Companies are more frequently seen shifting their focus from technological innovation towards business model innovation. One efficient option for business model innovation is to learn from existing solutions, i.e., business model patterns. However, the various understandings of the business model pattern concept are often confusing and contradictory, with the available collections incomplete, overlapping, and inconsistently structured. Therefore, the rich body of literature on business model patterns has not yet reached its full potential for both practical application as well as theoretic advancement. To help remedy this, we conduct an exhaustive review, filter for duplicates, and structure the patterns along several dimensions by applying a rigorous taxonomy-building approach. The resulting business model pattern database allows for navigation to the relevant set of patterns for a specific impact on a company's business model. It can be used for systematic business model innovation, which we illustrate via a simplified case study.

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Large manufacturing companies will in future be continuously challenged to develop and implement new IoT-related business models. Existing research offers interesting insights on high-level stages of business model innovation (BMI) processes in general. However, only little is known about the presence of main gates in BMI processes and even less about the underlying decision criteria applied at these gates. To shed more light on this research field, 27 expert interviews with employees from eight companies across the IoT ecosystem were conducted. The expert interviews reveal that, despite the increasing popularity of (radically) new innovation approaches, two main decision points can be identified across BMI processes. These findings are a first explorative step towards a better understanding of IoT adoption and provide a starting point for interesting future research avenues.

Large manufacturing companies will in future be continuously challenged to develop and implement new IoT-related business models. Existing research offers interesting insights on high-level stages of business model innovation (BMI) processes in general. However, only little is known about the presence of main gates in BMI processes and even less about the underlying decision criteria applied at these gates. To shed more light on this research field, 27 expert interviews with employees from eight companies across the IoT ecosystem were conducted. The expert interviews reveal that, despite the increasing popularity of (radically) new innovation approaches, two main decision points can be identified across BMI processes. These findings are a first explorative step towards a better understanding of IoT adoption and provide a starting point for interesting future research avenues.

No abstract