Value proposition test-driving for service innovation

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Journal of Service Theory and Practice Value proposition test-driving for service innovation: How frontline employees innovate value propositions Maria Åkesson, Per Skålén, Bo Edvardsson, Anna Stålhammar,

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To cite this document: Maria Åkesson, Per Skålén, Bo Edvardsson, Anna Stålhammar, (2016) "Value proposition test-driving for service innovation: How frontline employees innovate value propositions", Journal of Service Theory and Practice, Vol. 26 Issue: 3, pp.338-362, https://doi.org/10.1108/JSTP-10-2014-0242 Permanent link to this document: https://doi.org/10.1108/JSTP-10-2014-0242 Downloaded on: 16 June 2017, At: 01:04 (PT) References: this document contains references to 59 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 2029 times since 2016*

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Value proposition test-driving for service innovation How frontline employees innovate value propositions

338 Received 28 October 2014 Revised 24 February 2015 20 April 2015 Accepted 1 June 2015

Maria Åkesson, Per Skålén, Bo Edvardsson and Anna Stålhammar CTF-Service Research Center, Karlstad University, Karlstad, Sweden Abstract

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Purpose – The purpose of this paper is to investigate the role of frontline employees in service innovation from a service-dominant logic (SDL) perspective. Frontline employees lack a formal innovation obligation. Service innovation is a resource integration process resulting in the creation of new value propositions. Design/methodology/approach – A case study of service innovation projects that includes three different businesses in the IT sector and personal interviews with 25 frontline employees. Findings – The findings suggest that frontline employees contribute to service innovation by test-driving potential value propositions. Three types of value proposition test-driving have been identified: cognitive, practical, and discursive. The findings suggest interdependencies between the different modes of value proposition test-driving, as well as specific phases of the service innovation process dominated by one form or another. Research limitations/implications – Value proposition test-driving offers a fruitful context for managers to involve frontline employees and use their creativity and expertise. The case study approach, however, limits the statistical generalizability of the findings. Originality/value – The study is novel in that it introduces the notion of value proposition test-driving for service innovation; provides a systematic empirical analysis of how frontline employees contribute to service innovation by test-driving value propositions; offers a service innovation model informed by the SDL; and contributes to the SDL by detailing how service innovation occurs in practice. Keywords Service-dominant logic, Resource integration, Service innovation, Value proposition, Employee-driven innovation, Value proposition test-driving Paper type Research paper

Journal of Service Theory and Practice Vol. 26 No. 3, 2016 pp. 338-362 © Emerald Group Publishing Limited 2055-6225 DOI 10.1108/JSTP-10-2014-0242

Introduction The view that value is co-created during interaction between providers, customers, and other actors in service eco-systems (rather than produced by organizations in isolation from their customers) has become the dominant view in service management research (Lusch and Vargo, 2014). This view has implications for several areas of service research and practice, one of which is service innovation studied in the present paper (Ordanini and Parasuraman, 2010; Vargo et al., 2014). One key implication for service innovation is the fact that other service eco-system actors than the professional developers of the R&D department can significantly contribute to innovative novel and useful services (Sundbo, 2008). It has been acknowledged that customers, and users of services more generally, contribute to service innovation by contributing creative ideas (Kristensson and Magnusson, 2010) and suggestions about how to integrate a new service into an existing service eco-system (Tax and Stuart, 1997). However, contributions to service innovation made by employees outside of the R&D department have been little studied (Karlsson and Skålén, 2015). We argue that customer co-creation is a part of most service jobs and allows, in particular, employees with extensive customer contact – frontline employees – to

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develop long-term relationships with their customers (Grönroos and Voima, 2013; Lusch et al., 2007). Many frontline employees are well-educated professionals, e.g. consultants, physicians, engineers, programmers, and sales representatives. They know how to best support their customers, as well as the strategy and goals of the firm, making them well suited to contributing to customer-friendly service innovations which are in line with the strategic orientation of the firm. Frontline employees are key assets in service innovation (Karlsson and Skålén, 2015; Ordanini and Parasuraman, 2010); enabling these organizational members to take part in service innovation processes is an urgent requirement (Sundbo, 2008). While it has been noted that frontline employees contribute to service innovation (Melton and Hartline, 2010; Ordanini and Parasuraman, 2010), the ways in which these contribute to service innovation have not been empirically studied in detail. We understand frontline employees as personnel either working entirely with customer contact duties or combining customer-contact obligations with back-office work. Hence, a frontline employee can be both a person working at a hotel reception desk, whose main duties include customer contact and who is not traditionally seen as involved in service innovation, and an engineer whose duties include both formal back-office service innovation and customer contact. Recent developments in service research, such as service-dominant logic (SDL), have been adopted as the key theoretical frame of reference in this study. SDL argues that firms in collaboration with other service eco-system actors offer value propositions to their customers, promising value-in-use and integrated resources that customers can integrate into their value-creation process (Grönroos and Voima, 2013; Vargo and Lusch, 2008; Vargo et al., 2014). More recently, value propositions have been described as invitations to engage with the firm (and potentially other actors) in the co-creation of value (Vargo and Lusch, 2004; Lusch and Vargo, 2014; Lusch and Nambisan, 2015). One example of a value proposition is revenue assurance, a consultancy service studied within the telecom sector in the present paper. The aim of revenue assurance is to tighten financial leakages in mobile operators’ revenue streams. By tightening these financial leakages, revenue assurance consultants support mobile operators’ value creation, and increase their revenue. From an SDL perspective, service innovation involves either developing new or modifying existing value propositions by integrating existing resources in different ways, or by inventing new resources (Skålén et al., 2015). Service innovation is thus tightly interwoven with the resource integration process when value propositions are created. Because frontline employees co-create value with their customers, they know what types of resource integration these customers prefer and which forms of integration either do not work or represent major challenges for customers. For instance, the revenue assurance consultant may realize that a bug in the customer’s billing system is creating financial leakages. By solving the problem, the consultant prevents financial leakages for the customer. In addition, a similar solution can be implemented for future customers. The consultant has thus reintegrated the resources of the value proposition in such a way that better value-in-use can be promised. The consultant has innovated the service. Since the contribution of frontline employees to service innovation is under-researched, we have conducted a multiple-case study. During the research process, we iterated between data and theory, and between open coding and constant comparative analysis. Our data suggests that frontline employees contribute by testing different ways to integrate resources during service innovation processes; these efforts then lead to the creation of new value propositions or modifications of existing value propositions.

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Inspired by Edvardsson et al. (2010), who argue that customers “test-drive” services prior to purchasing them in so-called service experience rooms, we launch the term “value proposition test-driving” to refer to the process by which frontline employees try out different ways of integrating resources in order to create new, or to modify existing, value propositions. In order to develop an understanding of how front line employees contribute to service innovation through value proposition test-driving, the paper focuses on the following research questions: RQ1. How do frontline employees test-drive value propositions?

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RQ2. How does value proposition test-driving, by frontline employees, lead to service innovation? By developing an understanding of value proposition test-driving, the paper also contributes to the emerging literature on service innovation from an SDL perspective by outlining an SDL-informed service innovation model (Melton and Hartline, 2010; Ordanini and Parasuraman, 2010). In addition, the paper also offers insights into firms’ resource integration processes. The paper opens with a review of the service innovation literature from an SDL perspective. The section ends by conceptualizing employees’ contributions to service innovation as value proposition test-driving. The method section describes the multiple-case study design and explains the collection and analysis of data with regard to how frontline employees contribute to service innovation. The method section is followed by the findings section, which focuses on how frontline employees test-drive value propositions. This is followed by the discussion and contribution section. Finally, we suggest managerial implications relating to how the knowledge and skills of frontline employees can be used more effectively during service innovation processes. Theoretical framing Service eco-systems, value creation, and value proposition According to SDL, service is “the application of specialized competences (knowledge and skills), through deeds, processes, and performances for the benefit of another entity or the entity itself” (Lusch et al., 2007, p. 15). Lusch and Nambisan (2015) argue that actors, including firms and customers, need to engage others and, in this respect, are only able to offer value propositions as invitations to engage in service eco-systems. This view implies the key role of actors and resources in value co-creation and in linked activities such as service innovation. Actors’ resource integration and value co-creation efforts are almost impossible to understand without a deep understanding of service eco-systems (Vargo et al., 2008, 2014). From this perspective, value is co-created with customers and other actors, often including personnel employed by the service provider (Vargo and Lusch, 2004, 2008), who jointly integrate resources in order to co-create value for both themselves and others in a service eco-system (Edvardsson et al., 2011; Edvardsson and Tronvoll, 2013). Lusch and Vargo (2014) describe a service eco-system as “a spontaneously sensing and responding spatial and temporal structure of largely loosely-coupled value-proposing social and economic actors interacting through institutions and technology, to: first, co-produce service offerings; second, exchange service offerings; and third, co-create value”. Service eco-systems provide structures and coordinating mechanisms for the engaged actors’ resource integration and value co-creation in practice (Vargo and Akaka, 2012). Service eco-systems are embedded in social systems

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consisting of social structures that both enable and constrain actions. Social structures are manifested in social practices (Edvardsson et al., 2011); the “[…] sets of rules, procedures, and/or methods for meaning making and acting” (Lusch and Vargo, 2014, p. 137) that constitute actors’ agency. Hence, practices enable the engaged actors to coordinate their everyday resource-integrating and value co-creating actions; should they divert from social structures, they may eventually change them. Lusch and Vargo (2014) put forward representational, normalizing, and integrative practices. Representational practices are closely linked to language (the meaning of words is co-created), signs, and symbols for sensemaking and the facilitation of interactions between actors. Normalizing practices are guidelines, social norms, and rules that harmoniously coordinate actors. Finally, integrative practices relate to how actors integrate various available resources and co-create value, e.g. when going to work using public or private transportation, traffic laws and regulations, making phone calls, or listening to news or music. Practices shape actors’ roles and connect actors within service eco-systems (Akaka and Chandler, 2011). As indicated by the differentiation between structures and practices, service eco-systems consist of several levels (Vargo and Lusch, 2011; Lusch and Vargo, 2014). “[S]ervice eco-systems are multi-level in nature. From the micro system a meso system emerges and from a meso system a macro system emerges’ (Lusch and Vargo, 2014, p. 169). This paper focuses on the micro level, which is the level of practices; however, it is important to point out that there is always an interdependency between the different levels of service eco-systems. Focusing on the micro level, Grönroos and Voima (2013) present three spheres of value creation, claiming that it is only in the “joint sphere” that the firm has the opportunity to co-create value with the customer since it is only in this sphere that direct interaction takes place. The other two spheres are the “customer sphere” and the “provider sphere”. In the latter sphere, the firm facilitates its customers’ value creation: the firm is a value facilitator (Grönroos, 2008) that is only able to offer value propositions, that is, potential value or invitations to co-create value (Chandler and Vargo, 2011a). In the customer sphere, the value is created in use by the customer independently of the provider. Mele (2009) emphasizes that the core mechanism of value creation is the integration of the resources of several actors in accordance with their expectations, needs, and capabilities. The engine of value co-creation is interaction between actors, while the fuel is the resources they can access, integrate, and use. Interactions are not limited to the dyad of customers and employees. Rather, as service eco-system emphasize, value co-creation includes other types of interactions such as those between customers and information and communication technology (ICT) systems, between employees and ICT systems, or between other products and services that constitute resources enabling value co-creation. Through the SDL lens, value co-creation results from how customers, employees, and other actors integrate and operate on the available resources, in line with value propositions (Lusch et al., 2007). Value propositions (Lusch and Vargo, 2006; Lusch et al., 2007; Vargo and Lusch, 2008) communicate, to both customers and employees, what value is expected from a service and constitute an invitation to co-create value. As promised value-in-use, value propositions consist of integrated resources offered to customers to support their value-creation process (Vargo and Lusch, 2004, 2008). Value propositions also exist to facilitate value co-creation (Payne et al., 2008), although we suffer from limited knowledge of how value propositions themselves are created, developed, and changed. Because frontline employees

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frequently co-create value with their customers, they know these customers’ preferences and may be able to help in developing new or modifying existing value propositions. In line with Heinonen et al. (2010), this suggests that service providers would need to focus on becoming involved in their customers’ lives, something which frontline employees are well positioned to do.

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Resource integration and frontline employees A view of actors as resource integrators participating in value co-creation by integrating resources (operand and/or operant) provides the foundation for SDL. According to Vargo and Lusch (2008), value is co-created through this resource integration. Integration requires process(es) and forms of collaboration, although the practices of integrating resources and methods for designing and configuring the resource integration process remain uncertain (Kleinaltenkamp et al., 2012). Actors may have agency, to the extent that the flow of their actions and interactions is embedded in social practices, and their specific value-creation intentions drive resource integration. To understand the forces shaping resource integration, however, we need to specify role enactment by employees and customers in terms of who these are as both people and social agents (Edvardsson et al., 2011). Most service research considers only customers, without acknowledging the role of the employees as resource integrators during service innovation efforts (e.g. Hibbert et al., 2012). When the focus is on employees, it tends to be on professional developers and not frontline employees (Sundbo, 2008). However, Cadwallader et al. (2010) claim that frontline participation is common during the implementation phase of service innovation and that frontline employees make an important contribution by introducing new or refined value propositions to the customers. Also, recent research entitled “employee-driven innovation” has suggested that frontline employees’ knowledge and skills regarding customers’ value-creation practices lead to less inaccurate innovation decisions (Kesting and Ulhøi, 2010). Our view of resources matches that proposed by Mele et al. (2010), in that resources have no inherent value but possess important potential value instead, depending on how they are integrated and operated on. Resources require integration and application in order to become valuable to an actor, during a process referred to as resource integration. Mele (2009) claims that resource integration occurs in accordance with actors’ expectations, needs, and capabilities. Vargo and Lusch (2004, 2008) also suggest that resource integration creates value propositions, relatively stable constellations of operand and operant resources which firms offer to their customers. Thus, resource integration encourages several actors, including frontline employees, to integrate multiple resources both for their own benefit and for the benefit of others (Vargo, 2008). Service eco-systems and innovation Edvardsson and Tronvoll (2013) define service innovation as changes in the service eco-system structure which are due to a new configuration of actors, resources, and schemas, resulting in new practices that are valuable enough for the involved actors to make them sustainable. The service eco-systems perspective (Lusch and Vargo 2014; Edvardsson and Tronvoll, 2013; Edvardsson et al., 2014) suggests that innovation involves a constellation of actors (in this paper the focus is on frontline employees) who integrate resources and thus become co-innovators of the process (Russo-Spena and Mele, 2012). Vargo et al. (2014, p. 33) conceptualize service innovation as the co-creation

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or collaborative recombination of practices that provide novel solutions for new or existing problems. Skålén et al. (2015) argue that service innovation involves developing new or modifying existing value propositions by integrating existing resources in different ways, or by inventing new resources. Thus, service innovation is driven by collaborative efforts of the engaged actors; with their operant and operand resources, creating new value propositions and smarter ways of integrating resources and co-creating value within service eco-systems (Vargo et al., 2014). Ordanini and Parasuraman (2010) find that customer-contact personnel positively affect both the innovation volume (number of innovations) and the radicalness (magnitude of change). Toivonen and Tuominen (2009) reason that, by collecting information from different sources, e.g. customers, and relating that information to real situations, frontline employees can contribute service innovation ideas. In other words, frontline employees are the key to any service innovation process (Karlsson and Skålén, 2015). Scholars have also suggested various service innovation models. Typically, process models indicate a progression from the establishment of clear objectives to idea generation, to concept development, service design, prototyping, service launch, and customer feedback (some of which takes various labels) (e.g. Hamilton, 1982; Bitner et al., 2008). Other process models add nonlinear and parallel elements to service and product development processes (e.g. Alam and Perry, 2002; Cooper, 1996; Johnson et al., 2000; Edvardsson et al., 1995; Scheuing and Johnson, 1989). During the service innovation process, frontline employees integrate resources into value propositions; however, exactly how they do so during the different phases is poorly understood. An exception, perhaps, is the market launch/implementation phase where, as stated previously, research has focused on the boundary-spanning role of the employees, leading to the conclusion that frontline employees make important contributions to this phase (see, for instance, Cadwallader et al., 2010). Framing value proposition test-driving for service innovation for this study We study service innovation by focusing on frontline employees’ practices at the micro level in service eco-systems. In doing this, we contribute towards closing a knowledge gap in the service innovation literature. We argue that the engaged actors collaborate with multiple actors when integrating and combining their operant and operand resources by test-driving value propositions. Hence, frontline employees cannot be seen in isolation; they are, rather, actors engaged in a service eco-system practice. We assume that the frontline employees are inspired as well as influenced by other actors, including the customers and their practices. Our conceptualization of the frontline employees’ role in service innovation was inspired by the concept of service test-driving, which is the term Edvardsson et al. (2010) used to describe how customers experience a service prior to a possible purchase. They consider service test-driving to be a tool that gives customers a pre-purchase, systemic and hands-on understanding of the value of a particular service in context, which they would otherwise only be able to experience in use after purchase. The tool thus moves beyond brochures, videos, or websites, which represent limited ways to inform customers about services before purchase. Examples of service test-driving include free initial services provided by consultants, try-out activities at fitness centres, experience rooms at furniture stores, and open days at schools. By using the concept of value proposition test-driving, we are able to illuminate frontline employees’ resource integration activities during the service innovation process. Value proposition test-driving refers, in this paper, to the different ways

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frontline employees create, test, and experiment with different, novel and useful ways to integrate resources into value propositions. By using the notion in this way, this paper advances knowledge of the employees’ contributions to service innovation by analyzing how they test-drive value propositions. This focus is in line with the call by Michel et al. (2008) and Skålén et al. (2015) for research on how service providers combine (and recombine) resources as a means of innovating value propositions in service eco-systems. Method Design and background Knowledge is scarce regarding how frontline employees contribute to service innovation, in general, and how they test-drive value propositions, in particular. Therefore, we conducted a multiple-case study (Yin, 1984). A multiple-case study design includes two or more observations of the same phenomenon; in our case, of how frontline employees test-drive value propositions and contribute to service innovation. To avoid overly fragmented results, the theoretical case sampling (Glaser and Strauss, 1967) was delimited to the IT sector. This limits the generalizability of the results; however, conceptual development rather than statistical generalization is the aim of case study research. The theoretical sampling also considered access. Not all the companies we contacted gave us the opportunity to interview frontline employees involved in service innovation, which our design pre-requires. The study was conducted at three firms: first, a multinational telecom company (referred to as MTC); second, a publicly owned company in the broadband business (referred to as POC); and third, a multinational IT service company (referred to as MIC). At each firm, one or two service innovation projects featuring extensive employee involvement served as the focus of the case study. One of the two service innovation projects at MTC focused on developing service revenue assurance, which helps telecom operators to tighten internal financial leakages in their revenue streams. The second project, POC, focused on developing a tool for managing secure and flexible access to telecom operator networks. Both service innovation projects were largely driven by a group of consultants with extensive customer contact. The service innovation project at POC developed a broadband fibre network. This new service was called “liberating broadband”, as it was an open network whose customers could choose between different, and competing, providers of internet, TV, and telephone services. The project involved employees at different levels and positions within the organization, e.g. the CEO, customer service employees, technicians, and a marketer. At MIC, the service innovation project was about adding new functionality to radio base stations. This new value proposition gave customers access to more bandwidth and faster services on mobile phones (e.g. downloading videos). The project mainly involved software designers, programmers, and testers, all of whom had frequent customer contact. Data collection To collect the data, we interviewed frontline employees at each company and gathered relevant documents. In total, we interviewed 25 frontline employees (see Table AI for a description of the informants). Focusing on a specific service innovation project enabled us to formulate concrete context-specific questions, thus improving the quality of the interviews. A questionnaire guided each interview. The questions aimed to identify how frontline employees worked during the service innovation process and

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what they contributed (see Table AII for the questionnaire). The interviews lasted between 25 and 80 minutes and were transcribed verbatim within two weeks of being conducted. We also studied documents relating to the service innovation projects. The documents collected included reports, PowerPoint presentations, marketing brochures, and minutes of project meetings.

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Data analysis Data analysis focused on identifying the different ways in which frontline employees test-drive value propositions. The ongoing and iterative data analysis process was consistent with the emergent design and the constant comparative method (Strauss and Corbin, 1998). Our emphasis, thus, was on creating a reflexive process during which we could probe lessons learned from prior interviews, analyses, and theoretical exposure in order to inform our subsequent data collection, analysis, and theorizing. When analyzing the data, we began by identifying open codes, then engaging in axial coding to uncover key themes regarding how frontline employees test-drive resource integrations. Axial coding generates themes. In our case, axial coding suggested that frontline employees use three methods to test-drive resource integrations: i.e. cognitive, practical, and discursive. These are defined and empirically grounded in the findings section. Axial coding was based on our open coding, and we made sure that each type of test-drive was firmly underpinned by open codes. To exemplify: “prototype”, “test systems”, and “simulations” are open codes that make up practical test-driving. The following quote is reported in the data: “The [frontline employees] work with a simulator, which is supposed to have exactly the same functionality as reality […] and in that simulator […] a new feature is implemented […] and we’ll see if it meets all the demands”. The quote suggests that frontline employees, in their day-to-day work by means of simulating, add new features to the value proposition, thus contributing to service innovation. Practical test-driving was made up of 13 open codes, cognitive test-driving was made up of 11 codes, and discursive test-driving was made up of nine open codes. Furthermore, we identified two-thirds of the codes for each type of test-drive in all three cases. Based on our three themes/types of test-drive, we conducted pathway coding of the data, which suggested three parallel modes of service innovation. The modes are made up of all three types of value proposition test-driving but each is dominated by one of them. This implied that we had identified the following modes of service innovation: cognitive-dominant, practical-dominant, and discursive-dominant. When establishing their connections with the service innovation process, we further found that one mode dominated each stage of the service innovation process. Finally, using selective coding, we integrated the themes with extant theory relating to frontline employee involvement in service innovation. We continued to collect and analyse data until we achieved saturation, defined as the point when no new information emerged from our respondents with regard to value proposition test-driving. To validate the data collection and analysis, as well as the findings more generally, we used four of the techniques suggested by Belk et al. (1989) for increasing the trustworthiness of qualitative marketing research. First, we triangulated the data across the three cases and the 25 respondents. We also triangulated the coding and categorization between the first three authors of this paper, as well as between the interviews conducted and the documents collected. Second, we used member checks to increase the credibility of the results by presenting the results to representatives of the three firms for critiquing and correction. Third, we granted both the firms and the

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respondents full anonymity in order to increase the integrity of the research. Finally, the researchers involved in the project commented on the connections this paper makes between the data and the emerging conceptualizations, a process that resembles the confirmability audit recommended by Belk et al. (1989). Findings This section presents the three types of value proposition test-driving and the three different modes of frontline-employee-driven service innovation that we identified in our data.

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Types of value proposition test-driving Frontline employees test-drive resource integrations in three different ways: cognitive, practical, and discursive. In relation to Grönroos and Voima’s (2013) spheres, it is only in the joint sphere that test-driving can occur in co-creation with the customer, in the form of direct interaction. In the provider and customer spheres, test-driving does not involve any direct interaction; nevertheless, the customer can influence the provider sphere in such a way that the employee recalls knowledge and experience from previous co-creation with customers. Therefore, it is possible to say that the customer contributes to the provider sphere, but only indirectly. Table I defines the three different ways of test-driving resource integrations. It suggests that the different ways are intertwined with one another. For instance, cognitive test-driving conducted collectively entails the involved frontline employees sharing their thoughts through talk that is in discourse. Vice versa, when frontline Type

Definition

Cognitive Ordinary employees, individually or collectively, use their capacity of thinking to determine if a particular way of linking the resources of a value proposition will enable value co-creation

Practical

Table I. The three ways of test-driving value propositions

Ordinary employees, individually or collectively, try out the value proposition or parts of it through, e.g., simulations, prototypes, and usage, to evaluate if the resources constituting the value proposition are integrated in the best way

Discursive Ordinary employees, individually or collectively, use their linguistic abilities (e.g. talking, writing texts, communicating, etc.) to evaluate if the integration of resources of a value proposition enables value co-creation

Exemplar After co-creating value with a customer based on a particular value proposition the employee reflects weather or not the resources of the value proposition is integrated in the best way Several ordinary employees detects a problem in a service and together reflect how to integrate resources of the value proposition in such a way that the problem does not occur in the future A team of ordinary employees builds a prototype materializing the value proposition to (e.g. a computer programme) to see if the service works properly One ordinary employee uses the value proposition to see if it enables value co-creation Several ordinary employees discuss the integration of resources of a value proposition during a meeting One ordinary employee writes a description of a value proposition and during the process realizes that its resources are not integrated in the ideal way

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employees engage in discursive test-driving through talk in a meeting, this requires them to think. Thus, the three types of test-driving of resource integrations are intertwined in practice, but are kept apart in this section for analytical reasons. The three types of test-driving are generated from the data, but they are also theoretically grounded. The notion of cognitive test-driving is grounded in cognitive psychology, which studies mental processes such as creativity, thinking, memory, and perception. Frameworks from cognitive psychology have informed marketing research extensively. For example, the whole field of consumer behaviour rests on cognitive psychology. In service innovation studies, creativity models from cognitive psychology have been used to study what types of actors contribute the most creative ideas to the service innovation process (Kristensson et al., 2004). The term practical test-driving is inspired by practice theory devoted to studying the different typical ways in which humans carry out activities on the micro level, e.g. cooking, parenting, or marketing. Marketing practice theory has been used, for instance, to study the different typical ways in which contact personnel and customers co-create value (Echeverri and Skålén, 2011). Discursive test-driving is grounded in discourse analysis and marketing research which has drawn on discourse analysis in order to study marketing phenomena. In discourse analysis, discourse is defined as “a particular way of talking about and understanding the world (or an aspect of the world)” (Phillips and Jørgensen, 2004, p. 1). In previous marketing research, discourse analysis has been used to study how marketing professions understand marketing activities on the basis of particular types of language use and how the use of certain concepts impedes or fosters market orientation (Skålén, 2009). Next follows a discussion of each different way of test-driving value propositions, starting with cognitive value proposition test-driving. Cognitive. When engaging in cognitive value proposition test-driving, frontline employees participate, in their minds, in the individual and collective modelling of potential resource integrations and value propositions. Employees use their knowledge and skills to innovate services by integrating new or existing resources during the course of intellectual processes. In many cases, their cognitive value proposition test-driving is spurred on by the requirements and problems of other service eco-system actors, e.g. the customer, in such a way that the frontline employee seeks to integrate resources that customers use more efficiently. The first quote below suggests that interaction with the customer triggers mental processes (thinking) and that cognitive value proposition test-driving takes place in the joint sphere since there is direct interaction between the employee and the customer. The second quote suggests that talking to customers triggers the employees’ thinking and activates a will to do something in order to make improvements. This cognitive value proposition test-driving takes place in the provider sphere: It’s like listening [to the customer] the whole time, thinking, “Does that exist? Do you hear anything? Is there anywhere [new customer solutions are] needed?” (Project leader, MIC) Still we innovate. And that’s because those out in the field – sitting with the customers and talking to them and seeing their requirements – they see a lot of great opportunities here. “Let’s do something!” (Project leader, MIC).

In other cases, employees start with internal issues and find ways to solve a problem, improve a process, or come up with a better and more efficient technical solution: So [Person X] was responsible for figuring out which features to use and how to configure them (Programmer 2, MTC).

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Cognitive value proposition test-driving is often mediated by talking with other actors within the service eco-system, e.g. colleagues. This talking does not drive the innovation; rather, the cognitive process it embeds does so. Cognitive value proposition test-driving sometimes takes place informally during “water-cooler moments” – that is, conversations among colleagues during coffee breaks, unofficial phone calls, and informal meetings. On these occasions, frontline employees use one another’s, as well as other stakeholders’, different competencies and experiences to solve problems, discuss new innovations, and examine ideas:

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[…] [S]o we were always discussing things during coffee breaks and thinking (Customer service worker, POC). Yeah, and that if someone has an idea, you then get your mate from the other department and you say, “Yes, but we’ve already thought of that three times and it doesn’t work because that subsystem pre-requires that and then it just doesn’t work”. […] [S]o you can’t keep tabs on everything. And that business of […] this forum for technical discussion, it’s important (Project leader, MIC).

Employees thus think cooperatively and use others’ competencies to try out ideas regarding new, refined, or changed value propositions, and to analyse the viability of an idea before developing it further. The following quotes illustrate how an open atmosphere and a vibrant dialog about technical issues, both internally and externally with the customer, can stimulate mutual cognitive efforts and contribute, by extension, to innovation: Yeah, you have to have a good technical conversation, kind of thing, and having a good atmosphere specifically when talking technology is important […] [Y]ou just swing past and you have interesting problems to discuss with each other and then you always get involved in loads of other stuff. And then someone says, “But this […] how were they thinking there” […] (Consultant 5, MTC). […] and then you call someone at XXX and you say, “What are you doing?” “No, we hadn’t thought of that”. And that is, kind of, a signal that we might be able to think of something here and revert with a suggestion. So that’s how it starts most of the time. […] It’s really exciting, the field of technology is so wide. […] The scope is so broad, nobody can cope with all that. So you have to have, sort of, a conversation (Computer engineer 1, MIC).

Practical. When frontline employees revise existing or innovate new value propositions using hands-on activities such as trial and error and simulations, they engage in practical value proposition test-driving. Some of this test-driving takes place informally, such as when frontline employees iterate between problems and solutions using trial and error in their efforts to solve problems and to learn about how value propositions work in order to improve them by making relevant changes, both within the organization and together with stakeholders. The following quotes describe how and why the respondents trying out the potential value proposition, or parts thereof, in order to evaluate whether or not the resources constituting the value proposition have been integrated in a satisfactory way. The employees thus test-drive value propositions in a practical way: Then you have to optimize it. “No, you can’t do it like that. We’ll have to do it an entirely different way”, and then you try that and then you implement it. If that made it better, then you have to say, “You can’t do it like that. We’ll have to do this instead”. […] And then maybe it has to be changed, and then […] it’s iterated like this (Head of POC).

It took us several days to get it [the system] working properly, because we noticed that we were having some problems with it, that we hadn’t taken the specific scenario into account. So we had to spend extra time on that. And then, on the other hand, things we thought were really hard to do, we did in half a day (Tester, MIC).

Value proposition test-driving

The studied organizations also formalized some practical value proposition test-driving by simulating and examining value propositions. Simulating required making a model of the proposed value proposition in order to check whether or not its critical elements worked. Simulations may require several steps, different levels, and different segments of the process, as illustrated by the following quotes:

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[The frontline employees] work with a simulator, which is supposed to have exactly the same functionality as in reality […] and in that simulator […] a new feature is implemented […] and we’ll see if it meets all the demands. […] And then it’ll be easy to be wise in hindsight because “we’re good to go”. Now we know that we’ll pass the performance requirements and all that stuff (System developer, MIC). Group X [consisting of frontline employees] is involved and can bring down an idea if it doesn’t work. Then we test very early on, we implement, we test, and we see “will this work?” “No, it won’t work”, and then you backtrack […] then they have to make changes (Project leader, MIC).

Through their investigations, frontline employees check and determine whether or not new or refined resource integrations work in an existing resource system, as well as whether or not the existing parts of a service work as they did before the new resources were integrated into it. Both within the organization and in collaboration with customers, investigations can drive service innovation through frontline employee involvement: New functions are being added the whole time, and faults are being rectified. And then it’s really important that what worked before still works. So much of the job is about that – making sure that what worked before still works before continuing (Computer engineer 2, MIC). […] [W]hen the customer started to test the systems by himself, we got some feedback on how things were working. […] For example, what he wanted to have in the end was […] some functionality which it had already been agreed that he didn’t want. Now he suddenly wanted it (System developer, MIC). Pre-study, that’s a rather brief investigation. […] And if there are no red lights there, kind of thing, rather a case of things looking good […] “Yeah, that’s great, then we’ll run a feasibility study”. And then you get right to the heart of things. That’s a slightly larger investigation […] then you’re really focused, looking more at technical limitations […] in reality, all the changes you need to make (Project leader, MIC).

As illustrated by the quotes, practical value proposition test-driving may occur both in the provider and in the joint co-creation spheres of value creation. Discursive. During various linguistic acts, frontline employees articulate and represent their thoughts about new value propositions. This type of discursive value proposition test-driving often takes place in writing, such that the employees identify and connect the resources required to develop the value proposition on paper. Our analysis shows that the employees literally write, draw pictures, or create models as a means of consolidating, visualizing, and concretizing their thoughts about a value

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proposition, and then they communicate these thoughts to others. This process includes making plans, schedules, specifications, and written proposals: And the next step here and now [during the development process] is to make plans for this productification and investment requirement. […] Or the investment required in order to achieve this (Project manager 2, MTC).

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And then there’s a very special formalized way of doing it [changes to the service], where we write a proposal for a change, which in our way of doing things is called a change request (Project leader, MIC).

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[…] [I]f you write a number of specs, also on several levels, and those specs have no connection with overheads or suchlike, or how to do it, rather it’s a matter of how, from a functional point of view, you can solve it and so on. […] [Y]eah, it’s not clear at all which project it has to go into (Operational development manager, MIC).

In addition, discursive value proposition test-driving is done orally, including interactions with other actors in the service eco-system, e.g. between colleagues and with customers about ideas for new or changed resource integrations. A common example is the dialogue between colleagues and/or other stakeholders at formal meetings: So, every morning, we had a […] meeting, and we were keeping track of things [during the innovation process]: “What’s going on? Who’s doing what? What’s the status?” and so on (Head of POC). Yes, he had a couple of meetings, face to face, with the customer [about the progress of an innovation]. But then he had quite a lot of meetings by phone (Consultant 2, MTC).

In these examples, oral linguistic ability, both in the provider and joint spheres of value creation, drives the resource integration process towards articulating value propositions. Thus, discursive value proposition test-driving differs from cognitive value proposition test-driving, where the cognitive processes, not the talk itself, drive the innovation. Drawings are also examples of discursive value proposition test-driving. Our analysis suggests that employees draw images or pictures in order to communicate potential value propositions to customers and other stakeholders in the service eco-system. These images and pictures can encourage shared sensemaking about the value proposition, or changes to it, both externally and internally: We made them a presentation, more or less. So we were saying, “Okay, this is how it’s going to work”. […] In the final documentation, there’s a picture in which we show, “Okay, this is how it’s going to work”. And it was essentially boxes saying, “Okay, this is the core server part, and it works like this and it works like that” (Computer engineer 1, MIC). [The customer] had his requirements. […] [W]e took them into consideration and drafted a high-level picture of how it’s going to work. […] And we basically explained the high-level picture and how the parts work together. […] [W]e had our own requirements and the customer’s requirements, and then, when we were drafting the system, we tried to blend them […] without compromising the actual end product (Departmental manager, MTC).

In the latter quote, it is obvious that the value proposition test-drive also occurs in direct interaction with the customer, and therefore in the joint sphere of value creation. Modes of service innovation As previously stated, frontline employees innovate value propositions through cognitive, practical, and discursive value proposition test-driving. Value proposition

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test-driving occurs in co-creation with the customer in the joint sphere through direct interaction. Here, the customer is directly involved by means of, for instance, talking with an employee. In the provider sphere, the customer may be indirectly involved when an employee recalls previous experiences of, for instance, talking to a customer. Our pathway analysis suggests that all stages of the service innovation process combine all three types of value proposition test-driving. But the pathway analysis also suggests that each stage is dominated and driven by a single type. Hence, value proposition test-driving by frontline employees leads to service innovation by means of three modes that are salient during different stages of the service innovation process. In cognitive-dominant service innovation, the focus is idea generation. With practical-dominant service innovation, we find a connection with prototyping the value proposition. The final mode, discursive-dominant service innovation, is strongly associated with the concept development, service design, and service launch phases. In this section, we present a representative example in order to illustrate each service innovation mode and how it is associated with different stages of the service innovation process. As stated previously, there are different labels attached to the various stages of a service innovation process. In the following example, the following stages are visible: idea generation, concept development, service design, prototyping, service launch, and customer feedback. The example refers to the integration of new solutions into an existing value proposition relating to network security at MTC. An existing innovation provided the basis for the new innovation. The service innovation process started with a frontline employee who had an idea for making the value proposition better; i.e., he was thinking about modifying the value proposition. Hence, this first step in the service innovation process was idea generation. The modification of the existing value proposition required the acquisition of new resources that could be integrated into it. The informant we interviewed (a consultant with computer programming skills) was not officially involved in the development of the first version of the innovation; however, he had unofficially developed a good idea relating to that innovation: My friend created the very first version. He’s a really good friend of mine, actually, so we were always discussing things during coffee breaks and thinking of more flexible ways to manage the security of the network.

As our findings showed, cognitive value proposition test-driving is often mediated via interactions, talk, and discussions; however, it is the cognitive processes embedded in the talk that drive the innovation. Therefore, the combined thinking of the respondent and his colleague exemplifies informal collective cognitive test-driving, which represents the idea generation step of the innovation process. This first step, along with the following four steps, occurred in the provider sphere. In the next step, the respondent recalled that it was a working system, but not a flexible one: So, every time you needed to make small changes to the system, this required lots of maintenance work and getting lots of things done. And I suggested, “Okay, if we have the chance to do it again, for other customers, we should rewrite the whole base”. Just take it and see what we have there and throw it in the trash can and write something similar.

In other words, employees wrote a new plan for how to enhance value proposition by integrating new resources into it. This concept-development step is clearly dominated by discursive value proposition test-driving. The third step, associated with the service

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design phase, was again dominated by discursive test-driving in that the employees did not make a prototype but a presentation instead: We drafted a high-level picture of how it was going to work.

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The two next steps were linked to the prototyping stage and dominated by practical test-driving: informal trial and error, followed by a simulation. For the informal trial and error: What we did was, we had a couple of machines here. Once again, due to how the test plan works here, it’s a little bit bureaucratic regarding how you get the machines. You should always reserve them. But I have a friend who actually works at the department and is responsible for them. So, I said to him unofficially, “If you have any machines there, anything will do, just give me a couple of dummy boxes and I’ll work with those”.

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The next prototyping step was conducting the simulation: But we tried to use the internal testing here, as much as possible, because it’s always good if you can test software, and if something doesn’t work properly you don’t want the customer to see it, of course. Because you don’t want to deliver something which has not been properly tested.

Finally, the value proposition was communicated to the customer; the service was launched, which resulted in some modifications through customer feedback. This final step, therefore, is a form of discursive value proposition test-driving in collaboration with the customer, hence taking place in the joint sphere of value creation. Discussion: the service innovation process Using a service eco-system and dynamic view, service innovation is seen as a collaborative process that involves a diverse network of actors in creating new value propositions grounded in innovative ways of integrating resources (Lusch and Nambisan, 2015). This resource integration encourages actors to integrate multiple resources for the benefit of either others or themselves (Vargo, 2008). In the present study, the frontline employees are focal actors; however, our empirical data shows that they integrate resources with other actors in ways that can be described as collaborative processes. Thus, the resources integrated by the employees come from different actors in the eco-system, which is in line with Toivonen and Tuominen (2009). In the findings section, we shed light on how operant and operand resources were integrated, at the micro level of a service eco-system, into value propositions by frontline employees using three types of value proposition test-driving: i.e. cognitive, practical, and discursive. This answered our first research question: RQ1. How do frontline employees test-drive value propositions? And contributed to our knowledge of actors as resource integrators (e.g. Kleinaltenkamp et al., 2012) and to our knowledge of the role of frontline employees as resource integrators during service innovation (e.g. Hibbert et al., 2012; Sundbo, 2008). From the perspective of an eco-system view of service innovation, the three types of value proposition test-driving identified can be seen as different innovation practices, e.g. rules, procedures, and/or methods of meaning making and acting, which have an affinity with the practices suggested by Lusch and Vargo (2014). Cognitive value proposition test-driving has similarities to normalizing practices in its intention to harmoniously coordinate actors. According to our empirical data, this harmonious coordination of actors often occurs via mental processes with the aim of making improvements to value propositions.

Discursive value proposition test-driving can be linked to representational practices since both include the use of language, signs, and symbols to make sense of and to facilitate the interactions between actors (Lusch and Vargo, 2014). Practical value proposition test-driving can be linked to integrative practices (Lusch and Vargo, 2014) in its focus on what actors actually do in everyday life situations, e.g. hands-on activities; in our case, for instance, the simulation of new value propositions. Our second research question:

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RQ2. How does value proposition test-driving, by frontline employees, lead to service innovation? It was also answered in the previous section by means of illustrating the modes of service innovation. The modes are called cognitive-dominant service innovation, practical-dominant service innovation, and discursive-dominant service innovation and consist of different ways of test-driving value propositions, with one particular test-driving practice being salient in each mode. Applying the view of Vargo et al. (2014) of service innovation as the collaborative recombination of these practices, we argue that value proposition test-driving results in novel solutions to new or existing problems. Answering the research questions enables us to make a conceptualization of service innovation and the frontline employees’ contributions to service innovation. We do this by outlining an SDL-informed service innovation model. The model (Figure 1) links our findings regarding the three types of value proposition test-driving (the separate gearwheels), and the three modes of service innovation (the groups of gearwheels), to the service innovation process (the circular arrows with stages) and to the emerging value proposition (the circles in the outer edge). Our pathway analysis suggests that all stages of the service innovation process combine all three types of value proposition test-driving through service innovation modes. The analysis also shows that each of the modes is predominant in shaping a particular part of the innovation process in a way that complies with the stages of the service development process suggested by previous research (e.g. Johnson et al., 2000; Edvardsson et al., 1995; Scheuing and Johnson, 1989). To fully capture the essence of the SDL, our proposed service innovation model implies, however, a circular understanding of the service innovation process (rather than a linear one), and instead of focusing on fixed stages, we describe a dynamic process in which the mode of service innovation switches during the process (see double arrows between modes). The service innovation model includes the switches between service innovation modes and their correspondence with different stages of the service innovation process. Thus, cognitive-dominant innovation (C) is associated with the idea generation phase, discursive-dominant innovation (D) is emphasized during design, practical-dominant innovation (P) is associated with the development phase, and discursive-dominant innovation (D) again emerges during the market launch phase. These switches in mode occur when frontline employees change their way of test-driving value propositions, which is a function of where they are in the service innovation process and what sort of resource integrations are necessary. As illustrated, the SDL-informed service innovation model is practice-based and has implications for the micro level of a service eco-system. Note, however, that the macro system filters its way down and influences the innovation of the value proposition at the meso and micro system levels, and vice versa, as argued by Lusch and Vargo (2014) and Vargo et al. (2014). An example of this can be seen in terms of the meso level (e.g. organizational rules or schemas, shared by the colleague) influencing the micro level (e.g. the service encounter). Another example relates to employees’ knowledge of

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Figure 1. SDL-informed service innovation model

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their customers, knowledge usually gained over time and through intensive contact with these customers. This knowledge is spread by the frontline employees and they can thus be seen as a link between the levels of a service eco-system, perhaps most visibly as a link between the micro and meso levels. With regard to Grönroos and Voima (2013), the frontline employees in the study could also be described as a link between the customer and the provider sphere. The knowledge gained about customer preferences when co-creating in the customer sphere is an important operant resource for creating value propositions in the provider sphere. Skålén et al. (2015), Payne et al. (2008), and Michel et al. (2008) call for increased knowledge of how value propositions are created, developed, and changed. Our service innovation model (Figure 1) illustrates how a value proposition (circles at the outer edge of the Figure) is composed of integrated resources (R), first emerging from an idea into a value proposition ready to be designed and developed and then further emerging into a complete value proposition ready for market launch. The concept of value proposition test-driving helps to clarify how the different methods that frontline employees use to

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integrate resources can form the value proposition during the service innovation process. In comparison with existing process models, our model highlights the integration of resources into value propositions by means of employees test-driving value propositions. Inspired by the concept of service test-driving, as put forward by Edvardsson et al. (2010), value proposition test-driving could be described as a “tool” that gives employees a presale/prelaunch hands-on understanding of a value proposition under development. In summary, the proposed SDL-informed service innovation model portrays service innovation as a dynamic process, focusing on how frontline employees test-drive value propositions in practices. The concept of value proposition test-driving also captures the sequence of stages (switching modes during the process), the iterations within each stage (interacting types of value proposition test-driving within every mode), and the iterations between stages (ever-present and interacting types of value proposition testdriving within modes during the process). Our service innovation model thus contributes to both SDL and service innovation research. Contributions and conclusions Research contributions and future research Few empirical studies and conceptual developments have noted the role of frontline employees, their practices, and their experiences in service innovation (Melton and Hartline, 2010; Ordanini and Parasuraman, 2010). Drawing on the SDL, we instead address the extent to which frontline employees contribute, the importance of their contributions, and what they contribute by test-driving value propositions in practices. Furthermore, prior studies do not focus explicitly on how frontline employees might contribute to service innovation. To address this question, we focus on value proposition test-driving by frontline employees. The mere introduction of this notion represents a contribution to service and service innovation research. Our case study data specifically reveals three types of value proposition test-driving for service innovation by frontline employees: i.e. cognitive, practical, and discursive test-driving, and we illustrate their link with representational, normalizing, and integrative practices as put forward by Lusch and Vargo (2014). We thus show how these practices can be contextualized and used when analyzing frontline employees’ contributions to service innovation. Our findings contradict Melton and Hartline’s (2010) conclusion that frontline employees contribute to service innovation only during the implementation phase. We concur with Ordanini and Parasuraman (2010) and Karlsson and Skålén (2015) that frontline employees play a key role in service innovation processes. More extensive qualitative research should determine the importance of frontline employees, relative to other actors in service eco-systems during service innovation, and should also identify the contexts and stages of the process during which these employees play more, or less, important roles. Furthermore, by using a survey, for example, researchers might consider different categories of employees, e.g. salespeople, technicians, field service staff, or complaint handlers, to discern how and why these contribute during service innovation processes. Another interesting topic would be to determine whether frontline employees are more or less important in the development of different categories of innovations, e.g. radical vs incremental, or business model vs service process innovations. Finally, we suggest a comparative study of companies in the same industry, in which one group is more innovative and the other is less so, in order to determine the impact of the contributions of frontline employees. In addition to clarifying how frontline employees are involved in service innovation, we propose a new conceptualization of the service innovation process (Figure 1). Our model

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links process models of service innovation with the SDL (e.g. resource integration, value propositions, service eco-systems). This suggests not only that service innovation processes reflect constant iterations across cognitive, practical, and discursive test-driving in order to integrate resources into value propositions, but also that different phases of the service innovation process are dominated by different modes of value proposition test-driving and influenced by the different levels within the service eco-system. Our model thus transcends the debate about stage vs state models, or goods vs the service-dominant logic. Ongoing research should seek out additional types of value proposition test-driving, and the different ways of involving other stakeholders than frontline employees in value proposition test-driving during the service innovation process. One insight that has emerged as an outcome of this study is that employees visualize, test-drive, and assess ideas, plans, and various development suggestions more or less regularly as part of their day-to-day work. Some of these development efforts result in service innovations based on ideas created, developed, nurtured, and tested in close collaboration with customers and partners, and together with internal actors engaged in the service eco-system. Test-driving is carried out within their own network and business contexts, as well as in various customer business practices, which is a driver of service innovation (see de Vries, 2006 for a similar view). The integration of customers’ needs, requirements, resources, and value-creating processes into a company’s service business development practices and routines has emerged as a major foundation for, and a driver of, service innovation. We thus challenge the traditional view which suggests that we should not use employees as informants in order to capture customers’ views and ideas, but that we should instead involve customers directly in various ways. However, when collecting information from and about customers or users, the translation challenges must be taken care of; i.e. how to interpret, use, and act upon the information from the customers in a business practice. Applying the ideas and suggestions of customers to a company’s resource integration and business practices is not easy. The value proposition test-driving carried out by employees seems to be a successful way of dealing with this translation challenge, and of fostering service innovation, reducing risk, integrating a new service into an existing service context (Tax and Stuart, 1997). We add to the findings of Ordanini and Parasuraman (2010), i.e. that employees contribute to resource integration and service innovation by describing how this can be done in practice. This insight has implications for the design of future research in the field of service innovation. Finally, our study contributes to SDL research (Vargo and Lusch, 2004, 2008) by revealing how new value propositions drive innovation at the micro level of a service eco-system. Resource integration occurs through cognitive, practical, and discursive value proposition test-driving. Managerial implications As exemplified by our findings, this explorative empirical study shows that frontline employees, whose main task is not innovation, can play an important role throughout the innovation process if they are both invited and involved. These employees should be engaged in innovation activities throughout the service innovation process. It is important that employees are encouraged, recognized, and given time to develop their own innovation capabilities and contributions towards the creation of an invention culture at the company. This will most likely motivate the employees and thus affect their resource integration efforts and skills in a manner that fosters service innovation. This study suggests that managers have not realized the value of this potential

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resource, accruing not only from employees working with the customer but also from other external partners, e.g. business partners, suppliers, or colleagues at other companies, or researchers at universities. This study reveals what frontline employees can contribute and implies how they might be engaged in contributing. Value proposition test-driving, as presented here, offers a fruitful context in which managers can involve employees, and use their creativity and expertise. Managers can and should promote the three types of value proposition test-driving in proactive ways in order to foster innovation. Encouraging employees to visualize their innovative ideas by drawing pictures and/or talking with customers and colleagues, for example, might trigger their linguistic abilities, leading to improved or new value propositions (discursive value proposition test-driving). Employees’ innovation capabilities can also be engaged in developing smarter ways of co-creating existing value propositions or reconfiguring existing service eco-systems and their constellations of actors, resources, and technology. This can be done by practical value proposition test-driving, e.g. trial and error. Since interacting with customers triggers mental processes (cognitive value proposition test-driving), employees can also engage their customers and use their knowledge and skills in ways that may benefit both parties during service innovation efforts and projects. As we have emphasized throughout this paper, value proposition test-driving takes place in practices and in specific contexts of use. From a managerial point of view, context refers to the company’s business and must often involve customers, making it necessary to carry out value proposition test-driving in business practices that reflect value-in-context for pertinent beneficiaries.

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Appendix

Company

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MTC (multinational telecom company)

Value proposition test-driving Informants

Four project managers with close customer contacts: Project manager 1: male, aged 39 Project manager 2: male, aged 43 Project manager 3: male, aged 55 Project manager 4: male, aged 37 Departmental manager with close customer contacts: Male, aged 52 Six consultants working in the field with their customers: Consultant 1: male, aged 36 Consultant 2: woman, aged 32 Consultant 3: male, aged 31 Consultant 4: male, aged 28 Consultant 5: male, aged 29 Consultant 6: male, aged 47 Two programmers responsible for programming, but with previously extensive customer contacts: Programmer 1: male, aged 32 Programmer 2: male, aged 33 POC (publicly owned Head of POC. Marketing and sales. Frequent contacts with customers: Male, aged 45 company in the broadband business) Responsible for network. Answering technical questions from customers: Male, aged 54 Production worker in the field, laying fibre cables: Male, aged 51 Customer services operative, via phone and e-mail: Female, aged 41 Project leader. Development of routing techniques, also meets customers and explains how they install fibre networks in their homes: Male, aged 36 Salesman working in the field: Male, aged 60 MIC (multinational IT Operational development manager: service company) Male, aged 59 Project leader: Male, aged 56 Tester. Programmer working with testing: Female, aged 44 Computer engineers, working with maintenance: Computer engineer 1: female, aged 32 Computer engineer 2: male, aged 38 System developer: Male, aged 51

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Table AI. Informants

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Table AII. Interview guide

Background

Describe the company you work at Operations at XX? Which business? Describe your role at the company In what business? What is your job? Employed since? Describe X’s work with innovation/development Service innovation, Tell me about the Y project etc. What was it about? What was developed? Length of the project? (start/end) Who was involved in the project? How did they contribute? What was your role in the project/development? When did you get involved? Your contribution? How did the idea come up? What was new? Describe how you worked during the process The route from idea to launch Give some examples […] Describe collaboration with the customer(s) during the process Describe your customer contact What did the customer contribute? How? When? What information did you need from the customers to be able to realize the idea? How did you get that information? What did the other employees/project members contribute? How? When?

Corresponding author Maria Åkesson can be contacted at: [email protected]

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