Sustainability Challenges and Opportunities for Social Enterprises in Romania: A Multidimensional Analysis

Abstract

Over the last two decades, social enterprises in Romania have taken on an increasingly important role in the production and provision of social goods and services for vulnerable groups. Although forms of the social economy have long existed in Romanian society, sustainability remains a constant concern, particularly in the context of dependence on European Union structural funds. This study identifies the multidimensional factors influencing the sustainability of social enterprises in Romania, combining a quantitative analysis of 121 certified social enterprises from the National Register (2016–2022) with qualitative case studies of 15 selected organisations. Revenue diversification was significantly associated with financial sustainability (β = −0.28, p < 0.01), whilst high dependence on EU funding (>50% of revenue) was negatively associated with long-term viability (HR = 2.18, p = 0.002). Participation in networks was associated with markedly higher five-year survival rates (87.2% for network members versus 69.5% for non-members). Six key sustainability strategies were identified: hybrid revenue models, integration into the value chain, community inclusion, adaptive leadership, strategic partnerships, and effective communication of results and impact. Environmental sustainability is addressed with preliminary proxy evidence from the qualitative component; systematic measurement of this dimension represents a priority for future research. The findings confirm the absence of an integrated support framework for the sustainable activities of the social economy and, in some cases, the limited capacity of public institutions to support vulnerable groups. Policy recommendations include phased funding mechanisms, transitional support instruments and the systematic development of regional ecosystems.

1. Introduction

Paradoxically, although the social economy as an officially recognised sector is relatively new in Romania, there is a long tradition of structures that have been developing specific activities since the early years of the last century. Social enterprises—hybrid organisations that combine a social mission with market-oriented strategies [1,2]—address market failures in the provision of social services, whilst seeking to generate their own revenue to ensure the continuity of their activities [3,4]. The global expansion of social entrepreneurship [5] reflects the growing recognition of these organisations’ potential, yet in Romania the social economy sector only experienced rapid growth following its formal recognition through Law 219/2015 on the social economy [6], and challenges related to sustainability remain the primary concern for both practitioners and policymakers.

In Central and Eastern European (CEE) countries, the development of social enterprises takes place within unique institutional contexts, shaped by post-communist transition processes [7,8]. These contexts present both opportunities and constraints for the sustainability of social enterprises, linked to underdeveloped civil society institutions, limited social investment markets and a strong dependence on European Union structural funds [9,10]. In Romania, these dynamics are evident, with the social economy sector having experienced significant growth since the adoption of Law 219/2015, yet still facing substantial sustainability challenges. Research on the sustainability of social enterprises in transition economies remains limited, particularly regarding the complex relationships between funding sources, organisational capacity and long-term viability [11,12]. Although studies have examined individual dimensions of sustainability, comprehensive analyses addressing multidimensional sustainability in specific institutional contexts are underdeveloped [13]. The case of Romania offers valuable insights into how post-transition institutional environments shape the sustainability trajectories of social enterprises.

The social enterprise landscape in Romania comprised approximately 150 certified organisations actively operating by 2022 (a figure reflecting organisations with active status at that point in time, distinct from the total of 184 organisations certified across the 2016–2022 period and the cumulative stock of 2908 entities certified since the law’s enactment), operating under various legal forms, including associations, foundations, cooperatives and social enterprises for professional integration (WISE) [14]. These organisations operate mainly in the fields of social services (28.9%), education and training (18.2%) and employment support (15.7%), serving vulnerable populations, including people with disabilities, the long-term unemployed and Roma communities. However, sustainability challenges persist, with the mortality rate of organisations approaching 25% in the first five years after establishment. Recent studies confirm the severity of these challenges: of the 2908 certified social enterprises registered in Romania by 2023, approximately 90% are registered as limited liability companies—a model driven primarily by the eligibility requirements of the European Social Fund, rather than by organic development to achieve the social mission [15]. Over a third of certified social enterprises face financial difficulties as early as their first year of operation [16], which highlights the fact that the sector’s formal growth has not been accompanied by significant progress in terms of organisational sustainability. Comprehensive data on the current state of the sector confirm that, despite formal growth, only a minority of certified enterprises remain economically active and viable over time [17,18].

Sustainability in social enterprises goes beyond financial viability, encompassing multiple interdependent dimensions [19,20]. Financial sustainability requires the development of diversified revenue streams, whilst maintaining cost-effectiveness in the provision of social services [21]. Social sustainability involves demonstrating a measurable impact for the intended beneficiaries and wider communities [22]. Organisational sustainability entails building internal systems, developing human capital and maintaining institutional resilience [23]. Environmental sustainability is based on adapting to external conditions, including legislative changes, market dynamics and the expectations of stakeholders.

The European Union’s Structural Funds have significantly influenced the development of social enterprises in Central and Eastern European countries, providing crucial seed capital and capacity-building support [24,25]. However, concerns are emerging regarding the potential ‘grant dependency syndrome’, in which organisations become overly reliant on project-based funding, which could compromise long-term sustainability and focus on the social mission [26,27]. It has been found that approximately 80% of social economy entities in Romania are at high risk of bankruptcy, with only 6% of them achieving real financial sustainability [28]. The average cost of setting up a single social economy entity through EU programmes in Romania was approximately €35,000, a sum considered insufficient to establish a functional organisation [29].

Three key issues underpin this study. Firstly, existing research lacks comprehensive mixed-methods frameworks that integrate financial, social and organisational sustainability within Romanian institutional contexts. Secondly, the mechanisms through which dependence on EU funding affects organisational sustainability remain insufficiently theorised in the context of transition economies. Finally, validated sustainability measurement tools adapted to the Romanian context are lacking in the literature [30,31]. This study addresses all three critical aspects through a nationally representative mixed-methods design.

This study addresses these critical aspects through three main research questions:

RQ1: What organisational, financial and environmental factors predict multidimensional sustainability outcomes for social enterprises in Romania?

RQ2: How does dependence on EU funding (>50% of total revenue) affect long-term sustainability indicators compared to organisations with diversified funding portfolios?

RQ3: What strategies do successful social enterprises use to enhance financial resilience and operational sustainability?

This research makes a number of theoretical, methodological and practical contributions. From a theoretical perspective, it deepens the understanding of the concept of sustainability within hybrid organisations, providing empirical evidence from a specific institutional context, thereby contributing to the broader literature on social entrepreneurship in transition economies [32,33]. From a methodological perspective, the integration of register data analysis with in-depth organisational studies provides a more comprehensive understanding of the dynamics of sustainability [34,35]. From a practical perspective, the results underpin evidence-based policy recommendations, including transitional funding mechanisms and targeted regional interventions on the ecosystem [25].

2. Literature Review

2.1. Theoretical Frameworks for the Sustainability of Social Enterprises

The sustainability of social enterprises has emerged as a complex theoretical construct encompassing multiple interdependent dimensions that go beyond traditional financial indicators [36,37]. The most influential theoretical framework derives from the triple bottom line concept, which assesses organisational performance across economic, social and environmental dimensions [38]. However, critics argue that this framework oversimplifies the dynamic relationships between different aspects of sustainability and fails to capture the unique challenges faced by hybrid organisations [39]. More recent theoretical approaches have expanded beyond the three dimensions to include governance and ethical dimensions.

The concept of ‘dual outcome’ was introduced [3] to highlight the tension between fulfilling the social mission and financial sustainability—often referred to as the ‘mission-market tension’ [40]. Empirical studies demonstrate that successful social enterprises develop organisational capabilities that enable the simultaneous pursuit of social and financial objectives, rather than treating them as competing priorities [41,42]. Recent theoretical developments highlight the multidimensional nature of sustainability in hybrid organisations. A comprehensive framework [2] has been proposed that incorporates financial, social, organisational and environmental dimensions, arguing that sustainability requires simultaneous attention to all four areas. These three theoretical traditions generate distinct but complementary analytical predictions for the present study. Resource dependence theory [26,27] predicts that organisations with more diversified resource portfolios will be less vulnerable to the withdrawal of any single funder, generating the expectation that revenue concentration will be negatively associated with financial sustainability and organisational survival—the theoretical basis of H1 and H2. Social capital theory [43,44] predicts that embeddedness in networks of trust and reciprocity generates access to resources, information, and legitimacy that cannot be obtained through market transactions alone, generating the expectation that network participation will buffer organisations against funding shocks and dissolution risk—the theoretical basis of H4. Institutional logics theory [45] predicts that organisations capable of navigating competing institutional demands through formal governance structures and strategic planning will achieve greater internal coherence and external legitimacy, generating the expectation that organisational capacity variables will be independently associated with performance outcomes and will account for variance in sustainability beyond that explained by resource conditions alone—the theoretical basis of H3. Whilst these predictions are individually consistent with prior empirical findings, their simultaneous examination within a single post-transition institutional context provides an opportunity to assess their relative explanatory power under conditions of institutional underdevelopment and high EU funding dependency specific to Romania.

2.2. Organisational Factors in the Sustainability of Social Enterprises

Organisational capacity emerges as a critical factor linking external resources to sustainability outcomes, independently associated with performance across multiple dimensions. Leadership characteristics, particularly the ability to navigate between competing institutional logics, significantly influence organisational performance [45]. Research demonstrates that organisations with structured strategic planning approaches perform better across multiple dimensions of sustainability [46]. In the case of Romanian social enterprises specifically, an analysis of success factors conducted with 81 managers of non-profit organisations found that strategy and business model factors are the most influential determinants of organisational sustainability [31]. Further evidence shows that cognitive competence, social awareness and financial vulnerability statistically co-determine sustainability outcomes [47].

2.3. Sustainability Challenges in Transition Economies

Countries in Central and Eastern Europe present unique institutional contexts that shape the development trajectories of social enterprises [48,49]. The post-communist transition created institutional vacuums in the development of civil society, limiting the availability of support infrastructure for social entrepreneurship [50]. These institutional legacies continue to influence organisational behaviour and sustainability strategies decades after political transformation [51]. Levels of trust in institutions remain lower in post-transition societies, affecting stakeholder engagement and the development of partnerships, which are crucial for the sustainability of social enterprises [52]. Research indicates that social enterprises in CEE countries face greater challenges in terms of establishing legitimacy with both market actors and government institutions, compared to their counterparts in Western Europe [53]. In the Romanian context, it has been documented that limited availability of funds and low public awareness remain the main barriers to the development of social enterprises [54]. The involvement of local public administration and awareness of social issues are key factors enabling social entrepreneurs to develop viable projects [55]. A longitudinal analysis tracking the development of the social economy sector in Romania over a 15-year period confirmed that, although the number of registered entities has increased significantly, the sector continues to lack a clear legislative and institutional support framework to underpin long-term sustainability [56].

2.4. EU Funding and Issues of Dependency

The European Union’s Structural Funds have played a catalytic role in the development of social enterprises in Central and Eastern European countries, providing essential seed capital and resources for capacity building [8,9]. However, concerns are emerging regarding the potential negative effects of grant dependency on organisational sustainability. ‘Grant dependency syndrome’ describes situations where organisations become overly reliant on project-based funding, leading to mission drift, reduced innovation incentives, and organizational instability at the end of funding cycles [26,27].

Evidence from Romania provides particularly instructive examples of these dynamics. An analysis of social enterprises funded under Priority Axis 6 of the SOP HRD found that, although EU funding enabled organisational creation, the period following the end of funding brought significant risks and instability [57]. It has been documented that, of 1208 organisations supported by the ESF 2007–2014, only 20.86% maintained exclusively non-profit revenue models beyond the minimum sustainability period [29]. An unintended systemic effect has been identified [15]: the mandatory certification requirement in Romania for access to the ESF has led to a supply-driven development of social enterprises, in which entities were established primarily to access funds rather than to address real community needs. Research examining social enterprises in Germany has found that organisations with diversified funding portfolios demonstrate superior financial performance and greater organisational resilience [26].

3. Materials and Methods

3.1. Research Design and Philosophical Approach

The overall aim of the research was to assess the social enterprise sector in Romania in terms of its capacity to contribute to the social inclusion of disadvantaged groups and to achieve long-term sustainability. The research employed a sequential explanatory design using mixed methods [58], combining quantitative analysis of register data with qualitative case study investigations. This design was chosen because quantitative methods provide statistical scale and generalisability at the organisational level, allowing for the testing of hypotheses regarding the predictors of sustainability [59], whilst qualitative methods provide depth and contextual understanding of the mechanisms through which sustainability is achieved or compromised within specific organisational contexts [60]. The integration of these two approaches allows for complementarity: quantitative findings identify the prevalence and direction of relationships, whilst qualitative evidence highlights the processes and contextual factors that explain why these relationships occur.

The study adopts a pragmatic approach, treating both numerical models derived from register data and the narrative accounts of organisational actors as complementary sources of evidence regarding a shared empirical reality. The mixed-methods framework reflects the understanding that the sustainability of social enterprises is simultaneously a measurable organisational property and a socially constructed achievement, neither of which can be fully understood through a single mode of investigation.

3.2. Conceptual Framework and Hypotheses

Based on a review of the literature, we have developed a conceptual framework that posits that the sustainability of social enterprises results from the interaction of organisational, financial and environmental factors within specific institutional contexts (Figure 1).

The framework distinguishes four dimensions of sustainability—financial, social, organisational and environmental—each influenced by distinct sets of predictors, whilst interacting with the others through feedback processes. Each hypothesis is grounded in a specific theoretical mechanism: H1 and H2 derive from resource dependence theory’s prediction that portfolio concentration and single-source dependency increase organisational vulnerability; H3 derives from institutional logics theory’s prediction that governance capacity is associated with better performance outcomes and accounts for variance beyond resource conditions alone; and H4 derives from social capital theory’s prediction that network embeddedness is associated with greater resilience and lower dissolution risk, independently of funding structure. The four hypotheses are as follows:

H1. 

Revenue diversification (operationalised as lower Herfindahl–Hirschman Index scores) is positively associated with financial sustainability indicators.

H2. 

High dependence on EU funding (>50% of total revenue) is negatively associated with long-term sustainability outcomes, including organisational survival.

H3. 

Organisational capacity factors (staff stability, formality of governance, strategic planning) are positively associated with sustainability outcomes, and their inclusion in the regression models accounts for additional variance beyond that explained by external resource variables.

H4. 

Network participation and stakeholder engagement are positively associated with organisational performance and survival, with network membership expected to be associated with lower dissolution risk independent of funding source.

3.3. Quantitative Component

3.3.1. Data Source and Population

The quantitative analysis utilised data from the National Register of Social Enterprises in Romania, administered by the National Agency for Employment (ANOFM). The register contains comprehensive information on all certified social enterprises operating in accordance with Law 219/2015 [14], representing the most complete dataset available on the social enterprise sector in Romania. Access to the register was unrestricted and included annual financial reports, certification records, the number of employees and organisational characteristics for the period 2016–2022. All data were anonymised prior to transfer and managed in accordance with GDPR requirements. It should be noted that the figure of 2908 certified social enterprises cited elsewhere in this manuscript [15] refers to the cumulative stock of all entities ever certified under Law 219/2015 up to 2023, across all legal forms and registration periods since the law’s enactment. By contrast, the present study’s target population of N = 184 comprises exclusively those organisations that received initial certification within the 2016–2022 observation window and were therefore observable throughout the study period. These are distinct populations: the cumulative stock includes entities certified before 2016, entities that had already dissolved before our observation window, and a large proportion of limited liability companies certified primarily to access ESF funds in the 2014–2020 programming period [15], many of which were never intended as long-term social enterprises. The present study focuses deliberately on the cohort traceable across the full observation window, which represents the population for which longitudinal financial and organisational data were available.

The target population consisted of all social enterprises certified between 2016 and 2022 (N = 184). Organisations were included in the analytical sample if: (1) they maintained active certification status throughout the study period; (2) they submitted complete annual reports for at least two consecutive years; and (3) they operated independently (i.e., they were not subsidiaries of larger public or private entities). Organisations that were struck off the register due to merger, acquisition or administrative dissolution were retained in the survival analysis but excluded from the cross-sectional regression models. After applying these criteria, the analytical sample comprised 121 organisations (65.8% of the eligible population), with the remaining 63 organisations excluded mainly due to incomplete financial reporting (N = 41), loss of certification during the study period before accumulating two years of complete reporting (N = 14) and non-independent operational status (N = 8). The excluded organisations did not differ significantly from the analytical sample in terms of the available basic characteristics (legal form: χ² = 1.84, p = 0.61; region of registration: χ² = 3.21, p = 0.52). However, we acknowledge that these comparisons are limited to categorical administrative variables; financial characteristics, organisational age, and pre-exclusion performance trajectories were not systematically available for all 63 excluded organisations and could therefore not be compared. The possibility of residual selection bias—whereby excluded organisations differed from included ones in ways not captured by legal form or region—cannot be ruled out, and this constitutes a limitation discussed further in Section 5.5.

3.3.2. Measurement and Operationalisation of Variables

Financial sustainability was operationalised as a composite score derived from three annual indicators: (1) the ratio of revenue generated (revenue from sales, services and commercial activities) to total revenue, reflecting market orientation; (2) the operating margin (revenue minus operating costs, divided by total revenue), reflecting cost efficiency; and (3) a binary indicator of year-on-year financial growth (revenue in year t greater than revenue in year t − 1). The FSI is explicitly conceived as an operational composite index rather than a reflective latent construct: the three components capture conceptually distinct but empirically complementary dimensions of financial viability—market self-reliance, operational efficiency, and growth trajectory—each of which is theoretically relevant to sustainability in hybrid organisations [2,21]. Because the components are not assumed to be interchangeable indicators of a single underlying factor, Cronbach’s alpha (0.71) is reported as a descriptive measure of inter-item consistency rather than as evidence of unidimensionality. The three indicators were standardised (z-score) and summed to produce a continuous FSI, with higher values indicating stronger financial sustainability. We acknowledge that the inclusion of a binary growth indicator alongside two continuous ratios introduces measurement asymmetry; future research should examine whether a fully continuous specification—replacing the binary growth indicator with the year-on-year revenue growth rate—yields substantively different results. A potential concern regarding mechanical correlation between HHI and FSI also warrants explicit attention. The earned-revenue ratio—a component of FSI—is by construction negatively correlated with HHI, since lower revenue concentration implies a higher share of earned income. This structural overlap means that a portion of the reported association between HHI and FSI (β = −0.28) may reflect this built-in relationship rather than an independent economic mechanism. We were unable to fully disentangle this overlap within the constraints of the present dataset; readers should therefore interpret the magnitude of the HHI coefficient with appropriate caution, and future research should examine this association using specifications in which the earned-revenue ratio is excluded from the FSI or modelled separately.

Revenue diversification was measured using the Herfindahl–Hirschman Index (HHI) calculated across five revenue categories: EU structural funds, national public grants, revenue from social services, revenue from commercial activities, and private donations/philanthropy. Lower HHI values indicate greater diversification. Dependence on EU funding was operationalised as a binary variable (1 = EU funding constitutes > 50% of total revenue in a given year; 0 = otherwise), in line with the threshold used in previous studies in Romania [28,29]. Network membership was a binary indicator (1 = membership of at least one social enterprise network or a formally constituted umbrella organisation; 0 = otherwise), derived from registration statements and corroborated via the organisations’ websites. Urban setting was coded as 1 for organisations registered in municipalities with a population > 20,000. The level of regional development was identified using the European Commission’s regional competitiveness index for the NUTS-2 region in which each organisation operated.

Organisational size was measured by total revenue in the reference year, and organisational age was calculated as the number of years since the first registration certificate. Staff stability was operationalised as 1 minus the annual staff turnover rate (departures divided by the average number of employees). Governance was a binary indicator derived from a documentary analysis of the existence or otherwise of a functional board of directors, distinct from operational management. Strategic planning was also binary, coded as 1 if the organisation had a written strategic plan covering a horizon of at least three years, as documented in the organisational reports submitted.

For the survival analysis, the outcome was defined as official removal from the National Register due to voluntary dissolution or administrative removal for non-compliance, as recorded in the administrative registers of ANOFM. Organisations still active at the end of the observation period (31 December 2022) were included in the analysis.

3.3.3. Statistical Analysis

Descriptive statistics characterised the sample and examined the distributions of the variables. Bivariate associations were assessed using Pearson correlations for continuous predictors and point biserial correlations for binary predictors. Multiple regression analysis tested the hypothesised relationships between sustainability predictors and the financial sustainability index, using hierarchically constructed models: Model 1 included structural controls (size, age, legal form, region); Model 2 added financial predictors (HHI, EU dependence); Model 3 added organisational capacity variables (formality of governance, strategic planning, staff stability); and Model 4 added the network membership variable. Variance inflation factors (VIFs) were examined to assess multicollinearity; all VIF values were below 3.0, indicating acceptable levels of collinearity. Residual diagnostics confirmed that the assumptions of normality and homoscedasticity were reasonably met.

Survival analysis used the Kaplan–Meier estimate to compare survival curves between subgroups defined by dependence on EU funding and network membership, with log-rank tests assessing the statistical significance of the differences. Cox proportional hazards regression modelled time to deregistration as a function of organisational predictors, with the proportional hazards assumption tested using Schoenfeld residuals both globally and for each covariate individually. The 50% EU funding threshold used to operationalise high dependency follows prior Romanian studies [28,29]; sensitivity analyses treating EU dependence as a continuous predictor and testing alternative binary thresholds (30%, 40%, 60%, 70%) are acknowledged as a limitation in Section 5.5. Standard errors in the Cox model were not clustered at the regional or sectoral level due to constraints of the available software implementation; the potential consequences of within-cluster dependence are acknowledged as a limitation. The administrative register does not systematically distinguish voluntary dissolution from administrative removal for non-compliance; both event types are therefore treated as a composite outcome in the survival analysis, which may obscure economically distinct dissolution pathways. All analyses were performed using SPSS version 29.0, with a significance level of α = 0.05 and 95% confidence intervals reported throughout. Given the small number of dissolution events (n = 23), results from multiple specifications should be interpreted with caution; no formal correction for multiple testing was applied, and replication in larger samples is needed to establish the stability of the reported associations.

3.4. Qualitative Component

3.4.1. Case Selection Strategy

Qualitative case selection utilised purposive sampling to ensure maximum variation [61] across five dimensions identified as theoretically relevant following a review of the specialist literature: legal form (associations, foundations, cooperatives, WISE), geographical location (urban/rural; development region), main sector of activity, performance trajectory (improving, stable, declining—assessed based on data from the financial register) and level of dependence on EU funding. This strategy led to the selection of 15 organisations for case studies, spread across all eight NUTS-2 development regions, including three rural organisations, four WISEs and representatives from each major sector of activity. The 15 cases included 5 organisations from the high sustainability tertile of the FSI, 5 from the medium sustainability tertile and 5 from the low sustainability tertile, allowing for a theoretically grounded comparison between cases. The logic of this design follows the principle of maximum variation sampling [61], which seeks analytical breadth through deliberate diversity rather than statistical representativeness; cross-case comparisons are intended to illuminate theoretical contrasts and contextual configurations, not to support statistical generalisation across cells.

3.4.2. Data Collection Procedures

Data collection followed a multi-source approach, including semi-structured interviews, document analysis and observational data obtained from site visits. A total of 47 semi-structured interviews were conducted with organisation directors, board members, frontline staff and beneficiary representatives (average: 3.1 interviews per organisation; range: 2–5). The interviews lasted an average of 62 min and were conducted in Romanian, audio-recorded with the participants’ consent and selectively transcribed. The interview guides covered organisational history, funding strategies, governance structures, stakeholder relations, sustainability challenges and adaptive responses. Documentary sources included annual reports, strategic plans, project documentation and financial statements. Site visits (2–4 h per organisation) provided observational data on physical infrastructure, operational processes and organisational culture. Data collection took place between November 2021 and March 2022.

3.4.3. Qualitative Analysis Procedures

The analysis of qualitative data employed a systematic thematic analysis, following Braun and Clarke’s six-phase framework [62]: familiarisation with the data, generation of initial codes, identification of themes, review of themes, definition and naming of themes, and final analysis. Coding was carried out independently by two researchers using NVivo 12 software, with an initial assessment of inter-rater reliability (Cohen’s κ = 0.74, indicating substantial agreement), followed by a consensus discussion to resolve coding discrepancies. The coding scheme was developed inductively based on the data, whilst remaining sensitive to the conceptual framework. Thematic saturation was assessed iteratively across the case sequence: after the 11th case, no substantially new thematic codes were generated, with subsequent cases (12–15) serving primarily to elaborate and refine existing themes rather than to introduce new conceptual categories. It should be noted that this refers to thematic saturation within the scope of the defined research questions, not to statistical exhaustiveness across all possible configurations of the study population. Cases 12–15 were retained in the analysis because they served specific purposes beyond new code generation: two provided the sole representation of rural organisations in the sample, one was the only agricultural cooperative, and one allowed comparison of an organisation that had transitioned from high to low EU dependency during the study period—configurations considered analytically important for the maximum variation design. The final coding structure comprised three hierarchical levels: five overarching thematic domains (financial strategy, governance and leadership, stakeholder relationships, institutional context, and impact orientation), 18 mid-level categories, and 47 specific codes. Cross-case analysis utilised structured matrices comparing strategic profiles, funding structures and sustainability outcomes across the 15 organisations, enabling the identification of patterns, contrasts and configurations associated with differentiated sustainability trajectories. The six sustainability strategies reported in Section 4.6 represent emergent analytical constructs derived from cross-case pattern recognition, consistent with the abductive logic of qualitative comparative analysis [61], rather than pre-specified hypotheses subject to confirmation or disconfirmation.

3.5. Integration of Mixed Methods

The quantitative and qualitative results were integrated at two stages: (1) during case selection, where quantitative FSI scores guided purposive sampling to ensure variation in performance; and (2) during the joint display analysis (Section 4.7), where quantitative effect estimates were linked to qualitative explanations. This integration strategy follows the logic of ‘triangulation’ and ‘explanatory construction’ described in the literature [34,63], allowing quantitative findings to establish the generalisability of relationships, and qualitative findings to clarify the mechanisms that explain them.

4. Results

4.1. Sample Characteristics

The analytical sample comprised 121 certified social enterprises, representing 65.8% of all eligible organisations in Romania’s National Register.

Table 1. Descriptive characteristics of the analytical sample (N = 121).

Characteristic	N	%	Mean (SD)
Legal form
Association	52	43.0
Foundation	28	23.1
Cooperative	21	17.4
SE Professional Integration (WISE)	20	16.5
Development region
Bucharest-Ilfov	24	19.8
Southern Muntenia	14	11.6
North-West	18	14.9
Central	16	13.2
North-East	13	10.7
West	12	9.9
South-East	12	9.9
South-west Oltenia	12	9.9
Residential environment
Urban	87	71.9
Rural	34	28.1
Main sector of activity
Social services	35	28.9
Education and training	22	18.2
Employment support	19	15.7
Healthcare	14	11.6
Cultural/creative	11	9.1
Agriculture/food	20	16.5
Continuous variables
Age of organisation (years)			4.2 (2.1)
Total annual revenue (€)			87,340 (112,420)
Number of employees (FTE)			8.3 (7.1)
Annual staff turnover rate (%)			23.7 (15.2)
Share of EU funding in revenue (%)			47.3 (28.9)
Revenue diversification (HHI)			0.52 (0.18)
Key organisational characteristics
Number of network members	68	56.2
Dependence on the EU (>50% of revenue)	64	52.9
Official Board of Directors	79	65.3
Written strategic plan	54	44.6
Employs vulnerable people	83	68.6

Notes: HHI = Herfindahl–Hirschman Index (0 = perfect diversification, 1 = total concentration); FTE = full-time equivalent; SE = social enterprise.

presents the descriptive characteristics of the sample. The sample demonstrates a significant geographical concentration, with over 70% of organisations located in urban areas and nearly 40% concentrated in the three most economically developed regions (Bucharest-Ilfov, West and Centre). This geographical distribution reflects sector-level trends documented in the specialist literature: ESF funding during the 2007–2014 period was positively correlated with regional GDP per capita, rather than with development needs. Evidence at the local level in counties such as Brașov confirms that certified social enterprises remain few in number relative to the identified social needs, with the majority operating in the production of goods or specialised services for people with disabilities [64].

4.2. Results on Financial Sustainability

4.2.1. Revenue Structure and Diversification

An analysis of revenue sources reveals substantial variations in organisations’ funding portfolios (Figure 2). Market sales constitute the largest single revenue category, accounting on average for 31.6% of total revenue. EU structural funds and public grants together account for a further substantial share, with private donations representing 9.2%, government grants 7.5%, membership fees 2.8%, and other sources 1.6% of average revenue. However, this aggregate picture masks considerable variation: 23 organisations (19.0%) receive less than 20% of their revenue from EU sources, whilst 31 organisations (25.6%) rely on EU funding for more than 70% of their revenue. It should be noted that the revenue categories presented in Figure 2 reflect the classification used in the organisational financial reports; the share of EU structural funds is incorporated within the broader public and grant-based categories rather than reported as a separate line item in the figure. Revenue diversification, measured by the HHI, averages 0.52 (SD = 0.18), indicating moderate concentration, with organisations with higher rates of revenue from activities yielding significantly lower HHI values (r = −0.63, p < 0.001). Note that throughout this study, HHI is used as a measure of revenue concentration (higher HHI = greater concentration = lower diversification); consequently, negative regression coefficients for HHI indicate that lower concentration (i.e., greater diversification) is associated with higher financial sustainability.

4.2.2. Predictors of Financial Sustainability

Table 2. Results of the hierarchical multiple regression: predictors of the financial sustainability index (N = 121).

Variable	Model 1 β	Model 2 β	Model 3 β	Model 4 β	VIF
Structural controls
Age of the organisation	0.09	0.07	0.06	0.05	1.18
Revenue	0.18 *	0.14 *	0.12	0.11	1.43
Urban location	0.14 *	0.11	0.09	0.08	1.31
Regional competitiveness index	0.16 *	0.13 *	0.11	0.10	1.27
Financial indicators
HHI (income diversification) a		−0.28 **	−0.25 **	−0.19 **	1.52
Dependence on the EU (>50%) b		−0.36 ***	−0.32 ***	−0.31 ***	1.64
Organisational capacity
Formal governance b			0.19 *	0.17	1.38
Strategic planning b			0.16 *	0.15 *	1.29
Staff stability (1 − staff turnover)			0.21	0.20 **	1.41
Network variable
Network membership b				0.23 **	1.35
Model fit
R2	0.112	0.298	0.421	0.467
Adjusted R2	0.080	0.258	0.374	0.421
ΔR2	0.112 *	0.186 ***	0.123 ***	0.046 **
F for ΔR2	3.71 *	15.84 ***	8.79 ***	9.41 **

Notes: Standardised regression coefficients (β) are reported. a Continuous variable; lower HHI = greater diversification. b Binary variable (0/1). * p < 0.05; ** p < 0.01; *** p < 0.001. VIF = Variance Inflation Factor; all values below 3.0 indicate acceptable multicollinearity.

presents the results of the hierarchical multiple regression analysis examining the predictors of the financial sustainability index (FSI). The full model (Model 4) explains 46.7% of the variance (R² = 0.467, adjusted R² = 0.421, F(11,109) = 8.69, p < 0.001).

4.3. Results Regarding Social Sustainability

The social enterprises in the sample demonstrate a high level of interest in employing people from vulnerable groups. Of the 121 organisations, 83 (68.6%) employ at least one person from vulnerable groups (people with disabilities, the long-term unemployed, members of the Roma community or other disadvantaged groups), with an average of 32.4% of total staff coming from vulnerable groups. This figure exceeds both the national average for the employment of vulnerable groups in the private sector (estimated at approximately 12–15%) and the targets set by the European Commission for social economy entities (usually 20–30%), indicating that certified social enterprises in Romania are fulfilling their statutory obligations regarding their social mission in terms of workforce recruitment.

However, the depth and quality of labour market integration vary considerably from one organisation to another. Qualitative case analysis revealed that, in 6 of the 15 organisations studied (40%), vulnerable employees were concentrated in precarious roles, with low-skilled positions and limited opportunities for advancement, raising questions as to whether employment constitutes a genuine opportunity for inclusion or merely symbolic inclusion. Organisations in the high-sustainability tertile demonstrated not only higher rates of employment of vulnerable people (mean = 41.2% of staff, compared with 24.7% in the low-sustainability tertile; t(78) = 3.84, p < 0.001), but also superior outcomes in terms of wages (vulnerable employees earned 87% of the wages of non-vulnerable employees in organisations with high sustainability, compared to 64% in organisations with low sustainability) and access to training (2.8 days per year per vulnerable employee, compared to 1.1 days). Research on social entrepreneurship in Romania also confirms that social mission and community motivation are the main drivers of involvement in this sector, alongside a strong focus on social impact rather than financial gain [65]. The motivations behind social entrepreneurs in Romania also emphasise the creation of hybrid value, combining social inclusion with environmental sustainability objectives [66].

Organisations with formal impact measurement systems—defined as having at least two standardised indicators systematically tracked for at least two years—demonstrate superior social sustainability indicators across multiple dimensions. More specifically, they exhibit higher growth rates in the number of beneficiaries (r = 0.37, p < 0.01), a more diverse range of programmes (r = 0.33, p < 0.01) and better beneficiary retention rates (r = 0.29, p < 0.01). It is worth noting that only 34 organisations (28.1% of the sample) reported having such formal impact measurement systems in place, with adoption rates being significantly higher among organisations receiving private funding (41.2%) compared to those dependent on EU funding above the 50% threshold (18.6%; χ² = 6.84, p = 0.009).

Beyond employment outcomes, social sustainability encompasses the broader contribution of social enterprises to community well-being. In the qualitative case studies, 12 out of 15 organisations stated that they engage in unpaid community activities (free information sessions, pro bono services, community organising) that were not specified in their formal service provision contracts. Organisations with a high dependence on EU funding—over 70% of their income—were significantly less likely to report such unpaid community engagement (23.1% compared to 61.5% for organisations with an EU dependence of under 30%; χ² = 9.87, p = 0.002), suggesting that project-based funding may preclude a clear community focus.

Beyond employment and community outcomes, the study provides limited but indicative evidence on the environmental sustainability dimension of the four-dimensional framework [2]. In the qualitative case studies, 6 of the 15 organisations (40%) reported explicit environmental objectives in their strategic plans or activity descriptions, encompassing waste reduction, short supply chains, and local sourcing practices. Organisations operating in the agriculture/food sector (n = 20; 16.5% of the sample) were significantly more likely to report environmental objectives than those in other sectors (χ² = 7.42, p = 0.006), consistent with evidence demonstrating that integrating circular economy principles into rural social enterprise operations can strengthen organisational resilience [67]. This pattern aligns with broader sector evidence from Romania, where more than half of social enterprises report limited familiarity with circular economy concepts [68], suggesting that environmental sustainability capacity remains underdeveloped across the sector. These findings are preliminary and derived from self-reported strategic planning documents rather than standardised environmental performance indicators; they should be treated as exploratory evidence of a dimension that warrants systematic empirical attention in future research, rather than as a comprehensive assessment of environmental sustainability performance.

4.4. Findings on Organisational Sustainability

Staff retention within the organisation is emerging as a significant challenge across the entire sector. The average annual staff turnover rate of 23.7% (SD = 15.2%) far exceeds typical benchmarks in the non-profit sector, which generally range between 10 and 19% in mature social economy contexts in Western Europe. This high turnover varies significantly depending on the funding model: organisations with an EU dependency of over 50% have an average turnover of 29.4% (SD = 16.8%), compared to 17.1% (SD = 12.3%) for those below the 50% threshold (t(119) = 4.32, p < 0.001). These differences highlight a structural mechanism: organisations dependent on project-based EU funding face funding gaps between grant cycles (an average gap of 4.2 months, according to 11 of the 15 organisations in the case study), which forces recurrent staff redundancies and re-hiring, undermining job stability.

The high staff turnover rate reflects a structural challenge documented more broadly within the Romanian social economy. The regression results support this interpretation: staff stability significantly predicted both financial sustainability (β = 0.20, p < 0.01) and organisational survival (HR = 0.41, p = 0.009), indicating that human capital retention is not merely a consequence but also a determining factor of sustainability.

Governance stability represents an equally important, yet less frequently examined, dimension of organisational sustainability. Of the 121 organisations, 79 (65.3%) reported having a functional board of directors, distinct from operational management, but only 41 (33.9%) maintained a consistent board composition throughout the study period, with no resignations or replacements. The turnover rate of the board of directors was significantly higher in organisations with EU dependency exceeding 50% (average annual board turnover rate = 34.2%) compared to those below this threshold (12.7%; t(119) = 5.21, p < 0.001). Organisations with stable staff (turnover < 15%) and stable boards of directors (turnover < 20%) demonstrated three-year survival rates of 91.7%, compared with 68.2% for organisations with high turnover in either of these categories—a distinct subgroup comparison from the five-year Kaplan–Meier estimates reported in Section 4.5.

Strategic planning emerged from both quantitative and qualitative aspects as a critical factor in organisational capacity. Only 54 organisations (44.6%) reported having a written strategic plan covering a period of at least three years. Of the organisations that were struck off the register during the study period, only 21.7% had such a plan at the outset, compared with 49.0% of the organisations that survived (χ² = 5.98, p = 0.014). The qualitative case studies revealed an important distinction between ‘performative planning’ (the drafting of documents for external accountability) and ‘substantive planning’ (the iterative development of strategy embedded in organisational routines)—a conceptual nuance that quantitative indicators alone cannot capture.

4.5. Survival Analysis

Table 3. Cox proportional hazards regression: predictors of organisational dissolution (N = 121; events = 23).

Variable	b (SE)	HR	95% CI	p
Structural controls
Age of the organisation	−0.08 (0.06)	0.92	[0.82, 1.04]	0.18
Logarithmic revenue (scale)	−0.31 (0.14)	0.73	[0.55, 0.97]	0.03 *
Urban location	−0.24 (0.18)	0.79	[0.55, 1.12]	0.19
Financial predictors
HHI (diversification) a	1.12 (0.38)	3.06	[1.46, 6.44]	0.003 **
Dependence on the EU (>50%) b	0.78 (0.29)	2.18	[1.24, 3.84]	0.002 **
Organisational capacity
Staff stability	−0.89 (0.34)	0.41	[0.21, 0.80]	0.009 **
Formal governance b	−0.44 (0.22)	0.64	[0.42, 0.99]	0.04 *
Network variable
Network membership b	−0.66 (0.24)	0.52	[0.32, 0.83]	0.006 **
Model fit
Overall χ2 (df = 8)	31.42			<0.001 ***
Nagelkerke R2	0.38

Notes: b = unstandardised log-hazard ratio; SE = standard error; HR = hazard ratio; CI = confidence interval. a = Continuous; higher HHI = higher concentration = higher hazard. B = Binary (0/1). The assumption of proportional hazards was tested using Schoenfeld residuals (global test p = 0.41); variable-level tests were also conducted, with no individual covariate showing significant time-varying effects (all p > 0.10). Standard errors are not clustered; the administrative outcome variable combines voluntary dissolution and administrative removal as a composite event. The small event count (n = 23) limits statistical power; results should be interpreted as indicative rather than definitive. * p < 0.05; ** p < 0.01; *** p < 0.001.

presents the results of the Cox proportional hazards regression examining the predictors of organisational dissolution. Over the entire analysis period (2016–2022), 23 organisations (19.0% of the analytical sample) were officially dissolved. The Kaplan–Meier survival analysis revealed significantly higher five-year survival rates for network members (87.2%) compared with non-members (69.5%; log-rank χ² = 8.34, p = 0.004) and for organisations with EU dependency below 50% (76.2%) compared to those above 50% (58.4%; log-rank χ² = 6.92, p = 0.009) (Figure 3).

Cox regression identified network participation as reducing the risk of closure by 48% (HR = 0.52, 95% CI [0.32, 0.83], p = 0.006). Dependence on EU funding of over 50% doubled the risk of closure (HR = 2.18, 95% CI [1.24, 3.84], p = 0.002). High income concentration (HHI) tripled the risk of closure (HR = 3.06, 95% CI [1.46, 6.44], p = 0.003). Organisational size exerted a protective effect (HR = 0.73, p = 0.03), as did staff stability (HR = 0.41, p = 0.009) and the formality of governance (HR = 0.64, p = 0.04).

4.6. Qualitative Findings: Sustainability Strategies

A thematic analysis of 47 interviews conducted across the 15 organisations studied identified six main sustainability strategies used by successful social enterprises:

Hybrid revenue-generating models: The strategic use of EU funding for capacity building and infrastructure investment, alongside the development of own revenue streams through service contracts and commercial activities. Organisations that adopted this strategy used project grants to develop their capabilities (e.g., staff training, equipment procurement), which subsequently enabled them to enter the market, rather than to cover recurring operational costs. As one director of a high-sustainability cooperative explained: “We used the European funds to buy the equipment and train our people. After the project ended, we already had clients—the grant built our capacity, it didn’t pay our salaries.” (Director, social cooperative, Central region)”.

• Integration into the value chain: Active integration into established supply chains, alongside conventional businesses and public institutions. This strategy involved negotiating service agreements, social procurement contracts and subcontracting relationships that ensured stable and predictable income, independent of funding cycles. A WISE manager described this dynamic: “The contract with the municipality changed everything. We knew exactly what income we would have for the next two years—we could plan, we could hire, we could breathe.” (Manager, WISE, South-East region)
• Community integration: Deep local relationships that ensure resilience through the informal mobilisation of resources, volunteer networks and community legitimacy. Organisations with strong community ties were able to leverage social capital to bridge funding gaps and attract in-kind contributions.
• Adaptive leadership: Leadership characterised by dual social and commercial skills, enabling a fluid navigation between mission imperatives and market demands. Leaders in highly sustainable organisations described the deliberate cultivation of business skills through executive education and peer learning networks. This was articulated explicitly by one organisational leader: “I had to learn how to read a balance sheet. Nobody taught social workers how to run a business—I had to teach myself, because if the organisation fails, there is no mission left to pursue.” (Director, association, North-East region)
• Strategic partnerships: Diverse cross-sector partnerships encompassing public institutions, private companies, civil society organisations and universities, creating mutually reinforcing support ecosystems that spread risk and facilitate collective advocacy.
• Impact communication: Systematic and accessible communication of social impact to attract diverse support, including funding from corporate social responsibility, social investment and favourable public procurement decisions.

4.7. Integrating Quantitative and Qualitative Results

Figure 4 presents a joint representation integrating quantitative and qualitative findings around key dimensions of sustainability. The integration reveals three main meta-inferences. Whilst quantitative results show clear benefits of revenue diversification (β = −0.28, p < 0.01; HR = 3.06 for high concentration), the qualitative cases reveal that achieving diversification requires an initial investment focused on organisational capacity—a paradox that calls for patient capital instruments rather than immediate diversification mandates. The statistically significant network effect (β = 0.23; HR = 0.52) operates through three specific mechanisms: resource sharing (physical infrastructure, specialised expertise, client referrals), knowledge transfer (dissemination of best practices, collective problem-solving) and collective advocacy (joint representation in political arenas). The quantitative analysis shows the long-term negative effects of dependence on EU funding (HR = 2.18), whilst the qualitative cases demonstrate the catalytic role of EU funding when used strategically for capacity building rather than for operational support—suggesting that the critical variable is not the volume of EU funding, but its strategic application.

5. Discussion

5.1. Multidimensional Sustainability in the Institutional Context

The findings confirm the multidimensional nature of social enterprise sustainability, whilst revealing how institutional contexts are associated with the relative importance of different dimensions. Unlike studies in mature social enterprise ecosystems [69,70], our results suggest that organisational and environmental factors are more strongly associated with outcomes in Romanian social enterprises than purely financial considerations. The significant positive association between network membership and financial sustainability (β = 0.23, p < 0.01), together with the qualitative emphasis on community integration, reflects the enduring importance of social capital in post-transition societies [60,71]. Where formal institutions remain underdeveloped, informal networks appear to be associated with greater organisational resilience—a pattern consistent with previous findings from our research on the social economy in Romania [72], where cooperatives, mutual aid organisations and NGOs have all demonstrated that the lack of a specific legislative framework has significantly constrained the sector’s development.

It should be noted that the evidence generated in this study is unequally distributed across the four sustainability dimensions. Financial sustainability (Section 4.2) and organisational sustainability (Section 4.4) are supported by both quantitative regression and survival analysis evidence. Social sustainability (Section 4.3) is supported by quantitative indicators and qualitative case data. Environmental sustainability, whilst included in the theoretical framework [2] and increasingly central to the social enterprise literature [67,68], is the least empirically developed dimension in this study; the proxy evidence reported in Section 4.3 should be interpreted as preliminary and exploratory rather than as a systematic measurement. Future research should develop standardised environmental performance indicators adapted to the Romanian social enterprise context, including circular economy metrics and carbon footprint proxies appropriate for small hybrid organisations.

5.2. The EU Funding Paradox

Our findings reveal a complex relationship between EU funding and sustainability outcomes, which goes beyond mere concerns about dependency. The negative association between high dependence on EU funding and long-term sustainability indicators (β = −0.19, p < 0.05 in the cross-sectional models; HR = 2.18, p = 0.002 in the survival analysis) is consistent with concerns expressed in previous research regarding grant dependency syndrome [73,74], though the cross-sectional and observational nature of our data precludes causal attribution. The qualitative analysis reveals important nuances: successful organisations report using EU funding strategically as ‘patient capital’ for capacity building and market development, subsequently reducing their dependence over time. This contrasts with patterns observed in less successful organisations, where EU funding appears concentrated in operational expenditure, a configuration associated with structural vulnerability at the end of funding cycles. Evidence from Romania on supply-driven business creation [15]—where 90% of certified entities adopted the form of a limited liability company primarily to qualify for ESF funds—illustrates the systemic risks of path dependency on structural funds.

5.3. Theoretical Contributions

This research contributes to the theory of hybrid organisations by providing observational evidence on how institutional contexts may be associated with the relative importance of different organisational capabilities [43,44]. Whilst Western research emphasises commercial competencies and market orientation, our findings suggest that social competencies—relationship building, community engagement, and network development—may be more critical in the contexts of transition economies. Comparative evidence from EU Member States with distinct cultures further confirms that social enterprise models are shaped by socio-economic and cultural factors specific to each national context [66]. The finding that economic factors are stronger predictors of social entrepreneurship activity than social factors [75] provides an important counterbalance to mission-centred sustainability narratives.

5.4. Policy Implications

The findings generate four policy recommendations, each grounded in a specific empirical result from the analysis and contextualised within Romania’s transitional institutional setting.

Phased funding mechanisms. Cox regression identified high EU funding dependence (>50% of revenue) as the strongest predictor of organisational dissolution (HR = 2.18, 95% CI [1.24, 3.84], p = 0.002), whilst the qualitative case studies revealed that EU-dependent organisations face average inter-cycle funding gaps of 4.2 months—a vulnerability window associated with recurrent staff redundancies and governance instability. Current EU funding programmes under the 2021–2027 ESF+ cycle should include mandatory transition mechanisms that diversify revenue streams over a 3–5 year period following initial certification, replacing abrupt grant termination with graduated co-funding arrangements. This is particularly relevant in Romania, where the supply-driven creation of social enterprises under Law 219/2015 has generated structural dependence on project-based funding for a large share of the sector [15].

Regional ecosystem development. The analytical sample reveals marked geographical concentration: 19.8% of organisations operate in Bucharest-Ilfov alone, whilst rural organisations constitute only 28.1% of the sample despite representing a substantially higher proportion of development need. Network membership was associated with a 48% lower dissolution risk (HR = 0.52, p = 0.006), yet network access is structurally constrained in less developed and rural regions. Targeted policy interventions—including regional incubators, peer learning platforms, and social procurement frameworks anchored to local authority procurement budgets—are needed in areas underserved by the current ESF allocation geography, which has historically been positively correlated with regional GDP rather than development need [31]. In the Romanian context, this geographical imbalance reflects the systematic mismatch between ESF fund distribution and territorial development needs documented in the literature [54], and should be explicitly addressed in the 2021–2027 programming arrangements.

Revision of the legislative and fiscal framework. Formal governance (HR = 0.64, p = 0.04) and written strategic planning (β = 0.15, p < 0.05) are independently associated with improved sustainability outcomes in the observational models, yet only 65.3% of organisations have a functional board of directors and only 44.6% maintain a multi-year strategic plan. A revised legislative package under Law 219/2015 should create incentives for organisational formalisation—including tax benefits conditional on governance formalisation and accessible support for strategic planning—rather than focusing exclusively on certification criteria. The four institutional barriers identified in the literature [54]—the absence of operationalised responsible public procurement, dedicated national grants, reserved contracts, and fiscal incentives for employing severely disadvantaged workers—remain unaddressed and represent the highest-priority targets for legislative reform in the 2021–2027 programming cycle.

Impact measurement mechanisms. Only 28.1% of organisations in the sample have formal impact measurement systems, and adoption rates among EU-dependent organisations (18.6%) are significantly lower than among those with private funding (41.2%; χ² = 6.84, p = 0.009). This differential suggests that EU funding conditions as currently structured create indirect disincentives for impact measurement investment—prioritising project outputs over organisational learning and accountability. Standardised impact reporting requirements, coupled with publicly funded technical assistance for measurement capacity building, would enable social enterprises to demonstrate value to funders, public procurers, and corporate social responsibility partners. In Romania specifically, where most organisations rely on output rather than outcome indicators [54], this represents a structural gap that risks perpetuating the disconnect between formal growth of the social economy and genuine social impact, and requires attention in the 2021–2027 monitoring framework.

5.5. Limitations and Future Research

Several limitations must be acknowledged. Register-based sampling excludes informal social enterprises operating without certification, limiting generalisability to the formal sector. The focus on certified social enterprises excludes the wider informal social economy, estimated at 42,707 active associations and foundations in Romania [54]. The predominance of urban organisations in our sample creates a systematic under-representation of rural enterprises. The limitations of measuring social impact are also worth noting: most Romanian organisations rely on output indicators rather than outcome measures, so our assessment of social sustainability uses proxy indicators that may not capture the actual well-being of beneficiaries. Furthermore, the cross-sectional nature of the quantitative component precludes causal inference. A further and important limitation concerns potential endogeneity in the key predictors. Revenue diversification, EU funding dependence, and network membership are treated as predictors of sustainability outcomes, yet each may itself be a consequence of unobserved organisational quality, managerial capability, or prior performance. Stronger organisations may simultaneously diversify revenue and survive longer owing to unobserved competencies, rather than because diversification per se drives survival. Network membership may similarly reflect selection: better-performing organisations may be more likely to be admitted to or to seek out networks, inflating the apparent protective association. The observational design—without instrumental variables, propensity score matching, or a difference-in-differences strategy exploiting the phased implementation of Law 219/2015—does not permit the disentangling of these competing explanations. All associations reported in this study should therefore be interpreted as descriptive regularities consistent with, but not sufficient to establish, the theoretical mechanisms proposed. Future research employing quasi-experimental designs—such as propensity score matching on pre-treatment organisational characteristics, or difference-in-differences exploiting regional variation in ESF allocation—would provide stronger grounds for causal inference. The construction of the Financial Sustainability Index represents a further limitation. As an operational composite rather than a reflective latent construct, the FSI aggregates three conceptually distinct dimensions—market orientation, cost efficiency, and growth trajectory—with implicitly equal weighting in the z-score summation. No exploratory or confirmatory factor analysis was conducted to test unidimensionality, and the inclusion of a binary component alongside two continuous ratios introduces measurement asymmetry that standard reliability metrics do not fully capture. Additionally, the partial overlap between the earned-revenue ratio (a FSI component) and the HHI predictor creates a structural association between the two measures that cannot be fully resolved without either excluding the overlapping component from the index or employing a residualisation strategy. These constraints mean that the reported coefficient for HHI should be treated as an indicative association rather than a precise estimate, and that replication using alternative index specifications would strengthen the robustness of the findings. Sample composition and survivorship bias represent additional methodological concerns. The exclusion of organisations with incomplete financial reporting (N = 41) from the cross-sectional regression models, whilst partially retaining dissolved organisations in the survival analysis, creates an inconsistent estimation sample across the two analytical components. This asymmetry is methodologically motivated—survival analysis requires the inclusion of all dissolution events regardless of reporting completeness, whilst regression models require complete covariate data—but it means that the two sets of results are not fully comparable and may be subject to differential selection pressures. Furthermore, the comparisons between included and excluded organisations were limited to categorical administrative variables; financial and performance characteristics were not available for all excluded entities, leaving open the possibility of residual selection bias that the reported chi-square tests could not detect. Readers should interpret the generalisability of the regression findings with corresponding caution. The qualitative component is subject to several limitations specific to small-N comparative research. With 15 cases stratified across five dimensions, each analytical cell contains a single observation, which precludes cross-cell statistical comparison and limits the extent to which patterns can be attributed to specific combinations of characteristics rather than to case-specific factors. The six sustainability strategies identified through thematic analysis represent emergent descriptive constructs rather than tested causal propositions; their generalisability beyond the studied organisations cannot be established without further confirmatory research. Additionally, interview data are subject to social desirability bias and retrospective rationalisation, particularly regarding the strategic intentionality attributed to funding decisions and partnership development. These limitations are inherent to qualitative case study designs and do not invalidate the findings, but they counsel caution in treating the identified strategies as universally applicable prescriptions. More broadly, the theoretical framework employed in this study should be understood as primarily organisational and sociological in orientation, drawing on resource dependence, social capital, and institutional logics theories; it does not engage with formal financial modelling traditions such as capital structure theory or real options frameworks, which may offer complementary mechanistic explanations for the funding–survival relationship in nonprofit contexts and represent a productive avenue for future theoretical development. Several statistical limitations of the quantitative component also warrant acknowledgement. The Cox proportional hazards model treats voluntary dissolution and administrative removal as a single composite outcome; a competing-risks framework distinguishing these two pathways would provide a more nuanced picture of the determinants of each type of organisational exit, and is recommended for future analyses. Standard errors in both the regression and Cox models are not clustered at the regional or sectoral level, despite plausible within-cluster dependence; this may result in underestimated standard errors and inflated test statistics for the regional and sectoral predictors. The 50% EU funding threshold, whilst consistent with prior Romanian studies [28,29], is analytically arbitrary; the substantive findings are sensitive to this threshold to an unknown degree, and future research should systematically examine the association across the full continuous range of EU dependency. The Nagelkerke R² reported for the Cox model (0.38) is not accompanied by time-dependent discrimination metrics such as Harrell’s C-index or time-dependent AUC, which would provide a more complete assessment of the model’s predictive accuracy. Finally, with only 23 dissolution events across 121 organisations, the ratio of events to predictors is low, raising concerns about overfitting in the Cox model; the reported coefficients should be treated as exploratory estimates requiring replication in larger samples.

Future research should employ longitudinal designs that track organisations over extended periods to establish causal mechanisms. Comparative studies across Central and Eastern European countries would clarify which of our findings reflect dynamics specific to Romania and which reflect broader post-transition patterns. Experimental or quasi-experimental designs evaluating specific policy interventions would provide stronger evidence of causal effects. The dimension of environmental sustainability also deserves significantly greater attention from research: evidence shows that more than half of Romanian social enterprises do not understand the concepts of the circular economy [68], whilst integrating circular economy principles into the operations of social enterprises creates real benefits in terms of resilience [15,67,70,76].

6. Conclusions

Beyond the significant potential that social enterprises have for protecting vulnerable or disadvantaged social groups, the sector’s development faces persistent structural challenges. There is no integrated support framework to encourage the development of sustainable social economy activities, whilst the capacity of public institutions to support organisations serving vulnerable groups remains very limited.

This study analysed the challenges and opportunities related to sustainability for social enterprises in Romania from a multidimensional perspective, using a mixed-methods analysis that covered 121 organisations from the National Register and 15 in-depth case studies, supported by 47 interviews. The analysis confirms that the sustainability of social enterprises in Romania is, in essence, multidimensional, requiring simultaneous attention to financial, social, organisational and environmental factors. Revenue diversification emerges as the strongest predictor of financial sustainability in the analytical models (β = −0.28, p < 0.01), whilst high dependence on EU funding (>50% of revenue) is significantly associated with an elevated hazard of organisational dissolution (HR = 2.18, p = 0.002). Network participation is associated with a substantially lower hazard of closure (HR = 0.52, p = 0.006), equivalent to a 48% difference in estimated hazard rates, though this association may partly reflect the selection of more viable organisations into networks. Staff stability, formal governance and strategic planning further distinguish between sustainable and unsustainable organisational trajectories in the observational data. The qualitative analysis identifies six key sustainability strategies: hybrid revenue models, value chain integration, community embedding, adaptive leadership, strategic partnerships and effective impact communication.

Regarding the environmental dimension, the study confirms that this remains the least empirically developed area of social enterprise sustainability in Romania, with fewer than half of the qualitative case organisations reporting explicit environmental objectives. Systematic development of environmental performance indicators—including circular economy metrics—represents a priority for future work [67,68].

High efficiency in the absorption of structural funds depends on the quality of governance in general, and public administration institutions in particular. Without concrete measures to support the social economy sector—including a revised tax code, transitional funding mechanisms and targeted regional interventions—projects funded by structural funds risk generating temporary effects, without sustainable organisational outcomes. The transition from a grant-dependent sectoral identity to a self-sustaining one requires a ten-year commitment to building an ecosystem [54] and represents one of the most significant social policy challenges for Romania in the 2021–2027 programming cycle.