Blockchain technology enables new ways of organizing economic activities, reduces costs and time associated with intermediaries, and strengthens the trust in an ecosystem of actors. The impact of this seminal technology is reflected by an upcoming research stream and various firms that examine the potential uses of blockchain technology. While there are promising use cases of this new technology, research and practice are still in their infancy about altering existing and creating new business models. We develop a taxonomy of blockchain business models based on 99 blockchain ventures to explore the impact of blockchain technology on business models. As a result, we identify five archetypal patterns, which enhance our understanding of how blockchain technology affects existing and creates new business models. We propose to use these results to discover further patterns fueled by blockchain technology and illustrate how firms can use blockchain technology to innovate their business models.

While traditional organizations create value within the boundaries of their firm or supply chain, digital platforms leverage and orchestrate a platform-mediated ecosystem to create and co-create value with a much wider array of partners and actors. Although the change to two-sided markets and their generalization to platform ecosystems have been adopted among various industries, both academic research and industry adoption have lagged behind in the healthcare industry. To the best of our knowledge current Information Systems research has not yet incorporated an interorganizational perspective of the digital transformation of healthcare. This neglects a wide range of emerging changes, including changing segmentation of industry market participants, changing patient segments, changing patient roles as decision makers, and their interaction in patient care. This study therefore investigates the digital transformation of the healthcare industry by analyzing 1830 healthcare organizations found on Crunchbase. We derived a generic value ecosystem of the digital healthcare industry and validated our findings with industry experts from the traditional and the start-up healthcare domains. The results indicate 8 new roles within healthcare, namely: information platforms, data collection technology, market intermediaries, services for remote and on-demand healthcare, augmented and virtual reality provider, blockchain-based PHR, cloud service provider, and intelligent data analysis for healthcare provider. Our results further illustrate how these roles transform value proposition, value capture, and value delivery in the healthcare industry. We discuss competition between new entrants and incumbents and elaborate how digital health innovations contribute to the changing role of patients.

Digital transformation is continuously changing ecosystems, which also forces established companies to re-evaluate their value proposition. However, only transformations of single ecosystems have been studied. Therefore, this work targets to examine the similarities of digital transformation in five platform ecosystems: automotive, blockchain, financial, insurance, and IIoT. For our analysis, we combine the strengths of conceptual modeling using e3 value with a cluster analysis based on text mining to identify similarities in the respective ecosystems. As a result, we identified 15 clusters. Cluster 01 is the core cluster, containing the roles of organizations from all five ecosystems. Cluster 02-05 are intertwined, as they include roles from at least two ecosystems. Clusters 06-15 are ecosystem-specific that only include roles found in one ecosystem. Scholars and practitioners can use these clusters when analyzing or building a new platform ecosystem, or transforming a traditional ecosystem towards a platform ecosystem.

Determining the influencing factors of business performance is an important topic in theory and practice. This applies especially to the entrepreneurship context, characterized by extreme uncertainty and high failure rates. Existing research, which is mainly qualitative, has identified business models (BM) as a performance determinant. This paper empirically examines the relationship between BMs and startup performance. The analysis follows an industry-and region-independent approach and is based on a dataset of 121 startups. The findings reveal that some BM patterns outperform others, but on different performance measures. More specifically, the contractor pattern enhances revenue, add-on highly influences growth, customer lock-in boosts valuation, and advertising enhances funding. On the theoretical level, this paper enriches the qualitative research with statistical evidence. On the practical level, it adds value to both entrepreneurs and investors by identifying successful patterns. The findings guide entrepreneurs in BM design and support investors when considering potential investment opportunities.

Continuously innovating business models is necessary to leverage technological progress but remains a complex challenge for firms. Dynamic capabilities explain how organisations ensure long-term success by continuously transforming. Still, how continuous business model innovation unfolds and how dynamic capabilities might support remains understudied. Therefore, we use a 27-year old longitudinal case study of CEWE. CEWE transformed from an analog B2B2C business to a digital B2C and B2B brand in the photo industry. We derive a process model on continuous business model innovation, which explains how modular business model innovation builds dynamic capabilities and how architectural business model innovation utilises them. We enrich business model innovation and dynamic capabilities research by demonstrating how both enable and build on each other. For practice, we show explicit dynamic capabilities and routines to manifest them that guide firms to successfully navigate their business model innovation journey.