Which of the following is the best example in which to apply causal research?
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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: Show
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 scienceCausal 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: What is an example of causal research?For instance, a company implements a new one-to-one marketing strategy for a small group of customers and observes a measurable increase in monthly subscriptions. After they receive identical results from multiple groups, they conclude that the one-to-one marketing strategy has the causal relationship they intended.
What is causal research used for?Causal research is classified as conclusive research since it attempts to build a cause-and-effect link between two variables. This research is mainly used to determine the cause of particular behavior.
What type of research is causal research?What is Causal Research? Causal Research is a type of conclusive research, which attempts to establish a cause-and-effect relationship between two or more variables. of a change in process and existing methods.
Which of the following is a technique used in causal research?Experiments are the most popular primary data collection methods in studies with causal research design. The presence of cause cause-and-effect relationships can be confirmed only if specific causal evidence exists.
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