Introduction

Starting up is the most critical period in establishing a new digital health service company, and the decisions that are made during the early stages of growth have a definitive influence on a company’s success (Bennett 2016; Furlan and Grandinetti 2014). Despite massive empirical research into business growth, theoretical development has been slow (e.g., McKelvie and Wiklund 2010; Shepherd and Wiklund 2009). The early stages of business growth are mostly described using generic models. However, the latest developments are moving research towards more context-specific presentations of growth processes (Levie and Lichtenstein 2010; Muhos et al. 2010; Phelps et al. 2007). The majority of growth research has not acknowledged the qualitative and contextual differences in the growth processes of companies (see McKelvie and Wiklund 2010; Shepherd and Wiklund 2009). This paradigm shift provided a starting point for this study. The aim of this study is to clarify the management priorities as experienced by managers of the digital health service businesses in California in the critical start-up stage.

In the United States, healthcare spending is 17.2% of the gross domestic product (GDP), and an average of USD10,000 is spent annually on health care per person (OECD 2017). Because of demographic changes, increased longevity, the rising prevalence of chronic conditions and the re-emergence of infectious diseases, developed economies are challenged to ensure the sustainability and quality of healthcare service provision (European Commission 2017a). From the economic perspective, health care has never been more important than it is today. As economies shift from an industrial to a service-orientated approach (Pinto and Baracsi 2012), healthcare contributes to the rising percentages of GDPs. However, there is robust evidence for inefficiencies in healthcare (OECD 2017), and the healthcare industry lags other industries in the deployment of emerging technologies (PwC Health Research Institute 2016). These increased challenges emphasise the need for effective, scalable, sustainable, and innovative healthcare services (Rocha et al. 2013; Barnett et al. 2011; Pinto and Baracsi 2012).

Digitalisation and information and communication technologies (ICT) have been viewed as effective tools to meet the increased requirements of cost-effectiveness, accelerate efficiencies and quality improvement in healthcare systems and services (European Commission 2012; Agarwal et al. 2010; Pinto and Baracsi 2012). Moreover, digital technologies can provide tools to support the transition from hospital-based healthcare models to patient-centred models as well as improve the access to healthcare, and contribute to the sustainability of healthcare systems (European Commission 2017b). Borrelli and Ritterband (2015) pointed to an unprecedented opportunity to utilise digital technologies to prevent, assess, inform, promote, and treat health behaviours across large segments of the population. Digital technologies facilitate the development of innovations, products, and services, thus providing possibilities to restructure the business model of health care delivery (European Commission 2017a; Meier et al. 2013) and offer opportunities to build new businesses that, in a long run, improve health care sustainability (Chowdhury 2012).

According to Samuelsson and Davidsson (2009), start-ups are major factors in economic development because of their innovations and competitive pressure they produce. Start-ups are new (Sutton 2000), active, independent (Luger and Koo 2005), and pioneers in innovation (Rosenbusch et al. 2011). They typically have organisational agility, promising ideas, the willingness to take risks, and the tendency toward growth (Weiblen and Chesbrough 2015). Radical and disruptive innovations require the orientation toward experimentation and the willingness to fail (Nanda and Rhodes-Kropf 2013). However, start-ups have shortcomings regarding resources (Sutton 2000), routines, products, and the environment because they try to do something that nobody have done before (Hite and Hesterly 2001). Thus, the success rate of new start-up companies is low (Griffith 2014), and failure is an integral part of the search process (Blank and Dorf 2012). Most of the new healthcare service businesses never reach the market (Kijl et al. 2010).

Nevertheless, little is known about the critical early growth processes of newly established digital healthcare service businesses. There is a need for research on the different stages of a healthcare service development (Van Meeuwen et al. 2015). The above mentioned provides a solid starting point for the in-depth analyses of the management priorities of digital healthcare service start-up. To clarify the critical management processes of the start-ups in the context of healthcare in California, this study focuses on the management priorities of five digital health service start-ups.

Theoretical framework

Business growth has been researched from numerous viewpoints, including stochastic theory (Gibrat 1931), static equilibrium theory (Coase 1937), resource-based theory (Penrose 1959), economics of growth theory (Penrose 1959), transaction cost theory (Williamson 1975), organisational ecology theory (Hannan and Freeman 1977), evolutionary theory (Nelson and Winter 1982), strategic adaptation theory (Sandberg and Hofer 1982), motivational theory (McClelland 1961), and configuration theory (Churchill and Lewis 1983; Greiner 1972). The vast majority of research has focused on the factors that lead to growth (i.e. growth as an outcome), without acknowledging possibly considerable qualitative and contextual differences among the growth processes of firms (i.e. growth as a process) (see McKelvie and Wiklund 2010; Shepherd and Wiklund 2009). A deeper understanding of business growth processes is needed.

The current study bridges this literature gap by selecting as its starting point the perspective of growth as a process. This study represents the configuration perspective of business growth, often called the stages of growth or lifecycle perspective. Among the first researchers to use the term ‘configuration’ in this sense were Miller and Friesen (1984), who agree with Hanks and Chandler (1994) that lifecycle stages are best characterised as configurations. In these studies, the term ‘stage’ corresponds to a unique configuration of variables (e.g. priorities, problems, and strategies) that growing firms are likely to face (Miller and Friesen 1984).

Configuration studies seek to clarify managerial priorities in the early stage of business growth. The configuration perspective focuses, for example, on how managerial problems occur and how they can be addressed during the firm’s presumed growth in typical stages of development (Davidsson and Wiklund 2006). The configuration school of thought explores, describes, and explains how growth affects a company and how a growing company can be best managed (Davidsson and Wiklund 2006; Wiklund 1998).

Based on reviews of recent developments in this field (see Phelps et al. 2007; Levie and Lichtenstein 2010; Muhos et al. 2010), there is an oversupply of generic–universal models and frameworks that seek to describe the stages of firm growth. These models tend to feature a vague (or altogether absent) contextual understanding. However, focused empirical configuration models have produced consistent findings. The results of the empirical tests of Hanks et al. (1993) and Kazanjian and Drazin (1990), among those of others, provide support for the applicability of these models. It is important to understand the phenomenon of business growth within its context (e.g. business environment, industry, etc.).

Moreover, the latest developments from the configuration perspective are migrating from the deterministic ‘stages of growth’ view towards a probabilistic ‘states of growth’ view (see Levie and Lichtenstein 2010; Muhos et al. 2010; Phelps et al. 2007). According to this latter view, developmental stages exhibit no inevitable linear sequence. From the probabilistic viewpoint, a company may proceed/return from one state to another through quantum leaps, and each state has a more or less stable set of challenges and opportunities. During each quantum leap (up or down, skipping states), the set of challenges and opportunities changes.

Empirically based configuration studies have traditionally focused on technology-oriented firms. However, interest in service business growth has increased in recent years; moreover, the number of empirically based stage models that focus on service business has increased. A recent meta-analysis by Muhos et al. (2017) provides a synthesis of nine recent empirically based service-business-focused stages-of-growth models (see Auzair 2010; Empson 2012; Ferreira et al. 2011; Greiner and Malernee 2005; Masurel and Van Montfort 2006; Shim et al. 2000; Teeter and Whelan-Berry 2008; Van Tonder and McMullan 2010; Witmeur and Fayolle 2011). This meta-analysis integrates the results of these models into a four-stage framework with reference to the early stages of service-based companies. It provides a starting point for exploring context-specific perspectives. The first stage of the framework, which is the focus of this study, is Start-up – growth through market exploration and commercialisation of services.

As digital health service start-ups constitute the main focus of this study, the start-up stage of the framework serves herein as a frame of reference. According to the results of the aforementioned meta-analysis, service-based businesses typically have the following management priority areas.

  1. 1.

    Focus

  2. 2.

    Power

  3. 3.

    Structure

  4. 4.

    Decision-making systems

  5. 5.

    Strategic management

  6. 6.

    Service development and delivery

  7. 7.

    Marketing

  8. 8.

    Human resources

  9. 9.

    Growth management

These findings provide a useful frame for in-depth and context-specific studies on service businesses. The previously described framework functions as the reference framework for the current study, and we use it to analyse and reflect on the experiences of managers in the context of digital health service businesses.

Aim and methodology

A welcome trend in the academic community is the growing interest in developing a context-specific understanding rather than seeking universal solutions. Therefore, understanding phenomena in-context is becoming increasingly salient. The aim of this study is to clarify the growth management priorities as experienced by managers of healthcare service businesses in California at the critical start-up stage. Our data analysis approach devised nine central management priority areas of a service business (Muhos et al. 2017) for in-depth analysis and clarification of the early growth process of digital health service start-ups in California. There is an urgent need for an empirical understanding of the processes underlying the growth of digital healthcare start-ups. This study bridges this gap by answering the research question: What are the critical management priorities in digital health service start-ups in Southern California?

This research is a multiple case study based on a holistic research strategy (Saunders et al. 2007; Yin 1989). Compared to single cases, theory building from the findings of multiple case studies typically yields more reliable (Baxter and Jack 2008), robust, generalisable, and testable theories than single-case research does (Eisenhardt and Graebner 2007). Moreover, multiple case studies provide a stronger basis for theory building (Yin 1989), and the propositions are more deeply grounded in varied empirical evidence (Eisenhardt and Graebner 2007).

Five digital healthcare case start-ups in Southern California were analysed using the critical incident technique (CIT) and semi-structured interviews that were completed in 2015. In total, we conducted 10 interviews. For the purpose of triangulation, our data collection protocol covered three managerial viewpoints: one in company management, one in operations management, and one in marketing management. The CIT facilitates the investigation of significant occurrences (e.g., events, incidents, processes, and issues) identified by the interviewee as well as the way they are managed and the perceived outcomes (Chell and Pittaway 1998). The CIT is a flexible method, and it may be used to identify the factors that lead to successful or unsuccessful performances in divergent phases of business growth. Although the cases may be unique, types of incidents, contexts, strategies, and outcomes may be applicable to other businesses (Chell and Karatas-Ozkan 2014).

In this study, the cases are based on companies that have a digital service focus, the company’s age (less than 5 years), and its geographic location. They are typical cases (Seawright and Gerring 2008), and accessible by the time of data collection. The main characteristics of the case companies analysed are summarised in Table 1:

Table 1 The main characteristics of the case companies
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The interview frame consisted of two sections: managers’ open-ended stories of the business’s growth and detailed descriptions of the positive and negative incidents experienced during the start-up stage. The interview frame was constructed to encourage the managers first to give a broad recounting of the business growth story and then detailed their experiences on both general and specific levels.

All interviews were audio-recorded and transcribed. To improve the coding reliability and to confirm the findings, two researchers coded each transcript. The transcriptions were analysed qualitatively using an inductive approach (Crabtree and Miller 1999). All critical incidents, both negative and positive, were identified case by case.

Innovative digital healthcare start-ups occur under certain conditions, such as in the United States where the rapid growth of the digital health sector has brought together numerous incubators and investors to specialise in the healthcare sector (Pinto and Baracsi 2012). Southern California was selected as the location of the study because of its flourishing healthcare and life sciences ecosystem. In the ecosystems, companies are part of ‘loose networks of suppliers, distributors, and outsourcers; makers of related products or services; providers of relevant technology; and other organizations that affect, and are affected by, the creation and delivery of a company’s own offering’ (Iansiti and Levien 2004). The Southern California region has a significant presence of start-ups, close ties to research institutes, high funding levels of venture capital, and economies focused on the life sciences industries (JLL 2014). The United States is the global leader in research and development funding and the life sciences sector in terms of the number of patent applications. Southern California can be considered a leader in the life science industry (JLL 2014), and its dynamic ecosystem is considered conducive to start-ups (Majava et al. 2016).

Data analysis and results

In this section, case-by-case analyses of the selected start-ups are provided. In analysing the critical managerial incidents, this study seeks to clarify the management priorities in the process of starting up digital businesses in the healthcare and life-science ecosystem in Southern California. The results were drawn from interview data on the critical incidents recalled by the management teams of the selected start-ups. In the following sections, the management priorities of the selected start-ups are presented using the critical incidents as the selective lens. Cases α through ε are presented first as inductive single case analyses. Then, a deductive cross-case analysis is provided by using the nine central management priorities as a selective lens.

Case α

Case α is aimed at building more sustainable health service. The business idea was to develop a new service that could help disabled people use pre-existing technologies. Currently, the corresponding personal services, such as hiring a personal assistant, are very costly. The aim of the company was to gather a community of disabled persons and their caregivers around new products and services. This start-up’s service platform enabled remote services via the internet that promoted resource utilisation and effective consumption, which were not tied to a specific time or place.

[T]his is like we’re helping people to become independent or helping people to really enjoy the world individually.

The critical incidents are presented in Table 2 and Table 3:

Table 2 The positive managerial incidents of Case α
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Table 3 The negative managerial incidents of Case α
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Case β

In Case β, the business idea was to develop the efficient use of existing healthcare resources. Typically, large amounts of funding are needed when health science companies need funding to buy the infrastructure required to conduct experiments. At the same time, resources may not be used in another organisation. Case β provided a market platform that enabled the efficient use of physical healthcare resources as infrastructure and equipment. Case β was an intermediary service actor that matched the demand side and the supply side. From the perspective of demand side companies, service could lower the barrier to utilise available infrastructure in the right time without a large amount of invested capital.

The critical incidents are presented in Table 4 and Table 5:

Table 4 The critical managerial incidents of Case β
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Table 5 The negative managerial incidents of Case β
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Case γ

Case γ provided a digital product-service platform for the guided self-care of a chronic condition. The advanced technology-based service solution allowed patients to take care of themselves at home. Telehealth treatment provides improved and alternative ways to accomplish the provision of an effective health service to patients with a chronic skin disease. The critical incidents are presented in Table 6 and Table 7:

Table 6 The positive managerial incidents of Case γ
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Table 7 The negative managerial incidents of Case γ
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Case δ

As the mobile telemedicine application and digital service platform developed by Case δ worked through network, the platform was particularly beneficial over long distances. The start-up implemented the idea of sustainable development and met the global challenges of health care provision. In the pilot projects, the service was used in rural clinics in developing countries in Africa and South America. This platform contributed to the efficient use of resources to avoid unnecessary primary care in emergency department or specialists’ visits to villages in rural areas. Over long distances, the platform allows both the faster time to care and substantial savings. The critical incidents are presented in Table 8 and Table 9:

Table 8 The positive managerial incidents of Case δ
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Table 9 The negative managerial incidents of Case δ
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Case ε

As an intermediate actor, Case ε aimed to respond to the need for an effective recruiting of patients for medical trials. From the perspective of such patients, the start-up offered a digital solution in which the patient could find a trial and experimental treatments in aggregate form in one place. The digital solution provided information about opportunities that patients did not know existed, thus providing the freedom of choice for patients who were ready to participate in riskier than normal treatments. The critical incidents are presented in Table 10 and Table 11.

Table 10 The positive managerial incidents of Case ε
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Table 11 The critical managerial incidents of Case ε
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Cross-case analysis

The inductive single case analyses that were previously described yielded critical management-related incidents as recalled by the managers of the digital health service start-ups. The cross-case analysis of these incidents was conducted with deductive logic to synthesise the managers’ experiences by using central management priority areas that were derived from the configuration literature. The distribution of the context-specific critical incidents as recalled by the managers was condensed as shown in Table 12 (see Muhos et al. 2017).

Table 12 Managerial priorities in the cases analysed (positive incidents = +, negative incidents = -)
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The majority of the incidents fell into the predefined management priorities. The incidents that did not fall into to the predefined categories were further analysed. These incidents were found to form a relatively consistent new category that is focused on external networks to the company itself. This category is labelled as network management.

Discussion

This study opened the qualitative and contextual characteristics in the growth process of digital health service start-ups in California by clarifying the managerial priorities based on experience. This study was based on the research question: What are the critical management priorities in digital health service start-ups in Southern California? The question was answered by analysing the positive and negative incidents that the managers of the case companies experienced.

The five single case analyses yielded critical management-related incidents as recalled by the managers of digital health service start-ups. The analyses were reported in detail in the Results section. The cross-case analysis of these incidents was carried out with deductive logic, devising the nine management priority categories. The nine predefined management priorities of the reference framework apply to the classification of the majority of the critical incidents. The incidents that did not fit into to the predefined categories were further analysed. These incidents form a new category focused on network management. The condensed findings related to the management priorities of digital health service start-ups in California are presented in Table 13:

Table 13 Management priorities of digital health service start-ups in California
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As a contribution to theory, the modified framework functions as a platform (a set of propositions) for further clarification of the qualitative and contextual characteristics in the start-up processes of the digital health service market in California. Cross-case analysis of these management priority areas revealed several context-specific characteristics as explained in the following paragraphs.

First, the start-up companies in each case focused on bringing radical, disruptive innovations (see Nanda and Rhodes-Kropf 2013) to the US health service market. The risk-reward ratio was considered high. The rising percentage of health in GDPs (OECD 2017), the mega trend of digitalised health (Agarwal et al. 2010; Pinto and Baracsi 2012), and the economic shift to services (Pinto and Baracsi 2012) were experienced as promising opportunities for disruptive digital service businesses. However, with radical service innovations, the risks of failure are high due to inefficiencies (OECD 2017) of the complex, slow-to-change, highly protected and regulated health market. As these digital service start-ups aimed at creating something that nobody had done before, they faced shortcomings regarding resources, service offerings, routines, and the environment (e.g., Sutton 2000; Hite and Hesterly 2001). For example, the slow speed of deploying emerging technologies within the US health market (PwC Health Research Institute 2016) increases the risk of failure. Alternatively, radical digital service start-ups seem to have the advantage of a prolonged time of operation under conditions of limited competition (see Rosenbusch et al. 2011).

Second, fundraising was an integral part of the strategy of these digital health service start-ups. The complex digital health service market requires long service development and, in some cases, approval cycles with nothing to sell yet. The key opinion leaders were the early target group of the marketing activities for customer verification. Organic cash flow was zero or limited. These digital service start-ups (active at start-up and seed and series A–C funding phases) raised capital from a broad range of sources, including self-funding, seed capital competitions, and family and friends. Capital also came from business angels that included “super angels” (high risk-tolerance and a proven record in the health space), foundations, patient groups, large companies, and so on. These findings are similar to the findings of Ford and Nelsen (2014). The fundraising landscape for early-stage companies has changed. These start-ups need to look toward new, emerging categories of investors to provide funding that venture capital historically provided. Corporate venture funds, angels, angel networks, government agencies, foundations, patient advocacy non-profits, family offices, and hybrid funds are all investing to start-ups (Ford and Nelsen 2014).

Third, development and delivery in the complex and hard-to-access digital health service market required early specialisation in skills, time, and the systematic development approach from early experimentation to a large scale. The market required contextual understanding from the founding team and effective acquisition of capable human resources who fit the context. Specialised skill sets were acquired by freelancers, part-time staff, volunteers, outsourcing (domestic or overseas), interns, and so on. However, the core was protected building it in-house, generating a culture of involvement and ownership.

Fourth, in a complex, multifaceted, and highly protected digital health service market, network management was experienced as an integral part of success (Elfring and Hulsink 2003) and growth (Hansen 1995). Because of the lack of necessary capital and legitimacy, news needed access to external resources and expertise (Hite and Hesterly 2001). Through networking, these start-ups aimed at enhancing their early performance (Baum et al. 2000), achieving positive effects on innovation (Pittaway et al. 2004), discovering opportunities, testing ideas, and building legitimacy (Parida et al. 2010). The start-ups that were interviewed perceived that they belonged to the health and life science ecosystem in Southern California. This ecosystem supported start-ups by providing rapid access to useful networks, including university accelerator programs, start-up competitions, incubators, health sector-specialised accelerators, business angel networks, private investors, advisers, and mentors. Incubators and/or accelerators were seen as an entrance into the ecosystem of the health business. These communities provided, for example, subsidised rent, business advice, marketing assistance, and networking advice (Davidsson and Honig 2003). In terms of the success of start-ups, networking with funding actors was highlighted in all cases. These results align with Lee et al. (2001), who found that start-ups preferred networks with external actors, such as venture capitalists and venture associations.

In addition to the context-specific features, the interviews also revealed typical characteristics of start-ups (Gartner 1985). These digital service start-ups created a new digital health service under conditions of extreme uncertainty (Knight 1921; Milliken 1987; McMullen and Shepherd 2006). They had promising ideas and accepted the high risk of failure in experimenting with an idea and reaching towards a scalable business model (Weiblen and Chesbrough 2015) within their specific digital service market. Everything, including the strategies, structures, and systems of the studied digital health start-ups, were prepared for scaling. Moreover, small failures were an integral part of the search process (Griffith 2014; Blank and Dorf 2012). The context-specific characteristics of digital health service start-ups in California are presented in the Figure 1.

Fig. 1
figure 1

Context-specific characteristics of digital health service start-ups in California

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For the managers who start up a digital health service business or target this market, this study provides a useful benchmark for the typical management priorities. The empirical-based stage framework forms an effective tool for reflecting on and predicting the challenges faced during the start-up stage. Compared to other available frameworks, this study provides an in-depth, empirical-based and context-specific view of the early growth processes of the digital health service start-ups.

To conclude, this study defined the qualitative and contextual characteristics of the growth process in digital health service start-ups in California by clarifying experienced managerial priorities. The devised empirical-based stage framework seems to be a useful starting point for reflecting on and predicting the challenges faced during early development of a digital health service start-up, taking into account the context-specific features of digital health service businesses. This study revealed some context-specific viewpoints partly comparable to the findings of Saarela et al. (2018). These viewpoints suggest that companies in different contexts face culture– and context–specific issues in their early growth. The healthcare context and the essential role of radical innovation of digital health start-ups were clearly visible characteristics of the case companies. Growth is a heterogeneous process with a high variable of patterns, growth factors, and knowledge sources (Brenner and Schimke 2015). Every service-based start-up is unique.

The context of this study partly limits the research. For example, the findings of the study cannot be generalised to other countries or business contexts and depend on the time of the data collection. With replication logic, analytic generalisation (generalisation based on a theory) is possible when building context-specific frameworks that are applicable to the digital health service start-ups in California.

The qualitative and contextual differences of growth management priorities in the start-up process provide promising paths for future research. It would be interesting to compare the results of similar analyses in other countries. Moreover, the support provided by the business ecosystems to start-ups requires further examination. Finally, understanding the context-specific management priority area—network management—requires more in-depth analysis and provides an interesting topic for future research. To support digital service start-ups and remove structural and context-specific barriers to their growth, in-depth knowledge of the processes involved is required.