Collaborative innovations, transactional relationships, and scaling. A multiple-case study of digital health platform start-ups

Abstract

Healthcare has a vibrant ecosystem of digital healthcare platform start-ups offering many innovations. However, these start-ups often struggle to scale and ensure a consistent adoption of their services by healthcare providers and patients. Scaling involves increasing the capacity and reach of platforms to handle larger user bases while maintaining performance quality and efficiency. Digital platforms are expected to scale and capture value through network effects. While digital healthcare platform start-ups successfully practice collaborative innovation to cocreate value, they often fail to build transactional relationships with their collaborators, preventing them from capturing value. This unresolved tension impedes platform scaling. Our study addresses the tension and poses the question of how digital healthcare platform start-ups can capture value from collaborative innovation. To explore this, we conducted a multiple-case study of 24 digital healthcare platform start-ups in Italy and Lithuania. We integrate open innovation and an industrial platforms framework to explain the transition from collaborative innovation and value co-creation to establishing transactional relationships with collaborators, thereby capturing financial and social value.

Headnote

Abstract

Healthcare has a vibrant ecosystem of digital healthcare platform start-ups offering many innovations. However, these start-ups often struggle to scale and ensure a consistent adoption of their services by healthcare providers and patients. Scaling involves increasing the capacity and reach of platforms to handle larger user bases while maintaining performance quality and efficiency. Digital platforms are expected to scale and capture value through network effects. While digital healthcare platform start-ups successfully practice collaborative innovation to cocreate value, they often fail to build transactional relationships with their collaborators, preventing them from capturing value. This unresolved tension impedes platform scaling. Our study addresses the tension and poses the question of how digital healthcare platform start-ups can capture value from collaborative innovation. To explore this, we conducted a multiple-case study of 24 digital healthcare platform start-ups in Italy and Lithuania. We integrate open innovation and an industrial platforms framework to explain the transition from collaborative innovation and value co-creation to establishing transactional relationships with collaborators, thereby capturing financial and social value.

Keywords: Digital Healthcare Platforms; Value Co-Creation; Value Capture; Open Innovation; Network Economic Theory; Social-Purpose-Driven Ecosystems; Scaling

JEL codes: 115; 033; L86; M31; 031

1. Introduction

This research investigates the mechanisms of value co-creation and co-capture in digital health platforms (Lo Presti et al., 2019; Nambisan et al., 2019; Kraus et al., 2021), focusing on their role within social-purpose-driven ecosystems, which are networks of stakeholders committed to achieving societal goals, such as improving public health, through innovative and sustainable practices. (Pundzienė et al., 2023). By leveraging platform (Rochet & Tirolé, 2003 ; Shapiro, 2023, and Parker & Van Alstyne, 2014 and open innovation theory by Chesbrough, 2003; Chesbrough, 2011; West & Bogers, 2013, the study explores how digital healthcare platform start-ups can capture value from collaborative innovations.

The global digital health market, valued at $175.6 billion in 20211, is expected to grow substantially by 2030. Despite these prospects, digital health platforms in the EU still struggle with sustainable integration and acceptance, exacerbated by disparities in adoption rates among healthcare providers. The challenge lies in understanding the complex interests of platform actors and formulating sustainable strategies for effective value co-creation and co-capture. While the role of collaborative innovation in fostering initial platform development is well established, the mechanisms through which platforms transition to sustainable transactional models remain theoretically underexplored, particularly within socially driven healthcare ecosystems. Understanding this critical scaling tension is essential to bridge the gap between value co-creation and effective value capture.

Fehrer et al., 2018 define the concept of value capture as a platform owner's ability to appropriate a portion of the value created within the ecosystem. Massa, Tucci, and Afuah (2017) further explain that business models involve performing value-adding activities to create and capture value. Fehrer et al. (2018) state that three critical elements of platform business models are network externalities, network complementarities, and transaction costs. Central mechanisms of value capture in platforms are igniting network effects through the multi-sided co-specialization of platform actors and reducing transaction costs among them, highlighting the importance of understanding the link between transaction costs and platforms (Fehrer et al., 2018a). Previous studies noted that "the experienced value of a private firm is primarily co-created in collaboration between a public hospital, and this triggers a change from initial value-in-use oriented practices towards appreciating first value-in-exchange oriented practices by sharing chosen resources and knowledge" (Alalaakkola et al., 2023). Put differently, it is observed that while digital healthcare platform start-ups successfully establish collaborative innovation networks to co-create value, they often fail to build transactional relationships with their collaborators, preventing them from capturing value. The study explored how digital healthcare platform start-ups can capture financial and social value from collaborative innovations. We aim to investigate how digital healthcare platform start-ups can effectively capture value from collaborative innovation by transitioning from co-creation to sustainable transactional relationships.

We adopted a multiple-case study methodology to investigate how digital healthcare platform start-ups in Italy and Lithuania capture value from collaborative innovations. The research design enabled an in-depth analysis of 24 platform-based start-ups, examining their strategies for transitioning from open collaboration to transactional relationships. Data collection included semi-structured interviews with CEOs, CTOs, and other senior executives, providing rich qualitative insights into the mechanisms driving value capture.

The study contributes to open innovation and platform literature by highlighting the critical role of early-stage financial commitment, stakeholder engagement, and the institutionalization of collaboration into formalized transactions. Furthermore, it shows the structural and cultural barriers that hinder the evolution from co-creation to value capture in socially driven healthcare ecosystems. Our findings offer practical implications for policymakers, platform designers, and industry stakeholders, presenting strategic recommendations to enhance stakeholder collaboration, optimize value capture, and promote sustainable scaling of digital health platforms.

2. Theoretical framework

2.1. Digital platforms

A platform can be defined through two theoretical lenses: economics, which views it as a double-sided market facilitating interactions between distinct user groups, and engineering design, which conceptualizes it as a technological architecture enabling modularity and integration (Gawer, 2014). Digital platforms are often multi-sided, providing interfaces with and among two or more groups of economic actors on different sides of the platform (Helfat & Raubitschek, 2018). The key elements of platform business model are platform governance and pricing structures established by the platform owner. These structures are crucial for attracting and retaining providers of complementary assets, who must be able to generate profits to remain as a platform side (Cusumano et al., 2019; Teece, 2018). However, platform business models rarely emerge fully formed, thus platform owners must navigate and align complex tasks under conditions of high uncertainty (Helfat & Raubitschek, 2018). To address these challenges, scholars have emphasized the importance of platform governance: how owners manage collaboration with third-party developers as a central mechanism for enabling value co-creation and value capture (Schreieck et al., 2021). Thus, platform theory offers a robust lens to analyze digital health platforms' structural dynamics and value flows.

Central to this theory are network effects (Tsai, 2001; Venkataramani & Chaoying, 2023), which are the added value created by each additional user of a service or product that inherently increases the utility for other users. In the context of digital health platforms, network effects can be seen in how platforms become more valuable as more healthcare providers, patients, and other stakeholders participate, thus enhancing the richness of the ecosystem (Ruutu et al., 2017; Helfat & Raubitschek, 2018)

A related branch of marketing research considers customers as co-creators in the innovation process, particularly in the context of services, where tangible artifacts like products may not be available and where the value of the service is consumed at the time of delivery (Vargo & Lusch, 2004; H. Chesbrough, 2011). This means that there often is no inventory to manage. The simultaneous provision and consumption of services may complicate the role of network effects in other industries.

The theory posits that successful digital platforms leverage these network effects to scale up and enhance service delivery (Lusch & Nambisan, 2015; Mcintyre & Srinivasan, 2016). However, aligning platform participants' diverse interests, including healthcare professionals, patients, tech providers, and regulatory bodies, is crucial for sustaining growth and effectiveness, making network economics particularly relevant to our study.

2.2. Open Innovation, Collaborative Innovations, and Open Collaborative Innovations

Open innovation is defined as "distributed innovation process that relies on purposively managed knowledge flows across organizational boundaries, using pecuniary and nonpecuniary mechanisms in line with the organization's business model to guide and motivate knowledge sharing" (Chesbrough & Bogers, 2014). Open innovation rests on the idea that not all the smart people work at organization, and managing human interaction across organizational boundaries is central to open innovation (Majchrzak, Bogers, et al., 2023). Open innovation includes external knowledge sources and paths to market as complements to internal innovation processes (A. McGahan et al., 2021).

Whereas the collaborative innovation "describes the structured joint process-for designing and developing new products, services or processes that requires information sharing, joint planning, joint problem solving, and integrated activities" (Serrano & Fischer, 2007). Collaborative innovation involves multiple external actors jointly engaging in knowledge sharing and R&D activities (Najafi-Tavani et al., 2018). By leveraging both internal and external expertise, firms can reduce innovation costs and risks, increase output diversity, and enhance performance (Baldwin & Von Hippel, 2011; Kafouros et al., 2020; Wang & Hu, 2020; Xie et al., 2022).

All open innovations are collaborative, however, not all collaborations are open innovations. The main difference lies in that the open innovation by definition is "purposeful" and "in line with the business model", thus seeking rents from knowledge flows. However, collaborative innovations would it be technical or relational can be curiosity-driven and less "purposeful". Furthermore, open collaborative innovations are "innovation project involves contributors who share the work of generating a design and also reveal the outputs from their individual and collective design efforts openly for anyone to use." (Baldwin & Von Hippel, 2011, p. 1403).

Open innovation is integral to understanding how digital health platforms harness external and internal ideas and paths to market while collaborating with various stakeholders.

In digital health ecosystems, open innovation can be operationalized through collaborations that extend beyond the conventional boundaries of the healthcare industry. This includes partnerships with technology firms, academic institutions, and even competitors. Such collaborations are essential for co-creating value and integrating diverse knowledge and resources, which are critical for the rapid iteration and scaling of digital health solutions (West & Bogers, 2013; Chou et al., 2016).

Involving stakeholders meaningfully is central to implementing open innovation strategies in digital health platforms. This involvement requires understanding and responding to each stakeholder group's expectations and needs, which is crucial for effective value co-creation (Pera et al., 2016).

2.3. Value Capture from Collaborative Innovations

Value capture refers to a firm's ability to appropriate part of the value created through innovation or collaboration (Fehrer et al., 2018; Massari et al., 2022). In the context of open innovation, the concept of value capture has evolved beyond mere appropriation to encompass a broader understanding. It is defined as "the process of securing financial or nonfinancial returns from value creation" (Chesbrough et al., 2018), highlighting that capturing value may involve both economic gains and strategic or societal benefits.

This broader concept of value capture is particularly evident in digital ecosystems, where firms seek not only financial returns but also strategic, data-driven, or societal gains through their participation and coordination of value-creating activities. This shift is largely driven by the evolution of business models, where the platforms have redefined how value is created, delivered, and captured across industries. Unlike traditional firms that rely on internal assets, platform-based models orchestrate distributed value creation by enabling interactions among multiple stakeholders (Autio et al., 2018). In this context, value capture becomes less about ownership and more about control. Platform leaders set the rules, mediate exchanges, and often appropriate a disproportionate share of the value generated by ecosystem participants. This control is exercised through platform governance mechanisms that coordinate access, participation, and the distribution of benefits across the network (Alstyne et al., 2016; Cennamo, 2021; Chen et al., 2022; Fehrer et al., 2018; Gawer, 2020).

However, scientific literature argues that effective governance must balance conflicting interests to sustain collaboration while avoiding exploitative practices (Gorwa, 2019). Platform stakeholders such as users, developers, and institutional partners contribute knowledge, capabilities, and resources that shape platform evolution. While this openness fuels responsiveness to complex societal needs, especially in fields like healthcare, it also creates ambiguity around value capture (Akter et al., 2022; Alalaakkola et al., 2023; Gleiss et al., 2021 ; Pundziene, Gerulaitiene, et al., 2023).

While collaborative innovation offers clear benefits, excessive reliance on it can diminish its effectiveness. Several challenges are highlighted in scientific literature, such as high levels of collaboration may erode a firm's core competencies (Ritala et al., 2015; Xie et al., 2022); intense collaboration can lead to information overload, complicating the effective use of knowledge and increasing coordination costs (Lee et al., 2016; Leiblein & Madsen, 2009); managing intellectual property rights becomes increasingly complex (Candelin-Palmqvist et al., 2012).

The challenge for digital platform start-ups is to convert these collaborative efforts into viable business models. Capturing value from collaborative innovations requires more than participation, it demands the institutionalization of relationships through mechanisms such as pricing, contracts, or data-sharing agreements (Gawer, 2020). Without this transition, platforms risk remaining in a state of prolonged co-creation without translating efforts into sustainable transactions.

In healthcare, where ethical, bureaucratic, and professional norms further shape stakeholder behavior, the path from collaboration to value capture is challenging (Pundziene, SermontyteBaniule, et al., 2023; R. Sermontyte-Baniule & A. Pundziene, 2021; Sermontyte-Baniule et al., 2024) Digital platforms must therefore navigate this terrain carefully, designing governance systems that support openness while enabling transparent value capture.

3. Dataset and methodology

3.1 Research design

This study adopted a multiple-case study methodology (Aberdeen, 2009 ; Eisenhardt, 1989), focusing on digital health platform start-ups operating in Italy and Lithuania. The case design particularly suited to investigate the complex dynamics through which digital health start-ups attempt to scale and capture value, enabling an in-depth examination of how different organizational strategies played out across diverse real-life settings. The approach allowed for the development of analytical generalizations and theory-building through the replication logic across cases.

The multiple-case study approach enabled an in-depth exploration of how digital health platform start-ups navigate the transition from open collaboration and value co-creation to establishing transactional relationships, essential for capturing financial and social value. The rationale for adopting a multiple-case design was grounded in the need to capture the diversity and complexity of real-world strategies across different organizational settings, reflecting the logic of analytical replication advocated by Aberdeen (2009) and Eisenhardt (1989).

Each case represented a distinct start-up operating within the healthcare ecosystems of Italy and Lithuania, selected to ensure variation in market positioning, partnership strategies, and ecosystem embeddedness. This variation was critical to developing a rich and nuanced understanding of the factors enabling or hindering the transformation of collaborative networks into stable, transaction-based relationships.

3.2. Data collection and analysis

3.2.1. Data collection

The primary data collection was based on a carefully designed sample of digital health platform start-ups in Italy and Lithuania. The sampling followed a two-step procedure to ensure relevance and diversity within the selected cases.

In the first step, we identified a preliminary list of potential start-ups using the PitchBook2 database. This widely recognized financial and market intelligence platform provides comprehensive data on private companies, including start-ups, venture capital investments, mergers and acquisitions, and financial metrics. This initial list was then refined using additional information from the Bureau Van Dijk (BvD) Orbis database, allowing us to verify corporate data such as incorporation dates, reported sales figures, and the number of employees. This dual-source approach ensured the selection of active and credible companies aligned with our research focus.

The second step applied specific selection criteria to finalize the sample. The selection included companies formally incorporated within the last five years, thus adhering to the standard definition of start-ups, or established companies that had recently launched an entrepreneurial branch or a dedicated start-up unit focused on digital healthcare platform innovation. This criterion ensured comparability across cases while capturing instances of corporate entrepreneurship, where larger firms engaged in start-up-like activities within the digital health ecosystem. Additionally, we selected an equal number of start-ups that had already generated sales and those that had not, enabling a more nuanced comparison between organizations at different stages of market validation.

Following this procedure, the final sample consisted of 24 digital healthcare platform start-ups, evenly distributed between Italy (Table 1) and Lithuania (Table 2). Italian start-ups were active in Al-driven diagnostics, hospital management platforms, telemedicine, patient support services, and digital mental health solutions. Lithuanian start-ups operated in areas such as telemedicine, patient pathway optimization, chronic disease management, Al-based diagnostics, and electronic health records.

Semi-structured interviews were conducted with founders, CEOs, C-level executives, and innovation managers directly involved in strategic decisions concerning stakeholder collaboration and value capture strategies. Interviewees held key leadership positions, including CEO, CTO, COO, and Operations Manager. The interviews varied considerably, ranging from approximately 12 minutes (e.g., LTCASE11) to over 51 minutes (e.g., ITCASE08), reflecting differences in availability, depth of responses, and organizational complexity. The average interview time was approximately 32 minutes.

All interviews were conducted via virtual call, ensuring consistency in the data collection process across all participants. Each session was audio-recorded with the informed consent of the interviewees, and all recordings are securely stored and available for verification purposes. Subsequently, the interviews were transcribed verbatim to preserve the richness and authenticity of the empirical material. All interviews were translated into English before the coding phase to ensure analytical consistency across the entire dataset. The interviews followed a flexible semi-structured protocol, allowing participants to freely elaborate on their experiences while ensuring systematic coverage of key topics, including stakeholder engagement strategies, collaborative innovation practices, mechanisms for transitioning to transactional relationships, and the main barriers and enablers encountered in scaling digital health platforms.

The diversity of the interviewees' backgrounds, industry segments, and business models provided a rich empirical basis for analyzing how digital health start-ups attempt to transition from open collaboration networks to stable, transaction-based relationships that enable financial and social value capture.

3.2.2. Data analysis

All coding activities were conducted using MAXQDA software to ensure a transparent, systematic, and auditable workflow throughout the analytical process.

The analysis followed a structured process, beginning with within-case analysis to identify individual patterns and critical incidents related to value co-creation and co-capture dynamics. Subsequently, a cross-case analysis was conducted to uncover commonalities and divergences across cases. This iterative comparison between cases allowed for identifying mechanisms, contingencies, and boundary conditions that explained why and how some start-ups successfully transitioned to transactional relationships while others struggled to capture value despite robust collaboration networks.

In line with the Gioia methodology (Gioia et al., 2013), first-order categories were developed by closely adhering to the language used by informants, followed by the abstraction of secondorder themes and the aggregation into higher-order dimensions. This analytical rigor ensured that the emerging theoretical framework was firmly grounded in the empirical material, yet capable of offering generalizable insights into the broader phenomenon of digital platform scaling in healthcare.

Overall, the multiple-case study approach provided a robust empirical basis for theorizing about the critical processes that underlie the shift from open collaboration to effective value capture, offering novel contributions to research on digital innovation, platform ecosystems, and healthcare entrepreneurship.

3.3. Sample description

The digital healthcare platforms analyzed in our study represent a diverse set of innovations across both Italy and Lithuania, showcasing distinct technological specializations, business models, market reach, and strategies for data harvesting and IP protection (Tables 3 and 4). In the Italian context, several platforms combined mathematical engineering and biosensor technologies to deliver non-invasive diagnostic solutions (ITCASE01). In contrast, others focused on creating ecosystems of interconnected health information management applications (ITCASE02). These platforms demonstrated varying degrees of market reach: some operated predominantly within the domestic market, while others had already initiated international expansion across Europe, the USA, Canada, the Emirates, and the United Kingdom.

The Lithuanian platforms similarly reflected a broad spectrum of digital healthcare innovations, including a contactless thermal imaging device and app for early detection of diabetic foot ulcers (LTCASE01), a globally used fitness motion tracking software (LTCASE02), and a psychological symptom checker operating in Africa and Asia (LTCASE03). Across both national contexts, the platforms displayed various levels of market maturity, with some focused on local deployment. In contrast, others expanded internationally, offering an analytical dimension to explore how geographical reach influences the transition from collaborative networks to transactional relationships.

The technological landscape of these start-ups highlights the innovative strategies in data harvesting and IP protection mechanisms. Italian cases often leveraged biosensors, Al-driven predictive models, and advanced software architectures to enhance healthcare delivery and diagnostics. On the other hand, Lithuanian platforms showcased strong capabilities in algorithmic analysis and medical-grade devices, facilitating early detection and telemonitoring. The international scalability of these platforms, coupled with strategic data management and IP protection, underlines their potential to transition from value co-creation to sustainable transactional relationships. Given the diversity of technological solutions and market strategies captured in the sample, it provides a robust representation of digital health innovations in Italy and Lithuania.

4. Results

4.1 Transition from Co-Creation to transactional engagements

This study, which examined 24 digital health platform start-ups operating in Italy and Lithuania, offers valuable insights into the scalability and sustainability of digital health innovations within socially driven ecosystems. The findings contribute to both theoretical advancement and the development of practical strategies for entrepreneurs, healthcare managers, and policymakers.

The research supports the theoretical assertion that strong stakeholder engagement is closely associated with perceived success in value co-creation within digital health platforms. Comprehensive and inclusive engagement strategies were found to be essential in cultivating collaborative environments that foster value creation, thereby affirming the central role of stakeholder involvement posited by open innovation frameworks. Furthermore, the analysis indicates that platforms implementing open innovation practices demonstrated a greater capacity for value co-capture. This finding aligns with theoretical propositions that emphasize the benefits of leveraging external collaborations and diverse knowledge sources to enhance competitive advantage.

Nevertheless, the study reveals that effective value capture within digital health platforms hinges on a critical transition: the progression from open, collaborative relationships to formal, transactional engagements. Several enabling mechanisms and barriers to this transition were identified through empirical analysis.

A crucial facilitator of this shift was the availability of early-stage financial resources. Startups that secured financial commitments from partners during the early phases of development were more likely to transform collaborative efforts into commercial relationships. As one CEO observed, "It was enough to have a small budget from the innovation partner for the pilot project (about 25,000€), which generated real interest " (ITCASE12). In some cases, partners actively supported the acquisition of initial funding through competitive grant programs. One interviewee remarked, "maybe it is also related to the fact that we have also received a public grant in a very newly established program, which has become very important for us"" (LTCASE01). Despite the high levels of risk, especially given the bespoke nature of the products being developed for specific partners, start-ups consistently succeeded when this funding model was employed.

Conversely, the absence of early financial engagement frequently hindered the conversion of partners into paying customers. The analysis of unsuccessful cases revealed several recurring patterns. Universities, for instance, were often deeply involved in co-creation processes, including algorithm development, prototyping, clinical trials, and ideation. As one participant noted, "That is probably the basis of the algorithm and our whole design and development of that medical device"' (LTCASE11). However, universities were rarely inclined to evolve into commercial clients. Their primary incentives remained aligned with academic goals-such as producing publications, launching spin-offs, and fulfilling third mission mandates. As one informant explained, "their only goal is to make publications, create research spin-offs, and meet ministerial criteria; they are not interested in the continuation of the life of the start-up" (ITCASE12).

A similar pattern was observed with incumbent organizations. These entities often refrained from engaging in transactional relationships, even after participating in collaborative activities. One CEO reflected, "they never want to be the first customer, the one who risks everything," noting that in over two decades of entrepreneurial experience, incumbents, especially in healthcare, exhibited a consistent reluctance to adopt innovations without prior validation from other adopters (ITCASE11). This cautious behavior aligns with the risk aversion highlighted in network diffusion models.

The study also identified challenges in collaborating with public health organizations. Even after conducting successful pilot projects, start-ups frequently encounter bureaucratic obstacles and legal constraints. As one participant explained, "those who participate in the innovation process take on the double risk: the failure of the start-up and the failure of their career if the innovation does not perform as expected' (ITCASE09). This dual risk made public employees hesitant to endorse new technologies, a situation exacerbated by rigid procurement processes and career-related concerns. Another interviewee highlighted, "when we started 5-6years ago, it was a big issue that there is just no budget line and then for the public sector it's already a problem" (LTCASE07).

Moreover, the lack of personal incentives emerged as a significant impediment to fostering transactional engagement. As one respondent stated, "a cardiologist earns the same salary whether or not they introduce a new technology in the hospital" (ITCASE02), suggesting limited motivation for individual healthcare professionals to support innovation adoption. Nevertheless, some platforms addressed this issue by offering direct financial incentives to physicians. As one informant explained, "the financial motive and some of it is obviously interesting for doctors as well, as they will make money by looking at remote data" (LTCASE01).

Bureaucratic inefficiencies also played a crucial role. Purchasing decisions were often controlled by administrative offices disconnected from clinical operations, creating a disconnect between healthcare professionals who recognized the innovation's value and the administrative systems that authorized expenditures. One participant summarized this challenge: "although a specialist might recognize the value of a start-up's innovation, the administrative office, unfamiliar with the project, blocks the procurement process" (ITCASE03).

Finally, the research uncovered a persistent cultural stigma surrounding private-sector involvement in healthcare innovation. These empirical findings underscore how transaction costs, institutional inertia, and risk aversion shape the development of digital health platforms. Specifically, they demonstrate that both real and perceived transaction costs represent critical bottlenecks that inhibit the translation of network externalities into tangible financial and social value, as theorized in network economics (Williamson, 1981). Start-up initiatives were often met with suspicion, particularly when perceived as prioritizing profit over public benefit. As one participant remarked, "there is still an ideological barrier: when a private company promotes an innovation, it is often viewed with suspicion, as ifprofit and public benefit cannot coexist" (ITCASE04). A similar perception was evident in the Lithuanian context, where innovations from private digital health companies struggled to gain legitimacy. As one interviewee noted, "Why is it small? Because it is new and plus it is being done as a commercial body, the State is doing it itself from its side" (LTCASE04).

Collectively, these findings reaffirm the relevance of open innovation and collaborative innovation in understanding the dynamics of digital health platforms. However, they also reveal that successful scaling is not solely contingent on expanding networks or promoting co- creation. Instead, it critically depends on the platform's ability to transform open collaborations into stable, trust-based, and economically sustainable transactional relationships.

By systematically examining these mechanisms, this study offers a refined conceptualization of the barriers and enablers that shape the transition from value co-creation to value capture within digital health ecosystems. The results directly address the research question and provide actionable insights into how start-ups can navigate systemic constraints and achieve sustainable growth in socially oriented yet economically limited environments.

4.2 Mechanisms of financial and social value capture from collaborative innovation

The findings (Table 5) reveal that mechanisms of financial value capture in digital healthcare platforms are interconnected with collaborative relationships established with institutional partners. Partnerships with hospitals, rehabilitation centers, and insurance providers are critical enablers for market access and revenue generation, particularly in B2B models (ITCASE01; ITCASE03; ITCASE04; ITCASE12; LTCASE07; LTCASE11; LTCASE08). However, the dependency on public and private institutional agreements exposes these platforms to significant market entry barriers, including lengthy negotiations and regulatory challenges, which can delay commercialization (ITCASE10; LTCASE06). This indicates that institutional partnerships are essential for financial sustainability, but they also add layers of complexity that need strategic navigation.

Furthermore, the role of development expertise and funding is a double-edged sword. On the one hand, collaboration with accelerators and technology providers accelerates prototyping and market entry (ITCASE03; ITCASE02; LTCASE01), while participation in public innovation programs like Horizon 2020 mitigates funding gaps in the early stages (ITCASE03; ITCASE05; ITCASE08; LTCASE06; LTCASE01). On the other hand, this reliance on external expertise and public funding raises concerns about long-term financial independence, especially if grant availability fluctuates or institutional support diminishes.

The analysis also underscores the strategic value of data as a long-term asset. Data collected through platform use is increasingly seen as a 'currency for collaboration,' especially with pharmaceutical companies for clinical trials and drug discovery (ITCASE09; ITCASE12; LTCASE01; LTCASE06). However, data monetization remains contingent on robust data privacy and regulatory compliance, which can act as both a market differentiator and a barrier to scale.

Platforms demonstrate a strong commitment to public health improvement on the social value side, with significant contributions to elderly care, cognitive testing, and rehabilitation (ITCASE07; ITCASE08; ITCASE12; LTCASE11; LTCASE10). These initiatives align with broader societal goals of healthcare accessibility and enhancement in quality of life. Nevertheless, the reliance on institutional networks for deployment raises questions about the scalability of these social impacts outside established partnerships.

5. Discussion and contribution

This research investigated how digital healthcare platform start-ups operating within socially driven ecosystems can transition from collaborative innovation networks to stable transactional relationships, enabling financial and social value capture. By integrating open innovation and network economic theories, the study explored the conditions under which platforms move beyond value co-creation to realize sustainable scaling, directly addressing the research question posed in the introduction.

The findings confirmed that although collaborative innovation remains a fundamental driver of platform development, transitioning to transactional relationships requires overcoming substantial structural and cultural barriers. As highlighted in the literature, open innovation processes (Chesbrough, 2003; West & Bogers, 2013) create opportunities for external collaborations, while network economic theory (Tsai, 2001; Helfat & Raubitschck, 2018) emphasizes the power of user growth and network effects. However, our empirical evidence showed that these mechanisms alone were insufficient for value capture.

Instead, the transition toward financial and social value capture depended critically on earlystage financial engagement from partners, management of perceived risks, and mitigating institutional and cultural barriers. Factors such as the reluctance of incumbents to serve as first customers, the bureaucratic inertia of public health organizations, and the lack of incentives for individual adopters significantly inhibited the ability to formalize collaborative relationships into sustained transactions. These findings nuance previous theoretical frameworks by demonstrating that transaction risk, career risk, and reputational concerns deeply condition how and when network effects translate into economic value.

The study thus advances existing literature by reinforcing that open innovation in healthcare ecosystems is not only a technological and organizational challenge but also an institutional one. The strategic organization of financial incentives, early pilot funding, and trust-building measures emerged as central to enabling platforms to move from open collaboration to value appropriation.

These insights suggest that digital health start-ups should prioritize securing small but formal financial commitments early in the collaboration process, identify partners with intrinsic motivation toward commercialization, and actively manage adoption risk perceptions. Policymakers aiming to foster healthcare innovation ecosystems should better consider reforms to procurement procedures and incentive structures to support early adoption of emerging digital health solutions.

This study aims to enhance the theoretical understanding of digital health platforms within socially driven ecosystems by clarifying the transition from value co-creation to value cocapture. Drawing on open innovation theory (Chesbrough, 2003; Chesbrough, 2011 b) and platform theory (Parker & Van Alstyne, 2014; Rochet & Tirolé, 2003) our findings extend existing frameworks by highlighting the critical role of early-stage financial engagement, risk mitigation strategies, and institutional adaptability in enabling sustainable value capture. While previous literature emphasizes the importance of collaborative innovation for initial platform scaling (Nambisan et al., 2019; Kraus et al., 2021), our analysis reveals that financial and social value capture is contingent on overcoming transaction barriers, aligning stakeholder incentives, and structuring formalized economic exchanges.

Furthermore, this research introduces the concept of "transactional readiness" within digital health platforms, which we define as the platform's capability to institutionalize co-created value into durable financial agreements with partners. This concept bridges the gap in the literature concerning the shift from open co-creation to value capture, emphasizing that network externalities and stakeholder engagement alone are insufficient without structured transactional mechanisms. This contribution is particularly salient for socially driven ecosystems, where public and private stakeholders often prioritize social impact over immediate financial returns, complicating sustainable commercialization (Lo Presti et al., 2019; Pundzienė et ak, 2023).

6. Conclusions, limitations, and future research

This study explored how digital healthcare platform start-ups operating within socially driven ecosystems can transition from collaborative innovation networks to sustainable transactional relationships, enabling financial and social value capture.

By integrating platform theory (Ruutu et al., 2017; Helfat & Raubitschek, 2018) and open innovation frameworks (Chesbrough & Bogers, 2014 b; Majchrzak et al., 2023), this research identified key mechanisms and barriers influencing the transition from value co-creation to value co-capture in digital health ecosystems. Platform theory emphasizes the role of network effects, where the addition of new users, such as healthcare providers, patients, and institutional partners, enhances the value of the platform for all participants (Tsai, 2001; Venkataramani & Tang, 2023). This interconnectedness facilitates richer data flows, improved service delivery, and stronger stakeholder engagement, yet it also introduces complexities in aligning diverse interests within the healthcare context (Lusch & Nambisan, 2015; Mcintyre & Srinivasan, 2016). Open innovation theory, on the other hand, underscores the importance of structured external collaborations and managed knowledge flows across organizational boundaries (Chesbrough & Bogers, 2014 b); McGahan et al., 2021) In digital health platforms, these managed interactions are crucial for integrating knowledge from diverse stakeholders, codeveloping solutions, and reducing the risks associated with innovation (Serrano & Fischer, 2007; Najafi-Tavani et al., 2018). The findings contribute to the theoretical understanding of value co-creation and co-capture in platform-based business models by demonstrating that stakeholder engagement, formalized economic exchanges, and risk mitigation strategies are critical for transitioning from open collaboration to sustainable value capture. This research also introduces the concept of transactional readiness, defined as the platform's capability to institutionalize co-created value into durable financial agreements and structured economic exchanges. This concept addresses a critical gap in the literature by highlighting that while network externalities and collaborative innovations enable growth, they do not inherently guarantee financial sustainability (Fehrer et al., 2018 b; Massari et al., 2022). Effective value capture requires platforms to overcome institutional dependencies, align stakeholder incentives, and establish clear governance mechanisms to formalize transactions, particularly in healthcare settings where regulatory and ethical constraints are pervasive (Pundziene, et al., 2023;Gawer, 2021).

Our analysis further emphasized the role of public and private partnerships in overcoming market entry barriers, highlighting data-driven strategies as strategic assets for long-term collaboration and innovation. Nevertheless, achieving stable economic exchanges often requires navigating substantial regulatory and institutional complexities, particularly in healthcare ecosystems. These insights suggest that successful digital health platforms must prioritize technological development and strategic alignment with institutional partners to secure long-term sustainability. However, the study is subject to several limitations. First, the analysis was confined to start-ups in two European countries, Italy and Lithuania, potentially limiting the generalizability of the findings across different regulatory and cultural environments. Second, the qualitative nature of the study, although allowing for rich theoretical insights, did not permit the testing of causal relationships between identified factors and platform scaling outcomes. Third, while interviews were translated carefully into English to enable consistent coding, minor nuances may have been lost, despite efforts to preserve the original meanings.

Future research could expand on these findings by conducting comparative cross-country studies to explore how national regulatory frameworks and healthcare system structures influence the transition from collaboration to transaction in digital health ecosystems. Largescale quantitative analyses would be valuable to statistically validate the critical role of early financial commitment and risk mitigation strategies identified in this study. Longitudinal research could further illuminate how transactional relationships evolve and the long-term effects of early adoption strategies on platform scalability. In addition, investigating the role of ecosystem orchestrators, such as innovation hubs, accelerators, and public-private partnerships, could provide a deeper understanding of the systemic factors that facilitate or hinder the formation of transactional business models. Finally, future studies could assess the impact of specific policy interventions, such as procurement reforms or dedicated innovation funding schemes, on the capacity of digital health start-ups to capture value and achieve sustainable scaling.

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Footnote

1 https://www.grandviewresearch.com/industry-analysis/digital-health-market

2 PitchBook. (2024). PitchBook Data, Inc. Retrieved from https://pitchbook.com