Experiment -- refers to a research project constructed such that the researcher (experimenter) changes one element (an explanatory or independent variable) to observe the effect of that change on another element (the dependent variable).
An experiment measures the change in the dependent variable created by a specific, controlled change in another variable(s) which is called the independent variable(s).
This is done by controlling or holding constant the other independent variables while manipulating the independent variable(s) of interest, and measuring the change created in the dependent variable.
Thus, the researcher is an active participant in the research process instead of a passive collector of data as with the survey or observation methods of research.
Experimental Settings - are three types:
1. Laboratory Experiments - Tests done in a sterile environment in which the researcher can control almost all possible causal factors. However, while the laboratory allows the researcher to control the variables involved, the lab may not accurately represent the real marketplace. Thus, the research results my not hold up when transferred to (generalized to) the actual marketplace.
Thus, lab results are said to have good internal validity, but often lack external validity.
This suggests that lab results are more likely to be statistically correct than results from field experiments, but less likely to be generalizable to the population of interest which is always located outside of the laboratory.
2. Field Experiments - Tests conducted outside the laboratory in an actual market environment. A test market is a good example. This solves the problem of realism of the test environment, but factors other than the independent variable(s) of interest may influence the observed changes in the dependent variable of interest because the researcher cannot control all other independent variables that may affect the dependent variable.
For instance, the researcher cannot control nor even precisely measure the effects of competitive actions, the weather, the economy, societal trends, the political climate, nor other elements of the uncontrollable environment.
Thus, field experiments often lack internal validity, while having better external validity.
This suggests that the results have a better chance of being statistically wrong, but they are more likely generalizable to other similar market situations, if they are statistically correct.
3. Continuous research:
Certain types of data are gathered on a regular basis as opposed to the ad hoc survey. Moreover, researchers will use standardized methods in order that the data collected at one point in time is comparable with that collected at other times.
In this way, a picture of market trends can be built up. This type of longitudinal research is often funded on a syndicated basis. Syndicated research usually involves an independent research company collecting data and supplying it simultaneously to a number of clients.
An experiment measures the change in the dependent variable created by a specific, controlled change in another variable(s) which is called the independent variable(s).
This is done by controlling or holding constant the other independent variables while manipulating the independent variable(s) of interest, and measuring the change created in the dependent variable.
Thus, the researcher is an active participant in the research process instead of a passive collector of data as with the survey or observation methods of research.
Experimental Settings - are three types:
1. Laboratory Experiments - Tests done in a sterile environment in which the researcher can control almost all possible causal factors. However, while the laboratory allows the researcher to control the variables involved, the lab may not accurately represent the real marketplace. Thus, the research results my not hold up when transferred to (generalized to) the actual marketplace.
Thus, lab results are said to have good internal validity, but often lack external validity.
This suggests that lab results are more likely to be statistically correct than results from field experiments, but less likely to be generalizable to the population of interest which is always located outside of the laboratory.
2. Field Experiments - Tests conducted outside the laboratory in an actual market environment. A test market is a good example. This solves the problem of realism of the test environment, but factors other than the independent variable(s) of interest may influence the observed changes in the dependent variable of interest because the researcher cannot control all other independent variables that may affect the dependent variable.
For instance, the researcher cannot control nor even precisely measure the effects of competitive actions, the weather, the economy, societal trends, the political climate, nor other elements of the uncontrollable environment.
Thus, field experiments often lack internal validity, while having better external validity.
This suggests that the results have a better chance of being statistically wrong, but they are more likely generalizable to other similar market situations, if they are statistically correct.
3. Continuous research:
Certain types of data are gathered on a regular basis as opposed to the ad hoc survey. Moreover, researchers will use standardized methods in order that the data collected at one point in time is comparable with that collected at other times.
In this way, a picture of market trends can be built up. This type of longitudinal research is often funded on a syndicated basis. Syndicated research usually involves an independent research company collecting data and supplying it simultaneously to a number of clients.