Artificial Intelligence as Driver for Business Model Innovation in Smart Service Systems

Neuhüttler, Jens; Kett, Holger; Frings, Sandra; Falkner, Jürgen; Ganz, Walter; Urmetzer, Florian

doi:10.1007/978-3-030-51057-2_30

Cited by 11 publications

(3 citation statements)

References 14 publications

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“…In addition to approaches to developing traditional services, there are also reference models that integrate the use of data and digital elements (cf. Frank et al, 2020;Neuhüttler et al, 2020). Typically, these models include the following six generic development activities, which are combined into phases with varying levels of differentiation.…”

Section: Service Engineeringmentioning

confidence: 99%

“…However, calls for adaptation of service engineering concepts refer not only to the new characteristics of AIbased services but also to their increasingly systemic and collaborative development. Due to the complexity of AI-based services and their impact on internal service systems, different actors with specific competences and resources need to be involved in the development (Neuhüttler, Kett, et al, 2020). On the one hand, this includes technical competences for the collection and preparation of the data basis as well as the development of algorithms and system architectures.…”

Section: Service Engineering For Internal Ai-based Servicesmentioning

confidence: 99%

See 1 more Smart Citation

Introduction to the Minitrack on Cyber Deception and Cyberpsychology for Defense

Ferguson-Walter,

Fugate,

Lafon

et al. 2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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Latest research has shown that one challenge for the development and implementation of Industrial AI-based services is uncertainty of roles and responsibilities. To address this challenge, we developed a generic role model for the systematic development of AI-based services in manufacturing. The role model describes which roles are necessary within the development process of an Industrial AI-based service. Thereby, a distinction is made whether the roles are assigned to the "core team", the "extended team" or participate in "supporting roles". Furthermore, the model shows whether the roles are involved in the "Ideation" phase, the "Requirements and design" phase, the "Test" phase or the "Implementation and roll-out" phase. Based on desktop research, semi-structured interviews and expert workshops we identified 22 roles that are relevant to the development and implementation of Industrial AI-based services.

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Section: Service Engineeringmentioning

confidence: 99%

Section: Service Engineering For Internal Ai-based Servicesmentioning

confidence: 99%

Introduction to the Minitrack on Cyber Deception and Cyberpsychology for Defense

Ferguson-Walter,

Fugate,

Lafon

et al. 2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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show abstract

“…The increasing use of data and the application of machine learning methods support everything-as-aservice (XaaS) business models and, in particular, use-or outcome-based revenue models in which products are not sold but rather their use or result of use are evaluated and billed on the basis of empirical data. The use of digital technologies, such as AI and the IoT, can increase the number of parameters considered, automate the evaluation of product performance, and thus create mutual transparency, which reduces the economic risk of these business models [32].…”

Section: Developing Business Models For Internal Smart Servicesmentioning

confidence: 99%

Digital Factory Transformation from a Servitization Perspective: Fields of Action for Developing Internal Smart Services

Neuhüttler

Feike

Kutz

et al. 2023

Sci

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In recent years, a complex set of dynamic developments driven by both the economy and the emergence of digital technologies has put pressure on manufacturing companies to adapt. The concept of servitization, i.e., the shift from a product-centric to a service-centric value creation logic, can help manufacturing companies stabilize their business in such volatile times. Existing academic literature investigates the potential and challenges of servitization and the associated development of data-based services, so-called smart services, with a view to external market performance. However, with the increasing use of digital technologies in manufacturing and the development of internal smart services based on them, we argue that the existing insights on external servitization are also of interest for internal transformation. In this paper, we identify key findings from service literature, apply them to digital factory transformation, and structure them into six fields of action along the dimensions of people, technology, and organization. As a result, recommendations for designing digital factory transformation in manufacturing companies are derived from the perspective of servitization and developing internal smart services.

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Towards a Capability Based Approach to Strengthen the Strategic Decision Making Process for Developing Smart Products and Services in SMEs

Frings

Kett

2021

Advances in the Human Side of Service Engineering

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Artificial Intelligence as Driver for Business Model Innovation in Smart Service Systems

Cited by 11 publications

References 14 publications

Introduction to the Minitrack on Cyber Deception and Cyberpsychology for Defense

Introduction to the Minitrack on Cyber Deception and Cyberpsychology for Defense

Digital Factory Transformation from a Servitization Perspective: Fields of Action for Developing Internal Smart Services

Towards a Capability Based Approach to Strengthen the Strategic Decision Making Process for Developing Smart Products and Services in SMEs

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