Like Chapter 7, this chapter also discusses the sequencing of case study designs. Here we particularly focus on the deductive–inductive sequencing. Using an exemplar case study, we discuss how prediction outliers (deviant cases) identified during the initial study can guide the sequencing of designs in further stages. In the context of the example, we discuss the research question, theoretical sampling, cases, levels of analysis, and the potential requirement for additional data collection. Furthermore, we discuss the issue of omitted variable bias and internal validity in the context of sequenced case study designs. We end the chapter with a discussion on how to report sequenced case studies following deductive–inductive reasoning.

We discuss the single embedded case study design in this chapter. We deliberate how this design is different from multiple and single holistic designs in terms of the levels of analysis and the nature of replication. The selection rationale and sampling are discussed next. Afterwards, we move on to the longitudinal and/or cross-sectional single embedded designs. The strengths and the weaknesses of the design in terms of internal validity, external validity, and the number of variables are discussed subsequently. This chapter also discusses the (mis)conception regarding longitudinal designs and temporal embedded units.

In this chapter, we discuss the fundamentals of case study research. First of all, we discuss the research functions underlying research questions (i.e. exploratory and explanatory). Different types of explanatory research questions catering to the research functions are discussed next. Depending on the focal variable, these questions are termed X-centered (focusing on the independent variable X), Y-centered (focusing on the dependent variable Y), and X&Y centered (focusing on X and Y). The importance of the context (Z) is discussed afterwards. The logical reasonings underpinning case study research (i.e. induction, deduction, and abduction) are also discussed. The chapter also addresses some common (mis)conceptions regarding the research functions, research questions, research context, and logical reasoning.

In this chapter, we move on from the archetypical to the sequenced case study designs. First of all, we discuss what sequencing case study designs entail. Using an illustrative example, we discuss one type of sequencing in detail (i.e. the inductive-deductive sequencing). In the context of the example, we discuss the research question, theoretical sampling, controls, cases, embedded units, and the levels of analysis involved in the sequenced design. Lastly, we briefly discuss how to report the sequenced case study design.

We introduce and define the single holistic case study design in this chapter. The strengths of the design are discussed in detail, with examples. In particular, we discuss the potential of single holistic design in providing a detailed explanation of processes. Single holistic case studies also explore the theorizing potential of unique cases which hold the potential to reveal new dimensions of a phenomenon or falsify/refute an existing theory. Relatively high data access, construct validity, potential to include an unlimited number of variables, etc., are some other strengths that we discuss. The weaknesses of the design (i.e. low internal and external validity) are discussed afterwards. The chapter also addresses some common (mis)conceptions regarding single holistic designs and their external validity.

Here we discuss the multiple embedded case study design and the levels and cases involved in it. The design’s capacity to undertake between- and within-case comparative analyses are deliberated upon afterwards. Multiple embedded designs offer a variety of design possibilities, which we discuss in this chapter. The potential of the design for high internal validity is considered afterwards. Lastly, the design’s weaknesses, including the lack of contextual depth, the smaller number of explanatory variables, and the access difficulties to the cases/embedded units, are detailed.

The final chapter in this book discusses some methodological considerations and debates surrounding case study research and its quality. In particular, we revisit the topic of research paradigms (i.e. positivism and interpretivism). Relatedly, we discuss different quality criteria as proposed by prior researchers from both paradigmatic camps. In particular, we focus on the rigor versus trustworthiness discussion and the internal versus external validity debate. Afterwards, we briefly discuss the iterative cycles of data collection and analysis one would encounter during a qualitative case study research process. We end the chapter (and subsequently the book) with a guiding framework which will help researchers in sequencing case study designs by acknowledging the weaknesses of individual designs and leveraging their strengths. The framework can be adopted and adapted to suit the specific research objectives of the study in hand.

This chapter introduces the readers to case study research, with the help of historical and contemporary examples. We define case study research and briefly discuss the existing case study designs. Subsequently, we explain the main purpose of this book: To take case study research to the next level by discussing the combinations of different case study designs in the same study, which we call "sequencing case study designs." Furthermore, we discuss the building blocks of case study designs, the strengths/weaknesses of archetypical designs, the conundrum surrounding the crafting/relaying of theoretical contributions, some concrete examples of designs, and the differences/similarities amongst different paradigmatic camps in case study research. We end the chapter by briefly introducing the contents of the subsequent chapters.

We discuss multiple case studies in this chapter. We start off with a discussion of theoretical sampling and replication logic. We specifically discuss literal and theoretical replication (LR and TR) in connection with multiple case studies. The strengths and limitations of LR and TR are discussed thereafter. In particular, we deliberate upon the potential of TR to enhance the internal and external validity of a case study. Henceforth, we address some common (mis)conceptions regarding replication logic, internal validity, external validity (generalizability), and reliability. We also discuss how multiple case studies might need to sacrifice the depth of observation for breadth. Other potential weaknesses, such as the smaller number of independent variables and the difficulty in controlling context, are also discussed thereafter.

Chapter 5 introduces network analysis. Social media data frequently has elements that are amenable to network analysis, including friend/follower networks and retweet networks. This chapter addresses how to collect and operationalize this data into measures appropriate for network analysis. It shows how to collect en masse the timelines of a given set of users, in addition to traversing their friend and follower networks. In addition, it demonstrates how to do so by collecting all tweets of all members of Congress in real time. Finally, it demonstrates in applied form how to identify automated accounts (bots) among the data being collected.