central to active socio-labor integration policies, especially in the sheltered employment model, which has gained growing demand (Savall Morera et al., 2022). Notably, in 2020 in Spain, SWs were responsible for generating 75.5% of employment contracts for individuals with disabilities (ODISMET, 2020).

Spanish SWs operate under varying legal statuses, either as for-profit (FP) or non-profit (NP) entities. NP centers reinvest profits to further their social missions, while FP centers focus on maximizing shareholder returns and incentives and subsidies for hiring people with disabilities.

Historically, SWs have demonstrated robust capabilities to address social challenges, showing resilience in times of economic hardship and a greater capacity to withstand crises (Stiglitz, 2009; Birchall, 2013; Bretos and Morandeira, 2016; Calderón and Calderón, 2012; Bandini et al., 2023). As these entities often benefit from substantial government support incorporated into their budgets, they are required to prove their efficiency, profitability, and viability, and to assess the impact of their economic and social missions. However, reliance on public funding poses sustainability risks, particularly highlighted during financial crises such as the sovereign debt and COVID-19 crises, which have put a strain on public spending and have forced funding sources to be diversified to maintain service provision (López-Arceiz et al., 2017; Díaz et al., 2020; Bouchard and Rousseliere, 2016).

This research, rooted in resource-based (RB) theory (Barney, 1991; Barney et al., 2011), explores the unique internal characteristics and resources of firms as drivers of profitability, proposing that these factors are more influential than general sectoral ones. SWs possess a combination of financial and non-financial resources, both tangible and intangible. This perspective is especially innovative within the context of SWs, due to their requirement for a varied array of operational resources to fulfill their multiple financial and social objectives (Amran et al., 2023).

Empirical investigations analyzing the determinants of profitability in social enterprises are rather scarce (Magnanelli et al., 2016; Asmalovskij et al., 2019; Jace and Maroudas, 2021), particularly for SWs. The few studies that exist have primarily analyzed economic and financial dimensions with ratio analysis and did not encompass significantly disruptive periods, such as that of the COVID-19 pandemic (Gelashvili et al., 2016; Segovia-Vargas et al., 2021; Monzón-Campos and Herrero-Montagud, 2016). The only paper analyzing factors that conditioned the financial viability of Spanish SWs highlighted that factors like age, size, sales growth and financial risk were crucial for their profitability to be understood, which notably declined in post-crisis years (Gelashvili et al., 2022).

The literature emphasizes that poor management in social enterprises is a frequent cause of financial failure (Meadows and Pike, 2010; O’Hara and O’Shaughnessy, 2021), suggesting an underexplored link between management efficiency and profitability. Regarding the relationship between social efficiency and profitability, Bellostas et al. (2016) and Stevens et al. (2015) found that in social enterprises, there is an inverse relationship between the two, a complex dynamic that this study aims to explore further.

No existing studies have utilized data envelopment analysis (DEA) to measure operational and social efficiency and examine its relationship with profitability in social enterprises, neither is there any research that has investigated the impact of legal form (profit or non-profit) and COVID-19 on profitability.

Our study addresses these gaps by studying 1133 Spanish SWs over a decade, from 2010 to 2020, employing a mixed-methods approach that includes DEA, a static panel data model (random effects) and a dynamic panel data model (GMM system). This methodology provides a robust analysis of the efficiency–profitability nexus in SWs, guiding their operational dynamics and strategic decision-making, as well as promoting sustainable growth in the sector.

This study makes several significant contributions to the literature on SWs. Firstly, it theoretically clarifies the nature, functions, and impact of SWs, providing a deeper understanding of these entities. Secondly, it assesses the economic-financial situation of SWs based on their orientations, namely either FP or NP, adding a more comprehensive analysis to the existing literature by measuring the aspects of both their financial and social efficiency, often overlooked in studies of social enterprises. Thirdly, this body of research analyzes the main determinants of profitability and the effect that efficiency has on it, considering the impact of the global financial crisis and COVID-19. This feature is particularly novel, as no previous research has analyzed the effects of efficiency or the COVID-19 pandemic on the profitability of SWs under different legal forms. Moreover, the study expands on the direct impact of efficiency on profitability and explores how this effect might be moderated by factors such as legal form and the COVID-19 crisis. Additionally, it considers various internal and external elements that may affect profitability.

The empirical results demonstrate that both financial and social efficiency are strongly related to SW profitability. The positive effect of operational efficiency is much higher than the negative effect of social efficiency, so the effect of overall efficiency is positive on profitability. SWs have successfully managed to balance their social and economic objectives, effectively serving the needs of individuals with disabilities while maintaining financial viability.

The global financial and COVID-19 crises have significantly impacted SW performance, albeit less dramatically than in other sectors of the Spanish economy. This resilience underscores the growing importance of SWs supporting individuals with disabilities during ongoing economic uncertainty. Financially efficient companies reported the highest returns during the COVID-19 pandemic, yet the for-profit legal status did not significantly influence profitability during these times.

This study offers comprehensive guidelines for enhancing public policy and legislative frameworks as support for SW growth, especially for NPs, in recognition of their critical societal role. This includes tax breaks, subsidies, grants, and training programs. Strategic use of public procurement, facilitating financial assistance, providing consultancy services, and offering business and management training are essential and so are fostering network connections and collaborations between SWs, conventional enterprises, government agencies and other social enterprises.

Additionally, by identifying key profitability determinants, this body of research equips SWs with the knowledge to improve operational performance and make informed decisions. Such information empowers SWs to be more accountable to their governments, investors and other stakeholders, while also enabling them to acknowledge their successes and shortcomings in terms of the social and economic value created.

The structure of this paper is outlined as follows: section “Theoretical background” details the theoretical framework and hypothesis development; section “Research methodology” outlines the research design, including the sample and empirical specifications; section “Empirical results and discussions” presents the empirical findings; and section “Conclusion” offers conclusions and suggestions for future research.

Theoretical background

Sheltered Workshops: dual objective and crises

There is extensive literature pointing out the advantages of SWs for integrating people with disabilities into their workforces (among others, Bellostas et al., 2016; Díaz et al., 2020; López-Arceiz et al., 2014). Among the criticisms of the results produced by these centers, other authors state that workers with disabilities are often segregated into these so-called “finalist” centers. Although they have been conceived as a transition formula towards the ordinary employment regime, they have been used as an alternative measure for the disabled so that companies with more than 50 workers meet the “reserve quota”; additionally, the jobs on offer are of lower quality than ordinary ones (López and Seco, 2005; Rodríguez Álvarez, 2012).

Another controversial aspect is the legal status of SWs. NP SWs may obtain profits, but these are primarily reinvested to support their social mission, with a primary emphasis on creating social value. In contrast, FP SWs focus more on maximizing profits with incentives and subsidies for hiring people with disabilities, aiming to distribute them among their owners and reinvesting them only when they believe that this will improve results in the following years. These differing outlooks are reflected in the types of disabled people hired, with NP SWs focusing more on those with greater disabilities who are more likely to have trouble integrating into the labor market (Santos Jaen et al., 2021).

Law 5/2011 on Social Economy considers all Spanish SWs to be Social Economy entities, without taking into account that the core principles (prioritizing people and social objectives over capital and reinvesting earnings into social programs) need to be followed. These requirements only apply to NP SWs and some authors (Lorenzo, 2019; García Sabater, 2019; Moratalla Santamaria, 2016) propose that only NP SWs, today known as “social initiative centers”, should be regarded as Social Economy entities.

In Spain, the term “Social Economy” has been used instead of “Social Enterprise” for a very long time, the former of which has no explicit regulation. However, its principles (Law 5/2011) are in accordance with the EU definition of “social enterprise”, and this law has become the legal framework for these businesses in Spain. They are considered hybrid companies that move along a continuum, at the extremes of which are non-profit organizations, characterized by an exclusive social vision, and traditional for-profit companies, which typically make profit-making their priority (Popoviciu and Popoviciu, 2011; Muñoz and Kimmitt, 2019).

The debate around hybrid enterprises, which balance social and economic missions, centers on whether their orientations are in tension or whether they complement each other harmoniously (Dorobat et al., 2024). Research shows that such enterprises can be economically sustainable, efficient, and capable of redistributing economic resources effectively (Santos et al., 2015). However, balancing these dual missions can lead to internal conflicts. A focus that leans too heavily on economic objectives can lead to “mission drift,” as highlighted in studies of hybrid enterprises (Battilana et al., 2012). Conversely, prioritizing the social mission at the expense of economic performance may compromise financial sustainability, potentially jeopardizing the social mission as well (Santos et al., 2015). Staessens et al. (2019) note that in a sample of SWs, there is a risk of “mission blockage,” where an overemphasis on social goals at the expense of economic ones prevents improvement in either area over time.

The lack of sustainable funding is one of the major factors in the failure of social enterprises, leading them to seek unsubsidized income to survive (Phillips, 2006). It is increasingly important for Social Economy enterprises, and in particular SWs, to generate diversified income to allow them to combine the resources obtained from their economic activity, thus avoiding over-dependence on public subsidies, which are largely used to support the employment of disadvantaged people (López-Arceiz et al., 2017; Díaz et al., 2020; Bouchard and Rousseliere, 2016).

So far in the 21st century, there have been two serious economic and social crises with different roots. Between 2008 and 2014, Spain went through an employment crisis, derived from the international financial collapse and the real estate bubble. Similar to other regions around the globe, the COVID-19 crisis has profoundly impacted the Spanish economy. GDP contracted by 11.20% on average in 2020 (INE, 2023), one of the highest falls in developed countries (the average for the Eurozone being 6.8%).

With this in mind, the question arises as to how Social Economy organizations have survived. In general, the literature points to their strength as leaders for improvement in the arena of social welfare and stable employment and are therefore considered organizations that have the ability to tackle any social problems that may arise from crises (Stiglitz, 2009; Birchall, 2013). These enterprises also better withstand such downturns (Bretos and Morandeira, 2016; Calderón and Calderón, 2012), during which time employment falls less than in the rest of the economy (Cancelo et al., 2022; Juliá et al., 2022; CEPES, 2020).

Despite this, the growth trends of the Social Economy have been cut short as a consequence of the COVID-19 crisis (Juliá et al., 2022). Fiorelli and Gafforio (2020), according to the results of a survey to find out the impact of this crisis on 274 Social Economy enterprises in Europe, have pointed out that some of the most affected sectors in terms of unemployment tend to be found in SWs.

In Spain, compared to the general population, the work situation of people with disabilities has been severely affected by COVID-19. One example of this is that the rate of those on furlough in 2020 (37%) was much higher than for people without disabilities (3.1%). The explanation lies in the type of employment that predominates in the group, that is, its connection to the services industry, which incorporates customer services, hospitality and commerce (ODISMET, 2020). Therefore, as it is a unique scenario, it allows for an opportunity to study its impact on SWs as well as that of the 2008 financial crisis.

Literature review and hypothesis development

The long economic and financial crisis that began in 2008 and the COVID-19 pandemic most recently have led to the disappearance of numerous companies. Thus, not only the importance for economic agents to be aware of the factors that might influence the economic success of businesses but also the scarcity of literature in this regard, have persuaded us to write this paper and explore a model that analyses the determinants of profitability in SWs.

Financial economic situation: effects of COVID-19

Some of the available empirical analyses on SWs in Spain have concentrated on examining their economic and financial health through ratio analysis, which has been shown to be important predictors of the financial health of a company (Wang and Guedes, 2024).

Gelashvili et al. (2016), Segovia-Vargas et al. (2021) and Monzón-Campos and Herrero-Montagud (2016), who have analyzed all SWs in Spain, are noteworthy studies on this topic. Other empirical studies have focused on various Spanish autonomous regions (López-Arceiz et al., 2014; Manzano Martín et al., 2016; Redondo and Martín, 2014; Gelashvili et al., 2020; Santos Jaen et al., 2021; López-Penabad et al., 2019, 2020). Their results have shown that they are companies with a solid financial position, with high levels of solvency and liquidity, albeit with low returns, that their main source of financing is equity and that they borrow mainly in the short term.

None of the abovementioned studies cover the COVID-19 period, while others, which do not specifically refer to SWs, do incorporate it. Blanco et al. (2020) analyzed the pandemic’s impact on the financial situation of Spanish non-financial firms in 2020, concluding that, as expected, their financial situation and in turn their solvency margin, deteriorated; this as a result of the increase in indebtedness, the corresponding financial burden and the fall in performance (when more than half of the firms, 55% to be precise, were making losses).

After reviewing the existing papers, a preliminary aim of our study is to assess the economic and financial evolution of both FP and NP SWs from 2010 to 2020. In addition, the aftermath of the COVID-19 pandemic is taken into account.

The link between efficiency and profitability

Profitability stands as a crucial variable for assessing enterprise performance and ensuring long-term survival (González et al., 2002; Gelashvili et al., 2022). Social enterprises need to be profitable in order to build social contributions sustainably. If companies do not generate enough revenue to cover their costs or make a profit, they eventually disappear. Moreover, the bankruptcy of a social enterprise has greater implications than that of a traditional one since, in addition to employees and investors, its potential beneficiaries are also affected.

When analyzing the connection between organizational resources and the performance of social enterprises, it is imperative to acknowledge the significance of resource-based (RB) theory (Barney, 1991; Barney et al., 2011). This theoretical framework emphasizes the importance of internal resources, such as tangible assets, human capital and organizational processes, when the organizational performance of a firm improves.

Although there is a considerable amount of literature analyzing the determinants of profitability, it is scarce for social enterprises and, in particular for SWs. Previous literature identifies various economic and financial variables to evaluate the profitability of different types of social enterprises. These include solvency, liquidity, financial risk, leverage, sales growth, employee productivity, size, age, sector of activity, location, subsidies, and crises (Gelashvili et al., 2022; Magnanelli et al., 2016; Asmalovskij et al., 2019; Jace and Maroudas, 2021). Regarding the determinants of profitability for Spanish SWs, we are only aware of the paper of Gelashvili et al. (2022), which identifies key factors such as size, age, financial risk, and sales growth. Additionally, the financial crisis affected the profitability of these SWs, which notably declined in post-crisis years.

Terms such as profitability and efficiency are becoming more and more important, and the need to focus on these increases during crisis periods. The literature indicates that poor management is one of the primary causes of financial failure (Van Gestel et al., 2006; Yeh et al., 2010). In addition, some papers have warned of the risks that social enterprises face. Meadows and Pike (2010) pointed towards weak organizational capacity, poor financial performance, weak service development and the inability to show added social value as risks. More than 80% of social enterprises fail in their first 3 years due to lack of funding, operational issues, limited understanding of the business environment and limited access to sustainable resources (Gasca 2017a, 2017b). O’Hara and O’Shaughnessy (2021) have pointed out that WISEs encounter significant issues including an unstable financial resource framework, high costs for employee support, inadequate leadership and entrepreneurial skills, and limited ability to comply with regulations and showcase their social and economic impacts.

Although social enterprises have the fulfillment of social needs as their main objective, they should be considered from a management point of view as for-profit firms (Barraket and Yousefpour, 2013; Boschee, 2001; Meadows and Pike, 2010; Thompson and Doerthy, 2006), since they integrate the innovation, efficiency, and resources characteristic of traditional for-profit companies with the commitment, values, and missions of nonprofit organizations (Battilana et al. 2012). Hence, SWs are no strangers to this management requirement and must deal with additional challenges in the measurement of their dual objective, both economic and social, the latter of which can be difficult to quantify.

The relationship between economic efficiency and profitability has been studied very little (see Alarussi and Alhaderi, 2018) mainly in the banking sector. It is commonly believed that low efficiency within an organization indicates ineffective management, resulting in poor performance in competitive markets (Li et al., 2022; Lamothe et al., 2024; EL-Chaarani et al.,2023).

For efficiency estimation in this paper, the frontier estimation method, DEA was used. This approach incorporates both economic and social indicators, aspects that have been largely overlooked until now, particularly in Spain.

We are not aware of any paper that has used DEA to measure efficiency or analyzed its relationship with profitability in social enterprises. However, other studies have employed other accounting measures of economic efficiency (ratios) for SEs. Magnanelli et al. (2016) used return on sales (ROS), which is operating profit divided by net sales, as a proxy for efficiency, their findings indicating that it has a positive and highly statistically significant effect on ROA (profitability). Asmalovskij et al. (2019) have shown that there is a significant positive correlation between profitability and employee productivity. They have also found that economic efficiency is significantly and positively associated with profitability.

Regarding the relationship between social efficiency and ROA, Bellostas et al. (2016), in a sample of 118 SWs in Spain, analyzed the total value created by combining social and economic outcomes. Their findings revealed a strong dependency between these values, which was not bidirectional; it was necessary to prioritize either social or economic value within the business strategy, as pursuing both simultaneously was not feasible. Mori and Sakamoto (2018) studied the relationship between hiring people with disabilities and its effect on a firm’s profit rate, noting that the impact was lower than expected. The decrease in profits from employing disabled people only occurs if disabled workers are paid more than they produce, which is influenced by factors such as the productivity of disabled workers, type of employment, subsidies and grants, and priority systems in public tenders.

Taking the measure of social efficiency into account, it has been considered that the most socially efficient SWs, i.e., those that employ the highest number of disabled workers for a given level of inputs, on the contrary, have the lowest margins and the lowest profitability, as part of the results are used for higher wages, training and/or recruitment. Consequently, the first two hypotheses of the study are as follows:

Hypothesis 1: The level of operational efficiency is positively related to profitability.

Hypothesis 2: The level of social efficiency is negatively related to profitability.

The mediating role of legal form (FP)

A moderating variable can alter how an independent variable affects a dependent one, influencing either the direction or the strength of the relationship. By introducing this variable, we gain a clearer understanding of the interaction between the two primary variables. This moderation might result from specific individual characteristics or contextual factors that change how these variables interconnect.

An interesting question is whether efficiency influences profitability differently in FPs and NPs. For a range of SWs in Spain, López-Penabad et al. (2019, 2020) and Monzón-Campos and Herrero-Montagud (2016) have pointed out that NP SWs achieve lower returns (ROE and ROA) compared to FP ones. This suggests that economic profitability may not be their primary objective, but rather is subordinate to their social mission. Battilana et al. (2015) said that economic productivity tended to be low in non-profit French WISEs in the period 2003–2007. Magnanelli et al. (2016) found that their legal status, i.e., that they are cooperatives and less profit-oriented has a negative and statistically significant effect on the financial performance of social enterprises, which means that pursuing profit is not their main goal, whereas in for-profit firms, it is. In a study of 166 SWs in the Region of Murcia for the period 2012–2016, other authors, such as Santos Jaen et al. (2021), have suggested that there is no direct effect of the legal statuses “for-profit” or “non-profit” on economic profitability.

In this paper, FP SWs are considered to be more economically oriented than NP SWs and a positive association is expected between the legal status “for-profit” and the profitability of SWs. For this reason, it has been hypothesized that the effect of efficiency on SW profitability varies more significantly for FPs (higher financial efficiency and lower social efficiency).

Hypothesis 3: The association between efficiency and profitability is more accentuated for FP SWs.

The mediating role of crisis (COVID 19)

Data related to SWs in Spain shows that during the financial crisis (2008–2014), these social enterprises managed to maintain jobs for disabled people (Manzano Martín et al., 2016). However, other studies have pointed out that many SMEs in Europe were affected by it (Kokocinska and Rekowski, 2013). Regarding its effects on profitability, Gelashvili et al. (2022) have found a negative and statistically significant relationship for the financial crisis in the ROA.

It would be of great interest to know whether the financial and COVID-19 crises conditioned the profitability of SWs. Being efficient is especially important in crisis periods, and the more efficient firms are, the more resilient they are to external shocks such as pandemics. The empirical literature suggests that the Social Economy has a greater capacity to withstand crises (Bretos and Morandeira, 2016; Calderón and Calderón, 2012; Bandini et al., 2023).

Therefore, it can be assumed that the impact of efficiency on SW profitability was strong during COVID-19.

Hypothesis 4: The positive relationship between efficiency and profitability was more significant during the COVID-19 pandemic.

Research methodology

Sample and data sources

Based on the list of Spanish SWs provided by the official register of the Spanish Public Employment Service, known as the Servicio Público de Empleo Estatal (SEPE), all existing Spanish SWs from 2010 to the end of 2020 were considered. The variables of interest were obtained from the SABI database (Iberian Balance Sheet Analysis System). Firms with missing values, as well as those with only one or two values were excluded.

The final sample comprised an unbalanced panel of 1133 SWs. There were a total of 8546 observations from different SWs (for-profit: 6476; non-profit: 2070) with all of the financial variables that we chose.

Empirical specification

In order to estimate the financial performance of Spanish SWs, a panel data model, defined below, was proposed:

$$\begin{array}{ll}{{{{ROA}}}}_{\rm{it}}=\alpha +{{{\upbeta }}}_{1}{{\rm{Effic}}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{2}{Z{{\_}}{{{ALT}}}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{3}{{{{LNTA}}}}_{{\rm{i}},{\rm{t}}}\\\qquad\qquad+\,{{{\upbeta }}}_{4}{{{{LNAGE}}}}_{{\rm{i}},{\rm{t}}}+\,{{{\upbeta }}}_{5}{{\rm{LQ}}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{6}{{\rm{TA}}}_{{\rm{i}},{\rm{t}}}+{{\upbeta }}_{7}{{\rm{LTL}}}_{{\rm{i}},{\rm{t}}}\\\qquad\qquad +\,{{\upbeta }}_{8}{{\rm{FP}}}_{{\rm{i}}}+{{\upbeta }}_{9}{{\rm{SEC}}}_{{\rm{i}}}+{{\upbeta }}_{10}{{\rm{LOC}}\_{\rm{TE}}}_{{\rm{i}}}\\\qquad\qquad +\,{\beta }_{11}{{\rm{COVID}}19}_{t}+{{{\updelta }}}_{{\rm{t}}}{{\rm{time}}}_{{\rm{t}}}+{{\upmu }}_{{\rm{i}}}\,+{{{\epsilon }}}_{{\rm{it}}}\end{array}$$
(1)

where \({{{\rm {ROA}}}}_{{it}}\) is a measure of the performance of a SWi in year t and \({{\rm{Effic}}}_{{i},{t}}\) is a measure of DEA efficiency; for the VRS model, the variables used were overall (VRSO), financial (VRSF) and social (VRSS); \({{\rm{Z}}\_{\rm{{ALT}}}}_{{i},{t}}\) is Altman’s Z-score, \({{\rm{{LNTA}}}}_{{i},{t}}\) is the logarithm of total assets, \({{{\rm{LNAGE}}}}_{{i},{t}}\) is the logarithm of the number of years that passed since a SWi had been founded, \({{\rm{LQ}}}_{{i},{t}}\) is the liquidity ratio, \({{\rm{TA}}}_{{i},{t}}\) is the fixed assets to total assets ratio and \({{\rm{LTL}}}_{{i},{t}}\) is the financial leverage ratio. The remainder is dummy variables: \({{\rm{FP}}}_{{i}}\) is equal to 1 if the SWi was for-profit and 0 otherwise; \({{\rm{SEC}}}_{{i}}\) is equal to 1 if the SW was in the services sector and 0 if it was in manufacturing; \({{\rm{LOC}}\_{\rm{TE}}}_{{i}}\) has a value equal to 1 if the SWi was located in an autonomous region with the highest rate of employment of people with disabilities and 0 otherwise; COVID-19 is equal to 1 for 2020, μi captures persistent cross-sectional heterogeneity that was not observed and εit is the random disturbance. \(\alpha\), \({{\beta }}{{\mbox{'}}}{\rm{s}}\) and \({{\delta }}{{\mbox{'}}}{\rm{s}}\) are the parameters which were to be estimated.

$$\begin{array}{ll}{{\rm{ROA}}}_{{\rm{it}}}=\alpha +{{\upbeta }}_{1}{{\rm{Effic}}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{2}{Z{{\_}}{ALT}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{3}{{LNTA}}_{{\rm{i}},{\rm{t}}}\\\qquad\qquad+\,{{{\upbeta }}}_{4}{{LNAGE}}_{{\rm{i}},{\rm{t}}}+\,{{{\upbeta }}}_{5}{{\rm{LQ}}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{6}{{\rm{TA}}}_{{\rm{i}},{\rm{t}}}+{{{\upbeta }}}_{7}{{\rm{LTL}}}_{{\rm{i}},{\rm{t}}}\\\qquad\qquad+\,{{{\upbeta }}}_{8}{{\rm{FP}}}_{{\rm{i}}}+{{{\upbeta }}}_{9}{{\rm{SEC}}}_{{\rm{i}}}+{{{\upbeta }}}_{10}{{\rm{LOC}}\_{\rm{TE}}}_{{\rm{i}}}\\\qquad\qquad+\,{\beta }_{11}{{\rm{COVID}}19}_{t}+{{\upbeta }}_{12}{{{\rm{Effic}}}_{{\rm{i}},{\rm{t}}}\times {\rm{FP}}}_{{\rm{i}}}{+{{\upbeta }}}_{13}{{{\rm{Effic}}}_{{\rm{i}},{\rm{t}}}\times {\rm{COVID}}19}_{{\rm{t}}}\\\qquad\qquad+\,{{{\updelta }}}_{{\rm{t}}}{{\rm{time}}}_{\rm{t}}+{{{\upmu }}}_{{\rm{i}}}+{{{\epsilon }}}_{\rm{it}}\end{array}\,$$
(2)

Equation (2) includes an interaction term between the variables \({{{\rm{Effic}}}_{{i},{t}}\times {\rm{COVID}}19}_{{t}}\) to examine whether the positive effect of efficiency was stronger during the pandemic. In addition, an interaction term between the \({{{\rm{Effic}}}_{{i},{t}}\times {\rm{FP}}}_{{i}}\) was included to analyze whether the positive effect of efficiency was more accentuated for-profit SWs.

Firstly, the estimation method used in the static panel was generalized least squares (GLS) (random effects). When the explanatory variables are not strictly exogenous and they are correlated with the error term, it is necessary to estimate using the system GMM, proposed by Arellano and Bover (1995) and Blundell and Bond (1998). This choice is based on preventing endogeneity problems, reverse causality, and considering the persistence of dependent variables.

To check for possible problems of multicollinearity between the independent variables of the study models, we calculated the correlation matrix (Pearson’s coefficients) and the variance inflation factor (VIF). In this study, the correlations between the independent variables and the VIF were low, so there is no multicollinearity.

Measures

Taking into account previous literature, we proposed a theoretical model to analyze both the internal and external factors that contribute to the profitability of a SW. The following internal elements that characterize this type of company were considered: firm management measured in terms of efficiency, risk distress, liquidity, leverage, tangibility, size, age and legal status. External factors were also considered, such as the sector of activity and the geographical area in which it operated (see Fig. 1).

Fig. 1: Framework of the study.
Fig. 1: Framework of the study.
Full size image

Source: Own elaboration.

The dependent and independent variables considered in our analysis are shown in the table below (Table 1), where, in addition to the names, abbreviations, explanations and expected signs, previous papers on which each of the variables were based and source of data are listed.

Table 1 Definition of variables.
Full size table

The dependent variable

Following Sanchis-Palacio et al. (2013), Retolaza et al. (2014), Gelashvili et al. (2022), Magnanelli et al. (2016) and Asmalovskij et al. (2019), among others, return on assets (ROA) was chosen as a proxy for profitability. ROA is calculated as net income divided by average assets. It shows the capacity of a company to generate profits as a result of using assets productively and the efficiency of its management in using them.

Independent variables

For efficiency estimation in this paper, the frontier estimation method, data envelopment analysis (DEA) was used. This methodology, which considers the constant returns-to-scale (CRS) hypothesis, was first proposed by Charnes et al. (1978), and Banker et al. (1984) introduced a new model of variable returns-to-scale (VRS). The election of inputs and outputs is crucial for DEA methodology, so the following efficiency indicators, based on prior literature in the field of SEs and non-profit entities, were selected: for input variables, fixed assets, total liabilities, total equity and operating costs; for the outputs, operating revenue, which is a classic measure of economic output. In SWs, in addition to operating revenue, a very significant item is what is known as “other operating revenue”, since it includes operating subsidies, which are mainly for maintaining jobs (salary cost subsidies) and is quantitatively the most important financial aid in this type of entity. As for the measurement of social value, the absence of standardized values and limited data availability for such companies meant that it was necessary to make use of the quantifiable indicators for the whole sample, in particular, those collected in similar literature, based on the fulfillment of their main social mission, namely, the professional integration of disadvantaged workers via employment (Staessens et al., 2019; López-Penabad et al., 2020, 2021; Lee and Seo, 2017). Social efficiency specifically evaluates how efficient decision-making units are in terms of their social outcomes or the impact that they have, and should not be considered purely economic or financial measures. It is used to assess how well organizations or entities utilize their resources to achieve social objectives, i.e., in contributing to job creation for disadvantaged employees.

The suggested models met the isotonicity requirement, which stipulates that inputs must increase and that outputs must not decrease, since the coefficient association is statistically significant and positive between outputs and inputs. The input and output combinations with Spearman’s rank correlation coefficients < 0.9 were utilized (Lee and Seo, 2017).

Moderating variables

The study does not only focus on the direct impact of efficiency on the profitability of SWs, but it also enriches previous literature by exploring whether this effect may be moderated by factors such as legal form (profit or non-profit) or the COVID-19 crisis.

We included several dummy variables, one to control for potential differences in the legal form (FP being equal to 1 when an SW was an FP and 0 if it was an NP) and another one for the COVID-19 crisis (COVID-19 being equal to 1 for 2020 and 0 otherwise).

Control variables

The study also used a set of control variables for firm-specific characteristics that might impact the profitability of SWs.

Financial risk (Z Altman)

One variable to be analyzed was the effect of financial risk on profitability. Altman’s Z-score (1968) model is one of the most popular financial risk models due to its combination of five key financial ratios, which was adjusted over time and adapted to non-listed companies:

$${Z}{\mbox{-}}{\rm{score}}\!\!:0.717X1+0.847X2+3.107X3+0.42X4+0.998X5$$

where X1 = working capital/total assets; X2 = retained earnings/total assets; X3 = earnings before interest and tax/total assets; X4 = book value of equity/total liabilities; X5 = sales/total assets.

The result of this equation made it possible for three SW groups to be established: the first one, “Distress” (Z-score below 1.23), meant entities with a high possibility of becoming insolvent; the second, “Grey” (a score between 1.23 and 2.89), was where companies had a moderate chance of going bankrupt; the third, “Safe” (a score of 2.90 and above), referred to businesses which had a low risk of insolvency.

The empirical literature on non-financial companies and, in particular, on SEs is scarce, with the results pointing to a negative relationship between financial risk and performance. Z Altman is an inverse measure of risk, so if a firm is financially healthy (higher Z Altman), it has the capacity to increase its profitability.

Mushafiq et al. (2021), in a study about 69 non-financial companies from Pakistan’s Stock Exchange between 2012 and 2017, have remarked that Altman’s Z-score showed a positive relationship with financial performance. Along the same lines, in a sample of Spanish SWs, despite using another measure of financial risk, Gelashvili et al. (2022), have found a negative and statistically significant effect of financial risk (financial expenses/sales) on ROA. In a sample of 124,632 non-financial small and medium-sized enterprises (SMEs) from 10 EU countries, Li et al. (2019) pointed out that credit risk and leverage have a negative effect on profitability. Firms that experience the highest credit risk have the worst performance and the highest debt ratios. When a business’s financial health improves, its financial performance is expected to increase.

Liquidity (LQ)

Financial liquidity is measured by the current ratio, expressed as current assets divided by current liabilities, and indicates a company’s capacity to meet its current liabilities with its current assets. Regarding the effect of financial liquidity on profitability, the empirical literature has not yet reached a consensus. Lim and Rokhim (2020), Batrancea (2021), Ali et al. (2019) and Ahmed and Bhuyan (2020) have shown that the impact of the current ratio on ROA is positive in a range of sectors. Other authors, such as Santos Jaen et al. (2021), have concluded, in a sample of SWs in Spain, that an excess current ratio reduces profitability, and Raheman and Nasr (2007) pointed out that the current ratio has a negative and significant relationship with profitability. Other researchers, e.g., Gelashvili et al. (2022), have not seen evidence of a significant relationship being established between liquidity and profitability in Spanish SWs. Similar conclusions were reached by Alarussi and Alhaderi (2018) in Malaysian-listed companies.

Capital structure (LTL)

Another variable that is usually analyzed when studying profitability is capital structure, expressed by long-term debts to total liabilities (LTLs). In general, SWs have a capital structure in which they are not highly indebted, as most operate in the services sector and are, therefore, less capital intensive, lacking assets for collateral. In addition, limited liability is the legal condition of most companies. External financing is mainly composed of short-term debt derived from the delay in receiving subsidies (López-Penabad et al., 2019). The higher the values of the LTL ratio, the greater the financial strength, which allows for more confidence on the part of financial institutions and, therefore, higher financing capacity (Martínez-Franco and Guzmán-Raja, 2014).

Papers on social enterprise have indicated that LTLs positively affect profitability (Magnanelli et al., 2016) and efficiency (Martínez-Franco and Guzmán-Raja, 2014). Likewise, Weill (2008), in a study of 11,836 firms from seven European countries between 1998 and 2000, stated that LTLs were positively related to performance in Spain and Italy but negatively so in Belgium, France, Germany, and Norway, with no significance in Portugal. Ahmed and Bhuyan (2020), in a sample of 1001 firm-year observations over eleven years (2009–2019) of Australian stock market services sector firms, have commented on long-term debt and liquidity being positive and significant predictors of ROA. In general, these studies have suggested the positive effects of the use of long-term debt on ROA.

Tangibility (TA)

Another variable that may affect companies’ profitability is the structure of their assets (fixed assets/total assets). In general, social enterprises are characterized by a lower level of fixed assets, as most of them operate in the services sector. Previous literature has indicated a negative relationship between tangible assets and profitability. Gharaibeh and Bani Khaled (2020) analyzed the factors influencing profitability in a sample of 46 Jordanian services sector firms from 2014 to 2018. They have found that tangible assets have a significantly negative relationship with profitability. Nunes et al. (2009) examined the factors influencing profitability in a sample of Portuguese service companies. The results obtained showed that companies with lower levels of fixed assets were more profitable.

Firm size and age are the two most researched independent variables affecting firm performance.

Size (LNTA)

The logarithm of total assets was employed as a proxy for the size of an SW. While many studies suggest evidence of a relationship between size and ROA, the findings remain inconclusive. In social enterprises, Asmalovskij et al. (2019) and Gelashvili et al. (2022) have considered that size positively affects profitability. The literature has also found the same to be true in other types of companies (Alarussi and Alhaderi, 2018; Lim and Rokhim, 2020; Mushafiq et al., 2021). In spite of this, other papers have recorded there to be a negative relationship between the above, with diseconomies of scale for SEs (Battilana et al., 2015; Magnanelli et al., 2016) and European firms in the manufacturing and services sectors alike (Goddard et al., 2005). Considering the related literature and given the small size of the companies in our sample, it was expected that size would be positively related to profitability.

Age (LNAGE)

Age is defined as the natural logarithm of the number of years since a firm’s establishment. Dunne et al. (1989) discovered that a firm’s age plays an important role in its growth and performance. Younger organizations, whose internal routines have not yet sufficiently stabilized, tend to have lower profitability. Asmalovskij et al. (2019), Battilana et al. (2015), Magnanelli et al. (2016) and Bouchard and Rousseliere (2016) concluded that age positively affects profitability in social enterprises. Nevertheless, Gelashvili et al. (2022) and Alarifi et al. (2019) have stated that age has a negative and significant effect on them. SWs originate from non-profit organizations, which may lead to age negatively affecting profitability, since, among the oldest SWs, there is a higher percentage of non-profits, which have lower returns. Considering these aspects, we expected age to have a negative relationship with profitability.

External factors, such as the sector of activity of the SW and the geographical area of operation, were considered.

Sector (SEC)

Retolaza et al. (2007) showed that the viability of social integration companies depends on their sector of operation and geographic location. Magnanelli et al. (2016) indicated that the sectors in which social enterprises operate can present a varied range of significant positive or negative signs with profitability. However, for SWs in Spain, Gelashvili et al. (2022) have said that the services sector does not present significant coefficients regarding profitability. This variable is split into two groups, mainly because most SWs operate in the services sector (López-Penabad et al., 2019; Segovia-Vargas et al., 2021). This variable is equal to 1 if the SW operates in the services sector according to the NACE (Statistical Classification of Economic Activities in the European Community), and 0 otherwise.

Location (LOC_TE)

The geographical area where a social enterprise operates can affect its profitability. In Spain, there is a significant delegation of powers to regional governments affecting the status and potential activities of social enterprises. In the case of SWs, they may be regulated and promoted differently depending on the region. There are several reasons for these differences: the characteristics of the population, varying approaches within civil society and a regional government’s differing levels of support and regulations regarding social enterprises (Díaz et al., 2020). To control for location, the ratio of employment of people with disabilities divided by total regional employment was used, thus proxying the degree of SW activity in the area. It is equal to 1 if the firm operated in a regional government with among the highest rates of employment of people with disabilities, and 0 otherwise.

Magnanelli et al. (2016) indicated that territorial and socio-economic variables positively impact ROA. However, Gelashvili et al. (2022) have found no significant relationship between location and profitability.

It was expected that this higher employment rate would lead to higher levels of performance for SWs located in these regions.

Empirical results and discussion

Descriptive statistics and univariate analysis

This first analysis offers an initial overview of the economic and financial situation of the SWs. Tables I and II in Annex I indicate the descriptive statistics of SW variables after winsorizing extreme values at the 1% and 99% percentiles. To test the significance of the mean differences, we employed the Mann-Whitney non-parametric test. Broadly speaking, most of these companies operated in the services sector (64.39%), the tangibility of the assets had low values (36.19%), and NP SWs had a higher average asset value and age than FP SWs.

In terms of profitability, ROA and ROE reached average values of 4.1884% and 13.5964%, respectively, whereas the ratios were lower for NP SWs. This may indicate that profitability was not a target in itself but was subordinate to the social purpose. In the case of NP SWs, it is difficult to interpret the economic results, as part of the profits may have been distributed via wage increases or the hiring of new workers. Regarding the effects of COVID-19, in 2020 there was a significant decrease in both ratios, especially ROE.

In SWs, in addition to the income generated from the sales of goods and services to customers, a very significant aspect is “Other operating revenue”, as this includes operating subsidies and aid received from public administrations. In order to analyze the effect of revenue diversification on SWs, two margins were calculated: the gross profit margin (GPM) defined as the difference between the net sales of goods and services to customers and the cost of the goods sold, and the operating profit margin (OPM), defined as the difference between total operating revenues (net sales of goods and services and other operating revenues) and the cost of the goods sold. The GPM showed negative values throughout the study period, which were substantial for the NP SWs for 2020. The OPM, which incorporates other operating revenues, showed positive values despite their being very low. SWs were not able to meet their current or supply expenses with their turnover. This seems to indicate that the activities undertaken were, in general, loss-makers with no additional operating income, consisting mainly of subsidies and public aid that they received and which contributed to most of their funding. However, results indicate that in the few years prior to COVID-19, sales-based income increased, and, therefore, so did their financial autonomy with respect to subsidies. The other operating revenue/net sales ratio had an average value of 31.94%, but it was much higher for NP SWs (40.34%), given their greater financial dependence on grants.

It should also be noted that in SWs, the percentage represented by staff expenses with respect to net sales was, in general, very high, and recorded an average value of 89.12% for NP SWs compared with 74.49% for FPs, a situation that reflected the former’s commitment towards their employees. In NP SWs, part of the profits may have been used for wage increases or recruitment. Even in 2020, the average number of workers increased in NP SWs, while it did the opposite in FPs.

It is worth noting that the level of efficiency can be a good measure of financial health and the social mission fulfillment of SWs. The DEA methodology, and the Charnes–Cooper–Rhodes (CCR) and Banker–Charnes–Cooper (BCC) models, with output orientation, were applied. The efficiency scores of an entity range from 0 to 1. An SW with a score equal to 1 indicates placement on the frontier, while a score below 1 denotes inefficiency. In general, and in average terms, considering variable returns to scale (VRS) (BCC model), the overall efficiency level was high, at 81.4%. FP SWs had slightly higher levels of overall and financial efficiency, but they were lower from a social point of view. In addition, a slight decrease in efficiency in 2020 was observed for both types of SWs. Applying the constant returns to scale (CRS) methodology, we obtained similar conclusions, although efficiency was lower and the drop in 2020 was proportionally higher.

Univariate tests of mean differences show that FPs dominated in performance over their counterparts (NPs) when it came to profitability and financial efficiency, but, in terms of social efficiency, it was higher in the NP SWs. When analyzing the efficiency of both types of company at the same time as incorporating social aspects, these differences almost disappeared in later years. Examining whether these observed relationships were statistically significant in a more rigorous regression analysis, as we have done below, is highly useful.

Regarding indebtedness, NP SWs had lower leverage than FP ones. In recent years, as a result of the improvement in profitability, there had been a very significant reduction in indebtedness until the COVID-19 pandemic struck in 2020 when it increased significantly again (2.6242). Long-term indebtedness (long-term debts/equity) was low and external financing was mainly made up of short-term debt resulting from delays in receiving subsidies. Because of this, our results were in line with Monzón-Campos and Herrero-Montagud (2016) and López-Penabad et al. (2019). This situation worsened throughout the pandemic and in its first year, the short-term debt ratio (short-term debts/equity) stood at 1.7804, especially worrying for FP SWs (1.9633). However, despite the increase in indebtedness, liquidity values remained high, and the current ratio, especially lately, showed high values (2.8436), even for 2020 (3.3977). The increase in short-term debt in 2020 appears to have occurred as a result of favorable financing conditions (Blanco et al., 2020).

Table I (in Annex I) shows how the SWs had a lower risk with slightly higher values for FPs (3.1121) than NPs (2.8701), as did companies located in the stress zone (FP: 19.11%; NP: 22.25%). In the last few years, the Z-Altman has increased considerably, even doing so for 2020, albeit slightly (3.4989 for 2020 vs. 3.4301 for 2019). It seems that the notable decrease in ROA and the increase in indebtedness have not yet significantly affected their risk of bankruptcy.

Next, to extend our previous statistical analysis, we conducted a linear regression for panel data.

Linear random effects models

In this study, we have identified a set of factors that can contribute to an SW’s profitability increasing or decreasing.

Independent variables

Both financial and overall efficiency had a positive and significant influence on SW profitability, while social efficiency had a negative and significant effect on SW profitability (ROA) (see Models 1–3 in Table 2). The analysis confirmed our initial hypotheses 1 and 2.

Table 2 Panel regressions (Random-effects GLS) of SW profitability (All, 2010–2020).
Full size table

The results confirmed that the SWs with the best management, and therefore the most efficiency from an economic point of view, obtained higher profitability. For instance, in Model 1, when VRSF increased by 0.01 (an additional 1% increase in the observed financial efficiency level), there was an increase of 0.01 × 52.70 = 0.527 percentage points in ROA. This finding was consistent with the studies of Magnanelli et al. (2016) and Asmalovskij et al. (2019). As for social efficiency, if it increased by 0.01, profitability decreased by 0.019 percentage points, resulting in a negative effect, which was similar to the findings of Bellostas et al. (2016). The positive effect of operational efficiency was much higher than the negative effect of social efficiency, so the effect of overall efficiency was positive (0.504 percentage points) on profitability. The SWs were able to operate effectively to meet the needs of people with disabilities while achieving financial viability by combining social and economic goals.

It was the companies that were managed and organized best, i.e. being the most efficient from an operational point of view, that achieved the best financial results. In order to improve profitability and ensure continuity and growth, it is increasingly important for SWs to carry out their core business activity as efficiently as they can to generate diversified income, while avoiding excessive dependence on public grants and subsidies, as these resources can sometimes be scarce or unstable.

If they wish to continue complying with their important social mission alongside traditional business operations, it is imperative for them to mitigate social and financial inefficiencies, thereby ensuring ethically responsible management that considers all stakeholders. Achieving satisfactory returns for shareholders can be done without compromising social value, considering the interests of stakeholders (Battilana et al., 2015) and SWs can see better results precisely because of their hybrid nature (Mongelli et al., 2019). SWs can better prioritize their social objectives when economic returns free up the necessary resources to do so.

Control variables

Most of the control variables in the models had the signs and magnitude that have been predicted in the empirical literature. For instance, in model 1, the variables, less risk (Z-Altman), long-term debt (LTL) and size (LNA), with estimated coefficients of 0.74, 4.43 and 2.24, respectively, had a positive impact on SW profitability.

The effect of a 0.01 increase in Altman’s Z-score on profitability in the model in Eq. (1) was 0.74 percentage points. The SWs with the highest Altman Z score, i.e., with the lowest financial risk, were the best performers, so our results matched those obtained by Mushafiq et al. (2021) and Gelashvili et al. (2022).

Regarding the effects of capital structure, the estimated coefficient associated with LTL was 4.43, indicating that the financing strategy that the firms had of rising long-term debt increased the ability of assets to generate profits (ROA), allowing them to grow and make investments thanks to the obtention of financial resources. This result was similar to previous studies by Magnanelli et al. (2016) and Martínez-Franco and Guzmán-Raja (2014). Another important factor that may have improved the profitability of these firms was their size, whose estimated coefficient was 2.24, in line with the findings of Asmalovskij et al. (2019) and Gelashvili et al. (2022).

In contrast, the estimated effects of liquidity, tangibility and age were −0.29, −7.77, and −2.33, respectively, and were negative and significant. The impact of the excess current ratio had a negative and significant relationship with profitability (Santos Jaen et al., 2021). This was a consequence of SWs being characterized as having lower levels of fixed assets and inventories, as most of them operated in the services sector. Similarly, the fixed assets ratio was negative and led to lower profitability, showing that when a company invested in its technical and production infrastructure, it did not instantly produce positive results (Gharaibeh and Bani Khaled, 2020; Nunes et al., 2009). In terms of age, the youngest organizations tended to have the highest profitability (Gelashvili et al., 2022; Alarifi et al., 2019).

The dummy variables that classified SWs by legal status, sector of activity and location were not significant. The legal statuses “for-profit” and “non-profit” (Santos Jaen et al., 2021), the services sector (Gelashvili et al., 2022) and the geographical area where a SW operated (Gelashvili et al. 2022) did not appear to have direct effects regarding profitability.

The dummy variables that classified SWs by legal status, sector of activity and location were not significant. The legal statuses “for-profit” and “non-profit” (Santos Jaen et al. 2021), the services sector (Gelashvili et al., 2022) and the geographical area where a SW operated (Gelashvili et al. 2022) did not appear to have direct effects regarding profitability.

The effect of the crisis on profitability was further analyzed by introducing a COVID-19 variable in Eq. (1). The negative coefficient indicates that Spanish SWs experienced reduced profitability during COVID-19 (and for the financial crisis, between the years 2010 and 2014). One could conjecture that SWs were impacted by the crisis, just like other companies were in Spain.

Our main results in relation to efficiency continued to stand after incorporating various control variables affecting profitability.

Moderating variables

Next, hypothesis 3, which states that the efficiency effect on SW profitability varies more significantly for FPs, was tested.

The estimated coefficients of the interaction term between the variables \({{{\rm{Effic}}}_{{i},{t}}\times {\rm{FP}}}_{{i}}\) were positive (overall and financial efficiency) and negative (social efficiency) but not statistically significant across the different models (Models 4–6), so hypothesis 3 could not be accepted.

However, the descriptive analysis (see Table I in Annex I) showed slightly higher financial efficiency levels and lower social efficiency in the FP group.

To evaluate the hypothesis that the relationship between efficiency and SW profitability was more significant during the COVID-19 crisis, we introduced an interaction term between the variables \({{{\rm{Effic}}}_{{i},{t}}\times {\rm{COVID}}19}_{{t}}\,\)(see Models 7–9 in Table 2). The estimated coefficients were positive for overall efficiency, 10.39, and financial efficiency, 6.99, and negative for social efficiency, −6.91. A positive relationship between overall efficiency and profitability during COVID-19 was found, confirming hypothesis 4.

The positive effect of operational efficiency on profitability was greatest in crisis periods; it was the most economically efficient SWs whose profitability was least affected. The pandemic forced many SWs to optimize their operations and improve their efficiency to maintain their performance in a difficult environment; it was the most efficient firms better withstood economic downturns due to their lower operating costs and greater adaptability, while the most inefficient firms may have found it difficult to survive. This was especially true for SWs operating in sectors where competition was intense and margins were tight. Conversely, the negative effect of social efficiency on ROA was less negative. State policies to minimize the consequences of COVID-19 may have played an important role in this respect.

We believe that the COVID-19 crisis made hybrid organizations focus their attention on how to balance their dual purpose. The crisis encouraged organizations to rethink their priorities, enhance stakeholder engagement, embrace technological advancements, and explore new opportunities for change (Bandini et al., 2023).

The differential effect of legal status on the profitability of SWs

The existence of a differential impact of efficiency on profitability was also investigated with respect to each legal status by running the model separately for the FP and NP sub-samples (Table 3). The results indicated that there were no significant differences. The effect of efficiency on profitability was similar for FPs and NPs. It is worth noting that in the latter, social efficiency did not affect ROA and both objectives were compatible in terms of performance. The dummy coefficients for all the years in the two crisis periods were negative. In general, the control variables tended to show the same signs and significance for the two subsamples.

Table 3 Panel regressions (random-effects GLS) of SW profitability (both legal statuses, 2010–2020).
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Robustness analysis

As a robustness analysis, the system GMM with Windmeijer corrected standard errors in a two-step estimation was implemented. In the estimations performed, autocorrelation tests of the idiosyncratic errors (AR(1), AR(2)) and validity tests of the set of instruments used (Sargan) were carried out to ensure the consistency of the system GMM estimator. All diagnostic tests confirm the validity of the instruments, showing no issues of serial autocorrelation and validating our dynamic model.

Table 4 presents the estimated coefficients from the system GMM and confirms the positive and significant relationship between ROA and overall financial efficiency (see models 10–12). However, for social efficiency, the estimated coefficients were negative but not statistically significant. Additionally, the control variables produced results consistent with those of the random effects model, indicating the robustness of our model. Notably, the significant positive effect of the one-lagged-dependent variable confirmed the persistence of the SW performance indicators.

Table 4 Panel regressions (GMM estimator) of SW profitability (All SWs, 2010–2020).
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Similar estimates were made taking other variables such as operating profit margin (OPM) (see Models 13 and 15) and Gross Profit Margin (GPM) (see Models 14 and 16) as dependent variables; as independent variables, the measures of efficiency obtained with the CRS model were used (see Models 17–19). The conclusions regarding efficiency and alternative measures of profitability were the same for the indicated models and for the main control variables.

Conclusion

The socio-labor inclusion of people with disabilities represents a substantial social challenge in European countries, particularly in Spain. SWs strive to improve this situation by providing employment opportunities and providing ongoing support to people with disabilities throughout the integration process. However, balancing the dual mission of achieving economic viability with social impact requires the complex demands of multiple stakeholders to be handled, which may lead to increased tension and complexity for their management.

This study, grounded in RB theory, explored the main determinants of the performance of 1133 Spanish SWs between 2010 and 2020 using a panel data analysis and data envelopment analysis. Beforehand, an analysis of their economic financial and social situation was conducted.

SW profitability is low (or negative) and public subsidies and grants are necessary for these organizations to run. The least socially efficient SWs, namely for profits, reach the highest levels of profitability because staff costs are proportionally lower, the productivity of disabled workers is higher as their degrees of disability are lower, and they operate in the most profitable sectors with the highest margins. Conversely, non-profit SWs are less profitable and less financially efficient. Additionally, they show lower indebtedness and greater liquidity and risk. The professionalization of non-profit SWs has allowed them to survive in a competitive economy and has brought them to an economic-financial situation quite similar to that of the other types of SWs that seek to maximize their results. Although non-profit SWs obtain lower economic returns, they have higher social efficiency, assigning a higher proportion of their resources to their workers, which leads to the conclusion that they prioritize the social variable over the economic one to a greater extent.

In terms of the effects of the COVID 19 crisis, SWs were more resilient to them than to those of the previous financial crisis. Compared with the situation of productive Spanish companies (Blanco et al., 2020), although SWs were observed to share patterns (such as an increase in short-term indebtedness or a decrease in results and profitability), the impact on the economic and financial variables was less traumatic for SWs than for productive Spanish companies in general.

Regarding the determinants of profitability, the efficiency of SWs is a key factor. The positive effect of operational efficiency was much higher than the negative effect of social efficiency, so the effect of overall efficiency was positive on profitability. The SWs were able to operate effectively to meet the needs of people with disabilities while achieving financial viability by combining social and economic goals.

Furthermore, the largest SWs, which have the least risk and the least long-term debt, were the most profitable. The oldest ones, with the greatest burden of fixed assets and highest liquidity ratio were those that had the lowest profitability. Other variables, such as sector and geographical location, were not significant in any of the models presented.

Despite having such different orientations, the legal status “for-profit” was not a significant enough factor to explain SW profitability, and when we ran our models separately for the subsamples there were no significant differences from the baseline model. It should only be noted that in the case of for-profit entities, social efficiency negatively and significantly affected profitability, indicating the risk of “mission drift” by emphasizing economic aspects over the social component. It should also be pointed out that the Spanish SWs experienced low profitability during both crises, just like other companies in Spain did.

As for the moderating variables, our results indicated that legal form did not moderate the relationship between firm efficiency and financial performance either. However, we were able to confirm that the positive effect of operational efficiency on profitability was greater in crisis periods; it was the most economically efficient SWs that saw their profitability least affected in said periods. Conversely, the negative effect of social efficiency on ROA was less negative. We believe that the COVID-19 crisis pushed organizations into rethinking their priorities, focusing on stakeholder engagement, adapting technologically and exploring their potential for change (Bandini et al., 2023).

The conclusions drawn from this paper are of great relevance, especially in an environment in which the European authorities have made a clear commitment to the Social Economy as an important instrument in the post-crisis social and economic reconstruction. It is of utmost importance that national, regional and local governments financially support SWs. These organizations not only create employment opportunities for people with disabilities but also operate efficiently and profitably. These organizations debunk the myth that they are uncompetitive by demonstrating resilience in fluctuating economic conditions.

This body of research provides actionable guidelines for policymakers to enhance support for SWs, especially focusing on non-profit entities due to their crucial societal role. Understanding how financial and social factors impact profitability is essential to developing policies that allow for the growth and sustainability of SWs. The COVID-19 pandemic underscored the necessity for increased governmental support and recognition of SWs’ social contributions. To create a more stable environment for SWs, enhanced public support measures are paramount. These should include increased government tax relief, subsidies and grants, along with the strategic use of public procurement policies to open up new markets and stabilize SW operations with longer-term contracts. Easing access to financial resources, such as repayable finance, alleviating financing difficulties and aiding the development of the social investment markets for these enterprises is also critical. Training and consultancy support are pivotal to enhancing the business skills and regulatory compliance of SWs. Collaborations between these, conventional enterprises and government agencies should be encouraged for local development and to increase market competitiveness (Galera et al., 2022; O’Connor and Meinhard, 2014; O’Hara and O’Shaughnessy, 2021).

Moreover, companies require information to enhance their performance by identifying profitability determinants, as this enables them to assess strengths and weaknesses, aiding decision-making processes. They should diversify income sources to reduce reliance on donations and public services, which in turn would enhance their market presence. Effective marketing and branding efforts are essential to highlight the social mission of SWs and attract new clients. By strategically partnering with others, social enterprises would be able to increase visibility, boost their reputation, unlock funding opportunities and expand market reach. This collaborative strategy would enable SWs to access a wide range of expertise, optimize operational efficiencies and foster growth and development, leading to broader social impact, greater sustainability, and ultimately, improved financial performance (Amran et al., 2023).

The main limitation of this study is that it focused on Spanish SWs, which are one type of Work Integration Social Enterprise (WISE). However, there is a great diversity of employment systems and policies for the social and labor inclusion of people with disabilities among countries; therefore, different legal forms could be qualified as WISEs; however, they are only granted as having “social enterprise” status if their scope and modus operandi permanently and significantly integrate a disabled workforce (Díaz et al., 2020). Therefore, we consider that the results obtained in our paper are applicable to the different types of companies classified as WISEs that may operate in other countries. On this note, a possible further line of research could be to incorporate WISEs from other countries, although for the moment we do not have an exhaustive list of these on an international scale. Another way of developing our research could be to analyze all social enterprises operating in Spain that meet the operational EU definition of SEs, including SECs, social initiative cooperatives and social insertion enterprises, thus enabling comparisons to be made.

One final limitation of this study is the data available to assess the creation of social value of SWs for the stakeholders, a hard-to-reflect reality in these types of companies. Consequently, the analysis of social data could be more extensive to enrich future research on this aspect for these entities.