In many business domains, rapid changes have occurred as a consequence of digital innovation, i.e., the application of novel information technologies to achieve specific business goals. A domain where digital innovation has great potential is smart mobility, which aims at moving around large sets of people and goods in a specific geographic setting in an efficient and effective way. So far, many innovations in this domain have concentrated on relatively isolated, technology-driven developments, such as smart route planning for individual travelers. Nice as they are, they have relatively small impact on mobility on a large scale. To achieve substantial digital innovations-for example, optimizing commuting on a city-scale-it is necessary to align the efforts and related values of a spectrum of stakeholders that need to collaborate in a common business model. To this aim, the study proposes the use of service-dominant business logic, which emphasizes the interaction of value network partners as they co-create value through collaborative processes. Moving to this paradigm has significant implications on the way business is done: the business requirements for services will change faster, and the complexity of value networks required to meet these requirements will increase further. This requires new approaches to business engineering that are grounded in the premises of servicedominant logic. The paper introduces the service-dominant business model radar (SDBM/R) as an integral component of a business engineering framework. Following a design science approach, the SDBM/R has been developed in close collaboration with industry experts and evaluated through an extensive series of hands-on workshops with industry professionals from several business domains. This paper focuses on the application and evaluation in the smart mobility domain, addressing the design of new business models for digital innovation of collaborative transport of people and goods. In summary, it contributes a novel business design approach that has an academic background and relevant practical embedding.

Business services are offerings that enable organizations to achieve their strategic objectives by making their functionality accessible to their customers and business partners. Thus, organizations pay significant attention to and invest in the explicit identification and definition of their business services. This is, however, not a trivial endeavor as multiple concerns that are intrinsic to the concept of business service should be taken into consideration in identifying services. Existing business service identification methods used in isolation do not offer adequate coverage for these concerns. Addressing this issue, we propose a novel method assembled by situational method engineering from a set of existing service identification methods, taking the best aspects from each of them. In this paper, we present an instantiation of the situational method engineering approach alongside the details of the constructed method. We also provide a demonstration of the method with an illustrative scenario based on a real-life business case.

Evaluating the Design of Service-Dominant Business Models: A Qualitative Method Rick Gilsing, Eindhoven University of TechnologyFollow Oktay Turetken, Eindhoven University of TechnologyFollow Baris Ozkan, Eindhoven University of TechnologyFollow Paul Grefen, Eindhoven University of TechnologyFollow Onat Ege Adali, Eindhoven University of TechnologyFollow Anna Wilbik, Maastricht UniversityFollow Frank Berkers, TNOFollow Abstract Background: Driven by factors such as digitization and rapid technological change, many contemporary organizations adopt a service orientation to sustain competitiveness and to improve their value propositions to customers. In doing so, organizations typically engage in collaborative service ecosystems to co-create value and exchange services, and conceptualize such collaborations using business models. The resulting models should be evaluated to support the development of service ecosystems and their long- term viability. Despite academic efforts on the evaluation of traditional, organization- centric business models, limited research is present supporting the evaluation of service- dominant business models, taking into account their key characteristics, such as service exchange and value co-creation in business networks. Method: Following a design science research methodology, we have iteratively designed a method addressing the qualitative evaluation of service-dominant business models, building on and integrating the theory on service-dominant logic, business model design and business model evaluation. To structure the steps of the design process, we leverage a situational method engineering approach, following a paradigm-based strategy. To evaluate the validity and utility our method, we have applied it to a real-life business case in the mobility domain, involving eight industry stakeholders in the process. Results: The method constitutes a set of guiding questions and a procedural description of their use, addressing the evaluation concerns of feasibility, viability, structural validity and robustness with respect to the service-dominant business model. The results of the evaluation demonstrate that the use of the method facilitates users to reflect qualitatively on design decision with respect the business model design and offers insights on its expected performance. Conclusions: This work contributes to extant research on service systems engineering and the instantiation of service-dominant logic, clarifying how service ecosystems can be evaluated through the business model concept and explicating how business models are impacted through service-dominant logic.

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To sustain competitiveness in contemporary, fast-paced markets, organizations increasingly focus on innovating their business models to enhance current value propositions or to explore novel sources of value creation. However, business model innovation is a complex task, characterized by shifting characteristics in terms of uncertainty, data availability and its impact on decision making. To cope with such challenges, business model evaluation is advocated to make sense of novel business models and to support decision making. Key performance indicators (KPIs) are frequently used in business model evaluation to structure the performance assessment of these models and to evaluate their strategic implications, in turn aiding business model decision making. However, given the shifting characteristics of the innovation process, the application and effectiveness of KPIs depend significantly on how such KPIs are defined. The techniques proposed in the existing literature typically generate or use quantitatively oriented KPIs, which are not well-suited for the early phases of the business model innovation process. Therefore, following a design science research methodology, we have developed a novel method for defining business model KPIs, taking into account the characteristics of the innovation process, offering holistic support toward decision making. Building on theory on linguistic summarization, we use a set of structured templates to define qualitative KPIs that are suitable to support early-phase decision making. In addition, we show how these KPIs can be gradually quantified to support later phases of the innovation process. We have evaluated our method by applying it in two real-life business cases, interviewing 13 industry experts to assess its utility.

Given its essential role in understanding, explaining and structuring digital innovation, we see the increased prevalence of the business model concept as a unit of analysis in IS research. In contemporary, fast-paced markets, business models are volatile in nature and should be continuously innovated to accommodate new customer needs and technology developments. Business model innovation can be considered as an iterative process to guide business models from ideation towards implementation, in which the proper evaluation of business model prototypes is essential. For this evaluation, we need normative guidance, tools and rules to understand the relative performance of a new business model design. In the early design phases, this implies dealing with high levels of uncertainty. A few techniques and methods have been proposed for this purpose, but these lack the formal basis required for systematical application and development of automated evaluation tools. As a novel approach, we have earlier proposed the application of linguistic summarization to support early-phase, soft-quantitative business model evaluation. In this paper, we focus on a structural formalization of this approach as the basis for the development of well-defined user guidelines and automated evaluation tools. In doing so, we bridge the existing gap between qualitative and quantitative business model evaluation. We demonstrate the formalization by means of a running case inspired by a real-world project in the highly dynamic urban mobility domain.

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