The chapter outlines social media and qualitative research. It describes social media for data collection and different qualitative research approaches to data collection. The chapter describes social media as a phenomenon for research and outlines different levels of social media utilization: individual, work-practice and supra-organizational levels. Vignettes for the different levels are provided and the need for qualitative research concluded.

In collaboration with the HR team of a large IT service provider, this chapter relates to a study of fifty individuals who have been identified as high performers by their employer and the search for indicators and patterns of sustainable high performance.

The research design consisted of initial interviews at a virtual day, attendance of 2.5-day off-site coaching workshops and up to 60-minute follow-up interviews. During the workshop days, 24-hour heart rate variability (HRV) measurements were collected – a well-established biomarker of well-being, strain and recovery. As HRV data are difficult to analyze without contextual information, interviews, focus-group sessions, participatory observation and debriefing interviews were combined in order to contextualize the quantitative measurements and involve the participants in the interpretation and sense-making of the findings.

The methodological goal of this chapter is to demonstrate how orchestrating, improvising and performing a mixed-method study has been essential to validate, augment and complement quantitative data. The study results depend on the ability of the researchers to skilfully and empathetically engage with the interviewees and to engage them as participants in the interpretation of their data and thus as co-producers of meaning.

Recognizing the pervasive influence of modern digital technologies, this chapter argues for the supremacy of strategy work in terms of giving shape and effect to the associated agenda for strategic, organizational and technological change. The chapter focuses on the theory and practice of action research as a Mode 2 approach to knowledge production as managers co-inquire into the practice of strategizing. The discussion speaks directly to the practice of action research in government organizations, of enhancing strategy work and its related outcomes, and the broader outcomes of co-inquiry. The chapter affirms the central role of action research in knowledge production and emphasizes how the practice of action research is itself being transformed by enabling digital technologies during the current COVID-19 pandemic. The contention throughout is that good practice informs research and good research informs practice.

This chapter advocates further advancing qualitative research methods by creating tools to investigate digital traces of digital phenomena. It specifically focuses on large-scale textual datasets and shows how interactive visualization can be used to augment qualitative researchers’ capabilities to theorize from trace data. The approach is grounded on prior work in sense-making, visual analytics and interactive visualization, and shows how tasks enabled by visualization systems can be synergistically integrated with the qualitative research process. Finally, these principles are applied with several open-source text mining and interactive visualization systems. The chapter aims to stimulate further interest and provide specific guidelines for developing and expanding the repertoire of open-source systems for qualitative research.

The exponential development of information technologies (IT) which has been described as the digital revolution has led to different IT outcomes at individual, organizational and societal levels. The chapter theorizes these different IT outcomes as digitally led emancipation and digitally led exploitation. The chapter postulates that the attainment of the outcomes depends on different power mechanisms and their associated fault lines. Power mechanisms and IT are theorized to create a framework explicating these dynamics. Power mechanisms are outlined as episodic power and digitally led emancipation (collective action, participation), episodic power and digitally led exploitation (manipulation, information asymmetries), systemic power and digitally led emancipation (empowerment, inclusion) and systemic power and digitally led exploitation (surveillance/monitoring, automation/algorithmification). The chapter concludes with a research agenda to understand these power mechanisms, which may enable digitally led emancipation and digitally led exploitation.

The digitalization of business organizations and of society in general has opened up the possibility of researching behaviours using large volumes of digital traces and electronic texts that capture behaviours and attitudes in a broad range of natural settings. How is the availability of such data changing the nature of qualitative, specifically interpretive, research and are computational approaches becoming the essence of such research? This chapter briefly examines this issue by considering the potential impacts of digital data on key themes associated with research, those of induction, deduction and meaning. It highlights some of the ‘nascent myths’ associated with the digitalization of qualitative research. The chapter concludes that while the changes in the nature of data present exciting opportunities for qualitative, interpretive researchers to engage with computational approaches in the form of mixed-methods studies, it is not believed they will become the sine qua non of qualitative information systems research in the foreseeable future.