To Drive or not to Drive - A Critical Review regarding the Acceptance of Autonomous Vehicles

With the advent of autonomous vehicles (AVs), research has put much effort in investigating the factors relevant for the acceptance of this new technology. In order to identify, critically assess, and combine extant findings, we performed a structured literature review regarding the acceptance of self-driving vehicles. Results of this review spanning 58 articles include (1) a comprehensive AV acceptance framework outlining significant factors across three areas: individual characteristics, vehicle characteristics and policy/society. We also (2) analyze the operationalization of relevant constructs and items in the identified studies as they strongly diverge in extant literature. This new level of detail helps researchers and practitioners to pervade and compare the AV acceptance research in-depth. Additionally, we contribute to the AV research stream as we (3) identify possible future research avenues, which we examine regarding content, method, and focus

Making Data Tangible for Data-driven Innovations in a Business Model Context

As digital transformation has occurred over the last decade, organizations have been compelled to seek new business models. As a consequence of this development, the impact of data on business models has become a focus of interest in research as well as in practice. Based on typical characteristics of data-driven business models (DDBMs), this paper develops 19 design principles for their visual representation. The design principles were derived from semi-structured interviews with experts in the field of DDBMs and were clustered into the Business Model Canvas (BMC). The contribution of this paper is threefold. First, the developed design principles deepen the knowledge base on DDBMs. Second, other business model representations can be assessed against these design principles and new or aligned representations can be developed. Third, the design principles can be used by practitioners to develop a DDBM

Making Data Tangible for Data-driven Innovations in a Business Model Context

As digital transformation has occurred over the last decade, organizations have been compelled to seek new business models. As a consequence of this development, the impact of data on business models has become a focus of interest in research as well as in practice. Based on typical characteristics of data-driven business models (DDBMs), this paper develops 19 design principles for their visual representation. The design principles were derived from semi-structured interviews with experts in the field of DDBMs and were clustered into the Business Model Canvas (BMC). The contribution of this paper is threefold. First, the developed design principles deepen the knowledge base on DDBMs. Second, other business model representations can be assessed against these design principles and new or aligned representations can be developed. Third, the design principles can be used by practitioners to develop a DDBM