The chapter re-examines the case study research method and its role and contribution to the IS discipline and focuses on the current status of the case study research and the increased digitalization. The advantages of qualitative interpretive cases studies are identified, recent case studies are described and analyzed, and their contributions highlighted. These examples continue to enhance the discipline and sustain the traditional benefits of the case study research through rich data, analysis and understanding the links between people, organizations and technologies, the advancement and expansion of theory, the identification of hidden aspects, and the emergence of new concepts and theorization. Two of the cases use trace data, a type of data emerging as a product of digitalization. While these cases provide contributions, they also challenge the traditional understanding of what a case study is, and the benefits that accrue. The chapter emphasizes the need for mixed-method and multi-method case studies research in addition to trace data to enhance the benefits of the case study research.

An overview of empirical findings, emerging theories, and challenges to the ego-centric perspective in the study of social media and digital technologies broadly. The relationship between social media use and network size and diversity has been discussed in relation to topics that include social capital, social support, political engagement, and mental health. We explore the role these technologies play in shaping networks, and how the ego-centric perspective can advance the study of social media. Two trends – persistent contact and pervasive awareness – are explored for their potential to counter transitory, segmented personal networks. The ego-centric perspective can play an important role in the study of social media, which has primarily focused on understanding how media works as an agent of change, while overlooking opportunities for research related to social influence and network flows. However, ego-centric researchers face methodological challenges, including the risk of overgeneralizing from social media platforms to personal networks more broadly, and the role of algorithmic personalization. We end with a discussion of how ever shifting social media platforms remain a barrier to advancing one of the most promising opportunities for the ego-centric approach: combining relational data from social media platforms with data from other sources, such as surveys.