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Driven by advances in information and communication technology, end users nowadays operate extensive information systems to support all kinds of private and professional activities. Previous IS research has coined various terms to refer to this rather new phenomenon. Some scholars call it individualization in IS; others refer to it as consumerization of IT. While scholars still struggle to agree on a common conceptualization and terminology, it is clear that particular aspects of this new phenomenon have already been addressed by previous work on technology acceptance, satisfaction, or technology diffusion. However, these previous findings do not form a distinct and integrated body of knowledge because no one has yet associated them with the phenomenon of individualization. To address this gap, we suggest an integrated, yet generic, conceptualization of individualization in form of a metatheory. Based on the key entities and relations of the meta-theory, we conduct a structured literature review to identify pre-existing IS contributions to the individualization phenomenon, which help explain the phenomenon of individualization in IS. Furthermore, we analyze the identified literature for gaps in understanding the phenomenon and outline future research opportunities.

Abstract. Several papers have addressed the theory foundation of DSR. While researchers usually emphasize that the existence of such a knowledge base (KB) is essential for high quality design science research (DSR), opinions depart what kind of knowledge comprises such a knowledge base and which qualitative requirements apply regarding the knowledge leveraged. Some researchers demand that DSR is based on descriptive formal theories, while other scholars extend the width of the knowledge base also to unverified empirical evidence, conceptual knowledge and prescriptive knowledge. In order to provide some guidance for practical DSR, we apply literature review methodology on recent DSR articles to determine the common practice regarding the use and development of knowledge bases in previous projects. Based on this investigation, we discuss current issues, derive implications for future research and suggest measures to strengthen the role of the knowledge base in DSR.

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