Ronny Schüritz

Blockchain Technology as an Enabler of Service Systems: A Structured Literature Review

Blockchain technology is expected to revolutionize the way transactions are performed, thereby affecting a vast variety of potential areas of application. While expectations are high, real world impact and benefit are still unclear. To be able to assess its impact, the first structured literature review of peer-reviewed articles is conducted. As blockchain technology is centered around a peer-to-peer network, enabling collaboration between different parties, the service system is chosen as unit analysis to examine its potential contribution. We have identified a set of characteristics that enable trust and decentralization, facilitating the formation and coordination of a service system.

Towards a Unified Approach to Identify Business Model Patterns: A Case of E-Mobility Services

The introduction of new technologies creates the pursuit for innovative business models. In order to compare and evaluate such models in new markets, business model patterns can support the provision of new insights. However, so far there is no agreed upon transparent approach that helps to identify these patterns. Based on a combination of established statistical methods we propose a systematical approach that allows to identify business model patterns of any given domain. In order to validate the approach, we apply it on a data set of 58 e-mobility projects and as a result identify five distinct and semantically meaningful business models types. This paper contributes on the one hand by suggesting a new approach to identify different patterns of business models and on the other hand provides a valuable insight of the current state of e-mobility service business models that can further drive the adoption.

Capturing Value from Data: Revenue Models for Data-Driven Services

Undisputedly, the amount of data is growing exponentially and huge opportunities exist to exploit them. New service business models are being built around value propositions based on data and analytics. Suitable revenue models need to reap the benefits of these value propositions. However, the question of how to best turn a value proposition into revenue for data-driven services is not systematically addressed in literature. We provide an overview of possible revenue models for data-driven services. Based on a sample of 100 start-ups, we apply qualitative analysis to identify different revenue models for newly established data-driven services such as subscription, gain sharing and multi-sided revenue models. This paper will contribute to the fundamental understanding of how companies can capture value from data-driven services. It should give guidance on the design and selection of appropriate revenue models and, thus, inspire new forms of revenue generation from the use of data.

Towards a Process Model for Data-Driven Business Model Innovation

The growing importance of data and analytics in a broad range of industries has led to an increased attention of business model literature on this matter. The question of how to capture the business potential associated with data, drives researchers to explore the impact of data and analytics on the business model concept. However, little research has been conducted on how an organization should approach to enrich its existing business model with data or, yet, to develop a completely new, data-driven business model.Our research aims to address this issue by providing a process model for data-driven business model innovation. Therefore, we conduct an extensive review of existing business model innovation processes and derive distinct requirements, taking into account both data specific and business model innovation specific characteristics. The requirements are used to assess the suitability of the identified processes for the development of a data-driven business model. We disclose that existing processes are not appropriate for creating such business models. Based on these findings, we design a new, data-driven business model innovation process that meets the data specific requirements.

Using Employees’ Collective Intelligence for Service Innovation: Theory and Instruments

In this chapter, we reflect on the potential and instruments for involving employees in service innovation processes. Based on a discussion of value co-creation scenarios in the context of service innovation, we conjecture that frontline employees of service providers can be powerful proxies for their customers. Thus, they might be a particularly valuable group to involve in service innovation endeavors. The quality of these proxies may increase with the depth of insights frontline employees can gain from their customers. Moreover, as the literature suggests, these employees can also cater for the strategic and cultural fit of service innovations to their organizations, to avoid a reported drawback of directly involving customers in the service innovation process. Hence, we first suggest leveraging the potential of large numbers of these employees through collective intelligence instruments and derive design recommendations for such approaches. In the second part of the chapter, we then introduce and compare four types of collective intelligence instruments that are currently used by companies to involve employees. We close by suggesting avenues for further research in this domain.

Service Science Textbooks: Opportunities of an Interdisciplinary Approach

With the rise of service science, management and engineering as an independent and interdisciplinary research school, several courses and entire study programs emerged in several universities around the world. Several textbooks address teaching service science from the perspective of a specific discipline such as marketing, operations management or computer science. Therefore, so far teaching service science requires the preparation and combination of lecture material from different textbooks and other teaching material, since there was a lack of interdisciplinary and integrated textbooks for teaching service science. This paper reviews existing service textbooks for motivating the need for an integrated service science textbook. Furthermore, the outline of a new forthcoming interdisciplinary service science textbook is presented. This textbook integrates several disciplines, such as business and economics, quantitative sciences, and computer science. The textbook therefore provides an interdisciplinary map of the world of service science that conquers the challenges to explain service systems to students and practitioners. This enables lecturers to organize their courses along a comprehensive and integrated course concept which has been the result of teaching service science at universities for several years.