Enabling value-in-use with digital healthcare technologies: combining service logic and pragmatic constructivism

The term ‘customer value’ (CV) has been used to refer to both what a supplier gets from a customer (i.e., customer lifetime value) and what a customer gets from a supplier (i.e., value for the customer) (Woodall, 2003). The latter type, value for the customer (Woodall, 2003), has been framed and used in different ways. For example, as a sum of benefits and sacrifices (e.g., Hansen et al., 2008; Khalifa, 2004; Narayandas, 2005), through different ‘service-oriented’ logics Grönroos, 2008, 2011; Grönroos & Voima, 2013; Lusch & Vargo, 2014), from the customer point of view (Heinonen et al., 2010; Heinonen & Strandvik, 2015), economically and non-economically (Grönroos & Helle, 2010; Narayandas, 2005), and from both the supplier’s and the customer’s perspective (e.g., Songailiene et al., 2011). However, the term ‘value’ is too often used to mean something vague that should be pursued, which is done without providing evidence that any real value has been created or even explaining the mechanisms of the value creation. There lays still an important question about the nature of CV that service logic (SL) tries to answer: who actually creates value and who benefits from it (e.g., Grönroos 2008; 2011; 2019; Grönroos & Voima, 2013; Lusch & Vargo, 2014).

To understand these questions in the B2G context, following the logic of SL (Grönroos, 2008, 2011; Grönroos & Voima, 2013), this paper takes a step forward from assuming that CV is just something embedded as part of technology. Instead, it considers CV as something that is actively created by the customers by using the technology. One of the premises of SL is that ‘the customer is the creator of value’ (Grönroos, 2011; Grönroos & Voima, 2013), and their role is at least as significant in enabling VIU as is the supplier’s role as value facilitator (Grönroos & Voima, 2013). Instead of the supplier creating CV, the customer can allow the supplier to participate in their value creation process (Grönroos, 2011). This customer orientation of SL also states that the customer creates value with or without the supplier; if the customer allows the supplier to interact with them, the supplier might be able to influence how the customer creates value, enabling VIU to emerge (Grönroos & Voima, 2013). As such, this perspective views the change in how the customer acts when a technology, product, or service disrupts action as a key to the emergence of VIU. Since value is created by the customer it must be ‘uniquely experientially and contextually perceived and determined by the customer (Grönroos & Voima, 2013, p. 146). The provider’s role should not be undermined either, since not only can they make value propositions and define value-in-exchange, but they can also facilitate, understand, deliver, and support the creation of value as value co-creators (Grönroos & Voima, 2013). However, value can only be co-created when the supplier and the customer interact, a notion which separates the value creation into three spheres: provider, customer, and the joint sphere, as illustrated in Fig. 1 (Grönroos & Voima, 2013). This interaction does not occur only at the point of transaction; instead, historical, and future factors influence meaning creation within the communication of providers and customers (Finne & Grönroos, 2009).

There is also a temporal dimension to customer value, as it emerges as VIU and accumulates throughout the use of the technology (Grönroos & Voima, 2013). In simple terms, before the customer starts using the offering, the customer value can only be (proactively) proposed and expected. After implementation, the customer begins to realise the (factual) value as value-in-use (Grönroos, 2011). Earlier literature proposes three temporal phases, ex-ante, transaction, and ex-post customer value (Woodall, 2003), all of which include some level of interaction, whether direct or indirect, and as such, different forms of value co-creation (Grönroos & Voima, 2013). Especially with new technologies, there is limited information about the possibilities enabled by the technology and whether they are factual or not. Thus, the supplier and the customer must reach a consensus, even with limited information clouded by complexity, for there to be a purchase decision.

Grönroos (2019) also makes a distinction between what is provided and how it is provided, a perspective which holds much potential in the public sector, which is often criticised for limited consideration to how service is being provided. Since the paper considers the customer’s action as the basis for the creation of VIU, it is only natural to investigate how the customer acts, how they could act, and how they should act to achieve the potential VIU of new healthcare technologies. A healthcare context also implies the challenge of balancing health outcomes (i.e., what) and joint productivity gains (i.e., how) as types of VIU (Grönroos & Helle, 2010). As such, SL provides an approach to understanding the roles of different actors in enabling the creation of CV and emergence of VIU, but it does not explain what kind of action is required to create CV and if that action is in the interests of the actors (Lee, 2018). Therefore, the paper utilises PC to analyse how the customers can act based on the new possibilities proposed by the suppliers and if this action is in accordance with the customers’ values and facts (e.g., Nørreklit 2017a, b).

PC has been used in various management accounting studies to explain actors’ behaviour. The contexts of these studies vary from strategic management (Mitchell et al., 2013) to operational management (Laine et al., 2016), decision-making (e.g., Saukkonen et al., 2018) and organising (Korhonen et al., 2020). These issues are more related to various kinds of organisational life skills than accounting even if PC studies have been particularly active in accounting research. In the marketing literature, scholars have also attempted to understand the behaviour of customers, whether consumers, businesses, or public governmental institutions, and it has been suggested that technology can influence marketing activities from the PC perspective as well (Mattimoe & Seal, 2011). However, there is an inadequate understanding of how this occurs, especially in complex healthcare networks. Studies using PC have not yet thoroughly examined how actor-based viewpoints could support marketing literature to understand value creation. And yet, PC is an approach that focuses on the actor’s reality construction and hence could support marketing literature in its quest to understand the foundations of service performance (Wilden et al., 2017). Therefore, there is a clear purpose to exploring PC as a method theory (Lukka & Vinnari, 2014) in the marketing context: to understand how technologies can digitalize healthcare by changing the drivers for customer’s action and the resulting VIU.

PC explains that an actor’s reality construction includes facts, possibilities, values, and communication (Jakobsen et al., 2011; Nørreklit, 2017a, b; Nørreklit et al., 2006, 2010). Whereas past events are a source of facts, the future offers us possibilities. In the present moment, we can make choices regarding which possibilities to pursue based on our values and then communicate with other actors to start realising those possibilities (Nørreklit, 2017a, b). The pragmatic constructivist approach for reality construction is illustrated in Fig. 2.

According to PC, actors integrate facts, possibilities, values, and communications to construct reality. Nørreklit (2017a, b) explains that first, there must be factual basis for action, or otherwise there is no reason to assume that the action will work as expected. Second, there must be a possibility, a purpose for action, or otherwise there is no reason for the actor to act. Third, for the actor to act, they must want to act, and the possibility must be in line with their values. Fourth and finally, the actors exist with other actors; their facts, values and possibilities overlap with the facts, values, and possibilities of others. For successful construction of a common reality, actors must communicate with each other to integrate their facts, values, and possibilities. (Nørreklit, 2017a, b)

In the B2G healthcare context, PC offers a lens through which to understand the different values that guide organisational action. Prior studies that utilise PC in the public sector have addressed the ambiguity (Cinquini et al., 2017) and illusory realities (Mauro et al., 2019) caused by a complex environment with often conflicting values. In such environments, actors manage uncertainty and complexity by their actor-world relations (Heinzelmann, 2016). In the healthcare sector, studies have examined the use of non-financial performance measures (Guven-Uslu, 2017) and the differing realities among clinical and managerial actors (Guven-Uslu & Seal, 2019). In addition, implementation of technology in public organizations has challenges, such as change resistance and the rigidity of public procurement practices (Landaeta et al., 2008; Lindholm et al., 2019; Nilsen et al., 2016), which might hinder the possibilities for public healthcare providers from the perspective of creating value. Grönroos (2019, p.) highlights “that value creation and the creation of public value and service delivery are themes that seem to draw a growing interest among researchers”. As this is of key importance (Lindholm et al., 2019), there is a need for further knowledge concerning value creation in the public sector. In this paper, we intend to create such knowledge, especially concerning the digital age, and to understand how technology builds a basis for the foundations of value to emerge and ultimately for VIU to be acquired.

Pragmatic constructivism has a number of striking similarities or compatibilities with service logic, and vice versa, but the approaches also have their differences. First, both investigate subject at the same level, typically that of an individual or an organisation. However, while PC often focuses on single actors that interact through communication to realise values that are meaningful for those actors’ lives, e.g., happiness, wellbeing, even finances (Nørreklit, 2017a, b), service logic builds on this communication as series of interactions that more straightforwardly enable suppliers to co-create utilitarian value (e.g., Grönroos 2011). Interestingly, the values in PC do not directly correlate with (utilitarian) customer value or VIU. Instead, it is related to the motivation of actors as values impact and influence their intentionalities for action. For PC, utility can subjectively be a value for an actor, but it is not intrinsically valuable; rather, the values in PC are something more profound (Nørreklit, 2017a, b), e.g., love, happiness, friendship, or conservation of nature. While the customer must perceive value that is in accordance with their values to be motivated towards completing a transaction with a supplier (e.g., Khalifa 2004), CV and VIU need are often communicated as possibilities and facts.

Second, both PC and SL highlight the customer’s role, as an actor, in creating value within their own process through action. However, SL is not as focused on actors’ intentions (Lee, 2018) and behaviours (Nørreklit, 2017a, b) but rather on the nature of VIU and the role of provider and customer in facilitation, co-creation, and creation of value (Grönroos & Voima, 2013). Third, both approaches have a temporal aspect: they acknowledge that the past, present, and future are windows to understanding human action (Finne & Grönroos, 2009​; Finne & Grönroos, 2017; Nørreklit, 2017a, b). Before one verifies a fact through evidence or observation, it is only an assumption: future conditions are only proactively true (assumptions) before they are realised as pragmatically true facts (Nørreklit, 2017a, b). In all, though the approaches have their differences, the striking similarities (a focus on values and actors, temporality) will enable a combination of the two approaches. To draw on the similarities between these two viewpoints, the paper presents a combined framework that is illustrated in Fig. 3.

When combining SL with PC, it is worth elaborating on how the four elements of PC (facts, possibilities, values, and communication) can be seen from the SL point of view. First, without interaction that builds a factual basis, the provider only produces resources that have potential (i.e., possibility) to be used for value creation. As such, the provider can only facilitate the creation of value (Grönroos & Voima, 2013. The value foundation of the technology must be based on factual resources and both the supply (provider sphere) and demand (customer sphere) must be factual. Thus, the provider can provide factual resources (i.e., the value foundation referred to earlier by Grönroos 2008) and the supplier must have factual conditions. As Nørreklit (2017a, b) puts it:

There must be a factual basis for the actions. If there is no factual basis to act upon, then there is a risk that actions do not work. If the basis is fictitious, a guess, a hope or a dream or belief, then the actor cannot expect activities to function. The actor needs to know her factual resources, the factual conditions, and her abilities to act successfully. (p. 32)

Second, while the technology provider can propose possibilities enabled by the technology, VIU remains as possibility unless the customer is willing to change their value creation process according to these new possibilities (if they are factual). Examination of this VIU as a possibility that drives the creation of value is largely missing from the SL literature. Moreover, the value proposition by the technology provider must be possible, or as Nørreklit (2017a, b, p. 32) states: ‘What the actor tries to do and accomplish must be possible. She cannot realise the impossible […] If the possibilities are factual, then the action can be realised with success’.

Thus, third, definition of the process of value propositions not as ‘a feature’ to be communicated to the customer but as a process of exchanging facts and possibilities that is driven by the values of the actors is critical in enabling the transaction. During this process, the actors exchange evidence to construct facts with the aim of identifying if the proposed value, the possibility, is factual.

Fourth, to act, it is not enough that there is a factual possibility. The actor must also have an intention (willingness) to act. She must get something from it. If the possibility is realised, she will then realise the value proposition as VIU. Both actors, the technology provider and the customer, need to get value to be willing to act. From PC point of view, this means that ‘The mere fact that it is possible to do things is not a guarantee that they will be actually done. The actor must want to do it. But if doing something realises her values, then she will do it’ Nørreklit 2017a, b, p. 33).

These intentions are conveyed among actors through communication, the interaction that begins from the first contact with the customer, that ends after the ‘value delivery’ is completed and that is the domain of value co-creation. Thus, the joint sphere of value co-creation can expand depending on the depth of business relationship. It can be quite short in the case of transactional business relationships; however, it can be continuous in joint ventures or business collaborations. The firm can both offer value propositions and directly support the value creation of the customer through interaction (Grönroos, 2011):

Cooperation is organized through communication that functions as the glue that connects people. For communication to function and enable practice it must convey the integrated fact-possibility-value structure of the participating actors and enable them to form a common narrative as the basis of a common reality construction which realises the values of the actors involved. Nørreklit 2017a, b, p. 33)

Value propositions are promises of possibilities (Mouritsen & Kreiner, 2016; Nørreklit 2017a, b), and thus, they lack factual basis. One might postulate that the provider could try to increase the factual basis of the possibility, but it will remain a possibility until the customer acts and transforms it (i.e., the value proposition) into a fact (i.e., VIU). Vice versa, for the provider, a deal with the customer is only a possibility until the deal is made, after which the possibility becomes a fact.

The actors need to act (both make the purchase and implement the technology as intended) for the possibilities (value proposition) to be realised as facts (VIU). To accomplish this, they need to integrate facts, possibilities, values, and communication to perform (act) and succeed. If they still fail, there is either a lack of motivation (values), impossible possibilities, or the factual conditions and resources were illusions. To investigate this value-driven exchange of facts and possibilities, this paper investigates two cases where healthcare technology providers and their customer organizations are trying to understand potential VIU.

To approach the research questions, we wanted to be actively involved in unveiling the potential VIU and the roles, motivations, and required activities of the different actors. The paper takes advantage of two interventionist case studies Jönsson & Lukka, 2006; Lukka & Suomala, 2014; Lukka & Vinnari, 2017; Lyly-Yrjänäinen et al., 2017; Suomala & Lyly-Yrjänäinen, 2012; Suomala et al., 2014;) to directly access practices in which potential VIU is being examined. With the help of the unique access, we acquired by directly helping the practitioners (Jakobsen, 2019), the paper operationalises the central notions of PC (such as values, possibilities and intended actions) and SL (such as VIU) to the cases as its method theories (Lukka & Vinnari, 2014). The combined use of SL and PC in the interventionist case studies yields important insights to understanding VIU possible by using healthcare technologies.

Both interventions focused on analysing the potential VIU enabled by the technologies. To perform these analyses, we utilised data gathered from the cases, such as the interviews with the hospital and laboratory representatives from in the ScreenTech case and the homecare visit records in the MedTech case. In these analyses, we adopted the SL view that highlights the role of the customer in creating value (Grönroos & Helle, 2010; Grönroos & Voima, 2013). These analyses were mostly constructed by the researchers and developed iteratively in cooperation with both the suppliers and the customer organisations, between which the researcher acted as a mediator (Tiitola et al., 2020). With ScreenTech, most of the interventionist work was done ex ante implementation, by developing and iterating the accounting models for evaluating the cost impacts of the technology. With MedTech, the researcher also supported ex-post facilitation of value creation, by observing and influencing the potential robot user patient selection and by introducing tools for patient selection in cooperation with the technology supplier.

The case descriptions in this paper focus on understanding the VIU. The researchers were interested in the temporal dimension of value, the roles of different organisations and the end customers (patients) in creation of value, as well as in the transition from value as a proactively true possibility to value as a pragmatically true fact (Nørreklit, 2017a, b). Since SL focuses on supplier-customer dyads, we included the end customer perspective as part of the service of the healthcare organisations. We also know that, through pricing, suppliers already capture their share of the joint productivity gains (Grönroos & Helle, 2010). So, instead of focusing on mutual value creation between the technology supplier and its healthcare customer organizations, we mainly looked at how the customer organizations change practices to create value for themselves (i.e., public hospitals and healthcare organisations improve their practices), without forgetting the outcomes of those changes to the patient. We also utilised our theoretical framework (Fig. 3) to analyse and illustrate both empirical cases. The data consist of the interventionist work, data about current practices (both cases) and practices when technology is being used (MedTech) as well as dozens of individual events with multiple stakeholders, including detailed meeting notes and recorded meetings when possible (patient data was classified).

Our first case study is based on an interventionist research project with a biotechnology company, pseudonymously ‘ScreenTech’, that is a provider of medical laboratory diagnostics. ScreenTech is a small yet multinational company operating in the Nordics and Western Europe. The company had developed a new digital platform for performing on-demand screening of clinically relevant pathogens and aimed to successfully implement the solution in medical laboratories. Our research cooperation started in late 2018 when ScreenTech became interested in evaluating the cost-effectiveness of their new digital screening platform in different healthcare settings. Hence, the role of the interventionist researchers was to analyse the value potential of the new technology and to economically model its impact, especially from a cost reduction perspective. We were actively involved right from the start, learning as much as possible about the significance of the antibiotic resistance problem from the point of view of the case company, laboratories, and hospitals. We wanted to identify the possibilities that were enabled by the technology for each actor, how those possibilities could be translated into potential VIU and the co-creative role of each actor in transforming this potential into actual VIU. We were also trying to understand the dynamics of the investment decision-making process around screening technologies. Empirical data were gathered through research interactions, as illustrated in Table 1. Parts of this information were also used to develop the supporting cost-effectiveness models.

We held several meetings and teleconferences with ScreenTech to either gather the solution-specific information, discuss the possibilities the solution might bring or provide updates on the current progress. The main contact point in the case company was the marketing manager responsible for a cost-efficiency study. However, other company representatives were also involved, especially the research and development manager and the key account manager. We interviewed employees of a Finnish microbiology laboratory, a business that closely collaborates with a public hospital, to gain an understanding of medical laboratory values and processes as well as the potential influence of the automated screening platform in laboratories and hospitals. The researcher observed workflow in one of the laboratory units and interviewed the representatives of infectious diseases teams of two Finnish hospitals. All meetings, teleconferences, and interviews were semi-formal, and the researchers were also informally in contact with a hospital nurse who provided general insights regarding hospital practices and processes. We also interviewed hospital representatives, but interaction with the possible end customer (i.e., a patient with carbapenem-resistant Enterobacteriaceae (CRE) carriage) was difficult, and therefore was considered unnecessary. The carriage of a case of CRE manifests itself only through a positive test result, and therefore, it is difficult to identify a person that will be a CRE carrier in the future.

The second case study examines the VIU of a medicine dispensing technology in public home care (i.e., B2G). The case company, pseudonymously ‘MedTech’, is a mid-sized company that mostly operates in the Nordic countries. The MedTech case enables a more longitudinal view of how VIU emerges as part of technology deployment. The development work, conducted for over five years, examined communication, delivery, and creation of customer value at 10 different organisations in Nordic countries. The number of samples highlights the quality of the research data and provides transferability of the findings within the context. The interventionist approach enabled the researcher to examine the process of identifying possible VIU and communicating it to the customer through value propositions. It also allows for assessment of the effects and customer value based upon actual operative changes (VIU) and for investigation of possibilities for cooperation between the technology supplier and the customers to encourage value co-creation. For a list of the data gathering activities utilised with MedTech, see Table 2.

These meetings included presentation of research results from other municipalities, planning research collaboration and technology implementation, choosing end customers, observing end customer recruitment, review of performance and discussion of future expansion plans. In addition, the data was supplemented with experience from more than 100 meetings with the supplier as well as more than 2,000 individual emails and hundreds of calls regarding the case. The research data includes research notes from the meetings, a research diary and audio recordings from some events as well as samples of 7.7 million records of homecare visits of the 825 homecare patients using the medicine dispensing robot. Altogether, these materials made it possible to construct a narrative of how VIU emerges in MedTech’s network.

The ScreenTech case focuses on one of Screentech’s products that is compatible with the new digital platform and is used to screen for carbapenem resistance in hospital in-patients. Carbapenem resistance is caused by carbapenem-resistant Enterobacteriaceae (CRE), bacteria that have become resistant to nearly all available antibiotics (Li et al., 2018). Carbapenem resistance is transferable and limits treatment options, leading to increased patient morbidity and mortality, prolonged hospital stays and increasing healthcare costs (French et al., 2017). Quite understandably, CRE are considered a serious threat (Li et al., 2018; van Beek et al., 2019). As the prevalence of CRE differ significantly between countries (Albiger et al., 2015), the geographic location of the hospital is significant. In some countries, CRE are quite rare, likely due active attempts to control them. In other areas, the prevalence of CRE is already so high (i.e., the pathogen has become endemic) that it is no longer screened as there would be no point in attempting to isolate such a large number of people. Similarly, isolation of common flu patients would also be pointless; the flu, although dangerous for some, is something you can catch almost anywhere.

Somewhere in the middle is a group of countries in which the prevalence of CRE is high enough that isolation capacity in hospitals becomes a bottleneck for providing healthcare but not so high that isolation of patients would be pointless. Infectious disease professionals in each country tries their best to prevent undesirable developments (i.e., local epidemics) but must proceed in a cost-aware manner. As the antibiotics needed to treat those with CRE are much more expensive, countries have an incentive to screen patients. Thus, the case company mainly negotiated with the laboratory decision-makers who were responsible for performing the screening. However, they had to also incorporate the opinions of their customers (i.e., hospitals). As one of the laboratory chief physicians said:

We [as a laboratory] make investment decisions ourselves. But of course, we have to consider what our customers need and how much they are willing to pay for investigations. When we make investments into new investigation methods and if those imply changes in the screening protocol and the price of an investigation goes up or turnaround time changes, then we have to discuss with the hospital and other customers whether it is ok and if they are willing to pay this extra amount of money to get for example more comprehensive or faster results.

The solution developed by ScreenTech allows 48 h faster CRE screening than traditional methods that are still commonly used in hospital laboratories. In traditional methods, laboratory employees mainly manually process a sample (cultivation of a bacterial sample on a plate and seeing whether antibiotics work), while ScreenTech’s digital solution automates this process, reducing laboratory staff involvement. Shorter time-to-result provides possibilities for more timely administration of accurate treatment, thus improved patient outcomes, and gaining monetary and non-monetary efficiencies within the larger healthcare system. As a representative of the laboratory put it:

One of the most relevant ones [values] is quality so basically that the customer [hospital] can rely on those results (…). Other value is probably that we try to do things as efficiently as possible in meaning of speed and costs. We try to be as cost effective as possible.

Laboratories and hospitals base their decisions on the recommendations made by authorities and policymakers. These recommendations consider both the performance of novel screening methods and the financial capabilities of local healthcare systems. To provide better evidence in support of these decisions, a wider perspective was needed, especially considering what the faster screening could enable for the hospital and patients. One of the ScreenTech representatives explained:

Budgets in hospitals are tight, and if none can see direct savings, it is difficult; none likes to rearrange budgets. We need a way to convince the hospital management that we bring positive change. What would be helpful for us is to be able to showcase how the change from chrome agar [traditional method] to our solution impacts hospitals in terms of cost efficiency. Benefits, anyway, come on a patient level—shorter length of stay, lower mortality—and on macro-level – less spread and correct use of antibiotics.

In this way, the foundations of value (i.e., laboratory processes) could, through the VIU expected to stem from the new technology, create something that is even intrinsically valuable (i.e., macro-level health). A faster screening has the potential to significantly improve an outbreak and the quarantine practices of hospitals by providing shorter patient waiting times. It became an intricate endeavour to understand the complexity of the phenomenon under study and the numerous and varied actors, whose needs, values, and possibilities had to be considered. ScreenTech would need to understand both the potential VIU enabled by the new digital solution and the roles each of the actors play in co-creating that value. The specific context and conditions of the customer laboratory and the hospital would affect how the different elements of VIU would emerge. For example, a single positive test result might trigger a renewal of the whole service system if it shows the possible weak points of CRE prevention. An unrelated case in the Nordics showed that CRE could transmit via surfaces with no person-to-person contact (van Beek et al., 2019). This discovery could further alter the facts (e.g., regulation) regarding how healthcare providers should prevent CRE outbreaks and which kinds of technologies could be of help. One of ScreenTech’s representatives highlighted that:

We need to know each customer perfectly well to be able to identify what would be of interest to them and adapt our proposition to them. The benefits proposed to customers are not always the same. It really depends on the customer and their expectations, the history of the customer with carbapenems—for example, have they had an outbreak already or not? So, we adapt our proposition to each customer to make sure that our offering will have an impact on the customer.

Figure 4 shows, through the lens of PC, the key aspects of reality integration of ScreenTech and its customer laboratories. As shown, both ScreenTech and their laboratory customers would have to integrate their reality constructions by sharing their views on facts, possibilities, and values for the laboratories to have an incentive for purchasing and changing their operations (i.e., change laboratory screening process, quarantine practices and outbreak management plan) for VIU to emerge. Despite the technology’s ability to deliver earlier screening results, the deployment of the new automated solution in the medical laboratories was not straightforward. First, the laboratories were already able to perform the manual screening for CRE, and hospitals already had practices in place to handle patients suspected of CRE carriage. Such conditions were facts that challenged the introduction of a new screening technology that remained a possibility. Second, many healthcare institutions, in their investment decision-making, favoured lower direct costs over more indirect and intangible long-term cost savings potential. ScreenTech’s higher-cost solution has potential to be cheaper over time, but this remains only a possibility until they can prove that the VIU has a factual basis. Thus, whether the improved screening quality and speed, and the possibilities in reorganizing hospital quarantine practices would be enough to justify the price of the technology depended on the values of the decision-makers. However, ScreenTech could use their understanding of VIU to provide increased factual basis for the more intangible possible VIU, such as the changes in the local epidemic outbreak management practices of hospitals. Third, there was no universal protocol for handling patients suspected of CRE carriage. Hospitals in different countries or regions would adopt various practices that might impact perception of the VIU enabled by the technology. Finally, there were several actors involved in deciding to change the screening method, which makes the process very complex. Thus, the implementation of a new solution would not only have to be justified in terms of the screening time reduction but also required revisiting current routines and adjusting the protocols to the new integrated reality constructions.

By applying the SL lens in the ScreenTech case, we were able to examine not only what the technology is able to achieve (faster screening) but also what kind of changes were possible in the operations of both laboratory (screening process) and hospital (quarantine and outbreak management). These changes would improve the VIU enabled by the technology, not only for the laboratories but also for hospitals and for patients. The PC perspective then enabled us to better understand how the technology and the changes it enables are linked to the reality construction of different actors as well as what kind of steps would be necessary to help the involved actors to take appropriate actions and enable VIU.

Homecare is typically arranged for patients who can live at home but cannot manage their daily tasks independently. They sometimes have challenges completing some physical activities, such as showering, cleaning, or preparing food. Other times, their cognitive capabilities have reduced to the extent that, while they would be physically able to perform these activities, they cannot remember to act, or how to act. Since there are a variety of different scenarios in which some kind temporary or long-term help is required, the variance among homecare patients and their needs is rather high. One of these activities, which does not require high coordination but is easy to forget, is medicine administration.

There are several approaches to how homecare nurses administer medicine to the elderly. The simplest solution are manually refilled medicine containers with multiple slots per day for doses of medicine. Depending on the condition of the patient, the home care nurses either support, coordinate, or control medicine administration. Until recently, many homecare organisations still used these weekly containers to facilitate this task, but the manual refill was work-intensive and prone to errors. However, during the last decades, an automated dose dispensing (ADD) service started to gain a foothold in the Nordic countries (Sinnemäki et al., 2017). The service pre-packaged prescription medicine in sachet rolls, with each sachet containing a dose of medicine (in some cases, large doses had to be divided among multiple sachets). These ADD rolls helped to significantly reduce medication errors, but elderly patients still often required reminders to take the medicine. For this purpose, MedTech developed a medicine dispensing robot that reminds the patient and administers the required medicine.

The medicine dispensing robot helps patients take the right dosage of the right medicine at the right time. The right medicine is ensured by electronic prescriptions that are checked by the ADD provider for drug compatibility. The right dosage is ensured by the ADD service, which packages each dosage in the roll of sachets according to the prescription of the patient. Finally, the right time is ensured by the robot, which utilises the information on the sachets to coordinate the dosing by reminding the patient to take their medicine. In this way, the robot ensures a high level of medicine adherence. To keep the medicine dispensing robot operational, it only needs to be filled with new sachet rolls every second week. Moreover, the robot is connected to a telecare system that is used to enable communication among the robots and the homecare nurses, as well as by MedTech to ensure that each robot is operational. Before this robot was invented, these sachet rolls were stored in a box, in which only the latest sachets were visible to the patient. However, this was not always robust, and oftentimes part of the medicine sachets could be found inside or around the box. Even more often, the sachets were forgotten between visits. There was also no way to ensure that the patient did not take several sachets at the same time or at the wrong time. Building upon this ADD service, MedTech takes the medicine administration further by having the robot dispense the sachets at the right time, increasing control at the patient level.

The medicine dispensing robots can alter both the outcomes and the process of the medicine distribution service. The robot can achieve around 99% medicine adherence by controlling the sachet distribution. To ensure the same level of medicine adherence, home care would require multiple visits per day. This is rarely the case, unless the patients have medicine critical for their health, such as pain medicine or Parkinson’s medicine, that requires a high level of control. In the less than 1% of cases where medicine adherence is not achieved, the robot alerts the home caregivers that something has gone wrong, and the caregivers can act accordingly. Thus, the actual benefits come from being able to improve medicine adherence while also being able to alter the service process.

Contrary to general belief, short medicine reminder visits are not always favoured by the homecare patients. By automating these medicine administration visits, most patients can independently take their medicine, which can help them regain some of the autonomy lost when they were considered no longer able to take care of their own medication. They regain ability for self-service, even if it is supported by technology, making some patients seem more proactive. According to the caregivers, this increased autonomy has been well received by some patients, and they have also noticed an improvement patient well-being. One of the caregivers described the increased autonomy of their patient as follows:

Typically, when we were visiting her, she had hardly woken up and was confused during the visit. Now she is already waiting for us and has often brewed us some coffee.

As this quote implies, value could be captured in utilitarian (care effectiveness) as well as more profound ways (patient health). While the medicine adherence and patient well-being are the focus point of the robot, the homecare has to justify these improvements to the municipalities through sufficient cost savings. The increased autonomy and improved medicine adherence that have been reported are both goals of the ‘dignified aging’ programs of municipalities. At the same time, a fleet of robots can become expensive, and municipalities often request clear reports of cost savings. As described by a director of elderly care in one of the municipalities:

We [homecare management] and the caregivers would like to keep [the robots], but we need to show cost savings to justify the price. Otherwise, I won’t be able to convince [the municipality] to add the robots to our budget.

From the service perspective, these robots can help the homecare organisation redesign the care of patients as well as redirect workload to patients with more demanding needs. Based on the data analyses conducted with the care organisations, we found four different ways that the robots can be used to reduce the care workload. First, during rush hours in the morning and evening, the robot removes the time criteria for some of the visits, thus enabling caregivers to visit the customer during more flexible hours. Second, some of the medicine administration visits are no longer necessary and can be removed or combined. Third, in some cases there are some minor signs that the patient’s medication will require higher workload in the future, which can be delayed through use of the robot. Finally, the improved medicine adherence should reduce the risk of surprising health-related events, such as hospitalisation. All four sources of workload reduction can be achieved simultaneously to varying degree and can help the homecare managers justify the monthly price of the medicine dispensing robots to the municipality. Figure 5 presents how these different elements and the outcomes enabled by the dispensers fit into the reality construction of the technology supplier and the customer homecare organisations.

Figure 5 provides a general overview of the motivation for action for both the supplier and the customer. The medicine dispensing robot by MedTech can help homecare resolve many of their challenges by altering the nature of how care is arranged. Thus, there is potential for a win-win situation, which explains the interest shown by municipalities. However, it is apparent that this supplier-customer service logic dyad is insufficient to explain the whole picture, as municipality actors and the homecare patients themselves are important actors in the whole service network. Moreover, the snapshot provides only an overview of the motivations of the supplier and customer actors, and it does not show how these intentions evolve throughout the implementation of the technology. By taking the longitudinal perspective, we identified five major steps where significant change occurs in the reality integration of the homecare customers during the technology implementation.

First, the snapshot shows the scenario before the deal, where VIU remains a possibility. Here, negotiations with the municipality and homecare are ongoing and the supplier can only use the facts they have acquired from previous experiences to provide a proposition of value. MedTech took the time to document the impact and customer experience of their first pilots to obtain factual basis for the value proposition. Further, each time they do this sort of value assessment with new customers, the factual basis strengthens. A deal will only be made after the municipality is convinced of the possibilities of the technology. When MedTech was still a start-up, many municipalities approached the implementation through a pilot project to evaluate if the possibility of VIU was factual or only an illusion. After they documented the results of prior implementations, the technology started to diffuse more quickly, and nowadays, MedTech has been able to move past pilots and into larger-scale deployments.

Second, once a deal was made, it became the task of the homecare managers and caregivers to select the patients with whom the dispensing robots should be implemented. Communication played an important role here, as the decision to implement was typically made by municipalities and sometimes the homecare caregivers first heard about the technology in the patient selection session. If the homecare was not familiar with the technology beforehand, they needed support from MedTech to identify prospective patients. As such, MedTech has put much effort into helping homecare organisations identify patients with whom significant operative changes could be possible as well as into redesigning care after implementation. The integration of the factual contexts of each patient with the factual resources of MedTech allowed for identification of possibilities with specific patients. Moreover, it was critical for the caregivers that the dispensing robots would help the patients, while the homecare managers emphasized the need to exhibit cost savings to the municipality. Thus, the most promising patients were those with whom both goals were possible, and if only one of these goals seemed possible, a higher emphasis was put on the judgement of caregivers. Some caregivers were more open to the technology than others, and sometimes there were also varying opinions about the implementation of the dispensing robot with specific patients. From MedTech’s point of view, it helped that the technology was rather easy to deploy and re-deploy if needed, so homecare could try it with a potential patient without altering the care right away.

Third, once a medicine dispensing robot was deployed with a homecare patient, the care organisation still needed to actively reconsider the care planning and redesign the care. Without redesign, the medicine dispensing robots, at best, only help to alter medicine adherence (i.e., what) without gaining the possibility for cost savings through a redesigned workload (i.e., how). Typically, caregivers delayed redesigning care to see if the patient would get used to the dispensing robot. This period illustrates the reality integration of the caregivers and homecare patients. If everything goes well and the homecare can redesign the care, the expected possibilities of care redesign become factual and VIU emerges for the homecare organisation. If the redesign proves unsuccessful and the caregivers return to the prior form of visits, this is an indication that the possibility was an illusion, either because some of the conditions of the patient were not factual or because there was something wrong with the dispensing robot and its factual basis was an illusion. For example, the care organisations sometimes realised that there were other tasks, such as putting on support stockings or giving insulin injections or eye-drops, that did not enable caregivers to remove or reschedule visits.

Fourth, once the fleet of dispensing robots was deployed and the care of patients redesigned, the municipalities still expected a report on whether the dispensing robots ‘were able to reduce costs’ (while this was the way it was typically discussed, the concept of robots creating value by themselves is not in accordance with our empirical findings and service logic). The problem was that neither homecare nor even the municipalities had the resources or the expertise to start evaluating the VIU enabled by the dispensing robots, which is where the intervention of the researcher came in. By documenting the changes in care ex-post and discussing the technology and its implementation with the homecare representatives and homecare patients, MedTech was able to identify many of the mechanisms through which VIU emerges and for whom. Finally, it was also quickly realised that, as the condition of elderly homecare patients deteriorates over time, the care redesign would be temporary, resulting in a need to actively evaluate and manage the fleet of dispensing robots over time. This also meant that the VIU is temporary and dynamic and will disappear when the patient moves away from home care.

These two in-depth interventionist cases help us answer how healthcare providers can enable value-in-use with digital technologies in complex healthcare service contexts. The two cases illustrated the differences among the contexts of various healthcare providers (laboratories and homecare), and while both cases were in Nordic countries, the healthcare setting, the technology, and the nature of care were still different. The two cases expand upon each other, highlighting both some of the differences and some of the similarities related to VIU and the digitalizing of public healthcare practices. While provision of better health and more efficient service remains the purpose of healthcare digitalizing in both cases, the mechanisms through which VIU emerged are different. Overall, the SL perspective identifies the actors and their roles in value creation [i.e., what and how by Grönroos (2019)], while the PC perspective explains how VIU can emerge and what motivates actors to either facilitate, co-create or create value or not (i.e., why).

In the healthcare context, VIU can emerge for both the patient as well as for the healthcare provider concurrently. In our case, we were more interested in the VIU for the healthcare provider (stemming from how) while not compromising the care of the patients (what). In the ScreenTech case, the laboratory test results could become more accurate (what), but the result could also be acquired much sooner (how). This could enable hospitals to redesign their quarantine practices to better manage potential outbreaks (how). In the MedTech case, the homecare organisations were able to provide their patients the same or even higher medicine adherence and improved autonomy (what) while reducing and rescheduling workload or preventing workload from increasing (how). The approach to VIU suggested by Grönroos (2019) thus helped us define VIU is in each context and understand how it manifests. While what is being provided mostly impacts the patient, how healthcare service is provided even after digitalization can impact both the patients as well as the healthcare providers in various ways. These possible VIUs were also in accordance with the general values of interviewed healthcare actors in providing care efficiently and effectively.

Furthermore, the more longitudinal view of the MedTech case enabled us to observe the evolution of VIU, which highlighted both possibilities and the challenges and ambiguities related to long-term use. In both cases, there was a threshold where new screening devices or a new medicine dispensing robots would no longer help a healthcare provider enable anymore VIU or at least enough to justify the cost of the technologies. With MedTech technology, the fleet of medicine dispensing robots also would benefit from active management as new patients arrive and old ones move on to more intensive level of care. The cases and the combination of PC and SL helped us understand the foundations of value (Wilden et al., 2017) and provided two value creation stories that were narrated from inside specific organisations in the public sector (Stenvall & Virtanen, 2017). These findings of the paper have several implications on studies about the complexity and challenges of digitalizing processes Bolander, 2019; Korhonen et al., 2021; Quattrone, 2016;), especially in healthcare (Beaulieu & Bentahar, 2021).

VIU emerges as an outcome of change in the practices of the customer. As such, VIU emerges dynamically through how the customers acts differently than what they would without the technology. The technology provides a foundation for value creation, but the customer (i.e., healthcare providers and its actors) actively create value enabling VIU to emerge. In both cases, the realisation of the pursued impact (proactively true VIU) depends on if the customer (laboratories/hospitals or homecare organisations) redesigns their service activities for patients (whether they make VIU pragmatically true). Using the PC lens, it all depends on whether the customers achieve an integrated reality construction, new or old (Jakobsen et al., 2011; Nørreklit, 2017a, b; Nørreklit et al., 2006, 2010). In some cases, suppliers need to put effort into communication to convince and educate their customers about the possibilities of using the technology. Also, the possible VIU is not necessarily obvious, and it can consist of several inclusive and exclusive elements. Actors’ values define which elements are considered more important than others and are therefore emphasized. For example, financial optimisation is seldom the only goal in public healthcare organisations, but it can significantly impact the way healthcare services can be provided. Sometimes managers need to decide whether they want to ensure higher quality (i.e., medicine adherence or lower chance of outbreak), even if this means an increase in the direct the cost of care. In these cases, technology providers might want to put more effort into communicating their own perceptions of possibilities for VIU to integrate their realities with the healthcare providers and improve the chances that the healthcare organizations try to convince the municipalities to decide to acquire the technology.

VIU also evolves dynamically. It starts as a possibility and gains factual basis until it becomes a factual possibility. Once the customer acts upon it, VIU either becomes a fact or the factual basis for VIU was an illusion. This change from VIU as a possibility to VIU as a fact converts proactive truth about VIU (i.e., it should be possible) to pragmatic truth about VIU (i.e., it was possible). Our findings thus show that healthcare customers are in a key position regarding determining if technology is implemented and if value can be created, which enables VIU to emerge. This motivation for value creation has previously been identified as important but has not yet been theoretically explained (Finne & Grönroos, 2009​; Finne & Grönroos, 2017, Lee, 2018). Similar analysis can be used for the supplier, who creates hypotheses about value potential (possibility) and can only start getting the factual basis for this possibility after their first pilots. Finally, the reality integration through communication between supplier and customer is critical to communicating the possibility of VIU, and in accordance with SL, it is the only way the supplier can influence the customer’s value creation activities. Communication between the technology provider and the customer is a value-driven exchange of facts, such as the factual resources of the technology provider and the factual conditions of the customer as well as possibilities for realising the values of both actors. PC can help explain the act of communication in its multiple forms and, thus, has the potential to expand the concept of value co-creation from its rather abstract sense to various concrete types of value co-creation (Grönroos, 2011). In addition, SL can be used to identify the different roles of actors (specifically, those of suppliers and customers). While PC is most interested in individual actors and understands that interaction and communication with others is an important part of reality construction, SL expands this view into looking at action and interaction within dyads and thus joint action. This paper reveals some of the dynamics of such interaction, but more thorough analyses are highly encouraged.

As a final note, we also identified major differences between ‘values’ in PC and ‘value-in-use’ in SL. Values drive actors’ reality integration in PC and thus represent an input for action, while VIU manifests from the customer’s value creation and is thus considered an output of action. VIU can be part of all four elements of reality integration: possibility, something that can be achieved; values, something that the actor wants to achieve; communication, something that is discussed between actors; and fact, something that happened and can be later acted upon. The form of VIU then depends on time and on whether value has already been created. However, since our findings suggest that VIU emerges and evolves over time, VIU does not always proceed from a possibility to a fact; there is always possibility for new or more VIU, and realised VIU strengthens its factual basis. Actors’ values also evolve, which might either strengthen or hinder the customer’s intention to continue creating value with the technology.

The findings presented in this paper are meaningful in developing public healthcare practices when digitalization is introduced. We recommend that managers rethink how value is created and do not just assume that the implementation of technologies will automatically release the potential value of those technologies. Instead, one should consider what kind of possibilities does the technology enable in arranging care without forgetting what the outcomes of that care are for the patients. Sometimes some opportunities are not implicit and require a level of detective work to realize how the care could look like now that the technology becomes part of it. Furthermore, even if a worthwhile possible change is identified, the actors that provide the care and use the technology will also need to adapt to the new practices for the value to start emerging. One way to manage these potential pitfalls is to introduce performance measurement that can capture how the new way of care differs from the old one. Moreover, to ensure that VIU has the possibility to emerge, emerges, and keeps emerging, continuous attention to network’s different actors’ needs and the dynamics of value creation is most likely required.

From the supplier’s point of view, the suppliers might want to avoid “throwing goods over the fence” approach where the fact if value is created is left for the customers. This might work in short-term, but the customer will notice it eventually if there is some unrecognized condition that obstructs the creation of value or if there is no evidence of value that was proposed is emerging. However, suppliers will have some opportunities to facilitate the value creation or even co-create value together with the customer. Thus, it might be worth doing some assessments to whether the customer was able to create the promised value and whether there are some activities the supplier could do or features that could be added to the technology that could help the customer create value as intended.

Our paper is also the first to combine SL with PC and opens an ample scope of interesting opportunities for future research. Based on the empirical findings and case study illustrations, the combined use of PC and SL helps identify how VIU emerges in public healthcare services when healthcare technologies are used by actors to improve their activities. Combining PC and SL provides an explicit view of the different values, facts, and realities that underly actors’ intentions for actions that create value. By expanding SL with PC, organisations can understand what the world should look like (proactive truth) for the customer to be able to create value as VIU (pragmatic truth) (Nørreklit, 2017a, b). With PC, by looking at the factual resources of the technology provider and the factual conditions of the customers, managers can integrate their realities to achieve a factual basis for the VIU as a possibility. With SL, we understand the limitations of the supplier and the technology regarding supporting value creation, and we can focus on how the customer can create value based on the new possibilities enabled by the technology and the supplier.

However, we are not normatively prescribing the combined use SL and PC and this combination is worth more in-depth methodological investigation. However, our use suggests that these theoretical approaches can together help managers go beyond the initially perceived potential enabled by technologies and understand both the underlying (joint) actions that can improve the VIU enabled by the technologies and the support needed to motivate relevant actors to act accordingly. As we have showcased so far, there are multiple synergies for combining these theories, but there is also some discord between them. For example, SL does not clearly state if customers and suppliers are individual actors or organisations. Most SL literature looks at how consumers create value with the products and service(s) of supplier organisations (e.g., Grönroos 2008; 2011; Grönroos & Voima, 2013), with some B2B exceptions (Grönroos & Helle, 2010). PC, on the other hand, clearly focuses on individual actors (Nørreklit, 2017a, b). In our paper, we overcame this challenge by looking at organisational dyads while also recognising that these organisations consist of individual actors with individual realities. We do not claim that a single new theory combining both SL and PC is necessary, especially when service logic is specific to supplier-customer relationships, such as those presented in this paper. However, we do see many possibilities for using these separate theories, both concurrently as individual theoretical lenses for the same purpose and as a combined lens, as is demonstrated in this paper. We show one combination, but we highly encourage further research that combines these theories in different ways and for other purposes.

One important issue in the healthcare context is how the end customer (i.e., an individual patient) is given a voice in their care. Naturally, the same applies in B2B customer’s value creation, but in the B2G context, the end customer might have significantly different values than the B2B customer. For instance, important facts and possibilities identified by a B2G customer’s representative (e.g., a controller, manager, or nurse) might include the work atmosphere and quality of work. They might also highlight the need to use public money efficiently and effectively. An individual patient could, on the other hand, bring up very different values: they might value their own privacy and individual will, getting help for loneliness, safety when living at home, the informal care given by their relatives, etc. Values of each actor are important in acquiring a fuller picture of B2G value creation. There could be, for instance, some communication between a technology provider and the patients or other relevant stakeholders, for example a representative of the society (e.g., a health minister). Or it might be that these stakeholders are given voice only through the B2G customer (such as a publicly owned enterprise, a governing organisation, a municipality, a hospital district, etc.). In a worst-case scenario, the changes in healthcare practices might make the patient lose some value due to the changing practices of the healthcare provider. Vice-versa, the patients might, through lack of cooperation or illusive facts, make it impossible to achieve the VIU, even if they could also be a beneficiary of the changes. As such, value creation in healthcare expands outside the typical supplier-customer dyad of service logic into value-chains (the technology provider to public healthcare organisation(s) to healthcare patient), and even further, into value-networks (see Balta et al., 2021) which include relatives, other patients, other health and social care institutions, the government, etc., and that service logic has not yet sufficiently addressed.

We contribute to the literature on digitalizing healthcare practices by showing how value-in-use stems from digitalizing different public healthcare contexts using digital technologies. Using pragmatic constructivism and service logic as method theories, we give practical examples of healthcare contexts showing how the customer organisations need to actively change their practices if they want to realise the possible VIU with digital technologies. Suppliers and the technology can offer such VIU as a possibility, but the VIU stems from customer organisations changing their practices. Moreover, this kind of VIU emerges and evolves dynamically. We show how it is not always enough to understand what kind of VIU could be achieved but also what is required to ensure the customer actors have intention for action. This challenges the traditional marketing perspective of value-in-exchange as something embedded in the product or service, which has many implications also to the provider. Since the technology can only be used to facilitate a change in the organisational practices of healthcare, providers need to focus on interaction and communication to ensure that their customers have the motivation and intention to start creating value. Our empirical cases also explain the customer’s intention for action by showing that the reality integration of the customer actors provides the intention for the customer to create value and for VIU to emerge. As part of this reality integration, VIU evolves from a possibility to a fact as part of the actor’s reality construction, which is driven by the actor’s values. At the core of this reality integration is VIU, which, more than part of the values of the actor, drives the reality integration among actors, and as such, their action.

The paper extends understanding of the VIU of digital technologies in public healthcare service contexts. More specifically, we investigated the unveiling and examining of actors’ realities, values, and intentions, deepening our understanding of the antecedents and impacts of VIU, with the combined use of PC and SL. The paper does not provide definitive conclusions, but It also provides a starting point for further elaboration on these two theoretical approaches, including their synergies and interlinkages. As such, we open an ample scope for future research not only on value creation and VIU in healthcare service chains and networks, but also on the combined use of PC and SL. On the one hand, as we mostly focused in unveiling how VIU emerges, our study leaves plenty of room to further investigate the motivation perspective, for example, in cases where technology faced resistance to change throughout their implementations – or did not even pass through the public procurement and capital investment processes. It would be particularly interesting to see, which factors of certain actors’ reality integration hinder or even stop technologies with potential for possible VIU from being invested in, implemented in practice, or the practice being changed. On the other hand, the role of interaction and the types of value co-creation therein or the value-network perspective that has previously been absent from the SL literature could provide inspiring contexts for both SL and PC (and combined) research. We, therefore, strongly suggest that future research combine PC and SL (for example in the form of the framework of this paper) in other supplier-customer contexts as well as transfer these ideas into new ones.