Social Innovation and Social Care: Local Solutions to Global Challenges

Abstract

This paper presents a case study of the Local Care Ecosystems developed by the provincial government of Gipuzkoa (Basque Country, Spain) to strengthen coordination between social services, health services, and community-based initiatives at the municipal level. The initiative seeks to personalize care, enhance service integration, and support community-based care with the overarching goal of improving the quality of life for older adults living at home. These ecosystems incorporate social, institutional, and technological innovations aimed at supporting individuals who are frail or vulnerable throughout the care cycle. At present, 18 Local Care Ecosystems are active, providing services to 1202 people over the age of 65 and 167 families. The model addresses a growing global challenge linked to population aging, which has led to increasing demand for care and support services that are often fragmented, under-resourced, and constrained by outdated regulatory frameworks. These structural issues can compromise both the quality and efficiency of care for dependent individuals. Based on the findings, the paper offers policy recommendations to support the transfer and adaptation of this model, with the aim of improving the well-being of older adults who wish to remain in their own homes.

1. Introduction

Demographic aging represents one of the main structural challenges on a global scale. The sustained increase in life expectancy, combined with declining birth rates and the transformation of family structures, has overwhelmed traditional models of care provision, both in family and institutional settings. Added to this reality are chronic limitations in public social protection systems, characterized by fragmented services, scarce resources, and insufficient recognition of care work, both formal and informal.

In this context, the paper presents the case of Local Care Ecosystems (LCE), promoted by the Gipuzkoa Provincial Council, which seeks to integrate social, technological, institutional, and cultural innovation to organize the provision of integrated services at the local and networked level, incorporating individuals into the care cycle.

Gipuzkoa is one of the three provinces that make up the autonomous community of the Basque Country in northern Spain, sharing a border with France. Its capital is Donostia-San Sebastián, a coastal city renowned for its quality of life and cultural vibrancy. With an area of approximately 1980 km², it is the smallest province in the Basque Country, but also the most densely populated. According to the most recent data, Gipuzkoa has a population of around 730,000 inhabitants, of whom more than 23% are aged 65 or older, reflecting a marked demographic aging similar to the trend observed in other regions of Europe (SIA-ADINBERRI 2022).

Far from being a technocratic recentralization or an individualized delegation of responsibilities, the Local Care Ecosystems (LCE) are conceived as intermediary spaces for the co-production of well-being, where public action, expert knowledge, citizen participation, and community action are articulated.

From this perspective, the LCE model contributes to the international debate on social care and social innovation in three essential dimensions:

An adaptive response to aging: By placing prevention, personalization, and living at home as guiding principles, LCE offer sustainable alternatives to mass institutionalization and promote more humane and dignified life trajectories for older adults.

A strategy for institutional resilience: In the face of the financial and organizational limitations of classical social services, LCE promote a more efficient and contextualized use of available resources, integrating local capacities, community assets, and social technologies.

A cultural transformation of care: By fostering co-responsibility, recognition of caregivers, and community involvement, the model contributes to a redefinition of care as a common good, overcoming its historical invisibility and feminization.

The first section of this paper offers a social innovation cycle that explains how global problems are explored to implement local solutions. The second section identifies the global problems of aging and longevity that put pressure on local environments. In the third section, the experience of the Local Care Ecosystems promoted by the Gipuzkoa Provincial Council (Basque Country—Spain) is presented. The fourth section provides the results of the Local Care Ecosystems after five years of implementation (2020–2025). The fifth section opens a space for discussion of the results. Finally, the limitations of the Local Care Ecosystems are presented.

2. Social Innovation Process: From Global Problems to Local Solutions

Social innovation can be defined as the generation of new or improved products, processes, methods, and/or services aimed at mitigating or resolving social problems (Nicholls and Dees 2015; Castro-Spila et al. 2016; Pue et al. 2016; Unceta et al. 2017). Ideally, social innovations are inclusive, participatory, and empower the individuals and social groups involved throughout the entire social innovation cycle (Chataway et al. 2014; Castro-Spila and Alonso González 2021; Alonso González et al. 2024; Arias Astray et al. 2023).

Despite these ideas, Beckman et al. (2023) point out that, in reality, it can sometimes hide existing inequalities instead of challenging them. When responsibility for creating change is shifted to local communities and social enterprises, these groups may be expected to do the work of the state, often without enough resources. This approach may be praised as “grassroots,” but it can actually support policies that reduce government involvement. Supposedly inclusive or participatory processes may also give the appearance of equal decision-making, while real power remains with established institutions. As a result, participation can become more about appearance than actual influence. Beckman and colleagues (Beckman et al. 2023) call this the “social innovation trap”: the idea that promises of new solutions can distract from ongoing inequalities. If these issues are not addressed, social innovation may end up maintaining the current power structure rather than changing it.

There are many perspectives on how social innovation and its innovative processes are defined (Edwards-Schachter and Wallace 2017). In Figure 1, social innovation is understood as an interactive and non-linear cycle in which different phases and competencies of social innovation unfold (Unceta et al. 2017).

Governance. The first stage involves structuring governance processes (cross-sector collaboration and social participation) (Baker and Mehmood 2015) that make it possible to capture the diversity of perspectives involved in a social problem, whose nature is always complex and tangled (wicked problems) (Lönngren and van Poeck 2021).

In the realm of governance for social innovation associated with care models, certain structural limitations can be identified, namely: the inflexibility of organizations, disparities in the distribution and allocation of resources, and the challenging interactions among stakeholders involved in the process.

Public institutions may play a fundamental role in establishing legitimacy and facilitating the widespread adoption of innovative practices; however, this endeavor is often hindered by bureaucratic procedures that impede the flexibility required at the grassroots level, thereby potentially delaying timely implementation in care settings (Campomori and Casula 2022).

There is a risk that participatory care initiatives end up being shaped primarily by more privileged groups—such as the middle class or well-resourced organizations—which can unintentionally marginalize vulnerable populations and compromise the principle of equity (Mulgan et al. 2007; Roth et al. 2024).

Finally, local actors may question the long-term reliability of state involvement. In contexts where electoral cycles are short and governance is fragmented, the absence of stable, long-term policy frameworks can gradually erode the resilience of community-based care systems (Borins 2001; Dolmans et al. 2023).

Exploration. The second stage of the social innovation cycle refers to the implementation of exploratory processes, which consist of applying collaborative and participatory methodologies to provide a “situated interpretation” of how global problems affect the local context. Global trends impact local or territorial areas differently and require creative and situated interpretations of their effects (Moulaert and Mehmood 2010; Van Dyck and Van den Broeck 2013). This interpretative process of local problems is structured as a “causal hypothesis,” that is, a prioritization of the central causes of a social problem in order to offer feasible solutions, according to the resources and competencies available at the local level (Unceta et al. 2016).

While the exploration phase of the social innovation cycle is often described as participatory and responsive to local conditions, in practice, it may place too much weight on what local actors are able to interpret and articulate. The concept of ‘situated interpretation’ tends to overlook how power is distributed among participants, and how local dynamics are already shaped by wider political and economic pressures (Jessop et al. 2013). There is also the issue that when causal explanations are drawn mainly from the resources and capacities already present in a given community (Unceta et al. 2016), the result may be solutions that follow familiar paths—small adjustments rather than structural change. In that sense, the exploration stage can unintentionally reinforce the very inequalities it aims to address, unless the process explicitly engages with these tensions (Evers and Ewert 2015).

Experimentation. A third stage of the social innovation cycle refers to the application of experimental or quasi-experimental methodologies (solution prototyping and testing in real-world contexts) (Castro-Spila 2018). Experimentation is key to evaluating the small-scale social impact of a solution, establishing cost-effectiveness, and measuring the degree of improvement in the quality of life and well-being of vulnerable people (Castro-Spila 2018; Castro-Spila and Alonso González 2021; Alonso González et al. 2024).

Although experimentation occupies a prominent role in the discourse on social innovation, much of the literature pays limited attention to the specific capabilities required to design, carry out, and assess pilot initiatives in practice. Developing experimental or quasi-experimental frameworks involves more than technical knowledge; it also calls for solid experience in participatory design and impact evaluation, ensuring that the prototypes developed are not only viable but aligned with the social realities in which they are situated (Voorberg et al. 2015).

Tasks like negotiation and stakeholder facilitation are not peripheral; they often become the very mechanisms that allow experimental models to function once theory meets institutional complexity. The real-world application of these approaches rarely follows a predictable path, and success frequently hinges on the capacity to navigate constraints as they emerge, rather than avoid them entirely (Ansell and Torfing 2014).

Judging the value of pilot interventions tends to be more complicated than standard evaluation procedures suggest. Common indicators—cost, efficiency, short-term effects—can certainly yield some insight, but they rarely capture the subtler dynamics that emerge over time. These might include shifts in how actors relate to one another, the adaptation of practices, or unexpected outcomes that were not part of the original objectives. For this reason, evaluators often rely on formative or developmental methods, which are specifically designed to track evolving patterns and support learning within complex systems (Patton 2011).

Innovation. A fourth stage of the social innovation cycle refers to the stabilization of social innovations and consists of a process by which innovative products, processes, methods, and/or services (projects or experimental initiatives with proven impact) are embedded in social organizations, institutions or public services, companies, universities, and local networks with the aim of improving the quality of life of vulnerable populations.

The stabilization stage means integrating social innovations into local services and organizations. This is often challenging because established interests and existing rules may oppose change (Grin et al. 2010; Smith et al. 2010). For example, new care models might face resistance from traditional service providers who fear losing control. A focus on results, especially those that appear most favorable to local authorities, can sideline less visible but valuable innovations (Jessop et al. 2013). When community projects are modified to fit bureaucratic requirements, their original spirit and community involvement may be weakened (Evers and Ewert 2015). Therefore, stabilization is a complex process that involves ongoing negotiation between community goals and institutional rules (Haxeltine et al. 2017).

Evaluation. A fifth stage of the social innovation cycle refers to the monitoring and evaluation of the social and institutional impact of social innovations (once stabilized and embedded). Monitoring and evaluation are processes that cut across all stages of the social innovation cycle. Thus, different methodologies and evaluation techniques are applied to assess governance, exploration, experimentation, innovation, and the scaling of social innovations. From the evaluation perspective, the core impact of social innovations is the improvement of quality of life and the empowerment of vulnerable individuals, as well as changes in the ways local organizations and institutions enhance their capacities for social intervention (Antadze and Westley 2012; Unceta et al. 2016; Sadabadi et al. 2022; Arias Astray et al. 2023).

Evaluation is a cross-cutting process across all stages of the social innovation cycle. The emphasis on improvements in quality of life, outcomes, and the development of institutional and local capacities (Antadze and Westley 2012; Unceta et al. 2016) risks reducing evaluation to an exercise that privileges short-term measurable results over more complex and transformative changes in power relations or systemic structures at the local level (Nicholls et al. 2015). Moreover, conventional evaluation techniques may be ill-suited to capturing the emergent and non-linear dynamics inherent to social innovation processes, in which unintended consequences and learning processes are as critical as direct impacts (Patton 2011; Haxeltine et al. 2017). Another critical issue in evaluation processes lies in the limited participation of beneficiaries and grassroots actors in defining evaluation criteria. This limitation can reproduce top-down logics and underrepresent the experiential knowledge of vulnerable groups (Bryson et al. 2011). Therefore, evaluation in social innovation should move beyond summative approaches toward reflexive and developmental methodologies that can account for complexity, contestation, and the co-creation of value within diverse social contexts (Patton 2011; Jessop et al. 2013).

Scaling out/up. A sixth stage of the social innovation cycle refers to the scaling of social innovations. Two types of scaling can be identified. The first refers to transferring or replicating (adopting/adapting) social innovations among different organizations and territories to increase the geographical reach or the number of beneficiaries. The second refers to changing structures (organizational, institutional) to sustain innovations in the long term by modifying regulatory frameworks, rules of the game, and public service funding models (Moore et al. 2015; European Union 2022).

The distinction often made between scaling out—through replication and geographic spread—and scaling up—via institutional or structural integration—has been useful as a basic framework (Moore et al. 2015; European Union 2022). Yet, this binary has also drawn criticism for failing to reflect the political and institutional intricacies involved in expanding social innovations.

The idea that a social innovation tested in one location can simply be moved elsewhere—with only minor changes—is still surprisingly common. But it rarely works that way. I have come across plenty of cases where an initiative seemed effective in one setting and then completely lost its traction when applied in another. These mismatches do not necessarily mean the innovation was flawed; often, it is the new environment that is not ready, or simply incompatible in subtle ways that are easy to miss. Smith et al. (2010) have described this phenomenon as “contextual misfits,” and it captures the problem well.

Now, if we shift to the idea of scaling up—that is, embedding innovations in formal institutions—we face a different sort of challenge. The official narrative makes this seem like a matter of steps: integrate, regulate, repeat. But institutions are sticky. Institutions are, more often than not, shaped by histories that extend well beyond their formal structures—sometimes acknowledged, but often not—and these histories come with embedded assumptions, routines, and power dynamics that resist change in subtle ways. Attempting to embed an innovation into such settings, even when driven by a genuine commitment to impact, usually means accepting a series of trade-offs. Some of these may seem minor at first, but over time, they can shift the initiative away from its original intent, diluting the qualities that made it valuable to begin with. And in the process of adapting to institutional norms or expectations, the core of what made the initiative distinct—its critical or disruptive potential—can be softened or even lost entirely (Grin et al. 2010; Avelino et al. 2019).

There is also the question of how we define “scale.” Is it numbers? Reach? Budget? Too often, the push to expand becomes a numbers game. And when that happens, the local, participatory, adaptive aspects of an initiative may be the first to get lost (Jessop et al. 2013). Just increasing user counts does not necessarily deepen impact. In fact, it can sometimes flatten it. What is gained in reach might be lost in richness.

So instead of thinking about scale as a ladder to climb, it may be more helpful to think of it as a conversation to have—one that is ongoing, shaped by context, and never really finished. That conversation includes negotiation, missteps, learning, and change. And maybe that is where the real work of innovation lies (Haxeltine et al. 2017; Avelino et al. 2019).

Finally, as shown in Figure 1, the social innovation cycle has two central characteristics: inclusion and impact. Inclusion refers to the processes that ensure that all individuals (regardless of their ethnic background, gender, disability, vulnerability, socioeconomic status, etc.) actively participate throughout the entire social innovation cycle. In this way, the social innovation cycle guarantees spaces for the active participation of people and organizations that are typically underrepresented in innovation processes. Inclusion, ensured through governance processes, allows for the integration of different perspectives on a social problem into its solution.

For its part, impact is a strategic requirement of social innovation and refers to the technical application of various methodologies that make it possible to measure and assess the degree of improvement in the quality of life of vulnerable people, the degree of enhancement of local capacities for social intervention, and the level of sustainability (cost-effectiveness) of the solutions implemented.

3. Global Problems: Aging and Longevity

3.1. Longevity and Population: Trends

Over the past century, advances in public health, improvements in lifestyles, more universal access to education, technological developments, and economic growth have radically transformed living conditions, especially in industrialized countries. As a result, humanity has achieved unprecedented longevity. Globally, in 2024, life expectancy reached 73 years, representing an increase of 8.4 years compared to 1995. This situation means that there is an ever-growing number of older adults. It is expected that the number of people over the age of 60 will reach 1.4 billion by 2030 (World Health Organization 2025).

In other words, in 2020, 9% of the world’s population was over 65 years old (around 728 million people), and this proportion will double to 16% (1.55 billion) by 2050. These changes reflect the global trend of a shifting population pyramid, that is, a decline in birth rates and a notable and growing increase in the elderly population (Jarzebski et al. 2021).

However, it is important to note certain regional discrepancies. Europe leads the demographic aging process. In 2020, its median age was 43.9 years, significantly higher than the global median of 30.9 (Jarzebski et al. 2021). In Africa, by contrast, the population remains very young. Nevertheless, the global trend—especially in countries of the global North—is toward progressive aging and inverted population pyramids, which poses a challenge for social dynamics and global economies (World Health Organization 2025; Jarzebski et al. 2021).

According to Eurostat (2024), in 2023, the average life expectancy in the EU-27 was 81.5 years, with Spain reaching the highest figure at 84 years. Thus, the Spanish context shows an even more pronounced trend, making it one of the longest-lived and most aged countries in the EU. Despite this, longevity does not always imply good health. The number of years lived with chronic illnesses or some degree of dependency has increased, raising significant challenges for the health and care systems.

In this regard, Zurynski et al. (2022) argue that while longevity represents an achievement of modern societies, it also requires rethinking the sustainability of health systems. Greater life expectancy, without adequate health promotion and prevention strategies, can result in a disproportionate increase in healthcare costs and a higher number of years lived with functional limitations (Zurynski et al. 2022).

This aging process also substantially modifies family structures, migration patterns, and the composition of the labor market. For example, in countries where fertility has been below replacement level for decades (such as Europe and some parts of East Asia), pressure on social protection systems and the labor market increases, especially regarding pensions and long-term care (Bloom et al. 2015).

Population aging should be considered not only from a statistical perspective, but also as a social construction, with all that this entails. The perception of aging as a problem depends largely on public policies, cultural values, and the institutional capacity to adapt social and economic systems to a new demographic reality. Currently, the concept of active and healthy aging is frequently used, which involves components of health, social participation, and economic security, with the aim of maximizing and maintaining well-being during later stages of life (Khan et al. 2024). Ultimately, the increase in longevity and the transformation of population pyramids is a phenomenon occurring in most countries of the global North. This phenomenon presents significant challenges, but it also opens opportunities for social innovation, the reformulation of care models, and the valorization of the social role of older adults.

3.2. Challenges for Health and Social Services

The phenomenon of aging presents direct challenges to the sustainability, accessibility, and quality of care available for a growing elderly population. Many of these individuals may experience chronic illness, functional dependency, and/or specific psychosocial needs.

As people live longer, it becomes more common for them to accumulate multiple medical conditions such as cardiovascular diseases, diabetes, dementias, and mood disorders (Khan et al. 2024). This reality poses a challenge for both primary care and health, social, and health-social services, especially when these services are not designed to provide comprehensive, personalized, multidimensional, and holistic care.

Care systems, unlike the case presented in this article, are often insufficient and fragmented. In many places, there is no adequate infrastructure to guarantee dignified and sustainable care for elderly individuals, particularly those living in their own homes. This situation leads to unwanted institutionalization, increased strain on public services, and greater burden on caregiving families (Thinley 2021).

The fragmentation of care systems reveals problems of coordination between the health and social sectors. These structures often operate independently, resulting in duplication of services, loss of information, delays in care, and frustration for both users and professionals (Zheng et al. 2016).

Additionally, the overload on family caregivers—especially women—and the lack of adequate support increase the risk of loneliness, exclusion, and deterioration in the quality of life for both older adults and their caregivers (Hernández-Padilla et al. 2021).

Loneliness and isolation are also significant issues in the global North, although they do not affect only this population group and are rather a feature of contemporary industrialized societies. Unwanted loneliness has been identified as a significant concern, even being considered a public health problem (Blazer 2020; Ding et al. 2022).

Several intrinsic protective factors in human beings can counteract loneliness and social isolation in older adults (Roy et al. 2023). Wisdom, characterized by prosocial behaviors and learned emotional regulation (Lee et al. 2019; Morlett Paredes et al. 2021), along with resilience, which involves the effective use of personal resources to overcome challenges (Madsen et al. 2019; Ribeiro-Gonçalves et al. 2023), have been shown to be protective against loneliness in recent studies. In addition, community and social factors, marital status, housing, aging in place, socioeconomic status, and the quality of personal relationships also play a role (Donovan and Blazer 2020). Recent studies highlight the importance of connections with neighbors, suggesting that the quality of social relationships at the community level can have a significant impact on the emotional health of older adults (Seifert and Hassler 2020).

Finally, the financing and sustainability of social protection and health systems are a growing concern. The increased demand for services requires a review of both public and private funding models to ensure that resources are sufficient, equitable, and efficient (Bloom et al. 2015).

3.3. Summarizing the Challenges

The main challenges for health and social systems in the context of population aging are, in summary: (1) the higher prevalence of chronic diseases and comorbidities; (2) the fragmentation and insufficiency of long-term care; (3) the lack of intersectoral coordination between health and social services; (4) the participation of older adults in the community and in the development of social, health, and health-social policies; (5) social isolation and loneliness, as well as the need to strengthen community ties; and (6) the financial sustainability of social protection systems.

4. Methodology

4.1. Research Design

This study adopts a mixed-methods approach based on a single-case design. It is, therefore, a non-experimental and exploratory study. The article focuses on the presentation and systematization of a specific model—the Local Care Ecosystems—which has been implemented across several municipalities and currently serves 1202 users, 167 family members, and 124 caregivers.

During the implementation of this model, a wide range of materials and activities has been generated, including presentations, meeting minutes, interviews, audiovisual content, and executive reports. However, the aim of this article is not to conduct a comprehensive analysis of all these materials. Rather, it seeks to document and systematize the model’s implementation, highlighting both its limitations and its potential.

The systematization process involves reconstructing the model’s internal logic—what is often referred to as its “theory of change.” This entailed an analytical effort to chronologically reconstruct the stages of implementation. Additionally, the study includes an interpretative analysis of the information collected, with the goal of making the model more explicit and extracting practical conclusions that may support its replication and transferability within the field of public policy.

4.2. Case Selection

The selection of Gipuzkoa’s Local Care Ecosystems (LCE) model as a case study is based on both strategic and contextual criteria. Gipuzkoa is a region facing significant demographic aging, which poses urgent challenges in the field of care and calls for innovative responses at the Provincial and municipal level. The region also has a well-established tradition of social innovation, characterized by collaborative initiatives involving public institutions, private actors, third-sector organizations, and community networks.

Another key consideration is the diversity of local contexts in which the model has been implemented. This variability allows for the observation of how the model functions in municipalities with different organizational structures, community networks, and institutional cultures. Such heterogeneity, combined with the model’s systematization focus, offers a valuable opportunity to explore its internal logic, assess its potential for transferability, and derive relevant lessons for the design of public policies in other regions.

4.3. Research Questions and Objectives

This study is guided by the following research questions:

• What is the internal logic and theory of change underpinning the implementation of the Local Care Ecosystems model?
• What strengths and limitations emerge from the implementation of the model in relation to its potential for replication and transfer?
• Based on these questions, the study aims to:
• Reconstruct and systematize the internal logic of the Local Care Ecosystems model, identifying its key components, phases, and implementation dynamics.

Analyze the model’s strengths and challenges in order to extract practical lessons that may support its adaptation to other contexts and its integration into public policy design.

4.4. Limitations

Local Care Ecosystems are a public initiative that has been underway for five years. Despite the progress observed in their development, several limitations can be identified that should be considered for their future consolidation:

• Limitations in data availability and digital competencies. The Interoperable Data Platform (Zaintza Datu Gunea) is a relevant initiative within the Local Care Ecosystems that enables service coordination for personalization. However, disaggregated and systematized data on the older adults served, profiles of frailty and dependency, and the distribution of support among services and actors are still not available for integration into the Platform. Another significant limitation concerns the technological capacities of public services and territorial entities within the ecosystem, which restricts the ability to achieve data interoperability. Limited digital skills among users/beneficiaries and certain professional profiles also represent a noteworthy constraint.
• Mismatch between administrative and social timeframes. Experimental projects require extended timeframes to consolidate the organizational, cultural, and relational changes they entail. However, the funding timelines for projects and the associated administrative requirements can limit experimental processes. This mismatch between administrative schedules and the temporality of social transformation processes may affect the impact of innovation initiatives.
• Uneven maturity levels of the ecosystems. Local Care Ecosystems exhibit varying degrees of development, depending on local capacities. While some territories have advanced in consolidating complex coordination and evaluation structures, others remain in early stages of reflection or exploration. This disparity presents significant challenges for both scaling and the generation of collective and transferable learning.

5. Results

5.1. Local Care Ecosystem as Local Solutions

Local Care Ecosystems offer a local solution to the global challenges of longevity. LCE develops coordination processes among social, health, and community services at the local level, as well as spaces for the participation of beneficiaries of social services, coordinating public, social, private, and citizen action around the real needs of individuals, their families, and their communities at the local level.

Local Care Ecosystems represent a good practice in the combination of social, technological, and institutional innovation, facilitating personalized care, service coordination, and the promotion of community-based care to improve the quality of life and well-being of people over 65 who are vulnerable, frail, or dependent and live in their own homes.

The main challenges for health and social systems in the context of population aging are, in summary: (1) the higher prevalence of chronic diseases and comorbidities; (2) the fragmentation and insufficiency of long-term care; (3) the lack of intersectoral coordination between health and social services; (4) the participation of older adults in the community and in the development of social, health, and health-social policies; (5) social isolation and loneliness, as well as the need to strengthen community ties; and (6) the financial sustainability of social protection systems.

In Gipuzkoa, as in the Basque Country as a whole, the care system for individuals is structured across three levels of government: the health system managed by the Basque Government (known as Osakidetza), specialized social services under the responsibility of the Provincial Government, and primary social care under municipal jurisdiction. This distribution presents significant coordination challenges, especially in the care of older adults who are dependent or vulnerable (Eusko Jaurlaritza-Gobierno Vasco 2023). Differences between municipalities in terms of scale, resources, and technical capacity, along with the absence of effective mechanisms for coordination and cooperation, contribute to the fragmentation of the care system for older adults. This lack of integration undermines continuity of care and makes it difficult to provide truly person-centered attention.

5.2. Local Care Ecosystems: An Integrated Model

A Local Care Ecosystem is defined as a space for prevention, coordination, participation, and local management of care and support networks, based on the coordination of social services, health services, health-social services, community services, and other services aimed at improving the quality of life of families and vulnerable, frail, and dependent individuals (Dessers and Mohr 2020; Uribarri et al. 2024).

Figure 2 shows the three central objectives of Local Care Ecosystems. These objectives, linked among them, are based on a person-centered model:

• Objective 1. SERVICES. Improve the coordination of social services, health services, community services, and other services to provide person-centered care and ensure continuity of care.
• Objective 2. COMMUNITY. Foster relationships among frail and dependent individuals, experts, professionals, families, and caregivers by consolidating local support networks and proximity networks.
• Objective 3. IMPACT. Promote models for monitoring and evaluating the quality of life and well-being of vulnerable, frail, and dependent individuals, as well as those considered complex cases.

Implementation of Local Care Ecosystems. Figure 3 describes the implementation process of Local Care Ecosystems, structured in different development phases.

• Governance. Multilevel governance is organized through a Steering Group at the territorial level, composed of health services, health-social services, and social services, with working groups of professionals and experts, as well as panels of users/beneficiaries of social services. The main function of governance is to activate and organize spaces for cooperation between different institutional levels and types of local stakeholders (public, private, and social), as well as spaces for the participation of users, families, and professionals to deploy the Local Care Ecosystem (exploratory, experimental, stabilization, and scaling phases). At the level of each ecosystem, these tasks are carried out by a management unit (see Figure 3).
• Exploration. Exploration within LCE aims to develop local diagnostics that interpret the global trends and challenges of aging and longevity, translating these into local conditions. This involves applying methodologies such as problem mapping, solution mapping, frailty and dependency mapping, local capacity mapping, trend analysis, and participatory future design regarding aging and longevity. These tasks are performed by each ecosystem in collaboration with the Territorial Observatory (BEHAGI/SIA-ADINBERRI).
• Experimentation. Experimentation in LCE involves implementing experimental projects that test new or improved products, processes, methods, and/or services to promote personalized care, service coordination, and community-based care, with the goal of improving the quality of life of frail and dependent individuals living at home. These tasks are coordinated by a Territorial Laboratory (Zaintza Herri Lab), which also supports the monitoring and evaluation of experimental projects developed at the local level.
• Digitalization. Digitalization in LCE focuses on deploying the Interoperable Data Platform (Zaintza Datu Gunea) for social and health data, connecting the management of public service data with local stakeholders (third sector organizations, companies, universities), and with users/beneficiaries of social services. This facilitates personalized care management and system coordination. The outcome of this phase is improved integration of social and health data for local-level services (see Figure 3).
• Evaluation and Scaling up/out. Monitoring within LCE measures the progress in personalized care, service coordination, and the promotion of community-based care. Evaluation assesses the social impact (improvement in the quality of life and well-being of frail and dependent individuals) and includes cost-effectiveness analyses to determine the sustainability of the ecosystems. These monitoring and evaluation processes are conducted in the territorial scaling laboratory (Zaintza Scaling Hub) (see Figure 3).

Scaling in LCE aims to systematize successful innovations (products, processes, methods, and/or services) to scale social innovations from one organization to another and from one territory to another. This process is carried out through the Learning and Transfer Network, in which local municipalities participate. Finally, learning processes are designed for the development of social policies and public innovation, updating the transition agenda toward a care model centered on people, coordination, and community care. These learning, transfer, and policy design processes are conducted in the territorial scaling laboratory (Zaintza Scaling Hub) (see Figure 3).

The implementation of Local Care Ecosystems in Gipuzkoa has spanned five years (2020–2025) and is monitoring based on three combined methodologies: (a) follow-up surveys with municipalities developing Local Care Ecosystems; (b) in-depth interviews with technical staff and those responsible for managing the Local Care Ecosystems; and (c) cross-evaluation workshops among municipalities with established Local Care Ecosystems. According to the data provided by the monitoring process, several key findings emerge. Currently, there are 18 Local Care Ecosystems in operation, reaching 1202 users, 167 family members, and 124 caregivers. In total, 240 territorial stakeholders have collaborated in the execution of various experimental projects.

The monitor shows the following results:

• Institutional consolidation and coordination figure. Over the five years of development, governance structures (steering committees) have been consolidated, as well as forms of participation for professionals, users/beneficiaries, and families in the deployment of the ecosystems. When municipalities establish a Management Unit, the ecosystems are more successful in energizing projects and ensuring their continuity, facilitating dialogue with the various actors and sectors involved.
• Multidimensional innovation. Most experimental projects have incorporated the three fundamental axes of the LCE model: personalization of care, improvement of service quality and coordination, and strengthening of community care. Some projects, due to their early stage or focus on specific services such as Home Help Service (SAD), have progressed unevenly across these three axes, but the overall trend is positive.
• Transferability and local adaptation. The experiences developed have demonstrated a high degree of transferability. However, it is not possible to directly replicate all projects and their results; rather, an adaptation process is required for each ecosystem, given that each municipality has specific organizational structures, community networks, and institutional cultures.
• Consolidation and sustainability. Half of the Local Care Ecosystems foresee progressive expansion, while the other half remain in exploration and experimentation phases. Sustainability depends not only on financial resources but also on the consolidation of local governance, strengthening of local capacities, and the establishment of appropriate regulatory and organizational frameworks aligned with an ecosystem-based approach to care.

It is worth pausing on some of the results, as they raise questions that cannot be answered with surface-level assessments. Take, for instance, the claim that governance and participation mechanisms have been “consolidated.” That sounds positive, but what does it actually mean in practice? Discussions around governance in the care sector often emphasize participation. The language used—collaboration, inclusion, co-decision—suggests openness. Behind these terms lies a reality that, more often than not, complicates the picture. Formal spaces like committees and advisory panels are usually created to encourage dialogue among diverse stakeholders. Still, what happens inside those spaces can vary greatly. In many cases, authority does not disappear—it simply takes another shape. Those already connected to institutions, or who are better resourced in other ways, often have more weight in setting the tone, guiding the agenda, or steering decisions. The kind of influence that plays out in these spaces is not always obvious. Influence in these spaces is not always loud or obvious. It does not need to be. Sometimes it is the person whose voice carries more weight—not because of what they say, but because of who they are, or how others have learned to defer to them. Titles, credentials, habits of deference—all of that matters, even if no one names it out loud.

And sure, others are “present” at the table. It is clear that presence is not the same as participation. When people speak from more precarious positions, their voices are often diminished—talked over, ignored, or politely set aside. This can happen so subtly that even those in the room do not notice it happening (Evers and Ewert 2015; Avelino et al. 2019).

Which brings us to a harder question. If we want to understand what Management Units are doing, it is not enough to look at who is officially involved or how the structure is set up. What actually happens in those spaces? Do people disagree and still feel safe? Can someone without institutional power shape what gets decided? These are the kinds of things that reveal whether shared governance is real—or just procedural. Are different voices being heard—not just allowed to speak, but listened to, seriously? Do they allow those without power to meaningfully shape outcomes? These are the questions that speak more directly to democratic governance in practice (Voorberg et al. 2015).

Then there is the issue of so-called “multidimensional innovation.” Referring to the LCE model here suggests that progress can be tracked neatly along three axes, but that assumption can be misleading. Some scholars have warned against using service personalization or coordination as stand-ins for deeper change. After all, a system can become more “efficient” while leaving its underlying inequalities untouched. What seems to matter more is whether innovations shift relationships, challenge hierarchies, or unsettle entrenched ways of thinking about care (Jessop et al. 2013). Not all change fits into predefined categories. Evaluation, in that sense, has to remain open—not rigidly tied to predefined metrics. What matters is not only what can be measured, but also what begins to take shape unexpectedly, as systems evolve and people adapt (Patton 2011).

As for transferring practices from one context to another, the document does acknowledge that some degree of adaptation is needed. But it does not really dwell on the tension between making a model scalable and keeping it meaningful in specific, local settings. That tension is not minor—it can fundamentally alter how a project functions once it is removed from the environment where it originally emerged. Westley et al. (2014) have shown how transplanting a model can create friction, especially when local ecosystems thrive on experimentation and autonomy. Scaling, if done carelessly, can flatten everything it touches.

And regarding sustainability—yes, governance and regulation matter. But treating sustainability as just a managerial or administrative concern misses the point. Achieving long-term change is not simply a matter of good planning. It usually involves working through political tensions, resource imbalances, and institutional patterns that are deeply ingrained and slow to change. What is often described in policy documents as “consolidation” may, in practice, look more like a continuous effort to hold onto an idea or a set of values, even as priorities shift and other agendas compete for attention (Grin et al. 2010; Haxeltine et al. 2017).

In that sense, maybe it makes more sense to treat sustainability not as something to be reached and then maintained, but as a process—sometimes messy, often uncertain—of ongoing negotiation.

In line with the above, during the year 2024, an in-depth evaluation of a Local Care Ecosystem case in the municipality of Pasaia (Gipuzkoa—Basque Country) has been conducted (Legarreta-Iza et al. 2024). The evaluation shows some limitations of local ecosystems of care: (a) At the institutional level: Local ecosystems of care require dedication and new competencies from technical staff of social services side, which can mean an administrative burden and limitations in training, affecting the stabilization of the model in the long term; (b) At the social level: Local Care Ecosystems have the vocation of promoting a co-responsible care model between men and women. The evaluation shows that progress has been made on this point, but there are still cultural barriers to improving gender equity in care; (c) At the technological level: The ELCs promote a Digital Platform for Data Interoperability. The platform facilitates accessibility to socio-health data, but there are legal limitations to facilitate access to these data by all local entities (public, private and social). These limits hinder continuity of care and coordination between systems; (d) At the level of transfer and scalability. ELCs promote scalability at the territorial level, but this depends on critical factors such as sustained funding, systematization of integrated model management tools and a regulatory framework that facilitates scalability and coordination between systems. The evaluation of the municipality of Pasaia shows that there are efforts to address these limitations but there is still a long way to go (Legarreta-Iza et al. 2024).

6. Conclusions and Discussion

The article presents a model of the social innovation cycle based on governance, exploration, experimentation, innovation, evaluation, and scaling as a framework for interpreting global problems and adapting them to the local environment. This approach involves designing and testing new or improved products, processes, methods, and/or services to address or mitigate local social problems; consolidating or embedding effective innovations; transferring those successful innovations (new or improved products, processes, methods, and/or services) to other organizations and territories; and promoting innovation within public policy and the public sector. Finally, the monitoring and evaluation of social innovations are carried out using various methodologies (quantitative, qualitative, and participatory) to assess the different stages of the social innovation cycle.

Additionally, the article introduces the comprehensive model of Local Care Ecosystems, promoted by the Provincial Government of Gipuzkoa (Basque Country—Spain), which unfolds as a process of social innovation (governance, exploration, experimentation, innovation, evaluation, and scaling), connecting social innovation with social care.

Local Care Ecosystems, structured as a social innovation cycle, represent an appropriate approach to bridging the global challenge of aging and longevity with local solutions. Several key elements can be highlighted:

• Complex cases. One of the observed global problems relates to increased life expectancy, a trend associated with a greater number of years and a higher prevalence of chronic diseases. Local Care Ecosystems promote service coordination processes to provide personalized management for complex cases.
• Service coordination. Fragmentation in long-term care services is a global issue that requires local solutions. LCE foster the coordination of social, health, health-social, and community services, offering higher-quality care strategies by providing a continuum of care.
• Community approach. In response to a marked global trend of changing family structures—one of the pillars of the care model—older adults are increasingly experiencing loneliness. Local Care Ecosystems consolidate community support networks, where older adults can take active roles in their care networks, not just recipients of care, thereby addressing the problem of unwanted loneliness.
• Centrality of autonomy. In contrast to the global trend where aging calls for models that allow older adults to maintain their autonomy—prioritizing staying in their own homes and personalizing support systems—Local Care Ecosystems aim to create technological, organizational, and relational solutions that promote independent living and active participation in the community.
• Personalization. The personalization of care is a global trend that requires promoting solutions tailored to the characteristics, resources, and culture of each individual. LCE design personalized plans and services, integrating technological tools to adjust support to each person and their environment, thereby enhancing personalization.
• Collaborative and Multi-Actor Governance. The creation of social innovation ecosystems depends on collaboration among the public sector, private sector, and civil society, generating multi-actor platforms and social experimentation spaces (“social sandboxes”) that allow for the testing and adaptation of new solutions prior to scaling. This shared governance facilitates sustainability, knowledge transfer, and the continuous adaptation of care models, guided by personalization, coordination, and community-based care.
• Innovation as a Driver of Sustainability and Equity. Demographic pressure and the growing demand for care require sustainable and equitable models, in which social and technological innovation enable the optimization of resources and guarantee the universality and quality of care. Local Care Ecosystems integrate resources, develop public-private-social partnerships, and conduct cost-effectiveness evaluations to foster public innovations that reinforce the long-term viability of Local Care Ecosystems.