What type of research design which is commonly used to measure the impact of a particular change?

What are the main types of qualitative approaches to research?

While there are many different investigations that can be done, a study with a qualitative approach generally can be described with the characteristics of one of the following three types:

Historical research describes past events, problems, issues and facts. Data are gathered from written or oral descriptions of past events, artifacts, etc. It describes “what was” in an attempt to recreate the past. It is different from a report in that it involves interpretation of events and its influence on the present. It answers the question: “What was the situation?”

Examples of Historical Research:

A study of the factors leading to the historical development and growth of cooperative learning
A study of the effects of the historical decisions of the United States Supreme Court on American prisons
A study of the evolution of print journalism in the United States through a study of collections of newspapers
A study of the historical trends in public laws by looking recorded at a local courthouse

Ethnographic research develops in-depth analytical descriptions of current systems, processes, and phenomena and/or understandings of the shared beliefs and practices of a particular group or culture. This type of design collects extensive narrative data (non-numerical data) based on many variables over an extended period of time in a natural setting within a specific context. The background, development, current conditions, and environmental interaction of one or more individuals, groups, communities, businesses or institutions is observed, recorded, and analyzed for patterns in relation to internal and external influences. It is a complete description of present phenomena.

One specific form of ethnographic research is called a case study. It is a detailed examination of a single group, individual, situation, or site.

A meta-analysis is another specific form. It is a statistical method which accumulates experimental and correlational results across independent studies. It is an analysis of analyses.

Examples of Ethnographic Research:

A case study of parental involvement at a specific magnet school
A multi-case study of children of drug addicts who excel despite early childhoods in poor environments
The study of the nature of problems teachers encounter when they begin to use a constructivist approach to instruction after having taught using a very traditional approach for ten years
A psychological case study with extensive notes based on observations of and interviews with immigrant workers
A study of primate behavior in the wild measuring the amount of time an animal engaged in a specific behavior

Narrative research focuses on studying a single person and gathering data through the collection of stories that are used to construct a narrative about the individual’s experience and the meanings he/she attributes to them.

Examples of Narrative Research:

A study of the experiences of an autistic student who has moved from a self-contained program to an inclusion setting
A study of the experiences of a high school track star who has been moved on to a championship-winning university track team

By the end of this chapter, students must be able to:

Explain the three types of research design used by marketers
Understand the application of these designs

This chapter looks at the types of research designs that are utilized by marketers. A research design is an overall plan or structure for a research project. A research design will use different combinations of primary, secondary, qualitative, and quantitative data. Depending on the overall research questions, research designs in marketing may fall into one of the following three categories:

Exploratory research design
Descriptive research design
Causal research design (experiments)

An exploratory research design is more informal and unstructured than the other two types of designs. Exploratory design is used to explore a situation, especially when the researcher is in unfamiliar territory. Most academic projects begin with exploratory research when researchers undertake desk research. Similarly, when marketers plan to venture into new markets, such as India, it is advisable to employ an exploratory research design. This could mean going through case studies, accessing published reports (i.e., secondary data) on the market, undertaking experience interviews with experts, and conducting focus groups – if needed. Exploratory design is useful in gaining background information and deciding about future research approaches. It may generate more questions, which need to be tackled with other research designs.

As the name suggests, descriptive research design is employed to describe the market or respondents’ characteristics. This type of research design generates quantitative information. Therefore, such a design would often involve surveys. Surveys are useful to measure the descriptive numbers relating to respondents’ age groups, income levels, expenditure patterns, and even attitudes. This can be done by employing relevant scales, such as, “On a scale of 1–5, how satisfied were you with this organisation’s service?”.

Physiological measurements, such as people’s involuntary responses (such as heart rate, skin changes, and eye movement) to marketing stimuli, such as an advertisement may also be categorised in descriptive research. While recording such information requires special instruments, it is nevertheless a type of descriptive information that can be useful for marketers.

A descriptive research design could be either a cross-sectional study that is undertaken at one point in time (such as in March 2022) or a longitudinal study that is implemented with the same respondents – repeatedly – over a given time period. Thus, a longitudinal survey may be undertaken with WSU students in April, May, and June to track student satisfaction with a subject over a semester.

Source: Meanthat and authentic data science

Causal research design (also known as experimental research design) examines cause-and-effect relationships. A well-designed experiment is the best way of understanding how one variable (e.g., advertisement) may influence another variable (e.g., sale of a product). An experiment involves one or more independent variables (for example, price level, and product features) which are manipulated to determine how they may impact one or more dependent variables (such as customer preference or customer satisfaction). Independent variables can be ‘manipulated’ by the researcher while the dependent variables are variables that get influenced due to changes in the independent variables.

Experiments can be categorised as field experiments or lab experiments. When an experiment is conducted in a natural setting – such as in a retail store – it is referred to as a field experiment. On the other hand, experiments conducted in a researcher’s office or a university classroom are lab experiments. A lab experiment may be undertaken to measure the impact of an ad on the subject’s attitude.

A field experiment is often seen as providing researchers with reliable results as it is undertaken in the actual environment. However, it is not easy to implement a field experiment. It is difficult to control other factors – in the real environment – which may also impact the final results. Moreover, running an experiment requires expertise in the design of the experiment. It may also require financial and time resources. As an example, Mcdonald’s may wish to see if a drop in the price of its cheeseburger results in greater sales. The fast-food restaurant may drop the price in one locality, such as Fairfield. It may also tediously measure the sales around the time of a price reduction. While interpreting the results, it would need to be assured that any changes in sales figures can be attributed to the price change – and not to other environmental factors such as an increase in prices at Hungry Jacks or an overall increase in customers due to a local football match. Thus, controlling such extraneous variables – that is, all those variables besides the identified independent variables which may also affect the dependent variable.

One of the popular experimental research designs is the ‘Before-After’ Testing design. As the name suggests, it measures the dependent variable, before and after a change in the independent variable. An example will help clarify the concept:

Experimental Group (R) O1 X O2

Control Group O3 O4

Experimental Effect (E) = (O2 – O1 ) – (O4 – O3)

R = random allocation of subjects to experimental or control group

O = observation

X = treatment or manipulation of the independent variable, such as a change in price

Explanation of the above example:

Subjects or research participants are randomly allocated to one of the groups
The experimental group is the one in which the independent variable (e.g., price) is manipulated (e.g., reduced)
The control group is not exposed to any changes in the independent variable
Measurements (i.e., O) for the dependent variable (e.g., sales) – for both groups – are taken before the change in price (X) – PRE-TEST
Measurements (i..e., O) for the dependent variable are taken after the change in price – POST-TEST
The difference between O2 and O1 demonstrates the change in the dependent variable due to the change in X (independent variable)
The difference between O4 and O3 demonstrate any change in the dependent variable due to factors other than X
Therefore, the difference between the two groups (O2 – O1 ) – (O4 – O3) demonstrates the true effect of the independent variable as it removes any influence of extraneous variables.