So, we have a well-designed and carefully tested Web survey ready to go. How do we actually implement the survey to collect the data in which we are so interested? This chapter deals with a variety of design issues related to the process of data collection. I do not address technical issues such as Web hosting, database management, CGI (Common Gateway Interface) scripts to execute the survey, and so on. Rather, I focus on issues of design such as the invitation to participate, the use of incentives or other inducements to do so, the login and authentication process, the follow-up of nonrespondents and partial respondents, and so on. The focus in many of the preceding chapters was on reducing measurement error. In this chapter, the attention is more on reducing nonresponse or increasing the number of sample persons who start – and finish – the survey. No matter how well the instrument is designed, if it is poorly executed, the desired respondents may not even get to the questions that were so carefully developed.

This chapter is organized around the sequence of events that typically occur in a Web survey, from the initial invitation to the completion of the survey and then any follow-up that may be necessary. Following this, I discuss the use of incentives in Web surveys.

Let us assume that you have an idea that has led you to identify a topic that you believe to be of sufficient importance and of feasible execution to conduct research on it. It may be a doctoral dissertation, or just a seminar exercise, but regardless of length and complexity no topic can ‘research itself’. You will have to translate it – via a series of strategic choices – into a project. It is this process of translation from something problematic or puzzling into something on which you can gather valid data and about which you can make compelling inferences that constitutes your research design.

Granted, much social scientific research is not self-consciously designed – it is not subject to a deliberate and critical process of choosing its components and defending its overall configuration. In many areas of inquiry, the design is literally given along with the topic. So much research has already been conducted on it that adding yet another case or extending it to yet another time period does not seem to require a novel effort of translation. Indeed, the universal desire of all sciences to produce cumulative knowledge seems to militate against continuously challenging and changing the standard way of doing research. If you do propose a change in design – say, a reconceptualization of the topic, a revised instrument for measuring variation, a different way of selecting relevant cases, or a novel method of testing for association – you will risk confusing your reader-cum-critic.

Most political and social science research, whether explicitly or implicitly, is comparative research. That is, most research is concerned with findings which are directly compared across countries or cases, or which can be tested against theories and inferences derived from such a comparison of countries and cases. Comparison also involves explanation, in that one of the principal reasons that we invoke comparisons is to explain how ostensibly different factors have led to similar outcomes, or how ostensibly similar situations have led to different outcomes. Why, for example, does turnout in national elections fall below 50 per cent in two countries as diverse as the United States and Switzerland (Franklin 2004)? And why has a far-right populist party, the Vlaams Belang, enjoyed substantial electoral success in the Flemish-speaking region of Belgium, while the equivalent party, the Front National, has failed miserably in the French-speaking region (Coffé 2005)?

The first, and in many ways most important lesson in developing and understanding these comparisons is to know whether like is being compared to like. Are the objects being compared – national electoral contests, far-right populist parties – similar to one another? Are they the same thing, or perhaps even functional equivalents? Or are they so different that any comparison between them is likely to prove meaningless? In England, when like cannot be compared to like, and hence when the objects involved are strikingly different, people tend to speak of chalk and cheese.

Introduction

This chapter presents a set of approaches to systematic explanation of specific empirical political and social phenomena. These approaches strive to create theoretical, generalizable knowledge with respect to the phenomena in question. In the search for terms of generalization, they differ from research that seeks an in-depth understanding and an ideographic description of the unique and singular aspects of a given empirical political or social phenomenon (see Bray, ch. 15). Rather, they concentrate on theory development and the use of empirical cases or observations as illustrations or as a way of testing hypotheses and theories (Von Wright 1971: 19). This type of social science strives to provide answers to ‘why’ questions by seeking to identify one or several antecedent factors (explanans) that are responsible for the occurrence of the event or behaviour in question (explanandum) (Nachmias and Frankfort-Nachmias 1976). As Gerring (2005: 170) puts it: ‘to be causal, the cause in question must generate, create, or produce the supposed effect’.

The procedures of explanation discussed here are all based on the ontological (unproven) assumptions that there are recognizable regularities and a recognizable order in the world ‘out there’. No causal argument can be made without making a number of assumptions about how the world works – ‘that there is a degree of order and structure and that change itself is patterned and can be understood’ (Nachmias and Frankfort-Nachmias 1976: 6–7).

This book is an introduction to approaches and methodologies in the social sciences. ‘Approaches’ is a general term, wider than theory or methodology. It includes epistemology or questions about the theory of knowledge; the purposes of research, whether understanding, explanation or normative evaluation; and the ‘meta-theories’ within which particular theories are located. It takes in basic assumptions about human behaviour; whether the unit of analysis is the individual or the social group; and the role of ideas and interests. The first part of the book outlines some of these approaches, their development and the key issues they address. It is, in the spirit of the project as a whole, pluralistic, and readers should not expect the chapters to build into a single picture. Rather, they present different research traditions and orientations, some of which overlap while others are more starkly opposed.

The second part moves into questions of methodology, of how we turn a research problem into a workable design and of the basic choices to be made about methods. It does not go into detail on methods themselves; for this, students must turn to the numerous manuals available. The chapters should, however, help them to read and understand research based on different methodologies as well as help to guide their own choices. Readers will not find a road map leading step-by-step to their final goal.

Historical institutionalism is neither a particular theory nor a specific method. It is best understood as an approach to studying politics and social change. This approach is distinguished from other social science approaches by its attention to real-world empirical questions, its historical orientation and its attention to the ways in which institutions structure and shape behaviour and outcomes. Although the term ‘historical institutionalism’ was not coined until the early 1990s, the approach is far from new. Many of the most interesting and important studies of politics – from Karl Polanyi's classic Great Transformations, to Theda Skocpol's States and Social Revolutions and Philippe Schmitter's Still a Century of Corporatism? – would clearly be categorized as historical institutionalist were they written today.

The best way to explain historical institutionalism (HI) is to situate this approach in a historical and comparative context, showing where the approach originated and how it is different from other approaches in the social sciences. In short, what follows is an HI account of historical institutionalism. The chapter concludes with a discussion of the implications of this approach for our understanding of political and social science as ‘science’.

Origins

Institutional theory is as old as the study of politics. Plato and Aristotle to Locke, Hobbes and James Madison long ago understood the importance of political institutions for structuring political behaviour.

Introduction

Game theory is a branch of so-called Bayesian rational choice theory (RCT). It has two distinct forms of application:

1. (i) explaining individuals' behaviour in social settings by their motives and reasons;

2. (ii) as an abstract model for the analysis of social structure, within the paradigm of methodological individualism (MI).

Game theory is explanatorily useful only to the extent that it models individuals' motives and reasons appropriately. Modelling, by contrast, aims not at replicating the world, but at artificially isolating features in order to study their potential or dynamics. An explanatory approach fails if it cannot explain observable real-life behaviour. An abstract model, by contrast, can be a very fruitful analytical tool exactly when it fails if it is precise enough to tell us why it fails, and how the model can be enriched, changed or modified. Insights achieved from abstract modelling do not themselves explain phenomena but can be used in the development of explanatory hypotheses or even concept-formation; but these hypotheses then have to be tested independently.

The first section of this chapter clarifies the basic concepts and assumptions of RCT: rational choice, preference, expected utility and the structure of modern utility theory. The subsequent section turns to game theory proper and remarks on its relationship to the broader concept of RCT.

Do we need a concept of culture?

The social sciences face four enduring problems in understanding and explaining behaviour. First is how to account for both continuities and change over time within societies. Second is to explain the connection between microlevel changes and the larger, macro level. Third, and related, is how to explain the connection between individual decisions and the aggregate behaviour of a society as a whole. Fourth is the relationship between the hard facts of the social world and the way in which these are interpreted by people. Several chapters of this book broach these issues. Methodological individualism focuses on the individual and seeks to account for collective behaviour as the sum of individual actions. Chwaszcza's chapter shows how this is done through game theory, but also the limitations of this form of explanation. Pizzorno takes a different approach, by locating the individual within society in a set of reciprocal understandings. Kratochwil argues that our understanding of the world is shaped by the conceptual apparatus that we use.

This chapter seeks to make the link through the concept of culture. Cultural explanations of social phenomena go directly to the collective level, they are essentially social and in many respects (but not quite all) they represent a challenge to methodological individualism. They also seek to bridge external explanation, by reference to the social world, and internalist explanations, which rely on individual interpretation and decision.

Introduction

Once students in the social sciences have identified their personal research interest, they must find the most appropriate methodology. In this chapter, we explore a methodology central to the qualitative approach in the social sciences: that of ethnography. Its value lies in the flexible process by which it takes place, giving precedence to empirical findings over theoretical formulating. It is described as a naturalistic approach whose main data-gathering and analysing techniques consist of participant observation and open-ended interviewing. Ethnography is also a form of writing that encompasses a research philosophy central to the qualitative approach. Ethnography provides a valuable contribution to the social sciences that can be taken into account by researchers with differing quantitative and qualitative inclinations.

Vignette 1

In a small Spanish town, a group of women, accompanied by a few men and children, walk in silence along the main street, lined by local onlookers. As the evening gradually darkens, the lanterns they carry light up their colourful medieval-style garb. A researcher, also dressed in ceremonial clothes, walks alongside them as they approach a large concrete expanse. Gathered in this space, the members of the group stand in a wide circle surrounding a large heap of wood and bracken. An old woman steps forward from the group and sets fire to it. Soon, a big bonfire is blazing.

Comparative analysis holds a central place in social science research. There is a well-established view in the social sciences that it should be based on variables (see Héritier, ch. 4, and Schmitter, ch. 14). Yet much research – especially in political science, but also in some branches of sociology – is case-oriented: that is, it aims at rich descriptions of a few instances of a certain phenomenon. This chapter argues that both approaches are legitimate. Variable-oriented studies mainly aim at establishing generalized relationships between variables, while case-oriented research seeks to understand complex units. Some people would argue that case-based comparisons follow a different logic of research, while others insist that the rules are essentially the same.

The chapter starts by introducing the debate on comparative analysis, distinguishing the experimental, statistical and ‘comparative’ methods. We then single out two main strategies of research, presenting their origins in the methodological reflections by Durkheim and Weber, and focusing on the assumptions that are linked to the variable-oriented and case-oriented approaches, respectively. Advantages and disadvantages of each will be discussed on the basis of illustrations from social science works on democratization, political violence and political participation, looking at examples of large-N statistical research designs and contrasting them with small-N comparisons, especially in the tradition of historical sociology. The chapter also discusses recent attempts to bridge the gap between the two approaches, in particular with qualitative comparative analysis (QCA) and recent reflections on the case-oriented strategy.

Surveying the differences in approaches

As mentioned in the Introduction, this volume is a plea against the construction of impenetrable barriers be tween approaches. We believe that social science knowledge is a collective enterprise, built using various techniques, methodologies and methods.

Social science research is made from different tasks and different moments – from the selection of a problem for analysis, through the development of proper theories and concepts, to the choice of cases and units of analysis, data collection and data analysis. Although each research project has to give serious consideration to each of these tasks, single pieces of research usually privilege some of them. Some are more oriented towards the development of new concepts; some explicitly aim at theorization; some are field-oriented, producing new data; some use sophisticated techniques for data analysis; and some are geared to normative questions.

Even very good pieces of research are usually remembered because they gave a particularly original contribution to one (or a couple) of these tasks. Some contributions are often cited because of the systematization of new concepts (for example, Charles Tilly's concept of a repertoire of collective action), others because they put forward a new theory about a macro-phenomenon (such as Barrington Moore Jr's work on the origins of democracy). Some pieces of research are considered as particularly valuable because of the collection of new databases (for example in values surveys or electoral studies), while others use existing databases but aim at developing new instruments of data analysis.