JUST LINKING THE DOTS? BARRIERS AND DRIVERS IN CREATING VALUE FROM APPLICATION PROGRAMMING INTERFACES

Digital product platforms have emerged due to advancements in enabling technologies such as Application Programming Interfaces (APIs), allowing for easy access to distributed functionality and data. In the context of platforms, APIs have been conceptualized as boundary resources and used to analyse platform dynamics. However, these conceptualizations are based on ex-post studies of successful use cases with a core platform and platform firm exerting control at the centre of a business ecosystem. We address the lack of studies on emergent digital platforms and ecosystems without dominant control entity, where involved stakeholders potentially show more complex behaviour. We study the German automotive industry and observe how stakeholders use—or intend to use—APIs for providing access to vehicle-generated data. While preconditions for the emergence of platforms based on this data are met, to date, no eminent or industry-wide platform exists. We use a qualitative approach and 21 expert interviews to explore why APIs can turn into barriers or drivers for platform development. Our preliminary analysis identifies vignettes of barriers and drivers and suggests that future research needs to advance our understanding of the microstructures that undergird the creation of boundary resources in more complex platform and ecosystem settings

A Systematic Mapping Study on Business Ecosystem Types

Researchers and practitioners increasingly recognize the relevance of the complex business environment in which companies develop, produce, and distribute their products and services. This environment is often referred to as business ecosystem. Various types of business ecosystems have been presented and discussed in literature, such as innovation or platform business ecosystems. We conduct a systematic mapping study analyzing 136 papers in order to characterize types of business ecosystems. We provide an overview of 12 business ecosystem types and visualize how they interrelate with each other

Towards a Privacy-Enhancing Tool Based on De- Identification Methods

Advancements in information and communication technologies (ICTs), e.g. smartphones, wearables, and smart cars, enable the collection and processing of data containing sensitive information about consumers. However, while the collection, processing, and sharing of data realizes economic potentials, it also imposes privacy requirements. Thus, we envision the development of a privacy-enhancing tool based on de-identification methods to meet privacy requirements while simultaneously enabling data processing. In this research in progress paper, we present two initial contributions towards this goal consisting of an overview of de-identification methods based on a structured literature review, and a description of the use cases to evaluate the resulting tool

Towards an Ontology-Based Information System for Smart City Ecosystems

Smart city ecosystems concepts comprising firms, public authorities, and other stakeholders demonstrate innovative characteristics and high dynamics, thus enforcing both the integration between ontology management and information systems to be adaptable in short iteration periods in modern enterprises. In this paper, we describe the challenges of integrating ontology services in information systems in the context of Smart City Ecosystems. From a design science research cycle, we derive a holistic approach to integrate the ontology management process and its use in the collaborative information systems. Additionally, we describe the reference architecture for such ontology-based information systems, which allows multiple roles to create and modify the mobility ecosystem model in an agile process

Towards a Process and Tool Support for Collaborative API Proposal Management

The number of publicly offered Web APIs has increased continuously over the last decade (Santos 2017) since successful public Web API initiatives provide a new source of profitability for organizations. Nevertheless, such initiatives are only successful, if the functionality or data offered is actually demanded by third-party developers and the API design meets developers’ expectations. However, to the best of the authors\u27 knowledge, there are currently no processes or tools enabling the direct influence of API consumers on the design of public Web APIs. Therefore, we propose a process for collaborative API proposal management using collaboration engineering. Furthermore, we develop and evaluate a prototype supporting this collaborative API proposal management process, which is designed using a design science approach and is evaluated in an action research case study. The evaluation results show, that the presented collaborative API proposal management prototype was perceived as useful and meets usability requirements

A Machine Learning Based Approach to Application Landscape Documentation

Part 2: Model DerivationInternational audienceIn the era of digitalization, IT landscapes keep growing along with complexity and dependencies. This amplifies the need to determine the current elements of an IT landscape for the management and planning of IT landscapes as well as for failure analysis. The field of enterprise architecture documentation sought for more than a decade for solutions to minimize the manual effort to build enterprise architecture models or automation. We summarize the approaches presented in the last decade in a literature survey. Moreover, we present a novel, machine-learning based approach to detect and to identify applications in an IT landscape