investigation in a particular piece of research. Quantitative data analysis will always relate to a particular set of cases, usually referred to as the ‘sample’ even if that set is not actually a sample but the total number in a population of cases. The set will normally be defined in terms of particular characteristics that define membership and all members will have those characteristics in common. Ideally, the rationale for the selection of such characteristics, for example in terms of their relevance to the inquiry, should always be explained. The number of cases used in any particular analysis will be known and will relate either to the entire set or to some subset. In some research, membership of a research population may be a matter of degree, for example an ‘alcoholic’, a ‘workaholic’, a ‘bulimic’ or an ‘autistic’. Here, the researcher will be constrained to define a particular quantity, for example number of units of alcohol consumed per day or per week, as a cut-off point between inclusion and non-inclusion in the sample of research cases.
In some research projects there may be more than one set of cases, sometimes arranged hierarchically as sets within sets, or sets at different points of time. Sometimes, when a sample is taken, the precise number of cases in the population that the sample is meant to be a sample of is unknown or may or may not be estimated.
Properties
Each case will be a configuration of a potentially infinite set of characteristics. In practice, researchers undertaking quantitative research will focus on a limited set of properties – variously described as ‘variables’, ‘set memberships’, ‘causes’, ‘effects’, ‘conditions’ or ‘outcomes’ – that are taken as a basis for recording characteristics. Properties are the characteristics of cases that are included in the research sample or population and that the researcher has chosen to observe or measure and then record. Some of these properties will be common to all the cases, for example all the cases in a sample of individuals are female, aged between 18 and 40 and resident in the UK. These properties are sometimes called ‘constants’ and they define which cases are considered to be members or potential members of the research population. Alternatively, some properties will relate to characteristics that vary between cases, for example some nation-states in a research population of states have parliamentary democracies and others do not.
The type of characteristic to which properties may relate can be broadly classified into demographic, behavioural or cognitive. Demographic properties relate to features that researchers have chosen to characterize the nature or condition of a case like a person’s age and sex, a household’s size, an organization’s legal status or a country’s rate of net immigration. These qualities may be fixed or relatively fixed (like gender or organizational legal status), or slow to change (like age). Some may be subject to sudden changes interspersed with periods of stability, for example an individual’s social, economic or marital status, or an organization’s location of company head offices.
Behavioural properties relate to what cases did in the recent past, to what they usually or currently do, or to what they might do in the future. Typical measures for individual consumers in marketing, for example, relate to the purchase and use of products and brands like purchase/non-purchase of a product or brand over a specific time period, brand variant purchased, quantity/size of pack, price paid, source of purchase, other brands bought, nature of purchase, and use/consumption of the product. These measures may, in turn, be used to generate calculations of brand loyalty, brand switching behaviour and frequency of purchase. If the research is a product test or product concept test, consumers may be asked about future behaviour, for example the likelihood of trial of a new product and likely frequency of purchase.
Cognitive properties relate to mental processes that go on within individuals and include their attitudes, opinions, beliefs and images. These are notoriously difficult to assess. Attitude scaling, which is explained in the next section, focuses on how researchers have attempted to address this problem. There is an issue of whether or not aggregations of individuals or macro units can ‘do’, ‘think’ or ‘believe’ things; that will be something on which researchers will need to take a view and decide.
In terms of the various roles that demographic, behavioural or cognitive properties may play in research, we can distinguish properties being used as descriptors and properties being used either as potentially causal factors or as outcomes. Descriptors are properties that are studied one at a time in order to illustrate or summarize the key features of a set of cases. They are not being investigated for their potential relationship to other characteristics. Demographic properties in particular are often used to provide a framework for defining and describing the key characteristics of the cases that are providing the data in a piece of research; for example, a sample of online shoppers may be described in terms of the numbers of males and females, the age distribution and whether or not they have access to broadband. However, behavioural and cognitive properties may also be used for descriptive purposes. Where, in a piece of research, properties are being used solely in this fashion, then it may be called a ‘descriptive’ study.
Alternatively, properties may be used precisely for the purpose of investigating the nature of their relationships to other properties. In some research the purpose of the study may be to explore whether or not, or the extent to which, patterns exist; for example, that males are more likely than females to instigate divorce proceedings. Most researchers, however, are interested in examining whether some properties, variously called ‘conditions, ‘independent variables’ or ‘causes’, have some influence or impact on other properties – ‘outcomes’, ‘dependent variables’ or ‘effects’. The notion of causality is extremely complex and is considered in detail in Chapter 10.
Behavioural, cognitive and some demographic properties may be used in any of the three roles in research, as illustrated in Figure 1.1. Some demographic properties, however, are difficult to conceive as being ‘effects’, for example trying to ‘explain’ a person’s gender or age! Some properties may be used in more than one role in a piece of research. Thus some demographics may be used for both structural and analytic purposes, for example using age to describe the sample of respondents and also using it to see how far it ‘explains’ variation in one or more of the other properties. Some characteristics may be used by researchers as both cause and effect in the same piece of research. Thus customer satisfaction may be seen both as a result of a customer’s prior expectations about the product or service (it is an effect) and in turn as causing or influencing repeat purchase behaviour (it is also a cause).
Figure 1.1 Attributes and roles of properties in research
Properties are, in effect, researcher constructs: they are what the researcher has defined them to be. Either they are the deliberate creation of researchers who have decided how, where and when the assessment of properties are to take place, or researchers accept the constructions of other individuals, taking them as appropriate for their own research. In some instances the degree of ‘construction’ is limited, as in recording the gender of a respondent in a survey, although even here there may be the odd discrepancy between observed gender and self-reported gender. In other situations, recording a person’s social class may be the result of a highly complex process. Such processes may be referred to as ‘measurement’, ‘scaling’ or creating ‘operational definitions’. They are the means by which researchers create their ‘yardsticks’ for categorizing, counting or calibrating the values to be recorded. This may be achieved in one of four main ways:
directly;
indirectly;
deriving from two or more separate measures;
creating a multidimensional profile.
The values of some properties may be directly observable by the researcher, for example the number of individuals in a group. Sometimes a construct is redefined so that there is a one-to-one correspondence between the construct and what can be observed or recorded. Social class might, for example,